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National Institute of Justice ""~ J . United States Department of Justice 

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U. S. Department of Justice 

National Institute of Justice 

The Effect of 

Prison Crowding on 

Inmate Behavior 

a publication of the National Institute of Justice 

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About the National Institute of Justice 

The National Institute of Justice isa research. development, and evaluation center within the U.S. Department 

of Justice. Established in 1979 by the Justice System Improvement A-:t. f\:)J builds upon the foundation laid by 

the former National Institute of Law Enforcement and Criminal Justice. the first major Federal research 

program on crime and justice. 

Carrying out the mandate assigned by the Congress. the National Institute of . ./ ustice: 

• Sponsors research and development to improve and strengthen the criminaljustice system and related civil 

justice aspects. with a balanced program of basic and applied research. 

• Evaluates the effectiveness of federally-funded justice improvement programs and identifies programs that 

promise to be successful if continued or repeated. 

• Tests and demonstrates new and improved approaches to strengthen the justice system, and recommends 

actions that can be taken by Federal, State, and local governme11S and private organizations and 

individuals to achieve this goal. 

• Disseminates information from research. demonstrations, evaluations, and special programs to Federal. 

State and local governments: and serves as an international clearinghouse of justice information. 

Q Trains criminal justice practitioners in research and evaluation findings, and assists the research 

community through fellowships and special seminars. 

Authority for administering the Institute and award ing grants. contracts, and cooperative agreements is vested 

in the N)J Director.assisted by a 2 I -member Advisory Board. The Board recommends policies and priorities and 

advises on peer review procedures. 

]\; lJ is a uthorized to support research and experimentatieJn dealing with the full range of criminal justice isslle~ and related civil justice matters. A portion of its resources goes to support work on these long-range priorities: 

• Correlates of crime and determinants of crimina! beha"ior 

• Violent crime and the violent offender 

• Community crime prevention 

• Career criminals and Iiabi .ual offenders 

• Utilization and deployment of police resources 

iii Pretrial process: consistency. fairness. and delay reduction 

• Sentencing 

• Rehabilitation 

• Deterrence 

• Performance standards and measures for criminal justice 

Reports of N lJ-sponsored studies are reviewed by Institute officiall. and staff. The views of outside experts 

knowledgeable in the report's subject area are also obtained. Publication indicates that the report meets the 

Institute's standards of quality. but it signifies no endorsement of conclusions or r~commendations. 

Harry M. Bratt 

Acting Director 

'I 

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THE EFFECT OF PRISON CR()WDtr~G 

ON INMATE BEHAVIOR 

Garvin McCain 

Verne c. Cox 

Paul B. Paulus 

December 1980 

U. S. Deparbnent of Justice 

National Institute of Justice 

" 
National InstitUte of Justice 

Harry M. Bratt 

Acting 'DIrector 

This project was supported by Grant Number 78-NI-AX0019, awarded to the University of Texas at Arlington by , the National Institute of law Enforcement and Criminal 

Justice, Law Enforcement f.sslstance Administration, U. S. 

Department of Justice, under the Omnibus Crime Control 

and Safe Streets Act of 1968, as amended. Points of view 

or opinions stated in this document are thoSG or the authorsand do not necessarily represerrt the official pOSition 

or pollcle.c; of the U. S. Department of Justice. 

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TABLE OF CONTENTS 

Acknowledgements · . . . . · . . . . . . . . Executive Summary · . . . . . . . . . . . . . . . . . . . ~ . . . ,Abetract •• . . • • 0 0 · . . . . . . , . . . . . . . . . Introduction . . . · . . . . . . · . . . . . . . . . . . . . . ~. . General Procedures · . . . . . . · . . . . . . . . . . . . . . . . Findings ••• · . . . . . . . . . . . . . . . . . . . . . . . Site-Coll~cted Data 

El Reno • 

Atlanta · . . 

. . O'! • • • • • • • • 0 • • • • • • • • • • 

G • • • • • • • • • • • • a • • • 

Danbury 

Texarkana 

l,a Tuna 

Fort Worth 

• • • • • • • • •. • • • • • • • • • II • • • • • • 

1978 '& 1979 

1978 & 1979 

. . . · . . . . . . . . . . . . . . . . . . . . . . . . . . . · . . . . . . . . · . . . . . . . . . . . . . . . Archival Data . . . . . . . . . . . . . . . . . . . . . . . . Inter-institutional Analyses • • • • 5 • . . . . . . . . . . . . . Summary of Findings Related to Crowding . . . . . . . . . . . . . Conclusions and Recommendations • • • • • e • • • • • • • • • • • 

Additional Considerations - • • • • • • • • • • • • d d • • • 

Some Possible Interpretations • • • • • • • • • t'I • • • • • 

Recommendations for Future Research . . . . . . . . . . . . . . Cross Institutional Illness Effects Unrelated to Crowding . . . . References • • • • • • • • • • • • • • • • • ~ • • • • • • • • s 

Appendix A. Data Collection Forms 

1. 

2. 

3. 

4. 

Questionnaires • • • • • • • 

Background and Medical Form 

Informed Consent Form • • 

Crowding Tolerance Task • • 

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Acknowledgments 

A project of this scope was not completed solely by the efforts of 

the three principal investigators. We were aided greatly by Dr. Marylie 

Karlovac who joined our team in March 19i9. Dr. Karlovac assumed the 

primary responsibility for computer analyses of the project data. 

We are particularly grateful to the large. number of inmates who gave 

of their time and often provided insights into their own experiences. The 

U.s. Bureau of Prisoas provided cooperation and aid that was indispensable 

and went far beyond ordinary access and courtesy, We would also like to 

thar.tk the students at the Unive~sity of Texas at Arlington and other institutions who cheerfully worked long hours, often under demanding conditions. 

Below is a list of people who have contributed their time and efforts 

to this project. 

U.s. Bureau of Prisons 

Norman Carlson, Director 

Howard Kitchner, Director of Research 

Warden F. Arnold 

D.K. Adams 

Dr. John Bland 

Dr. Fred Carrington 

Deverue Colvin 

Steve Fisher 

Warden Fred Frey 

Dr. Carl Gates 

Warden Louis Gengler 

Bruce Grant 

Warden Jack Hanberry 

Dr. Gary Henman 

University of Texas at Arlington 

Margaret I. Casler 

Dr. Frank Cheavena 

Linda Chernick 

Roma Eckrich 

Douglas C. Eveland 

Vanessa Genung 

Carolyn Hamm 

Dr. Ben Judd 

Raymond Keel 

i 

Dr. Syed A. Hosain 

ArIes Keckler 

Warden T.M. Keohane 

Dr. Bill Lucker 

Dr. Jerry Mabli 

Warden William Nelson 

Dr. Louis Rogol (Deceased) 

Dr. Jerry Stringfellow 

Dr. Jerome Sullivan 

Betty Terry 

Elmer Watson 

Jerry La Valley 

Dr. Robert Matthews 

Richard McDaniel 

Elaine Phelps 

Sharon Powell 

Sam Saunders 

Dr. Janette Schkade 

Carolyn Smith 
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University of Texas at EI Paso 

Adolfo A1ITarez 

Jorge Ayalas Lara 

Richard Saavedra 

Richard Samaniego 

Texarkana Junior College 

Charles Jones 

William Russell 

Yale University 

Randall Billington 

Marjorie Carpenter 

Paula Durlach 

Amy Goldberg 

Georgia State University 

Charles Hopper 

Jim Purvis 

Department of Justice 

Charles Ory 

David Vanderhoof 

The principal investigator designation was determined by random 

lot. The order of authorship on this report reflects the outcome of 

this procedure. Each of the three investigators played a full and coequal role in this project. 

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Executive Summary 

The purpose of this research was to identify the effects of prison 

crowding on inmate health and behavior. The findings were derived 

from two sources: 1) on-site data collection at prisons that vary 

greatly in housing modes and degree of crowding; 2) data for ten year 

periods taken from the archives of the Texas an~ for a shorter period, 

from the Oklahoma prison systems. These findings provide ne:w information 

relevant to prison housing standards as well as confirmation of previous findings 

aboat the negative effects of prison crowding. 

A. Housing and Inmate Behavior 

1. Methods. Data was collected from 1400 inmates serving in' '8i~C~ederal 

prisons. The prisons ranged from a large penitentiary to a minimum 

security co-ed institution, inclUded a variety of housing modes and 

differed in degree of crowding. The inmate populations varied greatly 

in gge, time served, prior commitments, aad ethnicity. Female inmates 

were included in one sample. At all sites inmates were confined to their 

living quarters only during sleeping hours. 

, . 

Data collection consisted of testing inmates for: 1) blood pr~ssure; 

2) crowding tolerance; 3) affective state; 4) evaluation of their living 

quarters; 5) perceived control of environment; 6) biographical data. 

In addition, data was collected from institution records on inmate 

demographic characteristics, illness complaints,and disciplinary records. 

Housing modes were claslsified into several categories: Single member 

units, double units, mUltiple units; distinctions were made between 

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cells, open and segmented dorms, eub-units within dorms, and high/low 

partition cubicles. Thus the most comon prison housing var:t,.atl.ons 

(including double bunking) are included in this study. 

Inmate housing modes were analyzed from two perspectives: spatial density 

(square feet per individual) and ~i2i.l dent5ity (number of occupants per 

living unit). These two variables are sometimes partially independent of 

one another as some housing units of high social density actually provided 

greater space per inmate (i.e., some large open dormitories provided more 

square feet of space per individual than was provided by some single cells 

and cubicles). 

2. Findings. The flndi'ngs were generally consistent across all institutions 

and inmate populations. The basic finding, which confirms cowman sense, 

is that there is a progl:essive and measurable increase in negative effects 

with an increase in housing density. However, while a decrease i'lLs.~uare 

feet per individual is an important factor, it is the increase in social density 

that is most significant. Increasing an individual's space in an open 

dormitory will not inevitably improve the quality of the housing environment from either the individualts perception or as measured by such indicators as illness complaint rates, disciplinary incidents and other objective measure~. Stated otherwise, these findings indicate that once space 

per per:son exceeds 50 square feet, the number of people that one is living 

with and how that space is arranged (single bunking, cubicles, etc.) may b~ 

more importan'c factors in determining reactions to hGusing than mere space 

per person. 

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Further confirmation, of the importance of social density was the findit!.8 

that the negative effects of open dormitories could be greatly attenuated 

through the use of single occupancy cubicles. Although the minimally adequate amount of square feet per individual could not be established in 

this study, the findings do indicate that such cubicles eould be as small 

as 50 square feet without being detrimental to the individual as compared 

to the effects seen in open dormitories. 

Thus one finding of this study is consistent with the Y.iew that individuals 

prefer privacy and a clearly demarcated boundary of "my space" to shared. 

or open territory, even if square footage must be reduced in order to 

achieve such privacy. InroAtes consistently rated individual rooms 

as !!lO~~t desirable: and open dorms as least desirable. Even double cells 

were found to be more desirable than open dorms, although double bunking 

was not favorably perceived in any housing mode, possibly because double 

bunking eliminates the vestiges of personal territory. 

This finding is particularly important because it suggests that providing 

50 square feet in single cells or cubicles is superior to more spacious 

multiple occupant housing. The picture is less clear regarding adequ,ate 

space parameters for single occupant housing. We found no measurable difference in our measures between 50 and 60 square feet but this may in part 

reflect the limitations of our measures. 

Additional findings about housing and inmate behavior include: 

O!arge dormitories can be improved through sub-dividing open 

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space into smaller units that house small (10-20 individuals) 

groups; the positive effects are less than those obtained 

through individual cubicles of 50 square feet; 

~ tolerance of crowding was found to vary greatly among individuals, 

apparently due to personal background factors. Differences in 

tolerance were also found among ethnic g~oups with Mexican 

Nationals exhibiting the greatest tolerance and Anglo-Americans 

the least; Black Americans and Mexican-Americans had tolerance 

levels that were between t;ha.t of the Anglos and· Mexican. Nationals; 

o there is some evidence that tolerance of crowded housing does 

not improve with time; that is, individuals apparently do not 

become adjusted to their crowded environment over time; 

o illness complaint rates exhibited a consistent but unexplained 

pattern of increasing for six weeks for individuals who enter 

housing units, then declining and leveling off; 

Q inmate affect or moodiness appeared to be influenced more by 

the individual's security level and how long he/she had been 

incarcerated than by housing environment; 

o crowding effects were not found to be associated with individual 

participatj.on in religious., education or recreational programs; 

o Blood pressure readings were not found to be indicative of c.rowding related stress. This is inconsistent 't'lith previou!i studies 

and perhaps, in the researcher's opinion, reflect the relatively 

benign milieu of federal prisona. 

B. Institution Size and Inmate Health/Behavior 

This part of the study examined the consequences over time of increases 

in total institutional populations. Data was available for Texas prisons 

for the ;;>eriod 1968-1978, ~ period in which. institution populations nearly 

doubled but housing capacities increased by only 30%. In Texas, the 

rates of suicides, violent deaths, disciplinary incidents, D.atura1 deaths 

for "e1der.1y" (age 50 or more) inmates $ ,increased beyond statistical 

expactancies. The larger prisons in the Texas system (1600 average .. 

daily population) consistently demonstrated rates higher than the 

smaller (800 average dialy population) prisons, a consistency that could 

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not he readily explained by demographic characteristics of the populations, 

housing mode, or average am01lnt of space per inmate. 

Data from Oklahoma on. crowding and violent deaths corroborated t'he Texas 

data. The apparent explanation of this data is that sheer population 

size of an institution exerts a negative infh~ence OIl its inmates, an 

influence that is seemingly independent of other factors. 

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______________ ________________ . __________________________ ~ ______ . __________________ ~ __________________________________________ ~ __ ~ __ ~ ________________ ~ma __ ar~ __ .. __ .... a. ____ ~ 
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Abstract 

Data from over 1,400 prison inmates together With substantial archival data were used to evaluate the Psychological and physiological effects 

of crowdin,~ and varicus housing arrangements on inmates. Measures used 

included: illness complaint rates, disciplinary infraction rates, blood 

pressure, perception of crowding, sleep, and il~te evaluations of housing, death rates (both violent and non-violent), suicide rates, psychiatric 

commitment rates, self mutilation and suicide att,empt rates. The findings 

supported the following principal conclusions. 

1. High degrees of sustained crowding have a wide variety of negative Psychological and physiological effects inclu:!;!,ng increased illness 

complaint rates, higher death and suicide rates, and higher disciplinary 

infraction rates. 

2. Large institutions produce much mo'ce severe negative psychological and physiological effects than small institutions, as expressed 

in higher death, suicide, and psychiatric commitment rates. 

3. Partitioning of open dormitories into privacy cubicles has a 

strong positive effect as indicated by the reduction or elimination of 

negative effects typically associated with open dormitories. 

4. Both number of occupants in housing quarters (social density) 

and space per person (spatial denstty) contributed to crowding effects. 

Social density was ;ypically the most influential factor. Some of these 

effects were time relatsd. 

5. Our findings also indicated that there are substantial individual differences in response to crowding as well as racial and ethnic 

group differences. 

Recommendations regarding optimum housing arrangements policies are 

included. Future research needs are also discussed. 

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Introduction 

The United States prison population is increasing at a faster rate 

than prison housing facilities. Consequently, crowding in prisons is becoming more intense and frequent. An all too frequent example of intense 

crowding is illustrated in Figure 1. It is widely accepted that crowding 

in prisons is a major source of administrative problems and adversely affects inmate health, behavior, and morale. For example, the recent tragedy 

at the New Mexico State Prison has been blamed at least in part on crowding. 

In spite of these concerns there has been relatively little systematic research on prison crowding. Such research is necessary if we are to accurately identify the consequences of crowding and establish housing standards 

that will minimize these effects. The current interest in revision of prison 

housing standards would be greatly aided by additional information regarding 

the psychological effects of prison housing. The present project was directed at providing a systematic evaluation of crowding effects in prisons. The 

project began in March 1978 and the initial phases involved locating suitable 

research sites. Data collection began in May 1978 and continued through May 

1979. Preparation of data for computer analysis and statistical analyses 

continued through January 1980. 

Research has indicated that nonprison crowding can have negative psychological and physiological effects (see Paulus, 1980 for a review). Yet 

some investigators are not convinced that crowding has generally negative 

effects (e.g., Freedman, 1975, 1979). This view is apparently derived from 

the fact that a number of studies have shown no effect of crowding while 

others show effects only under special conditions (e.g., all male environFIGURE 1. Triple-bunked, s1ng . 1 e ce 11 in a large state prison, . providing 19 square feet per 1nmate. 

ments). Another problem with past crowding research is a paucity of good 

evidence from naturalistic or real life settings. Many studies done in 
4 

laboratory settings may have little relevance for residential or institutional environments. Other studies have focused on urban environments but 

often reported no crowding effects or failed to eliminate alt~rnative 

interpretations of obtained results. Nevertheless, a number of consistent 

trends have appeared in the study of residential crowding. 

A ~eries of studies in college dormitories have found that increasing 

the residents in a room from two to three increases feel~ngs of crowding, 

loss of control, physiological stress, and illness complaints (Aiello and 

Epstein, 1979; Baron, Mandel~ Adams, & Griffen, 1976). Some studies (Baum 

and Valina, 1977) have demonstrated that dormitory designs that increased 

the number of unwanted interactions with other students led to social and 

psychological withdrawal. 

Our previous research on crowding in prisons has focused on the effect 

of different types of prison housing. This research has demonstrated that 

inmates living in open dormitories felt more crowd~d, rated their environment more negatively, had higher illness complaint rates and greater psychologic:al stress than inmates living in single or double o,ccupant rooms 

(Paulus, Cox, McCain, & Cht,mdler, 1975; McCain, Cox, & Paulus, 1976; COli:, 

Paulus, McCain, & Schkade, 1979). A study of a county jail revealed that 

the inmates living in the most crowded units also had the highest illness 

complaint rates (McCain et a1., 1976). In a state prison we found that 

feelings of crowding and systolic blood pressure increased as the number 

of inmates in a cell increased from one to six (Paulus, McCain, & Cox, 

1978). 

Several other researchers have also examined the effects of prison 

housing. D'Atri (1975) found that inmates in open dormitories have higher 

blood pressures than those in single cells. Ray (1978) found that high 

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social density in dormitories led to increased blood pressure and illness 

complaint r.ates. Megargee (1971) found that crowding was related to 

increased disciplinary.infractions. 

A number of studies have also assessed the effects of institutional 

size or changes in institutional population. Nacci, Teitelbaum, & Prather 

(1977) surveyed all of the federal correctional institutions and found 

that the ones that were most overcrowded relative to 'their capacity had 

the highest disciplinary infraction rates, especially in the case of institutions with young offenders. We were able to examine effects of 

variation in population in a psychiatric hospital within a sta.te prison 

system (Paulus at al., 1978). As population increased and then decreased, 

the death rate also increased and decreased. In the same state system 

the death rate for males over 45 was found to be higher when inmate population was higher. 

In summarY9 there exists some evidence that high levels of density 

can produce negative emotional reactions as well as increaSing the occurrence of disciplinary infractions, illness ('.Jmplaints, and even death. However, in an area of study as important as crowding, this evidence is still 

relatively meager. Only a small number of published studies have shown 

some health related effects of institutional crowding. Since this is a 

very serious consequence it is clearly important to obtain much more information about ~he health related effects of institutional crowding. 

There also exists very little information on the effects of different 

types of prison housing conditions. Most studies have involved comparisons 

of different 1eve1~ of overall institutional crowding or comparisons between 

single or double occupant rooms and crowded dormitories. There is hardly 

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any evidence available about the effects of amount of space in various 

types of housing (e.g., single rooms and dormitories) and the nature of 

dormitory design (e.g., the use of privacy partitions). Also, all of the 

relevant studies have used only a restricted range of measures. A comprehensive understandi.ng of the effects of crowding requires the use of psychological, physiological, and behavioral measures. 

The goal of this project was to deal with these gaps in our knowledge 

as well as a number of other issues. Our primary goals were as follows: 

1. Generality. We sought to determine the degree to which effects 

of crowded housing conditions could be consistently observed in a variety 

of correctional institutions. Our previous work was limited primarily to 

the Fede:ral Correctional Institution at Texarkana. We ~.Janted to examine 

the effects of crowding across different types of institutions and institutional populations. Hence, we examined inmates in six differ~nt institutions ranging from minimum to maximum security. 

2. Individual Differences. We were also interested in examining 

the effects of inmate racial or ethnic group and sex. Some studies suggest that blacks and Mexican Americans might be more to1erarlt of crowding 

than whites (Baxter, 1970). A number of studies have shown that females 

react more negatively to residential crowding than males. The effects 

of inmate background (rural vs urban), age, and custody level were also 

of interest. 

3. Social and Spatial Density. One major gap in the literature is 

our knowledge about the precise effects of different levels of social den-. 

sity (number of occupants in living quarters) and spatial density (square 

feet per person). These two factors are often difficult to disentangle, 

but it is important to determine the extent to which these factors 

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contribute to the observed effects of crowding. Several of our previous 

studies (e.g., Paulus et a1., 1975) suggested that social density is the 

most important. It is of course quite likely that both of these factors 

have an impact. So our goal was to determine the relative contributions 

of these two factors to crowding effects by examining a wide variety of 

housing conditioI1S and institutions. 

4. Insti~utional Densfty. Since several studies have shown that 

large, densely populated nonprison environments (e.g., Levy & Herzog, 

1974) can have negative effects on the health of residents, we also examined the effect of popu1at10n levels of institutions. 

7 

5. Crowding Tolerance. I~ one of our previous studies we had examined crowding tolerance using a task involving a simulated dormitory 

task. This task yielded results indicating that living under crowded 

conditions decreased crowding tolerance. Furthermore, the longer inmates 

were exposed to crowding, the less their tolerance for it. These findings 

have been replicated in a number of other studies (e.g., Baum & Valins, 

1977). We wanted to examine this effect further using both the simulated 

room task and a modified version. 

Methodological Considerations 

1. Multiple Measures. To determilne the potentially broad range of 

effects of crowding we employed measures of mood, attitudes, social behavior, blood pressure~, health, and crowding tolerarlce. 

2. Assessment of Confounding Factors. Although in many of the institutions housing assignment appears to occur on a semi-random/space 

available basis, there is a tendency at some institutions for inmates to 

move into more desirable housing as they attain seniority through length .\ 
f t 

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of time in the prison. Consequently we examined the contributions of 

such variables as age, time in prison, time in housing, custody level, 

and months left on sentence to the various effects of crowding. 

General Procedures 

Our general approach was determined by the practical considerations 

governing research in a prison environment. We sought a wide range of 

housing conditions that reflected variation in spatial density (square 

feet per person) and the social density (number of occupants in living 

quarters) as well as other features such as cubicles. Each research site 

was chosen after careful planning. Blueprints of various prisons were examined and details obtained regarding housing condit:f.ons. On the basis 

of information obtained by telephone, written correspondence and blueprints, 

potential research sites were selected and were visited. Following on-site 

inspection, some sites were selected for data collection and negotiations 

ensued to provide for a data collection visit. Data collection visits were 

typically three to four days in duration ,and involved processing a large 

number of inmate volunteers in a relatively short time and obtaining information from their records. Each visit involved all three investigators and 

several aSSistants, some of whom were hired at the prison locale. These 

trips involved intensive effort during the day within the prison and in the 

case of La Tuna, night data collection as well. Following data collection 

during the day many hours we~e spent each night organizing collected data. 

These data collection visits were extremely demanding phYSically and mentally, and because of the ever present risks inherent in a prison environment, emotionally as well. We received superb cooperation from the U.S. 

Bureau of Prisons Director Norman Carlson and the U.S. Bureau of Prison 

personnel at every adminlstrative level. This cooperation together with 

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the superiority of records in the Federal Prison System led us to conttne 

our research visits to federal institutions. The following prison facilities have been employed in the project: Atlanta FCI, Georgia; Danbury 

FCI, Connecticut; El Reno FCl, Oklahoma; Ls Tuna FCI, Texas; Fort Worth 

FCI, Texas; and Texarkana FCI, Texas. Each of these sites were chose~ because they offered special types of housing conditions and were accessible 

for research~ 

Unutilized Sites 

A number of potential research sites were visited but proved to be 

unsuitable and/or inaccessible for our research purposes. In some cases 

the prison population had declined to the point where the existing types 

of housing provided limited variation in spatial erA social density and 

little or no crowding. In the case of the Florida and Texas prisons, Qur 

access was initially approved by prison officials but subsequently denied 

because of pending litigation. Listed below are the prisons that were 

site-visited but not utilized as research sites. 

Allenwood FCI, Pennsylvania 

Huntsville Unit, Texas 

Lake Butler Reception Center, Florida 

Lawtey Prison, Florida 

Leavenworth FCI, Kansas 

Lewisburg FCI, Pennsylvania 

McAlester State Prison, Oklahoma 

McNeil Island FCI, Washington 

Milan FCI, Michigan' 

Reception Center, Huntsville, Texas 
.. 

10 

Trenton State Prison, New Jersey 

Union Prison, Florida 

Scope of the Study 

We have collected data for over 1400 inmates in six different institutions. We were able to obtain information in 90 separate categories 

per inmate and now have in excess of 100,000 rieta entries. This does not 

include archival data from 20 institutions which cannot easily be classified according to the number of entries. The institutions have provided 

a wide range of variation in spatial and social density of housing conditiona. Some of the housing we have examined include different sizes of 

single occupant cells, double bunk cells, single and double bunk partially 

open cubicles, large (70 occupant), medium (40 occupant), ~~all housing 

areas (10 occupant), and multiple o~cupant housing ranging from three to 

six man cells. 

Mcasu'res 

We attempted to collect data regarding the effects of crowding with 

measures that were feasible to use in a prison setting. Some of our measures, such as the que,stionnaire and blood pressure, required brief direct 

contact with inmates while others involved prison records, as in the case 

of illness complaint rate and disciplinary infraction rate. Our questionnaire involved several psychological scales designed to measure perception 

of crowding, evaluation of living quarters, and mood state. In addition 

we obtained biographical information from inmates (e.g., number of people 

in home during childhood) or from records (e.g., number of prior incarcerations, age). Many of thes~ measures have been examined to determine '": >,"" 

their relationship to specific housing conditions and inmate reactions to I 

ft 

IIf-= 

• 

housing. Our data collection fbrm was modified over the course of the 

data collection phase of the project. The most complete and recent 

version is included in Appendix AI. Our report will focus on only a 

subset of all measures taken. Some measur~s are not discussed because 

they have not proven useful and others remain to be a,nalyzed. The measures that h~~e received the major part of our attention have been perceivedc~t1'"..ro.in$' blood pressure, illness complaint rate, disciplinary 

infraction rate, housing unit evaluation, mood state, and perception of 

control. Archival measures included death, psychiatric commitment, and 

suicide rates. 

BlC!od Pressure 

We included this measure as a potential lphysio,logical index of 

crowding-induced stress because of previous findings by ourselves and 

others which indicated higher blood pressure values in crowding ho~sing. 

Measurements were taken with a p~~tammed Electro-sphygmomanometer 

(PE 300 NARCO Biosystemg) and a chart recorder. This procedure provided 

for consistent maximum cuff pressure, constant cuff inflation and deflation ~ates and a written record of blood pressure data. Because of the 

lack of consistency :l.n our blood pressure findings, we do not recounnend 

t;tlis measure except for special situations. 

Illness Complaint Rate 

In each institution we examined and recorded from medical records 

11 

indi'llidual illness complaints dur1.ng the period of time (up tc! six months) 

the individual was in the housing quarters in which he was residing on 

the da9 of testing. tile obtained medical records from infirmary files at 

each research sit£. Inmate infirmary visits were recorded by date and 

c· • ! ' 

.'<' 

, :.1 
I 

(U_ .. 

12 

natu~p- of comp~aint. we have employed four measures of illness complaints. Overall r~te reflects all volitional visits to a medical 

facility except those compelled by serious injury, emergency illness 

conditions and physician scheduled examinations such as x-rays and workrelated plrysicals. The second m~sure involves the further exclusion of 

colds and flu. Finally, we also separately examined contagious and non .• 

contagious illnesses. In all measures no Mbre than one complaint in a 

given day was recorded for an individual. 

In the course of analyzing the relationship between housing snd ill~ 

ness complaints it was discovered that transfer to different housing was 

accompanied by a high lavel of illness complaints. Further examination 

indicated that this period of high illness complaints was concentrated in 

a period of about six weeks following transfer. After six weeks the complaints tended to be stable. This measure has discriminated among one and 

two man cells, racial groups, and a variety of other factors. It should 

be noted that illness complaint behavior can be promoted by psychological 

stress with or without actual changes in physical health. ~echanic, 1976). 

Disciplinary Infractions 

Thus far we have coUected data from disciplinary records w:l'th sufficient number of infractions for analysis at El Reno. At~his institution 

we analyzed the relation between housing and disciplinary infractions. We 

focused on nonaggr~aaive disciplinary infractions because aggressive infractions would be reduced in single occupant housing by the lack of additional housing partners. 

Crowding Tolerance Task 

One version of this task involved asking inmates to place figures 

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13 

in a mqdel of a dormitory until it appeared crowded. The number of figurea placed was used as a measure of crowding toleranc~. In the past 

this task has shown a modest relationship to the social density. We 

'~shed to collect further data with this task to further assess its utility. Since the task is time consuming and cumbersome to administer, we 

also devised a simplified version that requires that inmates select from 

a series of dra~ings the ideal number of beds £~'l';' a standm;o4: size dormi""'-

tory. 

Perceived Crowding 

This measure simply asked inmates to characterize their housing as 

uncrowded, moderately crowded, crowded, or very crowded. The question 

was asked orally and was designed to circumvent problems with inmates of 

limited literacy and/or intelligence. One reason for our inlterest in perceived crowding scores is that, as will be seen later, they are related to 

illness complaint rates. 

Inmate Evaluation 

of Housing Units 

We have employed a. n~~ber of scales on our questionnaires that focus on 

the inmates' evaluation of their living quarters. These focused on dimens:f.ons such as Good--Bad, Attractive--Unattractive, Pleasant--Unpleasant, 

Quiet-··Noisy, and Crowded--Uncrowded. 

Mood Scales 

Another set of scales was directed at measurement of psychological 

mood state and focused on dimensions such as Relaxed--Bored, Tense--Calm! 

Satisfied--Unsatisfied, Happy--Unhappy, and Important--Unimpor.tant. 

-
t - ---------~-------~-------------~-------------.....-----------------------------

14, 

Perception of Control 

Other research (Cohen, Glass, and Phillips, 1978) has indicated that 

the degree of perception of control of one's life situation can determine 

ability to cope with stress. Consequently we asked inmates to rate the 

amount of control they ielt they had over their situation and over others 

in the prison and how mucn choice they thought they had over housing 

assignment and prison activities. 

Background Qu~stionnaire 

Information on this questionnaire (see Appendix A2) was taken directly from the inmates records. Commitment date, offense, race, housing 

record, and disciplinary infractions were the items of greatest interest. 

A number of other items were obtained, but either have not yet been analyzed or proved to have little utility. 

Archival Data 

Archival data was obtained from the Texas and Oklahoma prison systems. 

These data of interest were related to death rates, suicide rates, self 

mutilation and attempted suicide, disciplinary rates, and psychiatric commitments as they related to institutional population level and institutional size. Data from the Texas Department of Corrections was extensive 

and covered, in some cases, periods of time up to 15 years. 

Data Collection Procedure 

A similar procedure was employed at each institution. A typical research visit involved the three pril1cipal investigators and three to eight 

assistants. On the day prior to data collection, one of the principal investigators prepared an inmate "call-out" list for each testing day. This I 

" 

15 

list consisted of inmates selected from specific types of housing. In 

some cases length of stay in housing, ethnic identification, type of 

offense, and sex (at Fort Worth) were used as criteria for determining 

inmate inclusion in the "call-out." When an individual inmate came to 

the testing area, their first contact was with one of the research group 

acting as a receptionist. Here the general nature of the study was explained and consent forms were signed (see Appendix A3) if the inmate 

wish~j to participate. Participants proceeded to the first station where 

their blood pressure was measured. From this station the inmate was sent 

to a nearby location and given the Crowding Tolerance Test (see Appendix 

A4). They were then directed to a third location to fill out a questionneire. The questionnaire was explained by one of the investigators. If 

the inmate could not read, the investigator helped fill out the questionnaire. Spanish language forms were given to Spanish-speaking inmates. 

Our test procedure allowed for testing four to six inmates every 15 minutes 

and up to 100 inmates per day. At the same time two or three members of 

the team were consulting records for background medical and disciplinary 

data (see Appendix AS). 

Findings 

The data are divided into two sections for purposes of this report. 

The section on Site-Collected Data includes those measures taken at the 

research sites. The bulk of our analyses of site-collected data were 

based on within institutional data to insure that the data were derived 

from a conunon institutional milieu. Archival Data j,nclude information 

from various reports and records. The greater part of the latter data 

is from institt.tions in which, for various reasons, we were not able to 

carryon direct o'bservations. Findings for some variables such as 
16 

disciplinary infractions will appear under both Site-Collected and Archival 

headings due to the different Sources of the data. All statistical comparisons and correlations in the report !<;q~~ significant at the .05 level or 

less if not otherwise noted. Differences at or beyond the .001 level are 

re\ported as .001. 

Field research, by its very nature, does not oft3n provide for the kind 

of control typical of laboratory research. This is certainly true of this 

project and consequently the statistical tests cannot have the same validity 

as when used in laborato~y or highly controlled field research. We made 

every effort to. collect data that would meet the assumptions and requirements of conventional tests. However, because of 'the natu£e of the project, 

this goal was, at best, only approximated. Equally important, fram our perspective, were findings that were consistent across institutions. We are 

especially cautious in attaching importance to findings unique to one institution though they often suggest further lines of research. 

I 

• 

17 

SITE-COLLECTED DATA 

El Reno 

The Federal Corrections 1 Institution at El Reno is a medium security 

institution. At the time of our research visit it had 1,212 residents, 

45% of whom were over 28, with an average age of 29.9. The inmates are 

initially housed in an admissions and orientll'tion cell block. They stay 

there for about two months an d t h en are transferred to other units in the 

prison, Most of these units cons i st 0 f either cubicled dorms or enclosed 

rooms. Four single-story buildings contain two wings of cubicles separated 

by- sanitary facilities, a lounge, and an administrative office. The partitions of the cubicles are 5'6" high and enclose a 7' by 7' area of living 

space. The cubicles provide some storage and writing space. Each wing 

contains 48 such cubicles. Nineteen of these cubicles contained double 

bunks. Figure 2 shows cubicles at El Reno. 

Two double-story buildings containe d enc 1 ose d rooms measuring 5' 10" 

by 10'. Each floor contained two wings of 35 rooms arranged on both sides 

of a hallway. Eleven rooms in each section of the hallway contained two 

men. Except for Youth Corrections Act (YCA) inmates, assignment of inmates in our sample to a particular type of housing is done on a completely 

random basis. Within a unit residents are initially assigned to a double 

and moved to a single on a seniority ~asis. 

We were primarily interested in two aspects of the El Reno housing. 

First, we wanted to obtain data on the effects of cubicles. 

wanted additional data on singles as compared to doubles. 

Housing Units 

Second, we 

One hundred and eighty-three inmates were tested on July 11-13, 1978. 
• 

"., 1 

, 

FIGURE 2. Cubicles, El Reno Federal Corre~tional Institution. 
,= 

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• 

Four buildings were sampled and contained both single and double units. 

The inmates were distributed as follows: Building 2, 23 singles, 17 

doubles; Building 3, 29 singles, 23 doubles; Building 5, 20 singles, 22 

doubles; and Building 6, 22 singles, 27 doubles. 

Cur first analysis was concerned with overall differences among 

residents of the different housing units. Table 1 shows the various 

factors on which residents of the various units differed significantly 

as determined by analysis of variance. It can be seen that Unit 5 which 

contained the YCA inmates had the youngest and most infraction prone population. The cubicles were rated as more attractive than the rooms and 

residents in the cubicles had relativply lower blood pressures (see 

Table I). The blood pressure effect was only marginally significant 

(p < .06) for systolic blood pressure and the low diastolic blood pressure of the Building 5 residents can be attributed to their age. A 

comparison of black and white inmates showed that blacks tended to rate 

their housing a little more negatively. 

Singles versus Doubles 

Inmates who lived in singles were compared with those who lived in 

doubles (in the cubicles and rooms combined). Those who lived in the 

doubles rated themselves to be more crowded and rated' their living quarters more negatively on all of the room rating scales as compared to those 

who lived in singles. Double residents also had higher nonaggressive disciplinary infractions and less involvement in club activities than residents who were singles (see Table 2). Double residents differed frO-a! 

single residents in having been in the institution a shorter time period, 

having shorter times in their housing units, and having a lower custody 

--1 . -;.--':--:-"'-(i'-"~ )~!1',.~ I 

19 
• 

-

, 

.-, 

'I 

Table 1 I Results for El Reno Buildings 

2 3 5 6 Cubicles Significance Cubicl@a Rooms Rooms F-Values Levels 

Age 29.9 30.2 23.9 32.3 F(3,179) = 16.01 P < .001 

Room Attractiveness a 3.1 3.1 1.9 2.2 F(3,179) ... 4.99 P < .01 ? Nont~ggressive Infractions .09 .23 .45 .06 F(3,179) ... 3.16 p < .05 . .-

Diastolic Blood Pressure 50.9 53.8 50.3 56.6 F(3,179) 3.07 p < .05 ... Systolic Blood Pressure 111.1 110.3 114.5 115.9 F(3,179) ... 2.45 p < .06 

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Table 2 

El Reno Results for Singles vs Doubles 

Perceived Crowding a 

S~ary Room Rating b 

Nonaggressive Infractions 

Club Activities 

Time in Institution (weeks) 

Time in Housing (weeks) 

Custody Level 

Crowding Tolerance c 

(More than 6 weeks) 

Diastolic Blood Pressure 

(More than 6 weeks) 

Singles 

2.4 

15.6 

.07 

.52 

59.6 

29.4 

2.25 

18.1 

55.6 

Doubles 

3.3 

11.6 

.35 

.22 

29.1 

9.2 

1.72 

14.2 

51.2 

Notes: a. Higher number means more crowded. 

b. Higher nP,mber means more favorable rating. 

c. Hi$her number means more tolerance. 

F-Values 

F(l, 180) = 30.47 

F(l, 181) ... 20.66 

F(l, 181) ~ 7",63 

F(l, l8l") = 6.44 

1':(1, 180) =- 33.55 

F(l, 181) = 37.64 

F(l, 177) :I 8.22 

F(l, 105) Oil 4.08 

P(1, 105) ... 3.97 

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S:J.gnifican,ce 

Level 

p < .001 

P < .001 

P < .01 

p < .05 

p < .001 

p < .001 

p < .01 

p < .05 

p < .05 

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22 

level. When one controls for the effect of ~ime in the institution and 

for custody by analysis of c.ov~riance, the discipline effect I'emains 

atI'ong, but it is weakened somewhat when one controlf;! for time in housing 

conditi('1ns (p < .10). Similar analyses of covariance controlling for 

time in institution, time in housing condition, and custody revealed that 

all of the effects of room rating and perceived crowding were not significantly 1n~luenced by these variables. However, the club effect disappeared when time in housing unit was used as a covariate. When one 

examines only those who have been in the housing for six weeks.o~~~nger, 

most of the a1,love-mentioned findings are obtaipe.r:Le"ieilmore strongly. In 

addition, the singles had hi&heI' c~owding tolerance scores (indicating 

more crowding toli:l:'snce) and higher diastolic blood pressure. F'or inmates 

. \ilio had been in a particular housing unit over six weeks, the disciplinary 

infraction effect remains strong even when one controls for time in housing (p < .01). 

Cubicles versus Rooms 

In comparing cubicles and rooms we found that the cubicles were rated 

as more attractive than the rooms, while systolic blood pressure was higher 

in the rooms (see Table 1 ). When one examines only those who have been in 

the hous~ng six weeks or more the effect for systolic blood pressure weakens (p < .11). There was also a slight tendency for room residents to 

have more trouble sleeping (p < .06). Custody, age, and length of stay in 

housing and in the institution did not differ between these two housing 

types. 

Illness Complaints 

Residents of double occupant rooms or cubicles were found to have 

, 

·1 

• ----------~.--- . 

23 

higher illness complaints than residents of sin~le~. When the rates were 

calculated for the first six weeks,. oftesid·~~ce·· in the housing units, the 

weekly illness complaint .rates for the singles were .06 and for the 

doubles .16 (p < .05)~ For the period after six weeks of living in the 

housing uniJ;:~;A:he rates were .14 for the doubles and .07 for the singles 

(p. :/ .03) (see Figure 3). When only noncontagious illnesses are considered, the relative differences remain large. In the period before six weeks 

the doubles (.089) are about 2-1/2 times as high as the singles (.036). 

The ratio is two to one for the period after six weeks. Illness ~ates for 

ir~ates in cubicles were slightly higher than for those living in rooms. 

The differences were not statistically significant. For this period of 

time, the rates for the blacks were also higher than those fur the whites 

(.13 vs .07). However, this effect wa.s not significant • . . -

When illness rates are calculated separately for different periods 

of time, it appears that in both one and two man units illness rates are 

high during the first six weeks and considerably lower after the initial 

six weeks, especially for one man units (see Figure 3). The difference 

between these periods is highly significant (p < .005). 

Perceived Crowding and Illness 

A detailed analysis of the relationship of perceived crowding to 

illness indicates that inmates who feel more crowded within particular 

housing units have hi g h er ill ness ra te s. Ind1·viduals in two-man units 

were divided into those reporting that they were very crowded and those 

reporting they were less crowded. For the period less than six weeks 

those reporting "Very Crowded" the illness rate (average = .200 per week) 

was over four times as high as those reporting less crowding (average = 

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EL RENO Fe. Singles 

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1-3 4-6 7-12 13-26 

Weeks In Housing Unit 

Figure 3 

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25 

.042 per week). This difference was statistically significant (p < .015). 

For the period over six weeks the inmates reporting very crowded had illness rates over twice as high as those reporting less crowding. However, 

the number of subje~Ls available was too small for statistical analysis. 

Sunnnary 

The results for El Reno indicate that double occupant housing produced greater feelings of being crowded, more negative ratings of the 

living units, greater disciplinary problems and higher illness complaint 

rates than singles. High perceived crowding scores were accompanied by 

higher illness complaint rates. Blacks had higher illness complaint 

rates than whites. Cubicles were rated as more attractive than rooms and 

the residents in these units had lower systolic blood pressures. The 

fact that there were no other statistically significant differences between 

the rooms and the cubicles indicates that cubicles are quite effective in 

reducing the crowding effects typically encountered in open dorm living. 

--, I 

\' 
26 

Atlanta 

The primary objective in our data collection at Atlanta was to 

compare the effects of housing in single and multiple occupant cells 

(see Figure 4). Earlier work had covered single.:;, doubles, and dorms. 

This was an opportunity to examine 3, 4, 5 and 6 man cells. The secondary objective was to collect data in a high security institution in 

order to test the generality of our findings. 

The Atlanta Federal Penitentiary is a large, old, maximum security 

institution. The population at the time of our site visit (September 12, 

1978) was 1,924. This decreased by about 200 at the time of our research 

visit (January 2-4, 1979). Inmates are older (average age 37) than in 

most institutions. The average inmate spends approximately six years in 

this institution. There are several types of housing at Atlanta. Our 

primary interest in Atlanta was in the potential comparisons among single 

and several types of multiple occupant cells, since multiple cells such 

as those at Atlanta are extremely rare. The single cells had approximately 50 square feet. The mUltiple occupant cells are 22; x 8 i , providing a 

total of 176 square feet (see Figure 4). Multiple occupant cells had 

three to eight inmates at the time of th~ site visit with space per person 

ranging from 22 to 59 square feet. Housing assignment for inmates in our 

sample was made initially on the basis of availability except for maximum 

security inmates who are ordinarily assigned to A and B blocks. We did 

not test any inmates from the special unHs, Detention and Security. At 

the time of the site visit Atlanta Wp.s converting to a unit management 

system. 

Our research visit included the days of January 2-4, 1979. We collected data on 121 inmates in single, 3, 4, 5 and 6 man cells. Due to a 

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FIGURE 4. Eight-bunked cell in Atlanta Penitentiary. 
------------.--------------------------------------------------------------------------------------------------------------~----~------------------~.----------~----------------------------

----, 

~--------~:~.~-- I 

28 

decrease in oVerall population there were no longer any seven and eight 

man cells. 

Perceived Crowding 

There was a significant effect for perceived crowding among the 

housing conditions (p < .001). Figure 5 shows the increase in perceived 

crowding as the number of men per cell increases. Sinc~ space per man 

increases from 50 square feet in the one man cells to 59 square feet in 

three man cells p the social density factor seems to be more influential 

than spatial density in this particular comparison. Both social and 

spatial density increased in the three to six man range. Consequently 

we are unable to say which factor was more influe~tial in that range. 

In Figure 6 we have plotted the average perceived crowding scores 

for blacks and whites. In the 1, 3, 4 and 6 man units the whites are 

higher in perceived crowding. These results are similar to those obtained at other institutions. 

Housing Unit Ratings 

Single cell inmates rated their housing more favorably than did inmates from the multiple cells on four of the six room rating measures 

(p < .01). Results on two of the scales, Attractiveness and Pleasantness, 

did not yield statistically significant differences but were in the same 

direction (see Table 3). 

Illness Complaints 

A comparison of single cells versus multiple occupant cells yielded 

a significant difference in illness complaint rates (p < .05) with singles 

having lower illnesR complaint rates. A similar comparison, excluding 

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1 3 4 5 6 

Number of Inmates In Cell 

Figure 5 

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• 

-- Black 

CJ CJ CJ CJ a White 

1 3 4 5 6 

NUMBER OF INMATES PER CELL 

Figure 6 

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TABLE 3 

Atlanta Results 

Variables Housing Units 

Social Density 1 3 4 

Space (sq.ft. per man) 54 59 44 

Number of Subjects 24/27 18/20 39/40 

Perceived Crowding a 

1.4 2.4 2.1 

Summary Room Ratings b 21.7 18.6 19.0 (6 scales) 

Blood Pressure 60.6 52.7 65.7 

c Custody 1.3 1.6 1.7 

Notes: a. The higher the number~ the more crowded. 

b. The higher the number, the more positive. 

c. A high score means more favorable custody. 

5 

35 

26/27 

3.1 

15.8 

64.8 

1.6 

6 

29 

8/9 

3.3 

15.0 

52.4 

1.3 

Significance 

F-Va1ues Levels 

F(4,119) = 9.47, p < .001 

F(4,113) = 3.85, p < .01 

F(4,113) = 5.30, p < .001 

F(4,119) = 3.43, p < .01 

.. 

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32 

colds and flu, also yielded a significaut difference (p < .05). 

Figure 7 shows the trend of illness complaints for the housing 

conditions. There is an obvious and significant increase (Spearman 

Rank Order Correlation, p = .05) in illness complaints as crowding 

increases. These data are for illness rates after the initial six 

weeks in any particylar housing condition. Data for the period before 

six weeks could not be analyzed by individual housing unit because 

there are too few inmates in some housing conditions. The trends in 

racial differences, though not statistically significant, are cons1stent with findings at other institutions where blacks had higher illness 

rates than whites. 

Illness rates in the period before six weeks were approximately 80% 

higher than in the period after six weeks. This is in agreement with 

findings from other institutions. 

Blood Pressure 

There was no significant difference among hc~sing conditions for 

systolic blood pressure. With regard to diastolic blood pressure, a 

significant result was obtained. but it bore no systematic relationship 

to crowding (see Table 3). 

Sleeping Problems 

The single cells were compared with 3, 4, 5, and 6 man cells as a 

group on the degree to which they reported problems with sleeping. The 

three through s1~ man cells had 75% more complaints of sleeping problems 

than did the single cell inmates. This difference was significant 

(p <: .021). 

~ 

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i .15 

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1 2 3 

NUMBER OF MEN PER CELL 

Figure 7 

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34 " 

Housing Related Complaints 

The single and multiple cell inmates showed a different pattern of 

complaints regarding their housing conditions. A goodness-of-fit test 

indicated the difference in patterns was statistically significant 

(p < .05). While the single cell inmates scattered their complaints over 

five categories, the overwhelming primary complaint for the multiple cell 

occupants was crowding. 

The primary complaint for the single cell inmates and multiple cell 

inmates are shown in Figure 8 for those inmates who had one or more complaints. In one instance we were able to identify complaints solely with 

social density. The three man cell inmates complaints regarding crowding 

were over twice as high as single cell inmates, in spit·~ of the fact that 

the three man cells had 59 square feet per man as contrasted with 50 

square feet in the single cells. 

We also asked inmates what bothered them most, too TDany people or too 

little space. Only the inmates in four man cells were sufficient in number and distribution of responses to all~; for analysis of this question. 

Number of people was the chosen complaint for 44% and amount of space for 

the remainder. Those indicating too many people as the primary complaint 

also had higher perceived crowding scores than those indicating the greatest problem was space. This difference was significant (p < .03). In the 

period of less than six weeks those who said people were the greatest 

bother also had illness complaint rates {average = .446 per week) over 

twice as high as those who selected space (average = .209 per week). The 

number of individuals in each group is relatively small and the difference 

was not statistically significant. These groups were almost identical for 

the period after six weeks. These data should only be considered suggestive. 

" 
t- • 

ATLANTA 

II Single Cells 

D 3,4,5 & 6 Man Cells 

FIRST COMPLAINTS 

Figure 8 

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37 

Analysis of Confounded Variables Danbury 

The inmates in the various housing units did not differ in regard Housing at Danbury consists of singles, cubicles and dorms. Withto such factors as age, months left, weeks in housing, and weeks in in the singles and dorms it was pOf3sible to make comparisons where social 

prison. There was a significant variation in custody level among the density was constant but spatial dfensity differed. Examination of the 

housing conditions (see Table 3). When one controls for custody by effects of cubicles and spatial density were the primary objectives. 

analysis of covariance, the perceived crowding, #room rating, and blood The design of the cubicles at Danbury FCI was like those ~t El Reno 

pressure effects remain essentially unchanged. with 5-1/2 foot high walls providing 49 square feet for a single occupant 

Summary (see Figure 9). Danbury FCI had many different housing units and differThere was essentially a linear relationship between crowding and 

ent units were assigned to different programs including alcohol abuse, 

both perceived crowding and illness complaints. That social density drug abuse, life skills, and industries. Consequently we were also able 

effects may be more important than spatial density effects at these to examine the influence different programs might have on crowding effects 

levels was seen in the relation between the one and three man cells typically associated with different types of housing (see Table 4). At 

since the three man units had more space per person but higher social the time of our data collection the total inmate population was 669 as 

density. The data from Atlanta are particularly important because they compared to 887 one year earlier. Danbury is a medium security prison 

provide information about housing in the range between double cells and with inmates classified in either security level 2 or 3. The average age 

conventional dormitories. These data indicate that our findings based 

of :l,nmates at Danbury FCI was 36 years. 

on single cells, double cells, and dormitories are applicable to housing Perceived Crowding 

of intermediate social density values. The perceived crowding scores for dormitory inmates were twice as 

high and significantly different from the scores for inmates in cubicles 

I 

'f 

<.' and cells (p < .001). The perceived crowding scores for single cubicles 

and single cells were identical (see Table 5). 

There has been some question as to whether individuals adapt to 

crowding over time. In Figure 10 perceived crowding is plotted 'in terms 

of those who have been in a particular housing condition less than or more 

than six weeks. Clearly there is a slight increase in perceived crowding 

for both the single and dormitory inmates. In this measure, at least. 

" 

" 
-

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i 

i". 

b 

FIGURE 9. Inside view of cubicle, Danbury Federal Correctional Institution. 

,i 

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~ 1.0 .... 

== 

= 

DANBURY FCI ······Dorms 

---Singles 

.................. ma ............. . 

lessthan6 greater than 6 

TIME IN HOUSING (Weeks) 

Figure 10. Perceived Crowding 

Related to Time in Current Housing 

'. 

...... ~10._ 

." '.:'--... - ' 

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TABLE 4 

Danbury Housing Units 

Social Spatial Density Unit Density (sq.ft/person) 

Singles 

Industry 1 60 

Industry 1 48 

Alcohol Abuse 1 60 

Life Skills 1 60 " 

Dormitories 

Industry 65 49 

Unassigned 65 49 

Alcohol Abuse 54 59 

Cubicles 

Unassigned 1 50 

" 
t-- _ 

) 

l' I 

TABLE 5 

Danbury Results 

Variables Singles Cubicles Open Dorms 

Number of Occupants 1 1 54/65 

Space (sq.ft/person) 48/60 50 49/59 

Number of Subjects 60/75 20/24 47/63 

Perceived Crowdinga 1.5 1.5 3.2 

Summary Room Ratingb 25.9 29.7 14.4 

b 

4.6 4.1 2.7 Relaxed 

Weeks in Prison 71.9 61.4 28.3 

Weeks in Housing 21.3 14.8 14.7 

Custody 3.2 3.5 2.6 

Notes: s. A high score is more crowded. 

b. A high score is more positive. 

F-Values 

F(2,157)=79.89, 

F(2,156)=39.60, 

F(2,125)=10.14, 

F(2,156)=32.52, 

F(2,158)= 3.26, 

F(2,155)=20.23, 

Significance 

Levels 

P < .001 

P < .001 

P < .001 

P < .001 

p < .05 

P < .001 

• 

I 

, 

I 

" 

I 

, 

. __ ~ ________ ~ _____________ ~ __ ~~_.......t~ ________________________________ ~$ .I .. ua_---~~-----~---
--'--~----~---.-------- '- '----

42 

there is nOi indicatilon of adaptation to crowd::~.ng over time. The contrary seems more lik1

e1y. Our earli~r work at Texarkana in 1974 yielded 

similar results. Th:l.s does not necessarily conflict with the evidence 

from illness complaints. The temporal course of crowding effects is 

complex and merits further investigation,. 

Housing U~it Ratings 

All cf the six room rating scales yielded more positive scores for 

the single cells and cubicles as compared to dormitory housing. On one 

scaler- Attractiveness, cubicles were rated more favorably than either 

open dormitories or single cells. 'In all other cases the reaponse was 

very similar for cubicles anc single cells and more positive than dormitory scores (see Table 5). 

Mood Scales 

Only one of the scales designed to measure mood and emotional state 

was different for dorms as compared to cubicles and cells. Scores for 

cubicles and cells were equivalent and more positive than dormitory 

scores (see Table 5). 

Ia~ate Complaints 

Inmates were asked an open-ended question as to "some of the things 

that bother you about your housing." We assumed that the first complaint 

mentioned was the most important to that inmate. Figure 11 provides a 

distribution of the percentages of most common complaints. Where the 

complaints were less than 5% in that housing condition, they are shown 

as a uniform short bar. The far left of the graph indicates the per-:-

centage of inmates who did nct offer a complaint or indicated they had no 

• 

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DANBURY FC. 

TYPE Of COMPLAINT 

Figure 11 

• Singles 

~CulJes 

~Dorms 

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44 

complaints. As can be noted 43% of the single cell inmates, 36% of the 

cubicle inmates and 20% of the dorm inmates did not report any complaints. 

There was a significant difference in the "no complaint" category in comparison of single cells and dorms (p < .05) and comparisons of dorms with 

the combined cubicles and single cells (p < .05). The primary complaints 

from single cell inmates concerned noise (10%), the people in their unit 

(6.5%), the amount of space in their cell (14%), and cleanliness (7%). 

Primary complaints from cubicle inmates involved noise (25%) and privacy 

(21%). In the dorms crowding (31%) and noise (14%) were the sources of 

most complaints. 

Illness Complaint Rates 

and Housing 

Illness complaint rates were not substantially different for the open 

dormitories, cubicle dormitories, and single cells for the period representing the first six weeks in a particular type of housing. However, for.' 

the period after the first six weeks there was an overall significant difference (p < .01) between the single cells (average = .081 per week), the 

dorms (average = .165 per week), and cubes (average = .183 per week). The 

difference between the cubesl and dorms was not significant. However, the 

difference between the singles and the combined dorms and cubes is highly 

significant (p < .002). As found elsewhere, illness rates in the dorms 

were over twice as high as in the single cells. 

Illness complaint rates for the cubicles did not change substantially 

from the period of less than six weeks to greater than six weeks. This is 

contrary to the general finding and may account for the lack of differences 

between cubicles and dorms in the period greater than six weeks. We were 

able to establish that illness rates in the cubicle unit (8-0) rose very 

• 

45 

sharply in one six week period shortly before our research visit. Administrators indicated there had been a substantial change in program status 

in the unit at the ttme illness complaints rose. This change left the inmates 

uncertain as to their future program assignments. While we cannot be sure 

that stress aroused by the uncertainty was responsible for an increase 

in illness complaint rates, this seems a plausible interpretation. There 

were several inmates with relatively large scores. If these extremely 

high scores are dropped for all groups, the relationship for the first six 

weeks among housing conditions is similar to the period greater than six 

weeks. The singles (average = .117 per week) were much lower than either 

the cubes (average = .195 per week) or the dorms (average = .237 per week). 

The overall difference is highly significant (p < .001). A similar result 

is obtained if you eliminate all those inmates who had less than six weeks 

in their particular aousing unit. The resulting order is singles (average = 

.103 per week), cubes (average = .218 per week), and dorms (average = .228 

per week) yielding a significant overall difference (p < .003). In sum, 

single occupants clearly have lower illness complaint rates than either 

dormitories or low-partitioned cubicles. 

Additional analyses were conducted in which illness complaints were 

separated into contagious and noncontagious categories. This provided 

an opportunity to examine illness complaints that were not influenced 

by transmission factors. The contagious category is probably overestimated 

since all illnessess, such as rashes and diarrhea, were classed as contagieus even though we are aware that this is not necessarily the case. 

Results for both the contagious and noncontagious categories are shown 

in Figure 12. Note that for the period of less than six weeks the single 

rate would have been substantially less with extreme scores excluded. 

For the period beyond six weeks the Singles rate (average = .031 

per week) is much less than either the dorms (average = .058 

-
,a_ 

~I I 

DANBURY Fel 

Greaterl tun 

6Wt.teks 

CONTAGIOUS 

Figure 12 

" 

'. Sinlles ~ Dorms 

o Cubes 

NONCONTAGIOUS 

• 

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-

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47 

--1 '., 

per week) or the cubes (average = .096 per week). 

Results for complaints in the noncontagious category are also shown 

in Figure 12. For the period less than six weeks the cubes and singles 

have somewhat lower rates than the dorms. In the period over six weeks 

the dorm rate (average = .109 per week) is nearly four times higher (average = .028 per week) than the singles (p < .05). The rates for the cub icles were very similar in the less than and greater than six weeks categories. These results indicate that the differences in illness complaint 

rates between housing conditions is not limited to complaints of contagious 

illness. While dormitories yielded higher illness rates than less crowded 

housing, within the dormitories the typical relationship between high perceived crowding scores and illness complaint rates was not present. 

There were no significant racial differences in illness complaint 

rates at Danbury and the small differences observed were opposite those 

found at all other institutions we examined. 

Illness Complaint Rates 

and Single and Double Bunks 

Danbury provided our only opportunity to examine the effects of single 

and double-decked bunks within the same dormitory. In two dormitories 

.. (6-0 & 4-1) there are both single and double bunks. We compared illness 

rates for two different bunk conditions. Inmates in double-decked bunks 

(average = .351 per week) had 78% higher illness rates than inmates in 

single-decked bunks (average = .197 per week) in the period before six 

weeks. The same trend was found for the period after' six weeks. Here the 

double-decked inmates (average = .152 per w(~ek) had 45% higher illness 

rates than the single bunk inmates (average = .105 per week). Neither of 

the differences was statistically significant and was probably related to 
48 

the fact that the number of inmates in the sample was ra.ther small (N .. 

5 in one group). Consequently these results must be considered as no 

more than suggestive. 

Bother and Illness Complaints 

Inmates who indicated that people bothered them most had higher illness complaint rates thai'/. those uho indicated "space" bothered 

This was true for both the periods before and after six weeks. 

them most. 

This finding was similar to Atlanta but was not statistically significant. 

Spatial and Social Density Effects 

The wide variety of housing conditions at Danbury FC! allowed for 

evaluation of the influence of variations i n spatial and social density 

on our measures of crowding effects. We were able to compare space and 

social density levels in a factorial design that allowed for assessment 

of the independent effects of these variables. This comparison involved 

dormitories versus single cells and 60 square feet versus 50 square feet 

housing. This comparison required combinations of housing groups that 

differed in program assignments. C onse9uently we first determined that 

~here were no significant differences among programs within the spatial 

\ and social conditions. We found significant independent contributions 

of social and spatial density to perceived crowding scores. 

density effects reflected significantly lower scores for the 

The spatial 

60 square 

foot condition as compared to the SO square foot condition in both singles 

and dormitories. Thus ten additional square feet was psychologically perceptible in terms of perceived crowding due to spatial density. The 

effect of space was evident for comparisons both within program housing 

and across program housing. Although a difference of ten square feet may 

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49 

seem relatively small, it represents an incr2ase in free floor space of 

about 40%. 

Potential Confounding Variables 

The length of time in prison, length of time in hou~ing, and custody 

level varied significantly among residents of singles, dorms, and cubicles 

(see Table 5). Only effects which remained significant when these factors were controlled by analysis of covariance are reported. The housing 

assignments at Danbury FCI are organized in terms of inmate programs such 

as alcohol treatment and industries. Consequently we were concerned with 

the possibility that differences in inmate responses in different housing 

conditions might be due to the influence of different programs rather than 

housing variables. We were able to examine this question with regard to 

programs and social density. We assessed the effects on perceived crowding 

of three programs: Industries, Alcohol Treatment, and Unassigned; and two 

social density conditictts: single cell or cubicle versus multiple occupant housing. This analysis yielded a significant social density effect 

but no significant program effect. There was also a significant program 

by social density interaction which suggests program assignment influences 

perceived crowding scores to some degree. Consequently we are confident 

that when program assignment and social density are found to be inextricably confounded, findings with regard to perceived crowding can be attributed 

primarily to social density. 

Summary 

The dorm inmates were much higher on perceived crowding than either 

the singles or cubicles. On both housing unit ~atings and affective scales 

the cubicles and singles were very similar with the dorms giving more 
. 4 

50 

negative responses in each case. Dorm inmates made more complaints 

overall and more complaints about crowding than either the cubicles or 

singles. The dorms were clearly higher than the singles in illness complaint rates. Results from the cubicles were not so clear. Similar 

results were obtained for noncontagious illness complaints and overall 

illness complaint rates. Double-decked bunks had higher illness rates 

than single-decked bunks within the same dormitories. Inmates having 

higher perceived crowding scores had lower illness rates in the dorms. 

Even small changes in spatial density had an effect on perceived crowding with higher spatial density giving higher scores. Possible confounding variables were examined but found to have no statistical significant 

influence. 

The finding that dormitories yielded more negative responses than 

single units was expected and consistent with other findings of the 

project and earlier work. Of particular interest was the finding that on 

all measures except illness complaint rates cubicles resemble single unit 

housing. These data corroborate findings from El Reno, La Tuna, and Fort 

Worth FeI and support the conclusion that cubicles substantially reduce 

most of the negative effects of open dormitories. The illness findings 

are discrepant from those at El Reno, La Tuna, and Fort Worth FeI and as 

indicated earlier may reflect administrative actions. One of the most 

interesting findings at Danbury was evidence that rather small changes in 

available space (ten square feet) can have measurabl~ psychological effects. 

The results from Danbury differ in several significant ways from other 

institutions in this project. First, the cubicles showed no decline in 

illness rates during the period over six weeks. Second, blacks had lower 

illness complaint rates than whites. Third. in the dorms illnf?ss complaint 

l 

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51 

rates for inmates reporting "very crowded" were less than those reporting 

less crowded. The basis for these differences from the general trends is 

not known. They do suggest that in these specific instances the Danbury 

data should be treated with some degree of caution. 
 ... --------~-~----~ 

52 

Texarkana 

The F~deral Correctional Institution at Texarkana is a medium security inntitution which has housed up to 780 inmates. We made research 

visits to this institution on May of 1978 and 1979. The population was 

approximately 710 in 1978 and 510 in 1979. The population was also somewhat older in 1979 than in 1978 (34.1 vs 32.8). 

T,.xarkana FCI was chosen because of its great variety of housing 

conditions. Specifically, inmates are housed in Single rooms, double 

rooms, and dormitories that have from 20 to 50 people in them. Some of 

the Singles and doubles are located along very short hallways while others 

are along relatively long hallways. Two of the dormitories are designed 

so that the inmates are separated into three visually separate groupings 

or bays containing from 10 to 20 inmates per bay and will be referred to 

as speciul dorms. Another dormitory houses approximately 20 inmates in a 

single-bUllk configuration. The different types of housing are summarized 

in Table 6 and Figures 13 and 14 show the population levels of the variol.ls 

units in Texarkana FCI at the time of our two visits. Figures 15 to 18 

illustrate housing types. 

Inmates are assigned on a space available basis to one of the five 

d~fferent units of the prison. Typically they are initally assigned to 

dormitories and then can move to single or double rooms on a seniority 

basis within their unit, 

Texarkana provided the opportunity to make a number of interesting 

comparisons: singles versus doubles, large versus small Singles, singles 

and doubles versus dorms, three different types of dormitories, and unit 

size. These various comparisons allowed an a~sessment of the relative 

importa~ce of spatial and social density. 

1st Floor 

Rooms 

Sing.&Double 

A48 

Rooms 

Double 

• 

Dorm 

~ Food 

p~~:~r~~~o~ .. 

Dining L Hall 

H11 t mm 

~38L I.-.~_ 

~~eJO IC~~L 1:0

1 1--- 18 L '-----~ 

WM1J 

Rooms Dorm Visiting 

Double Room 

2nd Floor 

Rooms 

Double 

B-3 

63 

Rooms 

Double 

Activity 

Center 

Rooms Dorm 

Single 

Old Hospital -

Visiting Room 

Rooms Dorm 

Sing.& 

Double 

Rooms Dorm 

Sing.& 

Double 

Figure 13. Floor Plans and Population 

Levels in Units for Texarkana 1978 

I 

53 

Single R 

I 0 10 

0 

Court 8 m 

Yard s 

10 

East Unit 

R 

0 

10 0 

DB m 

s 

10 

East Unit 
54 

1st Floor 

Rooms 

Sin~~pouble 

A-3 

46 

Rooms Dorm 

Couun Double 27 Dl~e 38 

...1-' 

RoomsJ~_j 

----El 10 1 .r --.- .. _--....... -. 

2nd Floor 

Rooms 

Dauble 

- Rooms 

Double 

Activity 

Center 

-, .......... _-

B-3 Dorm 

38 j ;4 Double 

2 Rooms 

__ fB-4 ,-I ___ 

Rooms Dorm 

Single 

12 

Old Hospital - Visiting Room 

Rooms Dorm 

Single 

Figure 14. Floor Plans and Population 

Levels in Units for Texarkana 1979 

'-__ --..JJ..l 

Regular Singles 

Large Singles (E-dorm) 

Doubles 

Regular Dorms 

At Capacity 

At 75% Capacity 

Single-bunked 

Spaciou.s Dorm 

At Capacity 

At 80% Capacity 

R 

o 

TABLE 6 

Social 

Density 

1 

1 

2 

40 

30 

20 

50 

40 

• 

Spatial 

Density 

(Sq. Ft/Person) 

54 

66 

27 

34 

45 

68 

42 

51 

55 

--, 

I 

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,a ------~---~----------~---- ~--------------------------~---------------------------------------------------------------------------------------------------------------------. .---------------------------------------------

- -- "1 

FIGURE 15. Large single cell, Texarkana 

Federal Correctional Institution. 
_ s~ 

 

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FIGURE 16. Double cell, Texarkana 

Federal Correctional Institution. 

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FIGURE 17. Regular open dormitory, Texarkana Federal Correctional Institution. 
, 

FIGURE 18. A bay of a special dormitory 

Texarkana Federal Correctional Institution. 
60 

Results 

Many new measures were introduced during our second Texarkana visit, 

but a number of measures were the same for both visits. We will discuss 

the results for each individual visit, and for two measures provide an 

analysis of the combined data from both visits. The first analyses presented involve a comparison of the six major types of housing units--regular 

singles, large singles, doubles, regular dorms, single-bunk dorm, and the 

special dorms. We were able to obtain only seven volunteers from the singlebunk dorm. Consequently the data from these iI~ates were not included in the 

statistical analyses, but the means for the various measures are discussed 

and presented in the summary table for reference. During the 1978 Visit, we 

collected data only for the regular singles, the doubles, the regular dorms, 

and the special dorms. During the 1979 visit we collected information on 

all six different types of housing. 

Type of Housing 

Perceived Crowdin&. Perceived crowding varied significantly among the 

various housing conditions in both 1978 and 1979. In 1978, the singles 

were rated as less crowded than the doubles and the dorms. The doubles and 

the regular dorms were rated equally crowded, while the special dorms were 

rated somewhat less crowded than those two (see Table 7). Similarly, for 

the 1979 sample the residents of the regular dorm and the doubles rated 

themselves as "crowded" while the residents of the singles and the singlebunk dorm rated themselves as "moderately crowded" or less (see Table 8). 

The larger singles had the lowest rating of being crowded, while the special 

dorm inmates rated theroselves as less cr'owded than th,e regular dorm inmates. 

These results indicate that both the number of people one is living with and 

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t 

Singles 

54 sq •. ft. 

Variables Na "" 32-33 

Perceived Crowdingb 2.33 

Summary c Room Rating (6 scales) 19.6 

Weeks in Housing 42.0 

Weeks in Prison 89.7 

Custody d 2.6 

TABLE 7 

Texarkana 1978 Results 

Doubles Regular Donn 

27 sq.ft. 34 sq.ft. 

N = 39 N = 45-46 

3.36 3.30 

12.5 11.5 

12.1 12.2 

31.2 24.0 

2.4 2.2 

Special Dorm 

66 sq.ft. 

N = 33-3.5 

3.1 

17.2 

15.9 

17.8 

2.0 

F-Values 

F(3,149)= 8.01, 

F(3,149)=' 8.89, 

F(3,149}=13.37, 

F(3,147)=33.27, 

F(.3,145)=2.93, 

","~~ .... "", .. ,..-~"""-------...-----------------

Significance 

Levels 

p < .001 

p < .001 

P < .001 

P < .001 

p <.05 

=-----.------------------------------.------------~~---~~.~. ------------------------------------------------ Notes: a. N is num~~r of subjects in each.housing type. 

h. A high score means more crowding. 

c. A high score is more positive. 

d. A high score means more favorable custody. 

-. 

, 

l~ 
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TABLE S 

Texarkana 1979 Results 

Regular Large Singles Singles Regular Special Single 

54 sq. ft. Doubles Dorms Dorms Bunk Dorm 

Variables 

N

66 sq.ft. 27 sq.ft. 34/35 sq.ft. 51 sq.ft. 6S sq.ft. 

a=43/50 N = 30/32 N = 35/40 N = 31/45 N = 24/32 N = 4/7 F-Va1ues 

Perceived Crowding b 1.S 1.5 2.9 3.2 2.5 (1.9) F(4,17S)=19.D, Summary Room 

Ratingc (6 scales) 25.S 2S.2 15.6 11.S 16.0 (21. 9) F(4,175)=20. j'S, Summary Room 

RatingC (S scales) 34.4 36.5 21.0 16.3 20.3 

c (27.4) F(4,164)=21.58, 

3.9 3.1 3.1 2.3 2.6 (2.9) F(4,174)= 3.30, 

Relaxed 

Satisfiedc 

3.5 3.2 2.4 2.1 2.5 (4.0) F(4,174)= 3.14, Stimulated 3.7 3.6 3.7 4.0 4.S (4.9) F(4,174)= 2.44, Illness Complaint Rate 

(greater tnan 6 weeks) .14 .14 .08 .33 .23 F(4,106)= 3.62, Diastolic Blood 

Pressure 60.2 65.3 65.4 63.0 64.4 (69.7) F(4,179)= 2.4, Crowding Tolerance 

(Revised Version) 10.6 B.O 9.5 10.!. 7.S (10.3) F(4,172)= 6.01, Weeks in Prison 46.8 64.7 42.9 42.6 2;; .1 (lS.9) F(4,204)= 5.11, Cus tody Level 2.7 2.7 2.7 2.6 2.0 (2.5) F(4,160)= 4.21, Months Left to Serve 16.1 11.3 21.5 11.2 15.3 (J0.9) F(4,169)= 2.63, 

Notes: a. N is the number of subjects in each housing type. It varies vecause all of the information 

was not obtained from all of the inmates. 

b. A high score means more crowding. 

c. A high score is more positive. 

'. 

'. 

0'1 

N 

Significant 

Levels 

p < .001 

p < .001 

p < .001 

p < .02 

p < .02 

p < .05 

p < .01 

p < .05 

p c- .001 

p < .001 

p < .01 

p < .05 

• 

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63 

the amount of space are important factors. Space by itself is impol'tant 

because increasing the amount of space in a single and a uormitory reduces 

the perception of crowding. However, even the special corms (with 40/50 

residents) divided into bays were rated as more crowded than equally 

spacious singles. The combined results for the two visits are shown in 

Table 9. Perceived crowding did not change over time in housing units. 

It should also be noted that absolute values of the perceived crowding scores in 1978 were higher than in 1979 for each of the four housing 

types sampled during both visits and the difference was particularly large 

for single cells. This effect was highly significant (p < .001) and probably reflects the higher population of the prison in 1978 rel,ative to 1979. 

Housing Unit Ratings. During ol .lr 1978 visits we employed six scales 

on a questionnaire to determine inmate evaluation of their housing units, 

and in 1979 we added two more. Since the results on these scales were 

highly intercorrelated, only the analysis of the overall summary scores 

will be presented. The patterns of results for these scores were very 

similar to those obtained with the perceived crowding measures. In the 

1978 sample, the singles were rated most Positively (see Table 7). In 1979, 

using either a six-scale or eight-scale summary score, the singles were 

rated most positively while the regular dorm was rated most negatively. 

The doubles and the special dorm were also rated rather negatively, while 

the single-bunk dorm received a relatively favorable evaluation (see 

Table 8). Thus the ratings were similar for the two visits with the exception of the relatively poorer 1979 evaluation of the special dorms. 

The combined results for the six-scale measure are shown in Table 9. As 

'with the perceived crowding measure the ratings were more favorable in 

1979 than in 1978, especially for regular singles (p < .001). 
__ ____ __ ______ 

rI 

TABLE 9 

Summary of Results for Texarkana FCI - 1978 and 1979 

Regular Regular Special 

Variables Single Doubles Dorm Dorm 54 sq.ft. 27 sq.ft. 34/45 sq.ft. 42/50 sq.ft. F - Values 

Perceived Crowdinga 2.1 3.1 3.2 2.B F (3,300) =21. 01, Overall Housingb 23.5 14.2 12.0 17.0 Rating F(3,294)=28.7l, (6 scales) 

Illness Complaint Rate 

(Without colds and 

and flu) .11 .09 .23 .17 F(3,154)= 4.55, Custody 2.6 2.5 2.4 2.1 F(3,272)= 4.25, Weeks in Prison 64.8 3B.6 34.7 23.6 F(3,327)=19.BO, Weeks in Housing 

Unit 30.3 17.5 IB.6 lB.2 F(3,346)= 6.30, 

.. , 

Notes: a. A high score means more crowding 

b. A high score is more positive 

" 

~ I 

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-., .. 

Significance 

Levels 

P < .001 

P < .001 

p < .01 

p < .01 

P < .001 

p < .001 

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65 

1979. Three of the eight mood scales resulted in significant differences. 

Mood Rating~. Ratings of general mood state were obtained only in 

On the relaxation scale, the regular single inmates were most relaxed, the 

the residents of the other housing units were in between. The satisfacresidents of the regular and special dormitories were least relaxed, and 

tion scale scores showed that the residents of the single cells were more 

bunk dorm rAceived the most positive rating on this scale. The residents 

satisfied than those of the regular and special dormitory. The singleof the dormitories also rated themselves as more stimulated as opposed to 

being relaxed than the residents of the other housing units (see Table 8). 

The mood scale results are not as clear as those of the perceived crowding 

and room rating scales. However, if one takes all three scales into 

for residents of regular and special dormitories than the other residents. 

Illness Complaint ~. Illness complaint rates were analyzed for 

account at the same t:fJne they show a generally more negll-tive mood state 

those inmates who had been at least six weeks in their housing units. Exeluding colds and flu, significant effects of housing on illness complaint 

rate were found both for the 1978 and 1979 data (p < .01 in both cases). 

In 1978, the rates of the regular dorms and the special dorms wers higher 

than that of the doubles and Singles, with the regular dorms having the 

highest rate (see Figure 19). In 1979 we found a similar pattern of results 

(see Figure 20), indicating that high social density dormitory living is 

associated with increased levels of illness complaints. 

Perceived Crowding and Illness Complaint Rates. Inmates from the 

dormitories (combined for 1978 and 1979) who reported themselves as "very 

crowded" had higher illness complaint rates for the period greater than 

six weeks, than those repDrting less crowding. Data from double cell 

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TEXARKANA 1978 

Doubles Specia,I Regular 

Dorms 

Figure 19 

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TEXARKANA 1979 

Large 

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Figure 20 

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Special 

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Regular 

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______________________ ~ ______ ~ ____ ~ __________ ~ ____________________________ '_________ i_= __________________________________ _ 
~.~.--------~~--~--~~--------~-------

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68 

i~~ates for. 1978 and 1979 were. also combined and gave the same sor~ of 

results. Although these findings were not statistically significant, 

the results for both the dormitory and doubles agreed with results from 

other institutions, except Danbury. 

Blood Pressure. There were no significant differences :i.n blood 

pressure among the housing units in 1978. However, in 1979 a significant 

diastolic blood pressure effect was found with regular singles inmates 

having lower blood pressure than those in the other types of housing 

(see Table 8). 

Control and Choice. In 1979 we asked several questions to determine the extent to which inmates felt some degree of choice or control 

over their lives in the prison. The only finding for the questions was 

a trend for the doubles and regular dorm inmates to feel somewhat less 

control over others. This finding is in the expected direction but only 

marginally significant (p < .10). 

Crowding Tolerance. During the 1978 visit we ~mployed a task that 

we had used in previous studies to examine crowding tolerance. This task 

in~rolved the actual placement of small figures into a miniature room until the inmate felt it was crowded. Th 'd - e room was sa~ to represent an 

open dormitory drawn to scale relative to the size of the figures which 

represented people. It was assumf:!d that placing more figures in the room. 

would represent greater tolerance of crowded living conditions. The analysis of the. results from this task revealed no significant differences 

among the housing conditions, 

During our 1979 visit we employed a revised version of the tolerance 

task that consisted of showing the i,mates drawings of increasingly crowded 

dormitories. They were asked to say at what point having any more bunks in 

.. 

--l 

69 

the dormitory would make it too crowded. Again, a higher score here 

would reflect greater tolerance. The analysis of these data revealed 

that the residents of the East Unit which contained the large singles 

and special dorms had a lower tolerance than residents of the other 

houstng types (see Table 8). The crowding tolerance of the residents 

of doubles was slightly greater than East Unit residents. Scores for 

inmates in other housing types wer~ similar to each other and represented 

the highest tolerance scores. It is interesting to note the average tolerance for a dormitory that was drawn exactly to the scale of the regular 

Texarkana dormitory was about 9.5 people. This contrasts to a typical 

population of 30 to 40 inmates. The results for the tolerance measure 

do not show a clear relationship to either social or spatial density. 

They do indicate, however, that the crowding experienced in the dormitories is greater than the expressed tolerance. 

Analysis of Confounde~ Variables. The residents of the various 

housing units also differed in time in prison, custody level, and months 

left to serve on sentence (see Tables 7 and 8). Controlling statistically 

for these factors did not reduce any of the reported findings to statistically unreliable levels. In fact, in almost all cases, the effects 

remained strong. I~ addition, it should be noted that on five other 

measures signifj.cant eff~cts of housing type were obtained, but these 

effects disappeared when one controls for one or more of the confounded 

variables and hence are not reported. 

Additional housing Comparisons 

Dormitory Density. Earlier we reported that the special dormitory 

and the single-bunked dorm were rated more favorably than the regular 
70 

dormitories. However, the regular dormitories actually had two different population levels. In 1978 all of the regular dorms tested had about 

40 Occupants. In 1979 only one regular dormitory was at this level while 

the other regular dormitories had populations of about 28 inmates. Because of sample size limitations, the only feasible comparison involved 

comparing the 40 person dorms with the 28 person dorms. This, of course, 

confounds dorm size with visit. However, there were no significant differences between these two dormitory conditions in either perceived crowding or housing unit evaluation. It appears that in densely populated open 

dormitory environments, moderate reductions in number of people do not 

significantly reduce negative emotional reactions. This lack of change 

in ratings is also somewhat surprising in light of the almost 25% reduction in total institutional popUlation that occurred between the two visits. 

Regular Dorm versus SpeCial Dorm. Our earlier analyses indicated 

that the special dormitories produced generally more positive reactions 

than the regular dormitories. This result is quite interesting since it 

suggests that dormitory design and arrangement may be an important influence 

that is independent of spatial and social density. To determine more precisely the nature of the differences between these two types of dormitories, 

results from these two dormitories were analyzed separately. For those 

measures cornmon to both visits, the data were combined for the analyses. 

The other measures reflect data obtained only in 1979. For the combined 

data, it was found that the regular dorms were rated as more crowded and 

evaluated more negatively on the housing evaluation scales than the special 

dorms. For the period greater than six weeks, the regular dorms had 62% 

higher illness complaint rates (p < .05). The regular dormitory inmates 

had also been in the prison longer and had a higher custody level. The 

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analysis of measures unique to the 1979 visit revealed that the regular 

dorm irunates felt less relaxed and had mOLe tolElrance for croloJding than 

special do:rm irunates. Analysis of cuvariance c()ntrolling for the contributions of weeks in pr.ison and custody e.limil.liated only the relaxation 

effect. 

The general conclusion that can be drawn f:r:om these results is that 

71 

dormitory design can have a significant impact on irunate reactions. Even 

though the sp,ecial dormitory hou13ed more residents overall than the regular dormitory, the residents in this special dormitory were segmented 

into three visually separated bays. The special. dorms also had mostly 

single bunks and somewhat more space per person. All three of these factors may have contributed to the relatively favolrable reactions of the 

special dormitory irunates. 

Large versus Small Singles. These two cell types were compared to 

determine more precisely on what basis these two differed. The small 

singles had 54 square feet of space while the large ones had 66 square 

feet. The small cells are represented in four of the prison units, but 

the large singles are found only in the East Unit. The inmates in the 

large cells had been in the institution longer; this factor was controlled 

by analysis of covariance. The only effects obtained were that the large 

cell inmates had higher diastolic blood pressure (p < .01), rated their 

rooms as more attractive (p , .07), and had less tolerance for crowding 

(p < .01) than the small cell inmates. The finding suggests that small 

increases in space for regular size single cells did not have a beneficial 

impact and is inconsistent with our findings from Danbury. 

Singles versus Doubles. Since residents in doubles have a shorter 

time in prison and in housing, the following analyses controlled for 
• 

--, ! 

72 73 

these factors by analysis of covariance. Comparison of the residents in 

these two housing types indicated that the doubles residents rated their 

unit as more crowded and less attractive than did the singles resideats 

(p < .001). The doubles residents also felt relatively less wide awake 

and less satisfied (p < .05). They also seemed to be relatively less 

tolerant of crowding as indicated by lower tolerance (p < .08) and higher 

ideal scores (p < .05). At Texarkana the doubles lead to more negative 

the small units felt least crowded, had the highest ideal scores, and 

h.ad the most problems with headaches. Since the residents of the medium 

size units had been in the institution the longest, appropriate analyses 

of covariance were performed. None of the effects were changed subs tantially as a result of these analyses. While these results suggest that 

smaller units may be somewhat preferable, it is quite clear that this 

variable was not a major contributor t~ stress-related reactions at 

Texarkana FCI. 

reactions than singles, but these reactions were not severe enough to 

lead to statistically significant differential illness complaint rates. Housing Complaints 

Unit Size. At Texarkana FCI the residents who are housed in singles Housing complaints for 1978 and 1979 were combined since there was a 

and doubles live in units that vary greatly in number of rooms on the very high degree of uniformity between the two years. In Figures 21 & 22 we 

corridor. Some have only ten rooms and ten residents while others have have plotted the complaints by racial groups. In those categories where 

up to 32 rOOins and 64 residents. The popUlation of these units vary with there was a substantial percentage of complaints there are some clear 

institutional population and consequently differed somewhat beu~een our racial differences. Percentages of responses from the Mexican Americans 

1978 and 1979 visits. The work by Baum and Valins (1977) suggests resi- and blacks were much mo~e similar to one another than to the Anglo Ameridents living in large units will show more negative psychological reactione cans. The principal differences by category were in: the no complaint 

than those living in small units due to the high number of unwanted inter- category, where Anglos were much lower; noise, with Anglos substantially 

actions encountered in the lar-ge units. By combining the subjects from higher; space, where :.oglos were lower; crowding, where Anglos were much 

both visits we were able to compare the effects of living in small (10-22), higher; and people, with Anglos the lowest. The differences in distribumedium (23-33), or large units (34-63). Since these units do not have an tion of complaints were statistically significant (p < .01). 

even number of single and double-bunked residents, this fac.tor was analyzed The basis of these differences is not clear. For example, differin conjunction with the unit size factor. ences in the degree of literacy may be an important factor. Attitudes 

Only a small number of significant effects were obtained. In contrast toward criticism of a system may also be quite different. Unfortunately, 

to the other residents, residents of the medium size units rated themselves Texarkana 1s the only institution in which we had sufficient numbers of 

as more crowded~ having less choice about recreation actiVities, and having the three ethnic groups--Mexican Americans. Blacks, and Anglos--to make a 

less problem with headaches, and they gave a lower score when asked what comparison. While the differences are quite interesting and potentially 

the ideal number of residents in a dormitory would be. Th~ residents of important, additional data are badly needed. 
,c 

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-~--~------------------~------------,..------------- --------- ---

TEXARKANA FCI 1978 

• Blacks 

~ Mexican Americans 

& Mexican Nationals 

o Anglo Americans 

TYPE OF COMPLAINT 

Fiogure 21 I 

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TEXARKANA FCe 19719 

TYPE OF COMPLAINT 

Figure 22 

o Anglo Americans 

• Blacks 

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76 

Summary 

At Texarkana perceived crowding and m~gative room rating increased 

with increased social density and spatial density. Doubles were rated 

more negatively than sil:ngles, and dormitciries (exc:ept for the spacious 

single-bunk dorms) were rated most negatively. Measures of mood and i11-

ness complaint revealed primarily negative effects of dormitory living 

relative to other housing. Thus, while evaluation of housing units is 

affected both by amount of space and. number of people in the unit, negative mood state and il1llees ccmpl~d.nt rates were elevated only in socially 

dense dormitories. A v~riation of twelve square feet of space in the 

single rooms had very little effect on resident reactions. However, 

singles were rated much more favorably than doubles with half the space 

per person. Illness rates did not vary significantly for singles and 

doubles. 

The special dormitory residents rated their environment more favorably, felt more relaxed than regular dorm inmates, and ha.d lower illness 

complaint rates. Yet a reduction of ten inmate$ in the regular dormitories 

did not ameliorate the negative reactions to this dormitory. 

The number of residents living in a unit of singles and doubles did 

not appear to have a systematic influence on inmate reactions. 

The inmates gave more favorable reactions during the less crowded 

1979 visit than during the 1978 visit (except for the regular dormitory 

inmates). This finding indicates that overall density of the prison housing areas is also a contributor to inmate evaluation of their living environment. 

f 

I 

·r • 

77 

La Tuna 

The La Tuna Federal Correctional Institution consists of a medv~ 

security prison and a minimum security camp. The La Tuna facility was 

chosen as a research site because it offered a unique opportunity to 

compare the responses to hous~ng conditions of Anglo American, Mexican 

American, and Mexican National inmates. Since there are substantial 

numbers of the latter two ethnic groups in U.S. prisons it seemed, imp ortant to determine if they differed in any significant ways from}~lo 

Americans in. their responses to vB,rious degrees of social and spatial 

density. We made data collection visits to La Tuna FeI in July 1978 and 

May 1979. Toe housing in the prison consists of an honor dorm of two man 

cells and se'Jeral large double-bunked open dorms containing from 65-70 

occupants. The space per person in the honor dorm double cells is 27 

square feet and in the large open dormitories approximately 30 square 

feet. The camp hou$~g consisted of bays or cubicles which contained three 

or four m~n d~ring 1978 and four men in ~979. These cubicles are shown in 

Figure 23. They provided 31 square feet per person when occupied by four 

occupants" Figure 23 and 24 are photographs of the two types of prison 

housing. Total institutiunal population during both research visits was 

approximately 700. The 1918 visit provided data from the three types of 

housing for Anglo Americans and a cQmbined Mexican American-Mexican 

National sample. The 1979 visit focused on two typ~s of housir~, camp 

cubicles and prison open do·rms. Data were obtained from three separate 

ethnic groups: Anglo Americans, Mexican Americans, and Mexican Nationals. 

A substantial number of Mexican Nationals are inc,arcerated at La Tuna for 

illegal entry involving no other individuals~ To insure that all three 

ethnic groups were approximately comparable in terms of offense history 

-., i 

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.. --------__ ------------------·------------------------__ --'----------~----------~.r-'---------------------------------------

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FIGURE 23. Cubicle in Compo Unit, La Tuna Federal Correctional Institution. 

I 

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, 

FIGURE 24. Large open dormitory, La Tuna Federal Correctional Institution. 
Ie 

80 

we i.ncluded in our sample only Mexican Nationals convicted of some 

offense other than individual illegal entry. Spanish-speaking assistants were employed with Spanish-speaking inmates and Spanish language 

The majority of analyses for the La Tuna 1978-1979 v~sit8 are two 

factor ANOVAS with housing and ethn1.c group as factors. Findings from 

these analyses, presented in tables 10 and 11, represent analyses that were 

significant when several potantial confounding variables such as length 

of time in prison, length of time in housing, months left to serve, and 

age were used as covariates. 

1. Perceived crowdi~. In the 1978 sample, perceived crowding was 

signifi'cantly different for housing conditions ( p < .002) and for ethnic 

group (p < .001). The camp cuaicles were perceived the least crowded as 

compared to the open dormitory or dou~le cells in the prison. The double 

cell inmates yielded lower ratings relative to the dormitory inmates but 

the difference only approached statistical significance with a one-tailed 

test (p < .08). Anglo Americans had higher perceived crowding scores than 

the combined Mexican groups. 

In our 1979 sample the Anglo Americans were substantially higher in 

measures of perceived crowding than the Mexican American and National inmates. Mexican Americans had higher perceived crowding scores than 

Mexican Nationals. A two-factor ANOVA yielded significant effects for 

housing condJ.tions (p < .001) and ethnic groups (p < .001). Thus both 

ethnic group and housing influenced perceived crowding. Dormitories were 

perceived as more crowded than camp housing and Mexican Nationals felt 

• 

81 

least crowded and Anglo Americans most crowded in each housing condition. 

Figure 25 illustrates the perceived crowding score for each ethnic group 

in each'of the two housing conditions. 

Housing Un:f,t Ratings 

For the La Tuna 1978 visit two factor ANOVAS for housing and ethnic 

group indicated that fou~ of the room rating scales were significantly 

different for housing conditions and ethnic group. The scales that yielded differences were Attractive--Unattractive, Right Number of People--Too 

Many People, Unpleasant--Pleasant, Comfortable--Uncomfortable. The 

cubicles were rated more positively than the double cells and dormitories 

which were equivalent in value (p < .01). It is particularly interesting 

that four-man cubicles were rated more positively than double cells indicating that higher social density can be compensated for by one or more 

variables represented in the camp environment, one of which is slightly 

greater spaCE~ per person. With regard to ethnic groups, Anglo Americans 

rated their housing less positively than the combined group of Mexican 

Americans and Nationals. 

For the La Tuna 1979 visit a summary housing unit score was employed 

that reflected the sum of all six rating scales. Significant differences 

between dormitory and cubicle residents were obtained for summary housing 

unit rating with cubicle residents rating their environment more positively. 

There were reliable differences in housing rating relate': to ethnic group 

membership as well. The Anglo American and Mexican National groups were 

the most different in all cases but the Mexican American ratings shifted 

toward one or the other ethnic group for different questions. In general, 

Anglo Americans viewed their environment as less attractive than the Mex.-

ican National residents. 
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F'lgure 25 

LA TUNA Fe. 1979 

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Housing Complaints 

As can be seen in Figure 26 the pattern of housing complaints for 

the cubicles and dorms is quite different. The difference in crowding 

the dorms was almost five times as great as those from the cubicles. A 

complaints is most striking. The percentage of crowding complaints from 

goodness-of-fit test indicates this difference is highly significant 

(p < .01). 

Affect Scales 

The data collection for the 1979 La Tuna visit included use of several scales to measure emotional state or mood. Two self-affect scales 

were reliably different with regard to ethnic group. These were Questions 5 (Satisfied--Unsatsfied) and 8 (Tense--Calm). On question 5 

Mexican Nationals Yielded the most Positive affect and Anglo Americans 

the least Positive affect with Mexican Americans equidistant between the 

other ethnic groups. For question 8 the Anglo Americans reported less 

tension and Mexican Americans the most with Mexican Nationals in between. 

Illness Complaint Rates 

Ethnic Groups. For the 1979 sample, a two-factor ANOVA of illness 

complaints with housing and ethnic group as factors yielded a significant 

effect for ethnic group (p < .05). Anglo Americans had the highest weekly 

illness complaint rate (.18) followed by Mexican Americans (.13) and finally Mexican Nationals (.07). A similar finding was obtained for illness 

complaints with colds and flu excluded (p < .033). For the La Tuna 1978 

sample ethnic group differences between Anglo Americans and a combined 

sample of Mexican Americans and Mexican Nationals did not achieve statistical significance but was in the same direction as the ethnic difference 

83 

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No Complaint 

lA 'TUNA feD 1979 

Noise Space 

TYPE OF COMPLAINT 

Figure 26 

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observed in the 1979 sample. The Anglo Americans had higher illness 

complaint rates than the combined Mexi.can American and Mexica.n National 

inmates. The nurriber of Mexican Nationale~ and Mexican Americans was much 

less than in the 1978 sample and the necessity of combining them for 

I statistical analysis probably accounts for the attenuation of differences 

between those inmates and the Anglo Americans. 

Data on illness complaints were combined for 1978 and 1979 for the 

period greater than ~; ",x weeks and analyzed in terms of ethnic idp.ntificaI tion. The Anglo American group had much higher illness rates than either 

the Mexican American or Mexican National groups. The difference was 8ignificant (p < .012). 

Housing Conditions. A two-factor ANOVA for the 1978 La Tuna data 

yielded significant differences among housing conditions with dor-illitory 

illness complaint rates highest, .28 complaints per week as compared to 

.16 for camp cubicles and .13 for honor double cells (p < .01). Illness 

complaints with colds and flu excluded were also different but fell just 

short of statistical significance (p < .06) when time left to serve was 

employed as a covariate in an analysis of covariance. Unl1.ke perceived 

crowdip~ scores, the illness complaint rate was significantly higher for 

the period after the initial six weeks (p < .05) and near significant 

for the initial six week period (p < .06). The illness complaint rate 

for the dormitories was over twice as high as the double cells in both 

cases. For the period less than six weeks the dorm illness complaint 

rates were over twice as high as the cubicles. The difference was significant (p < .025). In the period over six. weeks dorms were over three 

times as high as the cubicles. The difference was highly significant 

(p < .001). 

• 
42 

l 

• 

86 

In 1979 sample illne$s complaint rates for the dormitories (average 

rate = .127) were about three times as high as for the cubicles (average 

rate = .044) fo~ noncontagious illness complaints occurring during the 

first six weeks of st~y in housing. The difference was signifi~ant 

(p < .05). As in our other findings at other prisons, dormitory illness 

complaints declined in the period beyond the first six weeks of stay. 

However, quite unexpectedly, illness complaints of cubicles residents 

rose substantially after the first six weeks. The failure to find higner 

illness complaints in the crowded dormitories i;ol' the post six-week period. 

was discrepant from our fin~:lj.nga obtained in our 1978 visit as well as our 

finding.s f1!'om other institutions. A detailed analysis of the data indicated a four-fold increase in noncontagious illness complaints occurred 

during a six-week period in the six months preceding our visit. We determined that the period of increased illness in the camp was associated with 

a particular phys,icia.'l' s assistant and the elevated rates existed only 

during the time the assistant served at the c~JnP; eonsequently the elevated 

illness complaint rates probably eliminated what would otherwise have been 

a difference in illness complaint rates between the tl170 he-us,ing conditions. 

For housing stays of less than six weeks the overall illness complaint rate 

findings for La Tuna 1979 were not statistically significant but were in 

the slame direction as those observed for La Tuna 1978 in the camp and open 

dormitory. That is, the dormitories yielded 41% higher illness complaint 

rates (average = .190 per week) than the camp cubicles (average = .135 per 

week). 

Illness Complaint Rates 

OVer Time 

In Figure 27 we have plotted the course of illness rates. The first 

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1-2 3-4 5-6 7-10 11-14 15-18 19-22 ! 

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88 

six weeks are plotted in Ovo week blocks. The remaining data are shown 

in four week ~locks. It appears that as indicated ~lsewhere illness complaint rates are highest during the first six weeks. The curve thereafter appears to be relatively flat. 

Perceived Crowding and 

Illness Complaint Rates 

As found at all other institutions, except D2~bury, there was a 

strong relationship between perceived crowding and illness complaint 

rates at La Tuna for 1978 and 1979. In 1978 the combined cubicled dorm 

and doubles were compared on the basis of those rating their housing 

"very crowded" and those rating "moderately <!rowded" or "uncrowded." 

Those rating "very crowded" had an illness rate four and one-half times 

as large as the less crowded raters for the period greater than six weeko. 

The difference was highly significant (p < .001). The same comparison 

for the period of less than six weeks was not significant. However, those 

rating "very crowded" had approximately 60% higher illness complai:::lt rates. 

For 1979 the only Possible comparison was for the dorms. For the 

period less than six weeks, the illness complaint rate for those r.ating 

"very crowdedQ1 was over three times as high as for those rating "moderately 

cro".rded" or "uncrowded." The differ i ifi t ( 02) ence was s gn can p <. • In the 

comparison for the period greater than six weeks those rating "very crowded" 

had approximately 90% higher illness complaint rates. The difference was 

not significant. 

Blood Pressure 

In the 1978 sample no differences were found between housing conditions 

in blood pressure measures. For the 1979 La Tuna sample systolic blood 

• 

pressure was higher among camp residents as compared to dormitory residents (p < .003), while no difference was observed for diastolic blood 

pressure. No difference was observed among ethnic groups in blood 

pressure. This finding is inconsistent with earlier findings reported 

by ourselves and others indicating higher blood pressure in more crowded 

conditions. 

Crowding Tolerance Task 

During the 1978 visit we employed the model room version of the 

Crowding Tolerance Task. This version failed to differentiate housing 

or ethnic group. During our 1979 visit to La Tuna FCI we employed a 

modification of The Crowding Tolerance T,ask that required subjects to 

simply indicate both the ideal and the highest tolerable number of beds 

in a dormitory by selecting from a series of drawings of a dormitory 

89 

with various numbers of beds. A two-factor ANOVA for housing and race 

indicated that this test, when ideal number was examined. reliably differentiated residents in the two types of housing dormitory and cubicles 

(p < .001) but yielded no difference for ethnic group. The higher scores 

for dormitory residents (18) a3 compared to camp residents (9) indicated 

the ideal number of occupants was higher as crowding increased. There 

were no differences for housing conditions or ethnic groups when the value 

for the highest tolerable number of beds was examined. 

Choice Questions 

The feeling of having choices in a situation can influence the amount 

of psychological stress associated with a particular environment. Consequently for the La Tuna 1979 visit residents of various housing conditions 

were asked how much choice they felt they had over certain aspects of their 

t 
90 

living situation. None of these questions yielded different scores for 

the cubicles as compared to the dormitory. However, one of the four 

questions, Choice of Living Unit, was an3wered differ~ntly (p < .001) by 

the three ethnic groups. Anglo Americans felt the least choice over 

these variables, Mexican Nationals the most 5 and Mexican Americans fell 

approximately midway between. These findings suggest the interesting 

possibility that perception of more choice in their situation may lead 

Mexican Nationals to perceive their prison environment more positively 

and attenuate crowding-induced stress. 

Control 

In the La Tuna 1979 visit questions pertaining to control over one's 

situation or other people were used. Neither question ~as answered differently in relation to housing condition. With regard to ethnic groups, 

Mexican Nationals viewed themselves as having more control over others 

than the other two ethnic groups (p < .01). There were no ethnic group 

differences in response to a question regarding control over one's situation. 

Summary 

The findings from the La Tuna visits clearly indicate that there are 

sUbstantial differences in the perception of crowding among three ethnic 

groups: Anglo American, Mexican American j and Mexican Nationals. The 

Anglo Americans yielded the lowest tolerance of crowding and Mexican 

Nationals the highest as indicated by measures of perceived crowding. 

These findings were paralleled by illness complaint rates which were highest for Anglo Americans. The 1978 findings also indicated that open dorrnitory housing generated higher illness complaint rates as compared to doubles 

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91 

or four-man cubicles. The cubicles were associated with much lower perceived crowding scores than the double cells or dormitories in the prison. 

In the 1979 sample the cubicles were again associated with much lower 

perceived crowding scores than the dormitories. Some affect measures 

were different in relation to ethnic group but not housing condition. 

Housing unit ratings differed both with respect to housing condition and 

ethnic group with lowest ratings associated with dormitories and Anglo 

American inmates. 

--I , 

, , , 
.. 

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r- - ........ 

\ 

TABLE 10 \0 

I\J 

La Tuna 781 

Variable Significance F-Values Values 

Perceived Crowding 

Doubles Cubicles ~ 2.8l(N=25) 2.l9(N=27) 3.02(N=42) F(2,93)= 6.89, p < .002 Illness Complaint Rate .13 .16 .28 F(2,87)= 4.91, p < .01 Housing Unit Rating 

Attractiveness 2.84 4.56 2.22 F(2,92)=11.73, P < .001 Optimal Occupants 

Pleasant 

2.32 4.14 2.00 F(2,92)= 7.86, p < .001 1.48 2.97 2.19 F(2,92)=14.20, P < .001 

Anglo Mexican 

Perceived Crowding 3.05(N=64) 2. 17 (N=35) F(1,93)=20.l2, p < .001 Housing Unit Rating 

Attractiveness 2.56 3.88 F(1,92)= 5.25, p < .024 Optimal Occupants 1.87 4.17 F(1,92)=27.70, P < .001 Pleasant 1.15 2.19 

Comfort F(1,92)=18.4l, P < .001 2.68 3.93 F(1,93)= 8.67, p < .004 

1 

Group sizes vary slightly across variables due to missing values. I 

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Variable 

Perceived Crowding 

Systolic Blood Pressure 

Crowding Tolerance (Ideal) 

Summary Housing Rating 

Frequency of Talk to Others 

Feeling-Satisfaction 

Perceived Crowding 

Illness Complaint Rate 

Summary Housing Rating 

Choice, Living Unit 

Control of Others 

Feeling-Satisfaction 

Feeling-Tension 

Sport Participation 

Dormitor~ 

2. 79(N=49) 

117 

18.13 

17.59 

2.82 

2.71 

Anglo Am. 

3.08(N=25) 

.18 

16.38 

1.36 

2.07 

2.50 

3.29 

.41 

"-::-' 

TABLE 11 

1 La Tuna 79 

Cubicles 

1. 92 (N=38) 

126 

9.22 

25.48 

2.41 

3.98 

Mex. Am. 

2.62(N=3l) 

.13 

19.42 

1.60 

2.96 

3.24 

4.13 

2.05 

Mex. Nat. 

1.S8(N=3l) 

.07 

26.77 

2.32 

3.99 

3.95 

4.75 

2.97 

lGroup sizes vary slightly across variables due to missing values. 

\ , 

F-Values 

F(1,8l)=21.90, 

F(1,78)= 9.68, 

F(1,79)=15.90, 

F(1,79)=20.99, 

10'(1,75)= 5.16, 

F(1,80)=10.74, 

F(2,8l)=21. 79, 

F(2,69)= 4.10, 

F(2,79)=12.92, 

F(2,80)=10.97, 

F(2,79)= 7.11, 

F(2,80)= 4.97, 

F(2,79)= 3.29, 

F(2,79)= 8.86, 

• 

" 

.i

1 

Significance 

Values 

p < .001 

p < .003 

P < .001 i 

.\ 

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P < .001 4 

-I 

p < .026 

P < .()02 

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p < .001 d --, 

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p < .02 1 

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p < .04 

p < .001 

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-

94 

Fort Worth 

We had several objectives at Fort Worth FCl. It presented a 

unique opportunity to gather data in an institution housing both males 

and females, allowed for male-female comparison, and provided for examination of both high and low-partitioned cubicles, singles, and dorms. 

The institution hes at least ten different types of housing. Females 

are typically housed in single and double rooms and low-partitioned 

cubicles. Occasionally they are housed in groups of five to six in open 

bays at the end of large corridors. The rooms were 10' by 8-1/2' and 

9' by 12' yielding 85 square feet and 108 square feet for Single inmate 

rooms. The cubicles were approximately 8 0 long and 6' wide yielding 48 

square feet of space per person. The partitions were 5-1/2' high. The 

males were housed in comparable housing units as well as high-partitioned 

one, two, and three-man cubicles and non-partitioned dormitory housing 

with 15 men. The one three-man cubicle was twice as large as the one and 

two-man cubicles. Some men were housed in open spaces adjacent to the 

cubicles. 

Fort Worth FCI is a minimum security institution and is one of only 

two Federal prisons housing both males and females. Because of the proximity of this institution a number of Visits were made during a one-year 

period. During that year institutional population ranged from 596 to 653. 

The average age. of the inmates was in the low 30's. 

A large percentage of the inmates spend relatively short times at 

Fort Worth. Records and measures on 212 inmates were collected. However, 

due to the fact that at this institution there were both males and females t 

a wide range of housing conditions, and generally short confinement. times, 

sample sizes were in some instances too small for analysis. 

I 

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fill/ J f114 IH'I~ tlt·",~ t:l.ClJlly identical. 

(}J.'()W.I1II1~tJ~(g£.rance. Tolerance 

1111 uti 11110111 hifH: was greater for the 

- - -

.-==::::: ::::::--' -'-_..e<;, 

for cl~()wd Illf-! til:! IIllIi''''III,.',1 I I • Ii , '\I I I H II' Ill!! 

residentll or 1/t/3 111"11,11'" 'I 

' i 11/11 "1/ 11'/1 

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4 

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Males 

~ Females 

Uncrowded Moderate!y 

Crowded 

Crowded 

Percentage of Perceived Crowding 

FORT WORTH FCI 

Very 

Crowded 

Scores In Each Category (low Partitioned Cubicles) 

Figure 28 

" 

• 

" 
,tQ 

TABLE 12 

Results of Singles and Cubicles Comparison for Fort Worth 

Variables Singles 

Males Females 

Number 37 51 

Space per Person 

(sq.ft.) 85/108 85/108 

a Perceived Crowding 1.5 1.7 

Room Rating b 

(6 scales) 29.6 30.1 

Talking 2.8 2.9 

Crowding Tolerance 17.0 10.5 

Cubicles 

Males Females 

17 27 

49 49 

2.2 2.1 

20.8 21.0 

2.4 2.6 

10.4 9.8 

Significance 

F-Va1ues Levels 

F(l, 130) = 8.62, p < .01 

F(l, 129) = 30.22, p < .001 

F(l, 129) = 3.42, p < .07 

F(l, 130) = 5.94, p < .02 

Note: The scores of males and females were combined for the analysis. 

a. A high scores is more crowded. 

b. A high score is more positive. 

, 

, i 

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rI 

TABLE 13 

Results fo~ Male Housing at Fort Worth 

Variable Singles High Cubes Low Cubes Alcoves Open Dorm 

Number 37 28 17 18 21 

Program Drug Health Alcohol Drug Orientation 

Social Density 1 1/3 1 5/6 15 

Space 

(sq.ft./person) 85/108 60/120 48 80/96 74 

Perceived Crowding a 1.5 1.2 2.2 2.3 2.6 

Room Rating b 

(6 scales) 29.6 30.0 20.8 22.0 18.9 

Crowding Tolerance 17.0 17.2 10.2 17.2 10.9 

Talking 2.8 3.2 2.4 2.5 2.4 

Note: a. A high score means more crowded. 

b. A high score is more positive. 

"".,.' ~',;'='=:'."~=C=-'i:7::'= • :;-:';. ... :::;.r~::::=-::-~ .::~::"":'~::.::.:-_~:::::-:-'-.-.~:::::~.~'--:~ ~.:~ " 

Significance F-Value Level 

F(4, 116) = 10.75, p < .001 

F(4, 114) = 9.46, p < .001 

F(4, 116) = 2.72, p < .05 

F(4, 116) = 2.61, p < .05 

-,0; .~"-<'- " , ~ 

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99 

residents of the c~bicles. This effect was due primarily to the males, 

however (Table 12). 

Talking. There was a marginally significant effect for both the 

male and female residents of the cubicles to report that they spend less 

time talking with others than the residents of the singles (see Table 13). 

Comparison of Male Housing Units 

There were five different types of housing for which we had a sufficiently large sample of males for statistical analysis--singles, high 

cubicles, low cubicles, alcoves at the end of hallways, and an open dormitory. 

Perceived Crowding. As seen in Table 12, the residents of the 

singles and high cubicles gave similarly low ratings of perceived crowding relative to the residents of the other units. The residents of the 

open dorm gave the highest crowding ratings. 

Housing Unit Rating. The ratings of the housing on the six scales 

produced a similar pattern to perceived crowding with the singles and high 

cubicles residents giving a relatively positive response and the open dorm 

inmates the most negative response (see Table 13). 

Crowding Tolerance. The tolerance for crowding scores were lower 

for the r.esidents of the open dorm and the low cubicles than for the other 

residents (see Table 12). 

Talking. The residents of the singles and high cubicles reported 

more talking than the other residents. 

Illness Complaints 

and Housing 

Only a limited number of comparisons were possible since sample size 

,. --- '1 
,= 

100 

was too small in a number of cases. A comparison between men housed in 

singles and those housed in open sleeping areas indicated that in illness complaint rates for the period over six weeks the open areas had 

rates over twice as high as the singles. This is in agreement with findings at other institutions except that in this case the differences were 

not statistically significant. 

In the period before six weeks illness rates for men in singles were 

slightly lower than for low-partitioned cubes. High-partitioned cubes 

had much lower illness complaint rates than either singles or low-partitioned cubes. The differences were not significant. In the period over 

six weeks illness complaint rates for singles were slightly lower than the 

high-partitioned cubes. For women, illness complaint rates in singles 

were about half as high as low-partitioned cubes in the period less than 

six weeks. This difference was not significant. However, when data from 

men and women were combined the ISingles were significantly lower (p < .05) 

than the low-partitioned cubes. 

Race and Illness Complaints 

For both men and women, whites had higher illness complaint rates 

than blacks for the periods less than and greater than six weeks, although 

the differences were not statistically Significant. 

Sex Differences and 

Illness Complaints 

In the single8, womens' illness complaint rates were higher than 

males in both the period before and the period after six weeks. In the lowpartitic·!'.~d cubes female rates were over twice as high as the men for the 

period less than six weeks, although the differences were not statistically 

signif ican t • 

i 

\ 

• 

Summary 

The reactions of males and females to their housing environments 

were quite similar suggesting that females as well as males will show 

negative effects of living under crowded conditions. High cubicles, 

which consisted of partitions which reached almost to the Cf';lin .... anu 

contained doors, eliCited positive reactions similar to the single rooms 

even though they contained from one to three men. However, the low 

cubicles which had no doors and which were less elaborate than those at 

Danbury and El Reno were rated more negatively than the singles and high 

cubicles. The low cubicles were also smaller in space than the singles. 

As was the case in our other prisons, the open dorm was rated most negatively. 

The comparison of the singles and the a .:ove residents is also of 

interest. These residents lived in the same unit and have similar space 

per person. Yet the ratings of the alcove residents are more negative 

than those of the singles, again indicating the importance of social 

density. The comparison of the singles and the low cubicles suggests 

that space may also be an important factor. However, this effect could 

also be due to the lack of privacy afforded by these cubicles. 

Because the Fort Worth data was the last to be prepared for analYSis, 

our analysis is still somewhat incomplete. The contributions of potential 

confounding factors such as time in prison have yet to be dealt With, although these factors have not negated the perceived crowding and housing 

rating results in any of our other studies. However, the crowding t0lerance and talking effects should be considered tentative. 

Program type was partially confounded with housing type at Fort Worth. 

However, inspection of our pattern of findings does not indicate it to be 

101 

.\ 
102 

a major contributor to our results. At Danbury we found that program 

type also had little influence on our findings. 

." 

" 

• 

103 

ARCHIVAL DATA 

Introduction 

Archival data were obtained from two prison systems, the Texas Department of Corrections (TDC) and the Oklahoma Department of Corrections (ODC). 

The great majority of archival data was from the TDC and was related to 

deaths, suicides, psychiatric commitments, self mutilations and attempted 

suicides and disciplinary infractions. 

Changes in Population Without Parallel 

Increases in Housing Facilities 

A number of state correctional systems have experienced increases and 

decreases in population with only minor. changes in housing space over the 

same period of ti~e. We obtained data from official state sources on deaths, 

suicides, psychiatric commitments, and disciplinary infractions which allowed 

us to evaluate some of the behavioral and physiological consequences of 

changes in population. 

In the Texas Department of Corrections the population from 1968 to 1978 

increased from 12,500 to 23,900 when housing facilities increased approximate1y 30%. During this period there was a disproportionate increase in the 

number of suicides, disc.:{,plin~);'Y.:int~actions, and deaths of irunates over 50 • • ,.~ , ' • . __ ,.:" 'J...- ••• ,;"t .,' .• ~ _~ ... 

Data from the Oklahoma Department of Corrections covered 1973-1976. During 

those years the population decreased, then increased. 

Suicides. Information was obtained on all deaths in the TDC for 

January 1968 through August 1978. This information included an inmate's 

name, date of birth, cause of death, date of death and unit of assigrunent, 

and in most cases racial identification. Some of these data came from TDC 

records; other data were obtained from individual death certificates. An 

-
-------------------------------------------------------------------------------------------,.------------------------------------~~--

104 

additional source of data was a masters thesis on suicide in the TOC 

[, 

authored by David L. Smith (Sam Houston State University, October 1977). 

Smith's thesis covered the period 1964 through 1976, while the TOC records 

covered 1968 through November 1978. The two sources of data were in very 

close agreement as to the number of suicides in any given year. Consequently they were combined to provide an unbroken l4-year period. In 

Figure 29 suicide rates and mean populations are plotted in three year 

creased over 1000%. A comparison of the first and last seven years yielded 

blocks. Over this period population increased 91% while suicide rates in-

~. 

[; 

a very substantial difference (p < .001). These data indicate that an increase in housing was accompanied by a dramatic increase in suicide rates. 

This is the case in spite of the fact that no suicides were reported in 

1976. (see Page 108 for a comment). 

Deaths Due to Violence. Data on deaths for the four years 1973-1976 

were obtained from the Oklahoma Department of Corrections. The report did 

not include any deaths from natural causes, which reflects Oklahoma's 

policy of releasing or removing to a civilian hospital inmates who appear 

to be terminally ill. Causes listed were suicide, homicide and other. The 

category "Other" included two deaths during escape and three from accidental poisoning. Figure 30 shoWR the population and death rate trends, ineluding the "Other" category. Whether the "Other" category is included or 

excluded does not make any substantial change in the conclusions. In each 

case the two highest population years had higher rates than the low population years, with rates in the high population years 2.5 to 2.8 times higher 

than in the low population years. The difference was significant (p < .05). 

The results complement our earlier findings from the Illinois prison system 

where population first rose and then declined (see Figure 31). 

" 

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TEXAS DEPARTMENT OF CORRECTIONS 

• • Average Population _v 

1\ • -- - - - - .. Suicides I \ 

I \ 

I 

I " \ 20 1 \ 

I \ 

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I \ 

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I \ 

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., 

1 ---- • .,c--- ....... e • Base Line 

~~------------------------~-------.------------------~------------------------~ 1964-66 1967-69 1970-72 1973--75 1976-78 

Figure 29 

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PULATION OKLAHOMA PRISON POPULATION AND DEATH RATE 

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\, L-------------------------__ ~L_ ________________________ ~o 1973 1974 1975 1976 

YEARS 

Figure 30 

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650 

600 

550 

Q 500 

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450 

350 

1953 1955 1957 1959 1961 

YEARS 

Figure 31 

3.0 0 

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1963 1965 1967 1969 

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--------------------------------------------------------------------------------...... ---.------------------------

I 

108 

Data obtained from the TOC regarding violent deaths were compared 

over the period 1968-1977. The violent death rates in the higher population years (1973-l977, .160 per 1,000 inmates) were 40% higher than in 

the low population years (1968-l972, .115 per 1,000 inmates). Although 

this trend was not statistically significant it is clearly parallel to 

the violent death data obtained from the Oklahoma Department of Corrections and suicide and psychiatric commitment data described elsewhere in 

this report. 

Deaths from Natural Causes. In an earlier published report we presented evidence indicating that death rates in the Illinois prison system 

were greater in periods of higher populations and fixed housing capacity. 

The effect appeared to be most pronounced in inmates over 50 years old. 

In Figure 32 we have plotted the expected and actual death rates in TOC 

of imnates ove!' 50 using 1971 as the base year. On this basis the actual 

death rates are higher than the expected death rates at all points. Overall the actual death rates are 220% of the expected rates. The difference 

between the expected and actual rates is statistically significant (p < .001). 

We also examined the data using an average of 1971 and 1972 as the base year. 

The differfmce t'emains significant (p < .01). These findings are particularly striking in light of evidence presented recently in The New England 

Journal of Medicine which indicated that overall u.s. death rates fell 17.7% 

in the period 1968-1977. 

Special note should be taken of the data from 1976. There is a very 

substantial drop in the death rates to approximately 39% of the previous 

year. In addition there were no reported suicides or killings in 1976. We 

have not been able to determine the basis for this rather astounding decrease. 

'- -

, 

-<-, 
.,. z _ 

"" ____ .. um .. ~~~------.. --.-~qa--~----.. ------------------------------.. -------------------------------------------.----------------------------------------------__ ----------------------------~u._---------------------

'. 

'. 

~ 

W 

ACTUAL AND EXPECTED DEATH R"TES IWithout Suk~1esl FOR 

TEXAS MALE INMATES 50 YEARS Of AGE AND OLDER 

____ ACTUAL DeATH RATE 

___ __ EXPECTED DEATH 

RATES AruUSnD FOR 

1.91% YEARLY ~CREASE 

~11om------L--~~~~------------------------------------­ ---------------------- Base Rate 

197:f-M~15=73:----:1=f7:':'4---1:::9=7S::--~157=ti--l~fr7--7~-1I-7-8---­

YEARS 

(16.224) (16.427) (17.115) (18.377) (20.200) (21.382) (23.935) 

SYSTEM POPULATION IN PAf-IENTHESES 

Fj.gure 32 

'. 

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II H 

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,.... ~ \0 

0 ~ ~ f( 

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~~------~t~·~------.. --·,~----------.--------------------------------~----------------------------------------------------------------------~------------------------~.---------------------------------------------... 

110 

Disciplinary Infractions. Disciplinary infraction data from TDC 

covered the periG~ ~969 through 1978. As may be seen in Figure 33 

inmate population in 1978 was approximately 91% higher that! irunate population in 1969 (12,482 to 23,935). During the same period the rate of 

disciplinary infractions nearly quadrupled (83 per 1,000 to 312 per 

1,000). TDC housing facilities are estimated to have increased approximately 30% during the period. The difference was highly significant 

(p < .001). Population increased much more rapidly than housing facilities, and was accompanied by a very sharp rise in the rate of disciplinary 

infractions. These results are similar to those recently reported by 

Nacci, et a1. (1977) for the entire Federal prison system. It seems 

~easonable to attribute at least part of the disproportionate increase 

in disciplinary infractions to crowding induced stress. 

Institutional Size 

Previous findings in nonprison settings have indicated that other 

things being equal sheer size, that is the total population of an institution, is a variable that can produce physiological and psychological 

effects. Large institutions have a greater negative impact on individuals 

than smaller institutions that are in other respects equivalent. We 

sought to determine if this relationship was relevant to prison size. 

Deaths. Four smaller units of the Texas system were compared with 

five larger units in terms of death rates excluding suicide, violence and 

accidents. The period covered is 1971-1978. Earlier years were not included since reliable information on ages was not available. As shown in 

Figur~ 34 the larger unit~ had higher death rates at every age level surveyed {17-25 ratio 1.68 to 1, 26-35 ratio 3.15 to 1, 36-45 ratio 1.77 to 1, 

, 

'> 
500 ... 

400 

300 

200 

co 

... 

co 

CD 

> 

• c. 

--' 

• (I 

to 

m 

o 

le 

o .-..., 

ca 

-.. 

ac 

1969-70 

~----------------------.---- • 

" 

\ 

TEX"S DEPARTMENT OF CORRECTIONS 

0- - - - 0 Disciplinary Infract.lons 

.. 8 Inmate pO~Qjlatlon 

1 

, 

~ '1 

~ 

l 

1977-72 1973-74 1975-76 1977-78 

Figure 33 

ij 

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~ Small Units Av.Pop. -:::-' 800 

Large Units Av.Pop. "':.:'" 1600 

Age Ranges 17-25 26-35 36-45 

Deaths Excluding Suicide, Violence and Accidents, TDe 

Large Vs. Small Units 1971-78 

Figure 34 

" 

.. ,

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1 

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1 

• 
--~--~------------~- • :a:o=== U _ .. 

overall ratio 2.81 to 1). The ages above 45 were not considered since 

the number of inmates in the small units above this age was too small 

for statistical analysis. Compared at the individual age levels none 

113 

of the group differences were statistically significant. However, a 

comparison of large and small units based on the age range 17-45 yielded 

a statistically significant difference in death rates (p < .025). Two 

of the large units (Huntsville and Wynne) have more extensive hospital 

facilities than any of the small units. However, removal of these units 

from the analysis does not change the trend (17-25 ratio 1.58 to 1, 26-35 

ratio 1. 73 to 1, 36-4·5 ratio 1. 09 to 1). While the difference was not 

statistically significant the violent death rate in large units (.207 per 

1,000 inmates) was 59% higher than in small units (.130 per 1,000 inmates). 

Suicides. In the TDC, units with large populations had much higher 

suicide rates than units with small populations. A comparison was made 

between the large and small population units. As can be spr. in Figure 35 

the suicide rate for all age groups was much higher in the large as compared to the small population units with the suicide rates in the large 

units about ten times as high as in the small units (p < .05). These 

results are compatible with other published data. 

Psychiatric Commitments. Two reports from the Texas Department of 

Corrections provided information regarding the units of origin for psychiatric commitments (Special Study No. 12 dated March 1975 and Technical 

Note No. 28 dated April 1975). The Technical Note covered the period 

September 1, 1974 through February 28, 1975. During this period the 

commitment rate for large units (1,450 or more inmates) was .984 per 100 

inmates. The rate for small units (1,100 or less inmates) was .575 per 

100 inmates. The rate in large units was 1.71 times as high as in the 
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OVERALL RATE 17-45 

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Eastham 

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IIU. Ellis 

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36·45 

-Clemmens 

Centra! 

Darrington 

Retrieve 

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115 

small units (p < .05). 

Special Study are very similar to those from the Technical Note (see 

The Special Study No. 12 covered all of 1974. The results from the 

Figure 36). The large units had a yearly commitment rate of 2.10 per 100 

inmates (1.05/100 on 6-months basis). The small units had a rate of 1.18 

1.78 times as high as in the small units (p < .001). 

per 100 (.58/100 on 6-months basis). The rate in the large units was 

On the basis of these reports it appears that larger units produce 

with other published work. 

higher rates of psychiatric commitments and this is in general agreement 

lations and sUicide attempts varied in quality among institutions. The 

Self Mutilation and Attempted Suicides. Data from TIDC on self mutidata from six institutions were of sufficient completeness to allow for a 

comparison of three small units (Central, Clemmens, and Darrington, average population 924) with three larger units (Ellis, Eastham and Coffield, 

able in a number of ways. Their records reports were also much more 

average POpulation 2,981). These were selected since they seemed comparcomplete than others. In terms of self mutilations and attempted suicides 

2.35 to 1). The differences were statistically significant (p < .05). 

the rate in the large units was much higher than in the small units (ratio 

Taken alone the self mutilation and attempted suicide data shOUld be 

viewed with considerable reservation. However, they are parallel to and 

psychiatric commitments. 

provide corroborative support for our data on death rates, suicides, and 
J 

r' .. I 

1.90 

1.80 

L70 

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-~-'~------'-------------------------------------- ..... __ --------------------------~.r------------------------------------------­

TEXAS PSYCHlAmlC COUIoUTIoEHTS 

1.11 

UNITS OF 11CN) 

INMATES 00 SMALLER 

Figure 36 

UNITS OF MOO 

INMATES OR LARGER 

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,= 

- m • 

Summary of Archival Findings 

There are two major findings, each supported by several lines of 

eVidence. First, our archival data indicate that increases in inmate 

population without concomitant increases in housing facilities produce 

a number of very undesirable effects as indicated by disproportionate 

increases in disciplinary infraction rates, suicide rates, rates of 

death by violence, and death rates of inmates over 50. Second, other 

things being equal, large prisons appear to produce more undesirable 

effects than units with small populat1.ons as indicated by higher psychiatric commitment rates, death rates, and suicide rates. In other 

words, in addition to space per person and number of occupants in housing quarters, sheer size of the institution is :lmportant with larger 

size related to more deleterious effects. 

Since our data regarding large and small prisons come from TDC, 

we examined floor planl3 and numbers of irunates in individual cell blocks 

in the institutions involved. Most hOusing is in two man cells with 

23 square feet per inmate. These appear to be standard for both large 

and small institutions. Space and Socj:al density in the dorms is confounded between large and small institutions and does not seem a consistent factor. The small units have a larger percentage of ~nmates housed 

in dorms, due in part to the fact that one unit (Central) is almost 

exClusively dorms. Our confidence in the probability that size is the 

major factor is bolstered by the fact that FelrguSOn (large) has a higher 

suicide rate than the small units (all ages included) even though the 

overwhelming majority of Ferguson inmates are 22 or younger. And the 

evidence is very clear that younger individuals are the least likely to 

commit suicide in or out of prison. 

• I 

117 
liS 

In sum, we have not found any factors other than total population 

that seem to account for the differences between large and small institutions. 

Acceptance of archival findings should of course be tempered by 

awareness of the potential contribution of unrecognized confounding 

variables. To the extent possible we accounted for the potential contribution of age and race. These and other potential confounding 

variables were examined in a recent dissertat!on study by Timothy Carr 

(1980) which involved an extensive analysis of the Georgia prison system. 

Carr found a strong relationship between population level and aggression 

but failed to find a similar relationship for cardiovascular deaths. In 

the latter case the total number of deaths was quite small. The Carr 

study was stimulated by this project and Professor Paulus served on the 

dissertation committee. 

Inter-institutional Analyses 

One measure of the generality of findings and conclusions is how 

consistent results are for similar housing conditions in different institutions. In this project there were several housing conditions 

common to two or more institutions. For example, double occupant cells 

and open dormitories were found at La Tuna FC! and Texarkana FCI. Summarized below are findings for several comparisons of housing common to 

two or more institutions. 

Single versus Double 

Occupant Cells 

119 

At El Reno and Texarkana FCI illness complaint rates in double cells 

were substantially higher (over 50%) and from a statistical standpoint 

significantly greater than in single cells (p < .015). The results from 

perceived crowding were parallel to the illness data. The difference was 

highly significant (p < .001). There was no interaction between housing 

condition and institution indicating that the housing effects were uniform 

across institutions. 

Double Cells versus Dormitories 

At Texarkana FCI and La Tuna FCI there was a large (73%) and statistically significant (p < .01) difference in illness complaint rates between 

double occupant housing and open dormitories. Again, there was no substantial interaction between housing conditions and institutions. The differences in perceived crowding were in the same direction as the illness data 

bu t very small. 

Single Cells versus Dormitories 

For Texarkana FeI an.d Danbury differences in illness complaint rates 
,,.--.--------.-. -~ - --

 -- --~- ---

._ --------------------

I 

120 

between singles and dormitories were large (105% h~gher in dorms) and 

statistically signj.ricsllt (p < .001). The results from perceived 

crowding were parallel to the illness results. The difference was highly significant (p < .001). As in the earlier comparisons there was no 

interaction of housing condition and institution. 

Relative Influence of 

Social and Spatial Density 

We were interested in determining the relative contribution of 

social and spatial density to crowding effects. To evaluate this issue 

we calculated for each housing condition in our study a score for spatial 

density, social density, institutional size, perceived crowding, ratillg 

of housing quarters, and illness rates for the period after the first six 

weeks 1.n a housing condition. The correlations am~ng these variables 

w~r€) cbtait!ea and then partial corl~elation techniques were employed to deten»ine the relative strength of association of each variable to spatial 

and social density. Pearson correlation values were obtained as well as 

values for two nonparametric correlation procedures, Spearman and Kendall. 

All three correlation procedures yielded essentially the same values. 

Perceived crowding was significantly related to both spatial density 

(Pearson, r .. -.59, .E. < .04) and social density (Pears~)n, r ::II .45, .E < .01). 

Neither correlation value was appreciably changed when the other density 

variable was controlled by partial correlation. Consequently it appears 

that both social and spatial density have a moderately strong and independent relationship with perceived crowding. The relationship of spatial 

density to perceived crOl~ding was slightly stronger than that of social 

density to perceived crowding. Figure 37 is a scatter plot of individual 

housing units and regreSSion line for the relationship between perceived 

it t _ 

121 

crowding and spatial density. Considering the fa~t that this includes 

different security levels, institutions, social densities and times, the 

relationship is remarkable. 

Ratings of housil1g quarters bore a strong relationship to spatial 

density (Pearson, r = .57, _~ < .006) and moderate relationship to social 

density (Pearson, r = .39, ~ < .05). The correlation between ratings of 

housing quarters and social density was enhanced when the influence of 

spatial density was controlled by partial correlation procedures (Pearson, 

r ~ .47, ~ < .02). The correlation between housing quarters ratings and 

spatial density was not appreciably changed ln1en partial correlation procedures were used to control the influence of social density. In contrast 

to perceived crowding and ratings of housing quarters, illness complaint 

rates were moderately related to social densi~J (Pearson, r = .38, 

p < .05) but not spatial density (Pearson, r = -.19, p < .33). Figure 38 

illustrated the relationohip of illness complaint rates to social density 

when units 01: the same social density are combined for all institutions. 

These data yielded a Spearman correlation coefficient of .98 (p < .001). 

Again, this is a remarkable and very sturdy relationship. A similar 

analysis of perceived crowding yielded a Spearman rank order coeffieient 

of .60 (p < .05). 

Inter',-institutional Summary 

Combining data from two or more institutions indicated that single 

cells had fewer negative effects than double cells. Double cells had 

fewer negative effects than dormitories. 

Perceived crowding increased as social or spatial density increased. 

The relationship was stronger with spatial density. Ratings of bous~ng 

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SOCiAL DENSITY 

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124 

varied with both social and. spatial deJ\sity. The ~elationghip was 

stronger with spat:J.al density. Illness canplaint rates increased as 

social or spatial density increased. 'fhe i-!ell;ltionship with social 

density was the strong~I' of the two. 

a 

125 

Summary of Findings Related to Crowding 

Siagles versu~ Doubles 

Doub1e occupant housing is a common response to incT.eases in prison 

popUlation. We were able to compare these two types of housing at two 

institutions, El Reno and Texarkana FCI. We found that double cells or 

cubicles had measurably greater negative effects than single unit housing. 

Differences were o,bserved in illness complaint rates, perceived crowding 

scores, nonviolent disciplinary infractions, mood states, rating~ of 

environntent and perception of choice and control. We noted ,that a small 

number of individuals preferred double occupant housing and this was 

primarily found among inmates living in the mo~e crowded housing at 

La Tuzea FCI." All of the double cells we have examined also had doubledecked bunks and greater spatial density than the singles. These factors 

could possibly contribute, to the differences between singles and doubles. 

Single ver.sus Small 

.Multiple Occupant Units 

At Atlanta it was possible to compare single cells to small multiple 

occupant cells housing three to six men. Perceived crowding and. illness 

complaints, as well as other measures, increased as the number of imnates 

increased from one to six. The difference between single and three-man 

cells could be attr~buted primarily to social density since three-man 

cells had more space per person than the single cell~. 

Single'Units versus 

Open Dormitories' 

If there is anyone set of findings from this project or earlier work {! '---;::0 - -,,-,-

that seems beyond serious question, it is that dormitories have more negative consequences than one-man units. While this may seem intuitively 
r--

J 

, . 

126 

obvious, we have been able to document a number of ways this difference 

is expressed, as well as the magnitude of the difference. Our evidence 

consists of illness complaint rates (both ~ontagious and noncontagious), 

housing ratings, perceived crowding scores, mood states, and perception 

of choice and control. The findings were consistent across race and 

ethnic groups, security level, program assignments, and l~ngth of time 

in institution. 

Doubles versus Dormitories 

A comparison of double cells and open- dormitories was Possible at 

both Texarkana and La Tuna j~CI. The dorms were higher in illness rates 

and perceived crowding, though the effects were not large at La Tuna. 

Measures of mood, perceptionl; of control and choice, and environmental 

ratings generally supported the contention that dormitories produce more 

negative impact on residents than double cells or rooms. 

Open versus Segmented Dormitories 

Texarkana FCI provided an opportunity to examine inmates living in 

ope~ dorm:f;tories with inmates housed in segmented dormitor1.es. The segmented dormitories consisted of three bays containing ten to twenty residents. These segmented dOrmitories were associated with lower illness 

rates, perceived crowding scores, more positive mood, and favorable 

ratings of housing units. 

Cubicles versus Rooms 

This comparison was possible at El Reno, Danbury, and Fort Worth. At 

EI Reno and Danbury the effects of cubicles were ~omparable to rooms on all 

measures except illness complaint rates which Were higher in cubicles at 

,-

I 

,'pa • 

127 

Danb,lry. At Fort Worth the cubicles were rated more negatively and were 

associated with higher illness complaint rates than rooms. The cubicles 

at Fort Worth are less elaborate than at El Reno and Danbury. They are 

lower and consist only of partitions. The cubicles at Danbury and 

EI Reno include storage and desk space and are visually more al~tractive. 

At these two institutions the cubicles almost completely attenuat~ the ' .. 

effects of ope~ dormitory living. 

Cubicles versus Open Dormitories 

Since cubicles, in fact, represent an inexpensive mef.lUS of affordi:ng 

privacy in (H;nerwise open dormitories, we compared the effects of living 

in cubicles and open dormitories at La Tuna, Danbu::;y:!' and Fort Worth. In 

". ~--' 

general~ open dorms produced stronger negative effects than ~pe dorms with 

cubicles. Open dorms were higher on percei~ed crowding scores, yieldad 

-<'~.' -, 

more negative mood states and lower rati:ngs of housing quarters. With the--< 

exception of Danbury, cubicles yielded lower illness rates than open dorms. 

Illness Complaints 

and Perceived Crowding 

At all institutions, except Danbury, we found that itm1ates who rated 

themselves "very crowded" had higher illness rates than those rati'ng themselves as less crowded. These comparisons were made within individual 

housing units (see Figure 39). 

Changes in Population Without 

Parallel Changes in Facilities 

Over a .ten year period total popl!lation in the Texas Department of 

Corrections increased sharply while facilities increased only slightly. 

Death rates, suicide rates and disciplinary rates rose even more sharply 

/ 

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129 

than population. In the Oklahoma system when ~opulation dropped there 

was an even greater drop in rates of deaths due to violence. These 

results confirm e21rlier fin.dings f?om llB.nois. Thus, when facilit.ies 

are relat,ively fiJced, increases in populatiort lead to disproportionately 

higher negative effects. Population reduction had opposite results as 

seen in the Oklahoma data. 

Institution Size - , .. ;. 

" •• _+ 

There is evidence that :.f.nstitution$,with :r.sl:ger populations ptC>ddce 

more negative effects tMm units wi,th smaller papulations. Differences 

were found in death rates (violent and' nonviolent), fJuicides, psych'iatric 

connnitments and self mutilation and attempted suicid.es. The comparisons 

were between institutions 'With approximately 1,500 /and those with about 

1,000 inmates. 

Racial and Ethnic 

Groqp Differences / 

An examination of data for black and white inmates indicated that on 

most measures whites reacted more negatively to crowding than blacks as 

revealed in higher perceived crowd,ing scores, mere negative mood states, 

housing related complaints, feelings of choice and contrQl, and ratings 

of housing qU<;ll;ters. With regard to housing related illness complaint . / .. ~~ ,~ 

rates, blacks in all but one institution were higher than whites. 

At La Tuna FeI it was possible to compare Anglo Americans, Mexican 

Americans, and Mexican Nationals. The Anglo Ameri.cans had the most neg ative responses to crowding on almost all measures, ineludirig illness complaint rates, follow~d in Qrder by Mexican Americans and Mexican Nationals • 

A similar result for illness complaint rates was found at Texarkana in a 

1 
r-~~-----'---~--~ 

A 

130 

comparison of Anglo Americans and a combined sample of Mexican Americans 

and Nationals. 

Individual Differences 

in Responses to Cro~ing 

Racial and etbnic differences in responses t 

o crowding are discussed 

elsewhere. Individuals Who petceive themselves to be more crowded in a 

particular bousing unit produce more negative responses. such a~ illness 

complaints, than those wbo perceive tbemselves as less crowded. Individuals whp say they are bothered more by too many people rather than too 

little space also have bigber illness rates. 

Time Related Factors 

Length of time in a particular housing unit was! important in determining illness complaint rates. There i$ an initial high level for about six 

weeks follOwing bousing aSSignment, followed by d 

a rop. then ~he ~ates 

level off. This is independent of any particular type of housing. Our 

duta also indicate that perceived crowding does not decline as a 'function 

of ti.1lle in housing. This W f .oJ b - as oun~ to e the case at all of the institutions atudied, although we have not reported .it for each institution separately. 

" 

-

Conclusions anp Recommendations 

The most straightforward conclusion that can be drawn from our 

reported research_is that both the amount of space and the number of 

residents must be considered in assessing the suitability of prison 

housing. Most prison standards emphasize tbe amoun.t of space rather 

than the number of inmates in one's unit. Yet we bave found tha:;: negative reactions increaae botb as space is reduced and as the number of 

inmates in the housing unit increase. Further, increases in the number 

of inmates in the housing unit is more influential than reduced space 

in determining illness complaint behaviclr. 

More specifically, we have found tbat singles are mnst desirable 

and open dorms least desirable as housing quarters. However, even 

dormitories can produce relatively favorable reactions under certain 

conditions.. Single bunking, spaciousness, and segmenting the dormitories into small bays were all associated with reductions in the negative reactions typically associated with open dormitories. Dividing 

open dorms into small cubicles is particularly effective in reducing 

the negative effects of open dorms. In the case of two prisons in 

which fairly elaborate cubicles were used, almost all of the effects, 

with the exception of illness complaints, associated with dormitory 

crowding disappear6~~ 

Another new trend :tn prison housing is the use of prison camps 

outside of the main prison~ .These camps are a very low security level. 

At La Tuna, such a camp was rate~ very favorably even though inmates 

were housed four men to a cubicle. 

When comparisons were possible, we found that males, females, 

131 

blacks, whites, Mexican American~ and Mexican Nationals all show similar 
132 

patterns of reaction to different housing units.' However, we did find 

overall differences in reaction to prison housing as a function of ethnic 

group, With Anglo Americans being most negative and Mexican Nationals 

least negative. 

Although we did not find a systematic relationship between institutional size and inmate reactions for the institutions we tested, archival 

data did suggest that this is an important factor. The data indicates 

that substantial variation in total institutional Population can have 

dramatic effects on health related behavior'. The larger an institution 

is in terms of tota.l :population the 'higher the death, SUiCide, and psychiatric commitment. Increases in population without parallel increases 

in facilities had the same type of effects. Also, at Texarkana we found 

inmate reaetions were considerably more positive when the institutional 

population declined frlOlU 710 to 510. 

If we had to SUggf!st a design for an ideal prison solely from the 

perspective of reducing crowding effects, and independ~nt of other prison 

management considerations, it would be relatively small (certainly less 

than 1,000 and preferably 500) and consist of single rooms or cubicles. 

The amount of space required for these inmates is harder to pinpoint. 

We found that increasing square footage from 50 to 60 square feet improved 

inmatereactiona at Danbury, but a similar variation from 54 to 66 square 

feet'had no appreciable effect at Texarkana. In fact, even the 50 square 

foot' singles received quite favorable reactions at Danbury. While making 

single cells more spacious than 50 square feet seems desilt:'able and may 

improve'inmate,reactions, we have found no evidence to inelicate that a 

50 square foot cell is Psychologically inadequate. Since we have found 

,no single cells smaller than that, we do not know whether 50 square feet 

represents, the minimally adequate size for a sing 1 e room. Certainly, 

simpl,y frcm the standpoint of bein~ e able to move ~round in one's cell, 

smaller units do not seem feasible. Whether extremely large slngl~ 

cells can produce additional benefits remains to be seen. ,It should be 

noted that the large single rooms at Fort Worth were rated ab~ut the . 

same as the smaller singles at Danbury and Atlanta on perce ived crowding. However, they <. were rated more favorably on the room evaluation 

scales. 

The data on the effects of space in dormitories,is also not very 

clear. Although the mure spacious dormitories at Danbury were rate4 

133 

more favorably, a reduction of 12 men in a 40 man dorm , at another institution did not tmprove inmate reac tions • While the two dormitory types 

at Texarkana that received relatively favo~able ratings were more 

spacious than the n~gat i ~e 1 y rated double-bunk dormitories, they also 

had special design features (small bays) and/or single bunks. 

In brief, it appears that once one reaches space per pe rson levels 

of 50 square feet or higher, the numb ex of people one is living with and 

how one's space is arr ~"Oed __ ~ (single bunkir~, cubicling, segmenting into 

bays) may be the main faetors determining r~act i on to one~s housing. 

; -'I 
.. 

----- ----~ 

._

134 

Additional Considerations 

Although small variations in space did not lead to strong effects 

in our studies, it is Possible that space may be a more important factor 

in prisons where inmates are confined for large parts of the day to their 

housi'i1g units. In all samples in this project inmates were confined to 

their housing units only during sleeping hours. In our only study of a 

state prison where inmates are confined for large parts of the day in 

their cells, we did find stronger effects of space than of social density. 

The space levels in these cells varied from 19 t;o 58 square feet while 

social density varied from 1 to 9. 

One factor to consider in evaluating the inmates' rating of their 

housing units is that this may in part be a relative matter. At all of 

our sites there was a variety of housing types and inmates may have eval- . . 

uated their housing relative to the other housing in the prison. That is, 

inmates may find small single cells attractive relative to dormitories, 

but these same cells might be rated much more negatively in an institution that has only single cells. In fact, inmates sometimes mentioned 

spontaneously that they were rating their housing on their impliCit standards for prison housing rather than on an .absolute scale. 

The strongest statistical effects of sp,atial and social density were 

obtained for the perceived crowding and the room rating measures. In 

contrast, the scales design~d to assess mood state showed less consistent 

and weaker results, espeCially when such factors as custo~y level and time 

in prison are taken into consideration. This pattern of result.s suggests 

that while the inmates' evaluations of their environment are strongly determined by spatial and social denSity, their mood states may be more 

dependent on their custody level and length of confinement. When mood 

:' i 

i .. 

i . 

r " 

• 

effects were obtained, they occurred primarily for comparisons between 

singles or doubles a~ -~ open d 0 or es. rmit i This parallels the strong 

effects of social density on illness complaints. 

Our most consistent behavioral measure was illness complaint rate. 

Our illness complaint measure is based on a physician's medical record. 

This feature is important in increasing its validity as a measure of 

stress (Mechanic, 1976). However, we 'have no straightforward way of 

knowing whether the complaints reflect actual increas,a pathology, increased sensitivity to pathology, or mere complaining. Whatever its 

basis, there is much evidence suggesting that illness complaint behavior 

is increased under stressful conditions (Mechanic, 1976) while other 

that stress can increase one's susceptibility to research indicates 

disease (Rogers et a 1 ., 1979) • Also some studies have found cr,owding in 

prisons to be associated with physiological indices of stress (D'Atri, 

1975; Cox, et al., 1979; P~ulus et al., 1978). SQ,:,. at the least, we 

suspect that illness 

situation. Further, 

complaint behavior is a response to a stressful 

while our study does not prov:l.de direct evidence 

ofa pathol~D1cal basis . f or these ~ ~omplaints, we suspect, on the basis 

of other research on stress, that the illness complaints may in part 

reflect real pathology. Certainly, direct proof of this will require 

further research. 

Calculation of illness complaint rates was based on length of stay 

in housing. Length of stay did not differ for housing conditions at 

Texarkana and failed to influence illness complaint rates findings when 

employed as a covariate in analyses of data from the La Tuna 1978 visit. 

At. El Reno we matched two groups of inmates for length of stay in either 

singles or doubles and found much higher illness rates associated with 

" 

.j 

" 

, 
, 

-

.. 

f' 

r 

~-~-~~~ --~----.-- 

136 

doubles. A similar matching of single and dormitory residents at 

Danbury yielded illness complaint rates that were twice as high in dormitory residents. There was no systematic relationship between iength of 

stay in housing and social density at Atlanta. Taken togehter, these 

findings indicate that our illness complaint rate results were not si,gnificantly determined by length of stay in housing. 

The strong and consistent effects of density on illness complaint 

behavior contrast sharply with the general lack of effects on other behavioral measures. We found no effects of density on reported religious, 

club, and educational activities, and only one effect on talking. In 

most institutions reported incidences of infractions were too low to 

allow meaningful analysis. 

The failure to find consistent density related effects on blood 

pressure indicate that this may not be a useful meaSure of exposure to 

moderate stressors such as crowding in federal prisons. Long periods of 

exposure to intense stressors or very strong situational stressors may 

be required to elevate blood pressure. Our choice of blood pressure as 

a measu,,=e of stress was motivated both by its convenience and past research indicating that it was sensitive to variations in density (D'Atri, 

1975; D'Atri and Ostfeld, 1975; Paulus et al., 1978). All of these 

studies were done in state prisons. It is possible that the greater 

degree of confinement to housing units, higher density levels~ and the 

greater fear of violence in these prisons may have elevated stress levels 

high enough to influence blood pressures • 

Another interesting feature of our data is that for all of the prisons 

studied perceived crowding did not decline with length of stay in a housing 

unit. This supports findings of research cited earlier that individuals do 

not seem to adapt to crowding over time. 

;-

• 

~~-~~=--=---------------------------- ..... ,~---~---,--... ------... -'"-'"-' .... ---.,.,~.'----- , ... _--

137 

Some Possible Interpretations 

There exist many different perspectives about the important factors 

underlying crowding effects (c.f., Paulus, 1980). One popular approach 

is that cr~wding has negative effects on people because it induces a 

feeling of loss of control over, one's life, or helplessness. This state 

of helplessness is supposedly associated in.th depression and deterioration in health (e.f., Baron & R· 0 di n, 1978) • Another interpretation holds 

that crowding serves to overstimulate the individual. This overstimulation is a source of stress and leads to behavioral and psychological 

withdrawal (Seegert, 1978). A third approach argues that crowding has 

negative effects because of the "fear-reaction" produced by too many 

strange others in confined areas (Paulus, 1980). In other words, crowdiug increases the chance of having negative encounters with others. A 

fourth view proposes that environments are aversive to the extent that 

they intexiere with an individual's attempts to attain a desired privacy 

level (Albn&n, 1977). Pt':I,vacy can be attained by physical mechanisms 

such as spatial and visual separat19.I),~o~ behavioral-mechanisms such as 

territoriality or modification of social contact. 

Some of our findings of the negative effects of reduced space, increased social density, an d increased population density are of course 

consistent with all four of these models. All of these analyses predict 

negative effects of these variables. They only differ in the presumed 

det~"":!Ilining factors. 

The failure of the results of our control and choice qaestions to 

be ~ignificantly related'to density variables certainly goes counter to 

the predictions of a "perceived control" theory. The failure to find 

reduced reports of social and educational activity among the more crowded 

\, 
rf 

--.-~ --- • ~--~----~~~--~- c 

138 

reSidents goes Counter to expectations based on an overstimulation 

model. 

Some of our data suggests that privacy or territoriality may be 

important factors. The finding that partitions in open dormitories 

significantly, and sometimes completely, reduce the reactions associated 

with such dormitories is consistent with such a view. These partitions 

provide each inmate with a territory to call his or her own. The findings for the various Texarkana dormitories are also supportive of this 

perspective. 

A reduction of ten i~tes in the 40 man double-bunked dorm did not 

lead to a change in housing evaluation. However, the 20 man singlebunked dorm and the 50 man special dorms were rated more Positively than 

those 30 and 40 man dorms. The special dorms had three sep~rate bays and 

large numbers of Single bunks. It is imPossible to be certain whether 

the relatively positive reactions of these two dormitory types were due 

to spaciousness, low social density (20 in single-bunk dorm and 20 or 

less in the bays). Yet the failure to find positive reactions to reduced 

densit¥ i~ the re~llar dorms suggests the possibility that having single 

bunks may be an important factor. A Single bunk may provide a feeling of 

individual territory not Possible with a double bunk. The finding at 

Danbury that double-decked bunks have higher illness rates than singledecked bunks is compatible with a privacy or territorial interpretation. 

Thus, it appears that the degree to.which inmates have their own space or 

territory may be an important factor underlying our major reSUlts. Social 

and spatial density variations may have their effects largely through 

their- impact on the degree to which inmates have privacy or territory. 

-,' . .( 

This analysis of ou~ findings seems mos t consistent with Altman's 

(1977) in that having one's own space may increase feelings of privacy 

139 

and territoriality and thus have positive psychological and phy~iological 

effects. However, our analysis is not necessarily inconsistent with the 

Havinn other views. e. . one's own space can indirectly serve to reduce 

social stimulation, r. ' e~!!!:e neg a tive social encounters, and increase one's 

sense of control over interactions with others. A more detailed analysis 

of our data and 'future research may allow us t .0 determine mOl'e precisely 

the relative adequacy of these differing views of crowding. 

, 

" 

, ! 

.~ 

"1 

--, 

I 

;_0' 
----------------~~~------------------------.~-----.------------------

.. 

140 

Recommendations for Future Research 

The results of the current project point to a rt~mber of areas that 

merit additional researcb. These areas are listed below. 

1. Of particular interest is the sensitivity of illness complaint 

rate to variations in housing conditions. This variable may prove even 

more informative if analyzed in terms of specific illness categories. 

Specifically, ~tt would be of interest.- to examine no!,contagiou.s illness 

categories that can be readily diagnosed by a physician. 

2. The utility of blood pressure as an index Qf r.5yehol~gical 

stress has not met our expectations, which were based on earlier findings 

reported by o~rselves for the Statesville Prison in Illinois and Dr. David 

D'Atri's findings based on three prisons in Massachusetts. The intensity 

of crowding in the Federal prisons never approached those that we observed 

at Statesville and this may account for/~ur findings in the Federal prisons. 

Far more promiSing 1s the use of urine chemistry measures of stress related 

adrenal gland activity. This approach is more complex than blood pressure 

measurement but has been shown to be related to psychological 3tress in 

many Situations, including incarceration. We would encourage consideration 

of a research project which uses this approach t~ "~asurement of stress related to housing as well as other prison stress. The results on this 

measure would then be related to illness complaint rate. 

3. More data is needed on the long-term effects of crowding. Most of 

our find~ngs are based on data obtained from inmates with exposure to crowding of three years or less. 

4. Individual differences in responses to crowding need much more 

study. There are ,~.'variety of factors which seem to tnfluencei"es~!onses 

to crowding. Some of the variables identified·in our project were :ethnic 

[ __________ ~7~'.~ __________________ _ 

. ';j 

! 

" 

~ , 

,----.......... ~~"'='~~~x~.::::m::t;:;~~~.~=:l:':'.zct~~;:_~ 

141 

group, number of individuals in the home dur~ng childhood, and size of. 

city of residence;prior to incarceration. Of particular interest ate 

housing pref~l'~nces. For example, a minority of inmates prefer double 

cells to single cells. Understanding the determinants of such individual 

differetlces would be helpful in devising housing assignment policies. 

.~~-: 

·5. Cubicles appea:r::~-to be very effective in diminishing crowding 

effect~C-typ:lcally associated with open dormitories. More research is 

needed to determineth~-r~nge of positive effects' that might be obtained 

by partitioning open dorms with cu.bicles and the effects of. different 

types of cubicles. 

6. Additional research needs to be done regarding time related 

crowding effects. We have observed that a "ilariety of responses to crowding during the initial six weeks of stay are different than later periods. 

A systematic study may reveal other time related effects. 

7. The double cel1~t.$ilil cubicles we have examined were the same size 

as single cell,~±n the same institution. In addition, they were· doublebunked. ,11()ub I e-bunking and spatial density could well account for some of 

the negative effects found. Comparisons of double cells with single bunks 

and the same spatial density as single cells should resolve some problems 

of negative effects and individual preferences. Locating such conditions 

may be difficult. 

8. A more detailed analYSis of the effects of housing type at Fort 

Worth would be desirable since this institution has a broad range of nousing units and has both males and females • 

., 

, 

-:~~ 

I 
~~---'''''-' -----,--,-'""',~., 

--~--~~------------------'----~;~ 

' 

L ~. 

.. "-, 

. ,-*~ - ... -~-. --~'A-----""~~"":'--~/.=7~~~~~~·"'-""'·~-t 

142 

-Cross Institu~iona1 Illness Effects 

Um:elated to Cro~ding 

Illness Complaint Rat~s 

and Institutions 

As indicated in two of the cross institution comparisonsl!'c illness 

complaint rates vary ~ong institutions. For example, the rates for 

singles were: El :Q.en.o .036, Atlanta .099, Danbury .108, Texarkana .147. 

N6te that th'e'~rate=~at~ ~arkana is over four times as high 8S El Reno. 

These diff~rences are not solely due to different proportionfj of nousirai '" "> c, 

types. For example, we compared singles and doubles at Texarkana and 

,·-,>£1 Reno. Texarkana t s illness complaint rate was over twice 8S high as 

El Reno. The difference was highly significant (p < .001). In a similar 

compari$on based on singles and, dorms at Danbury and Texarkana. the rate 

at Danbury was about half that at Texarkana. The difference was significant (p < .01). The causes for these differences are not clear. They do 

not appear related directly to crowding. Inmates in these institutions 

dodi~fer in several ways such as age, custody level and racial or ethnic 

,identif~c~tion. 

planation of the ord~~.ing; 

_ ,'!',:f.me Course of IJ.lness Complaints 

Illness rates over time have been analyzed in several different ways 

and frc4l1l several institutions. Figure 40 represents only som~ of these 

analyses. The absolute rates of the .",arious curves should be disregarded 

since they were calculated in different ways. It is apparent that rates 

are very high initially but drop rather rapidly. The curt'es appear. to begin to flatten somewhere around twelve weeks. We have examined data from 

-.::.::.:::. ~.~,. 

t, 

/' 

..... ;4 ...... ;::?--

_."=-. --:;-::-

" 

--I I 

I ,' ___ I 
~-----'-"-- ----- ~~---.. 

~ .5 

ell 

~ .. 

:. .4 

-&AI 

IeI: 

<:. = .3 ~ 

eI: 

-' 

:E "'" .2 

0 

u 

en 

en 

w 

z . 1 

...a 

.... 

'1- I 

e. 

• 

1-3 

• •• Q. 

• •• • ., -0. •• -. 

4-6 

o •• EL RENO fe. SINGLES 

-- TEXARKANA Fe I DORMS 

(197S) 

- •• 0 _____ ... 

•• 

•••••••••••• 

7-12 

WEEKS IN HOUSING 

Greater than 

12 

Figure 40 

, 

-

I 

I I 
[ 

~------.-, 

r-'-

, 1 

_._

144 

the period greater than six weeks. It is not completely clear whether 

these curves are flat or show a slight decline after this period. Much 

more data will be required to resolve this point. 

Illness rates were also sUmmed a~~~~s all in~titutions and all housing by periods 'of less than and greater than six weeks since this type of 

breakdown is used in several parts of this r.eport. The trend from the 

initial six weeks period (X = .253) to the period greater than six weeks 

(X • .165) is clear. Illness rates at less than six weeks are 53% higher 

Further, in all eight institutions the trend was essentially the 

same. Of 32 housing conditions measured, 30 (94%) showed the same trend. 

Considering the fact that a large variety of housing conditions, administrations, levels of security, racial groups, etc. are involved this is a 

very sturdy finding. 

Racial and Ethnic Differences 

At La Tuna there was clear evidence that Anglo Americans had higher 

illness rates than Mexican Americans who in turn had higher rates than 

Mexican Nationals. Those samples did not have enough blacks to compare 

with the other groups. While we had found blacks to be higher in illness 

complaint rates at all institutions except Danbury, the results were 

typically not statistically significant. This seemed to be due to the 

small sample sizes and uneven distribution across housing conditions. 

In order to overcome some of these problems and to get an overall 

persp·:;ctive we looked at black-white illness complaints across all institutions except La Tuna. La Tuna was omitted since there we~e no blacks 

in the 1979 sample and only a small number in the 1978 sample. In the 

19~8 sample the blacks had substantially higher illness rates than any Qf 

the other groups. 

In compiling data across institutions we equated the rae,ial representation for each housing co~dition at each institution. For example, 

145 

10 blac'ks and 2:0 whites in doubles cells at Texarkana, all if there were 

10 blacks were included and only 10 randomly selected whites. The 

results are very clear, blacks have about 1.0% higher illness complaill t 

f the first six weeks (V < .05) and the period rates in both the period 0 

after six week~ 35) Taken together with the La Tuna results, (p <.0 • 

this indicates a consistent pa~tern. Illness complaint rates in descendMexican American and Mexican Natioual. The ing order are black, white, 

patterns are very similar, illness complaint rates decrease in each group 

after the first six weeks ailld each group responds to increased crowding 

by increasing the rate. 

The most reasonable explanation of these findings s~ems to lie in 

We have considered such factors the cultural background of these groups. 

as size of family and prior medical care, but they do not explain the 

data. 
~----'-r-~ 

~ I 

146 

References 

Aiello, J.R., & Erstein, Y.M. Effects of residential social density on 

human behavior: A longitudinal field experiment. Unpublished 

manuscript, Rutgers University, 1979. 

Altman, I. The environment and social behavior. Monterey: Brooks-Cole, 1975. 

Baron, R.M., Mandel, D.R., Adams, C.A., & Griffen, L.M. Effects of social 

density in university residential environments. Journal of 

P~rsonality and Social Psychology, 1976, 34, 434-446. 

Baron, R.M., & Rodin, J. Personal control and crowding stress: Processes 

mediating the impact of spatial and social density. In A. Baum, 

J. Silngar, & S. Valins (Eds.), Advances in environmental psychology 

(Vol. 1). Hillsdale, N.J.: Lawrence Erlbaum Associ,ates, 1978. 

Baum, A., .& Valins, S. Architecture and social behavior: Psychological 

studil:!s in social density. Hillsdale, N.J.: Lawrence Erlbaum 

Associates, 1977. 

Baxter, J.C. Interpersonal spacing in natural settings. Sociometry, 1970~ 33, 444-456. 

Carr, T.S. The effects of crowding on recidivism, cardiovascular deaths F and infraction rates in a large prison syStem. Unpublis~ed doctoral 

dissertation, Georgia State University, 1980. 

Cohen, S., Glass, D.C., & Phillips, S. Environment and health. In H.G. 

Freeman, S. Levine, and L.G. Reeder (Eds.), Handbook of medical 

sociology. Englewood Cliffs, N.J.: Prentice-Hall, 1977. 

Cox, V. C., Paulus, :P. B., McCaj.n, G., & Schkade, J. K. Field research on 

the effects of crowding in prisons and on offshore drilling platforms. 

In J.R. Aiello & A. Baum (Eds.), Residential c~owding and design. New York: Plenunl, 1979. 

D'Atri, D.A. Psychophysiological response to crowding. Environment and 

Behavior, 1975, 2, 237-252. 

D'Atri, D.A., & Ostfeld, A.M. Crowding: 

blood pressure in a prison ~etting. 

.!, 550-566. 

Its effects on the elevation of 

Preventative Medicine, 1975, 

Freedman, J.L. Crowding and behavior. San FranCisco, CA: Freeman, 1975. 

Freedman, J.L. Reconciling apparent differences between the responses of 

humans and other animals to crowding. Psychological Review, 1979, 86, 80-85. 

'. 

I 

.~ 

f 

f•· 

., 

~' 

:' 

J 

j 

, 

• 

147 

Levy, L., & Herzog, A.N. Effects of population density and crowding on 

health and social adaptation in the Netherlands. 'Journal of Health 

and Social Behavior, 1974, 15, 228-240. 

McCain, G., Cox, V.C., & Paulus, P.B. The relationship between illness 

complaints and degree of crowding in a prison environment. 

Environment and BehaVior, 1976, !, 283-290. 

Mechanic, D. Stress, illness, an~ illness behavior. Journal of Human 

Stress, 1976, 1, 2-6. 

Megargee, E.~. The association of population density, reduced space, and 

uncomfortable termoeratures with m.isconduct in a prison community. 

American Journal of Community Psychology, 1977, 1, 289-298. 

Nacci, P.L., Teitelbaum, H.E., & Prather, J. Population density and 

inmate misconduct rates in the federal prison system. Federal 

Probation, 1977, 41, 26-31. 

Paulus, P.B. Crowding. In P.B. Paulus (Ed.) Psychology of Group 

Influence. Hillsdale, N.J.: La~l7I'ence Erlbaum Associates, 1980. 

Paulus, P.B., Cox, V.C., McCain, G., & Chandler, J. Some eff.ects of 

crowding in a prison environment. Journal of Applied Social ~chology, 1975, 1, 86-91. 

Paulus, P.B., McCain, G., & Cox, V.C. Death rates, psychiatric commitments, 

blood pressure, and perceived crowding as a function of institutional 

crowding. ~ironmental Psychology and Nonverbal Behavior, 1978, J, 107-116. 

Ray, D.W. The effects of high density in a juvenile .correctional ir..stitutiona Unpublished doctoral dissertation, George Peabody College for 

Teachers, 19'18. 

Rogers, M., Devandra, D., & Reich, P. The influence of the psyche and the 

brain on the immunity and disease susceptibility--A critical review. ~ychosomatic Medicine, 1979, 41, 147-164. 

Saegert, S. High density environments: Their personal and social consequences. In A. Baum & Y. Epstein (Eds.), Human responses to 

crowding. Hillsdale, N.J.: Lawrence Erlbaum AssOCiates, 1978. 

Smith, D.L. Adult male suicide in the correctional setting. Unpublished 

masters thesis, Sam Houston State University, 1977. 
_._

r 

148 

APPENDIX A 

Data Collection Forms 

1. Questionnaires 

2. Background and'Medical Forms 

3. Informed Consent Forms 

4. Crowding Tolerance Task 

.. 

• 

\~~~~~~~=tt=~e_'w_Q= __ ~ ________________________ __ 

A-I 

149 

HMm ________________________________ _ NUMBER _________ _ 

In this questionnaire you will be asked to use several rating scales. 

Below is an example of how these scales are used. This particular example 

involves rating today'Q weather. 

Example: Today's Weathe~ 

Good x __ -__ . 

0, __ - __ ~ __ _ 

Bad 

Cold x Hot 

Comfortable __________ :-_________ X... Uncomfortable 

In this example someone has checked the blanks to indicate that he thinks that 

today's weather is pretty good, neither hot nor cold. but very uncomfortable. 

All of the questions below will be like the example. 1rne more strougly you 

feel that the word at one end of the scale (good, cold, etc.) describes how you 

feel, the closer you should place your check mark toward that end of the scale. 

The room, cubicle, cel.l~ or dormitory in which you live. 

Good 

Unattrasctive 

Right n\DDber 

of people 

Unpleasant 

Well 

Arl'anged 

_o_ · . .. _O_o_e_o_ . . . . 

-------

· · . . . . . . . . . . 

_o_e_._e_e_e_ · . . . . . · · . '" . . . . . . . . --~------

· . . . . .. -------- • II • • • • 

Bad 

Attractive 

Too many 

people 

Pleasant 

Poorly, 

Arranged 

Uncomfortable 

--------..-. 

: : : : : : Comfortable 

Quiet _:_:-.--:,: __ =._:_:_ Noisy 

Uncrowded _:_:_:._:_:_=_ Very Crowded 

.f 

. \ 

-, - , 
.. 

rI 

i 

r I 

--- ------~-~----~----------------------.--.~.-=-----------

150 

A-I 

Each pair of words below describes a feeling. You may generally feel 

more one way than the other. So, for each pair put a check mark to show 

how you have felt most of the time this past week. The more strongly 

you feel that the word at the end of the line describes how you reel, 

the closer you should place your check mark toward that end of the line. 

Please take your time. 

., 

j 

, :- -

151 

A-I 

Questionnaire 

NAME:.-___________ ~ruMBER:....... ____ BIRTHDATE 

1. How much more time do you expect to serve? 

2. Date arrived at institution 

This past week most of the time I felt_~ 

Relaxed . . -----------_ . ......,.._._-- --- Wide-Awake . . . . . - ........ ~-.---.---.---.--- --- Happy . ... --- --~--- ---.----,..,......-~--;;---

Tough __ : ___ :~ ______ t .. _: ________ _ 

Satisfied~: 

----------------------- Stimqlated . . . ---___ • __ 0 ___ 0 __ - ------

Important ------------:------=---

Tense _______________ . 

0 __ - __ _ 

In control 

of my situation in this 

institution 

In f;;ontrol Ji..V~r others 

---in this 

institution 

--,--

---

Bored 

Sleepy 

Unhappy 

Weak 

Unsatisfied 

Rela.."Ced 

Unimportant 

Calm 

Not in control -

of my situation 

in this 

institution 

Not in control 

over others 

in this 

instit.ution 

3. Have you ever been in prison before? If yes, where and for how long? 

Prison or Jail How Long 

4. Job assignment in this prison 

S. Level of custody at this prison 

6. Listed below are prison activities. Do you do any of them? Hot..r many times a week? 

~ctivities Yes 

- Times Per tITeek 

Sports 

Religious 

Clubs 

Education 

Other 

- .\ 

-, ~/"-; 
.,: 

-----, 

152 

Questionnaire - Continued 

7. Do you have any trouble sleeping? 

Never ___ _ Occasionally ___ _ Often ---- 8~ Do you have problcmls with headaches? 

9. 

Never ___ _ Occasionally ___ _ Often ---- As a child did you live in a small town of 30.000 or les8 or a large city? 

---------------,-~-----------------------------------------------

10. As an adult have you lived most of your life in a small town of 30,000 

or less or a larger city? 

11. While you were grOTiing up how many p~ople. incluAing yourself, lived 

in your home? 

12. How would you rate your home life While you were growing up? 

Excellent Good ---- Fair __ _ Poor --- Very Poor 

13. How much time do you typically spend talking to people 

A great deal __ A little 

--

Quite a bit __ --- Very Little ~ .. 

14. Father: Occupation _....-. ___ ._._,. __ ... _-_-__ "n:ld"'6e complete High Sehogl'l_" _-"' __ 

15. Mother: Occupation _________ Did she complete High ~ehool? __ 

16. What are some things that bother you mast about your bousing conditions? 

! 

I 

-1 

J17. If you had to choose, what would you say bethers you most. too many- l "<. 

people in your cellar too 'little space in your cell? 

--.... --~ .. -.------.--.[ .' 

Check Olle: 'l'oo m~~ypeople 

.', A-I 

153 Qt:CStiOi,lna:1~~ - Continued : .~--" .-- "'.'-' . ~,~·.r 

18. HOl-1 much choice do you think you have about where you live in this prison? 

19. 

A whole 

lot Pretty 

A lot __ Much 

A 1itt'lle 

bit 

lIot at 

all --- How much choice d~ you think you have about whom y~u live with in this 

prison? 

A whole 

lot A lot __ Pretty 

much --- A little 

bit 

Not at 

a11 __ 

20. How much say do you think you have in how this prison is run~ 

It. whole 

lot A lot --- Pretty 

much --- A littl.e 

bit ___ iG:i 

Not: at 

811 __ 

21. How much choice de you have ove~ Whether you can do the recreational 

activities you like.. to do in this prison? 

A whole 

lot Pretty 

A lot ._ much ....-__ A little 

bit 

Not at 

a11 __ 

22. What type of housing would you prefer in your unit? 

Open dormitory __ Double Cell Single cell __ 

- .-~ . 

0' 

-\ .. ,. 
154' . A-2 

RACE ______ '_ ... 

,-;;- , 

OFFENSE . >,,/ 

-~---------'-'--------- COMK. DATE _..;.... .. __ _ 

EXP. GOOD TIME ------- ELIG.. P.14.ROLE 

------------------ ~-.: -" "-: .... ::-- --

SAT ____ _ BETA __ .... ' ___ _ 

MMPI SCOPJ:~~~., }) ",-;~"SI __ ES __ DO __ ST ___ •. __ _ 

HOUSING HISTORY 

.:.', 

-0" '.', .:_ .:..._._.~. -' DISClFtlNARY HISTORY 

t,." .e;: 

I: 

MEDICJ\.L HISTQRY 

.~ ______________________ . __ ~ __ -"~~'>-J~,.J.L.' ___ _ 

: 'if.t;-W- '~17""~::~~6";::; 

.-.;::.-{? 

:''*" 

-------------~----

A-3 

INrorumn CONSENT FORM 

This study is being eOllducted by Drs!,.~1\~,'Fauius~ r-"~' :~ .. :.: .. ~-;::~ ....... ::...---. -

-. -.---;--

155 

Garvin McCain, and Verne Cox 

who are psyeho1og:lsta fr~'~~;;"U~iversity of Texas -;.:.'} .. "./ -

at Arlington. The study is 

designed to det~~tine the best kind of housing for a prison setting. One 

of your physiological response to your bousing. In addition we would like your 

permission to examine EOiiIe ef your records, including medical and psychological 

records. Participation in this study will irr"'~lve no d~eomfort or :risk. 

I, ______________________________ ~~~ understand the purpose of the study 

entitled ________________________ ~.~,----________________________________ __ 

----~--===---------~ ..... --~------~~~~~------~~-----------------------, /' 

as explained above, and I ~onsent to pa~tielpate in the study and to permit the 

Bureau of Prisons institutional staff to release the information in my records, 

including psychological and medical records, to the researchers for the purposes 

of the study. My consent is voluntary and I understand that all information 

will be handled in the stricteat confidence and that my participation will not 

be individually identifiable in any rc~orts. I further understand that there 

1:s no penalty or prejudice of any kind for not participating in the study. 

--- ----~~------.. ----------~--~--~~~ (~1gnatu~e) (Rep.1ster No.) (Date) 

<I (Wi tnC!ss) (Date) 

~ . 

--'-------~-=----------~-----~~-------- -_ .... _------ -------------~- ----- -------- ----------------

, . 

• ~:p ",~' 

0, 

./ 
--~ - -----~ 

._

156 

A-4 

! 

! , 

Crowding Tolerance Task 

.. u. S. GOVERNMENT PRINTING OFFICE: 1981 341·233/ IDS3 I ' 

i 

.,