DOT/FAA/AM-94/21 

Office of Aviation Medicine 

Washington, D.C. 20591 

94-34433 c~ 1111111111 "'S \.\j 

-

Age 60 Study; Part II: 

Airline Pilot Age and 

Performance -A Review of 

the Scientific Literature 

DT Hyland 

E.J. Kay 

Lehigh University 

Bethlehem, Pennsylvania 

J.D. Deimler 

Hilton Systems, Inc. 

Cherry Hill, New Jersey 

E.B. Gurman 

University of Southern Mississippi 

Hattiesburg, Mississippi 

Civil Aeromedical Institute 

Federai Aviation Administration 

Oklahoma City, Oklahoma 73125 

October 1994 

Final Report 

This document is a>"ailable to the public 

through the National1echnical Information 

Service, Springfield, Virginia 2216L 

U.S. Department 

of Transportation 

Faderal Aviation 

Administration 

94 11 4 
NOTICE 

This document is disseminated under the sponsorship of 

the U.S. Department of Transportation in the interest of 

information exchange. The Cnited States Government 

assumes no liability for the contents or use thereof. 
J. lbpofl No. 2. G<M>mment Accession No 3 ~fs Cotobg No 

DOT/FAA/AM-94/21 

4.-and~ 5 Reocr. Dote 

Age 60 Rule Research, Part II: Airline Pilot Age October 1994 

and Performance--A Review of the Scientific I 

Literature I 

I 

6 Pt:wfoi!IW'O OI'\1Jl'IZC"'' CC)ijp, 

7-) ! ~· •t.;:;O:gcuzc!V ~N-0 

D. T. Hyland, Ph.D., E. J. Kay. Ph.D .. ~ ~. D. 8025-lA 

Deimler, E. B. Gurlllan, ?h.D. 

Q _ .... Oigul...-. -cncl""""'" 10 w~ '..lt"l:' ~ <;l'T<A$) 

Hilton Systems, Inc. 

950 North Kings Highway Su;ite 202 

Cherry Hi 11 • New Jersey 08034 :~ C~aGr~No 

DTFA02-9C-C-90l25 

12. __._,.~.,.,....,...,- iJ ;~dQreoot!~~c....~ 

Office of Aviation Medicine 

Federal Aviation Administration 

800 Independence Avenue. s.w. 

washington, D.C. 20591 1< Sooreor•~ Agrcy Code 

tS S.i t•*'Hic:IIM 

This document is one of four products c~leted as a part of the Age 60 Rule 

research contract monitored by Pam Della Rocco, Civil A~romedical Institute, 

Contracting Officer's Technical Representative. This work was performed 

under Task AM-A-91-HRR-138. 

16. _,.,. 

This revi- of the literature establishes the scientific foundation for 

subsequent studies on the Age 60 Rule research conducted under a contract 

with Hilton Systems, Inc. The scie11tific literature relevant to the two 

separate scientific approaches required by the contract is reviewed. The 

document first provides a review of the "Age 60 Rule, • as well as the 

theoretical and methodological considerations critical to the study of aging 

and the assessment of individual pilot performance. A proposed model is 

presented to form a frall>eWOrk for the research. Pilot behaviors affected by 

aging and/or el~PE'rience are reviewed. Specific performance assessment 

batteries are reviewed in detail in Appendix A. Issues related to measuring 

COIIIPlex pilot performance are discussed. Recommendations and criteria for 

developing a performance methodology are presented. The second part of the 

literature review provides a discussion of the issues :related to the analyses 

of existing data to assess the relationship between pilot age, experience, 

and accident rates. This section provides a critical review of existing 

analyses and presents recommendations for an iMproved analytical methodology. 

17 . .,.,._ 18. Distribution Statement 

Pilot Age and Performance Document is available to the public 

Age 60 Rule through the National Tech..""'l.ical 

Mandatory Pilot Retirement j Information Service, Springfield, 

j Virginia, 22161 

19 SlcutiY~ (cf-- 120 Sec<dv Oosslf. (01""' page) 2"!. No. OIPoges 22. Pnce 

Unclassified I Unclassified 136 

• 

1 
PREFACE 

This technical report, entitled "Age 60 Rule Research, Part II: Airllne Pilot 

Age and Performance..-A Review of the Scientific Literature,• is the second in a 

col!ection of four major documents resulting from a two year contract to 

scie!!tif1C811y examine issues related to the Federal Aviation Administration's 

(FAA's) mandatory retirement regulations for pilots. The first report, entitled • Age 

60 Rule Research, Part 1: Bibliographic Database,' was published as an Office 

of Aviation Medicine Technical Report (DOTIFAA/AM-94120). 

The Federal Aviation Regulations (FARs), Part 121, prohibit individuals 

from sefVing as captain or copilot (1st officer) of an aircraft in air carrier 

opetations if those persons have reached their 60th birthday. Commonly 

•efened to as the "Age 60 Rule", the regulation was impiemented in response to 

COIIC8n'IS about the safety of aging pilots as the airline industry transltioned into 

the jet age. Although the rule has withstood legal and legislative challenges, 

little scientific evidenc:e has been available to either support the rule or to guida 

the FAA to an appropriate alternative. 

In 1990, the FAA's Associate Administrator for Certification and 

Regulation (AVR-1), Mr. Anthony Broderick, requested and sponsored a two 

year research contract to examine the relationship between age, experience. 

and accident rates. The Civil Aeromedical Institute (CAMI} was assigned the 

task of developir.g and monitoring the contract. In September 1990, the contvact 

was awarded to Hilton Systems Inc., of Cherry Hill, New Jersey. Hilton Systems 

collaborated with Lehigl'i University faculty to supplement technical expertise. 

The FAA requested that the wntoactor engage in a fresh, innovative approach to 

issues involved in the Age 60 Rule. 

Two separate scientific approaches to the research were requested in the 

contract's Statement of Work as follows: 1) assessment of the group-based 

standard (Age 60 Rule) through investigation of the relationship between age, 

experience, and accident rates from existing data bases, and 2) examination of 

the faasibi!ity of developing an indMdually-based performance assessment 

battery. This literature review served to establish the scientific basis for both 

investigative approaches in the contract. 

Finally, for clarity of presentation, graphs presented in Appendix 8 are 

Hilton Systems' reproductions of Golaszewski's figures from his original data. 

Some computational errors were corrected in the Hilton reproductions. 

Differences in the figures provided here and Golaszewski's report are due to 

these modifications. in addition, the x-axis in several of the Hilton Systems' 

graphs were labeled differently. 

Pamela Della Rocco, COTR 

Ul 
CONTENTS 

SECTION PAGE 

1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 

2. AGING M1> THE ASSESSMENT OF INDMDUAL 

PILOT PERFOR1i.fANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 

2.1 S~ific Aims . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 

2.2 Conceptual Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 

2.2.1 Existing Models of Aging and Performance . . . . . . . . . . . . . . . 4 

2.2.2 A Proposed Model for the Assessment of Aging 

and Pilot Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 

2.3 Background literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 

2.3.1 Pilot Characteristics: The Aging Pilot . . . . . . . . . . . . . . . . . . 8 

2.3.2 Otber Pilot Cbaracteristics ......................... 17 

2.3.3 Stressors: Their mteraction with Age . . . . . . . . . . . . . . . . . . . 17 

2.3.4 Assessing Pilot Perfonnance . . . . . . . . . . . . . . . . . . . . . . . . 19 

2.4 Conclusions and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . 26 

2.4.1 Criteria for Developing and Evaluating a 

Performance Assessment Methodology . . . . . . . . . . . . . . . . . . 26 

2.4.2 Longitudinal Examination of Aging and Pilot 

Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 

3. THE INFLUENCE OF AGE, TOTAL FUGHT TIME, AND RECE._,T 

FUGHT TIME ON PILOT ACCIDENT RATES .................... 29 

3.1 Specific Aims . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 

3.2 Background Literature ................................ 29 

3 .2.1 Description of Golaszewski Study . . . . . . . . . . . . . . . . . . . . . 29 

3.2.2 Drawbacks to Golaszewski Design .................... 31 

3.2.3 Other Studies of Age and Accidents .................... 34 

3 .2.4 Replicating Golaszewski . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 

3.2.5 Beyond Golaszewski ............................. 37 

3.2.6 Relationships among Medical Variables, Age, 

and Pilot Accidents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 
CONTENTS {Cont'd) 

SECTION PAGE 

3.2.7 Improved Ways to Examine Relationships among 

Medical Variables, Age. and Pilot Performance . . . . . . . . . . . . 39 

3.3 Conclusions and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . 39 

REFERENCES ............................................. 41 

APPENDICES 

A. Test Batteries Used for Pilot Selection or Evaluation 

B. Figures Plotting Age, Flight Time, and Accidents from 

GoJaszewsk:i (1983) 

C. Topical Bibliography of Aging, Medical Variables, and 

Pilot Ple..formance 

! NTIS CRA&l 

: DT!C TAB 

l U: .announced 0 

' J:;st;ficatic:m .. 

\ By···--···-···------! 

: Diet ib.:tiOCI I 

\ Dist 

Avaiiabiiity Codes 

Avail and i or 

Special 
1. INTRODUCTION 

The "Age 60 Rule", contained in Pan 121 of the Federal Aviation Regulations 

(121.383C), mandates retirement at age 60 of commercial airline pilots-in-command and 

co-pilots. When the rule was established in 1959, the stated aim was to reduce pilot contribution 

to aircraft accidents. Tills emphasis on pilot fitness and performance was assumed to be 

increasingly critical because of the indastry 's shift to aircraft with increased speed and 

passenger-carrying capacity. The selection of age 60 as a mandatory retirement standard was 

based on available studies which indicated that with increasing age there was progressive 

deterioration of relevant physiological and psychological functions. These studies also indicated 

that increasing age was associated with increased incidence of diseases such as bean attack and 

stroke, which were considered particularly problematic because of their association with sudden 

incapacitation. While there was recognition of the fact that not all individuals experience 

equivalent age-related deteriorations in health and performance, an age limitation was deemed 

r>eceSSary because deterioration in performance could not be reliably and objectively measured 

in indiViduals. 

In 1979, the US Congress mandated that the Age 60 Rule be re-evaluated. The general 

aim of this evaluation was to assess the effect of aging on the ability of individuals to perform 

the duties of pilots with the highest level of safety (National Institute on Aging, 1981). The 

National Institute on Aging (NIA) based their evaluation on an Institute of Medicine (IOM) 

committee assessment (1981) of existing relevant scientific data and comments on the IOM 

report. The NIA panel was not able to identify a medical or performance appraisal system that 

could identify those pilots who would pose a safety hazard because of early or impending 

deterioration in health or performance, and therefore they recommended that the Age 60 Rule 

be retained. Howc-\fer, they also recommended that systematic collection of medical and 

performance data meded to further evaluate the Age 60 Rule be carried out. With respect to 

medical data they recoum~ more stringent and under certain conditions more frequent 

sc!eening of physical he-.dth and in pmicular cardiovascular bealth in light of the increasing risk 

of cardiovl'scular acci<il=nts with age. With respect to performance data, they pointed out that 

it is possib!e to test asp!Cts of pilot performance in simulators which can reproduce critical flight 

situations. However, they were aware of no available standard for grading performance in 

objective quantifiable ways. Therefore, the NlA panel recommended that: 

• AdditiDnal research be conducted to develop quantifiable, objective criteria for 

measuring overall pilot performance; and 

• Performance data iJe systematically collected to further evaluate the Age 60 Rule. 

Ten years later, despite increased research attention being paid to these issues, these two 

recommendations have not been sufficiently met. Thus, these recommendations are the basis 

of !:be present Age 60 Project. 

The ultimate long-term aim of the Age 60 Project is ro enhance aviation safety by 

increasing understanding about the relationships among pilot age, experience, performance, and 

accident rates. The specific aims of the present project are: 

1 
• To consolidate the currently separate data bases related to pilot certification and 

aviation accidents and incidents, and to use this consolidated database to 

statistically examine the relationships that exist among chronological age, recent 

flight time, total flight time, and accidents (Task 3); 

• To develop a methodology for the assessment of individual pilot performance 

(Task 4); 

• To plan a longitudinal study that would systematically examine th<: effect of aging 

on pilot performance (Task 5). 

The empirical evidence obtained in this project concerning the relationships among pilot 

age, experience, and accident rates and the effects of age and experience on pilot performance 

should be extremely relevant to an evaluation of the Age 60 Rule. Evaluation of these 

relationships is an important step in determining the feasibility, reliability, and validity of 

individual pilot perfonnance assessment as an alternative to the Age 60 Rule. However, a 

definitive stance on the Age 60 Rule will also require consideration of pertinent issues beyond 

the scope of the present tasks. For example, before the Age 60 Rule can be replaced with an 

indi1tidual retirement standard, the medical certillcation procedure may need to be enhanced to 

more stringently cenify that the pilot is free from impairing physical and mental disease. This 

study will also not explicitly address in detail ismes related to the political, ~nomic, pension 

planning, pilot advancement, or age discrimination issues that have entered into the Age 60 Rule 

debate. 

The present report reviews the scientific literature r.le1t"ant to the three major tasks of this 

project. The organization of this report is as follows. Section 2 will examine the in..fluence of 

aging on pilot perfonr.JIIl!T. First, a conceprual approach for assessing individual pilot 

performaoce and for examining the influeiX:e of aging on this performance will be presented. 

Data related to the components of the model will be reviewed. Finally, conclusions and 

recommendations for a pilot perfonna~ assessment methodology (Task 4 of the present project) 

and for the longitudinal examination of the effects of aging on pilot performance (Task 5) will 

be ptcsenled. Section 3 will consider issues bearing on the relationships among pilot age, recent 

and total flight time, and aviation accidents (Task 3 of the praent project). Emphasis will be 

placed on a critical study by Golaszewski (!983), paying particular attention to the methodology 

and how to improve it. Since, the consolidated database will combine information about 

accidents with information about the medical status of the pilot.s, a brief review of the literature 

pettinent to the relationships among accidents, medical condition, and age will be presented, and 

ways in which the consolidated database could shed light on these issues will be suggested. 

2. AGING AND THE ASSESSMENT OF INDIVIDUAL PILOT PERFOR.MA.~CE 

2.1 Specific Aims 

This section of the repott will review scientific literature relevant to Tasks 4 and 5 of the 

Age 60 Project. Task 4 is aimed at development of a methodology to quantitatively and 

2 
objectively assess an individual pilot's performance. Specifically, these three levels of 

performance will be considered: 

• Basic psychomotor, perceptual, and cognitive skills which are not s!)ecifically 

related to flying but are assu..'lled to in...'luence pilot performance; 

• Knowledge, judgment, and decision making related to piloting an aircraft; 

• Pilot performance in a simulator under varying flight conditions. 

Task 4 will examine relationships among these performance measures within two age 

groups. The data obtained should be useful in the following respects: 

• Provide a preliminary step in the construction of an individual performance 

measure that could eventually replace the Age 60 Rule. 

• Development of an assessment methodology for use in a longitudinal examination 

of the effect..s of aging on pili>t performance. 

• Preli..minary cross-sectional examination of age differences on these measures of 

pilot performance. 

Task 5 is aimed at planning a longitudinal examination of the effects of aging on pilot 

performance. Key questions to be addressed in this study are: 

• With increasing age are there declines in performance on measuresof basic skills, 

pilotknowledge and decision making, or simulated flying performance? At what 

age do the declines occur? How much individual variation characterizes these age 

changes? 

• Are there increments in performance on any of the above measures associated 

either with pi":lts' increasing age or experience? 

• Are declines in some aspects of pilot performance being compensated for by 

increments i.n other aspects of pilot performance'! To what degree? Under what 

conditions? What is the mechanism? For example, if flying performance in the 

simulator appears unaffected by increasing age, is it because age declines in basic 

skills are compensated for by increases in pilot knowledge? 

To accomplish ilie research objectives of Tasks 4 and 5 of the Age 60 Project, two 

preliminary steps must be taken. Step 1 is to deveiop a high-level conceptual model for 

assessing the relationships among aging, experience, and pilot performance. This model will 

be descn"bed below in section 2.2. Step 2 is to review the scie:1tiiic literature in the areas of 

cognitive aging and pilot performance within the framework of this conceptual model. This 

review is presented in section 2.3. 

3 
2.2 Conceptual Approach 

2.2.1 Existing Models of Aging and Performance 

Advancing age is associated with declines in physiological functioning and an increase 

in the prevalence of disorders. However, individuals vary considerably in their rates of 

physiological aging and in their predisposition to disease. Thus, while average levels of 

functioning may decrease with increasing age, individual variability appears to increase. 

Behavioral researchers studying age have found it useful to draw a conceptual distinction 

(although in practice this may be difficult to diagnose) between: primary aging, which refers to 

normal disease-free aging; and ~ondary aging, which refers to disease-related aging. While 

primary aging reflects changes inherent to the aging process itself that are ultimately irreversible, 

secondary aging reflects changes that are not inevitable or always irreversible. Rather than 

being a result of the aging process itself, secondary aging changes may reflect a genetic 

predisposition or they may be lifestyle related. 

In additicn to distinguishing primary and secondary aging, researchers have also found 

it useful to distinguish usual patterns of aging (that describe the average or typical older person) 

from successful patterns of aging that describe the person who shows lesser declines in 

functioning. For example, factors such as internal locus of control, social support to deal with 

life stressors, a healthful diet, and exercise (Rowe & Kahn, 1987) seem lO be associated with 

more "successful" aging. An active, athletic 60 year old may "seem younger" than a sedentary 

40 year old smoker. This is the es..«ential problem with using chronological age as a meaningful 

marker. Chronological age implicitly involves a mixing of these influences. It reflects both 

primary and secondary aging and does not distinguish individuals who display typical as opposed 

to successful patterns of aging. 

Despite these problems in using chronological age as a meaningful marker of an 

individual's functioning, it is still impor-.am to investigate the relationship iJern.·een increasing 

age and functioning, at least in terms of group patterns. Researchers have attempted to identify 

typical patterns of change associated with increasing age for a variety of aspects of individual 

functioning. Schaie (1973; 1977; 1986) des..--n"bes four alternative trend models of changes with 

aging: 

• The increment model refers to behaviors that increase with age. It is used 

extensively to descn"be child development. There may be some aspects of pilot 

performance that also match this increment model (i.e., knowledge related to 

piloting an aircraft). 

• The stability model predicts no change with age in disease-free individuals. 

Many asp::cts of personality may follow a stability modeL For example, for 

pilots some aspects of persOnal style related to crew coordination and leadership 

may not change in systematic ways with age. 

• The irreversi"ble decrement model applies to processes where there is direct 

biological control over age-related decline in performance. These changes are 

4 
assumed to be unaffected by environmental factors mch as experience. 

Psychomotor slowing is a good example. 

• In the decrement with compensation model, environmental inputs may partially 

compensate for biologically determined decrements to produce stability or even 

increments in abilities. For example, there are anecdotal reports of some older 

pilots performing exceedingly well under extreme emergency situations. Perhaps, 

their experience and increased knowledge compensated for any age-related 

psychomotor slowing that they may have experienced. 

No one model is likely to explain all aspects of a complex behavior like piloting. 

However, since one goal is to determine if there a.c>-e age-related changes thai are 'l.ssociated with 

deterioration in piloting skills, there must be a search for aspects of performance that fit a 

decrement model. Second, it is important to consider the concept of compensation. Is 

compensation possible in a complex behavior such as pilot performance? To what degree? 

Under what circumstances? What is the compensatory mechanism? 

Some researchers (Cbamess, 1983; Rybash, Hoyer, & Roodin, 1987; Salthouse, 1987) 

studying age differences in COII1!1lex behaviors such as typing, chess, bridge, physics, and 

computer programming have found that older people seem to do as well as young people on 

these complex tasks. Surprisingly, these older adults seem to have experienced average 

age-related declines on the component psychological skills that are related to the complex 

behavior on which they are succes-sful. In other words, there appears to be compensation for 

declines in the basic skills. Of course this compensation is only possible when the older adult 

has developed expertise in the complex task. An older novice would not be able to make use 

of compensation, and in fact would tend to perform more poorly than a younger novice because 

of the age-related declines in basic skills. Thus, expertise (knowledge in a particular domain 

that has become intuitive, automatic and highly skilled) plays a crucial role in the compensation 

process. 

Rybash, Hoyer, and Roodin (1987) propose a theory of what they term encapsulation-the 

process of compensating through expertise for age-related declines in intellectual or cognitive 

functioning. Encapsulation is the theoretical notion that the domain-independent processes of 

cognition such as attention, memory and reasoning become linked with the !)rodu;;t of 

cognition-knowledge within a specific domain. As a result of this linkage, performance in a 

domain of expertise may be un..>-elated to declines in domain-independent cvgnitive processes 

because of the compensating role of expertise (the domain-dependent knowledge base). For 

example, it is possible that domain-dependent knowledge and judgment related to flying could 

compensate for age-related declines in the older pilot's domain-independent processes such as 

attention, information processing speed, and working memory. Thus, to underst.and aging and 

pilot performance it is necessary to look not only at ccgnitive processes but also the domain in 

which they are .:ncapsulated. 

Finally, it is important to determine in what domains, and to what degree, expertise can 

compensate for decrements in domain-independent processes. For example, Charness (1985) 

and Rybash, Hoyer, and Roodin (1987) s>.lggest that the cumulative eftects of age and experience 

that enhance the expert's knowledge base are most likely to compensate in certain domains, such 

5 
as chess or compute:- programming, where perforhlance allows more time for predictability, 

planning ah;>_ad and reflection, and demands fewer snap decisions and less physical exertion. 

In the latter domains, such as performance in sporting activities like basketball, expertise cannot 

totally compensate. Performance declines with age even among those individuals who display 

expert perfonnance during young adulthood. Thus, t!le degree to which older pilots = 

compensate for declines in basic skills likely depends on the type of flying they are doing. 

Under normal, routine conditioll3 flying may he more similar to "chess" and compensation may 

be possible. Under e; 'Teme emergency coflditioll3 the performance demands {e.g., quick 

decision-making and response) may become w . .-e similar to "basketball" and compensation may 

no longer be sufficient to maintain the same ,eve! of complex task perfoi'JllailCe. 

2.2.2 A Proposed Model for the AssesSIDent of Acing and Pilot Performance 

V..'hile there is a wealth of data on the effects of aging on perceptual, psychomotor, and 

cognitive abilities, most of this research involves basic skills tested unde,. laboratory comiitions. 

Comparatively little attention h2s ~:.. direcred at the effects of aging en complex behavior in 

real world situations, such as flying an aircl'2fi. There is a large and burgeoning literature on 

human factors aspects of piloting an aircl'2fi. yet comparatively little aimed directly a! the effec: 

of aging on pilot perfonnance. Because of the relatively small lllllil.ber of studies mat hav:! 

directly inves.:igated the effects of aging on specific aspects of pilot perform~ID:e, there is a great 

need for systematic investigation of multiple aspects of pilot performance acro:;s a wide age 

span. In order for this investigation to be most fruitful, it shouid be guiaed by a coherent 

conceptual framework. The framework proposed for the pre:;eru project (see Figure 1) att..ompts 

to draw : '"'gether !he fragmented resea_rch on aging and pilot performance from the cognitive 

aging literature and aviation human factors literature imo a model of aging and pilot performance 

th:rt is similar to the decremelit with compensation models that have been developed in the area 

of cognitive aging and that have S'JCCesSfuliy contributed to understanding the concept of 

expertise. The model is composed of th.."ee classes of v-ariables: 

• Pilot characteristics, including age, health status, and amount and type of flying 

experience. It is important to consider health status as well as age to attempt to 

disentangle as much as possible the effects of primary and seconda._ry aging. 

Pilots' medical certification procedures screen out cases of serious health 

impairment, but drJeS more subtle, subclinical disease aJfect performance? It is 

also important to consider the role of experience. "fo what degree does 

experience itself {i.e., simple practice as measu.=i in flight hou..-s} correlate V'ith 

levels of expertise? Cha..rness (1989) points out that expe;ience in tlie form of 

practice i;, necessary though not sufficient for developing high levels of expertise 

and sltill. All Part 121 pilots have a minimal level of e:~:perience which is 

significant, but does increasing this level of experience have beneficial effects? 

Up to what point? 

• Stressors, sw.;J::o as clcohol or ch-ugs, cir..adian disturbaJ:r..es, general life stress, 

and incteased worKload. T"nese srressors may influence pilot performance tlirectly 

and/or interact with pilor characteris::ic~ to im1uence perfonnance. For example, 

alcohol and o•.her drugs may have a greater affect on pilot performance in older. 

6 
'·I 

FIOURB I. A Model to ASGess Age-Related Changes in PIIOl Perfom•anc:c 

Pilot Cbaractert.Uc•: 

Age 

Absence/Presence of Disease 

EKportlae 

Stresaf'll,.: 

Stress 

Drugs/Alcohol 

High Workload 

Perfonnance: 

Complex Task Performance (Simulator): 

Routine performance conditions 

Emergency high performance 

condlllono 

Domain-Dependent Pilot Knowledge: and 

Judgment 

Ooinaln·lndependent Skills: 

Cognitive 

Perceptual 

Psychomotor 
compared to younger, pilots (Collins & Mertens, 1988: Leirer, Yesavage, & Horrow, 1989; 

Morrow, Leirer, & Yesavage, 1990) . 

.., Pilot performance, which includes bask cognitive, perceptual and psychomotor 

ski!ls; flight-relevant knowledge and judgment; ai.!d flighi performance in a 

sinulator under varying flight conditions. Changes in domain-independent basic 

skills may not show a relationship to complex performance until a critical 

threshold is exceeded. These thresholds may fu...'"Illselves change with age. One 

\vay to explore this situation is to identify younger and older subjects who are 

matched on the complex behavior (correlation between performance and age is 

zero); then break down the components of the compiex behavior to show 

age-related decline in some component that is compensated for by enhanced skili 

in another component. For exalllple, declines in ba,;ic ski!ls could be 

compensated for by increases in pilot knowledge and judgment that occur as 

pilots' expertise increases. However, increased knowledge may only compensate 

for declining skills under ideal or routine task conditions. Therefore, pilots' 

performance must be tested under li range of flying conditions. Standard 

maneuvers, because they are so we!l-learned and practiced, may only be useful 

in detecting obvious d~rements in pilot performance. Most of the literature on 

age and performance suggests that as tasks become more complex and demanding, 

age-related performance declines a..--e more pronounced. Cerrella, Poon, and 

Williams (1980) call this robust finding the age-complexity hypothesis. 

Performance of complex maneuvers under stress or in novel situations is more 

likely to be impaired in older pilots than well-learned familiar tasks (National 

Institute on Aging, 1981). Emergency flight cor:ditions such as turbulence, bad 

weather, and increasing communication demands could be manipulated and pilots' 

coping assessed. 

2.3 Background Literature 

2.3.1 Pilot C..."haracteristics: The Aging Pilot 

Within the separate r<!Sea!Ch areas of cognitive aging and pilot performance, there exists 

a vast literature relevant to the effects of aging on pilot performance. 7 )Wever, the intersection 

of thes:: two areas of research is composed of a very small number of studies that directly 

examine the effects of aging on pilot performance. Therefore, while the present re"iew will 

descnl>e in detail the methods and results of studies that have examined aging pilots, it will also 

be necessary to make reference to studies within the area of cognitive aging that have examined 

non-pilot subjects pe;:forming more generic laboratory tasks. Prior to reviewing this research, 

it is importallt to note several general iss-ues that must be considered in interpreting these 

findings with respect to the current project. 

First, the few studies done on aging pilots are generally limited in three respects: the 

pilots studied, the research design, and the aspects of perfo=ce examined. The research that 

has been done with aging pilots frequently utilized private pilots as subjects. Those results may 

no! generalize well to professional pilots with thousands of hours of flight experience. In 

addition, the scarce data on the effects of aging on pilot performance is predominantly 

8 
cross-scaional. 'That is, the studies have compared (at a single poi!lt in time) groups of pilots 

that vary in age, rather than repeatedly testing the same group of pilots as they age (a 

longin!diml design). While there are interpretation difficulties with both of tlr..se simple 

research designs, a reliance on cross-sectional data is particularly difficult to interpret because 

different age cohorts of pilots can vary on a number of dimensions besides age {such as health. 

education, and experience). Finally. the few longitudinal studies that have been conducted on 

pilots, including The One-Thousand-Aviator-Study (Macintyre. Mitchell. Oberman. Harlan, 

Graybiel, & Jobnson, 1978) and The Lovelace Foundation Study (Proper, 1969), did not 

emphasize cognitive abilities nor correlate these abilities with in-flight performance. 

Extreme Ql'e must also be taken in generalizing the findings with respect to cognitive 

aging in non-pilots performing generic laboratory-based cognitive tasks to the flying proficiency 

of the aging aviator. Generalization is frequently limited due to issues related to subject 

selection and task selection. Pilots may represent a se:!ect population that is systematically 

different than the general population of older adults. For example, older subjects who are drawn 

from the general population of community-residing elderly may on average be less educated and 

less physically fit than older pilots due to pilots' initial selection procedure and continuing 

medical certifications (Illstitute of Medicine, 1981). Many of these studies are also based on 

comparisons between extreme age groups who may not be equated on other key variables (i.e. 

comparison of 20 year-old college students and 70 year-olds attending a senior citizens activity 

center). Literature in the area of cognitive aging has also emphasized laboratory tasks. A 

reliable age difference in a laboratory reaction time task that involves a few hundred 

milliseconds may not have any significance in the aircraft {Institute of Medicine, 1981). 

Unfortunately, the type of cognitive aging data that would be most generalizable to aging and 

pilot performance are not available. There are very few studies that have examined the effects 

of aging on the performance of complex professional skills and even fewer studies that examine 

the contribution of practice or experience to the performance of these complex skills. 

It would be beyond the scope of the present !ask to comprehensively review the existing 

literature on cognitive aging and comprehensively review the aviation human factors literature. 

Therefore, the scope of the present review v.iil be limited to a brief re\'iew of the few studies 

that have comprehensively examined the effect of aging on pilot performance and then a more 

systematic evaluation of the discrete cognitive functions related to pilot performance that may 

be affected by aging. 

The few studies that have directly and comprehensively examined the effects of aging on 

pilot performance are of two distinct types. The first category of studies (Bohannon, 1969; 

Gerathewohl, 1977; l978a; Institute of Medicine, 1981; Tsang, 1990) is based on critical 

review, analysis, and integration of existing research, rather than actual data collection. When 

appropriate, the conclusions of these review articles are incorporated into the present liter-ature 

review. 

The second category of studies of the effects of aging on piiot performance (Braune & 

Wickeas, 1984a; 1984b; Szafran, 1966; 1969) is aimed at the development of a "functional age 

profile • that would address the issue of interindivid"ual and intraindividual differences in rate of 

agh•g. "Certain individuals may 'age' more rapidly in some or all components of performance 

than others. Hence, a given individual may be functionally old or young, independent of his or 

9 
ber chronological age" {Btaune & Wickens, 1984a. p.3). Therefore, these data collection 

studies assess a range of psychological abilities presumed to be important to pilot performance 

and correlate such data with chronological age and pilot perfollllliD:e. 

Szafran (1966; 1969) investigated cross-sectional age differences (airline. military and 

test pilots were selected to represent each decade from age 20 to 60) in perceprual and 

psycho-physiological skills. Each pilot was administered a battery of tests that was designed to 

measures the following flight-related skills: making high-speed decisions. detecting low 

probability and low intensity signals, and retaining significant amounts of information (Szafran, 

1966). For example, pilots completed sensory perception tasks measuring visual 

accommodation, Critical Flicker Fusion (CF-'~• dark adaptation, and hearing thresholds. They 

also completed a serial-choice reaction time task by itself (low workload) and simultaneously 

with a sbon-term memory task (high workload). The conclusion for almost all measures studied 

was that pilots' increasing age was not related to perfOilllliD:e of these flight-related tasks. 

Age-related perfonnance dec!emelllS were only found in the high workload condition which 

required the simultaneous performance of two tasks. 

Braune and Wickens (1984a) studied 100 non-pilot subjects between age 20 and 60 and 

had them complete a battery of information processing, aviation-relevant tests. They identified 

tbree general age-related changes: 

(1) Some perceptual--mot and spatial tasks (e.g., second-order tracking, maze 

tracing, dichotic listening) showed monotooic decline across the entire age span. 

(2) A second set of tasks (e.g., visual-spatial and visual-verbal Sternberg memory 

search tasks), primarily mlecting processing speed, declined systematically, but 

only after age 40. 

{3) A third set of tasks, primarily reflecting time-sharing, showed no influence of 

aging. Decline with age in dual-task performan::e was not greater than decline 

with age in single task performance. 

They also found that there was large variability within groups, with some older subjects 

displaying performance superior to the mean of the young group. In a follow-up study (1984b), 

Braune and Wickens studied a sample of 30 male pilots between the ages of 20 and 60. They 

gave the subjects a similar battery of information processing a,.;.:mon-related tests and then had 

each perfonn maneuvers in a GAT-2 twin engine simulator while simultaneously completing a 

communications task. They ;:ound that 24% of the variance on the flight simulator task and 46% 

on the communications task could be captured by the age-sensitive information-processing tests. 

The remainder of this section will examine the cognitive functions considered to be 

crucial to piloting. The selection of these functions was based on existing conceptualizations of 

the abilities underl)".ng pilot performance (Braune & Wickens, 1984a; Gerathewohl, 1977; 

1978a; 1978b; Imhoff & Levine, 1981; North & Gopher, 1976). The c-.onstructs and processes 

listed in Table 1 were found in one or more of these taxonomies. Review of pilot and non-pilot 

studies related to each of these constructs follows. For each construct, relevant data that 

addresses the question of the influence of aging and! or experience on that construct will be 

10 
-------------------·-~~~~~--· ~ ~·- ~~~··---~·---~~ 

,_. 

.... 

Construd 

Perceptual 

Psychomotor_ 

Attention 

--

Memory 

Information Processing 

Problem Solving and 

Dcx:ision·Making 

TABLB I. Key Piloting Behaviors Affected by Aging and/or Bxperienoc 

..._ Sample Pllotll!a Activity 

Auditory Peroeptlon Uste!IIO ATC communication, Iiden for variance ill cnaillo mile 01' air flow iiMif 

flight control surfaces . Visual Perccpdon Inspect, read instruments, obsme dw!SC~ in illllruntmt ~ dctM ud 

follow runway llghlln& 

Viaual Scannina Instrument IICIII'I, air traffic dctoclion 

Tracking TnK:k Instrument and CKtemal suuroos and llllj~~ controls ~y 

Selecllvc/Powscd Ignore IUk·irreleYallt lnf'oonation 

Divided Multiple task proc:euing (e.s .• .-eadlns instrumenli durins ATC ,'lOIIImll!llcalioll 

sequence) 

Switching ~~~ ~lllelllllfatca durina emerpncy 10-llillillllon 

Su.Wned Mlllntain conllfanl monitoring of inlltnlmenli and CKtemal c:ua (eepecially for 

situation ·-durlns 10111 mahli) 

Short term and worldns Mlllntaln Information for Immediate procmlm-lil (e.a., runway clellnmce 

memory informcllon) 

Long term memory Remember llfandllrd operallns and emerpncy pi'OI!lCIIum 

Prospective Remember 10 perform llfandllrd IICIII'II and safety checks 

Speed Identify inpuli quickly (e.s., rcooanir.eiiiiOIIIIIIous eoelllitlon which conki lend 10 

an emeraency) 

Visual spatial VIsualize 3-D situation, modifu:ation or rotation of mental imap for awanmeu of 

aln:raft lncstion and direction, distance, and speed perception -~ 

Verbal sequential Process A TC communication (c. a., for aw~~m~Css of surrooooina air traffu:) 

Domllln Independent Ability 10 apply rules, ability 10 draw conclusions regardina inte:rrelationihips 

among variables, menial arithmetic. 

Domllln Dependent Assess situation and decide on appropriate action (e.g., intcl]ll'd how weallm' 

impacli night plan); Identify and evaluate the worth of alternative solutions (e.s., 

mechanical failures) ~-~ 

I 

! 

I 
reviewed. While for ease of presemation each function is dis...-ussed separately, it should be 

noted that in reality these functions are closely interrelated and jointly influence various aspects 

of pilot performance. For example, pilot difficulty in decision making may reflect both a 

slowing in processing time and and a memory deficit (Tsang, 1990). 

Perceptual abilities. Banich, Stokes and Elledge (1988) reviewed relevant literature on 

aging and ~ormance of visuo-spatial tasks (such as facial discrimination, and judgments of line 

orientation) and concluded that advancing age is ass~iated with performance declines. This 

age-related decline has also been foUIII! in pilots. The older pilots in Braune and Wickens 

(1984b) study performed more slowly on a hidden figures task than the younger pilots <Lid. 

(Pilots studied were 20 to 60 years old). 

The literature not only indicates that there are age differences for some types of 

perceptual behavior, but also !las demonstrated links between performance on these types of 

perceptual tasks and performance of complex behaviors (automobile driving) that may be 

relevant to pilot performance. For example, field dependence, an aspect of perceptual style that 

reflects an individual's susceptibility to the effects of interfering stimuli, has been found to be 

greater in older than younger individuals and bas been found to be associated with impaired 

automobile driving performance (Institute of Medicine, 1981). Temple (1989) also found that 

older adults' (aged 60-78) driving performance was significantly related to their performance 

on perceptual tasks. Aging has also been found to be associated with poorer performance in 

estimating vehicle velocity (Scialfa, Guzy, Leibowitz, Garvey, & Tyrrell, 1991), and slower 

reaction to symbolic traffic signs (Halpern, 1984). In both these studies, the older subjects 

ranged from 60 to 75 years of age and performed more poorly in comparison to subjects under 

30 years of age. 

Psvchoinotor skills. "Sensory, perceptual, decision, and motor processes are involved 

in psychomotor performa~. All are more or less affected by aging" (Gerathewohl, 1977, p. 

5). Braune and Wickens (1985), who studied subjects ranging in ag;: from 20 to 60, found that 

second-order tracking performance, and latency of maze tracing significantly declined with age. 

Mertens, Higgins and McKenzie {1983) also found age decrements (in 60-69 year-olds compared 

to 40-49 year-olds and 20-29 year-olds) on a psychomotor tracking task. These age-related 

deuements were more pronounced at moderate and high workload levels. These age-related 

declines in performance on psychomotor tasks such as tracking tasks may to a significant degree 

reflect age-related diffelCIA:CS in speed of processing. Longitudinal studies show a similar 

pattern of age-related slowing as the cross-sectional studies (Fozard, Vercruyssen, Reynolds, & 

Hancock, 1990). 

This is an important area to investigate not only because of the appa.t·ent age declines but 

also because psychomt>tor skills have been found to correlate with the performance of complex 

behaviors such as rlriving and to be predictive of automobile accidents (Barrett et al., 1977). 

In addition, examination of aviation accident statistics indicates that faulty perceptual-motor 

behavior was a causal factor in a large proportion of nonfatal pilot-caused accidents 

(Gerathewohl, 1978b). 

However, it is also important to note that there are large individual differences in 

psychomotor slowing and that this type of performance is highly influenced by practice (Institute 

12 
of Medicine, 1981). Braune and Wickens (1984b), studying instrument-rated pilots aged 20 to 

60, found that tracking performance was significantly correlated with experience but not with 

age. Thus, practice and experience may ~unteract the detrimental effects of aging. A study 

by Stones and Kozma (1989) provides strong evidence that the overpracticing of an activity can 

counteract the effects of aging on psychomotor performance. They compared young and old 

subjects in terms of the number of times they could tap their hands and their feet in 30 seconds. 

Large age differences were found for hand tapping but not foot tapping. Hand tapping is an 

unpracticed task; foot tapping incorporates movements practir..ed everyday during normal 

locomotion. 

Attention, Braune and Wickens (1984a) point out that the pilot must continually monitor 

visual and auditory information from the external environment and within the cockpit. Because 

of this need to monitor multiple sources of information, "the pilot must be able to focus on the 

critical cues (selective attention), switch attention as different cues become relevant at different 

tin"...:s (sv.itching attention), aDd often integrate cues from diverse sources inside and outside the 

aircraft's cockpit (divided attention)" (p. 8). In addition, pilots must also maintain this 

monitoring of visual and auditory input over extended time (sustained attention). In a recent 

review of the resean:h on aging and attentional processes, McDowd and Birren (1990) 

summarize the current fin:lings related to age differences in these four aspects of attention. 

In selective attention, an individual must select and focus on a single input and filter out 

irrelevant information. Studies of age differences in selective at>..ention, which usually involve 

a visual search p:tradigm, have consistently concluded that older adults compared to younger 

adults are more distracted by irrelevant information (Plude & Hoyer, 1985). Specifically, oldtr 

adults appear to have more difficulty discriminating relevant from irrelevant information, 

particularly when the task is effortful or demanding. Using their battery of aviation-relevant 

tests, Braune & Wickens (1985) found that performance on selective attention tasks declines with 

age. Boer (1986), studying a wide age range of pilots, found a strong relationship between 

increasing age and poorer performance on this type of attention task. Further support for the 

important role of selective at•~ation in pilot proficiency comes from research by Gopher and 

Kahnemall (1971) and North and Gopher (1976), who found that selective attention tasks were 

significant predictors of fligh< proficiency. Glanser and Glaser (1959) studied Air National 

Guard and commercial airline pilots (who ranged in age from 20 to 50) and found that older 

pilots were less sw:cessful than younger pilots at detecting relevant from irrelevant targets in an 

aviation-relevant display. Thus, selective attention appears to be an important predictor of flight 

performance and age decrements in selective attention in aging pilots have been found. 

However, practice may reduce these age effects. Hoyer (1987) has found that expertise can 

reduce these age-related declines in selective attention. 

P2rticularly during high workload conditions, piloiS need to perform multiple tasks at the 

same time and must be able to divide attention between di.."ferent inputs and activities (Braune 

& Wickens, 1984a; North & Gopher, 1976). Divided attention, "the process by which attention 

is controlled to successfully perform two simul!aneous tasks" (McDowd & Birren, 1990, p.223), 

appears to be characterized by an age-related deficit. However, there are some data inconsistent 

with this general conclusion. Specifically, some sn1dies (Salthouse & Somberg, 1982: Wickens, 

Braune, & Stokes, 1987) have found no age differences in divided attention performance. It 

should be noted that the tasks used in these studies were simple perceptual and memory search 

13 
tasks. With more complex tasks age differences in divided attention performance are found. 

For example, Ponds, Brouwer, and van Wo!ffelaar (1988) found significant age-related 

decrements in performance on a simulated d..riving task. (Subjects over age 60 performed more 

poorly than those under ;;!g~ 60). This supports Hunt and Hertzog's (1981) proposal that 

attentional capabilities (such as divided attention performance) decline with increasing age. 

Complex tasks that demand more attention will show larger age-related deficits than simple 

tasks. Thus, it appears that the bulk of the evidence suggests an age-related deficit in divided 

attention that is particularly manifested on more complex tasks. However, a crucial question 

still remains about the role of practice and expertise in r.nitigating this age-related decline in 

divided attention performance. 

The available literature in the area of age differences in attention switching (the process 

of alternately monitoring more than one source of information) is also characterized by 

theoretical controversy and contradictory findings. Many of the available studies are aimed at 

examining the relationship between attention switching and short-term memory. Some 

researchers (Welford, 1964} have proposed that attention switching reduces short-term memory 

capacity and tha~ this reduction is most pronounced in older adults. Other researchers (McGhie, 

1969; Schonfield, 1981) propose that age-rc:lated differences in memory retrieval are responsible 

for older adults' problems with attention switching tasks. Neither of these theoretical positions 

has been consistently supported in experimemal studies. The nature of the relationship between 

short-term memory and attention switching is still unclear. More important to note is the fact 

that age-related differences in this aspect of attention have not been consistently reported. 

McDowd and Birren (1990) reviewed the few available studies and concluded that visual 

attention switching does not decline with age but that auditory attention switching does. For 

example, using an attention switching version of a dichotic listening task, Braune and Wickens 

(1985) did find that attention switching dechnes with age (subjects were 20 to 60 years old). 

Sustained attention, usually assessed with a vigilance paradigm, has not received much 

rescan:h attention in the area of cognitive aging. The few studies which have been done indicate 

that on vigilance tasks older adults {over age 70) are less accurate in detecting the target stimulus 

than young adults (under ag~ 30) and that this age difference remains even after extended 

practice (Parasuraman & Giambra, 1991}. Most researchers explain thil. age-related difference 

in detection accuracy on vigilance tasks as due to age-related differences in central nervous 

system arousal, however they do not agree on whether older adults are overaroused or 

underaroused in comparison to younger adults (McDowd & Birren, 1990). While most studies 

find a main effect for age on vigilance tasks (with older adults performing more pc;orly than 

young adults}, age does not seem to interact with the leng'.h of the task. "The vigilance 

decrement that normally occurs during an extended task does not seem to be greater for older 

than for young adults" (McDowd & Birren, 1990, p. 225). Since pilots must maintain 

performance over extended periods of time, sustained attention is a ~;ritical component of flying. 

Therefore, these age differences in detection accuracy in laboratory-based vigilance tasks have 

important implications for pilot performance and age-related differences in pilots' performance 

on vigilance tasks should be investigated further. 

Memory. Much of a pilot's activity requires memory operations. Salthouse (1985) 

reviewed the literature on aging effects on memory and concluded that age is responsible for 

between 4% and 24% of the variance on various memory tasks. It is clear that increasing age 

14 
l 

differentially affects different memory processes. Hultsch and Dixon (1990) draw tlle follo·.ving 

conclusions about those memory systems that show changes with age and those that a.--e spared. 

With regard to Craik's (1977) wel!-known distinction between primary (short-term) memory and 

secondary (long-term) memory, there still appears to be support for the notion that age effects 

on primary memory are minimal, unless these short-term memory tasks also require active 

manipulation of information or division of attention. There are significant age-related deficits 

on tasks involving retrieval from secondary memory that may also reflect age differences in 

initial encoding pi'O"..esses. Hultsch and Dixon {1990) also note that working memory, which 

requires the siimLtaneous storage of recently presented material and processing or additional 

ruaterial, is a critical system that may show substantial age-related decrements. Older adults' 

deficits appear to lie primarily in the processing rather than storage aspects of working memory 

(Hultsch & Dixon, 1990). These age-related declines in working memory are important because 

of working memory's contribution to performance on other cognitive tasks (Salthouse, 1985). 

Salthouse (1991) proposes that these age-related differences in working memory may be 

"Dediated by age-related decrements in processing speed. However, generalization from age 

differences in laboratory performance to the performance of aging pilots are suspect, because 

working memory appears to be domain specific and influenced by experience (Charness, 1989). 

The crucial question is: to what degree does poorer working memory influence pilots' 

performance of a well-practiced complex task. 

In the aviation literature there ar~ few studies that would allow conclusions to be clrawn 

about age-related differences in memory performance of pilots and the relationship of these 

differer.ces to pilot performance. While Braune and Wickens (1984a) found that performance 

on Stembery memory and delayed digit recall tasks (as measu..red with their aviation skills 

battery) declined with age in non-pilot subjects (aged 20 to 60), they (1984b) found no 

age-related declines on these measures in instrument-rated pilots (aged 20 to 60). Further, while 

showing no age decrement in pilots, the Sternberg memory task was found to be a strong 

predictor of performance on a GAT-2 twin engine simulator (1984b). Thus, while there appears 

to be support for the CDI!Clusion that memory performance does influence pilot performance, it 

is not clear to what degree pilots (as compared to the general population} ex..'rlbit performance 

decline on these relevant memory tasks and what role expertise and experiew..e may have in 

minimizing age-related differences on domain-specific memory tasks. 

Information processing speed. It has been well established that speed of information 

processing decreases with advancing age (Cerella, 1990; Kline & Szafran, 1975; Kline & Birren, 

1975). Because much of a pilot's behavior in high workload situations must be rapid as well 

as accurate (Braune & Wickens, 1984a), it is important to consider to what degree this slowing 

in processing speed is found in pilots and to what degree it influences flight proficiency. 

Wickens, Braune, Stokes, and Strayer (1985) studied non-pilot adults between age 20 and 60 

looking for age-related performance differences on a revised version of the Braune and Wickens 

(1984a) aviation-relevant skills battery and found age-reiated slowing in processing speed which 

was mostly localized in response processing. While this age-related slowing has been found in 

healthy, educated subjects, it is not clear to what degree it occurs specifically in pilots (Institute 

of Medicine, 1981). Even if pilots are found to exhibit the same magnitude of slowing on 

laboratory-based information processing tasks that has been found in other healthy older adults, 

further research will be needed to determine the impact of this slowing on flight performance. 

15 
Judgment and decision making. There is mounting evidence that errors in judgment and 

decision making contribute to a large proportion of aviation accidents and incidents (Jensen iJ;;. 

Bene!, 1977). Jensen (1982) estimates that faulty pilot judgment is involved in about 50% of 

civil aircraft accidents. With ~ increasing automation of the cockpit, the pilot's role as a 

decision niaker appears to be becoming even more prominent. However, most of the data 

relevant to this aspect of pilot performance is based on post-hoc analysis of accident reports. 

'There is currently very little experimental data related to pilot decision making (Wickens & 

Flach, 1988) and even less known about the effects of aging on this aspect of pilot benavior. 

The research that is being conducted on decision-making processes in commercial aviation is 

focusing heavily on crew decision niaking rather than individual decision makin~. The one study 

(Szafran, 1969) to examine age-related differences in pilot decision making found no significant 

age effects. 

While age per se has not been found to influence pilot decision making, there is ample 

~ti<)n that the ~ level of e~ that cbara!:.teti.7.e older pilots does. Mohler 

(1981) notes that there are numerous anecdotal accounts of older healthy captains utilizing their 

well-developed judgment and decision making to ave:t an accident. If the ievel of experience 

and expertise of the pilot does have an effect on decision making (Mosier, 1991), the question 

becoDles how is the experienced pilot's decision making different from the less experienced 

pilot's? Before descnoin,g a set of studies that have addressed this question directly, it is 

important to consider on a general level what differentiates expert from novice decision makers. 

Klein (1989) has developed a model of expert decision making, termed Recognition 

Primed Decisions. There are two critical pbaseS in this deciSion making model: the assessment 

of an uncertain problem situation and the systematic evaluation of plausible problem solUtions. 

Accol'ding to this model, expert decision mairers are able on the baSis of their prior experience 

to quickly recognize and aprropriately classify situations and to identify the most plausible 

course of action. When experts perform highly practiced tasks in familiar operational situations, 

they recognize and respond to complex situations using pattern recognition or intuition 

{Chappell, 1~1). Bxpert! mo fuquemly jmmed\atel-y ~'&he best rolutim\ ~\)a problem 

without evaluating alternatives (Klein, 1989). 

Stokes and Raby (1989) suggest that two factors appear to exert an influence on pilot 

decision making: the experience level of the pilot and the conditions of stress in which the 

decision is carried out. These two factcmo are being investigated at the University of illinois 

Institute of Aviation. Stokes and his colleagues (Wickens, Stokes, Barnett, & Davis, 1988) have 

used a computerized piiot decision-making simulator (MIDIS) to investigate an information 

processing model of pilot decision making that takes in!o account pilot experience and stress. 

They found that low and bigh experienced instrument-rat«! pilots did not differ significantly in 

their judgments, but that experienced pilots were more confident of their decisions. "The two 

groups however did differ in terms of what problem variables degraded decision performance, 

and what individual abilities affected that performance. In particular, novice decision 

performance was partially predicted by information processing tests related to spatial abilities, 

working memory capacity, llll'thematical ability and by tests of declarative knowledge. 

However, these tests had little predictive abilities for the more experienced pilots~ (p. ill). 1n 

a related study (Stokes, Belger, & Zhang, 1990), novice pilots were found to show significantly 

16 
I I 

poorer decision making when under laboratory-induced stress. This stress did not lead to poorer 

decision making in the experienced pilots. 

Clearly, judgment and decision making are important aspects of pilot performance that 

deserve increased research attention. In particular, the research has hardly begun to address t..he 

effects of aging on this aspect of pilot performance. The research on novice versus experienced 

pilots is intriguing but requires further examination. 

2.3.2 Other Pilot Characteri.stics 

Since the present project is aimed at exammmg the influence of aging on pilot 

performance, this section of the review has focused primarily on the role of pilot age. However, 

as can be seen in the conceptual model presented in Figure 1, other pilot characteristics aiso 

exert critical influences on pilot performance. Two of the most important, pilot health status 

and level of experience, will be addressed in section 3 of this report but will also be summarized 

briefly below. 

Presence/absence of d!sease. When considering pilot clmacteristics as predictors of pilot 

performance, it is critical to consider health status as well as age to disentangle as much as 

possible the effects of primary and secondary aging. For example, Szafran (1966; 1969) studied 

the performance of older pilots on a number of psychological and psycho-physiological tasks and 

found that age was not a significant predictor of peiformance, but cardio-pulmonary status was. 

Review of the aviation medical literature in section 3 of this report describes additional studies 

that have linlced medical variables, age, and pilot performance. 

Experience. Pilot experience and expertise is also a critical char..cteristic that influences 

pilot performance. The literature related to the influences of pilot age, recent flight time and 

total flight time on av';.ation accidents (described in section 3 of this report) strongly demonstrates 

the influence of experience on pilot performance. In particular, the role of recent experience 

appears to be critical. Childs and Spears (1986) reviewed much of the literature relevant to the 

role of experience in pilot performa;x;e. UnfortuiJately, most of the literature they surveyed is 

in the form of relatively inaccessible reports. They conclude that "pilots experience significant 

performance decrements over short periods of time . . . and such . . . decrements are mainly 

cognitive in nature (Childs & Spears, 1986, p. 237). "That the decrement in performance occurs 

over a short period of time seems to suggest that age, itself, is not an important factor in 

performance. Golaszewski's (1983) findings, to the extent that they can i>e trusted, bear on this 

question. He concluded that older pilots with little recent flight experience have a high accident 

rate. It InaY be that older pilots have greater difficulty reacquiring the skills that are lost over 

the short term when pilots do not maintain currency. 

2.3.3 Stressors: Their Interaction with Age 

Stress. Green (1985) identifies three kinds of stress which affect pilots: envL.-onmental 

stress (noise, vibration, cold, etc.), acute reactive stress {situations in which "fight or flight" 

occurs}, and life stress (stress produced by bereavement, divorce, etc.). Upon examining the 

records of approximately 300 aviation ar--eidents and incidents in the U.K. Confidential Human 

Factors Incident Reporting Programme, he concluded that with the exception of sleep 

17 
deprivation, the importance of which seems to be underestimated in analysis of accidents, 

environmental stress is mild and is a relatively unimportant factor in accidents. The meager 

experimental evidence does indicate that acute reactive stress can be disruptive. ..o\nalysis of 

some aviation accidents suggests that in some cases aircraft emergencies can increase a pilot's 

arousal level and contribute to pilot errors. Green also concludes that life stress may be an 

important factor in causing accidems. However, most of the available data is anecdotal and 

consists of the retrospective accounts of pilots who have been involved in accidents and 

incidents. For example, Ursano (1980) and Green (1985) cite case studies to illustrate the ways 

in which life stresses, such as marital difficulties and interpersonal probiems with work 

supervisors, can be impli.:ated in accidents. Alkov, Gaynor, and Borowsky (1985) employ a 

more epidemiological approach and provide evidence that life stress may be an important factor 

in aircraft accidents. Naval aviators who had heen involved in major aircraft mishaps were 

divided into two groups, those who were and were not causally involved in their mishaps. The 

group identified as culpable for their accidents reported higher levels of recent stressful life 

events. We are uaaware of any literature that descn1les the relationship between age of the pilot 

and stress. 

Drugs. Studies of drug effects on pilots focus mainly on alcohol and marijuana. Modell 

and Mountz (1990) survey the problem of drinking and flying, pointing out its special dangers 

and its implication in general aviation accidents. They note that approximately 10% of 

general-aviation pilots involved in fatal aircraft accidents due to pilot error had measurable blood 

alcohol concentrations. They further note that while alcohoi is often implicated in general 

aviation accidents "no fatal accidents have been recorded within the U.S. airline-transport system 

ju which alcohol was found to be a causative factor (Modell & Mountz, i990, p 455). • 

Direct studies of the effects of alcohol on performance (Collins & Mertens, 1988; 

Morrow, Leirer, & Yesavage, 1990; Ross & Mundt, 1988) show that alcohol deleteriously 

affects numerous aspects of pilot performance, including psychomotor and spatial abilities, radio 

communication, localizer tracking performance, and collision avoidance. Collins and Mertens 

(1988) and Morrow, Leirer, and Yesavage (1990) found that oider pilots are more impaired by 

alcobol than younger pilots. 

Yesavage, Leirer, Denari, and Hollister (1985) found that marijuana ingestion impaired 

pilot performance on a simulated landing t.ask. Leirer, Yesavage, and Morrow (1989) 

subsequently showed that marijuana ingestion impairs the performance of older pilots to a greater 

extent than it does younger pilots, particularly on pilot tasks involving working mem'Jry. 

High workload. The research of Szafran (1966; 1969) has demonstrated that workload 

is a critical factor to consider when examining age effects on pilot performance. Mertens, 

Higg:ms, and McKenzie (1983) found a significant interection between age and workload on a 

battery of aviation-relevant cogn.t'ti.ve tasks (the Multiple Task Performance Battery). These tasks 

included measures of tracking, problem solving, visual target identification, and mental 

arithmetic. Workload was varied by requir'..ng time-shared performance of different 

combinations of these tasks. At all age levels, increasing workload caused decrements in 

performance but the amount of decrease was greater as age increased. These f'..ndings suggest 

that there may be age-related decrements in important flight related functions that would 

adversely affect performance but these decrements would only be revealed under moderate or 

18 
high workload level. In l! simulated operational situation, they suggest that a seconda.ry 

monitoring task may be useful in this regard. 

2.3.4 Assessing Pilot Performance 

The model presented in Figure 1 is aimed at conceptualizing the reiationship between 

pilot age and performance. A critical component of thls model is the proposal that pilot 

performance be assessed at three levels of abilities: 

• Domain-independent psychomotor, perceptual, and cognitive skills which are not 

specifically related to flying but are assumed to influence pilot performance. 

• Domain-dependent knowledge, judgment, and decision making related to piloting 

an aircraft. 

• Complex pilot performai!Cf' under varying flight conditions. 

The remainder of this section will review the available literature relevant to these three 

aspects of pilot performance. 

Domain-independent cognitive skills. Tl..1ere is a large literature on pilot selection and 

training, particularly in military contexts, that attempts to identify the perceptual, psychomotor, 

and cognitive skills presumed to be impor-.aru: to piloting performance. Many of these research 

programs have involved the construction of aviation-relevant cognitive skills batteries that are 

then validated against some criterion, most frequently success in flight training. Some of the 

most widely used batteries are the: 

(1) Basic Attributes Test Battery (BAT) (Carretta, 1987a). 

(2) Complex Cognitive Assessment Battery (CCAB) (Samet, Geiselman, 

Zajaczkowski, & Ma....'"Shall-Miles, 1986). 

(3) ~mputerized Personnel Aptitude Tester (MlCROPAT) (Bartram, 1986). 

(4) Naval Aviation Selection Test Battery (Damos & Gibb, 1986). 

{5) Simple Pottable Aviation-Relevant Test-Battery and Answer-scoring System 

(SPARTANS) (Stokes, Banich, & Elledge, 1988). 

(6) Unified Tri-Services Cognitive Performance Assessment Battery (lJTC-PAB} 

(Perez, Masculine, Ramsey, & Urban, 1987). 

(7) COGSCREE.."'i (Horst & Kay, 1991). 

Complete descriptions of each of these batteries can be found in Appendix A, as well as 

more detailed analysis of each battery· s reliability and validity. 

Since much of this research focuses on the co;Jstruction of pilot selection test batteries 

(e.g., BAT, MICROPAT), the results focus on the relationship between performance on tbe test 

battery and successful completion of flight training. There is much less data available 

concerning the relationship between performance on the battery and actual pilot performance, 

particularly in skilled pilots. Other hat".eries have been constructed to examine aviation-relevant 

19 
cognitive skills, but not for the purpose of pilot selection. These batteries (e.g., COGSCREEN, 

SPARTANS) are aimed at assessing the effects of aging or neurological impai.rment on these 

aviation-relevant skills. While not specifically constructed for pilots, there are also additionai 

batteries that assess similar types of cognitive skills (e.g., CCAB, UTC-PAB). 

This section of tlJe report wiJl summarize information available about the 

domain-independent cognitive skills assessed by these batteries and the degree to which they may 

be useful for detecting decrements in the cognitive performance of commercial airline pilots 

occurring from the effects of aging or otber impairments. This summary will also focus on tlJe 

utility of the test batteries as measures of pilot performance and specifically, the feasibility of 

using these batteries to measure the proficiency of pilots over age 60. 

Test development in aviation has been a long a.'ld difficult process. Guilford (1947) 

attributed tlJe failure to predict success in flight training to three factors: (1) the tests were not 

designed to predict flight performance, (2) motivational factors compensated for weakness m 

personality traits during training, and (3) subject biase' yielded inaccurate measures of tlJe 

personality trait under study. Some of these problems remain today, but tlJe problem of 

differentiating among experienced pilots is an even more dannting task. Identifying cognitive 

deficits in experienced pilots is a conceptually different enterpr'.tse from selecting candidates for 

flying training from an untrained population. 

Most attempts to improve tlJe predictive validity of aptitude test batteries have some 

inherent methodological problems. The test variables have often been related to global criterion 

performance measures in training such as graduation/elimination or composite flight grades. 

These performance criteria may obscure the components of skilled performance or behavioral 

attnbntes associated with the selected sub-tests. Hel:mrP.ich et al. (19%} pointed out that 

different combinations of predictors relate to quite different measures of performance at different 

points in time. 

Tests developed and valida~ ~ ;;elect candidates for flying training should nQt be used 

to measure performance of highly trained and skilled commercial pilots, ·without fu.tther 

validation on tlJe target population. There is often little correspondence between tests that have 

high validity for training criteria and those that predict success on tlJe job. For example. tests 

of cognitive ability that have been proven as good predictors of the ability to learn are not 

comparably good measures of skilled performance. 

The test population itself poses a methodological problem in validation. Most seiection 

batteries are developed for testing heterogeneous groups. Airline pilots are a very homogeneous 

population that severely restricts group variance and the ability of the tests to discriminate among 

subjects. 

Keeping these methodological issJ.res in mind, there are some general conclusions that 

result from tile review of these seven cognitive skills bar.eries. The purpose for the development 

of the test batteries was to eitlJer identify the least competency required for successfully 

completing basic flying training or to identify decrements in certain cognitive skills. The tests 

have research support for their utility to accomplish their intended p!L."PPSe5. 

20 
However little has been found to show that the tests can be er.ended to reliably 

discriminate among levels of perfvrmance for experienced pilots. None of the test batteries 

reviewed have been validated against the performance of experienced pilots nor have they been 

normed for pilots over age 60. Little aviation-specific normative data is presently available. 

These two steps need to be accomplished before it can be determined if the batteries are 

appropriate for determining an experienced pilots' fitness to fly. 

The sensitivity, specificity and utility of some of the batteries has been suggested from 

past research attempting to discriminate between experienced pilots and clinicaily impaired 

patients. However, this !<!view did not fmd the batteries performing at a level necessary to 

reliably classify normai p..."iJulations according to levels of cognitive functioning. 

Some of the batteries were intended to be used as adjuncts to existing selection 

procedures. This still appears to be the most promising approach ro using the batteries in 

discriminating among experienced paots. If a point-to-point theory has merit here, then the 

more realistic computer-assisted approach should have more predictive power than earlier 

cognitive test batteries. Point-to-point theory states that the more common points between the 

predictor and the criterion space, the higher the validity coefficient. The combination of 

computer-based cognitive skills tests with flight simulators and other relevant selection methods 

would be appropriate. It is also suggested that if a cognitive test battery is to be used the 

sub-tests should be selected on the basis of: (a) is the sub-test measuring a skill that is affected 

by aging, (b) is the skill being measured critical to the task, and (c) can the skill be compensated 

for by experience and training. 

Domain-dependent pilot knowledge. judgment and decision making. The types of pilot 

selection and evaluation batteries descnbed in the last section primarily assess 

domain-independent cognitive skills. As Bamch, Stokes, and Karol (1990) conclude, these 

batteries assess the kinds of skills most likely to be detrimentally affected by neuropsychological 

impairment or aging. These batteries were not designed to and do not measure pilot expertise. 

Comprehensive evaluation of pilot competence would not be complete v.ithout including some 

measures sensitive to the advantageous effects of increasing expertise on pilot performance. In 

particular, it appears necessary to assess aspe..."'!S of pilot knowledge, judgment, and decision 

making that may not be detrimentally affected by aging and may even improve with increasing 

expertise. As Mohler (1981) notes, pilot judgment and reasoning tend to be preserved in older 

pilots and may compensate for some of the age-related losses in domain-independent cognitive 

skills. 

Since there has been so little research done on indiddual aecision ma.lcing in pilots, there 

are really no well-developed, validated measures that assess this elusive aspect of pilot expertise. 

The two most promising experimental measures of pilot knowledge and judgment were recently 

developed by Stokes (1991) and his colleagues (Stokes, Belger, & Zhang, 1990) at the 

University of illinois Institute of AYi.ation. Each of these measures will be descn"bed below. 

However, it should be noted at the outset that while the measures seem to have much promise 

for assessing the inf111ence of expertise on pilots' knowledge and judgment, fu."ther development 

is required before they can be used with commercia! pilots. 
!, 

:· 

Expertise can be defined as a highly deve1oped repertoire of pattern-oriented 

representations (Chase & Simon, 1973). Thus, one aspect of expertise that may be important 

to assess is its impact on knowledge representations in long-term memory. The fust measure, 

"FLITESCRIPT", developed at the University of Illinois Institute of Aviation, was designed to 

index pilots' representations of situational knowledge in long-term memory. It is analogous to 

the well-known chess experiments conducted by DeGroot (1965) and Chase and Simon (1973). 

There are two versions of the FUTESCRIPT test, a recall version and a recognition version. 

The recall version cf the test involves reconstructing both randomized and coherent air traffic 

control (ATC) radio call sequerrces from memory. The recognition version requires listening 

to an ATC communication sequence and selecting the correct graphic depiction of the situation 

represented by the ATC communications from a set of alternatives. "By controlling out simple 

memory effects by reference to recall of the random sequences, the quality of reconstruction, 

we believe, must be influenced predominantly by the availability of appropriate situational 

'scripts' in the pilofs repertoire" (Stokes, Belger, & Zhang, 1990, p 19). These scripts are 

presumed to be present to a higher extent in experts than novices. Stokes' research has shown 

that this knowledge representation task is a better predictor of expert pilot performance than are 

cognitive skills tests (Stokes, Belger, & Zhang, 1990). While modifications will need to be 

made in the test, including some revisions of the scoring system, this appears to be a promising 

measure to assess a crucial aspect of pilot knowledge that may be affected by the development 

of expertise. 

Stokes and his colleagues have also developed z. microcomputer-based simulator for 

cockpit decision making training and research called "MIDIS". MIDIS was developed to 

investig;Ke "pilot judgment in uncertain high-risk multi-cue decision-making contexts" (Stokes, 

1991, p 1®). It is implemented on an mM PC/AT and has a full, high-fidelity instrument panel 

based on that of a Beech C23, a single engine fixed-gear aircraft. "The formal structure of 

MIDIS software is that of a 'graph traverser', in which the nodes of a branching structure are 

linked by transitional probabilities. Each node is a realistic in-flight situation. The system is 

thus capable of considerable flexibility and is able to simulate the chain of deteriorating 

circumstances which typifies the development of mishaps in time-critical decision-making 

contexts" (Stokes, 1991, p 107). At various points during the simulated flight, "subjects are 

allowed to enter what they consider to be the optimum action alternative and indicate their 

confidence in that alternative. The computer scores the correctness of the decision, the 

confidence rating, and the latency within which subjects chose the alternative" {Stokes, et al., 

1991, p 314). 

There are several attractive aspects of MIDIS as a measure of individual pilot decision 

making. First. it presents problems, embedded in a coherent flight mission and thus has high 

face validity. Second, the types of flight scenarios programmed into MIDIS span the breadth 

of different cognitive and attentional demands (Stokes, et al., 1991). Third, the MIDIS system 

permits testing under differing conditions of workload and stress. Thus, MIDIS presents 

exciting possibilities for the examination of the effects of aging and experience on pilot judgment 

in particular and pilot performance in general. However, further development of the system 

with respect to scenario development and decision rating is needed. The question of whether 

a system configured for a single engine aircraft is appropriate for commercial pilots also needs 

to be addressed. 

22 
Saner and Hoods (1991) review one other area of ;:viation research relevant to the issue 

of pilot expertise based on knowledge, judgment and decision making. This body of research 

has been loosely labeled "situation awareness". While this phenomenon is frequently cited in 

the aviation psychology literature as a critical aspect of pilot performance, there is no commonly 

accepted definition or agreed upon methodological approach for measur'.ng it. In its broadest 

sense situation awareness appears to bette pilot's complete, coherently organized, flight-relevant 

knowledge that is continually updated over time. It is the ability to not only assess the aircraft's 

current situatiox:. but also to project its future status (i.e., "being ahead of the plane") (Sarter & 

Woods, 1991). Previous attempts to measure situlltion awareness have frequently involved 

intrusive in-flight probing techniques, such as blocking out cockpit dispiays at random points 

during a simulated mission and requiring the pilot to answer questions about the flight situation 

at that moment in time (Endsley, 1988). 

Other studies have attempted to assess pilor situation awareness by asking the pilot 

questions during a post-flight debriefmg session. Both of these approaches are restricted in that 

they focus on isolated components of situational knowledge rather than awareness of the overall 

situation. They also require that the pilot answer questions based on memory for the flight 

situation. However, this memory is recalled without the aid of the complex dynamic flight 

situation. In other words, the pilot might have been aware of much more information during 

the actual flight context than he is able to recall out of that context. Therefore, Sarter and 

Woods (1991) propose that to adequately assess situation awareness, it is necessary to stage 

complex dynamic situations in high-fidelity, full-mission simulations that require retrieving and 

integrating competing information from a variety of sources over time. Pilots' situation 

awareness in these simulations should be assessed with less intrusive and artificial probing. For 

example, they suggest that the experimenter might play the role of air traffic controller, asking 

the pilot for information that would assess the pilot's implicit knowledge of the situation. Such 

an approach seems to be a promising way to examine how pilot experience influences 

flight-relevant knowledge and judgment. 

Complex pilot performance: Simulators and airline proficiency checks 

Simulator utilization. High fidelity simulators have assumed a colllllll'.nding role in the 

process by which Part 121 aircarriers train pilots, certify their competence, ant.i conduct periodic 

proficiency checks. Simulators provide numerous advantages when compared to conducting 

training and/or certification in actual aircraft. In addition to the obvious fact that the hourly cost 

of operating a simulator is much less than the cost of Ia..rge aircraft, other benefits include the 

opportUnity for more in-depth training, increased safety, fuel conservation, and reduced noise 

pollution. The framework ~rithin which simulator training and certification is conducted is the 

FAA National Simulator Evaluation Program. Before a simulator can be legally used to provide 

training or checking, it must be certified by the FAA. FAR Section 121.407 mandates that 

simulators must meet and maintain strict performance and functional characteristics. Guidelines 

for simulator certification are contained in FAA Advisory Circular 120-40A. Devices which 

resemble simulators in form and function but that for various reasons do not meet established 

criteria for legal certification are considered to be training devices. 

The utilization of simulators as part of the overall Age 60 project evaluation scheme, as 

discussed in the Age 60 performance evaluation model (described earlier in this review) has 

23 
several positive attributes that go beyond the scientific issues of determining complex pilot 

performance. Logistically, simulators are presently used by all of the Part 121 aircarriers. They 

are integral to the industry. Pilots are routinely scheduled to be trained and evaluated in 

simulators. As a consequence, pilots accept simulators and simulator results as a valid tool for 

assessing their abilities. It is an established part of their culture. 

Line-oriented flight training. Air carriers rely heavily on simulators for their flight 

training and proficiency checking. The commonly used simulator training process is known as 

Line-Oriented Flight Training (LOFT). LOFT train!ng uses a complete crew flying complete 

flight segments that contain the normal, abnormal, and emergency procedures that are 

representative of aircarrier flight operations. LOFT is the procedural backbone of the Part 121 

aircarrier training process. All LOFT must comply with the requirements delineated in FAR 

Section 121.409(b). Guidelines for the design and implementation of LOFT simulations are 

contained in FAA advisory Circular 120-35B. 

One aspect of LOFT that is of interest in the context of performance evaluation (as 

opposed to training) is the Line Operational Evaluation (LOE). This concept is tied to the FAA 

Advanced Qwilification Program (AQP). AQP is the subje...--t of the FAA proposed Special 

Federal A\'iation Regulation (SFAR) No. 58. LOE is designed to check both crew and 

individual competence. LOE dLffers from LOFT in a fundamental way. LOFT is "no-jeopardy" 

training, in that an instructor does not issue a passing or failing grade to an individual 

crewmember. Flawed decisions are considered as contributing to the learning process. 

Performance deficiencies encountered in a LOFT session are addressed with additional training. 

At the end of a LOFT session, the instructor certifies that the LOFT session has been completed. 

Line Operational Evaluation, howeYer, contains elements of "jeopa..'l\iy" . That is, the instructor 

conducts evaluation of both crew and individual competence and performance. The development 

of LOE and the specific methods by which evaluations will be conducted is tied to the AQP 

development effort, which is still unfolding. Hence, LOE represents a near-term potential rather 

than a current approach for performance evaluation. AQP guidelines call for the development 

of se&ler measures of performance by which individual performance can be quantified. 

Successful realization of these stated goals would be useful in the context of the needs of AGE 

6C project and bear watching. The use of a LOFT scenario with unexpected situations may hold 

more promise as a performance assessment tool tlian the use of a standard check-flight scenario. 

However this is complicated by the difficulty of assessing individual performance in a closly 

integrated crew environment (National Institute on Aging, 1981). 

Crew coordination evaluation. The issue of crew coordination as an influence on overall 

performance in the cockpit is beginning to have a major impact on air carrier flight training and 

evaluation. Cockpit Resource Management programs are beginning to be adapted in the 

industry. For example, Federal Express and Delta Airlines (and others) have CRM training 

programs designed to increase crew proficiency in the area of CRM. Crew coordiilation issues 

(Cockpit Resource Management) grow increasingly important with the increased role of the pilot 

as a system manager in the glass cockpit aircraft, such as the MD-11 and the Boeing 777. 

Recent work at NASA Ames has focused on the measurement of the level of crew coordination 

and the associated quality of decision-making in the cockpit using the NASA Boeing 727 

simulator located at Ames Research Center (Chidester, 1990; Mosier, 1991). Indications from 

that ongoing work suggest that the quality of information transfer among the flight crew predicts 

24 
both process (crew coordination) as well as operational (errors) criteria. Although tl'Js research 

focused on measures for assessing crew performance, it appears that some of the measures are 

equally applicable in assessing individual performance. Thus, the NASA work should have 

potential for providing scenario development guidelines and performance measurement 

techniques that could contribute to the Age 60 project. 

Performance assessment. Historically, there were two major approaches to the 

development of the criteria and means for the assessment of pilot performance; 1) qualitative 

evaluation of performance based primarily on instructor ratings and judgement, and 2) 

quantitative grading of performance based on numerical rating scales and recordings of pilot 

actions which reflect the quality of performance (Gerathewohl, 1978). Subjective ratings of 

pilots have inherent reliability problems. Currently, proficiency check methods used by Part 121 

aircarriers continue to be subjective in nature. The individual being evaluated flys a scenario 

that presents routine and non-routine situations. Response is observed by an check instructor 

and judged to be acceptable or non-acceptable. Thus the exercise is a pass/fail evaluation. 

Individuals who fail portions of the check flight are given the opportunity to re-fly the 

evaluation, with additional instruction if necessary. Although the qualitative assessment 

approach is subjective in nature and is subject to possible instructor bias, it is widely used today 

in the industry and has proven itself to be operationally sound. The development of automated, 

objective measures and techniques in an aircraft or simulator will require the development of 

performance standards and acceptable criteria (Institute of Medicine (1981). 

Simulator Training Methods Simulator training methods are well-developed and proven, 

however, techniques for quantifiable performance measurement in a simulator is less so. Most 

research along these lines is oriented to military related requirements, where performance 

requirements are imposed by the unique needs of combat (K..-uk, Regan, Beverley, & Lon.,aridge, 

1983). Although scientifically interesting, development in the military context is of little use in 

the Age 60 project. 

Research conducted at the U.S. Air Force Human Resources Laboratory at the WrightPatterson Air Force Base has focused considerable effort toward development and validation of 

aircrew performance measures (Waag, 1988). Development emphasis was placed on criterionreferenced or behavior.J objectives in an attempt to standardize the measurement of aircrew 

performance. Ultimately, a Performance Measurement System (PMS) was developed to 

interface and function with the C-5A aircraft flight simulator located at Altus AFB, Old'lhoma. 

PMS had the capability to measure specific parameters of interest and also to assess performance 

using a scoring algorithm. PMS was independent and autonomous to the host simulator, but 

interfaced to the extent necessa.ry to passively monitor all required I/0 signals, and to pass 

control and malfunction data to the host. 

Scenario development. There is a useful base of literature on the subject of the simuiator 

as a training device. Inseparable from the subject of simulator training is the issue of scenario 

development. That is, the scenario is the framework that drives the exercise. It is the key that 

elicits the actions and reactions that support the entire simulation event. Consequently, scenario 

development is a critical first step in preparing for any intended simulator exercise, be it general 

training, specific type training, performance evaluation of individuals, or observation of crew 

coordination and management. Scenario development must reflect training objectives and must 

25 
elicit desired results. Feedback from students to instructors and scenario developers is important 

(Gregorich, 1991). An exhaustive analysis of simulator requirements, piloting tasks, and task 

perfol1Ilai1Cl: requirements was conducted under FAA sponsorship (Guilliom et al, 1985). This 

analysis developed an overall approach for simulator based training and checking. The resulting 

approach was termed Airman Certification System Development (ACSD). Of particular interest 

is the delineation within ACSD of Type A objectives and Type B objectives. These are defmed 

as Type A objectives related to proficiency in fme motor control of the airplane and its systems 

or Type B objectives related to proficiency in cognitive-procedural aspects of performance during 

which only basic control skills are required. 

2.4 Conclusions and Recommendations 

In 1981, the National Institute on Aging panel was not able to identify a medical or 

performance appraisal system that e0uld identify those pilots who would pose a safety hazard 

because of early or impending deterioration in health or performance, and therefore they 

recommended that the Age 60 Rnle be retained. However, they also made two major 

recommendations: 

• that more study and development be carried out to develop quantifiable, objective 

criteria for measuring pilot performance. 

• that systematic collection of performance data needed to further evaluate the Age 

60 Rnle be carried out. 

Ten years later, despite increased research attention having been paid to these issues, 

these two recommendations have not been sufficiently implemented. There remains a pressing 

need for a comprehensive, objective system for evaluating pilot performance. Once such a 

system has been developed, it is also critical that longitudinal analysis of the effects of aging on 

pilot performance be carried out. These are the major goals of Tasks 4 and 5 of the present 

project. Task 4 is aimed at development of a methodology to quantitatively and objectively 

tiSseSS an individual pilot's performance. Task 5 is aimed at planning a longitudinal examination 

of the effects of aging on pilot performance. The information obtained from this project should 

aid understanding about tbe effects of increasing age and experience on pilot performance. It 

should also provide additional information about the feasibility, reliability, and validity of this 

type of individual performance assessment as an alternative to the Age 60 Rule. However, a 

definitive stance on the Age 60 Rule will also require consideration of pertinent medical, 

economic, and political issues beyond the scope of the present tasks. 

2.4.1 Criteria for Developing and Evaluating a Performance Assessment Methodology 

A performance assessment measure of pilot proficiency that could eventually replace the 

existing Age 60 Rule should not only be judged against the standard psychometric criteria of 

reliability, sensitivity, specificity, and both construct and criterion validity, but it should also be 

developed in response to the following criteria: 

• Is it measuring a skill that is affected by aging? 

• Is it measuring a skill that is affected by experience? 

26 
• Is the skill being measured critical to the task of flying an aircraft? 

Specifically, several measures at each of these three levels of performance should be 

investigated: 

• Domain-independent psychomotor, perceptual, and cognitive skills which are not 

specifically related to flying but are assumed to influence pilot performance. 

These are the types of skills which are most likely to be detrimentally a..ffected by 

aging or neurological impairment. 

• Domain-dependent knowledge, judgment, and decision making related to piloting 

an aircraft. These are abilities that may be enhanced as a result of increased 

experience. 

• Complex pilot performance in a simulator under varying flight conditions. 

In order to insure aviation safety, pilot proficiency should also be tested under a range 

of flying conditions. Performance of complex maneuvers under stress or in novel situations is 

more likely to be impaired in older pilots than well-learned familiar tasks (Natioi'al Institute on 

Aging, 1981). For example, age-related declines in basic skills could be compensated for by 

increases in pilot knowledge and judgment that occur as pilots' expertise increases. However, 

increased knowledge may only compensate for declining skills under ideal or routine task 

conditions. There may be age-related decrements in important flight-related functions that would 

adversely affect performance that would only be revealed under moderate or high workload 

level. 

2.4.2 Longitudinal Examination of Aging and Pilot Performance 

This section of the report reviewed the available scientific literature bearing on the 

influence of aging on pilot performance. Unfortunately, quantitative, objective data on the flight 

performance of pilots varying in age do not exist. The available data on laboratory-based 

performance i.ests of basic perceptual, psychomotor, and cognitive skills suggests that >here are 

statistical decrements in performance with age. However, while average performance on these 

performance measures decreases with age, variability in performance increases with increasing 

age. Most importantly. these laboratory-based performance tests have not yet been demonstrated 

to be predictors of piloting performance. 

There are also very few studies that have examined me effects of aging on the 

performance of complex professional skills and even fewer studies that examine the contribution 

of practice or experience to the performance of these complex skills. However, the availabl:: 

literature suggests that, on some complex tasks, older adults perform as well as younger adults 

even though the older adults exhibit age-related declines on the component psychological skills 

that contribute to the complex behavior on which they are successful. In other words, there 

appears to be compensation for declines in the basic skills. Of course this compensation is only 

possible when the older adult has developed expertise in the complex task. For example, it is 

possible that domain-dependent knowledge and judgment related to flying may compensate for 

declines in the older pilot's processing speed and working memory. 

27 
Because of the relatively small number of studies that have directly investigated the 

effects of aging on specific aspects of pilot performance, there is a great need for systematic 

investigation of multiple aspects of pilot performance across a wide age span. In order for this 

investigation to be most fruitful, it should be guided by a coherent conceptual framework. The 

framework proposed for the present project is a model of aging and pilot performance that is 

similar to the decrement with compensation models that have been developed in the area of 

cognitive aging and that have successfully contributed to understanding the concept of "~pertise. 

Key questions that should be add.-essed are: 

• With increasing age are there declines in performance on measuresof basic skills, 

pilot knowledge and decision making, or simulated flying performance? At what 

age do the declines occur? How much individual variation characterizes these age 

changes? 

• Are there increments in performance on any of the above measures associated 

either with pilots' increasing age or experience? 

• Are declines in some aspects of pilot performance being compensated for by 

increments in other aspects of pilot performance? 

In addition, the little available data on the effects of aging on pilot performance is 

predominantly cross-sectional. That is, the studies have compared (at a single point in time) 

groups of pilots that vary in age, rather than repeatedly testing the same group of pilots as they 

age {a longitudinal design). While there are interpretation difficulties with both of these simple 

research designs, a reliance on cross-sectional data is particularly difficult to interpret because 

different age cohorts of pilots can vary on a number of dimensions besides age (such as health, 

education, and experience). Therefore, future investigations of the effects of aging on pilot 

performance should include a longitudinal component. 

The Naticnal Institute on Aging (1981) report on the experienced pilot includes a 

proposal for a sequential longitudinal data collection strategy that could produce information 

related to aging and pilot proficiency that could serve as a basis for modifying the Age 60 Rule. 

This strategy assumes that state-of-the-an medical and performance testing procedures have been 

validated. This strategy also assumes that pilots who participate in the program would be 

allowed to fly after age 60 under very selected conditions and with strict monitoring. The data 

collection strategy could be implemented without this condition (studying pilots only up to age 

60), but this would limit the conclusions that could serve as a basis for modifying the Age 60 

Rule. Key components of this strategy are as follows: 

(1) Pilots who wish to continue flying beyond age 59 would indicate this preference 

at age 55. These pilots would then undergo four annual comprehensive medical 

and performance evaluations and pilot proficiency tests prior to age 60 and on an 

anm1al basis after that. 

(2) This anm1al comprehensive testing would also be conducted on random samples 

of volunteer younger pilots (age range 40 to 55}. These multiple cohort groups 

would allow for baseline performance data for younger pilots and a comparison 

28 
for the older group. Performance measurements collected on younger pilots as 

a component of this research study would not be used to determine current 

eligibility to continue flying. 

If this approach was implemented, useful longitudinal data would accumulate within a 

decade. This data would be usef:Il in detecting population trends among pilots as a group. It 

would also determine whether it is feasible to use an individual pilot's performance trends over 

time to predict that pilot's future performance ability. This would provide a sound basis on 

which to draw conclusions about the influence of aging on pilot performance and could serve 

as a basis for a decision on modification of the Age 60 Rule. 

3. THE INFLUENCE OF AGE, TOTAL FLIGHT TIME, RECENT FLIGHT TIME 

ON Pll..OT ACCIDENT RATES 

3.1 Specific Aims 

Part II of the report will discuss attempts to relate pararr-ters such as age and flight time 

to the probability of an accident. The avruJabJe studies (Golaszweski, 1983; Office of 

Technology Report, 1990; Guide & Gibson, 1991) primarily use information from the NTSB 

accident and FAA medical databases. The most ambitious and most cited of these studies is that 

of Golaszewski (1983). First, the design and re.,;ults of the Golaszewski study will be reviewed, 

paying particular attention to the methodology and areas for improvement. Part of the Age 60 

project effort involves the development of a Consolidat::d Database (CDB) that incorporates 

information from several historic NTSB and FAA databases (including the NTSB accident and 

FAA medical databases) that record information about pilot performance and age. The CDB 

provides relationships among the databases that were unavailable to Golaszewski. Second, ways 

to take advantage of the CDB in the improvement of Golaszewski's design will be discussed. 

Finally, the literature pertinent to the relationshlp between accidents and medical condition will 

be reviewed along with ways in which the CDR can be used to examine these issues. 

3.2 Background Literature 

3.2.1 Description of Golaszewski Study 

In 1983 Richard Gola.szewski, working for Acumenics Research and Technology, Inc., 

submitted th.e paper "The influence of total fight time, recent flight time and age on pilot 

accident rates" to the Transportation Systems Center and the FAA. Golaszewski aggregated. data 

for the years 1976 to 1980 from two databases, the "Medical History File" (FAA Medical 

Certification) and the "National Transportation Safety Board (NTSB) Accident". 

The NTSB Accident Records database consists of data from detailed reports of all 

aviation accidents investigated by the NTSB and (some) self-reported aviation incidents. The 

CAIS medical database consists of data collected from m~ical examinations of all licensed pilots 

who take the examinations for medical certificates that fall into three classes: 

• A Class I medical certificate which must be renewed every six months and is 

required of all air transport pilots; 

29 
• A Class n certificate which must be renewed yearly and is required of all 

commercial pilots; and 

• A Class m medical certificate which must be renewed every 2 years and is 

require of all private and student pilots. 

Note that many employers of commercial pilots require their pilots to have Class I 

licenses (for example, according to Table IV.N on page 39 of the 1991) Aeromedical 

Certification Statistical Handbook, only 41% (59,259 of 145,599) flrst class airmen are 

employed by all airlines). In addition, a pilot may use an out-of-date certificate in place of one 

from a lower class, provided the certificate is not out-of-date for the lower class. 

The two databases give the age of the pilots, "recent" flight time, and total flight time. 

Golaszewski combined the information from the two databases to estimate the accident rate as 

a functiQn of the factorial combination of age, recent flight, and total flight time. The data were 

separately analy:zeG for two distinct groups - all pilots and only Class III pilots. The 

information utilized in the study are described in more detail below. 

Golaszewski used the following categories: 

• Age: 17-19, 20-29, 30-39, 40-49, 50-59, 60-69, and 70 & over. 

• Total flight time: 0-HlOhours, 101-500hours, 501-1000hours, 1001-5000hours, 

5001 hours & over. 

Recent flight time: 0-20 hours, 21-50 hours, 51-100 hours, 101-400 hours, 401 

hours & over. 

In general, one can calculate accident rates (per 100,000 hours of flight) for the various 

categories by computing the number of accidents and the number of hours flown in each 

category. Golaszewski obtained the age, recent flight time (in the last 90 days), and total flight 

time for all makes and models of airplanes for the pilots involved in accidents from the NTSB 

accident database. He estimated the exposure (hou...-s of flight) of the various groups of pilots 

by examining the Medical History File. This flle contained the medical reports of all licensed 

pilots. Reports for Class I pilots are flled every six months, for Class ll pilots every year, and 

tor Class ill fliers every 2 years. T11ese reports include information on total hours flown and 

recent hours flown (in the last six months), and the date of birth and date of medical examination 

for calculating age. 

Golaszewski defined "recent flight time" as the amount of time flown by the pilot in the 

previous 12 months. The NTSB Accident database records the pilot's flight time in the previous 

90 days. Recent flight time for these pilots was estimated by multiplying this number by 4. The 

CAIS medical database records the number of hours flown in the preceding six months. 

Golaszewski "normalized" the recent flight hours by taking into account the frequency with 

which pilots in a given class are examined and using the factors shown below: 

30 
Class I - 1 

Class II -2 

Class m -4 

Given the above data, Golaszewski plotted accident ratt-.s in various ways. The graphs 

he presented are included in Appendix B. After visual examination of these graphs, Golaszewski 

reached a numi>er of conclusions, summarized below: (see pp 23-24 of Golaszewski, 1983). 

(1) Accident rates are inversely proportional to recent flight time. 

(2) For low amounts of recent flight time, older pilots have more accidents than 

younger pilots, and the converse is true for higher amounts of recent flight time. 

(3) When recent flight time is less than 50 hours, Class I and II pilots have more 

accidents than Class ill pilots. 

(4) Accident rates are inversely proportional to total flight time. 

(5) Independent of total flight time, Class m pilots have more accidents. 

(6) Among Class I and II pilots with 101 to 5000 total hours of flight, older pilots 

have more accidents than younger ones. 

(7) The older the Class ill pilot, the less likely an accident until age 60, when 

accidents become more likely. 

(8) Pilots with over 1000 total flight hours and less than 50 recent flight hours have 

the most accidents, while pilots with over 1000 total hours and more than 50 

recent hours have the fewest accidents. 

(9} For Class ill pilots with low total flight time, if they have fewer than 50 recent 

flight hours then accident rates increase w1th age, and the converse is true if they 

have more than 50 recent flight hours. 

(10) For pilots with more than 50 recent flight hours and less than 1000 total flight 

· hours, accident rates decrease with age, while the converse is true for pilots with 

less than 50 recent flight hours and less than 1000 total flight hours. 

3.2.2 Drawbacks to Golaszewski Design 

(A) Pilot Class is the wrong independent variable. The Age 60 Rule is part of the Part 

121 FAR regulations (121.383c) which pertain to scheduled air carriers, yet Golaszewski 

induded in the study general aviation accidents which did not involve scheduled air carriers. 

Although the accident rates are based on accidents other than those of scheduled air carriers, 

they are used to make inferences about accidents of scheduled air carriers as a function of age. 

To further complicate matt.ers, the NTSB classifies accidents by kind of flight: 

31 
• Part 121 - scheduled air carrier 

e Part 135 -- commuter and air taxi, and 

• · Part 91 --general aviation. 

Tne medical database classifies pilots by class (I, II, and ill). These two sets of 

categories do not exactly correspond. For eAlmlple, pilots employed by scheduled airlines must 

have a Class I medical certificate but not conversely. A pilot employed by m air taxi need only 

have a Class II medical certificate, but the pilot's employer may require the pilot to have a Class 

I medical certificate. As a point of fact, a private pilot can have a Ciass I medical certificate. 

The lack of exact correspondence between medical certificate and the nature of the flight 

undermines the relevance of the Golaszewski study data to the Age 60 Rule. 

Further, because Class I pilots are involved in so few accidents, Golaszewski did not 

compute accident rates for Class I pilots alone. The rarity of accidents involving Class I pilots 

strongly suggests that the distribution of such accidents across the various categories will be 

different than for the groups of pilots smdied by Golaszewski - Class ill pilots alone and all 

pilots. The Part 121 pilots accumulate a substantial number of night hours but contribute 

(proportionately) very few accidents. That is, they contribute substantially to the denominator 

of the ratio for accident rate but hardly at all to the numerator. It is likely that this contribution 

changes as a function of age, so that the apparent effects of age in the Golaszewski data may be 

an llrtifact of the way accident rates are computed, i.e., they may reflect differences in flight 

hours accumulated by Class I pilots rather than differences in the likelihood of accidents. 

(B) Golaszewski included accidents by pilots whose meclical certificates bad lapsed. 

Thus, their flight hours are not recorded in the CAIS medical database, and these pilots only 

contribute to the numerators of the accident rates. Any systematic bias in the distribution cf 

these pilots by age would distort the corresponding accident rates. For example, younger pilots 

may be more likely to have lapsed certificates, thus inflating their accident rates. 

(C) Golaszewski performed no statistical analyses on his data, arguing (Golaszewski, 

1983, p. 6): 

"the data used in the present study are not amenable to analysis using parametric 

statistical techniques. '>uch techniques are reievant when investigl'ting the 

reliability of sample data to accurately portray normally distributed continuous 

population parameters. In the present case, the d&ta used in this study represent 

the entire population of pilots and the entire pop-ul:Ition of aviation accidents ... the 

most important measu..-e of the reliability of the results presented in this report is 

whether the underlying data are accurate." 

This mixes two arguments: (1) That the data are not normally distributed; and (2) that the data 

constitute the whole population. 

First, there are statistical tests (e.g., the ANOVA) that assume normality but are robust 

with respect to mild departures from normality. Further, the data are likely to be normally 

32 
distributed. A member of any particular group of pilots has a given probability of being in an 

accident. Each observation from that group constitutes an independent Bernoulli trial. Because 

the observations are ind~ndent, the number of accidents for the given group is binomially 

distributed. The normal distribution is a good approximation of the binomial when the mean ;s 

larger than 3 standard deviations and at least 3 standard deviations less than the number of 

observations (Drake, 1967). Golaszewski's data satisfy this criterion. Thus the accident rates 

are approximately normally distributed. 

Second, whether the data constitute the whole population depends on the inferences 

desired. We want to make inferences about the population of all possible flights. In particular, 

we want to infer the probability of an accident as a function of age in the population of all 

possible flights. The data collecred by Golaszewski can indeed be used to make such inferences. 

To understand this, we consider the logic of statistical testing in more detail for the example of 

comparing the probabilities of an accident for two populations. We estimate the probability of 

an accident in each population by drawing a sample of observations from each population and 

computing the proportion of observations in each sample that are accidents. We then statistically 

test whether the two proportions differ sufficiently to conclude that it is unreasonable to assume 

that the probability of an accident is the same for both populations. If it is unreast)nable to 

assume equal probabilities, then we expect a similar difference in the same direction when we 

repeat the experiment. If it is not unreasonable to assume equal probabilities we have no 

statistical evidence for predicting the outcome of a repetition of the experiment. Golaszewski 

presented data from an experiment which was more elaborate (and very large) but peti"ectiy 

analogous to the above example. Would the same results occur when we repeat the experiment 

(the following year)? 

For example, points 9 and 10 in the above summary of Golaszewski's conclusions suggest 

a triple interaction among age, recent flight time, and total flight time. Without a statistical 

analysis we do not know whether to expect that to reoccur. 

(D) The Age 60 Rule represents a sharp cutoff, presumably reflecting some relatively 

dramatic change in the pilots as they approach 60 years. The ten year age categories used by 

Golaszewski a,.-e too large to get a clear picture of such a change. A more fine grained analysis, 

i.e., by year, would be more appropriate. 

(E) As with any study of the effects of age, the outcome of the Golaszewski study may 

be pecn1iar to the particular age cohorts chosen. Replicating the study for a variety of cohorts 

should be performed to assess whether the same conclusions would be obtained. 

(F) Another lirrtitation of the Golaszewski study is that it considers the exposure to risk 

of accident solely on the basis of hours flown. Many sources indicate that most airplane 

accidents occur during takeoff or landing phase. Thus it may be more appropriate to compute 

the rate of accidents per number of lanrlings rather than per number of flight hours. It is quite 

likely that the data are systematically biased so that older airline pilots have fewer landings per 

hour flown. It could be argued that the older the pilot, the higher the seniority, the more likely 

the pilot gets the choice of flights, the more likely the pilot chooses a long flight, and the more 

likely the older pilot has fewer landings per flight hour. Assuming that this argument is correct, 

33 
using hours of flight for the denominator foe accident rate systematically deflates the accident 

rate for older pilots. 

3.2.3 Other Studies of Age and Accidents 

To the best of our knowledge, there are only two other major studies similar to 

Golaszewski's: an OTA report (1990) and a report presented at the 1991 meeting of the Human 

Factors Society by Guide and Gibson (1991) . 

The Office ofTecbno!ogy Assessment (OTA) report. The OTA report presents graphs 

of accident rates of Class I & II pilots as a function of (ten-year intervals of) age provided by 

Dr. Charles Billings, NASA Ames Research Center. The figures state that the data are from 

"Golaszewski 1983, and NTSB. 1990, • but no further information is provided. Conclusions 

from these data are difficult to substantiate, because it is unclear how the data are calculated and 

no statistical analyses were performed on the data. NeverJleless, the OTA drew the following 

major conclusions: 

• For Class I & II pilots with more than 1000 hours flight experience and more 

than 50 hours recent flight experience, •an age effect is present and is beneficial 

until 50, afrer which rates increase" (Figure 1). 

• For Class I & II pilots "an increase in accident rates with increasing age is seen 

after age 39 in pilots with 501-1000 hr, after age 49 in pilots with 1001-5000hr, 

and after age 59 in pilots with over 5000 hr" (Figure 2). 

• For Class I & II pilots "who fly more than 100 hr/yr, increasing age (and 

probably total experience) and increased recent flying time both have beneficial 

effects. After age 60, accident rates increase even if pilots continue to fly over 

400 hours per year" (Figure 3). 

These conclusions do not bear directly on the Age 60 Rule since they are hased upon 

both Chss I and II pilots. To get such e\<idence, it would be necessary to consider only those 

data for pilots of Part 121 aircraft. 

The Guide and Gllison report. The Guide and Gibson study provides few specific 

details of their design. but it is similar to that of Golaszewski. They obtained their data for the 

years 1982 through 1988 from four sources: 

• NTSB Accident datahllse; 

• Aircraft Owners and Pilots f..ssociation Air Safety Data Base (AOPA); 

• FAA Statistical Handbook on Aviation (providing the distnlmtion of pilots by age 

and type of license); and 

34 
• COMSIS Research Corporation (providing the flight hour distribution for Class 

I, II, and ill pilots in 5 year age groups, as compiled from FAA pilot medical 

records). 

They used 5-year age categories starting -with 20-24 and finishing with 55-59. Tney 

computed accident rates in two ways: (1) per number of active pilots and (2) per number of 

annual hours flown. All analyses depend upon visually examining four figures displaying the 

above data; no statistical analyses were reported. 

Three of the figures display the accidents per number of active pilots for air transport 

pilots, for commercial pilots, and for private pilots, respectively. Exposure was not accounted 

for in these figures. The fourth figure displays accidents per hours flown for Part 135 operators 

as a function of age and of hours flown in the preceding year (1 01 - 400 versus > 400), although 

the data for the 20-24 year age group is omitted for some unstated reason. There appear to be 

no discernible trends as a function of age in the data in the fourth figure. Indeed, differences 

among the various age groups appear minimal, however, this is difficult to veri.fy without 

statistical res+.s. For each of the seven age groups displayed, the pilots with more than 400 

recent flight hours have an accident rate roughly one third that :Jf the pilots with 101-400 recent 

flight hours. The probability of this happening by chance is less than 0.01 (applying the sign 

test, with N =7). 

3.2.4 Replicating Golaszewski 

Despite the limitations of Golaszewski's study, the general design has merit and deserves 

replication. The design could be replicated using data from the same period, 1976-1980, ·with 

design improvements incorporated based upon the criticisms described above so that reasonable 

interpretations of the data could be made relative to the Age 60 Rule. The design could be also 

be replicated using data from different periods, e.g., 1985-1989, and a determination made 

whether the same outcomes would occur with different age cohorts. Various ways to improve 

upon Golaszewski's work are discussed below. 

Use statistical analyses. Foremost, the data should be analyzed statistically so that 

reasonable inferences can be made from the data. A number of statistical approaches are 

appropriate to this type of data analyses and the recommendations include: analysis of variance 

(A."iOVA), regression, and chi square. Whereas the A.N'OV A and regression both assume 

normality, the chi square test is a non-parametric test which does not make any assumptions 

about the distribution of the date .. -\5 noted above, it is likely that accident rates are normally 

distributed and thus amenable to analysis using the first two approaches. 

ANOV A and regression share the same Ui1derlying model and assumptions. Thus, either 

apprc>ach can be used to answer a given question, although some questions are more natural for 

a giveu app:oach, and the comments about A."\0\'A that follow apply to linear regression as 

welL 

Initially, it appears that the At"OVA could be applied to a completely crossed, three 

factor design whose factors are age, recent flight time, and total flight time. However. in such 

a design C'nly one observation per cell is available and the triple interaction of the factors could 

35 
not be tested. One way around this problem involves segregating the data by the third of a year 

(grouping months 1, 4, 7 and 10; months 2, 5, 8, and 11; and months 3, 6, 9, and 12) before 

computing accident rates. Then three observations per cell (year) are available, allowing the 

computation of an error term for the analysis. The ANOV A has the advantage of being able to 

answer specific questions about trends in the data. For example, the question of whether a 

specific age group has a different accident rate than the remaining groups could be posed. 

The chi square analysis answers questions about tee frequencies of occurrence in various 

categories. Accidents could be categorized and the chi square applied, however, the categories 

must be exhaustive. For example, to compare the number of flights with accidents as a function 

of age, the number of flights without accidents also must be tabulated and this data are not 

readily available. The chi square can be used to answer subsidiary questions about, for example, 

the distribution of the kind of accident as a function of age, class of medical certificate, etc. 

Use smaller, lllOre precise designs. Smaller designs that reach more definitive but 

limited conclusions are better than larger designs that reach more general but equivocal 

conclusions. Thus, grouping together all pilots and all accidents leads to only tentative 

conclusions. In the present situation, the analyses should bear more directly on the Age 60 

Rule. The focus could be on Part 121 accidents only, which directly relates to the question, or 

on Class ill pilots and Part 91 accidents involving Class ill pilots to obtain a view of the general 

effects of age on accident rate. The data from Part 121 accidents may be too sparse for good 

statistical inferences. On the other hand, including the data from Class m pilots leads to 

analyses that are only indirectly relevant to the Age 60 Rule. In such a situation, it is 

appropriate to converge on the relevant question by using both ai)proaches, with reasonable 

expectations of arriving at meaningful conclusions. 

When examining data for other classes or flying types (e.g., Class ill pilots and Part 91 

accidents or Class II and Part 135 accidents}, the data should be selected so that the population 

is reasonably comparable to pilots involved in Part 121 accider..ts. Golaszewski's data suggest 

a triple interaction of age, recent flight time, and total flight time. Thus, th.: analysis should 

restrict the population to pilots with high recent flight time (e.g., at least 200 hours) and high 

total flight time (e.g., at least 2000 hours}, both of which are characteristic of professional 

airline pilots. 

To get a clearer picture of the age effect, age should be categorized by finer intervals, 

e.g., one or two years, instead of the 10 year intervals used by Golaszewski. At the same time, 

to examine cohort effects, the data shoul" be segregated by the year of the accident, rather than 

grouping together data for a.::cidents occurring during some multiple-year interval. 

For these data it is quite appropriate to use a completely crossed four-factor {age by 

recent-flight by total-flight by year-of-accident) A..'~ OVA design. Planned comparisons for linear 

and quadratic trends can be used to test whether accident rate is a U-shaped function of age, an 

effect suggested by Golaszewski's study. 

The results of the above analysis of Part 91 accidents are not fully generalizable to Part 

121 accidents. The two populations of pilots differ in unknown ways. Nevertheless, the 

analysis of Part 91 accidents would provide information about the effects on aviation accidents 

36 
of aging in a less select population. Further, it would provide data for accidents by pilots older 

than 60 where the Part 121 accidents is una"lailable. If accident rates increase at some point in 

time as one ages, the data from the analysis of Part 91 and 135 accidents should reflect this, 

especially when age is examined year by year. 

Focusing on Part 121 accidents requires the identification of Part 121 accidents and 

requires good estimates of the exposure of pilots to these accidents. The NTSB Accident 

database directly identifies Part 121 accidents, but estimating exposure is more problematic. In 

addition to recording the number of hours flown, the FAA medical database records the pilot's 

employer, the pilot's job, and the kind of flying (solely business, solely pleasure, or both). 

Obtaining this information for ail Class I pilots (the only pilots involved in Part 121 accidents), 

the number of hours of scheduled airline flights can be estimated. 

Applying the ANOVA to Part 121 accidents exactly as recommended fer Part 91 

accidents suffers from the dtawback that Part 121 accidents are rare, making the data sparse. 

This can be remedied by using 2-year intervals for age and by ignoring the year in which the 

accident occurred. Of course, this means that the data cannot be used to test the effect of 

cohort. Because the Age 60 Rule is predicated on changes occurring around 60 years, a planned 

comparison can be used to test the 1:1.ccident rate of the oldest age group (ages 59-60) against the 

remaining groups. This test both asks the right question and is statistically powerful. 

3.2.5 Beyond Golaszewski 

The above discussion is constrained by the kinds of data available in the present 

databases. The availability of additional information could provide more usef..U analysis m'ldeled 

after that of Golaszewski. First, the data could be improved by using the same definition of 

"recent flight time" in the two databases. Because it is easier to recollect more recent events, 

the definition of "recent" as the last 90 days wouid be preferred. Second, pilots shouid 

separately report the amount of time engaged in the three categories (Part 121, Part 91, Part 

135) of flying. This would avoid having to deal with the class of the medical certificate to 

estimate flight time and would yield much more precise estimates of accident rates. Thi..""d, the 

number of hours spent flying various makes and models of airplanes shouid be recorded in the 

medical database. These additional data would allow the analyses of the data that better discount 

factors not directly relatee to age. Finally, the number of landings should be recorded. This 

would allow investigators to study whether number of landings is a more appropriate variable 

than number of hours in computing accident rates. 

Given the information in the two primary databases, what other kinds of a11alyses can be 

done? Forming a good estimate of exposure constitutes the toughest problem in the Golaszewski 

design. Analyses that avoid this problem cannot deal directly with the question of accident rate 

as a function of age, but they still illuminate the question. Based upon the information in the 

NTS:S Accident database, accidents could be catego~..zed in various ways. This would allow a 

determination of whether the frequency of accidents in the various categories differ as a function 

of age. The chi square would be qmte appropriate for this analysis and the population of all 

accidents would be exhaustively partitioned into various categories. For example, whether the 

time of day of the accident varied as a function of age would be of interest. Then the chi square 

could be applied to a two factor ("time-of-day" by "age") frequency table of all accidents. In 

37 
a similar fashion, the analysis would focus on the information available in the CAIS medical 

database and ask questions about the trends in the various recorded medical variables. In some 

cases, ANOV A would be appropriate for the resulting data, in other cases the chi square would 

be appropriate. 

The consolidated database (CDB) also provides the ability to answer questions about the 

integrity of the data. For example, the flight time recorded in the NTSB Accident database is 

based upon log entries, wbereas the flight time recorded in the CAIS medical database is usually 

based upon the pilots' recollections. Are the latter data less reliable? Comparing the data from 

the two databases for the same pilots would answer this question. 

3.2.6 Relationships among Medical Variables. Age. and Pilot Accidents 

The CAIS medical database records the results of the periodic medical examinations 

required to maintain Class I, II, or ill certification. The medical information in these records 

includes the following: 

• Height and weight. 

• Cardiovascular, including blood pressure, pulse at rest and after exercise, and 

results of electrocardiogram. 

• Vision, including near and distant vision in each hemisphere, both corrected and 

uncorrected, color vision, and field of vision. 

• Hearing, including for each ear testing by whisper and by audiometer at 

frequencies from 500 to 4000 hz. 

• Results of test for albumin and sugar in urine. 

• Physical abnormalities discovered during the examination. 

• Medical pathologies from correspondence, from medical records, from remarks 

by applicant, or from AME's entries on application form. 

• Answers to 14 YesfNo questions from medical history taken during the 

examination. 

Brief S1liiiJmll'y of prior literature. The increased likelihood of sudden incapacitation 

with age partially constituted the original impetus for the Age 60 Rule (Lane, 1971). 

Consequently, there has been a great deal of research on those factors that lead to sudden 

incapacitation in pilots ("acute coronary events ... , new onset idiopathic epilepsy, and 

physiological problems including spatial disorientation, hypoxia, ... ") (Froom, Benbassat, Gorss, 

Ribak, & Lewis, 1988), even though a number of studies show that sudden incapacitation is very 

unlikely to cause an aviation accident {Booze, 1989; Martin-Saint-Laurent, Lavernhe, Casano, 

& Simkoff, 1990; Mohler & Booze, 1978; Rayman, 1973). Those studies that have considered 

the age of the pilot in conjunction with medical variables have mainly focused on cardiovascular 

38 
fitness. Bruce and Fisher (1987) suggest older pilots could be screened for cardiovascular risk. 

They readily identified men whose profile indicated either high or low risk for coronary disease. 

In a five year follow-up, 55-59 year olds with a high-risk profile had a mortality rate six times 

that of 60-64 year olds with a low-risk profile (34.2% vers-JS 5.8%). 

A number of authors have examined the effect of age on the pilot's vision or hearing. 

In these studies, with minor exceptions having to do with specific cotiditions, as pilot age 

increases, visual acuity decreases (Baisden & Monaco, 1983; Vola, Cornu, Carruel, Gastaud, 

& Leid, 1983), speed of accommodation increases (Elsworth, Larry & Malmstron, 1986; Temme 

& Morris, 1989), and the speed of shifting of gaze increases (Morris & Temme, 1%!:1). The 

hearing losses in pilots is mostly a function of exposure to noise rather than of age (Fitzpatrick, 

1988). 

An annotated topical bibliography of prior literature linking key medical variables with 

age and pilot performance is presented in Appendix C. For most articles, the annotation consists 

primarily of a condensation of the abstract of the article. 

3.2.7 Improved Ways to Bprnine Relationships among Medical Variables. A!!e. and Pilot 

Performance 

The CDB provides medical information about all pilots, both those involved in accidents 

and those who are not. Thus, how well the medical variables predict an accident as a function 

of age, exposure, etc. can be tested. Such a prediction depends not only on knowing the 

characteristics of pilots involved in accidents but also on knowing the characteristics of pilots 

not involved in accidents. 

The CDB records the resnlts of tests of cardiovascnlar fitness, hearing, and vision. The 

predictive value of each of these variables could be tested as follows. First, determine the 

correlation of each measure with age. Then use logistic regression to determine how well the 

measure predicts accidents. For example, the correlation of cardiovascular fitness with age could 

be determined for this population. Then logistic regression can be used to determine how well 

age, exposure, and C2I'diovascular fitness predict an accident for each Class of pilot. This would 

shed light on the predictive value of the various r::reasures. At the same time it would 

characterize some of the differences among the three classes of pilot. 

3.3 Conclusions lmd Recommendations 

Golaszewski made a worthwhile first step in analyzmg the association of the age of the 

pilot with the probability of an accident. Given hindsight, numerous improvements can be made 

in Golaszewski's methodology. The Age 60 project will have the advantage of a CDB that 

combines the above two databases, providing measures of relationships .mavailable to 

Golaszewski. Further, the CDB will provide the capability to generate more precise estimates 

of exposure (i.e., number of flight hours) and will provide checks on the reliability of pilots' 

reports of flight time. It is likely that number of landings is a better measure of exposure. This 

empirical question should be tested. If landings is, indeed, a better measure of exposure, then 

that data should be included in the information entered in the database. 

39 
Sudden incapacitation, while intensively studied, has been shown to be a relatively 

unimportant factor in aviation accidents. Thus, studies of the relationship between age and 

cardiovascular fitness in pilots are somewhat tangential to the question of whether the probability 

of an accident increases with age. 

The data clearly show that vision of pilots deteriorates with age, while the heari..'lg of 

pilots deteriorates with exposure to noise. Lacking a conceptual model of pilot performance, 

it is unclear what these data imply about the performance of pilots. For example, the older pilot 

with greater experience may more than compensate for weakened vision and hearing. 

40 
REFERENCES 

Alkov, R. A., Gaynor, J. A., & Borowsky, B. S. (1985). Pilot error as a symptom of 

inadequate stress coping. Aviation. Space. and Environmental Medicine, 56, 244-247. 

Baisden, A. G., & Monaco, W. A. (1983). Distributilln of visual characteristics of naval 

aviation nersonnel (Final Report). Pensacola, FL: Naval Aerospac..e Medi:::al Research 

Lab. 

Banich, M. T., Stokes, A. F., & Elledge, V. C. (1988). Neuropsychological screening of 

aviators: A review. Aviation. Space. and Environmental Medicine, 60, 361-366. 

Banich, M. T., Stokes, A. F., & Karol, D. (1990). Cognitive function evaluation in the 

medical certification of airmen: Phase B (Final Technical Report A.~-90-2/FAA-90-1). 

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50 
APPENDIX A 

Test Batteries Used for Pilot Selection or Evaluation 

Ernest B. Gurman 

University of Southern Mississippi 
TEST 

CONTENTS 

APPENDIX A 

PAGE 

Cogscreen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 1 

Basic Attributes Test ........................................ A - 7 

Complex Cognitive Assessment Battery (CCAB) ....................... A- 19 

Micro-computerized Personnel Aptitude Tester (MICROPAT) ............... A- 28 

Naval Aviation Selection Test Battery .............................. A- 34 

Spartans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A - 37 

Unified Tri-Services Cognitive Performance Assessment Battery . . . . . . . . . . . . . A - 44 

Linguistic Processing Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 44 

Grammatical Reasoning (Traditional) . . . . . . . . . . . . . . . . . . . . . . . . . . A - 44 

Grammitical Reasoning (Symbolic) ........................... A - 45 

Two-Column Addition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 45 

Mathematical Processing Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 46 

Continuous Recognition Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 46 

Four-Choice Serial Reaction Time . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 47 

Alpha-Numeric Visual Vigilance Task ......................... A - 47 

Memory Search Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 48 

Spatial Processing Task .................................. A - 48 

Matrix Rotation Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 49 

Manikin Test ........................................ A- 49 

Pattern Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 50 

Pattern Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 50 
Contents 

Page2 

Visual Scanning Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 51 

Code Substitution Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 51 

Visual Probability Monitoring Task . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 51 

Time WaU Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A - 52 

Inrerval Production Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 52 

Stroop Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A - 53 

Dichotic Lisrening Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 54 

Unstable Tracking Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A - 54 

Memory Search-Tracking Combination . . . . . . . . . . . . . . . . . . . . . . . . . A - 54 

Matching to Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A - 55 

Item-Order Test . . • . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A - 55 
----------------

COG SCREEN 

PURPOSE 

The COGSCREEN test battery was designed to be used as a cognitive function screening 

test for medical certification of commercial pilots. The purpose was to provide an efficient 

computer-based means to evaluate the components of cognitive functioning believed to be 

important to aviation safety. It was intended that COG SCREEN would reveal cognitive deficits 

in aviators more readily than would observation of actual flight under normal conditions. The 

COGSCREEN tests were not intended to be a comprehensive neuropsychological evaluation 

battery. 

DESCRIPTION 

The COGSCREEN test battery was developed over a period of several years by Horst 

and Kay (1991). The sub-tests were selected, based on task analyses available in the human 

factors literature. The COGSCREEN tests do not require knowledge of aviation tasks or 

familiarity with computer technology. The current version of COGSCREEN consists of a 

battery of thirteen cognitive tests that tap the mental processes involved in working memory, 

associative memory, selective attention, time sharing, and visual-spatial, verbal-sequential, and 

psychomotor functioning. 

The battery was designed to be used repeatedly with a given subject. Alternate forms 

of the sub-tests can be computer generated to minimize practice effects. The COGSCREEN subtests are as follows. 

Backward Digit Span 

Groups of three to six digits are presented sequentially. Subjects are required to 

reproduce each sequence in reverse order. The performance score reflects the longest digit spm 

that the subject successfully reproduces at least one sequence and the total number of sequences 

correct. This test taps attention, working memory, and verbal-sequential processing. 

Visual Sequence Comparison 

Pairs of alphanumeric strings, four to eight characters in length, are presented 

simultaneously on the monitor. The subject indicates "same" or "different" for each pair of 

strings. "Same" means the same characters in the same positions. Performance is measured by 

both response speed and accuracy. This test measures attention, short-term visuai memory, and 

verbal-sequential processing. 

Auditory Seauence Comparison 

Pairs of four to eight tones, varying in pitch, are presented sequentially. The subject 

indicates "same" or "different" for each pair of sequences. Performance is measured by both 

A-1 
response speed and accuracy. This test taps attention, short-term auditory memory, and sound 

pattern sequencing. 

Math Problems 

These are word problems with multiple choice answers that measure simple mental 

arithmetic. Performance is measured by both response speed and accuracy. This test taps 

working memory, long-term memory, mental arithmetic, and logical reasoning. 

Manikin Figures 

A picture of a man holding a flag in one hand is presented on the monitor in one of four 

orientations (i.e., right side up or upside down, and facing inward or outward from the screen). 

The subject must indicate which hand the manikin is holding the flag. Performance is measure 

by both response speed and accuracy. This test taps visual-spatial orientation and the ability to 

rotate mental images. 

SVJDbol Digit Coding 

Six paired symbols and digits are displayed at the top of the monitor throughou£ the test. 

Below this display a row of symbols are presented in random order, with adjacent blank spaces. 

The subject fills in the appropriate digit fuT each symbol by referring to the display at the top 

of the screen. Performance is measured by the nmnber of items completed in 90 seconds and 

the percentage correct. This test taps attention, visual scanning, working memory, and verbalsequential processing. 

Svmbol Digit Coding - Immediate Recall. Delayed Recall 

Immediately after the Symbol Digit Coding Test, and again after a 30 minute delay, the 

six symbols are presented in random order and the subject must recall the digits that had been 

paired with each symbol. Performance is measured by the number of correct items. This test 

taps immediate and delayed recall. 

Ml!!£Nng to Sample 

A sample grid pattern with filled and empty cells is presented briefly. After a short delay 

the same pattern is presented with a slightly different pattern. The subject indicates the grid 

pattern that is the same as the previously presented pattern by a forced-choice response. 

Performance is measured by both response speed and accuracy. This test taps visual memory 

and visual-spatial processing. 

Divided Attention 

In the upper balf of the screen. a horizontal bar moves up and down within a ciD:le, 

changing direction at unpredictable times. The subjecc is instructed to respond when the moving 

bar passes from the center of the ciD:le into the upper or lower colored regions. A response 

returns the bar to the center of the circle. This task is performed alone and concurrently with 

A-2 
a Visual Sequence Comparison task. Performance is measured by the speed and accuracy of 

responses to each task, and the differences between single task and dual task conditions. In the 

dual task mode, this test taps divided attention, working memory, visual-spatial processing, and 

verbal-sequential processing. 

Pathfmder 

A character is displayed in each the four quadrants of the screen. From one display to 

the next these characters form a sequence. With each new display, the subject indicates the 

character that comes next in sequence. The task is performed with the sequence of numbers, 

letters, and an alternating sequence of numbers and letters. Performance is measured by the 

time to complete each sequence and the spatial accuracy of respoiLOP.s. This test taps verbalsequential processing, working memory, attention, and the ability to apply rules systematically. 

Shifting Attention 

Four response boxes are displayed near the bottom of the screen, one with a colored 

border, one with an uncolored border, one with no border but containing a colored arrow 

pointing right, and one with no border but with an uncolored arrow pointing left. Stimuli are 

displayed in a similar box above this row of response boxes. There are five conditions, each 

requiring the subject to respond according to different rules. (1) The Border Color condition 

requires a straightforward matching of the stimulus to response boxes, whereas the (2) Arrow 

Direction and (3) Arrow Color conditions introduce the interference of an irrelevant stimulus 

dimension. In the (4) Instruction Condition, the response rule changes from trial to trail, with 

a message informing the subject of the rule for the upcoming trial. In the (5) Discovery 

condition the rule that is in effect must be discovered by trial and error. After an unpredictable 

number of consecutive correct responses, the rule is changed. In all conditions, the performance 

is measured by both response speed and accuracy. This test taps attention, visual discrimination, 

concept formation, and the systematic application of rules. 

Dual task Tracking 

There are two tasks, each is performed separately and then concurrently. One is a 

second-order compensatory tracking task in which the subject depresses the right and left arrow 

keys on the keyboard to center a vertical bar moving along a horizontallioe. In the other task, 

three numbers are presented sequentially in random order. The subject indicates with the light 

pen which number was presented previously. Performance is measured by the average absolute 

error and number of boundary hits in the Tracking task and the response speed and accuracy in 

the Previous Number task. Together, these two tasks tap fme motor speed and coordination, 

visual-spatial and verbal-sequential processing, working memory, and divided attention. 

PUBLISHER! AGENCY 

Civil Aeromedical Institute 

Federal A Yiation Administration 

Oklahoma City, Oklahoma 

A-3 
ADMINISTRATION 

Approximately 30-45 minutes are required to complete the test. 

&;!paratus required 

COGSCREEN runs on a standard MS-DOS mM PC-AT compatible computer with color 

monitor. The battery uses a light pen as the primary input device. 

Procedure 

The COGSCREEN software W!:S designed to support both standardized test administration 

and special-purpose research applications. Individual tests can be called from a menu or the 

entire battery can be run in an automated stream. In the automated mode, the battery is selfadministered. Each test includes on-line instructions and a brief practice session in which the 

subject must demonstrate sufficient proficiency to indicate that the instructions were understood. 

Trial data and some derived performance measures are saved to disk. The selected tests all lend 

themselves to alternate forms. The session number entered by the test administrator at run-time 

serves as the random number seed for automatically generating stimuli. The battery can be 

administered repeatedly to the same lildividuals with little test-retest bias. 

Since COGSCREEN was developed for use with pilots as the target population, the test 

instructions appear on the screen with no provisions for any mental or physical limitations. It 

was assumed that the test population would be well-educated, highly motivated, and would have 

good visual acuity and sensory-motor ability. 

The light pen input device was chosen to minimize biases in favor of subjects who may 

be familiar with computer keyboards. The use of a pointing device and labelled response boxes 

on the screen was intended to aid the explanation of the test instructions. T"ne battery was 

designed to be less intimidating by allowing the subject to review the instructions and offering 

trial-by-trial feedback during the practice segments. 

Reliability 

Reliability studies are not available. Practice effects are being examined currently. 

Criteria 

Not avai!able 

Validity 

Validity studies are not available. Age related biases are being examined currently. 

A-4 
Normative Data 

COGSCREEN is currently being standardized on commercial pilots. 

Scoring 

Performance data is automatically logged and scored. A supplemental program can 

compute additional measures and create an output ftle that can be ported into a statistical analysis 

software package. 

Summary 

The COGSCREEN battery is under development and reliability and validity studies are 

not available. However, similar computer-based screening devices have been examined e. g., 

Stokes, Banich, and Elledge, (1991). They concluded "mini-mental exams" are poor 

candidates for large scale screening of line pilots for cognitive impairment. This conclusion was 

in part based on the low prevalence of cognitive deficits among commercial pilots. 

The research results that have been reviewed on the use of computer-based tests for 

identifying cognitive deficits show that the tests may be useful in predicting membership in a 

population (e. g., differentiating pilots from known mentally impaired persons). However, the 

tests have not been demonstrated to be useful for differentiating among normally functioning 

pilots. The tests need further refinement to be able to make the accurate discriminations that 

are required. 

• Advantages 

COGSCREEN takes approximately 30-45 minutes to administer. 

The battery can be self-administered. 

The battery does not require special hardware and can be run on readily available 

microcomputers. 

Alternate forms of the sub-tests can be computer generated. 

Performance data is automatically logged and scored. 

• Disadvantages 

The battery has yet to be validated for detecting cognitive impairment in 

experienced pilots. 

A-5 
Horst, R. L., & Kay, G. G. (1991). COOSCREEN: Personal computer-based tests of 

cognitive function !'or occupational medical certification. in R. S. Jensen (Ed.), 

Proceedings of the Sixth International Symposium on Aviation Psychology. Columbus, 

Ohio. 

Stokes, A. F., Banich, M. T., & Elledge, V. C. (1991). Testing the tests - An 

empirical evaluation of screening tests for the detection of cognitive impairment in 

aviatMS. Avii~WD, Space, :md EnviFonmeotJi} Medicine, 62, 783-783. 

A-6 
BASIC ATTRIBUTES TEST 

PURPOSE 

The Basic Attributes Test (BAT) is a microcomputer-administered battery of tests developed 

to assess a candidates's potential for successfully completion of U.S. Air Force basic flying 

training. The BAT battery was designed to measure psychomotor skills, cognitive and 

perceptual abilities, personality characteristics, and attitudes believed to be related to flying 

training performance. The BAT battery was designed to measure a variety of psychomotor 

skills, information processing abilities, and personality characteristics that are considered 

important in determining the suitability of a candidate for flight training. 

DESCRIPI'ION 

Each test in the BAT battery was adapted from tests in the research literature that were 

identified as potentially useful predictors of flying performance (Imhoff & Levir.e. 198i). The 

criteria used to select the tests included feasibility, interest of the test -taker, independence from 

other tests in the battery, construct validity, and minimal dependence on verbal materials for 

administration. Individual test summaries are presented below. BAT apparatus specifications 

and details regarding hardware and software development are provided in Carretta (1987a). 

Test Battery Introduction 

This interactive subprogram prompts the subject to provide background information (e.g., 

identity, age, gender), also personal history and attitudes related to flyi.r1g. 

Two Hand Coordination 

Two tests are used to evaluate psychomotor abilities. The first, the Two-Hand 

Coordination Test, is a rotary pursuit task. An airplane (target) moves in an elliptical path on 

the screen at a rate of 20 cycles per minute. The rate of movement of the airplane within each 

cycle varies in a fixed sinusoidal pattern. The subject controls the movement of a small 

"gunsight" using a left-hand joystick for vertical movement of the gunsight and a right-hand 

joystick for horizontal movement of the gunsight. The subject's task is to keep the gunsight on 

the moving airplane. After receiving instructions, the subject completes a 3-minute practice 

session and a 5-minute test. The measures of interest are horizontal and vertical tracking error 

scores. The psychological factors assessed in the Two-Hand Coordination Test are 

low-to-moderate-order tracking and time-sharing ability in pursuit. 

Complex Coordination 

The Complex Coordination Test uses a dual-axis joystick (right-hand joystick) to control 

the horizontal and vertical movement of a cursor. The left-hand single-axis joystick controls the 

horizontal movement of a "rudder bar" at the base of the screen. The subject's task is to keep 

the cursor (against a constant horizontal and vertical rate bias) centered on a large cross fixed 

at the center of the screen, while simultaneously centering the rudder bar at the base of the 

A-7 
screen (also against a constant rate bias). The instructions, practice, testing, and scoring are the 

same as those in the Two-Hand Coordination Test. The complex Coordination Test assesses 

compensatory tracking ability involving multiple-axis continuous events. 

Encoding Speed 

Two letters are presented simultaneously to the subject, who is required to make a 

same-different judgment about the letter pair. The judgment may be based on a Physical identity 

rule (look the same or look different, AA versus Aa), a Name identity rule (same name or 

different name, AA versus AH) or Category identity rule (vowels versus consonants - AE versus 

AH). The reaction time for the judgment provides a measure of the speed of the cognitive 

encoding process. Reaction time and accuracy of response (correct/incorrect) are recorded for 

each trial (32 trials in each rule condition for a total of 96 trials). The psychological factor 

involved in this test is verbal classification at several levels of cognitive operation. 

Mental Rotation 

A pair of letters is presented sequentially, and the subject is required to make a 

same-different judgment. Elements of the letter pair may be either identical or mirror images, 

and the letters may be either in the same orientation or rotated in space with respect to each 

other. A correct "different" judgment occurs when one element of a pair is a mirror image of 

the other, regardless of orientation. 

To take the test, the subject must form a mental image of the fi..rst letter (no longer 

displayed) and perform a point-by-point comparison with the second letter (which remains on 

the screen). In &ddition, when the letters are rotated with respect to each other, the subject must 

mentally rotate the mental image of one letter into congruence with the other before making the 

comparison. Reaction time and accuracy of response are recorded on all 72 trials. The 

psychological factors assessed by this test are spatial transformation and classification. 

Item Recognition 

In this test, a string of one to six digit is presented on the screen. The string is then 

removed and followed, after a brief delay, by a single digit. The subject is instructed to 

remember the initial string of digits, then to decide if the single digit was one of those presented 

in the initial string. The subject is instructed to press a keypad button marked YES if the single 

digit was in the string, or press another marked NO if the digit was not in the string. The 

instructions inform the subject to work as quickly and accurately as possible. Reaction time and 

accuracy of response are recorded on all 48 ttials. Short-term memory storage, search, and 

comparison operations are the underiying psychological factors for this test. 

Tmte-Sharing 

During a series of 10 1-minute trials, the subject is required to learn a compensatory 

tracking task. To perform this task, the subject must anticipate the movement of a gunsight on 

a screen and operate a control stick to counteract that movement to keep the gunsight aligned 

with a fixed central point (an airplane). Task difficulty is adjusted throughout the test, 

A-8 
depending on the s>.lbject's performance. !ne gunsight movement control dynamics are a 

combination of rate and acceleration components. The "disturbance" factor is a quasi-random 

summed sinusoidal forcing function. 

After these "tracking only" trials, the subject is required to track while canceling digits 

that appear at random intervals and locations on the screen. A digit is canceled when the subject 

presses the corresponding button on the keypad. If the subject fails to respond to a digit within 

4 seconds after its appearance time, the gunsight will disappear until a digit response is made. 

These dual-task trials occur in two 3-minute blocks. The information processing load gradually 

increases during these trials. The Time-Sharing Test ends with a fmal 3-minute block 

of"tracking only" trials. There are a total of 19 1-minute trials(lO tracking only, 6 dual-task, 

and 3 more tracking only). The effect of the secondary task loads is reflected in the pattern of 

level of tracking difficulty changes caused by the adaptive logic that holds tracking error 

constant. Feedback concerning tracking difficulty is provided by a gauge that appears in the top 

right of the screen. The measures of interest for this test include the level of tracking difficulty 

at which the subject can perform consistently, response time on the secondary task, and dual-task 

performance. This test assesses a variety of psychological factors including higher-order 

tracking ability, and learning rate and time-sharing ability as a function of differential task load 

(Carretta, 1987b). 

Self-crediting Word Knowledge 

This test is essentially a vocabulary test in which a "target" word is presented to the 

subject along with five other words from which its closest synonym must be chosen. Tnere are 

three blocks of 10 questions each. The target words become more difficult with eac-h successive 

block. Subjects are informed of this increasing difficulty and are required to make a "bet" before 

each block according to how they expect to do. Response time and accuracy are recorded on 

all 30 trials. This test assesses self-assessment ability and self-confidence. 

Activities Interest Inventorv 

This test is designed to determine tbe subject's interest in a variety of activities. Eighty 

one pairs of activities are presented, and the subject is asked to choose between them. Subjects 

are told to assume they have the necessary ability to perform each activity. The activity pairs 

force the subjects to choose between tasks that differ as to degree of threat to physical SUIVival 

(sometimes subtly, sometimes not).The measures of interest are the number of high-risk options 

chosen and the amount of time required to choose between pairs of activities. The psychological 

factor assessed by this test is attitude toward risk-taking. 

PUBLISHER/AGENCY 

Human Resources Directorate Manpower and Personnel Division. 

Air Force Systems Command 

Brooks AFB, TX 78235-5000 

A-9 
RELIABILITY 

Test-retest reliability with 247 USAF pilot candidates on two consecutive days yielded 

a Pearson r = .56. It was concluded that short-term retesting on the BAT should be avoided to 

minimize test score gains due to prior exposure to the test, (Carretta, 199l).lnternal consistency 

reliability estimates were also computed. Chronbach's alpha ranged between .95 to .41 for the 

various measures. These correlations were on a shortened nine subtest version of the BAT. The 

abbreviate version was used because of time constraints and required about 2 hours to complete. 

Subtest reliability results are presented in Table 1. 

CRITERIA 

The criterion used in the validity study was Undergraduate Pilot TrainL'lg (UPT) pass/fail 

final outcome. 

VALIDITY 

The validicy of the BAT was studied and reported in combination 'With the Air Force 

Officers Qualifying Test (AFOQT). The subjects were 455 United States Air Force (USAF) 

UPT students. The best combination of predictors was achieved through a simultaneous 

regression solution r = .227. p < .01, N =430 and r = .242, p < .01, N = 455, (Carretta, 

1990b). 

ADMlll<lSTRATION 

The BAT requires about 3 hours to complete. The test session is self-paced by the 

subject. Rest ~riods are programmed retween tests. 

Apparatus 

The BAT is based on a microcomputer and monitor built into a mgged chassis with a 

glare shield and side panels designed to minimize distt·actions. 

Procedure 

Each subject responds to the tests by using individually or in combination a two-axis 

joystick on the right side of the apparatus, a single-axis joystick on the left side, and a keypad 

in the center of the test unit. The keypad includes the numbers 0 to 9, an "R.~ABLE" key in 

the center, and a bouom row wid1 "YES" and "NO' keys and two others labeled "S/L" (for 

same/left responses) and "D/R" (for differentfrighr responses). 

Norms 

Norms would need to be developed for the target population. 

A-10 
Scoring 

Scoring procedures for the BAT battery rely on a combination of tracking error and 

difficulty, response speed, response accuracy and response choice, and sometimes, specially 

derived scores (e.g.,regression slope and intercept, interaction terms) .. 

TWO-HAND COORDINATION 

Xl Tradjng Error 

Cumulative tracking error for the Xl axis (horizontal displacement of the cross from the 

tat-get) for the final 2 minutes of the test period. 

Yl Tracking Error 

Cumulative tracking error for the Yl axis (vertical displacement of the cross from the 

target) for the fmal 2 minutes of the test period. 

COMPLEX COORDINATION 

X2 Tracking Error 

Cumulative tracking error for the X2 axis (horizontal displacement of the cross from the 

center of the screen) for the final 2 minutes of the test period. 

Y2 Tracking Error 

Cumulative tracking error for the Y2 axis (horizontal displacement of the cross from the 

center of the screen) for the final 2 minutes of the test period. 

72 Tracking Error 

Cumulative tracldng error for the 'Z2 axis (displacement of the rudder bar from the center 

point at the bottom of the screen) for the final 2 minutes of the test period. 

E.l\lCODlNG SPEED 

Several tests in the BAT battery rely on response latencies as an indicator of test 

performance. The standard scoring technique for tests of this type uses data only from trials that 

were answered correctly when computing summary scores. For the BAT battery, this procedure 

includes the following te.."tS and scores used to evaluate performance: 

Encoding Speed Test 

• Average Response Time: Average response time in milliseconds based on all 

trials answered correctly. 

A-ll 
• Percent Correct: Average Response Timex Percent Correct. This is a response 

time by percent correct interaction term: (Subject's average response time-grand 

mean average response time) x (Subject's percent correct -grand meru~ percent 

correct). 

Mental Rotation 

• Average Response Time: Average response time in milliseconds based on all 

trials answered correctly. 

• Standard Deviation: Standard deviation of response time i.., milliseconds based on 

all trials answered correctly. 

• Percent Correct: 

Item Recognition 

• Average Response Time: Average response time in milliseconds based on all 

trials answered correctly. 

• Slope: This score represents a regression slope for the best-fitting line for 

average response time to digit strings of differing lengths (1, 2, 3, 4, 5 or 6 

digits). 

• Intercept: This score represents a regression intercept for the best-fitting line for 

average response time to digit strings of different lengths (1, 2, 3, 4, 5 or 6 

digits). 

• Percent Correct: 

Time-Shating 

• Slope (Tracking Difficclty): Average tracking difficulty was computed for each 

subject during each minute of the practice trials (minutes 1-10). This score 

represents a regression slope based on the best-fitting line describing the eight 

average tracking difficulty scores for minutes 3-10 of this test (learcing rate on 

the tracking task). 

• Intercept (Tracking Difficulty): This score represents a regression intercept based 

on the best-fitting line describing the eight 1-minute average tracking difficulty 

scores for minutes 3-10 of the test. 

• Average Tracking Difficulty: Average tracking difficulty achieved during minutes 

11-19. 

• Average Response Time: Average response time in milliseconds to cancel the 

digits that appear during the dual-task trials (minutes 11-16). 

A-12 
• Average Response Time x Tracking Difficulty: This is a response time by 

tracking difficulty interaction term based on performance during the dual-task 

trails (minutes 11-16). 

Self-Crediting Word Knowledge 

• Average Response Time: Average response time in milliseconds based on all 

trials answered correctly. 

• Percent Correct: 

• Average Response Time x Percent Correct: This is a response time by percent 

correct interaction term. 

• Bet: This score is the average bet the subject made before block of trials. It 

reflects self-confidence regarding expected performance. Higher scores reflect 

greater self-confidence. 

Activities Interest Inventory 

• Number of High-Risk Choices: This score is the number of high-risk choices 

made by the subject. 

• Average Response Time: Average response time across all 81 trials. 

SUMMARY 

The BAT, was developed by Illiana Aviation Sciences, Inc. and Technical Solutions, Inc. 

for the USAF Human ResO>..ICces Laboratory. The battery originally consisted of 15 tests, but 

successive studies have yielded a subset of nine tests that provide the greatest gains in predictive 

validity when combined with the (AFOQT). 

The nine subtests are: 

1. Test Battery Introduction (Biographical Information, e. g.,age, handedness, 

previous flying experience). 

2. Two-Hand Coordination (rotary pursuit). 

3. Complex Coordination (stick and rudder). 

4. Encoding Speed (Verbal classification). 

5. Mental Rotation (Spatial transformation and classification). 

6. Item Recognition (Short-term memory, storage. search, and comparison). 

A-13 
7. Time Sharing (Higher order tracking ability, learning rate and time sharing 

ability). 

8. Self-Crediting Word Knowledge (self-assessment ability, self-confidence). 

9. Activities Interest Inventory (survival attitudes). 

It should be noted which tests were removed from the BAT due to their low predictive 

validity since some similar tests remain in other test batteries. Two of these tests, 

Decision-Making Speed, and the Automated Air Crew Personality Profiles have been modified 

and currently are being evaluated for inclusion in the BAT battery. 

The deleted tests are: 

Dot Estimation 

Two boxes containing an arbitrary number of dots are presented simultaneously on the 

screen. Cne box contains one more dot than the other. The subject's task is to decide, as 

quickly as possible, which box has the greater number of dots. Subject are not told to count the 

dots in each box. They are only instructed to decide as quickly and accurately as possible which 

box has the greater number. 

Reaction time and accuracy of response are recorded on each trial. This is the only test 

in the battery that has a fixed time limit (5 minutes, for a maximum of 55 trials). The 

psychological factor assessed by this test is impulsiveness/decisiveness. 

Digit memorv 

A string of four digits is presented simultaneously and in random order. The subject is 

instructed to enter the digit string on a data entry keypad in the same order as presented. In 

addition to the recording of response accuracy and overall respotJSe time, a measure of 

perceptual speed is taken by forcing the subject to press a special ENABLE key that activates 

the data entry keypad buttons on each trial. 

The most important attribute measured by this test is perceptual speed. There are 20 

trials, requiring approximately 5 minutes to complete. 

Immediate/Delayed Memory 

In this test, a sequence of digits is presented, and the subject is required to respond by 

indicating the digit that occurred either one or two digits previously. The one-back and 

two-back subtests have two parts. In the first part, th:: digits are presented for 1/2 second, 

followed by a 2-second inter-stimulus interval. In the second part, the inter-stimulus interval 

is 5 seconds. Thus, for both subtests, part one deals with "immediate" memory and part two 

with "delayed" memory. 

A-14 
There are 25 trials in each subtest (one-versus two-back) for each length of latency 

condition (2 versus 5 seconds) resulting in 100 trials. As with the other tests, response time and 

accuracy are recorded on each triat 

This test assesses continuous short-term memory storage and retrieval operations. 

Decision-Making Speed 

In this choice-reaction-time test, one of several alternative signals is presented to the 

subject. The subject is required to respond to the signal as quickly as possible. The critical 

manipulation in this test is the amount of uncertainty that must be resolved to make the response 

decision. As increasing numbers of potential alternatives are increased, greater uncertainty exists 

and the decision is made more slowly. This test consists of four subtests. 

In subtest one, the subject knows both where and when a signal is to occur; in subtest 

two, the subject knows where but not when; in subtest three, when but not where; and finally, 

in subtest four, the subject knows neither where nor when. Each subtest has three parts. In part 

one, two potential signals and responses are defmed. There are four potential signals and 

responses in part two and eight potential signals and responses in part three. Therefore, degree 

of uncertainty of signal is manipulated in three ways: location of occurrence, time of 

occurrence, and number of signals/responses. There are 12 trials within each part of each 

subtest, resulting in 144 trials (12x3x4). Response time and accuracy of response 

(correct/incorrect) are recorded for each trial. 

The Decision-Making Speed Test assesses a variety of psychological factors. These 

include simple choice reaction time under varying degrees of information load and spatial and 

temporal uncertainty, as well as low-level cognitive and high-level sensory-perceptual motor 

involvement. 

Risk-Taking 

Ten boxes are presented in two rows of five boxes each. The subject is told that 9 of 

the 10 boxes contain a reward, and one box is a "disaster" box. If the selected box contains a 

payoff, the subject i& allowed to keep it; but if the subject chooses the disaster box, all of the 

payoff earned on that trial is lost. The average number of boxes selected provides an index of 

the subject's tendency to take risks when making decisions. 

Response time per choice and number of boxes chosen are recorded on each of 30 trials. 

Unknown to the subject, there is no "disaster box" (i.e., no risk) for 12 of the 30 trials. This 

method was used to achieve a unconta.;ninated measure of risk-taking behavior, since 

performance on the "disaster box" trials could be affected by chance. 

Embedded Figures 

A simple geometric figure and two complex geometric figures are presented to the 

subject. The subject's task is to decide which of two complex figures has the simple figure 

within it and to press the button corresponding to the figure. Speed and accuracy of response 

A-15 
are recorded on each of 30 trials. This test is designed to assess the psychological factor of field 

dependence/independence. 

Automated Air Crew Personality Profiles 

This is a questionnaire that examines the subject's attitudes and interests. The subject 

is given 66 questions, each requiring a choice between two alternatives. The subject is 

instructed not to spend time pondering responses, but to give the first answer that comes to 

mind. The questionnaire is a traditional personality inventory specially tatgeted for air crew 

selection. 

CONCLUSIONS 

Carretta (1990) concluded that a combination of the AFOQT and the BAT demonstrated 

sufficient utility for supporting USAF pilot candidate selections. The USAF plans to place the 

current version of the BAT in operation in the spring of 1992. 

REFERENCES 

Carretta, T. R. (1987a). Basic Attributes Tests (BAT) system: Development of an automated 

test battery for pilot selection. (AFHRL-TR-87-9) Brooks AFB, TX: Manpower and 

Personnel Division, Air Force Human Resources Laboratory. 

Carretta, T. R. (1987b). Time sharing ability as a predictor of flight training performance 

(AFHRL-TP-86-69, AD-A181 838). Brooks AFB, TX: Manpower and Personnel 

Division, Air Force Human Resources Laboratory. 

Carretta, T. R. (1988). Relationship of encoding speed and memory tests to flight training 

performance (AFHRL-TP-87-49, AD-A190 670). Brooks AFB, TX: Manpower and 

Personnel Division, Air Force Human Resources Laboratory. 

Carretta, T. R. (1989). USAF pilot selection and classification systems. Aviation, Space, and 

Environmental Medicine, 60, 46- 49. 

Carretta, T. R. (1990a). Basic attributes test (BAT): A prelinrinary comparison between 

reserve officer training corp (ROTC) and officer training school (OTS) pilot candidates. 

(AFHRL-TR-89-50) Brooks AFB, TX: Manpower and Personnel Division, Air Force 

Human Resources Laboratory. 

Carretta, T. R. (1990b). Cross-validation of experimental USAF pilot training performance 

models. (AFHRL-TR-89-68) Brooks AFB, TX: Human Resources Directorate 

Manpower and Personnel Division. 

Carretta, T. R. (1991). Short term test-retest reliability of an experimental version of the Basic 

Attributes Test Battery. (AL-TP-1991-0001) Brooks AFB, TX: Human Resources 

Directorate Manpower and Personnel Division. 

A-16 
Carretta, T. R., & Siem, F. M. (1988). Personality, attitudes and pilot training performance: 

Final analysis (AFHRL-TP-88-23, AD-Al99 983). Brooks AFB, TX: Manpower and 

Personnel Division, Air Force Human Resource.~ Laboratory. 

Imhoff, D. L., & Levine, J. M. (1981). Perceptual-motor and cognitive performance task 

battery for pilot selection (AFHRL-Kantor, J. E. (1984). The USAF pilot selection and 

classification research program. Aviation, Space, and Environmental Medicine, 56, 

258-261. 

Mercatante, T. A. (1988). The reliability and validity of psychomotor aptitude for pilot 

selection. Unpublished master's thesis, St. Mary's University, San Antonio, TX. 

A-17 
TABLE 1 

Reliability Estimates for BAT Performance Scores** 

CronNo of bach's 

Test score N Scores* alpha Reference 

Two-Hand Coordination: 233 10 .94 Mercatante, 1988 

X1 Tracking Error 

Complex Coordination: 

X2 Tracking Error 233 10 .95 Mercatante, 1988 

Y2 Tracking Error 233 10 .99 

'Z2 Tracking Error 233 10 .94 

Encoding Speed: 

Response Time 2,219 96 .96 Carrefta, 1988 

Response Accuracy 2,219 96 .71 

Mental Rotation: 

Response Time 1,685 72 .97 Carretta, 1990 

Response Accuracy 1,685 72 .90 

Item Recognition: 

Response T"nne 1,500 48 .95 Carretta, 1990 

Response Accuracy 1,500 48 .54 

Time-Sharing: 

Tracking Difficulty 1,130 19 .96 Carretta, 1987a 

Self-Crediting Word 

Knowledge: 

Response Time 1,992 30 .89 Carretta & Siem, 

Response Accuracy 1,992 30 .65 1988 

Activities Interest 

Inventory: 

Response Time 1,992 81 .95 Carretta & Siem, 

Response Choice 1,992 81 .86 1988 

* For the Two-Hand Coordination Test, Complex Coordination Test and Time-Sharing Test, 

"Scores" refer to summed tracking performance over time. For the other tests, "Scores" refer 

to test items. 

**Carretta, 1990 

A-18 
PURPOSE 

COMPLEX COGNITIVE ASSESSMENT BATI'ERY 

(CCAB) 

The Complex Cognitive Assessment Battery (CCAB) was developed to measure higher order 

cognitive processes involved in mgh level military decision making. The battery was to be used 

to evaluate the cognitive performance effects of prophylactic drugs used in chemical defense. 

Since many cognitive skills required to perform the tests are characteristic of those required for 

piloting aircraft, the (;CAB has been investigated to assess flying potential. 

DESCRIPTION 

The CCAB was developed by the Analytical Assessments Center (AAC) of the Eaton 

Corporation for the Army Research Institute. The CCAB is composed of eight sub-tests, each 

designed to measure more than one cognitive process. Each sub-test includes a set of instruction 

screens, practice problems. a quiz to evaluate ::.he subjects' ability to understand the tasks, and 

a set of test problems. The sub-tests are as follows. 

TOWER PUZZLE 

Purpose 

The Tower Puzzle test is a compu•':'r-administered version of the "Tower of Hanoi" 

problem. It was developed to meas;rre quantiu.tive reasoning, planning, situation assessment, 

decision making, and problem solving functions. In addition, the Tower Puzzle test assesses 

perception of form, concept formation, communication, and creativity. 

Description 

A monitor displays three posts with blocks stacked on each post. Five blocks are 

distributed among the three posts. The goal is to create a single "tower" of blocks on the center 

post, wi.t.'l the largest blocks at the bottom of the posts and the smallest at the top. 

All practice and trial problems have five blocks stacked on three separate posts. The 

problems differ in the initial distribution of the blocks among the three posts. This permits 

test-retest of subject performance. The following are descriptions of the sub-tests. 

FOLWWlNG DIRECTIONS 

Purpose 

The Following Directions test was designed to measure high-level cognitive abilities 

concerned with responding to data and going beyond the data. It tests attention to detail, 

memory retrieval, time sharing, comprehension, verbal and quantitative reasoning, and 

communication. 

A-19 
Description 

Directions are displayed on the monitor. The cursor is moved by pressing the RIGHT, 

LEFT, UP and DOWN keys on the numeric keypad on the computer keyboard. The goal is to 

follow fue directions as accurately and rapidly as possible. 

The following directions task includes three general procedures. The first to underline, 

or "mark," words as instructed. The second is to remove some underlining, or "unmark," 

wodcs as instructed. The third procedure is to mark and unmark words ba~ed on values of X, 

Y, and Z, which are given at the bottom of the display. These values of X, Y, Z change as 

each new trial is presented. 

WORD ANAGRAMS 

Purpose 

The Word Anagram test is a computer-administered variation of the well known anagram 

problem, that extensively investigated in the experimental psychology literature. This adaptation 

of the anagram task involves constructing a word or multiple words from a series of scrambled 

letters. This test is intended to measure attention to detail, perception of form, memory 

retrieval, concept formation, planning, decision making, problem solving, and creativity. 

Descrimion 

In the classic anagram task, the subject is given a set of scrambled letters and is required 

to use all the available letters to construct one solution word in an allotted time. For example, 

the subject may be presented with the letters U T R IF where the solution would be FRUIT. 

In the present variation six unique letters are displayed in the upper portion of a monitor. The 

letters are made up of four consonants and two vowels, for example, H A L T M I. The 

anagram problem in this task is to construct as many 3 and 4 letter words as possible from the 

displayed letters within an allotted time. Each time period makes up an individual test trial. 

In this task, the subject selects letters from those displayed (e.g., HALT M I) to form 

words of 3 letters (e.g., aim, hit, etc.) or 4 letters (e.g., malt, hilt) by first moving the cursor 

to the desired letter and tt.;:!' pressing the space-bar to select the letters one at a time. Any of 

the letters may be used more than once in forming a given word: for example, the words ''all" 

and "hill" would be acceptable words created from the given displayed letters. As the subject 

creates words, the letters remain displayed at the top of the monitor and the words that are 

formed are displayed in a numbered list in the middle of the monitor. 

LOGICAL RELATIONS 

Purpose 

The Log'.cal Relations test was designed to measure the ability to comprehend a pair of 

premises that defines a logical relationship among three items. The subject must decide which 

item has the greatest or least value (logical syllogism). Performance reflects the combined 

A-20 
cognitive skills of attention to detail, memory >:etrieval, comprehension, verbal and quantitative 

reasoning, and problem solving. 

Descrimion 

The ftrst task on each trial is to examii'e two premi~:::s that depict relations (e.g., worse 

than/better than, longer than/shorter than, faster than/slower than, <'~ 'ighter than/darker than) 

among three items (A, B, and C). For example the two premises might be "B is lighter thai: 

A", and "B is darker than C." Given these two premises each trial is proceeded with a question 

displayed on the monitor regarding the item with either the largest ("darker") or smallest 

("lighter") value. For example, the question that might follow from the two premises above is 

"Which is darkest?" The subject responds by enteri.ng the letter A, B, or C. The total time 

allowed for a given trial is set by the Test Administrator. Since a trial is made up of several 

individual syllogisms, the subjects can attempt to solve the syllogisms at their own pace. The 

objective is to solve all syllogisms for a given trial within the time limit. 

MARK NUMBERS 

Purpose 

The Mark Numbers test was designed to measure the ability to search an array of 

numbers and make specifted quantitative decisions about each number. The subject also must 

periodically respond to a secondary task involving a flashing command stat.!ment, that directs 

the subject to select one of two flashing numbers in the array. Performance on this test reflects 

principaTiy the combined cognitive skills of attention to detail, memory retrieval, time sharing, 

comprehension, verbal and quantitative reasoning, and situation assessment. 

Description 

The task on each trial is to examine a 6 x 10 array of two-digit number and to underline 

any number that falls within the category specifted ill an instruction presented at the bottom of 

the display (e.g., "Mark ODD numbers between 15 and 45"). Subjects roark the numbers by 

using the arrow keys to move to each number that meets the given criteria and then the press 

the space, that marks the number by placing an underline beneath the number. 

Besides the primary task of marking the numbers at the bottom of the screen, a secondary 

task begins twenty seconds into the trial. This secondary task is made up of two numbers in the 

array that begin flashing on and off. Tnese two numbers are always opposite of the number type 

specifted in the pr'Jlllary task. If the primary task involves marking ODD numbers, then the 

flashing munbers will be EVEN numbers, and vise versa. When they begin flashing, a second 

instruction fla~hes sil::J.ultaneously with the two flashing numbers at the bottom of the display. 

This instruction specifies which of the two flashing numbers is to be marked (e. g., "Mark 

SMALLER flashlng number" or "Mark BIGGER flashing number"). The subject has ten 

seconds to mark the specified flashing number. 

When the correct flashing :lumber is marked, or when ten seconds have elapsed, the 

flashing stops and the subject proceeds with the prhnary task of marking numbers in the array 

A-21 
as specified by the non-flashing, original instruction. Later, another pair of numbers flashes 

with a new instruction appearing approximately every twent.l' seconds. This secondary task will 

interrupt the primary task throughout the remainder of the trail. 

The total time taken for the test can be left open, allowing subjects to progress at their 

own pace, or the total time for the test can be set at 3, 6 or 9 minutes. The time allotted per 

trial ranges between 60, 90, and 120 seconds, and can be established by the test administrator. 

When all the two-digit numbers specified by the primary instruction have been marked, the trial 

is completed. The subject is instructed that points will be awarded only for acccrate marks and 

points will be deducted for inaccurate marks. 

NUMBERS AND WORDS 

Purpose 

The Numbers and Words test was designed to measure the ability to perform two 

cognitive tasks simultaneously. The test employs a classic time sharing paradigm, involving a 

perceptual monitoring task and a running memory task. In addition, to measllJ.-ing time sharing 

performance, the task is included to assess the cognitive functions of attention to detail, 

perception of form, memory retrieval, time sharing, concept formation and decision making. 

Description 

In the Numbers and Words test two tasks are presented simultaneously compelling the 

subject to share time between them. The "numbers" task involves a running memory task where 

a previously displayed number must be recalled as each number is displayed. The "words" task 

requires the subject to identify, when possible, a 3-letter word that emerges gradually over the 

course of a trial from a white blob to an easily discernible word. As the word emerges, the 

subject must monitor it; and simultaneously, respond to the continuous stream of displayed 

numbers. The display is divided into 3 panels; two at the top and one across the bottom. The 

upper right panel is us:!d to present a 3-letter word, that emerges from a white rectangle slowly 

overtime. The full emergence of the word is accomplished as more "noise" in the form of dots 

(pixels) are removed, until the letters forming the word are displayed in virtual clarity. 

The bottom panel presents 12 alternative words from which the subject selects a word 

that appears to match !he emerging word displayed in the upper right panel. These alternative 

words are labeled 'A' through 'L'. On each trial, the subject is allowed two tries to identify the 

correct word. Feedback is given on the monitor if the first guess is correct. If it is incorrect, 

the word in the upper right panel continues to emerge until the second guess is attempted. 

The upper left panel presents a series of numbers c~ at a time, throughout the timed trial 

segments. The number displayed changes every 4 seconds or sooner. Each new number is 

displayed for up to 2.5 seconds or until the subject responds with the previous number. After 

the new number is removed, there is a flxed delay of 1.5 seconds. When the number changes, 

the subject's task is to press the number key 1 , 2, or 3 to indicate the previous number ir; the 

series. Thus, this second task is one of "running recognition." and serves to create a 

time-sharing situation. 

A-22 
Th'FORMATION PURCHASE 

Purpose 

The Information Purchase test was designed to measure the ability to decide when 

sufficient information has been gathered to identify a target, in converging multiple trials. 

Performance reflects not only the combined cognitive skills of attention to detail, perception of 

form, memory retrieval, time sharing, concept formation, quantitative reasoning, situation 

assessment, and decision making, but also planning and problem solving. 

Description 

The basic stimulus display for this test is a grid that is 14 columns wide and 6 rows high. 

The rows are labeled A through F, with the letters placed both on the right and left si-:le of the 

grid. The test begins with a single digit displayed in the first column of each rows. Only the 

digits, 0, 1, and 2 are used. 

The subject can :fill additional rows with numbers by pressing the space-bar. Each time 

the bar is pressed, the next column of all the rows will be filled with a number ( 0, 1, or 2). 

The numbers are selected pseudo-randomly. The task is to decide in which row the sum of the 

numbers wm be the largest if all columns were filled. Though 14 columns are displayed and 

may be filled with numbers, each row is designed as a 20 column row. Because of this, even 

if all 14 columns were filled, the subject would still be "predicting" which row would end with 

the highest total if all 20 columns were filled with numbers. 

High scores are achieved by identifying the row quickly, with as few columns filled in 

with numbers as possible. When subjects make a decision, they enter the corresponding letter 

(A through F). Subject are allowed only two guesses. The more information purchased (i.e., 

the more rows the subject fill"'li with numbe~ by pressing the space-bar}, t.lle lower the J,-Di!ll 

score when a correct guess is made. The total time taken for the l:est can be set at 3. 6, or 9 

minutes. 

Sut-jects are allowed two guesses to predict which row will end up with the highest total. 

More points are awarded for a correct guess that is made earlier in the trial with less 

information. If the subject predicts incorrectly, a beep tone wm sound and an error message 

will be displayed. Vv'ben the co!T"'..£t prediction is entered, L.me has run out, or both guesses 

have been expended, the correct row letter is displayed. 

ROUTE PLA,~'NING 

Purpose 

The Route Planning test was designed to measure the ability to plan and execute a route 

from a star":.ing position to an ending (target} position. Simple rules of movement with a va..<iety 

of constraints must be followed. Performance should reflect the combir..ect cognitive skills of 

planning and communication, and others such as perception of form, attention to detail, situation 

assessment, decision making, concept formation. quantitative reasoning, and problem solving. 

A-23 
Description 

A 5 x 5 matrix (25 squares), with 11 squares shaded-in is presented, determined by 

pseudo-random selection. The remaining, unshaded squares display 14 letters of the alphabet. 

Since the matrix contains 25 squares, all letters of the alphabet, except the letter Z, could be 

displayed. However, the 11 shaded squares block out 11 of the letters so that only 14 letters 

are visible at any given time. The letters are ordered from left to right in the matrix, with the 

top left square containing tae letter A, and the bottom right square of the last row containing the 

letter Y. 

The task is to move from a designated starting square to a designated ending square by 

planning and communicating ~. route. Shaded squares can be traversed, but cannot be landed 

on. Moves are restricted to two "L" shaped forms, either "one out and two over" or two out 

anti one over. • This move pattern in similar to the "Knight's" move in a game of chess, though 

the subject does not need to be familiar with chess to perform the test. The subject indicates 

the moves by enterL'lg the letters of the squares to be moved to in sequence. 

A trial ends when the ending square is reached or when the allotted time (either 60, 90, 

or 120 seconds as predetermined by the experimenter) has elapsed. A complete test session 

consists of 2 to 4 practice problems, and 3 to 9 individual test trials; these parameters are also 

under the experimenter's control. The subject is instructed that more points will be awarded for 

solutions that are obtained quickly and with the minimum number of moves. 

PUBLISHER/ AGENCY 

U.S. Army Research Institute 

5001 Eisenhower Avenue 

Alexandria, VA 22333 

ADMINISTRATION 

An "open" setting is used in most testing situations. The test is completed when a 

specified number of trials is finished. 

APParatus 

An ffiM compatible XT or AT class microcomputer with a ntinimum of 384K memory, 

a hard drive and color graphics monitor. 

Procedure 

The test is self administered once a test session is set up and the subject begins. Each 

test has a set of instruction screens, practice problems, a quiz to meas-ure the subject's 

understanding of the tasks, and a set oftest problems that can be used for repeated testing. The 

A-24 
software allows the administrator to vary the test sessions to select wl>ich tests to be given and 

in what order, and if the test instructions and a quiz are to be given. 

Reliabilit . 

See Table 2. 

Criteria 

Not available 

Validitv 

Not available 

Norms 

Not available 

Scoring 

The test is automatically computer-scored and a set of scores are stored on disk for later 

printout. 

SUMMARY 

The following is brief summary of the eight sub-tests. Each sub-test measures multiple 

complex cognitive capabilities. 

1. Tower Puzzle planning, situation assessment, problem solving, 

decision-making, perception of form, concept formation, quantitative reasoning, 

communication, and creativity. 

2. Following Directions - attention to detail, memory retrieval, time sharing, 

comprehension, verbal reasoning, quantitative reasoning, and communication. 

3. Word Anagrams -memory retrieval, creativity, perception of form, planning, 

decision-making, attention to detail, concept formation, and probiem solving. 

4. Logical Relations-comprehension, verbal reasoning, qull!'.:itative reasoning, 

attention to detail, memory retrieval, and concept formation. 

5. Mark Numbers- attention to detail, quantitative reasoning, time sharing, memory 

retrieval, comprehension, verbal reasoning, and situation assessment. 

6. Numbers and Words - perception of form, time sharing, attention to detail, 

memory retrieval, concept formation, and decision making. 

A-25 
7. Information Purchase -situation assessment, decision making, attention to detail, 

quantitative reasoning, planning, perception of form, memory retrieval, time 

sharing, concept formation, and problem solving. 

8. Route Planning -planning, perception of form, situation assessment, 

communication, problem solving, attention to detail, concept formation, 

quantitative reasoning, and decision making. 

• Advantages 

The CCAB has the potential to measure higher order cognitive processes involved 

in complex decision making that may not be measured by other batteries. 

A comprehensive users guide is available from the US Army Research Institute. 

• Disadvantages 

Researchers are experiencing software problems with the current version. 

Validity studies and normative data are not available to date. 

REFERENCES 

Geiselman, R. E., & Samet, M. G. (1986). Complex Cognitive Assessment Battery (CCAB): 

Pilot test results. (AAC-TR-33212) Alexandria, VA: U.S. Army Research Institute. 

Samet, M., Marshall-Miles, J. C., & Albarian, G. (1987). Complex Cognitive Assessment 

Battery (CCAB): Final test administrator user guide. (AAC-UM-33212) Alexandria, VA: 

U.S. Army Research Institute. 

Samet, M., Geiselman, R. E., Zajaczkowski, F. & Marshall-Miles, J. (1986). Complex 

Cognitive Assessment Battery (CCAB): Test descriptions. Alexandria, VA: U.S. Army 

Research Institute. 

A-26 
TABLE 2 

Test-retest Reliability Coefficients*** 

(Number of Pair of Measures Available are Shown in Parentheses) 

Word Anagrams 

Tower Puzzle 

Logical Relations 

Following Directions 

Mark Numbers 

Route Planrung 

Weighted Average Across Tests 

** p < .001 

* p < .01 

***Geiselman and Samet, 1986 

.89** (53) 

.74** (39) 

.68** (54) 

.95** {30) 

.66* (18) 

.85** (51) 

.80 

A-27 
MICRO-COMPUTERIZED PERSONNEL API'ITUDE TESTER 

(MICROPAT) 

PURPOSE 

The MICROPAT was originally designed for assessing suitability 

for Army rotary-wing pilot training. It was planned to be a self 

contained unit that would be easily administered and scored. 

DESCRIPTION 

Initial research and development on MICROPAT began in 1980 and 

was conducted for the British Army Air Corps whose major 

operational interest was helicopters. In 1985, The Royal Navy took 

over funding for the project. MICROP AT is an automated testing and 

record-keeping system for air crew selection. The current version 

(5.0) contains two categories of tests --psychomotor ability and 

information management ability. 

The following is a description of the nine sub-tests: 

COMP2D <10 minutes) 

This is a two-dimensional compensatory tracking task using a position control law where 

the X-axis is controlled by foot-pedals and the Y -axis by a joystick. Three 2 minute trials are 

presented and error scores for each axis are taken. The six basic errors scores are highly 

correlated and so a composite error score is taken. 

ADTRACK2 <10 minutes) 

This is a one-dimensional pursuit tracking task with joystick control. There are three 

trials with 27 five second intervals (3 times 2 minutes 15 seconds). There are 17 levels of 

difficulty and the computer measures the candidates' performance every 5 seconds to vary or 

maintain the level of difficulty. 

The basic score is the mean difficulty level over the last 11 periods (5 seconds each) of 

each trial. Two measures are then derived: the mean level across the 3 trials and the difference 

between the first and last trial levels. 

ADTRACK3 (10 minutes) 

This is similar to ADTRACK2 except that the candidate can control the adaptation. 

Difficulty level is increased or decreased by pressing a key. Two trials of 2 minutes are 

administered. The level of difficulty reached is measured for each second of the last minute of 

each trial. Three measures are derived; the average level in the last minute of each trial, the 

mean number of key presses for the 2 trials and the average tracking error across both trails. 

A-28 
LANDING (15 minutes) 

This is a 3-dimensional tracking task that resembles an aircraft landing simulator. The 

candidate controls an aircraft symbol with a joystick and sliding power control. Information 

about height, speed and fuel reserve is provided. This test examines "division of attention" 

between the "within-cockpit" information (height, speed, and fuel) and the "external" visual 

information about attitude and position. Subjects are given one practice flight followed by 5 

assessed flights. Retest scores show there is a practice effect. 

Three basic measures are taken: accuracy of final landing alignment, speed control (mean 

speed minus the final speed) and rate of descent (height descended divided by fuel used). From 

these basic measures, 6 final measures are computed: mean accuracy over the last 3 flights; 

difference in accuracy between first 2 and last three flights; mean speed control over last 3 

flights; difference between mean speed control on frrst 2 and 3 flights; mean rate of descent on 

last 3 flights; difference between rate of descent on first 2 and last 3 flights. 

DUAL TASK (20 minutes and SUBTRACT (15 minutes) 

This test was designed to measure division of attention. The candidate is frrst presented 

with 30 subtraction problems that must be checked as correct or incorrect. The next section of 

the test involves a two-dimensional step-tracking task with laterally-inverted position control; the 

subject must make a box jump to 31 different locations on the screen. In the final section, the 

subject must check 25 subtraction problems and move the box 31 times. 

The current measures are: total time required to check the last 25 problems divided by 

the number correct; percent of accuracy in last 25 problems; mean per "jump" in last 25 jumps 

in the tracking only condition; percent of change in the time taken to complete problems in the 

2 conditions with a correction for wrong answers; change in accuracy in the problems in tht.; 2 

conditions; percent of change in tracking time in the 2 conditions. 

PLANE 

This test involves an application of signal detection theory. Two aircraft silhouettes are 

displayed, that vary in size. Candidates must decide if an enemy (large silhouette) or friendly 

aircraft (small silhouette) is on the display within 1.5 seconds. There are 3 trials of 50 

silhouettes with discrimination difficulty progressively increasing. Trials of earlier versions of 

SIGNAL showed that decision speed and accuracy measures had good psychometric properties 

but signal detection type parameters did not. The basic measures used in developing PLANE 

are: mean decision response time; probability of a hit averaged over the 3 test trials; probability 

of a false alarm averaged over the 3 trails; measure of discriminative sensitivity averaged over 

the 3 trials; log likelihood ratio-<>,-measure of response bias or the tendency to respond/not 

reEpond averaged over the 3 trials. 

SCHEDULE 

Five columns are displayed, each containing a target box of varying values (1,2,3 etc.). 

When a key is pressed for a colunm, a line begins to grow toward the target; only one column 

A-29 
can be active at a time: if another key is pressed, the first column is canceled and a new line 

starts in the new column. Boxes have a limited life and lines grow at different rates in different 

columns. Also, a random variable is added to the box life and the line growth rate. The 

candidate is instructed to achieve the highest score as possible (i.e., hits on boxes). After 2 

short practice trials, there are 4 trials of 128 seconds. The computer applies an optimal strategy 

algorithm and calculates the candidate's score. The candidate's performance is expressed as a 

percentage of an optimal score. The 2 measures taken are: the mean percent score across all 

4 trials and the increase in mean percent score from first 2 to last 2 trials. 

This is a gambling task where the candidate may select up to 8 keys; one key is a penalty 

key and results in the loss of any points gained from previous selections. In the first set of trials 

there is a penalty key on each trial but in the second set the penalty key operates only 50% of 

the time. The test taps relative cautiousness-risk taking and the adaptation of strategy from first 

to sec.ond set of trials . 

The current version uses the scenario of gaining valuable documents from 8 locations, 

with an enemy ambush at one of them. Four blocks of trials are presented, 2 blocks in each 

condition mentioned above (Blocks 1 and 4 penalty key 100% of time, Blocks 2 and 3, 50% of 

time). The measures are: mean number of key presses in the 100% condition; proximity to 

optimal nu:nber of key presses in 100% condition; mean number of key presses in 50% 

condition; difference between 100% and 50% conditions; difference in number of keys pressed 

following a win versus following a loss in 100% condition but for 50% condition. 

NAVOR 

This was designed as a measure of spatial orientation and was designed for helicopter 

Observers. The task is essentially dead-reckoning: candidates have to fly a journey mentally and 

then find their home base. The flight instructions tell them to fly a given distance on a given 

heading. The complexity of the task can be varied by the number of legs flown (2 or 4) and the 

number of compass points (4 or 8). The measures recorded are: the mean final heading error; 

the mean distance error; inspection time needed for the flight instructions and; the time taken 

to indicate position of home base after ackno\\ !edging last instructions. 

MANIKIN 

This a common cognitive paradigm. This version was originally developed as a marker 

variable for the NA VOR and NAVCALC trials. The screen displays a male figure holding an 

object in one band; the figure may be (1) upright, (2) upside down or (3) lying down, facing 

the candidate or with his back toward him. The subject must decide if the object is in the right 

or left band. There are 3 x 24 trials with feedback. A principal components analysis of all the 

measures used in the trial produced 3 components: Reaction Time (44% of \ariance), Percent 

Correction (22%) and a third unnamed measure (15%). 

A-30 
NAVCALC 

This is a work sample type test designed to simulate one aspect of Observer 

training/producing and updating a flight log. 

The candidate must copy a log from the screen. The log contains several locations on 

a flight plan, their radio frequency, departure times, turnaround times, and flight times between 

locations. The computer updates some items on the Jog as the test progresses and the candidate 

must change the log accordingly. Questions about the log are interspersed with the log update 

information. If the subject gives an incorrect answer, the correct answer is displayed and he can 

amend his log accordingly. 

PUBLISHER! AGENCY 

Ministry of Defence (Navy) 

London, U.K. 

ADMINISTRATION 

Testing time required is approximately 110 minutes. 

APParatus 

The MICROPAT battery requires no specially designed equipment and will run on an AT 

class microcomputer with a color monitor. This feature would allow the use of a portable 

system. 

RELIABD...ITY 

Internal consistency estimates of sub-test scores ranged from . 53 to . 93 (Jones and 

Abram, 1988). 

APPARATUS 

The test requires no specially designed equipment. M!CROPAT will run on an AT class 

microcomputer with a color monitor. This feature would allow the use of a portable system. 

CRITERIA 

The Royal Navy (RN) trial of MICROPAT used four major criteria: (1) Completion of 

Pilot Elementary and Basic Flying Training (obtained Pilot "wings"); (2) Successfully passing 

through elementary/Basic/Advanced/Operational Pilot training; (3) Passing Observer Basic 

Training (BOC); and (4) successfully passing through Basic/Advanced/Operational Observer 

training. 

A-31 
VALIDITY 

Prediction of RN Pilot Elementarv-Basic Rotary flying Training: A step wise multiple 

regression analysis of all MICROPAT variables yielded a correlation of r = .51 with training 

outcome. 

Prediction of RN Pilot Elementary-Advanced Rotary Flying Training: A multiple 

correlation of r = .29 was found when corrected for restriction of range. 

Prediction of RN observer Basic-Operational Flying Training: A multiple correlation of 

r = .55 (uncorrected) with successful pass/fail through Basic, Advanced and Operational phases 

of Observer training was reported. These correlations were based on a sample of 109 pilots and 

111 observers (Bartram, 1990). 

NORMS 

Current norms are based on sample sizes between 11 and 859. "T" scores and 

percentiles are available. The subjects were observer and pilot rotary wing flying training 

candidates. Norms are currently being gathered on air crew applicants for Cathay Pacific 

Airlines. 

SCORING 

Version 5 (MS-DOS version) runs under a commercially available administration 

marketed by ASE, NFER-NELSON ("SCREENTEST"). An interpretation package is under 

development to calculate composite predictor scores and generate a narrative to provide feedback 

of results. 

SUMMARY 

The nine subtests are: 

I. J anding (superficially resembling an aircraft simulator). 

2-4. Adtrack-1, 2 and 3 (three tasks of one dimensional pursuit tracking using a 

joystick controller. 

5. Risk (a gambling task involving explicit decision ma.ldng where the costs and 

payoffs are made known). 

6. Signal (a signal detection task involving implicit decision making. Sensory 

information must be interpreted and some correction to the flight path must be 

made). 

7. Schedule (sorting priorities). 

8. Dual Task (two-dimensional step-tracking and mental arithmetic). 

A-32 
9. Memory Span (an adaptive test of digit-span), Bartra..1n, 1986. 

• Po~sible Advantages 

High face validity 

Minimum hardware requirements 

Portability 

Output files can be read by current DOS based data analysis packages, e. g., 

SPSS-PC+, and Lotus 123. 

The battery bas been ref'med and validated as a composite test used as a 

composite test. 

Reasonable time required for administration. 

• Possible Disadvantages 

I>Pveloped for selection of rotary wing combat pilots and to date validity studies 

have not been reported for fixed-wing pilots. Studies are in progress. 

REFERF"!'::ES 

Bartram, D. (1986). Development and evaluation of MICROP AT Version 4, (TR-184) London: 

Ministry of Defense, and University of Hull, U.K.: Ergonomics Research Group. 

Bartram, D., & Marshall, L. (1990). ValidationofMICROPATVersion4, (TR-248), London: 

Ministry of D.::Iense, anJ University of Hull, U.K.: Ergonomics Research Group. 

Jones, A., & Abram, M. (1988). MlCROPAT databook: Issue two, (TR-255), London: 

Ministry of Defense. 

A-33 
NAVAL AVIATION SELECTION TEST BATTERY 

PURPOSE 

The Naval Aviation Selection Test Battery was intended to augment the Navy's 

paper-and-pencil selection test for aviators. 

DESCRIPTION 

The Naval Aviation Selection Test Battery is an automated performance-based test 

battery. Several combinations of predictors have been studied over the years. The latest study 

(Delaney, 1990), includes the automated dichotic listening task (DLT) and psychomotor tasks 

(pMT). On the DLT, subjects listen to two different series of letters and numbers presented 

simultaneously to their el'.rs over bi£aural headphones. The PMT includes single or dual modes 

of stick/rudder/throttle tasks. 

PUBLISHER/ AGENCY 

Naval Aerospace Medical Research Laboratory. 

Naval Air Station 

Pensacola, Florida 32508-5700 

ADMINISTRATION 

Time required: Approximately 75 minutes including brief breaks. 

APPARATUS AND PROCEDURE 

All tasks are presented on an Apple lie computer. 

PSYCHOMOTOR TASKS 

On the PMT subjects are required to maintain first one, then two, and fmally three 

randomly displaced cursers on fixed targets on a CRT by manipulating joysticks and foot pedals. 

Psychomotor test scores are the cumulated total absolute errors from the target in pixels. 

DICHOTIC LISTEI'i!NG TEST {DLT) 

On the DLT, subjects listen to two different series of letters and numbers presented 

simultaneously to each ear over binaural headphones. Subjects are instructed which ear to attend 

to on each trial. Subjects are told to indicate the digits presented to the designated ear in the 

order of their occurrence. Responses are entered with the left hand on a keypad placed in front 

of the subjects. 

A-34 
DUAL TASKS 

For the dual tasks, subjects are asked to simultaneously perform a 4.5 - minute PMT and 

a 12-trial DLT. Performance is scored in the same way as for the single tasks. 

RELIABILITY 

Not available 

CRITERIA 

Grades in the academic portion of naval flight training and pass/fail in the flying portion 

of primary flight training. 

VALIDITY 

The DLT/PMT tasks were administered to 677 student aviators upon completion of the 

academic portion of naval flight training and waiting to begin primary flying training. 

Correlational analyses showed primary flight grades were significantly related to PMT scores 

(r = -.26 to -.41, P < .05), and DLT scores (r = -.22 to -.28). Multiple regression analysis 

yielded a validity coefficient for a combination of performance measures of r = .442. The 

19.5% of the flight grade variance accounted for by the performance-based tests was largely 

independent of the 16.6% variance accounted for by a combination of current selection tests and 

demographic variables. Individual performance variables were not significantly related tc> the 

pass/fail criterion (Delaney, 1990). 

NORMS 

Not available 

SCORING 

Not available 

SllMMARY 

• Advantages 

No specially designed equipment is required. 

All tasks are presented on an Apple I!e computer. 

e Disadvantages 

None of the tasks were significantly relata> to the pass/fail performance criteria. 

A-35 
REFERENCES 

Damos, D. L. (1987). Scme considerations in the design of a computerized human information 

processing battery (NAMRL Monograph 35). Pensacola, FL: Naval Aerospace Medical 

Research Laboratory. 

Delaney, H. D. (1990). Validation of dichotic listening and psychomotor task performance as 

predictors of primary flight training criteria: Highlighting relevant statistical issues. 

(NAMRL - 1357) Pensacola, FL: Naval Aerospace Medical Research Laboratory. 

A-36 
SPARTANS 

PURPOSE 

The SPARTANS (Simple Portable Aviation-Relevant Test-Battery and Answer-scoring 

System) test battery was developed as a diagnostic battery to assess neurological impairment in 

high level skills in complex dynamic environments. 

DESCRIPTION 

The SPARTANS originated in studies reported by Braune and Wickens (1984) and 

Wickens, Braune, Stokes, and Strayer (1985). The original bttttery was devised to assess 

individual differences and age-related performance in pilots and was validated against 

performance in a motion-based flight simulator. 

The SPARTANS can be run on an ffiM compatible 286 microcomputer with VGA color 

graphics and a joystick controller. The current version, 2.0 is modular and each sub-task can 

be selected from a menu of 20 sub-tasks in any order and can be presented as a practice run or 

as a data collection run (Sanich, Stokes, and Karol, 1990). There are two forms of the battery 

to permit retesting of S"Jbjects. The tests were selected to incorporate those aviation-releva'lt 

skills that have been found sensitive to neuropsychological functioning. Spatia ability, for 

example, was found to be sensitive to dementia of various etiologies (Bani::h, Stokes, and 

Elledge, 1988) and is especially disrupted by right hemisphere damage (Perecman, 1983). 

Description of the sub-tasks are as follows: 

Spatial Memorv Task 

A set of nonsense or abstract figures designed to ease verbal encoding is presented to the 

subject (spatial memory task #1}. About twenty mim;tes after the initial presentation, subjects 

view another set of 40 figures (spatial memory task #2) and mnst decide if any have been viewed 

previously. 

Hidden figures Rec'.l!IDition Task 

This task ~-sesses flexibility of closure. Su'bjects must decide if an abstract line drav.ing 

is embedded within a complex pattern of lines that changes on each trial. The task is always 

presented in the same orientation. The location of the target pattern on the screen changes from 

trial to trial during presentations to avoid s de;;rease in difficulty. 

Rotated Hidden Figures Recognition Task 

This is a r«tated version included to add additional discrimination power in some 

categories of impairment. Since bom a rotated and non-rotared version of the task is presented, 

the specific effect that rotation has on performance can be determined. 

A-3i 
Maze Tracing Task 

Subjects are presented with a series of line mazes of increasing complexity. Each maze 

must be mentally traced to decide if there is an unbroken path from beginning to end. A 

response is recorded by pressing a "yes" or "no" button on the joystick and both accuracy and 

latency data are recorded. 

Scheduling Task 

This task was designed to assess flexibility of strategy and the ability to set priorities. lt 

is similar to the MICROPAT task (Bartram and Dale, 1990). In the task lines "grow" down the 

screen in any of 5 columns toward a set of boxes containing numbers, whose value is added to 

the subject's score when reached by a line. The subject decides in which column a line will stan 

by pressing a key from 1 to 5. Several variables fluctuate concurrently - line speed, duration 

of the box on screen ("box lifetime"), box position, and box value. Subjects must continually 

make and change decisions to maximize their score. Data is logged on total score and on 

decision reversals, a variable that is sensitive to cognitive impairment due to stress (Stokes and 

Raby, 1989). 

Spatial Memory Task #2 

This is a repeat of Spatial Memory Task #1. 

Visual Scanning Task 

In this task, subjects estimate the number of Xs printed on the longest of twelve 

horizontal lines that are presented for a 4 second duration. An average deviation score from the 

true number of targets is computed over 20 trials. 

Sternberg Task 

The Sternberg Task is a standard memory search task in which target letters are 

memorize and a series of stimulus letters are presented. Subjects depress a joystick button to 

indicate if a stimulus letter has been previously presented in a target set. 

Zero Order Pursuit Tracking Task 

The zero order (position) tracking task is similar to the First-Order (velocity) Tracking 

Task. This task is designed to be more sensitive to dysfunction and less influenced by 

experience than First-Order Tracking. 

In this task the uro order tracking task is presented in combination with the Sternberg 

task to permit dual-task decxements to be measured in both tasks. 

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First-Order Tracking Task 

Subjects are instructed to keep a vertical sinusoidal line between rwo horizontally 

movable cursers using lhe joystick. This task is an adaptation of that developed in the 

Netherlands by Boer liJ'..d Gaillard (1986). The task is perfonned twice. first in a single-task 

condition and again in a dual-task condition. 

Dual raw First-Qrder Tooinr 

1bil; task combines the Sternberg task with the first-order tracking task and measures 

performance dectements due to dual-task timesharing. Sternberg probes are presented randomly 

to the left or right of the tracking task. 

Box Task 

This is a measure of risk-taking. Subjccl:s may select up to ten boxes containing bidden 

scores. Tbe score, once revealed, is added to lb.! subject's box-task total. The subject is aware 

!hat one random box per trial is "booby-napped.· If the disaster box is selected, the subjecfs 

entire score for that trial is lost. First, the subject· s initial performance on trial 1 is recorded 

before the subject has been influenced by the random pattern of~ and failures across all 

trials. The mean and standard deviation of the oomber of boxes selected over 20 trials is 

calculated. Rist-taking co~istetq has proved to be sensitive to alcobol induced impairments 

(Stokes et al., 1990). 

This is a time-stressed anentioo task adapted from the paper-and-pencil in the Illinois 

Screening Test. In the p1c:sent version. a 3-digit number. and then six 3-digit mnnbers are 

displayed. Only one DUIDber is the r'm'eCt subtracted value - the others represent inconect 

subtractions. The subject selects one value using the joystick. and depresses the joystick button. 

Subjects proceed at their own pao:e. Two variables are measured; the total number of 

subtractions correctly identified in 30 seconds. and the mean response latency. 

Di&it Symbol TaM 

This task is also adapted from the Illinois Screening Test. In the present version. 

symbols (tldba- than digits} are pt :semed and the subject keys U:. the associated number. A 

practice test is given to ensure the instructions are understood. The subject· s score is the 

iiWIIber of squares correctly filled. 

Stroop Test 

This is a classic test !hat measures pmcessing flexibility. conceprualized as the ability to 

disregard irrelevant information (Stroop. 193S). Subjects are required to identify the color that 

a particular word spells e. g .. red. blue. etc. The test is conducted in rwo parts. In the comrol 

condition. the color words are displayed in black and the subject must match the word with a 

color pau:b at the bottom of the scm:n. In the experimental condit'.on. the terms are displayed 

A-39 
in randomly selected, primary colors that conflict w :_,It the color the word spells (e.g .. the word 

red displayed in yeUow). The subject must override a powerful perceptual effect to match 

correctly and rapidly the wl'rd to the appropriate color patch. The amount of interference is 

measured by comparing the time difference and the percent of ccrrect responses in the control 

and tbe experimenlal condition. 

This task is modified from standard verbal reasoning tests and involves deciding if 

DOII5CSISc: syllogisms are valid or invalid. Tbe test consists of 20 nonsense syllogisms. in which 

bolb speed and accuracy of response are monitored. 

Srprylpk 

This rest can be descnbed as the verbal equivalent of the Spatial Memory task. The 

presc:Dl form involves the presc:ntation of a short narrative containing several characters and 

eveniS. The subject tben responds to multiple cooice questions about the passage. The 

pera!Mage of correct rc:spouscs is n:corded. 

This task mcasuRS working memory capacity, a factor that has been shown to 

dillcriminate !Jetween good and poor pilot decision making (Wickens et al., 1987. It is adversely 

affecrcd in individuals with a variety of clinical conditions, including dementia (Albert, Butt,ers, 

and Brandt, 1981). substance aDIIse (Nixon. Kujawski, Parsons, and Yohman, 1987), and 

neurological damaF (Lezak, 1979). 

Subjects are present.:d with a set of digits at l second intervals accompanied by a brief 

tone. Tbe leDgtb of the digit series increases from one to nine digits as the number of trials 

prog1esses. After the screen is cleared the subjects key the digits they recall back into the 

wmputef. Conect/incorrec:t respol!lleS are recorded along with two latency variables of initial 

IIIII final keyboard input. 

Rcveqe Order yicmt! Number Soan Task 

This task is ~digits forward and reverse of the W AIS-R. Digit span forward is a 

left hemispbere task, number span t: reverse is a right hemisphere task. 

PVBLISBEit/AGENC""i 

AMIU., lfmnan Fngi!W%1:ing Division 

W,.._Paaeisou AFB. OH 

Af'mjpi4iltioo 

Notavaiblble 

A-40 
APPARATUS 

Not available 

Not available 

RELIABILITY 

Not available 

The battery bas been used to detect performance decrements under stress. 

VALIDITY 

Stokes, Belger and Zbang, (1990) found that the SPARTANS in combination with 

MIDIS, a microcomputer-based flight-decision simulator, was able to show significant 

decrements in performance under stress for boih experienced and inexperienced pilots in nondomain-specific information processing tasks. However, this impairment in information 

processing was not associated with any performance decrement in simulated flight decision 

making by experienced pilots. 

Banich, Stokes and Karol (1990) concluded that the SPARTANS effectively detects 

neuropsychological dysfunction and not pilot expertise. 

SPARTANS tests were found to be sensitive to the effects of alcohol upon cognitive 

performance (Stokes, Belger, Banich, and Taylor, 1990), to noise and workload related stress 

(Stokes and Raby, 1989), also to neuropsychological impairment (Stokes et al., 1988). 

Stokes, Banich, and Elledge (1991) concluded that the SPft..RTANS was not an 

~q~propriate instrument for large scale screening of flight medical certificate applicants. This was 

based on their discriminate validity study comparing pilots and subjects in a clinical population. 

They did suggest that the SPARTANS might be useful when combined with traditional 

neuropsychological testing when examining someone suspected of impairment. 

NORMS 

Data may be processed using a utility program that provides for graphic display of 

normative data. 

A-41 
SCORING 

SUMMARY 

The SPARTANS consists of 20 subtests, (1) Spatiai Memory Task (2) Hidden Figures 

Task, (3) Rotated Hidden Figures Task (4) Maze Tracing Task, (5) Schedule Task (6) Spatial 

Memory Task #2, (7) Visual Scanning Task, (8) Sternberg Task, (9) Tracking Task (zero order), 

(10) Dual Task (Sternberg with zero order tracking), (11) Tracking Task (first order), (12) Dual 

T;J;k (Sternberg with first order tracking), (13) Box (risk-taking) Task, (14) Subtraction Task, 

(15) Digit-symbol Task, (16) Stroop Task, (17) Syllogisms Task, (18) Story Task, (19) Visual 

Number Span Task and, (20) Backwards Visual Number Span Task (Banich, Stokes, and Karol, 

1990.) 

REFERENCES 

Albert, M. N., Butters, N., and Brandt, J. (1981). Development of remote memory loss in 

patients with Huntington's disease. Journal of Clinical Neuropsychology, l-12. 

Banicb, M. T., Stokes, A. F., & Elledge, V. (1987). Cognitive function evaluation in the 

medical certification of airmen-a literature review. (Final Tech. Rep. 

ARL-88-3/FAA-88-1) Savoy, II: University of Illinois, Aviation Research Laboratory. 

Banich, M. T., Stokes, A. F., and Elledge, V. C. (1988). Neuropsychological screening of 

aviators: A review. Aviation, Space and Environmental Medicine, 60, 361-366. 

Banich, M. T., Stokes, A. F., & Karol, D. (1990). Cognitive function evaluation in the medical 

certification of airmen phase B. (ARL-90-2/FAA-90-1), Oklahoma City: FAA 

Aeromedical Research Branch. 

Bartram, D., and Dale, H. C. (1983). Micropat version 3: A description of the fully automated 

personnel selection testing system being developed for the Anny Air Corps. (Report 

ERGIY6536/83/7). Ergonomics Research Group, University of Hull. 

Boer, L. C., and Gaillard, A. W. K. (1986). TASKOMAT: A standardized task battery. 

Soesterberg, Netherlands: Institute for Perception TNO. 

Braune, R., and Wickens, C. D. (1984). Individual differences and age related performance 

assessment in aviators. Part_ II: Initial validation (Tech. Rep. NAMRL-84-1/EPL-84-1). 

Savoy, IL: University of Illinois Engineering Psychology Laboratory. 

I..ezak, M. D. (1979). Recovery of memory and learning functions follow!ng traumatic brain 

injury. Cortex, 15, 63-70. 

Nixon, S. J., Kujawski, A., Parsons, 0. A., and Yohman, J. R. (1987). Semantic (verbal) and 

figural memory impairment in alcoholics. Journal of Clinical and Experimental 

Neuropsychology, 9(4), 311-322. 

A-42 
North, R. A., and Gopher, D. (1976). Measures of attention as predictors of flight 

performance. Human Factors, 18(1), 1-14. 

Perecman, E. (1983). Cognitive functioning in the right hemi!!phere. New York: Academic 

Ptess. 

Poon, L. W. (Ed.). (1980). Aging in the B80's. Washington, DC: American Psychological 

Association. 

Salthouse, T. A. (1982). Adult cognition: An experimema! psychology of human aging. New 

York: Springer-Verlag. 

Salthouse, T. A., and Somberg, B. L. (1982). Isolating the age deficit of speeded performance. 

Journal of Gerontology, 37, 59-63. 

Stokes, A. F., Banich, M. T., & Elledge, V. C. (1991). Testing the tests - An empirical 

evaluation of screening tests for the detection of cognitive impairment in aviators. 

Aviation, Space, and Environmental Medicine, 62, 783-788. 

Stokes, A. F., Banich, M. T., & Elledge, V. (1988). Cognitive function evaluation in the 

medical certification of airmen. (Final Tech. Rep. ARL-88-4/FAA-88-2) Savoy, II: 

University of Illinois, Aviation Research Laboratory. 

Stokes, A. F., Banich, M. T., Elledge, V. C., & Ke, Y. (1988). Cognitive function evaluation 

in the medical certification of airmen (Final Tech. Rep. ARL-88-4/FAA-88-2). Savoy, 

IL: University of Illinois, Aviation Research Laboratory. 

Stokes, A. F., Belger, A., & Zhang, K. (1990). Investigation of factors compromising a model 

of pilot decision making: Part II. Anxiety and cognitive strategies in expert and novice 

aviators. (Final Tech. Rep. ARL-90-8/SCEEE-90-2) Wright-Patterson AFB: AMRL, 

Human Engineering Division. 

Stokes, A. F., & Raby, M. (1989). Stress and cognitive performance in trainee pilots. 

Proceedings of the 33rd Annual Meeting of the Human Factors Society (pp. 883-887). 

Santa Monica, CA: Human Factors Society. 

Stroop, J. R. (1935). Studies of interferenct' in serial verbal reactions. Journal of 

Experimental Psychology, 18, 643-662. 

Wickens, C. D., Braune, R., Stokes, A., and Strayer, D. (1985). Individual differences and 

age related change: Refinement and elaboration of an information processing performance 

battery with aviation relevant task structure (Final Rep. EPL-85-1/NAMRL-85-1). 

Champaign, IL: University of Illinois Engineering Psychology Laboratory, Department 

of Psychology. 

A-43 
UNIFIED TRI-SERVICES 

COGNITIVE PERFORMANCE ASSESSMENT BATTERY 

PURPOSE 

The Unified Tri-Services Cognitive Performance Assessment Battery (UTC-P AB) was 

developed to access cognitive performance in a multiple level drug evaluation program. It also 

may have potential for the assessment of neuropsychological deficits, stress effects and pilot 

selection (Perez, Masculine, Ramsey, and Urban, 

1987). 

DESCRJYI'ION 

The UTC-PAB was drawn from several other batteries, primarily from components of 

the Army (WRAIR-PAB), Navy (PETER, NAVAL ccn or Air Force (CTS) batteries. The 

25 sub-tests are as follows: 

LINGUISTIC !KOCESSING TASK lVISUAL AND SEMANTIC CODING> 

The Linguistic Processing Task was designed to measure the ability to code linguistic 

information at different deptbs of process and transform linguistic information. 

DESCRIPI'ION 

This task is a based on Posner and Mitchell's (1967) letter match task and depth of 

processing tasks (e. g., Craik and Tulving, 1975). It is a standardized loading task requiring 

the classification of pairs of letters or words. Letter or word pairs are presented on a monitor. 

with instructions to respond "same" if the items match or "different" if they do not. Three 

levels of task demand are presented: (1) Physical letter match, requiring letter pairs to be 

physically identical to match (low d<:mand); (2) category match, requiring that both letters to be 

either consonants or -::>Wels (moderate demand); and (3) antonym match, requiring only words 

opposite in meaning to form a match (high demand). Each set lasts three minutes. 

GRAMMATICAL REASQNING ITRAJ)mONALl !LOGICAL REASONING> 

P\JRPOSE 

The grammatical reasoning test was designed to measure general reasoning ability. It 

is a type of sentence verification task that tests the processing capacity of working memory. It 

is also sensitive to environmental stress, pollutants, and the effects of sleep loss. 

A-44 
DESCRIPTION 

First, pairs of letters (AB or BA) and a statement about their sequential arrangement are 

presented to the subject. Then the task is to decide if the statement and letter pairs match or fail 

to match. Subjects respond by pressing one of two buttons on a keypad that are labeled TRUE 

and FALSE. 

GRAMMATICAL REASONING <SYMBOLIC..) <LOGICAL REASONING> 

PURPOSE 

This task was designed to measure general reasoning ability. The symbolic grammatical 

reasoning task is a type of sentence verification task that taps the processing capacity of working 

memory. It is sensitive to variable information processing demands and is probably sensitive 

to environmental stres.~, pollutants, and sleep loss. 

DESCIUPI'ION 

The symbolic grammatical reasoning task tests variable demands required for the 

manipulation and comparison of grammatical information. It is based on Baddeley's (1968) 

Grammatical Reasoning Task. The stimuli are sentences of varying syntactic structure 

simultaneously presented with two or three sets of symbols (e.g.,*, @,and#). The sentences 

must be analyzed to find if they correctly describe the ordering of the characters in the symbol 

set. The amount and complexity of g..-ammatical analysis decide task demand. Three different 

levels of task demand are measured, they are: (1) single-sentence items of variable syntactic 

construction that describe the order of symbol pairs (i.e., all possible stimuli from the Baddeley 

version, and substituting symbols for letters) -- low demand; (2) two-~ntence items worded 

actively and positively, that describe the relative positions of three symbols--moderate demand; 

and (3) two-sentence items worded either actively /negatively or passively /negatively that describe 

three symbols-high demand. 

TWO-COLUMN ADDITION !'NUMBER FACILJTY) 

This subject-paced, mental arithmetic test was designed to measure the ability to perform 

simple addition. It measures the ability to quickly and accurately retrieve arithmetic information 

and to use procedural knowledge. It also measures short term memory. 

DESCRIPTION 

First, a set of 45 trialll is presented to the subject on the monitor. Each trial consists of 

three 2-digit numbers simultaneously presented on a monitor in a column format. Subjects are 

required to sum and enter their responses as rapidly as possible on a keyboard. Responses are 

entered beginning with the left hand digit frrst {usually the hundreds and tens digit). The column 

A-45 
of digits 1isappears with the first valid key entry; requiring the subject to know the entire answer 

before entering a response. A trial is ended by pressing the return key or when a deadline 

period of 15 seconds has elapsed. Subjects receive speed/accuracy feedback during the training 

trials but do not receive feedback during the experimental trials. 

MA'flrnMATICAL PROCESSING TASK <NUMBER I<"ACILITY/GENERAL 

REASONING> 

PURPOSE 

This self-placed mental arithmetic task was designed to test a subject's information 

processiLg resources associated with working memory. The subject must: (a) retrieve 

information nom long term memory, (b) update information in working memory, (c) 

sequentially execute different arithmetic operations, and (d) perform numeric comparisons. 

DESCRIPTION 

Subjects perform one or more addition and/ or subtraction operations on single digit 

numbers and dedde if the answer is greater or less than five. Problems are presented in the 

center of the screen in a horizontal format for left to right solution and are followed by an equal 

sign. The responses are entered via a two button keypad. 

Three versions of this task can be selected and are designed to produce different response 

time performance. Each version requires three minutes of continuous performance and reaction 

times are recorded. There are three versions of this test: (1) low demand version--problems 

containing only one mathematical operation, (2) moderate demand version--problems containing 

two mathematical operations, and (3) high demand version--problems containing three 

mathematical operations. 

CONTINUOUS RECOGNITION TASK (WORKING MEMORY-ENCODING and 

RECOGNITION! 

PURPOSE 

The Continuous Recognition Task was designed to tap variable demands associated with 

encoding and storage in working memory. The task tests the ability to encode, rehearse, recall, 

and compare numbers In short term memory on a continuous basis. 

DESCRIPTION 

The memory test consists of a random series of numbers that must be encoded in a 

sequential fashion. As each number in the series is presented, a probe number is presented 

simultaneously. The operator must compare thi~ probe number to a previous item at a specified 

position back in the series. The subject must decide if the previously presented item is the same 

as or different from the probe number. Thus, the task taps working memory by requiring 

A-46 
subjects to maintain accurately, update, and access a store of information on a continuous basis. 

Task difficulty is manipulated by varying the number of digits comprising each item, and the 

length of the series that must remembered to respond to recall probes. 

FOUR-CHOICE SERIAL REACTION TIME <ENCODING. CATEGORIZATION. 

RESPONSE SELECTION) 

PURPOSE 

This task was designed to measure ~timulus encoding and categorization, and response 

selection. It probably tests encoding more heavily. 

DESCRIPTION 

A blinking plus sign imposed on the cursor is presented in one quadrant of a monitor. 

The subject presses a key on the keyboard tlmt corresponis to the quadrant with the blinking 

"+." The blinking "+" remains in a quadrant until the correct key is pressed and 1hen randomly 

reappears in another quadrant. If no button is pressed within 2.5 seconds, a beU rings at 0.1 

second intervals until a response is made. Subjects are instructed to respond ru. quietly and 

accurately as possible. The task lasts 6 minutes. 

ALPHA-NUMERIC VISUAL VIGILANCE TASK CS<JSTAINED VISUAL 

ATTENTION CHOICE RT> 

PURPOSE 

The Alpha-Numeric Visual Vigilance T&&k (ANVVT) was designed to test the ability to 

make rapid decisions in response to visual symbols for long nonstop periods. The ANVVT is 

a discrimination reaction task intended as a simulation of a person monitoring a visual display 

under conditions that might ptoduce fatigue and performance decrement without the subject 

being aware of it. 

DESCRIPTION 

In this version, random alphabetic characters or numbers are presented at random 

intervals on a monitor ranging between 6 and 14 seconds, with an average interval of 10 

seconds. The number or character is 10 by 28 mm in size and remains on the screen for 500 

msec. Subjects press a hand held push button with their thumb every time an "A" o;: a "3" 

appears. No other responses are 

required. 

Twenty "As" and "3s" a...-e randomly inserted within 160 other characters and numbers 

presented during this 30-minute task. Response latencies and errors are recorded. There are two 

types of possible errors: (1) errors of commiss~on (responding to non "As" and non "3s"), and 

(2) errors of omission (not responding to an "A" r "3" in 5 seconds). Reaction times are 

A-47 
recorded in msec for correct responses and errors of commission. Errors of omission are cored 

as reaction times of 5000 msec. 

MEMORY SEARCH TASKS <SHORT TER.l\-1 WORKING MEMORY-AUDITORY 

AND VISUAL MODALITIES) 

PURPOSE 

This memory search task was designed to test the ability to make compa1isons of letters 

stored in memory. The task diagnoses selective retrieval and comparison in short term working 

memory. It also may tap the encoding of stimulus items, categorization, response selection, and 

response execution. 

DESCIUPI'ION 

A "positive set" of either one, two, four, or six alphabetic characters is presented to be 

stored in memory. The remaining alphabetic characters make up the "negative set." Following 

the presentation of the "positive set," individual probe leners are presented for comparison and 

classification as members of the positive set or the negative set. Subjects respond by pressing 

a key on a two button keypad. 

There are three different versions of this task. Each version is presented in a visual 

format and an auditory format for a total of six unique versions. A different positive set is 

generated on every trial in the varied set procedure (VS) followed by a single probe item. In 

the fixed set procedure {FS) the positive set is followed by 100 probes to form a trial. A trial 

in the mixed set procedure (MS) consists of 10 separate positive sets of ef!uivalent size, .. ~.n 

followed by 10 probes for correct classification. In the visual format all stimuli are presented 

on a monitor. In the auditory versions the probe items are presented with a speech synthesis 

system and positive sets are presented on a monitor and the speech synthesis system. 

~PROCESSING TASK <SPATIAL ORIENTATION/ROTATION SHORT 

TERM MEMORY> 

PURPOSE 

This task was designed to measure the ability to rotate mentally a series of histograms 

before making a same/different judgement. Since the standard and test stimuli are presented 

successively rather than simultaneously the test is believed to tap visual short term memory. 

DESCRIPTION 

A series of histograms is presented one at a time. The subject must decide if the second 

hb"10gram of each pair is identical with the first. The subject answers by .ccither pressing a button 

labeled "same" or "different" on a two key response box. Task loadings a...-e varied by 

presenting a two bar standard stimulus with the test stimulus in the zero degn:e orientation for 

A-48 
low loading; a four bar standard with the test stimulus in the 90 or 270 degree orientation for 

a moderate task ioading; and a six bar standard witlt the test stimulus in the 180 degree 

orientation for a high task loaaing. 

MATRIX ROTATION TASK (SPATIAL ROTATION SHORT TERM MEMORY) 

PURPOSE 

The Matrix Rotation Task was designed to assess spatial rotation ability. Spatial rotation 

or spatial transformation is one component of spatial orientation. This task also taps short term 

perceptual memory. 

DESCRIFTION 

A series of 5 by 5 cell matrices, are presented at the center of the display. Each matrix 

has five illumii..ated cells. After a pause, the screen blanks and a s~ond matrix is presented. 

The subject must decide if the second matrix is identical with the first. Responses are entered 

on a two key response box. 

A matrix is considered identical only if it is a 90 degree rotation of the previous matrix. 

Successive t.est matrices are always presented in a different orientation. 

MANIKIN TEST <SPATIAL ORIENTATION ROTATION ABILITY) 

PURPOSE 

The Manikin Test was designed to assess the ability to rotate a mental image and related 

transformations. 'l'h...is ability is one measure of tllte-- genera! subdivisi'lns of spatial ability. 

Lohman (1979) called this ability spatial orientation (SO). It requires mental movement of the 

self to view a test stimulus from a different ?erspe<:tive. 

DESCRIPTION 

The Manikin Test consists of a series of 64 trials. On each trial, a human figure (the 

manikin) is displayed on a monitor. The figure will be in four orientations: (1) facing toward 

the subject; (2) facing away from the subject; (3) right side up; or (4) upside down. 

Combinations of all pos~ible pairs of these positions yield a bl0ek of 16 possible orientations. 

The manikin holds a red or blue box in each hand. The manikin stands on a platform 

that matches the color of a box m his hand. The task is to decide which hand is holding the box 

that matches the platform color. Responses are entered on a box with two labeled buttons, one 

"left hand" and one "right hand." During the 64 training tr..als (four presentations of each 

orientation) the subject receives feedback, but no feedback is given dmi.ng the test trials. 

A-49 

-----
PATTERN COMPARISON (SIMULTANEOUS) <PERCEPTUAL SPEED PATTERN 

COMPARISON) 

PURPOSE 

The self-paced pattern comparison test was designed to assess perceptual speed. 

Perceptual speed is one aspect of general spatial ability. The test taps the ability to make 

simultaneous judge:nents about the similarity of two patterns. 

DESCRIPTION 

There are 60 trials in the ;;est. On each trial, a monitor displays two patterns of eight 

dots, side by side. The pattern on the left is the standard. The task is to decide if the pattern 

on the right is identical with the standard. A response on the response box terminates the trial. 

If no response occurs before the end of a 15-second deadline, the trial is terminated 

automatically. Speed and accuracy feedback is given to the subjects during the 10 training trails. 

No feedback is given during the test trials. 

PATTERN COMPARISON <SUCCESSIVE) <PERCEPTUAL SPEED SHORT TERM 

SPATIAL MEMORY) 

PUP.?OSE 

This task was designed to measure the short term spatial memory and perceptual speed. 

The test diagnoses spatial memory, since the subject must store the standard in memory and 

compare it with the test pattern. 

DESCRIPTION 

The test consists of a series of 60 trials. Each trial proceeds as follows: The standard 

pattern is presented for 1.5 seconds. At the end of each period, the screen clears for 3.5 

seconds and the test pattern appears. The test pattern remains on the display until the 15 second 

deadline or if the subject makes a respanse. The task is to decide if the two dot patterns are the 

same or different. 

During the training phase, the subject responds to 10 trials. Response speed and 

accuracy feedback are provided to the subject after each training trials. Feedback is not given 

during the test trials. 

A-50 
\IISUAL SCAl'lllo'ING TASK <PERCEPTUAL SPEED> 

PURPOSE 

This task is based on Neisser's (1963) letter search task that required subjects to search 

for and detect a target embedded in non target items. This test was designed to diagnose the 

ability to perform rapid visual pattern discrimination. 

DESCRIPTION 

The UTC-PAB visual scanning task has two versions. Both versions require the subject 

to scan visually a matrix ot letters (25 rows by 5 columns) in normal reading order (left to right, 

top to bottom) to detect a target letter (e.g., "K") embedded in the matrix. In the lite pen 

version, when the target letter is detected, the subject identifies the exact location of the target 

using a lit pen. In the keyboard version, the subject identifies the row of the matrix where the 

target is embedded with a keypad. 

CODE SUBSTITUTION TASK <PERCEPTUAL SPEED. ASSOCIATIVE LEARNING 

ABILITY) 

PURPOSE 

This task was designed to tap the ability to encode rapidly and evaluate stimuli. 

DESCRIPTION 

The UTC-PAB code substitution task is based on a paper and pencil version of the task 

contained within the Wechsler Adult Intelligence Scale (Wechsler, 1958), and was designed to 

assPss associative learning ability and perceptual speed. A string of nine letters and a string of 

nine digits is presented on a monitor with the digit string positioned immediately below the letter 

string. Each digit corresponds to a given letter. A test letter is then presented at the bottom of 

the screen, below the two c()(l''lg strings. The subject has to decide which digit corresponds to 

that test letter in the coding strings by pressing a key on a numbered keypad. The letter-digit 

associative pairings are the same for the entire test. 

VISUAL PROBABILITY MONITORING TASK <SPATIAL SCANNING/SIGNAL 

DETECTION> 

PURPOSE 

This task was designed to measure the ability to scan and detect visual signals. 

A-51 
DESCRIPTION 

A display of dials is presented to the subjects with instructions to monitor the movement 

of a pointer located below each dial. Under nonnal conditions, the pointer moves randomly 

from one position to anntber to simulate the poL'lter fluctuations on an actual diaL At 

~.ictable intervals, the pc;inter begins to move non-randomly, staying predominantly to the 

left or right half the diaL Titese biases in pointer movement are the targets or "signals" that the 

subject is to respond. The task is to detect the presence of a "signal" and press the correct key 

after the biased dial has returned to the original random pointer movement. 

The test has three task demand levels based on the number of dials that are displayed and 

the discriminability of the signals. A test trial consists of 3 minutes of continuous monitoring and 

only one signal can be present at a time. Signals may occur any time within a trial with the 

restriction of a 25 second minimum separation of ilie offset of a signal and the onset of the 

following signal. Test trials usually contain two or three signals. In conditions where tb.-ee or 

four dials are monitored (Moderate Task Level and High Task Level) the signal display dial is 

randomly selected. 

TIME WALL <TIME ESTIMATION> TASK 

PURPOSE 

The time wall task was designed to measure the ability to estimate the time a moving 

target, moving at a constant rate, will travel a predetermined distance. On each trial the subject 

must integrate the available speed and distance information to anricipate the time the target will 

reach a certain spot on the screen. 

DESCRJPI'ION 

The UTC-P AB time wall task is a nonverbal time estimating task. A small object moving 

at constant velocity passes behind an opaque barrier and the subject must estimate the time when 

the object will reappear. The time wall differs from other time estimation tasks because the 

discrete mediating responses such as counting or tapping are of no direct obvious aid. In this 

version, movement is vertical not horizontal for purposes of visual field symmetry. The barrier 

contains a bold or notch the same shape and size as the object, and the subject estimates the 

moment when the entire notch will be filled. This implementation uses a nominal 10- second 

interval. 

~RV AL PRODUCTION TASK <RESPONSE TIMING> 

PURPOSE 

This task was designed to be used as a secondary task to measure demands placed on 

motor output by a primary task (Michon, 1966). However, it may be used as a stand alone test 

A-52 
to examine The degree to which variables such as drugs, enviromr.ental stress. and toxic 

substances disrupt manual response timing. 

DESCRIPTION 

The subject is required to generate a series of interVals by tapping a fmger key at a rate 

of one to three responses per second. The subject taps with the forefinger of the preferred band 

on a paddle shaped key. The subject must maintain equal intervals by tapping at as regular a 

rate as possible. InterVal response and interVals of less than 10 msec are rejected as spurious 

input. The task is run in 3-minute trials. 

STROOP TEST fiNTERFERENCE SUSCEPI'IBILITY TO RESPONSE COMPETITION> 

PURPOSE 

This test is based on the classic color-word test developed by Stroop (1935). It was 

designed to measure susceptibility to response interference. 

DESCRIPTION 

Both color and non-color words are presented one at a time on a monitor. All words are 

displayed in red, blue, or green and the subject is must press a color coded key that corresponds 

to the color that is presented. 

Three versions of this test are available for selection and each is designed to produce 

different response time performance. 

The following is a brief description of the three test versions: 

1. The control Version of this test contains three possible stimuli. This version of 

the test is intended to be used with the Interference Version; however, it may be 

used by itself as a choice reaction r.me task. 

2. The Interference Version contains six CWI (color-word incongruent) stimuli. 

This version represents the usual interference condition found in the Stroop 

color-word test. 

The Combined Version used six CWI and six NW (neutral words) stimuli. This 

version of the test represents the accepted procedure that is employed in the 

examination of response interference. That is, stimuli that are free of response 

interference (e.g., NW) are presented with those tbat produce maximum 

interferences (e.g., CWI). The difference in reaction time between CWI and NW 

shows response interference where such factor as stimulus encoding and response 

generation bave been equated. 

A-53 
DJCBm'IC YSIINJNG TASK <AUDITORY SELECTIVE ATTENTION> 

This test was designed to evaluate auditory selective attention. 

DFSCRIPI'ION 

Subjects must attend to a list of letters and digits that is presented to one ear while trying 

to ignore similar information being presented to the other ear. The stimuli are produced by a 

computer controlled speech synthesizer and are presented over dual channel headphones. 

UNSTABLE TRACKING TASK <MANUAL RESPONSE CONTROL> 

PURPOSE 

This task was designed to measure rapid and accurate manual responses. 

DESCRIPTION 

A monitor displays a fixed target area at the center. A cursor moves vertically from this 

target while the operator attempts to keep the cursor centered over the target via rotary 

movement of a control knob. Three reliably different demand levels have been established by 

Shingledecker (1984), based on two tracking performance measures (average absolute tracking 

error and number of control losses) and a subjective measure (task difficulty ratings). 

MEMORY SEARCH-TRACKING COMBINATION IT1ME SHARING ABILITY) 

PURPOSE 

This dual task combination was designed measure time sharing ability; that is, the ability 

to perform two tasks concurrently. 

DESCRIPTION 

This is a dual task paradigm involving unstable tracking and the Sternberg Memory 

Search Task as employed by Wickens and Sandry (1982). Subjects must track with their left 

band and respond to the memory search stimuli with their right hand. 

At the beginning of each trial, the subject is shown the positive set of the Sternberg task, 

as under single task conditions. This display is erased and the trial begins 2 seconds later. 

Subjects are told to respond qcickly and accurately and that both tasks are equally important. 

A-54 
MATCRJNG TO SAMPLE <SPATIAL MEMORY PATTERN RECOGNITION> 

PURPOSE 

This task was designed to assess the ability to choore quickly and accurately a test 

stimulus that is identical with a standard stimulus. The test measures short term spatial memory 

and pattern recognition skills. 

DESCRIPTION 

The subject is shown a single 4 by 4 matrix centered on the monitor. The matrix has 

either red or yellow cells. The number of cells of each color is randomly determined for each 

stimulus. After viewing the sample stimulus for a time adequate for committing the stimulus to 

memory, the subject begins the test trial. The test trial consists of two 4 by 4 matrices, side by 

side on the screen. One of the matrices is identical with the previously presented standard 

stimulus, while the other is different. The task is to select the test stimulus that ma:::hes the 

standard. There are 30 trials. 

ITEM-ORDER TEST (SHORT TERM MEMORY RECOGNITION> 

PURPOSE 

The item-order test was designed to examine the ability to recognize strings of letters as 

either the same or different. Error rates produced from this test should reflect short term 

memory recognition. 

DESCRIPI'ION 

In the item-order test, the subject is presented a target string of 7 consonants on a 

monitor. The target string is displayed for 2 seconds and then the screen goes blank for 2.5 

seconds. Immediately following the blank display, a new string of letters is presented. The 

second letter string is the test string. The subject must decide if the test string is identical with 

the target string. Subjects make their responses by pressing one of two buttons, labeled "same" 

or "different." The test string has three possible relationships to the target string: (1) the two 

strings are identical, (2) the same letters are in the two strings but the letters are in a different 

order, or (3) the two strings have different letters. A single target string-test string pair forms 

one trial. The test has 40 trials. The dependent variables are response accuracy and response 

latency. 

PUBLISHER! AGENCY 

Armstrong Aeromedical Research Laboratory 

Human Systems Division 

Wright-Patterson AFB, OH 45433-6573 

A-55 
ADMINISTRATION 

The time required would depend on the number of sub-tests used. 

MS-DOS, mM-PC compatible microcomputer. 

pgerlnp; 

This would vary with the number of sub-tests used. 

RELIABILITY 

The reliability of the complete battery is not available. 

Not available 

VALJDfl'Y 

Not available 

NOitMS 

Not available 

SCORING 

Not available 

SUMMARY 

The sub-tests were selected based on two dimensions thought to be critical in the effects 

of drugs on cognitive performance: (1) the stage of processing most markedly affected by task 

demands; and (2) the requirement to attend selectively to 4ifferent sources of information. 

There are six sub-tests in the UTC-PAB designed to measure the desired cognitive 

functions: (1) Perceptual Input, Detection, and Identification - visual scanning task, visual 

probability monitormg task, pattern comparison (simultaneous), and four-choice serial reaction 

time; (2) Central Processing - auditory memory search (memory search tasks), continuous 

recognition task, code substitution task, visual memory search (memory search tasks), and item 

order test; (3) Information Integration/Manipulation- Linguistic/Symbolic - linguistic processing 

task, two-column addition, grammatical reasoning (symbolic), mathematical processing task, and 

A-56 
grammatical reasoning (traditional); (4) Information Integration/Manipulation-Spatial Mode -

spatial processing task, matching to sample, time wall, matrix rotation task (spatial processing 

task), manikin test, and pattern comparison (successive); (5) Output/Response Execution -

interval production task, and unstable tracking task; and (6) Selective/Divided Attention-dichotic 

listening task, memory search/unstable tracking combination (Sternberg-tracking combination), 

and Stroop test. 

• Advantages 

Minimum hardware requirements 

• Disadvantages 

None noted 

REFERENCES 

Baddeley, A. D. (1968). A 3-minute reasoning test based on grammatical transformation. 

Psychonotnic Science, 10, 341-342. 

Carter, R. C., Kennedy, R. S., & Bittner, A. C. Jr. (1981). Grammatical reasoning: A stable 

performance yardstick. Human Factors, 23, 587-591. 

Craik, F. I. M., & Tulving, E. (1975). Depth of processing and the retention of words in 

episodic memory. Journal of Experimental Psychology: General, 04, 268-294. 

Hord, D. J. {1982). An EEG predictor of performance decrement in a vigilance task. (Tech. 

Rep. No. 82-2) San Diego: Naval Health Research Center. 

Keele, S. W., & Hawkins, H. L. (1985). Explorations of individual differences relevant to 

high level skill. Journal of Motor Behavior, 14, 3-23. 

~Cennedy, R. S., Dunlap, M. B., Jones, N. E., Lane, N. E., & Wllkes, R. L. (1985). Portllble 

human assessment battery: Stability, reliability, factor structure, and correlation with te~ts 

of intelligence. Final Tech. Rep., National Science Foundation. 

Kennedy, R. S., Wilkes, R. L., Lane, N. E. & Hamick, J. L. (1985). Preliminary evaluation 

of a tnicro-based repeated measures testing system. Essex Orlando Tech. Rep. 

EOSR-85-1. 

Lohman, D. F. (1979). Spatial ability: A review and reanalysis of the correlational literature. 

(Tech. Rep. No. 8), Stanford, CA: Aptitude Research project, School of Education, 

Stanford University. 

Michon, J. A. (1966). Tapping regularity as a measure of perceptual motor load. Ergonomics, 

9, 401-412. 

A-57 
Neisser, V. (1963). Decision-time without reaction-time: Experiments in visual scanning. 

American Journal of Psychology, 76, 376-385. 

Perez, W. A., Masculine, P. L., Ramsey, E. G. & Urban, K. E. (1987). Unified Tri-Services 

Cognitive Performance Assessment Battery: Review and methodology (U). 

(AAMRL-TR-87-007) Wright-Patterson, AFB, OH: Armstrong Aeromedical Research 

Laboratory. 

Posner, M. I. & Mitchell, R. F. (1967). Chronometric analysis of classifications. 

Psychological Review, 74, 392-409. 

Seales, D. M., Kennedy, R. S., & Bittner, A. C. (1980). Development of performance 

evaluation tests for environmental research. 

Shingledecker, C. A. (1984). A task battery for applied human performance assessment 

research. (Tech. Rep. No. AFAMRL-TR-84-071), Wright-Patterson AFB, OH: Air 

Force Aerospace Medical Research Laboratories. 

Stroop, J. R. (1935). Studies of interference in verbal reactions. Journal of Experimental 

Psychology, 18, 643-662. 

Wechsler, D. (1958). The measurement and appraisal of adult Intelligence. Baltimore: The 

Williams and Wilkins Co. 

Wickens, C. D. & Sandry, D. (1982), Task-hemispheric integrity in dual task performance. 

Acta Psychologica, 52, 227-247. 

A-58 
APPENDIXB 

Figures Plotting Age, Flight Time, and Accidents 

Golaszewski, 1983 
t>:l 

I 

,_. 

70 

60 

50 

i 'Ill 

11 

] i 30 

20 

10 

I!J. 

~ 

+--

1!J76·1!J80 Class IU l»llots 

Aeeldents per 100,000 Recent t11ght Houa'S 

Golaszewski (Figun 1) 

0 1------------+----------~~----------+---------~~~---------:~ 0-20 21-50 51-100 101-400 

lbccnt Flight Th11e Categories 

-17-19 

- .. - 20-29 

- - ·- - 30-39 

- ·- 40-49 

~o-- S0-59 

- ~- 60-69 

- - 6- - 70&0ver 

-o- All Ages 
;i 

bl I I 

N 

70 

I 

60 

I 

50 i 

40 •. 

I 

30 I 

• 

20 + 

10 

A 

• 

• 

. 

-

........ 

• 

1976·Ul80 Class 1,11, and Ill Pilots 

Aec:ldents per 100,000 Reeent Flight Houn 

Golaszewski (Figure 2) 

• 

• 

• 

• 

0... ........ •• 

"-.~ ......... o-. ~' •··· 

.,_ _____ 

....... .,.....~--.-~ ... ~-c ...... _ .... 

_.lf"'L...._ 

·--~ 

0 +----------r----------+----------~----------+-----------1 

0·20 21-50 51-100 101·400 >400 

Recent Flight Time Categories 

I 

--17·19 

1-.... - 20·29 

. . ... . 30-39 

1 - •-- 40-49 

1 --o- 50·59 

1-~-60·69 

1 . . -A· • 70&0ver 

I - o- All Ag,es 
'f 

w 

70 

60 

50 

1976·1980 Closs III Pilots 

Accidents per 100,000 Recent Flight Hours 

Golaszewski (Figure 3) 

~40 ... 

! 

ll' 30 ~ . .. .. -. .. ._ -..... ..... 20 . 

-------· _..-Q 

. ,. ..... . -- ,..-.. ...... ·· ........ ._ 

------- .... --~~ -~ ~- - - -. . --~·---

··--- - -

~ ........ -:-c....O... - - - ______ --

-=-....:::... ~- - :-. ___ -- •• -----

-

r • -

----~ • -

--~ -a-_ -cf------

10 J--------. 

0 -·~--------1----------r---------+--------~~----====;_------~ 1~19 20-29 30-39 40-49 50-59 60-69 

Age of l'ilot 

>70 

Reeent Flight Time 

Categories 

--0-20 

- +-- 21-50 

- . •· - 51-100 

- .0- 101-400 

---IJ->400 

-~-All 
70 

80 

50 

'f ~ 40 

..... 1i lao 

20 ! ... . . 

10 ~-

0 

17-19 

19'76·1'80 Closs 1,11, and Ill Pilots 

Aeeldents per 100,000 Recent Flight Hours 

Golaszewski (Figure 4) 

/ 

-------------------1 ................ . ..... ······ ---<> ~ •••••• A • • • • • • • • - --

- - -o- ~·-·-._.._ - - .. -- . ---- .. ---= ==' ~--·-·-

----~---~~----~- 0 

20-29 

-o-I ?=- ~ ~ -l 

30-39 40-49 

Age of l'ilot 

50.S9 60-69 >70 

Recent Flight Time 

Categories 

--o-zo 

- ... - 21-;50 

• • .... • !'1·100 

- ·- 101-400 

-o-- >400 

- -<>- -All 
35 

30 _, 

~~------"---  

1976·1!180 Closs Ill Pilots 

Accidents per 100,000 Recent Flight Hours 

Golaszewski (Figure 5) 

A 

0 +----------1----------4-----------~--------~--------~ 

0-100 10f-500 501-1000 1001-5000 >5000 

Total Flight Time 
40 

35 

30 

;i 

25 

"' I J a- 20 

15 

10 

5 -

0 

• 

lf7'·1980 Class 1,11, and Ill Pilots 

Acelde•ts per 100,000 Recent Flight Hours 

Golaszewski (Figure ~ 

• 

• 

• 

• 

A 

'A 

• 

tt::: A- ___ _ 

'=~:' .;...z: . - - • -... .. ...... o- ..._ ........ .. .. :.....- .. _ ~ .. . -- ---~ // -----="'--~ 

<1' 

0.100 101·500 501·1000 

Total Flight Time 

r. • 

- ·...:. "0 

1001·5000 >5000 

tt--17-19 

- + -20·29 

- - ... - 30-39 

- ·- 40·49 

-o-- 50-59 

- ~ -60-69 

- - A- - 70&0ver 

- o- All Ages 
'f 

..... 

35 

30 

25 

~ 20 

I 

~·· 15 

10 

5 . 

....... _ 

... -...... 

1976-1980 Class Ill Pilots 

Accidents per 100,000 Reeamt Flight Hours 

Golaszewski (Figure 7) 

I 

I 

I 

I 

I 

, 

I 

I 

...... -~'::::.--....,.. · .... ~-c:: __ ...__ ~I _.. 

,.,.. """' .. ....... .. .. .. -- --<>- - - - ......... ~ -- -· .. ....., .. A .. .. .. .. .. -._ ...._, • • ::-'"' ..o:W 

....... ............... --....... .:.-:---.. """' A -·-·-·---.. - • • • • • "'"()- .AJ =- - .. .......... :-:.~...,._--~ _,. 

--- • / . . _...... 0 

/ 

0+------+-------+------+------+-----~----~ 

17-19 20-~9 30-39 40-49 

Age or l'ilot 

50-59 60·69 >70 

Total Flight Time 

Categories 

-0.100 

- + -101·500 

• • .... • 501·11100 

- ·- 1001·5000 

-o--.sooo 

- .o- - ..... 
b:l 

I 

00 

40 

35 ~-

30 

;i 

25 

1!)76·1980 Class 1,11, and Ill Pilots 

Accidents per 100,000 Recent Flight Houn 

Golaszewski (Figure 8) 

I 

I 

I 

I 

I 

• I 

120 

I 

I 

I 

.. ) 

15 

10 

--------"" .·· ____ ............ " .. .....___ -- .... ..._..._ --...--- ...... ..._ ... . . ·"'- . . . . . ..... . -- -....: :.._- ......... " ....... ·- - - ~ __ ...... 

5 ·---------~....---=-----------·- ..&::: --o- - ~ CJ. ----~ 0 

0 

0 +---------+---------4---------+---------4---------~--------~ 

1~19 20.29 30-39 40-49 

Age oCI'ilot 

50· 59 60-69 >70 

Tolll Flight Time 

C.tcgoriea 

• 0.100 

- .. -101·100 

• • ". • "1·1000 

·- ·- 1001-SOIIO 

--a-.,... 

- o- -All 
t>l 

I 

"' 

70 

60 

50 

~40 

1i 

"" :!' 30 

-. 

--

• 

11»7'·1!180 Class Ill Pilots 

Accidents per 100,000 Recent Flight Houn 

Golaszewski Figure !I 

• 

• 

•........• 

• 

~1 -~ 

10 

:::: 

-~ - - - ~ . ~ -

- • - • - • - • - • :.: ·------· • • • • • • • - • ~ 

-~ --------- =- ::0-- - -~ ~ -· 

... 

0+------r------r-----,_-----+------+-----~ 

1~19 20-29 30-39 40-49 

Age of Pilot 

50.. 59 60..69 >70 

Recent and Total Flight 

Time Categories 

• >50&>1000 

- .... - >50&<=1000 

•• •· • <=50 & >1000 

- +- <=50 & <•1000 

-o--AII 
100 

90 

80 

70 

! 60 

b:l 

I 

,_. 

0 i 60 

~ 

.{!! 40 

30 

20 

10 

0 

17-19 

• 

• 

• 

1976-1!180 Closs 1,11, and Ill Pilots 

Accidents per 1001000 Recent Fllglat Hours 

Golaszewski (Figure 10) 

• • 

••• 

. . . . __,. .. .. ,.. ~ 

;::,;-._----.$:' ::-_:-.-.-.-.-.-.-.-.-::..:: V'/··· ... • 

+ - r .... _ -t • 2 a: ,... -,\: =-= c 0 

20-29 30-39 40-49 

Age ofl'llot 

50-59 

- . - 60-69 >70 

Recent and Total Flight 

Time Categories 

• >50&>1000 

- ... - >50 & <•1000 

- • •· • <•50 & >1000 

- ·- < .. 50&<=1000 

--o--- All 
I. 

I 

APPENDIX C 

Topical Bib6ograpby of Aging, Medical Variables, and Pilot Performance 

EdwinJ. Kay 

Lehigh University 
i 

I 

I 

I' 

'. 

' 

SECTION 

CONTENTS 

APPENDIXC 

PAGE 

Acceleration Toleration • • • • • • . • • . . • . • • • . . . . . • . • • • . . . . . . . . . . . • . C - 1 

Alcohol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C - 1 

Cardiovascular Epidemiology . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . c- 1 

Epidemiology of Disqualification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... C-3 

Pitiless . . . . . . . . . . . . . . . . . . . . . . . . . . . ~ . . . . . . . . . . . . . . . . . . . . . C - 4 

General Cardiovascular . . • • • . • • . . . • . . • • , • . . . . • • • • . . . . • . . . • • • • . C - 4 

General Epidemiology . . . . . . . . . . . . . • . . . . • • • • . . . . . . . . • . . . . • . . . C - 4 

Hearing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C - S 

Neurological • • . . . . • ; . . . . . • • . . . . . . . . . . . . . . . . . . . • • . . . . . . . . . C - S 

Prediction of Incapacitation . . . . . . . . . . . . . . . . . . . . . . • . . . . . . . . . . . . . C - S 

Respiratory Diseases • • • • • • • . . . • . . • • • • • • . • . • • • . . . . • • • • . . . . • . . . C - 6 

Vestibular" ................................................ C - 6 

Vision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C - 7 
ACCELERATION TOLER.<\ TION 

Suvorov, P. M. FJ!ect of age, occupalion, and physical training on human tolerance to longterm acceleration. Foreign Technology Div., Wright-Patterson AFB, OH. 16 Aug 89. !lp. 

Trans. ofKomischeskaya Biologiya i Meditsina, (USSR) n2 p62-66 1968, by Marilyn Olaechea. 

The effect of the age, occupation and physical training on the human tolerance to long 

term accelerations was investigated. The lowest tolerance was found in the test subjects 

of the age range of 20-24 while the highest in those of 30-34. The test subject of 40-49 

showed a decreased tolerance to accelerations. 

ALCOHOL 

Morrow, D., Leiter, V. & Yesavage, J. 71lt injluer.ce of alcohol and aging on radio 

communication duringfliglu. Aviat. Space Environ. Med. 1990 Jan. 61(1). P 12-20. 

Alcohol and age impaired communication-based and overall flying performance during 

and immediately after drinking. Alcohol and age cumulatively impaired performance, 

since older pilots were more impaired by alcohol. Moreover, overall performance was 

impai!ed for 8 h after reaching 0.1095 BAC. 

CARDIOVASCULAR EPIDEMIOLOGY 

Booze, C. F., Pidkowicz, J. K., Davis, A. W., & Bolding, F. A. Postmortem coronary 

alherosclerosis findings in general aviazion accident pilot fatalities: 1975-77. A\oiat. Space 

Environ. Mecl. 1981 Jan. S2(1). P 24-7. 

Autopsies of 764 pilots involved in fatal general aviation accidents during the years 

191S-n were reviewed. Only 595 of the autopsied group had severe coronary 

atherosclerosis. The rate per 1,000 of severe coronary atherosclerosis increased with age 

from 14.5 for ages less than 30, to 89.9 for ages SO years and above. The prevalence 

of coronary atherosc~erosis among the autopsied airmen is less than for the general 

population. 

Booze, C. F. Jr. & Staggs, C. M. A comparison of postmortem coronary atherosclerosis 

findings in general oviazion pilot fatalities. Aviat. Space Environ. Med. 1987 Apr. 58(4). P 

297-300. 

The autopsy reports of 710 pilots involved in fatal general aviation accidents for 1980-82 

were reviewed to appraise the age-specific prevalence of coronary atherosclerosis. Or.ly 

about 2.5" of the pilots had severe coronary atherosclerosis. Prevalence of severe 

coronary atherosclerosis increased with age from 5.8 per 1,000 for ages less than 40 

years to 73.9 for age SO years and above. 

Bruce, R. A. & Fisher, L. D. Exercise-enluuu:ed risk factors for coronary heart disease vs. age 

as criteria for 1flll1llllllory retireJMnt of healthy pilots. Aviat. Space Environ. Med. 1987 Aug. 

58(8). p 792-8. 

Mortality due to coronary heart disease is examined in 4105 asymptomatic healthy men 

of 15 to 80 years of age observed in Seatde wmmunity practice. The proportion of men 

C-1 
of 60-64 years at low risk with a 989ro 3-year survival rate is 16 times that of men of 

S5-59 years at high risk with a 78" survival rate. 

Bugrov, S. A., Kiselev, R. K., Beleda, R. V., Plakhatnyuk, V.I.&. .Artamonov, N. N. Blood 

Lipids and incidena of lipemia in flight perso1Wl. Space Biology and Aerospace Medicine, 

Vol. 20, No. 3, 1986 p 39-43. 

The content of cholesterol and triglycerides was measured in healthy pilots. Over 1500 

subjects were examined and age-related norms of the parameter were established. 

Gray, G. W. Oudiopulmonary screening for high-peifo17111U1Ceftying: selection and retention 

issues. Advisory Group for Aerospace Research and Development, Neuilly-sur-Seine (France). 

1987. 4p. 

Detection methods used in the cardiopulmonary screening of aircrew are discussed with 

reference to candidate selection standards and retention of older experienced pilots. 

Harrison, W. K. & Smith, J. E. Age trends in the cardiovascular dynamics of aircrewmen. 

Aviat. Space Environ. Med. 1979 Mar. 50(3). P 271-4. 

Age trends in the cardiovascular dynamics of 51 aircrewmen were investigated by means 

of noninvasive techniques. A statistically signifiamt (p less than 0.01) decline in the 

ability of their hearts to accelerate blood was found to accompany advancing age. 

Hoiberg, A. cardiovascular disease among U.S. Navy pilots. Interim rept. Naval Health 

Research Center, San Diego, CA. Jul 84. 17p. 

Results showed a direct relationship between cardiovascular disease incidence and age. 

Hoiberg, A. cardiovasculiJr disease among U. S. Navy pilots. Aviat. Space Environ. Med. 

1985 May 56(5), 397-402. 

Aim to determine influen~ of age and occupation on cardiovascular disease (CVD) in 

Navy pilots diagnosed with CVD during 12.5 year period (N = 150). CVD rate increased 

as a function of age. CVD onset occurred, on the average, 3 years earlier for pilots than 

for officers. 

Hoiberg, A. Longitudinal study of cardiovascular disease in U.S. Navy pilots. Interim rept. 

Naval Health Research Center, San Diego, CA. Feb 85. 16p. 

This longitudinal study examined the consequences of <.:anfiovascular disease (CVD) in 

145 U.S. Navy pilots who suffered a CVD incident during 1967-79. The findings 

reflected not only the few CVD cases in this popu!J.tion of 22,245 pilots who served for 

some time from 1967-79, but also the few after-effects of CVD. 

Hoiberg, A. &. Blood, C. Age-spedjfc morbidity among Navy pilots. Aviat. Space Environ. 

Mecl. 1983 Oct. 54(10). P 912-8. 

This study compares the morbidity (hospitalization) rates by age of male Navy aviators 

(n = 22,417) with rates for tltree male control populations: nonpilot aircrew officers (n 

= 9,483), unrestricted line officers (n = 55,593), and staff officers (n = 46,565). 

Aircrew members and pilots have the highest hospitalization ra=:. The highest rates for 

older pilots is for circulatory diseases. 

C-2 
Hoiberg, A. & Burr, R. G. Heallh risks associaled with aircraft model type among U.S. Navy 

pilots. Proceedings of the Symposium: Psychology in the Department of Defense (9th). 

Colorado Springs, Colorado, 18-20 April 1984. 

This study identified the ill health effects (hospitaliV~tions) among U.S. Navy male pilots 

(n == 22,245) who primarily flew one of eight aircraft model types for July 1967 to 

December 1979. Older track pilots had the highest rates for accidental injuries, 

musculosketetal conditions, and infective/parasitic diseases. The highest circulatory 

disease rate was observed for older fighter pilots. 

Jonsson, F. & Sundgren, N. E.ssen.tial hypertension in airline pilots. Aerosp. Med. 1969 Jan. 

40(1). p 70-5. 

Affect of age considered. 

Proper, R. PrelimiMry impressions ofcardiovasculGr jiuu:tion in the study ofphysiologic and 

psychologic aging in professional pilots. Aerosp. Med. 1969 May. 40(5). P 557-60. 

Proper, R. Age-related rlumges in professional pilots as defined by the Klensch-Schwarzer ultr:.-

low freq~ncy ballistocardiogram. Bibl. Cardiol. 1968. 20. P 50-6. 

Scarborough, W. R., Westura, E. E. & Podolak, E. Studies on a small group ofnorrntd test 

pilots with special reference to qUIJIIIitative relationships of age with the ULF ballistocardiogram 

and other cardiovascular measureme111S. Bibl. Cardiol. 1969. 24. P 66-74. 

Underwood-Ground, K. E. Prevalence of coroMry atherosclerosis in healthy United Kingdom 

aviators. Aviat. Space Environ. Med. 1981 Nov. 52(11 Pt 1). P 696-701. 

The coronary arteries of288 aircrew (135 military aircrew, 53 professional pilots, and 

100 private pilots) killed in 210 aircraft accidents were examined to assess the prevalence 

of coronary artery disease (CAD) in four groups in a 2 factor (age and professional vs 

private pilot) design with mean ages 29.1, 29.9, 39.7, and 37.2. There was no 

difference in CAD prevalence in the four groups (p greater than 0.1). 

York, E., Mitchell, R. E. & Graybiel, A. Cardiovascular epidemiology, exercise, and health: 

40-year followup of the U.S. Navy's "1000 avimors•. Aviat. Space Environ. Med. 1986 Jun. 

57(6). p 597-9. 

Beginning in 1940, a study of 1,056 student and instructor pilots lowered previously high 

attrition rates in training by emphasizing both physical and psychological screening. 

After World War ll, when 208 pilots in the group died, followup studies of the survivors 

were conducted in 1951, 1957, 1963, 1969-71, 1977, and 1980-81. In February 1981, 

715 q\lestionnaires were mailed to known survivors, with 500 replies subsequently 

analyzed. Additionally, 114 of the respondents who had previous!} been examined 

during 1969, were again enmined in 1980-81; those individuals were markedly different 

in their lifestyle, particularly in exercising regularly, abstaining from cigarette smoking, 

and drinking alcoholic beverages moderately, as contrasted to 28 aviators also examined 

in 1969 who died in the interim. Healthy lifestyle may alter cardiovascular risk, 

preventing premature death. 

C-3 
EPIDEMIOLOGY OF DISQUALIFICATION 

Dark, S. I. Ouuat:teristics of medically disqualified airline pilots. Federal Aviation 

Administration, Washington, DC. Office of Aviation Medicine. Ian 83. 18p. 

Denial rates for airline pilots increase to the highest rate at age interval 55-59. The most 

significant causes for denial are cardiovucular, neuro-;sychiatric, and the miscellaneous 

caqory. 

Dark, S. 1. Mediallly disqualified airlilll! pilots. Final rept. Performer: Federal Aviation 

Administration, Washington, DC. Office of Aviation Medicine. Jun 86. 18p. 

Rates of airline pilots denied medical certification in 1983 and 1984. Denial rates for 

airline pilots increase to the highest rate at age interval 55-59. The most significant 

causes for denial are cardiovascular, neuropsychiatric, and the miscellaneous category. 

Whitton, R. C. Medical disqualificlJlion in USAF pilots and TUZVigators. A viat. Space. Environ. 

Med. 1984, 55(4), 332-336. 

Displays tables of medical condition and age of 304 USAF persoMel disqualified during 

1980 and 1981. Cardiovascular disease was most common cause (30%) for 

disqualification. 

Nunneley, S. A., Finkelstein, S. &. Luft, U. C. LongirudiMI study on physical performance of 

ten pilots over a ten-year period. Aerosp. Mec1. 1972 May. 43(5). P 541-4. 

GENERAL CARDIOVASCULAR 

Durrer, D. Cardiological aspecrs. of the aging pilot. Aeorspace Med. 1974, 45(4): 438-442. 

Summary of panel discussion of Airlines Medical Directors Association meeting, May 

5, 1973, in Las Vegas. 

Loeppky, 1. A. & Luft, U. C. Worlr capacity, exercise responses and body compo~ition of 

professional pilots in relation to age. Aviat. Space Environ. MecJ. 1989 Nov. 60(11). P 

1077-84. 

Body composition and cardiorespiratory responses during a progressive upright bicycle 

ergometer test were measured in 410 professional male pilots, aged 20 to 68 years. 

Aerobic work capacity (V02max) fell at a rate of 0.25 ml.min-l.kg-1 per year in this 

unique population of healthy, but generally sedentary men. 

Mertens, H. W., Higgins, E. A. &. McKenzie, J. M. Age, altitude, and worlrload effects on 

complex peifo17111l11Ce. Federal Aviation Administration, Washington, DC. Office of Aviation 

Medicine. Sep 83. 18p. 

Fifteen healthy men in each of three age groups, 20-29 yrs, 40-49 yrs, and 60-69 yrs, 

were evaluated regarding complex performance in two altitude conditions (ground level 

vs. 3,810 m). Heart rate decreased slightly at the 3,810 m altitude in the 60-69 yr 

group, but increased significantly at altitude in the two younger groups. Both 

C-4 
epinephrine and norepinephrine excretion rates were highest in the 20-29 yr group and 

lowest in the 40-49 yr group. 

Scheinman, H. Z. Coronary alherosclerosis in military pilots. I. Relationship to flying and 

aviation accidents. Aerosp. Mcd. 1968 Dec. 39(12). P 1348-51. 

Szafran, J. Age differences in till! rale of gain of infomumon, signal drzclion strategy and 

cardiovoscular stOIUS among pilots. Gerontologia. 1966. 12(1). P 6-17. 

GENERAL EPIDEMIOLOGY 

Burr, R. G. & Hoiberg, A. Health profile of U.S. Navy pilots of electronically modified 

aircrqft. Aviat. Space Environ. Mcd. 1988, 59:168-171. 

Compared hospitaliqtion rates of pilots of electronically modified aircraft (n=1063) 

with age-matched sample of pilots of other aircraft (n=2126). Increases of 

cardiovascular disease and alcoholism as a function of age for control group but not 

experimental group. 

Guide, P. C. & Gibson, R. S. An analytical study of the effects of age and experience on flight 

SIJ/ery. Proc. Human Factors Soc. 35th annual meeting, 1991, 180-184. 

Authors plot accidents per number of pilots and accidents per hours flown as a function 

of age. Roughly a replication of Golaszcwsld, with the same limitations. 

Holt, G. W., Taylor, W. F. & Caner, E. T. Airline pilot medical disability: A comparison 

between three airlines with different approaches to medical monitoring. Aviat. Space Environ. 

Mcd. 1987, 58:788-791. 

Cohort of 12,866 pilots studied from 1975 to 1982. Medical losses increased rapidly 

after pilots reach 45, with cardiovascular disease responsible for about half the losses. 

Vlasov, V, V. & Kopancv, V. I. Effect of flying on the health stalUs of pilots in the light of 

epidemiologic dota. Kosm. Bioi. Aviakosm. Mcd. 1990 Jan-Feb. 24(1). P 4-9. (Review). 

This paper gives an analytical review of epidemiological data about the morbidity and 

mortality rate of the flying personnel. Flying personnel differ from the general 

population in their better health condition which manifests as lower morbidity and 

mortality rates in every large group of disease. This better health maybe a result of their 

selection, which makes it difficult to identify relationships between disease and flight 

effects. 

BEARJNG 

Fitzpatrick, D. T. An analysis of noise-induced hearing loss in Army helicopter pilots. Aviat. 

Space Environ. Mcd. 1988 Oct. 59(10). P 937-41. 

Hearing loss is primarily a function of noise exposure as measured by total flight hours. 

Age was found to be a less significant factor; aircraft type had no significant effect. 

C-S 
Schulthess, G. von. SttllistiCill evaluation ofhearing losses in mili:ary pilots. Acta Otolaryngol. 

(Stockh). 1969 Sep. 68(3). P 250-6. 

NEUROLOGICAL 

Marks, E., Zuzhcvich, V., Dvoretski, E. & Mazhentski, M. Age-related changes in the 

electroencephalograms of pilots. Kosm. Bioi. Avialrosm. Med. 1985 Sep-Oct. 19(5}. P 85-6. 

PREDICTION OF INCAPACITATION 

Boone, J.O. FunaioiUJl aging in pilots: an aaminalion of a mathmuztical model based on 

medical dala on general aviGJion pilots. Federal Aviation Administration, Washington, DC. 

Office of Aviation Medicine. 1982. 

Age is not as accurate in discriminating between the sudden incapacitating pathology :md 

nonpathology groups. 

Booze, C. F., Jr. Slllkkn injlight incabacitation in general aviation. Aviat. Space Environ. 

Med. 1989, 60, 332-335. 

Study of CAMI data for 1975-1982. About 3 accidents per 1000 due to incapacitation. 

Results suggest the likelihood of incapacitation increases with age. 

Castelo-Branco, A., Cabral, Sa. A. & Coelho-Borges, J. Comparalive study of physical and 

mental incapacities among Portuguese airline pilots Ulllhr and over age 60. A viat. Space 

Environ. Med. 1985 Aug. 56(8). P 752-7. 

The number of definitive flight incapacitations and deaths among Portuguese airline pilots 

between 1945 and 1983. The rate of incapacities became higher than under age 60, but 

64" of over 60 earninees were absolutely fit for flight duties. 

Froom, P., Benbassat, J., Gross, M., Ribak, J. & Lewis, B.S. Air accidents, pilor experience, 

and disease-related injlight sudden incapacilation. Aviat. Space Environ. Med. 1988 Mar. 

59(3). p 278-81. 

It may be preferable to grant waivers to experienced pilots with an increased incidence 

of disease-related inflight sudden incapacitation than to replace them with novices. 

Overly strict medical criteria may paradoxically increase accident rates. 

Kulak, L. L., Wick, R. L. & Billings, C. E. Epidemiological study of airline pilot 

incapacitation. 1971, Aeorspace Med. 42(6):670-672. 

Rates of career tennination during 11 year period determined as a function of age. Rates 

increase with age, with coronary heart disease playing a major role. Age-specific 

incidence of heart disease lower in pilots than in general population. 

Lane, I. C. Risk of in-flight incapacitation of airline pilots. Aerosp. Med. 1971 Dec. 42(12). 

p 1319-21. 

Martin-Saint-Laurent, A., Lavemhe, J., Casano, G. & Simkoff, A. Clinical aspects ofinjlighl 

incopodiiJiions in commercial avialion. Aviat. Space ENviron. Med. 1990, 61, 256-260. 

C-6 
Studied causes of inflight incapacitation in Air France pilots from 1.968-1988. None 

caused an accident. Incapacitations of a cardiac nature were rarer and less serious than 

those caused by gastrointestinal or neurological disorders. 

Rayman, R. Myocardial i'!farction: an in:flight problem? Aerospace Med: 1974, 45(1):86-89. 

L'l-light myocardial infarction has been a rare event during 1962-1971 in the USAF. 

Rayman, R. & McNaughton, G. Sudden incapacitation: USAF experience, 197()..1980. Aviat. 

Space Environ. Mec!., 1983, 54(2):161-164. 

Authors examine 146 reported cases of sudden in-flight incapacitation in the USAF. Of 

the 17 fatalities, 1 was suspected to be from myocardial infarction. 

Tunstall-Pedoe, H. Risk of a coronary hean attack in the Mrmal popukuion and how it might 

be modified in~n. Eur. Heart J; 1984 Mar. 5 Suppl A. P 43-9. (Review). 

About SO" of heart attacks might cause immediate total incapacitation, rates are such 

that only a very small percentage of fatal accidents could come from this cause. 

RESPIRATORY DISEASES 

Catlett, G. F. & Kidera, G.J. Detection ofrespiwory impalnnent in pilots. Aeros. Med. 1969 

Nov. 40(11). P 1252-7. 

Lategola, M. T., Flux, M. & Lyne, P. I. Spirometric assessment of potential respiratory 

impoinnent in general aviation alnnen. Aviat. Space Environ. Med. 1977, 48(6):508-511. 

Spirometric measurements of 181 male general aviation pilots showed increasing 

spirometric impairment with age and with amount of cigarettes smoked. 

Voge, V. M. & Anthracite, R. Spontaneous pneumothorax in the USAF alrcrew population: 

a retrospective stUdy. Aviat. Space Environ. Med. 1986, 57:939-949. 

Survey of all aircrew in USAF waiver file. The absolute number of occurrences of 

spontaneous pneumothorax decreases with age. 

VFSTIBULAR 

Moser, M. H. & R2nacher, G. R. Medical jiJlws examination of commercial pilots: new 

.criteria for evallllllion ofveslibular test. Aviat. Space Environ. Med. 1982, 53(12) 1215-1219. 

Compensation capacity of the eyes (to rotation of the head) decreases as a function of 

age. 

VISION 

Baisden, A. G., Monaco, W. A. (1983). Distribution of Visll41 Olaracterislics of Naval 

Aviation Personnd. Final Report. Naval Aeorospace Medical Research Lab, Pensacola, FL. 

With increasing age there are decreases in vist.al acuity accomodative amplitude, 

increases against-the-rule astigmatism and myopia, and stability in fusion-related 

variables and intraocular pressure 

C·7 
E!worth, C. L., Larry, C.&. Malmstrom, F. V. Age, deg7f.llkd viewing enviro11Fr.entS, aNi the 

speed of fXC~on. Aviat. Space Environ. Med. 1986 Jan. 57(1). P 54-8. 

The time to accommodate from a near to infinity target varied as a function of age, room 

illumination, attd the distance of the near-reading task. During ideal. conditions, older 

subjects could accommodate nearly as quickly as the younger subjects; however, during 

degraded viewing conditions, the accommodation time for older subjects L'lcreased as 

much as tenfold. 

Morris, A. & Temme, L. A. Time Required for U.S. Navy Fighter Pilots to Shift Gaze and 

lde111ifj Near fOIIi Far Targets. Aviation, Space, and ~=nvironmental Medicine, 1989, v60 

pl085-1089. 

The speed with which 163 U.S. Navy fighter pilots can shift tl<eir line of sight and 

discriminate high contr...st targets was measured. Both Far-to-Near and Near-to-Far times 

significa.'ltiy slowed with age, the difference due to the oldest subject (44 years of age). 

Sekuler, R., Kline, D. &. Dismukes, K. Aging and Visual Function of Military Pilots: A 

Review. National Research Council, Washington, DC. Committee on Vision. 

Temme, L. A. & Moms, A. Speed of Accommodation and Age. Optometry and Vision 

Science, v66 n2 pl06-112 Feb 89. 

The time needed to change accommodation was measured in 65 U.S Navy fighter pilots 

whose age ranged from 24 to 44 years. The speed of accommodative change, far-to-near 

(FN), slowed with age but near-to-far (NF) did not. 

Vola, J. L., Cornu, L., Carruel, C., Gastaud, P. & Leid, J. Age a1lli photopic and mesopic 

visual acuity. I. Fr. Ophtalmol. 1983. 6(S). P 473-9. 

Visual acuity at high luminance (100 cdrn2) and at low lumir.ance (0.8 cd!l'.2} was 

measured in normal subjects aged between 20 and 50 years. Low lumina.'lce acuity 

decreased with age whereas high luminance acuity remained unchanged (20/20).