DOT/FAA/AM-00/28

Larry L. Bailey

Linda M. Peterson

Kevin W. Williams

Richard C. Thompson

Civil Aeromedical Institute

Federal Aviation Administration

Oklahoma City, Oklahoma 73125

August 2000

Final Report

This document is available to the public

through the National Technical Information

Service, Springfield, Virginia 22161.

Controlled Flight Into

Terrain: A Study of Pilot

Perspectives in Alaska

Office of Aviation Medicine

Washington, D.C. 20591

U.S. Department

of Transportation

Federal Aviation

Administration
NOTICE

This document is disseminated under the sponsorship of

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

information exchange. The United States Government

assumes no liability for the contents thereof.
i

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No.

DOT/FAA/AM-00/28

4. Title and Subtitle

Controlled Flight Into Terrain: A Study of Pilot Perspectives in Alaska

5. Report Date

August 2000

6. Performing Organization Code

7. Author(s)

Bailey, L.L., Peterson, L.M., Williams, K.W., and Thompson, R.C.

8. Performing Organization Report No.

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

FAA Civil Aeromedical Institute

P.O. Box 25082

Oklahoma City, OK 73125 11. Contract or Grant No.

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered

Office of Aviation Medicine

Federal Aviation Administration

800 Independence Avenue, S.W.

Washington, D.C. 20591 14. Sponsoring Agency Code

15. Supplemental Notes

16. Abstract

This report presents the results of a survey designed to identify pilot and organizational risk factors of having

a controlled flight into terrain (CFIT) accident in Alaska. The population consisted of commercial (passenger

and freight) Alaskan pilots who operated under Parts 135, 133, 125 and/or 121 Federal Aviation Regulations

(FARs). A 103-item questionnaire was developed covering the following domains: (1) organizational

influences, (2) unsafe supervision, (3) preconditions for unsafe pilot acts, and (4) unsafe pilot acts. Pilots were

pre-coded into one of two groups based on whether their current employer had experienced a CFIT accident

within a five-year period (1992-1997). Response rates across both groups were 20% and although lower than

desired, it was not unusual for surveys of this nature. Survey results revealed that having to fly in marginal

weather conditions was a common experience for all respondents. However, pilots who worked for companies

who had a CFIT accident rated their company's safety climate and practices significantly lower than pilots

who worked for CFIT accident free companies. Based on the survey results and considering the findings of

the Aviation Safety in Alaska report (National Transportation Safety Board, 1995) the following

recommendations were developed to reduce the number of CFIT accidents in Alaska: (1) increase pilot

awareness of CFIT safety-related issues, (2) improve company safety culture, (3) improve pilot training in the

environment in which they commonly fly, (4) improve weather briefings, and (5) eliminate pressure to

complete a flight.

17. Key Words 18. Distribution Statement

Pilot Perceptions, Aviation Safety, Controlled Flight

Into Terrain, Human Factors Accident Classification

System, HFACS, Aviation Accidents, Aviation Risk

Factors

Document is available to the public through the

National Technical Information Service,

Springfield, Virginia 22161

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price

Unclassified Unclassified 49

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

iii

ACKNOWLEDGMENTS

Personnel from the following organizations participated in an inter-agency task force

assembled by the Alaska Region Flight Standards Office: Federal Aviation Administration Alaska Region Flight Standards Division; Civil Aeromedical Institute; University

of Alaska, Anchorage, and the Alaska Field Station of the National Institute for Occupational Safety and Health.

Special acknowledgments go to the following individuals for their contributions to

the successful completion of this research project: Ms. Tara Bergsten, Mr. Gary Childers,

Ms. Sally Glasgow, Mr. Gilbert Glover, Mr. Dan Jack, Ms. Janine King, Mr. Jan

Manwaring, Ms. Patricia Mattison, Mr. Robert Pearson, Dr. Timothy Thomas, and Ms.

Clara Williams.

1

CONTROLLED FLIGHT INTO TERRAIN IN ALASKA:

A STUDY OF PILOT PERSPECTIVES

In 1995, the National Transportation Safety Board

(NTSB) issued the safety study, Aviation Safety in

Alaska, which highlighted two accident types of major consequence: accidents during takeoff and landing, and accidents related to flying under visual flight

rules (VFR) into instrument meteorological conditions (IMC). The report states that accidents related

to VFR into IMC are less frequent but account for a

larger percentage of the fatal accidents, making them

the leading safety problem for Alaskan commuter

airlines and air taxis (NTSB, 1995).

Seeking to address this critical safety issue, the

State of Alaska and the Federal Aviation Administration (FAA) developed several initiatives to reduce

aviation fatal accident rates by 80% by the year 2007.

As part of the overall effort to reduce the number of

fatal aircraft accidents in the State of Alaska, an interagency task force was formed to study pilot perceptions of factors relevant to aviation in Alaska. Efforts

were focused on the procedures and behaviors of

management and employees of Alaskan passenger or

freight companies. For the purpose of this research,

the terms passenger and freight company are reserved

for those companies holding Part 135, 131, 125, and

121 FAA certificates and operating within the State

of Alaska. Major airline pilots, the Department of

Defense pilots, and pilots employed by the state or

federal government were excluded from the study.

The inter-agency task force began with an analysis

of the NTSB aircraft accident database for the period

January 1, 1990, to December 31, 1998. Data regarding probable causes for each Alaskan commercial

aviation accident reported by the NTSB between

1990 and 1998 were reviewed. Accident statistics

revealed that controlled flight into terrain (CFIT)

was a major factor in the fatality rate in aircraft

accidents in Alaska during this period. Of 126 fatality accidents that occurred in Alaska between January

1, 1990, and December 31, 1998, 89 (71%) involved

CFIT. A CFIT accident occurs when an airworthy

aircraft, under the control of a pilot, is flown

(unintentionally) into terrain, water, or obstacles

with inadequate awareness on the part of the pilot

(crew) of the impending collision (Wiener, 1977).

In general use, the acronym CFIT refers to a broad

spectrum of accidents. These include flights operated

under either Instrument Flight Rules (IFR), Visual

Flight Rules (VFR) or during transitions from one

mode to the other. IFR applies to flights conducted

by reference to the aircraft instruments when visibility is reduced. VFR rules apply to flying during which

the pilot navigates by maintaining visual contact

with objects on the surface.

Due to the specific challenges facing Alaskan aviation, CFIT accidents are limited in the current study

to accidents that occurred when aircraft flown under

Visual Meteorological Conditions (VMC) encountered Instrument Meteorological Conditions (IMC)

and subsequently impacted the terrain. VFR into

IMC occurs under the following circumstances: pilots depart for VFR only destinations with the intention of maintaining visual separation from terrain or

water and continue flying toward their destination

after encountering weather conditions that would

normally require flight under IFR. In Alaska, 69 of

the 89 fatal CFIT accidents fall into the category

described above involving VFR into IMC and account for 77.5% of all Alaskan CFIT accidents involving fatalities.

All other accident categories, including but not

limited to mechanical difficulties, pilot operational

error, wind draft or wind shear, runway conditions,

foreign objects, and weather and icing conditions at

take-off and landing, accounted for only 29% of the

fatal accidents between January 1, 1990, and December 31, 1998. Additionally, the majority of serious

injuries are associated with CFIT accidents.

The high fatality rate associated with CFIT events

emphasizes the importance of addressing this type of

accident and examining the associated risk factors. A

substantial reduction of CFIT accidents in Alaska

would reduce the number of commercial aviation
2

fatalities in that state by up to 70%. Understanding

the factors resulting in a pilot flying an airworthy

aircraft into terrain can assist in the development of

appropriate interventions at multiple levels within

the aviation industry and could reduce the number of

commercial aviation fatalities.

The NTSB aircraft accident database identified

Alaskan companies involved in accidents where NTSB

investigators reported VFR to IMC as a contributing

factor in the crash. These companies are referred to in

the remainder of this report as CFIT companies.

Companies without CFIT as an accident causal factor during the same period are referred to as nonCFIT companies. To examine potential differences

between CFIT and non-CFIT companies in Alaska,

a method of comparing pilot perceptions of the

practices, policies, and procedures of their companies

and their company’s pilots was developed. Identification of differences existing between the two types of

companies could heighten awareness of the factors

involved in CFIT.

Geographic, Environmental, Airport and Air

Route Issues

Alaska is a vast state, spanning 365 million acres

and equal to one-fifth the size of the continental

United States. The 49th state is a land of immense

geographic diversity, bordered by two oceans and

three seas, resulting in more than 33,000 miles of

coastline. In the north, Alaska is treeless with tundra,

while the Panhandle is lush with temperate rain

forests. Alaska also contains North America’s highest

peak, Mt. McKinley (20,320 feet). The temperature

between two locations in Alaska may vary as much as

one hundred degrees. Alaska’s large landmass, vast

mountain ranges, flat marshy tundra, and extensive

coastline result in variable climatic zones and weather.

Wide areas of poor flight visibility are common.

Many VFR destinations have no weather reporting

observers or equipment. Pilots base their pre-departure weather evaluations on area forecasts, with inflight updates coming from station agents and what

can be observed from the windscreen of their aircraft.

In the winter, southern Alaska succumbs to long

hours of darkness, and in the far north, night extinguishes day for more than two months. Summer days

are long in the northern latitudes. Aviation companies seeking to benefit by the extended daylight may

assign pilots to lengthy duty periods.

Although over half of the Alaskan population lives

in one of the state’s three major cities, Anchorage,

Fairbanks, and Juneau (Bureau of the Census, 1992),

much of the remaining population lives in remote

villages only accessible year-around by aircraft. Commuters and air taxis serve as the main link between

these villages and regional hubs, transporting people,

goods, and mail. Alaska has approximately 600 published airports and more than 3,000 airstrips

(FAA,1996, Flight Tips for Pilots in Alaska, paragraphs 8-10). These airports and airstrips are served

by 331 scheduled commuter or charter passenger and

freight companies. Sixty-six public airports are

equipped to handle IFR arrivals, with the remainder

accessible only by flights operated in VMC. A high

percentage of flights serving these areas terminate at

airports or landing areas with unlighted runways, and

many have soft gravel or rutted dirt surfaces. Due to

length restrictions, numerous airstrips are limited to

only those aircraft able to make approaches and

landings. In addition, many aircraft are equipped

with floats and land on water surfaces that are visually

challenging due to glare and reflection, in addition to

being susceptible to both wave fluctuations and wind

drafts. Landings under those conditions require special knowledge and skills.

This information presents a picture of Alaska as a

unique state with distinctive geographic and environmental features affecting aviation. From this

uniqueness emerges an operational requirement that

forces pilots to face many difficult decisions about

flying each day.

Human Factors Issues

The 1995 NTSB report investigated the following

issues: the operational pressures on pilots and commercial operators to provide reliable air service in an

operating environment and aviation infrastructure

that are often inconsistent with these demands; the

adequacy of weather observing and reporting; the

adequacy of airport inspections and reporting airport

conditions; the potential effects on safety of current

regulations for pilot flight duty and rest time, applicable to commuter and air taxi operations in Alaska;

the adequacy of the current instrument flight rules

system and enhancements needed to reduce the reliance of Alaska’s commuter airline and air taxi operations on visual flight rules; and the needs of special

aviation operations in Alaska.
3

On the basis of the preceding considerations, researchers determined that

CFIT mishaps in Alaska have

multiple levels of causality.

The concept of multiple levels of causality is a component of the Human Factors

Analysis and Classification

System (HFACS, Weigmann & Shappell, 1998), a

model developed to analyze and classify human

factors associated with aviation accidents.

The HFACS idea that aircraft accidents typically have

multiple levels of causality is

also known as the “Swiss

cheese” model of accident

causation and comes from

Reason’s (1990) work on

causes for human error (see

Figure 1). In 85% of all accidents, human error was

involved. The human error

involvement is not unique

to aviation; it applies to any

industry (Flight Safety

Foundation, 1999).

For an accident to occur,

failures have to occur at several different levels of responsibility. Responsibility

for an accident typically cannot be placed solely on the

pilot because, in the best

case scenario, there should

be a system in place that

would have prevented certain conditions that contributed to the accident. Failures

may be attributed to the following: Unsafe Acts, Preconditions for Unsafe Acts,

Unsafe Supervision, and/or

Organizational Influences.

The HFACS taxonomy defines four levels of causality for accidents, each of which is further subdivided

into specific types of failures. Figure 2 demonstrates the

four categories of the taxonomy and their representative subcategories. (See Appendix A for expanded

definitions.)

Errors

Perceptual

Errors

Skill-Based

Errors

UNSAFE

ACTS

Errors

Decision

Errors Routine Exceptional

Violations

Inadequate

Supervision

Planned

Inappropriate

Operations

Failed to

Correct

Problem

Supervisory

Violations

UNSAFE

SUPERVISION

Substandard

Conditions of

Operators

PRECONDITIONS

FOR

UNSAFE ACTS

Substandard

Conditions of

Operators

PRECONDITIONS

FOR

UNSAFE ACTS

Adverse

Physiological States

Physical/

Mental

Limitations

Adverse Mental

States

Personal

Readiness

Interpersonal

Resource

Mismanagement

Substandard

Practices of

Operators

Resource

Management

Organizational

Climate

Organizational

Process

ORGANIZATIONAL

INFLUENCES

Figure 2: The HFACS taxonomy

Figure 1: The “Swiss cheese” model of accident causation (Reason, 1990).

Excessive cost cutting

Reduction in flight hours

Deficient training program

Improper crew pairing

 Loss of Situational Awareness

 Poor CRM

Failed to Scan Instruments

Penetrated IMC when VMC only

Failures in the

System

Organizational

Factors

Unsafe

Supervision

Preconditions

for

Unsafe Acts

Unsafe

Acts

Accident & Injury  Crashed into side of

mountain

The “Swiss Cheese” Model of Accident Causation (Reason, 1990)
4

The first HFACS level is the Unsafe Act itself. For

example, the pilot failed to scan the instruments at a

critical time during the flight (Skill-Based Error) or

entered instrument conditions unexpectedly (Decision Error) and lost control of the aircraft. Before

those events took place, however, certain preconditions for the unsafe acts had to occur.

A second level in the taxonomy identifies Preconditions for Unsafe Acts, which are events that could

have led to the unsafe act itself. Fatigue (Substandard

Condition of the Operator), for example, could have

led to the pilot’s poor scanning.

The third level in the taxonomy is Unsafe Supervision. An example of a failure at this level would be

inadequate supervision regarding pilot rest requirements and the adverse physiological and mental consequences that could arise from a lack of sleep

(Inadequate Supervision).

Underlying Unsafe Supervision, the fourth and

final HFACS level involves Organizational Influences. Two examples of failures at this level are a

reduction in the training budget (Resource Management) which would eliminate training regarding pilot rest requirements, and an Organizational Climate

that condones working beyond the recommended

normal work schedule. Some studies stress that CFIT

is related to organizational failure (Khatwa & Roelen,

1998; Maurino, 1993; Weiner, 1977).

Using the HFACS taxonomy summarized above, a

survey was devised to assess pilot perceptions of

flying conditions in Alaska and evaluate possible

differences and similarities between pilots employed

by CFIT and non-CFIT companies. These differences could then be examined to formulate recommendations to heighten awareness and reduce CFIT

accidents in Alaska.

METHOD

Questionnaire Development

For the majority of survey items, item development

was based on the taxonomy of the Human Factors

Analysis and Classification System (Wiegmann &

Shappell, 1998; see Appendix A). Survey items were

generated to measure the extent to which pilot respondents agreed or disagreed that various problematic conditions existed within their company. The

majority of the survey questions were structured to

allow respondents to answer on a range from Strongly

Disagree to Strongly Agree, with the option of Not

Applicable. Questions that were not conducive to

agree or disagree ratings used rank order responses; in

some instances, categories required a single selection

(i.e., demographic information). Due to the difficulty in constructing appropriate items for some of

the HFACS domains, different numbers of items

were generated for each of the four levels. In all, the

following categories were created to assess individual

HFACS areas: Unsafe Acts (nine items), Preconditions for Unsafe Acts (20 items), Unsafe Supervision

(six items), and Organizational Influences (36 items).

In addition to the items based on the HFACS

taxonomy, several items were included for the collection of demographic information. An additional set

of items was included to measure pilot perceptions of

pilot interactions with FAA personnel and the impact

of certain Federal Aviation Regulations (FARs) on

flying in Alaska. In all, 87 survey items were generated (see Appendix B).

Pre-testing of the Survey Form

The survey was pre-tested by 30 personnel from

several of the Flight Standards District Offices in

Alaska. Pre-testing determined the expected time to

complete the survey and whether all of the items were

easily understandable by the general pilot population. Changes, additions, and deletions were made to

several items in the survey based on information

received from the pre-tests.

Survey Population

Prior to development of the survey, personnel

from the Alaska Region Flight Standards Division

assembled a list of flight companies in Alaska. Accident data available from the NTSB were used to

identify the companies involved in one or more CFIT

accidents between January 1, 1992, and September

10, 1998. Of the 330 companies so identified, 301 were

designated as non-CFIT and 29 as CFIT companies.

A list of pilots working in Alaska was generated

using information on pilot medical certification contained at the Civil Aeromedical Institute (CAMI) in

Oklahoma City. All pilots holding a class II medical

certificate and living in Alaska were identified. The

Alaskan Region Flight Standards Division generated a

list of pilots working in Alaska but living out-of-state.

These lists were combined and, when possible, employers were identified using the medical certification
5

database at CAMI. Pilots working for major airlines

were eliminated from the study, as well as military

and government pilots. A total of 3,237 pilots were

identified to receive the survey.

When appropriate employer information was available, pilots were identified as belonging either to the

non-CFIT group or the CFIT group, and the survey

they received was coded as a non-CFIT or CFIT

survey. When employer information was not available, surveys were coded simply as Other. The survey

provided respondents the opportunity to identify

their employer. Specific employer information was

not kept, and surveys did not contain information

regarding the personal identification of the pilots.

Returned surveys could be identified as belonging to

the non-CFIT or CFIT group but could not be traced

to a specific pilot, so the anonymity of the respondent

was assured. A total of 680 surveys were coded as nonCFIT; 186 were coded as CFIT; and 2,371 were

coded as Other.

Survey Procedure

One week prior to the distribution of the surveys,

an introductory letter was sent to the survey population explaining the need for and purpose of the

survey. It gave a broad overview of the types of items

contained in the survey and included a request for

cooperation, particularly for some of the more sensitive issues covered by the survey. The letter ended

with a promise to advise participants of the recommendations developed as a result of the survey analysis. Surveys were mailed the following week. Each

survey was accompanied by a cover letter, similar in

scope and content to the letter of introduction.

Approximately one month following the survey mail

out, a follow-up letter was mailed. The letter encouraged respondents to complete and return their surveys.

RESULTS

Return Rates

Of the 3,237 surveys distributed, a total of 491

were returned, giving an overall response rate of

approximately 15%. While low, this return rate is

similar to, or better than, that obtained for other

surveys in the Alaskan region (Driskill, Wiessmuller,

Quebe, Hand, & Hunter, 1997; Joseph, Jahns,

Nendick, & St. George, 1999; Rakovan, Wiggins,

Jensen, & Hunter, 1999). Of the 680 non-CFIT

surveys, 134 were returned, for a return rate of

approximately 20%. Of the 186 CFIT surveys, 37

were returned, also giving a return rate of approximately 20%. Of the 2,371 Other surveys, 320 were

returned, (approximately 14%).

The last item on the survey requested respondents

to identify their employing flight company. If the

respondent answered this question, and the company

was designated as non-CFIT or CFIT group, the

survey was coded as either a non-CFIT or CFIT

survey. One hundred and thirty-four surveys were

identified as non-CFIT or CFIT using this information. Forty-three surveys were dropped because respondents indicated that they worked either for the

military or for a major airline. After re-coding and

elimination, 234 surveys were identified as nonCFIT surveys, 71 surveys as CFIT surveys, and 143

surveys as Other surveys. Other was not used for

further analysis.

Given the low response rates and small sample

sizes, the reader is cautioned about generalizing the

results of this survey to the broader Alaska population. The lower the response rates, the more uncertainty there is about how well the results will generalize

to the target population. Thus, the reader is advised

to seek confirmation from other sources (e.g., accident reports or articles) before using the results of this

survey to guide policy and decision making.

Survey Item Analysis

The survey items were analyzed in two ways. First,

a descriptive analysis of the item response distributions was conducted for CFIT and non-CFIT company pilots. Next, the response distributions of CFIT

and non-CFIT company pilots were statistically compared using non-parametric Mann-Whitney and chisquare tests.

Graphical displays of item response distributions

were examined to determine the general shape and

frequency of responses. Reported in Appendix B are

item sample size, mean, and standard deviation. An

additional statistic, percentage disagree and percentage agree, was also included to assist the reader in

interpreting item distributions. The percentages were

computed by excluding respondents expressing a

slight opinion (the middle two rating options; Slightly

Agree or Slightly Disagree), and using only respondents who disagreed (combination of Disagree and

Strongly Disagree), or agreed (combination of Agree
6

and Strongly Agree) with an item. By reporting data

in this way, greater attention was given to respondents with more definite opinions.

It was determined that mean scores would not be

the appropriate statistic for comparing responses of

CFIT and non-CFIT company pilots. Instead, a

statistic was needed to determine whether CFIT and

non-CFIT company pilots differed in their overall

response for a given item. For all items employing a

rating scale, the Mann-Whitney test was chosen because it determines whether one population has larger

values than the other, regardless of the shape of the

response distribution. Using the Mann-Whitney test,

19 items yielded significant differences.

Several survey items required respondents to respond in a check-box-like manner or to rank-order

their responses. In these instances, a chi-square test of

significance was used to determine whether pilots

from non-CFIT companies responded differently,

compared with pilots from CFIT companies. The

chi-square test analyzes the distribution of responses

across the number of response options presented. It

uses the sample sizes and the number of response

options to determine the probability that a given

response will be endorsed. This probability is then

compared with the actual percentage of respondents

who endorsed a given response option. Using the chisquare test, five items yielded significant differences.

Significant differences in either the Mann-Whitney

or chi-square tests were found in the following categories of system failures: Organizational Influences,

11 of 36 questions; Unsafe Supervision, 3 of 6 questions; and Preconditions for Unsafe Acts, 5 of 20

questions. As previously mentioned, all categories

were not equally represented. The results appear in

Table 1 for items tested using the Mann Whitney

statistic and in Table 2 for items tested using the chisquare statistic. To aid the reader in interpreting the

results, the percentage of disagreement and agreement are provided, rather than mean scores.

Based on the results presented in Tables 1 and 2 in

the category of Organizational Influences, items 60

and 61, which refer to Resource Management (see

Figure 2 for HFAC categories and subcategories),

show that pilot perceptions differed concerning the

age of their company’s aircraft, with non-CFIT companies having older aircraft (21-25) than CFIT companies (16-20) (item 61). The perceptions of

maintenance provided by a company also differed,

with significantly more non-CFIT company pilots

agreeing that their company provided sufficient maintenance in the areas of basic flight instruments, navigation instruments, and communication equipment,

compared with CFIT company pilots (item 60).

The category of Organization Influences, (subcategory Organizational Climate), indicated differences

in pilot perceptions in the areas of pilot morale, safety

issues, and final pre-departure go-no-go decisions.

More non-CFIT company pilots rated their company’s

safety climate and practices as safety-oriented than

did CFIT pilots, with percentages ranging from 44 to

67% (items 17, 15, 16). Non-CFIT company pilots

also agreed by a greater percentage that their company’s

morale is high (item 11). Significantly more CFIT

company pilots indicated they rely on a flight follower or dispatcher for the final pre-departure go-nogo decisions than did non-CFIT company pilots

(item 63).

In the category of Organizational Influences, (subcategory Organizational Process), differences were

found between the perceptions of non-CFIT company and CFIT company pilots in the areas of safety,

safety awards, and the use of station agents for weather

reporting during pre-departure weather determinations. Significantly more non-CFIT company pilots

considered their company’s safety practices to be

better than CFIT pilot companies (item 66) and

believed they have more opportunity to make safety

recommendations (item 31). The data also reflected

that more non-CFIT company pilots agreed that

safety awards are used to promote safe flying (item

26). Significantly fewer non-CFIT company pilots

reported using station agents for weather reporting

services during pre-departure weather evaluations

(item 67).

In the category of Unsafe Supervision, (subcategory Inadequate Supervision), items 33 and 34

indicated that non-CFIT company pilots agreed that

their company was more cognizant of their frame of

mind and physical fitness than CFIT company pilots.

In the category of Unsafe Supervision, (subcategory

Failed to Correct Problem), non-CFIT pilots agreed

that they were more likely to encounter repercussions

from flying through weather below legal VFR.

Preconditions for Unsafe Acts, (subcategory Substandard Conditions), indicated significantly fewer

non-CFIT company pilots agreed that safety would

improve if the visibility requirement for special VFR
7

Table 1

Statistically significant items based on Mann-Whitney test of significance.

Item Company % Disagree % Agree

Organizational Influences

11. In my company pilot morale is high. NON-CFIT

CFIT

24.9

37.7

49.8

31.9

15. My company does all that it can to prevent accidents. NON-CFIT

CFIT

14.1

15.9

66.5

50.7

16. My company does not cut corners where safety is concerned. NON-CFIT

CFIT

14.1

14.5

64.8

43.5

17. My company considers the safety of its pilots as its top priority. NON-CFIT

CFIT

16.8

17.4

59.7

46.4

26. In my company, safety awards are used to promote safe flying. NON-CFIT

CFIT

63.6

79.3

23.0

12.1

31. My company provides me with opportunities to make safety

recommendations.

NON-CFIT

CFIT

8.5

18.8

73.2

56.5

61. The average age of the aircraft my company uses is_____ years old

(Disagree/Agree does not apply). Range: 1 yr. to more than 25 yrs.

NON-CFIT

CFIT

21-25 yrs.

16-20 yrs.

66. My company's safety practices are (Disagree/Agree does not apply;

higher score is better) range: bottom of industry to top of

industry.

NON-CFIT

CFIT

3.67 mean

3.19 mean

Unsafe Supervision

33. Before each flight, my company makes sure that pilots have the

right frame of mind for flying.

NON-CFIT

CFIT

43.4

53.7

26.5

13.4

34. Before each flight, my company makes sure pilots are physically fit

to fly (e.g., free from the adverse effects of fatigue, medications)

NON-CFIT

CFIT

40.9

52.2

33.6

16.4

68. The first time my company discovered I flew through weather

below legal VFR, they would: (Disagree/Agree does not apply;

higher score is more severe) range: severity of disciplinary action

NON-CFIT

CFIT

1.77 mean

1.53 mean

Preconditions for Unsafe Acts

38. In Alaska, safety would improve if the visibility requirement for

special VFR (conducted under FAR Part 135) was increased to 2

miles when operating under a ceiling of less than 1000 feet.

NON-CFIT

CFIT

51.7

39.7

31.7

47.1

43. In Alaska, during periods of extended daylight, pilot and co-pilot

aircrews fly over 10 hours per day.

NON-CFIT

CFIT

46.6

66.2

34.5

16.9

44. It is hard for Alaskan passenger and freight pilots to maintain a

consistent sleep schedule.

NON-CFIT

CFIT

31.3

46.5

43.6

26.8

45. In Alaska, during periods of extended daylight, a single-pilot

aircrew flies over 8 hours per day.

NON-CFIT

CFIT

49.0

65.7

28.3

13.4

46. Alaskan passenger and freight pilots understand how the time of

day can affect their flying performance.

NON-CFIT

CFIT

8.8

7.1

69.6

52.9

Demographic Information

70. I am ______years old. (Disagree/Agree does not apply) range: 18

years to over 50 years

NON-CFIT

CFIT

46-50 yrs.

41-45 yrs.

71. I've flown in Alaska a total of_______years. (Disagree/Agree does

not apply) range: 1 year to 56 years

NON-CFIT

CFIT

18.56 yrs mean

15.07 yrs mean

74. My total number of commercial rotary hours is (Disagree/Agree

does not apply) range: 0 hours to 17,000 hours

NON-CFIT

CFIT

2970 hrs. mean

1129 hrs. mean

Note: The percentages were computed by excluding respondents expressing a slight opinion (the middle two ratings options:

slightly agree or slightly disagree), and using only respondents who disagreed (combination of disagree and strongly disagree), or

agreed (combination of agree and strongly agree) with an item.
8

(conducted under FAR Part 135) was increased to

two miles when operating under a ceiling of less than

1,000 feet (item 38).

The HFACS category of Preconditions for Unsafe

Acts, (subcategory Adverse Mental Conditions), indicated the following differences in non-CFIT company and CFIT company pilot perceptions: Pilots

flying for non-CFIT companies agreed that they have

a better understanding of how the time of day can

affect their flying performance (item 46). Non-CFIT

company pilots report flying longer hours for both

single pilot and for pilot co-pilot crews (items 43 &

45). Additionally, non-CFIT company pilots report

having greater difficulty maintaining a consistent

sleep schedule (item 44).

Demographic differences were also noted, including:

a greater percentage of pilots who fly for CFIT companies do so under Part 135 rules, have an Airline Transport certificate (item 75), and fly during the months of

November, December, January, and February (item

72). Pilots flying for non-CFIT companies are, on

Table 2

Statistically significant items based on chi-square test of significance.

Item % Non-CFIT Pilots % CFIT Pilots

Organizational Influence

60. My company provides sufficient maintenance on each

of the following aircraft components

Basic flight instruments

Navigation instruments

Communication equipment

86.3

78.6

86.3

69.0

64.8

66.2

63. Who makes the final pre-departure go-no-go decision

Flight follower or dispatcher 12.4 23.9

67. My company uses each of the following weather

reporting services during pre-departure weather

evaluations: Stations Agents 46.2 60.6

Demographic Information

72. I fly in Alaska during the following months

November

December

January

February

85.5

82.9

83.3

84.2

97.2

95.8

95.8

94.4

75. I hold the following airman’s certificates and ratings

Airline Transport Pilot 61.5 80.3

Please indicate the certificate holder you work for:

Part 135 59.0 88.7

Note: The percentages were computed by excluding respondents expressing a slight opinion (the middle two ratings options:

slightly agree or slightly disagree), and using only respondents who disagreed (combination of disagree and strongly disagree), or

agreed (combination of agree and strongly agree) with an item.

average, older (item 70), have more years of experience

flying in Alaska (item 71), and have more hours flying

commercial rotary aircraft (item 74).

DISCUSSION AND

RECOMMENDATIONS

The primary purpose of developing the survey was

to create an instrument with the potential to differentiate between the perceptions of pilots who flew for

CFIT companies and those who flew for non-CFIT

companies. Based on the profile that emerged from

the results, it is clear that this objective was accomplished. The survey distinguished the perceptions of

pilots of non-CFIT and CFIT companies in the

following areas: Organizational Influences, Preconditions for Unsafe Acts, and Unsafe Supervision.

Data analyzed from the study indicate lower CFIT

company pilot agreement in the crucial areas of safety

practices and overall safety climate of their company

than pilot’s of non-CFIT companies. In the event
9

REFERENCES

Bureau of the Census. United States Department of

Commerce (1992). Population count in the 1990

U.S. census: statistical abstract of the United States,

112th ed. Washington, DC: U.S. Government

Printing Office.

Driskill, W.E., Weissmuller, J.J., Quebe, J.C., Hand,

D.K., & Hunter, D. (1997). The use of weather

information in aeronautical decision-making: II.

U.S. Department of Transportation, Federal Aviation Administration, Office of Aviation Medicine, Washington, D.C. Report # DOT/FAA/

AM-97/23. NTIS # ADA340406.

Federal Aviation Administration Alaskan Region (1996).

Flight Tips for Pilots in Alaska, [Online] Available: http://www.alaska.faa.gov/flytoak/flttips1.htm

[1998, December 2].

Federal Aviation Administration Joint Safety Analysis

Team (1999). General Aviation: Controlled flight

into Terrain. Washington, DC.

Flight Safety Foundation. (No date) [Online] Available: http://www.flightsafety.org/priorities.html.

[1999, December 1].

Hunter, D.R. (1995). Airmen research questionnaire:

Methodology and overall results. U.S. Department

of Transportation, Federal Aviation Administration, Office of Aviation Medicine, Washington,

D.C. Report # DOT/FAA/AM-95/27.

Joseph, K.M., Jahns, D.W., Nendick, M.D., & St.

George, R. (1999). A usability survey of GPS avionics equipment: Some preliminary findings. U.S.

Department of Transportation, Federal Aviation

Administration, Office of Aviation Medicine,

Washington, D.C. Report # DOT/FAA/AM-99/

9. NTIS # ADA362193INZ.

Khatwa R., & Roelen, A.L.C. (1998). An analysis of

controlled-flight-into-terrain accidents of commercial operators, 1988 through 1994. Flight

Safety Digest, 165-212.

that CFIT companies create a more positive safety

climate and improve their safety practices, it is likely

that they will also reduce their risk of CFIT accidents.

In addition, the data reflect that among non-CFIT

company pilots, the ranking of a company priority

for safety practices and overall safety climate ranges

from a low of 23% to a high of 73%. This range

indicates room for improvement in safety policies,

procedures and practices of non-CFIT as well as

CFIT companies.

Based on the survey results and considering the

findings of the Aviation Safety in Alaska report (National Transportation Safety Board, 1995) the following recommendations were developed to reduce

the number of CFIT accidents in Alaska: (1) increase

pilot awareness of CFIT safety-related issues, (2)

improve company safety culture, (3) improve pilot

training in the environment in which they commonly

fly, (4) improve weather briefings, and (5) eliminate

pressure to complete a flight.

An assessment to determine the efficacy of the

suggested interventions is essential to ascertain changes

in pilot perceptions in the four HFACS categories,

with an emphasis on exploring changes in safety

practices and safety climate.

The results of this survey research should not be

viewed in isolation of other related research on this

topic. In this case, a number of studies have examined

the issue of why CFIT accidents happen and what can

be done to prevent them. A recent study (General

Aviation Controlled Flight Into Terrain, 1999), conducted by a FAA Joint Safety Analysis Team reviewed

the CFIT records of U.S. general aviation during the

past five years. Many of the current survey’s findings

support the recommendations that emerged from the

safety team, adding further evidence for the validity

of the survey and its value as an organizational assessment tool.
10

Maurino, D. (1993). Efforts to reduce CFIT accidents

should address failures of the aviation system

itself. ICAO Journal, May.

National Transportation Safety Board (1995). Aviation

safety in Alaska: Safety study. (NTSB/SS-95/03).

Washington, DC.

Rakovan, L., Wiggins, M.W., Jensen, R.S., & Hunter,

D.R. (1999). A survey of pilots on the dissemination of safety information. U.S. Department of

Transportation, Federal Aviation Administration, Office of Aviation Medicine, Washington, D.C. Report # DOT/FAA/AM-99/7. NTIS

# ADA361233INZ.

Reason, J. (1990). Human Error. Cambridge, Cambridge University Press.

Weigmann, D.A. & Shappell, S.A. (1998). A human

factors approach to accident analysis and prevention. National Transportation Board of Safety.

Washington, DC: Author.

Weiner, E.L. (1977) Controlled flight into terrain:

System induced accidents. Human Factors Journal, 19.
A1

APPENDIX A

Taxonomy of Unsafe Operations (Shappell & Wiegmann, 1997)

ORGANIZATIONAL INFLUENCES

Resource Management

Human - refers to the management of operators, staff, and maintenance personnel. Issues that directly

influence safety include selection (including background checks), training, and staffing/manning.

Monetary - refers to the management of nonhuman resources, primarily monetary resources. Issues such as

excessive cost-cutting, a lack of funding for proper and safe equipment and resources have adverse effects

on operator performance and safety.

Equipment/Facility - refers to issues related to equipment design, including the purchasing of unsuitable

equipment, inadequate design of work spaces, and failures to correct known design flaws. Management

should ensure that human factors engineering principles are known and utilized and that specifications for

equipment and work space design are identified and met.

Organizational Climate

Structure - refers to the formal component of the organization. The “form and shape” of an organization are

reflected in the chain-of-command, delegation of authority and responsibility, communication channels, and

formal accountability for actions. Organizations with maladaptive structures (i.e., do not optimally match to

their operational environment or are unwilling to change), will be more prone to accidents and “will ultimately

cease to exits”.

Policies - refers to a course or method of action that guides present and future decisions. Policies may refer

to hiring and firing, promotion, retention, raises, sick leave, drugs and alcohol, overtime, accident investigations, use of safety equipment, etc. When these policies are ill-defined, adversarial, or conflicting, safety may

be reduced.

Culture - refers to unspoken or unofficial rules, values, attitudes, beliefs, and customs of an organization.

“The way things really get done around here”. Other issues related to culture included organizational justice,

psychological contracts, organizational citizenship behavior, esprit de corps, and union/management relations. All these issues affect attitudes about safety and the value of a safe working environment.

Organizational Process

Operations - refers to the characteristics or conditions of work that have been established by management.

These characteristics included operational tempo, time pressures, production quotas, incentive systems,

schedules, etc. When set up inappropriately, these working conditions can be detrimental to safety.

Procedures - the official or formal procedures as to how the job is to be done. Examples include performance standards, objectives, documentation, instructions about procedures, etc. All of these, if inadequate,

can negatively impact employee supervision, performance, and safety.

Oversight - refers to management’s monitoring and checking of resources, climate, and processes to ensure

a safe and productive work environment. Issues here relate to organizational self study, risk management,

and the establishment and use of safety programs.
A2

UNSAFE SUPERVISION

Unforeseen

Unrecognized Hazardous Operations - can be viewed as a loss of supervisory situational awareness.

Though somewhat broad, it includes those instances when unsafe conditions or hazards exist yet go unseen

or unrecognized by the untrained or over-tasked supervisor. Selected examples include:

§ Medical conditions such as illness or fatigue that adversely effect performance and

§ The insidious effects of recent life changes such as divorce, death of a family member, legal difficulties,

financial discord, and other personal difficulties.

Inadequate Documentation/Procedures – typical of most systems, particularly new ones where the “bugs”

have yet to be worked out.

§ Accounting for all possible contingencies through technical specifications, instructions, regulations, and

standard operating procedures is an extremely difficult task, at best. As a result, accidents, incidents,

and hazards continue to be a common way of identifying deficiencies in existing documentation, often

after tragedy has struck.

Known

Inadequate Supervision - refers to management of the individual on a personal level. It is expected that

individuals will receive adequate training, professional guidance, and operational leadership, and that all will

be managed appropriately. Unfortunately, supervision may prove inappropriate, improper, or may not occur

at all. Regardless, inadequate supervision is viewed as a function of some action, or purposeful inaction by

the supervisor.

Planned Inappropriate Operations - refers to management of the individual as an asset among many others

(I.e., a “cog in the wheel”). Occasionally, the operational tempo and/or schedule is planned such that individuals are put at unacceptable risk, crew rest is jeopardized, and ultimately performance is adversely

affected. Such operations, though arguably unavoidable emergency situations, are unacceptable during

normal operations.

Failed to Correct Problem - refers to those instances when deficiencies among individuals, equipment,

training or other related safety areas are “known” to the supervisor yet are allowed to continue uncorrected.

Supervisory Violations - refers to those instances when existing rules, regulations, instructions, or standard

operating procedures are not adhered to by supervisors when managing assets. Moreover, that it is considered an “intended” act implies a willful disregard for authority. This is quite different from inadvertently or

unwittingly violating the rules, considered unrecognized hazardous operations as described earlier.

PRECONDITIONS FOR UNSAFE ACTS

Substandard Conditions of Operators

Adverse Mental States - refers to those psychological and/or mental conditions that impact negatively on

performance. Principle among adverse mental states are the loss of situational awareness, cognitive effects

of sleep loss and circadian dysrhythmia, and other psychological diagnoses that effect safety. Also included

in this category are personality traits and pernicious attitudes such as overconfidence, and complacency, and

misplaced motivation.
A3

Adverse Physiological States - refers to those medical or physiological conditions that preclude safe operations.

Particularly important to some operational settings are conditions such as: hypoxia, physical fatigue, illness,

intoxication, and the myriad of pharmacological and medical abnormalities known to affect performance.

Physical/Mental Limitations - refers to those instances when necessary visual or aural information is not

available due to limitations inherent within the sensory system. For instance, in aviation, this most often

includes not seeing other aircraft, power lines and other obstacles due to the size or contrast of the object in

the visual field. Also included are those instances when time to process information or respond exceeds

human capacity (i.e., the individual simply could not physically respond or decide quickly enough to avert the

accident). Finally, there may be time when the individuals inherent aptitude or intelligence is incompatible

with the characteristics or requirements of the task.

Substandard Practices of Operators

Interpersonal Resource Management - was created to account for occurrences of poor crew coordination in

selected occupational settings. Also included are those instances when individuals directly responsible for

the conduct of the operations fail to coordinate and/or supervise operations appropriately. For instance,

within aviation this category is reserved for aircrew who function during the flight as aircraft commanders,

flight leaders, section leaders, etc. Elements of this category differ from those classified as unsafe supervision, since those generally involve individuals in positions of higher authority detached from the direct conduct of operations.

Personal Readiness - two general issues fall under this category. The first is readiness violations which refer

to the disregard for rules, regulations, and instructions that govern the individual’s readiness to perform.

These include such behaviors as violating crew rest requirements and alcohol restrictions. Both may lead to

altered behavioral states and lead to the occurrence of unsafe acts. On the other side of the coin, sometimes

aviators exhibit poor judgement when it comes to readiness, but do not necessarily violate existing instructions or standard operating procedures. For example, running 10 miles before piloting an aircraft may impair

the physical and mental capabilities of the individual enough to degrade performance and elicit unsafe acts.

However, there may be no rules governing such behavior, other than reasonable judgment.

UNSAFE ACTS

Errors

Decision errors - these represent intentional behavior that proceeds as intended, yet the chosen plan proves

inadequate to achieve the desired outcome. Procedural Decision Errors (Orasanu, 1994), or rule-based

mistakes (Rasmussen, 1986) occur during highly structured tasks (If X, then do Y). For example, for most

emergency situations, condition-action rules are available as standard procedures. Procedural decision

errors often occur when a situation is not recognized or is misdiagnosed and the wrong procedure is performed. However, not all situations have corresponding procedures to deal with them. Therefore, many

situations require a choice to be made among multiple response options. Under these circumstances,

choice decision errors (Orasanu, 1994), or knowledge-based mistakes (Rasmussen, 1986), may occur,

particularly when there is insufficient experience or time to determine which option is best. Finally, sometimes a problem is not well understood and formal procedures and response options are not available. In

these situations, the problem is ill-defined and it requires the invention of a novel solution; therefore, individuals must resort to slow and effortful reasoning processes, which may result in problem-solving errors.
A4

Skill-base Errors - these are errors in the execution of a response that has become highly automated. They

are actions that unwittingly deviate from planned behavior, and are generally classified as either attention or

memory failures. Attention failures may take the form of a break down in visual scan, inadvertent operation

of a control, or a failure to see and avoid. Memory failures may appear as omitted items in a checklist,

place losing, or forgotten intentions.

Perceptual Errors - these errors occur when we misrecognize some object or sensory input, for example

misjudging distance, altitude or airspeed. Other types of perceptual errors include visual illusions or spatial

disorientation where perceptions of the world are not congruent with reality.

Violations

Routine Violations - tend to be habitual by nature constituting a part of the individual’s behavioral repertoire

(I.e., driving consistently 5-10 mph faster than allowed by law). Often routine violations are perpetuated by a

system that tolerates such departures.

Exceptional violations - on the other hand, are isolated departures from authority not necessarily indicative of

an individuals typical behavior pattern nor condoned by management (an isolated instance of driving 105 mph

in a 55 mph zone is considered an exceptional violation, not because of its extreme nature, but because its

neither typical of the individual not condoned by authority.)
B1

APPENDIX B

Summary of Results for

Non-CFIT Company Pilots and CFIT Company Pilots

FAA Civil Aeromedical Institute

Human Resources Research Division

Oklahoma City, OK 73125

In collaboration with:

Dan G. Jack

Omni Corporation

Albuquerque, NM 87107

March 15, 2000
B2

Guide to Report Content

Results of the Alaskan Flight Industry Survey are summarized in this report. Presented are item by

item comparisons of responses for non-CFIT company pilots and CFIT company pilots. Included in

the comparisons are item descriptive statistics, response distributions, and significant findings.

Items are grouped based on The Taxonomy of Unsafe Operations (Shappell and Wiegmann,

1997)

Descriptive Statistics

Descriptive statistics apply to each individual item, independent of any other item.

n Number of valid responses for each pilot group for an item.

Mean Average of all valid responses for each pilot group for an item. Means for

selected items are also presented in graphs.

SD Standard Deviation - a measure of dispersion, or spread, of scores around the

mean for each pilot group.

These percentages were computed by excluding respondents expressing a slight

opinion (the middle two rating options; slightly agree or slightly disagree) or

agreed(combination of agree and strongly agree) with an item

Response Distributions

Where appropriate, response distributions are presented in bar graphs to the right of each item.

Distributions are based on the percentage of responses within each response category for each

pilot group. Distributions may not sum to 100 due to rounding.

Response distributions for multiresponse items are reported as percentages in tables. For these

items, percentages will not sum to 100 because respondents were asked to mark all that apply.

Significant Findings

All items were tested for significant differences between non-CFIT company pilot and CFIT

company pilot groups. Chi square tests were used for multiresponse items or nominal level data.

Mann-Whitney tests were used for all other items. The statistical tests were conducted on each

item independently of all other items.

sig. Indicates a finding of significant difference between non-CFIT company pilot and

CFIT company pilot groups.

% Disagree

and

% Agree
B3

Alaskan Flight Industry Survey Results

1.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 215 3.56 1.42 27.9 35.3

CFIT Company Pilots 68 3.65 1.41 26.5 36.8

2.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 219 4.06 1.27 15.1 50.2

CFIT Company Pilots 69 4.26 1.05 7.2 55.1

3.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 189 3.95 1.42 20.1 52.4

CFIT Company Pilots 62 4.06 1.30 12.9 54.8

4.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 220 4.50 1.12 7.3 66.8

CFIT Company Pilots 70 4.61 0.98 4.3 70.0

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

FAA inspectors are courteous when interacting with Alaskan

passenger and freight pilots.

I. ALASKAN PILOT AND FAA OFFICIAL INTERACTION

Descriptive Statistics

Descriptive Statistics

When interacting with FAA inspectors, Alaskan passenger

and freight pilots are allowed to express their point of view.

FAA inspectors use the same evaluation standard for

Alaskan passenger and freight pilots.

In Alaska, FAA inspectors adequately explain the rationale

behind the decisions they make.

8 12 14 14

48

5 10

3

13

19

55

0

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

3 4 9

17

57

10

1 3

9

17

60

10

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

18 15

22

33

2

10

16

10

26

35

1

10

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

6 9 11

23

47

3 1 6

16 22

52

3

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B4

Alaskan Flight Industry Survey Results

5.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 216 4.18 1.22 12.0 51.4

CFIT Company Pilots 67 4.39 0.98 6.0 62.7

6.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 225 3.91 1.63 27.1 42.7

CFIT Company Pilots 71 4.03 1.59 21.1 43.7

7.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 224 4.31 1.60 19.2 54.0

CFIT Company Pilots 71 4.20 1.53 15.5 49.3

8.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 217 3.47 1.49 35.0 29.5

CFIT Company Pilots 69 3.45 1.45 29.0 21.7

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

Overall, the FAA inspectors treat Alaskan passenger and

freight pilots fairly.

If Alaskan passenger and freight pilots followed all aspects of

the FARs, they would not be able to get their job done.

Additional exemptions are needed in the FARs so that the

rules conform to the reality of Alaskan flight operations.

The FARs interfere with the profitability of Alaskan passenger

and freight operations.

Descriptive Statistics

Descriptive Statistics

6 6 9

27

46

5 1 4

12

19

61

1

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

7

20

14 16 20 23

11 10 7

28 24 20

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

7 12 8

19 24 30

8 7 13

23 27 23

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

8

27

14

21 20

9 12 17 16

33

13 9

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B5

Alaskan Flight Industry Survey Results

A. Resource Management

Human

21.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 192 4.45 1.19 9.9 60.9

CFIT Company Pilots 63 4.65 1.08 7.9 68.3

59.

n

Non-CFIT Company Pilots 226

CFIT Company Pilots 69

79.

a. Conducting pre-employment background checks.

n Mean SD

Non-CFIT Company Pilots 206 2.61 1.36

CFIT Company Pilots 58 2.31 1.31

Response Distribution (percent)

Rank the following methods according to how effective each

is in obtaining qualified pilots for your company.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Descriptive Statistics

Passenger and freight pilots can find work flying in Alaska

even if they have prior aviation accidents on their record.

In the last two years, I have received training on weather and

weather avoidance approximately:

Descriptive Statistics

II. ORGANIZATIONAL INFLUENCES

2 8 9

20

46

15

0

8 5

19

51

17

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

27

60

8 4 1

36

55

7

0 1

0

30

60

90

0 to 1 times 2 to 4 times 5 to 8 times More than

8 times

Other

27 25

20 16 12

36

24 22

7 10

0

30

60

90

1=Least

effective

2 3 4 5=Most

effective

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B6

Alaskan Flight Industry Survey Results

b. Reviewing pilot's past accident records.

n Mean SD

Non-CFIT Company Pilots 203 2.16 1.05

CFIT Company Pilots 59 2.37 1.20

c. Conducting check rides.

n Mean SD

Non-CFIT Company Pilots 201 3.21 1.36

CFIT Company Pilots 60 3.53 1.38

d. Conducting face-to-face interviews.

n Mean SD

Non-CFIT Company Pilots 205 3.67 1.23

CFIT Company Pilots 61 3.44 1.27

e. Getting recommendations from other pilots.

n Mean SD

Non-CFIT Company Pilots 207 3.35 1.51

CFIT Company Pilots 61 3.36 1.41

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

Descriptive Statistics

Descriptive Statistics

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

31

37

20

10

2

27 34

20

12 7

0

30

60

90

1=Least

effective

2 3 4 5=Most

effective

Non-CFIT Company Pilots

CFIT Company Pilots

15 15

26 21 23

13 10

18

27 32

0

30

60

90

1=Least

effective

2 3 4 5=Most

effective

7 13 15

35

30

11 10

25

31

23

0

30

60

90

1=Least

effective

2 3 4 5=Most

effective

20

10

20 17

33

11

23

13

23

30

0

30

60

90

1=Least

effective

2 3 4 5=Most

effective

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B7

Alaskan Flight Industry Survey Results

Money

60.

(n = 234) (n = 71)

percent percent sig.

a. Engine 92.3 91.5

b. Basic flight instruments 86.3 69.0 1

c. Navigation instruments 78.6 64.8 1

d. Communication equipment 86.3 66.2 1

e. Flight controls 91.0 91.5

f. Airframe 91.0 87.3

Equipment

61.

n sig.

Non-CFIT Company Pilots 223 2

CFIT Company Pilots 65

62.

(n = 234) (n = 71)

percent percent

a. Global Positioning System unit 70.9 78.9

b. Head-up display 3.0 1.4

c. Ground Proximity Warning System 17.1 15.5

d. Auto-pilot 12.0 16.9

e. Other 32.9 33.8

Non-CFIT

Company

Pilots

CFIT

Company

Pilots

The average age of the aircraft my company uses is_____ Response Distribution (percent)

years old.

What kind of navigational equipment do you use when flying

VMC through low visibility (choose all that apply )?

Non-CFIT

Company

Pilots

CFIT

Company

Pilots

My company provides sufficient maintenance on each of the

following aircraft components (Choose all that apply) :

0

11 15 19 21

33

0

9

18

35

22

15

0

30

60

90

1 to 5 6 to 10 11 to 15 16 to 20 21 to 25 More

than 25

Non-CFIT Company Pilots

CFIT Company Pilots

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B8

Alaskan Flight Industry Survey Results

B. Organizational Climate

22.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 225 4.69 1.14 7.6 68.0

CFIT Company Pilots 70 4.70 1.11 7.1 64.3

Structure

9.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 219 4.03 1.76 26.0 58.9

CFIT Company Pilots 68 3.71 1.46 25.0 42.6

63.

(n = 234) (n = 71)

percent percent sig.

a. Director of Operations or Chief Pilot 27.4 26.8

b. Flight follower or dispatcher 12.4 23.9 1

c. Pilot 91.0 97.2

d. Other 4.3 2.8

In Alaska, if one passenger or freight company does not fly Response Distribution (percent)

because of weather, there is a chance that the company next

door will go ahead and fly.

I am satisfied with the way my company deals with pilot

complaints.

Non-CFIT

Company

Pilots

CFIT

Company

Pilots

Descriptive Statistics

Descriptive Statistics

Who makes the final pre-departure go-no-go decision

(choose all that apply )?

0 7 7

18

45

23

0 7 4

24

40

24

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

17

9 5 10

41

18

7

18 21

12

37

6

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B9

Alaskan Flight Industry Survey Results

80.

a.

n Mean SD

Non-CFIT Company Pilots 210 2.59 0.69

CFIT Company Pilots 63 2.41 0.71

b. Flight follower or dispatcher

n Mean SD

Non-CFIT Company Pilots 196 2.53 0.62

CFIT Company Pilots 58 2.69 0.63

c. Pilot

n Mean SD

Non-CFIT Company Pilots 223 3.84 0.44

CFIT Company Pilots 70 3.86 0.35

d. Other

n Mean SD

Non-CFIT Company Pilots 32 1.69 0.97

CFIT Company Pilots 10 1.70 0.95

Response Distribution (percent)

Note: Response options were reversed to maintain a consistent

direction for scoring.

Company management (i.e., Director of Operations or Chief

Pilot)

Descriptive Statistics

Descriptive Statistics

Rank the following according to who has the greatest

responsibility for pre-departure weather evaluations.

Descriptive Statistics

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Descriptive Statistics

2

45 43

9

3

25

10

62

0

30

60

90

1=Least

responsibility

2 3 4=Most

responsibility

Non-CFIT Company Pilots

CFIT Company Pilots

3

46 47

4 2

34

57

7

0

30

60

90

1=Least

responsibility

2 3 4=Most

responsibility

0 3

9

87

0 0

14

86

0

30

60

90

1=Least

responsibility

2 3 4=Most

responsibility

59

19 16

6

60

10

30

0

0

30

60

90

1=Least

responsibility

2 3 4=Most

responsibility 1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B10

Alaskan Flight Industry Survey Results

Policies

17.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 226 4.39 1.60 16.8 59.7 2

CFIT Company Pilots 69 4.04 1.44 17.4 46.4

23.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 226 3.64 1.42 24.8 37.2

CFIT Company Pilots 68 3.81 1.34 19.1 35.3

24.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 226 4.12 1.25 12.8 46.0

CFIT Company Pilots 70 4.31 0.97 5.7 50.0

Culture

10.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 225 4.11 1.68 24.4 57.3

CFIT Company Pilots 69 3.84 1.48 23.2 40.6

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

Descriptive Statistics

Passenger and freight pilots in Alaska are encouraged to turn

around when the weather deteriorates en route.

My company stays in touch with pilot concerns and problems.

My company considers the safety of its pilots as its top

priority.

In Alaska, passenger and freight companies rarely question a

pilot's decision to turn around due to weather.

Descriptive Statistics

8

17 21 17

32

4 5

15 21 25 26

9

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

3

10

15

27

36

10

0

6

13

31

44

6

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

12 13 7 11

36

21

9 14 12

25

30

10

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

8 9 10 13

28 31

7 10 13

23

33

13

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B11

Alaskan Flight Industry Survey Results

11. In my company pilot morale is high.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 229 3.94 1.73 24.9 49.8 2

CFIT Company Pilots 69 3.30 1.57 37.7 31.9

12. My company appreciates the good work that I do.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 222 4.29 1.56 18.0 58.1

CFIT Company Pilots 69 4.10 1.29 14.5 46.4

13.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 229 2.40 1.60 68.6 15.3

CFIT Company Pilots 69 2.80 1.48 44.9 11.6

14.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 228 2.33 1.61 71.1 15.4

CFIT Company Pilots 69 2.51 1.38 56.5 13.0

Descriptive Statistics

Descriptive Statistics

In my company getting the job done has higher priority than

safety.

My company is more concerned about making money than

being safe.

Descriptive Statistics

Descriptive Statistics

Response Distribution (percent)

15 10 12 14

29

21 16 22 14 16

28

4

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

9 9 6

18

36

23

3

12 14

36

10

25

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

39

30

6 10 8 7

29

16 16

28

9

3

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

41

30

7 7 7 8

30 26

19

12 13

0

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B12

Alaskan Flight Industry Survey Results

15. My company does all that it can to prevent accidents.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 227 4.60 1.51 14.1 66.5 2

CFIT Company Pilots 69 4.17 1.40 15.9 50.7

16.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 227 4.56 1.45 14.1 64.8 2

CFIT Company Pilots 69 3.99 1.38 14.5 43.5

C. Organizational Process

Operations

25.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 210 4.65 1.32 10.5 66.2

CFIT Company Pilots 67 4.78 1.25 9.0 74.6

26.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 165 2.78 1.60 63.6 23.0 2

CFIT Company Pilots 58 2.21 1.32 79.3 12.1

In my company, safety awards are used to promote safe

flying.

Passenger and freight companies in Alaska operate on small

profit margins.

Descriptive Statistics

Descriptive Statistics

Descriptive Statistics

My company does not cut corners where safety is concerned.

Descriptive Statistics

Response Distribution (percent)

5 9 9 11

31 36

4 12 13

20

35

16

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

3

11 10 11

33 32

6 9

22 20

32

12

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

3 7 6

18

38

29

3 6 4

12

46

28

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

21

43

4 10

16

7

31

48

3 5 10

2

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B13

Alaskan Flight Industry Survey Results

64. Indicate the method used to determine your pay.

n

Non-CFIT Company Pilots 192

CFIT Company Pilots 58

65.

(n = 234) (n = 71)

percent percent

a Flat terrain 63.7 62.0

b Open water 47.0 40.8

c Channels, islands and peninsula 39.7 43.7

d Hills 38.9 42.3

e Hills and mountains 68.4 71.8

f. Mountains and mountain passes 59.8 52.1

g Other 8.1 5.6

66. My company's safety practices are (select one):

n Mean SD sig.

Non-CFIT Company Pilots 231 3.67 1.04 2

CFIT Company Pilots 70 3.19 0.97

Procedures

27.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 220 3.80 1.47 26.4 40.5

CFIT Company Pilots 67 4.07 1.47 23.9 50.7

The majority of my flights are flown over the following terrain

(choose all that apply ):

Alaskan passenger and freight companies formally teach

unwritten “rules of thumb” for flying in areas of low ceiling and

reduced visibility.

Response Distribution (percent)

Descriptive Statistics

Note: Response options were reversed to maintain a consistent

direction for scoring.

Descriptive Statistics

Non-CFIT

Company

Pilots

CFIT

Company

Pilots

47 45

1 7

41 45

0

14

0

30

60

90

Base salary By flight hrs By difficulty of

assignment

Other

Non-CFIT Company Pilots

CFIT Company Pilots

4 10

23

42

21

9 6

51

27

7

0

30

60

90

At bottom

of industry

Below

average

Average Above

average

At top of

industry

5

21

15

19

29

11

4

19

4

21

37

13

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B14

Alaskan Flight Industry Survey Results

28.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 222 3.71 1.59 36.0 45.9

CFIT Company Pilots 61 3.66 1.58 32.8 45.9

29.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 186 2.75 1.63 64.0 26.3

CFIT Company Pilots 57 2.93 1.66 59.6 26.3

67.

(n = 234) (n = 71)

percent percent sig.

a. National Weather Service 67.5 67.6

b. Flight Service Station 81.2 87.3

c. Automated Flight Service Station 59.4 60.6

d. Station Agents 46.2 60.6 1

e. Pilot Observations 75.2 74.6

f. Other 13.7 14.1

83.

n

Non-CFIT Company Pilots 219

CFIT Company Pilots 66

Pilot training on how to operate in low visibility conditions is

provided by my company.

Descriptive Statistics

Non-CFIT

Company

Pilots

CFIT

Company

Pilots

Response Distribution (percent)

My company launches weather reporting observation flights to

supplement pre-departure weather services.

My company uses each of the following weather reporting

services during pre-departure weather evaluations (choose all

that apply ):

My company's training program contains an inadvertent IMC

recovery procedure.

Descriptive Statistics

7

29

5 13

36

11 10

21

8 13

41

5

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

24

40

4 5

22

5

19

40

2

12

19

7

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

58

42

53

47

0

30

60

90

Yes No

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B15

Alaskan Flight Industry Survey Results

84.

n

Non-CFIT Company Pilots 223

CFIT Company Pilots 67

Oversight

30. My company conducts formal pilot safety meetings.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 217 3.83 1.67 31.3 50.2

CFIT Company Pilots 66 3.47 1.60 34.8 36.4

31.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 224 4.72 1.27 8.5 73.2 2

CFIT Company Pilots 69 4.19 1.37 18.8 56.5

32.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 199 3.91 1.61 27.6 46.7

CFIT Company Pilots 59 3.56 1.49 32.2 33.9

Descriptive Statistics

Descriptive Statistics

My company requires “re-dispatch” or "re-contact" with the

company when pilots reroute due to weather.

Descriptive Statistics

Response Distribution (percent)

My company provides me with opportunities to make safety

recommendations.

My company's safety meetings focus on hard-hitting safety

issues that pilots face each day.

29 27

71 73

0

30

60

90

Yes No

Non-CFIT Company Pilots

CFIT Company Pilots

12

20

6 12

36

14 12

23 17 12

27

9

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

4 4 5

13

48

25

3

16

9

16

45

12

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

10

18

7

19

31

16

8

24

12

22 27

7

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B16

Alaskan Flight Industry Survey Results

85.

n

Non-CFIT Company Pilots 217

CFIT Company Pilots 68

86.

n

Non-CFIT Company Pilots 214

CFIT Company Pilots 69

A. Unforeseen

Unrecognized Hazardous Operations

33.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 219 3.16 1.57 43.4 26.5 2

CFIT Company Pilots 67 2.70 1.37 53.7 13.4

Response Distribution (percent)

Descriptive Statistics

III. UNSAFE SUPERVISION

My company's safety program includes something like a

safety risk reporting form.

My company's safety program includes something like a risk

management or internal audit process?

Before each flight, my company makes sure that pilots have

the right frame of mind for flying.

36

64

32

68

0

30

60

90

Yes No

Non-CFIT Company Pilots

CFIT Company Pilots

37 36

63 64

0

30

60

90

Yes No

17

26

12 18 21

6

19

34

19

13 10

3

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

significant difference (Chi square) p < .05

2

significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree=Strongly Agree or Agree
B17

Alaskan Flight Industry Survey Results

34.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 220 3.30 1.67 40.9 33.6 2

CFIT Company Pilots 67 2.78 1.38 52.2 16.4

Inadequate Documentation Procedures

35.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 220 4.95 1.15 5.9 85.5

CFIT Company Pilots 70 4.91 1.10 5.7 78.6

B. Known

Inadequate Supervision

36.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 223 4.75 1.25 8.1 74.9

CFIT Company Pilots 69 4.59 1.13 5.8 63.8

Before each flight, my company makes sure pilots are

physically fit to fly (e.g., free from the adverse effects of

fatigue, medications).

Descriptive Statistics

Descriptive Statistics

Response Distribution (percent)

My company's Standard Operating Procedures manual is up

to date.

My company ensures that pilots obtain sufficient training on

new equipment.

Descriptive Statistics

4 4 7 10

48

27

1 4

10

20

45

19

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

19 22

11 15

25

8

16

36

21

10 13

3

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

3 3 5 3

55

30

1 4 4

11

49

30

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B18

Alaskan Flight Industry Survey Results

Planned Inappropriate Operations

37.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 224 4.76 1.24 9.8 73.2

CFIT Company Pilots 69 5.03 1.06 5.8 81.2

Failed to Correct Problem

68.

n sig.

Non-CFIT Company Pilots 202 2

CFIT Company Pilots 64

18.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 230 4.72 1.46 14.8 71.3

CFIT Company Pilots 70 4.53 1.64 20.0 64.3

IV. PRECONDITIONS FOR UNSAFE ACTS

Descriptive Statistics

In Alaska, passenger and freight assignments require flying Response Distribution (percent)

under marginal VMC.

Descriptive Statistics

The first time my company discovered I flew through weather

below legal VFR, they would: (select one )

As a pilot I am concerned about having an accident while

flying.

3

12

4

10

33 38

4

16

7 9

24

40

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

39

50

7 4

55

39

5 2

0

30

60

90

Do nothing Give me a

warning

Place me on

suspension

Fire me

2

8 4

13

45

29

0

6 3

10

45

36

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B19

Alaskan Flight Industry Survey Results

A. Substandard Conditions

38.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 205 3.13 1.84 51.7 31.7 2

CFIT Company Pilots 68 3.65 1.79 39.7 47.1

39.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 215 3.77 1.50 27.4 41.4

CFIT Company Pilots 68 3.88 1.25 17.6 36.8

40.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 226 4.28 1.28 14.2 52.7

CFIT Company Pilots 70 4.49 1.19 10.0 58.6

41.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 225 2.57 1.22 52.0 9.8

CFIT Company Pilots 69 2.38 1.14 62.3 5.8

Descriptive Statistics

In Alaska, safety would improve if the visibility requirement for

special VFR (conducted under FAR Part 135) was increased

to 2 miles when operating under a ceiling of less than 1000

feet.

Descriptive Statistics

Descriptive Statistics

Descriptive Statistics

In Alaska, passenger and freight pilots would feel comfortable

flying VMC in low visibility over flat terrain or water.

Alaskan passenger and freight pilots talk about having to

“push” the weather during their flights.

In Alaska, one seldom sees passenger and freight pilots

“push” the weather at community airports.

Response Distribution (percent)

Response Distribution (percent)

23

28

8 9

16 16 12

28

9

4

29

18

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

8

20

11

20

32

9

3

15 16

29 31

6

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

2

12 8

25

38

14

0

10 9

23

40

19

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

22

30 27

11 10

0

23

39

20

12

6

0

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

1 Agree significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B20

Alaskan Flight Industry Survey Results

42.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 226 2.23 1.14 72.6 6.6

CFIT Company Pilots 68 2.32 1.09 67.6 5.9

Adverse Mental States

43.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 206 3.37 1.69 46.6 34.5 2

CFIT Company Pilots 65 2.66 1.41 66.2 16.9

44.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 227 3.81 1.66 31.3 43.6 2

CFIT Company Pilots 71 3.28 1.54 46.5 26.8

45.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 198 3.17 1.61 49.0 28.3 2

CFIT Company Pilots 67 2.61 1.34 65.7 13.4

Descriptive Statistics

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

Descriptive Statistics

Passenger and freight pilots in Alaska would feel comfortable

flying VMC in low visibility over hills and mountains.

In Alaska, during periods of extended daylight, pilot and copilot aircrews fly over 10 hours per day.

It is hard for Alaskan passenger and freight pilots to maintain

a consistent sleep schedule.

In Alaska, during periods of extended daylight, a single-pilot

aircrew flies over 8 hours per day.

26

46

14

7 6 1

21

47

18

9 6

0

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

10

37

10 9

19

14 15

52

9 8

12

5

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

8

23

11 14

25

19

6

41

11 15 15 11

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

14

35

9

14

19

9

15

51

9 12 10

3

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree 1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B21

Alaskan Flight Industry Survey Results

46.

n Mean SD % Disagree % Agree sig.

Non-CFIT Company Pilots 227 4.58 1.13 8.8 69.6 2

CFIT Company Pilots 70 4.34 0.96 7.1 52.9

69.

n Mean SD

Non-CFIT Company Pilots 226 1.89 0.71

CFIT Company Pilots 68 1.91 0.51

Adverse Psychological States

19.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 231 2.80 1.60 58.9 18.6

CFIT Company Pilots 71 2.87 1.59 52.1 15.5

20.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 230 4.53 1.46 14.8 60.4

CFIT Company Pilots 71 4.63 1.31 8.5 66.2

Descriptive Statistics

Alaskan passenger and freight pilots understand how the time

of day can affect their flying performance.

Compared to other Alaskan pilots with similar flying

experience, the salary that I receive is:

Note: Response options were reversed to maintain

a consistent direction for scoring.

Descriptive Statistics

Descriptive Statistics

Response Distribution (percent)

As an Alaskan pilot, the job that I perform requires flying in

hazardous conditions.

Descriptive Statistics

Over time, being an Alaskan pilot will adversely affect my

health.

2

7 6

15

56

14

0

7 9

31

49

4

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

31

49

20 18

74

9

0

30

60

90

Below the industry

average

At the industry

average

Above the industry

average

23

36

6

16

11 8

23

30

11

21

6

10

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

4

10

5

20

29 31

4 4 8

17

39

27

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B22

Alaskan Flight Industry Survey Results

47.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 230 4.82 1.09 6.1 74.3

CFIT Company Pilots 70 4.93 1.00 2.9 75.7

48.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 225 4.09 1.48 19.6 51.1

CFIT Company Pilots 70 4.10 1.25 17.1 45.7

Physical/Mental Limitations

49.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 229 3.10 1.43 41.5 22.7

CFIT Company Pilots 69 3.33 1.37 33.3 24.6

50.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 227 4.82 1.13 7.5 74.4

CFIT Company Pilots 69 4.90 1.11 7.2 81.2

Descriptive Statistics

Descriptive Statistics

Unless Alaskan passenger and freight pilots stay on top of the

situation, they can soon become overwhelmed with sudden

changes in flying conditions.

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

Alaskan passenger and freight pilots have to fly sometimes

when they are tired.

Boredom is a problem for Alaskan passenger and freight

pilots.

Alaskan passenger and freight pilots have to fly even when ill.

2 4 3

16

49

25

1 1 4

17

47

29

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

6

13 12

17

36

15

1

16

9

29

37

9

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

13

28

20 16 19

3 7

26 22 20 20

4

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1

7 4

15

47

27

1

6 3

9

54

28

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B23

Alaskan Flight Industry Survey Results

B. Substandard Practices of Operators

Interpersonal Resource Mismanagement

81.

a. Delivering the U.S. mail

n Mean SD

Non-CFIT Company Pilots 135 3.83 2.31

CFIT Company Pilots 51 4.00 2.07

b. Company management

n Mean SD

Non-CFIT Company Pilots 156 5.47 1.98

CFIT Company Pilots 55 5.25 2.04

c. Making money for myself

n Mean SD

Non-CFIT Company Pilots 148 4.68 1.99

CFIT Company Pilots 53 4.23 2.02

Descriptive Statistics

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

Rank the following factors based on the amount of

pressure created by each to fly in reduced visibility.

7

38

12 9 9 5 7

13 10

18 22

12 16

6

12

6

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

Non-CFIT Company Pilots

CFIT Company Pilots

1

6

17

9 13 17 15

21

4

9 11 13

7

24 20

13

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

2

13

21

14 13 15 11 11

4

21 17 21

9 9 11 8

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B24

Alaskan Flight Industry Survey Results

d. Tight schedule

n Mean SD

Non-CFIT Company Pilots 155 5.75 1.57

CFIT Company Pilots 53 5.30 1.51

e. Peer pressure

n Mean SD

Non-CFIT Company Pilots 153 4.63 1.75

CFIT Company Pilots 52 4.63 1.94

f. Pride in my ability

n Mean SD

Non-CFIT Company Pilots 156 5.21 1.93

CFIT Company Pilots 55 4.96 2.14

g. Passengers

n Mean SD

Non-CFIT Company Pilots 149 5.56 2.03

CFIT Company Pilots 53 5.62 2.28

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Descriptive Statistics

Descriptive Statistics

Note: Response options were reversed to maintain

a consistent direction for scoring.

Note: Response options were reversed to maintain

a consistent direction for scoring.

Descriptive Statistics

Descriptive Statistics

Response Distribution (percent)

Response Distribution (percent)

0 3 6

14 18

25 20 15

0

8

2

17

28

23

17

6

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

Non-CFIT Company Pilots

CFIT Company Pilots

4 8

12

25

21

12 12

4 5

10

21

15 13 13 17

6

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

1

7

16 15 16 15 13

17

0

16 16

11

16

11 9

20

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

0

13 10 9 7

17

28

17

4

11 8 9 8

15 15

30

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B25

Alaskan Flight Industry Survey Results

h. other reasons for flying in reduced visibility

n Mean SD

Non-CFIT Company Pilots 42 5.79 3.09

CFIT Company Pilots 17 5.35 3.39

Personal Readiness

Please indicate the certificate holders you work for:

(n = 234) (n = 71)

percent percent sig.

Part 135 59.0 88.7 1

Part 133 9.8 4.2

Part 125 3.4 0.0

Part 121 26.9 16.9

51.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 228 4.11 1.50 21.1 49.6

CFIT Company Pilots 69 4.01 1.47 20.3 43.5

70. I am ______years old.

n sig.

Non-CFIT Company Pilots 232 2

CFIT Company Pilots 70

Note: Response options were reversed to maintain

a consistent direction for scoring.

CFIT

Company

Pilots

Non-CFIT

Company

Pilots

Descriptive Statistics

Descriptive Statistics

In Alaska, it is possible to eliminate all accidents caused by

passenger and freight pilots flying into terrain in poor weather.

Response Distribution (percent)

1

5

9

13 12

21

38

1

7

16 14

23

16

23

0

30

60

90

18-25 26-30 31-35 36-40 41-45 46-50 Over 50

24

5

0 2 5

0 2

62

35

000

6

0 0

59

0

30

60

90

1=Least

pressure

2 3 4 5 6 7 8=Most

pressure

Non-CFIT Company Pilots

CFIT Company Pilots

4

17

11

18

30

19

7

13

9

28 29

14

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B26

Alaskan Flight Industry Survey Results

71.

n Mean SD sig.

Non-CFIT Company Pilots 233 18.56 10.38 2

CFIT Company Pilots 70 15.07 10.47

72.

(n = 234) (n = 71)

percent percent sig.

a. January 83.3 95.8 1

b. February 84.2 95.8 1

c. March 87.6 94.4

d. April 91.9 95.8

e. May 95.3 98.6

f. June 95.3 97.2

g. July 94.0 97.2

h. August 93.2 97.2

i. September 97.9 98.6

j. October 92.3 97.2

k. November 85.5 97.2 1

l. December 82.9 95.8 1

73.

a. non commercial fixed wing hours

n Mean SD

Non-CFIT Company Pilots 211 1820 5782

CFIT Company Pilots 65 1354 3842

Descriptive Statistics

Descriptive Statistics

CFIT

Company

Pilots

Non-CFIT

Company

Pilots

I've flown in Alaska a total of_______years (round to the

nearest year ).

I fly in Alaska during the following months (choose all that

apply ):

My total number of non commercial A/C hours flown in Alaska

is:

Mean Years

Mean Hours

1354

1820

1000

1200

1400

1600

1800

2000

15.07

18.56

10

15

20

Non-CFIT Company Pilots

CFIT Company Pilots

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B27

Alaskan Flight Industry Survey Results

b. non commercial rotary hours

n Mean SD

Non-CFIT Company Pilots 79 420 1336

CFIT Company Pilots 27 78 187

74. My total number of commercial A/C hours flown in Alaska is:

a. commercial fixed wing hours

n Mean SD

Non-CFIT Company Pilots 214 7046 6646

CFIT Company Pilots 68 6886 6550

b. commercial rotary hours

n Mean SD sig.

Non-CFIT Company Pilots 80 2970 4195 2

CFIT Company Pilots 28 1129 2611

75.

(n = 234) (n = 71)

percent percent sig.

a. Commercial 64.53 57.75

b. Airline Transport Pilot 61.54 80.28 1

Descriptive Statistics

Descriptive Statistics

CFIT

Company

Pilots

Non-CFIT

Company

Pilots

I hold the following airman’s certificates and ratings (choose

all that apply ):

Mean Hours

Mean Hours

Mean Hours

Descriptive Statistics

78

420

0

100

200

300

400

500 Non-CFIT Company Pilots

CFIT Company Pilots

7046

6886

6000

6500

7000

7500

8000

2970

1129

1000

1500

2000

2500

3000

3500

4000

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B28

Alaskan Flight Industry Survey Results

76. I attend pilot safety meetings of some kind:

n

Non-CFIT Company Pilots 215

CFIT Company Pilots 56

82. My permanent residence is in Alaska.

n

Non-CFIT Company Pilots 232

CFIT Company Pilots 71

A. Errors

Decision Error

52.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 220 4.30 1.17 11.4 56.8

CFIT Company Pilots 69 4.32 1.02 11.6 58.0

53.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 222 4.21 1.29 15.3 52.7

CFIT Company Pilots 69 4.39 1.05 8.7 55.1

Response Distribution (percent)

V. UNSAFE ACTS

It is safe for Alaskan passenger and freight pilots to fly under

low-lying narrow bands of clouds, provided that the visibility is

clear beneath the clouds and it looks clear beyond the cloudy

area.

Passenger and freight pilots in Alaska are more likely to

"push" the weather when aircraft are equipped with modern

navigation equipment.

Descriptive Statistics

Descriptive Statistics

2

12

25

46

15

0

16 18

48

18

0

30

60

90

Weekly Monthly Quarterly Annually Other

Non-CFIT Company Pilots

CFIT Company Pilots

2

9 9

23

49

8

0

12

4

26

57

1

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

2

13 11

21

41

12

0

9 7

29

46

9

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

5 0

95 100

0

20

40

60

80

100

Yes No

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B29

Alaskan Flight Industry Survey Results

54.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 220 3.80 1.38 23.6 38.2

CFIT Company Pilots 67 4.01 1.30 10.4 37.3

55.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 216 4.12 1.36 18.1 51.4

CFIT Company Pilots 69 4.22 1.19 14.5 50.7

B. Violations

Routine

56.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 218 3.06 1.48 45.9 22.5

CFIT Company Pilots 69 2.87 1.28 49.3 15.9

57.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 221 2.59 1.31 59.7 12.2

CFIT Company Pilots 69 2.52 1.22 62.3 8.7

Descriptive Statistics

Descriptive Statistics

Flying under VFR in low visibility conditions over hills and

mountains is a common experience for Alaskan passenger

and freight pilots.

Response Distribution (percent)

Descriptive Statistics

Descriptive Statistics

In Alaska, “rules of thumb” learned from more experienced

passenger and freight pilots are required in order to fly

through areas of low clouds and reduced visibility.

For Alaskan passenger and freight operations, it is considered

safe to fly VMC in visibility below 1 mile on routes over which

the pilot has flown many times before.

In Alaska, it is safe for passenger and freight pilots to fly VMC

en route when visibility is less than 1 mile, provided that pilots

know the destination weather is good.

15

31

15 17 18

5

10

39

22

13 14

1

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

4

20 16

22

30

9 4 6

24 28 24

13

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

4

14 10

20

41

11

1

13

6

29

43

7

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

19

41

18

10 10

3

19

43

13 16

9

0

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree
B30

Alaskan Flight Industry Survey Results

58.

n Mean SD % Disagree % Agree

Non-CFIT Company Pilots 220 2.77 1.53 59.1 20.9

CFIT Company Pilots 70 2.51 1.39 64.3 15.7

77.

n

Non-CFIT Company Pilots 212

CFIT Company Pilots 62

78.

n

Non-CFIT Company Pilots 215

CFIT Company Pilots 65

Descriptive Statistics

Response Distribution (percent) It is okay for Alaskan passenger and freight pilots to fly in

weather below 500-foot ceilings and 1-mile visibility as long as

the pilot feels it can be done safely.

When flying VMC over mountains, I would turn around when

the visibility is reduced to:

When flying VMC over flat terrain, I would turn around when

the visibility is reduced to:

15

28

12

5

41

18

29

11

3

39

0

30

60

90

5 miles 2 miles 1 mile 1/2 mile or

less

Unable to

see

landmarks

3

21

30

9

36

3

29 28

5

35

0

30

60

90

5 miles 2 miles 1 mile 1/2 mile or

less

Unable to

see

landmarks

21

38

9 11

17

4

26

39

10 10

16

0

0

30

60

90

Strongly

Disagree

Disagree Slightly

Disagree

Slightly

Agree

Agree Strongly

Agree

Non-CFIT Company Pilots

CFIT Company Pilots

1 significant difference (Chi square) p < .05

2 significant difference (Mann-Whitney) p < .05

% Disagree=Strongly Disagree or Disagree

% Agree= Strongly Agree or Agree