the relationship between housing characteristics, emotional well-being and the personal empowerment...

q 1998 Human Sciences Press, Inc.57

Community Mental Health Journal, Vol. 34, No. 1, February 1998

The Relationship Between HousingCharacteristics, Emotional Well-Being

and the Personal Empowerment ofPsychiatric Consumer/Survivors

Geoffrey Nelson, Ph.D.G. Brent Hall, Ph.D.

Richard Walsh-Bowers, Ph.D.

ABSTRACT: In this research, we examine the relationships between the housingcharacteristics and dimensions of community adaptation for 107 psychiatric consumer/survivors. Hypotheses about which housing characteristics best predict which dimen-sions of adaptation were made based on previous research and theory. Using a longi-tudinal research design, we found, after controlling for demographic variables andprior adaptation, that the number of living companions, housing concerns, and havinga private room all significantly predicted different dimensions of community adapta-tion. The findings partially support our theoretical expectations and illuminate therelationship between physical, social and organizational aspects of community-basedhousing and the adaptation of psychiatric consumer/survivors. We discuss the implica-tions of the results for policy and practice in providing housing for this population.

We are grateful to the National Health Research Development Program of Canada, the On-tario Ministry of Health, Community Mental Health Branch, Wilfrid Laurier University, and theUniversity of Waterloo for funding this research, and the Ontario Mental Health Foundation forsupporting the Principal Investigator with a Senior Research Fellowship. We thank the residentsand staff of the different types of housing for their participation in the research and the followingpeople for their research assistance: Donna Cameron, Gary Edwards, Lorie Fioze, Judy Gould,Karen Hayward, Janice McCarthy, Cari Patterson, Leslea Peirson, Kelly Peters, Ruth Slater,Denise Squire, and Colleen Wiltshire.

Geoffrey Nelson, Ph.D., is Professor of Psychology, Wilfrid Laurier University. G. Brent Hall,Ph.D., is Professor of Urban and Regional Planning, University of Waterloo. Richard Walsh-Bowers, Ph.D., is Professor of Psychology, Wilfrid Laurier University.

Direct inquiries for further information about this study to Geoffrey Nelson, Department ofPsychology, Wilfrid Laurier University, Waterloo, Ontario, Canada N2L 3C5.

58 Community Mental Health Journal

In recent years, there has been a growing body of research whichhas examined the housing of psychiatric ª consumer/survivors º (Hogan& Carling, 1992; Nelson & Smith Fowler, 1987). The term ª consumer/survivorº refers to people who have been hospitalized for severe andlong-term mental health problems, including conditions commonlyidentified as schizophrenia, manic-depression, and severe depression.We use this term because many individuals who have experienced se-rious mental health problems and organizations representing this pop-ulation prefer it. Adequate, affordable housing plays a vital role in theadaptation of consumer/survivors. However, the housing conditions inwhich many have been forced to live following discharge from hospitalhave been deplorable, as all too poignantly described by those whohave lived in such settings (e.g., Capponi, 1992). Thus, it is importantto understand the relationship between housing qualities and the com-munity adaptation of consumer/survivors. Knowledge about the effectsof housing characteristics on adaptation should help program plan-ners, practitioners, and consumer/survivors to create housing environ-ments that best promote adaptation and well-being. Research that hasexamined the qualities of housing for consumer/survivors has focussedon two broad dimensions: a) the physical-architectural environmentand b) the social environment (Nelson & Smith Fowler, 1987). Whilethere is often a close relationship between the physical design and con-dition of a dwelling and the social atmosphere and interaction of itsresidents, they are often examined in isolation from each other. In thispaper, we review research on how each dimension of housing, physicaland social, is related to two dimensions of consumer/survivor adapta-tion: a) emotional well-being and b) personal empowerment. Emotionalwell-being refers to subjective feelings of well-being and has been oper-ationalized by scales measuring positive affect, negative affect, and lifesatisfaction. Personal empowerment refers both to feelings of controland to instrumental skills, such as the ability to function indepen-dently.

Research on the physical-architectural environment has focused onhousing problems, privacy, and the number of people living in the resi-dence. Measuring problems with the physical quality of housing envi-ronments (e.g., problems with safety, maintenance), researchers havefound that housing problems are related to several aspects of adapta-tion, including negative affect (Earls & Nelson, 1988) and dissatisfac-tion with their quality of life (e.g., Nelson, Wiltshire, Hall, Peirson, &Walsh-Bowers, 1995). Furthermore, one of the complaints of con-sumer/survivors residing in small group homes is the lack of privacy

Geoffrey Nelson, Ph.D., et al. 59

which is particularly acute for people who had to share a room withsomeone else (McCarthy & Nelson, 1993). A two-factor theory of emo-tional well-being, consisting of pain-avoidance and growth needs, canbe used to understand how some housing characteristics have an im-pact on residents’ well-being (Earls & Nelson, 1988; Newman Re-schovsky, Kaneda, & Hendricks, 1994). When consumer/survivors failto have their basic pain-avoidance needs met for stable and predict-able housing because of poor-quality housing conditions and a lack ofprivacy, they experience emotional stress and possibly psychiatricsymptoms. However, such basic housing characteristics cannot meethigher-order needs for growth-fulfilment. The above literature sup-ports this theory, as poor quality housing is related to experiences ofnegative affect and dissatisfaction.

Research on the number of people living in a residence has foundthat settings with fewer residents are associated with less anxiety,less passivity, less psychological distance from others, and more posi-tive views of the social environment (Hellman, Greene, Morrison, &Abramowitiz, 1985) and more self-sufficiency (Kruzich & Berg, 1985).Moreover, Hellman et al. (1985) found that when three settings, hous-ing six consumer/survivors each, were merged into one large facility,the residents became more passive and experienced more psychologi-cal distance from others. These findings can be interpreted in terms ofthe theory of understaffing, which postulates an inverse relationshipbetween the size of a facility and the degree of involvement of resi-dents in its operation and maintenance (Barker & Gump, 1964).

The second broad dimension of housing is the social environment.Research has focused on social support networks, staff management-style, and resident control. Social support from living companions,staff, and people living outside the residence is very important for con-sumer/survivors’ positive affect and life satisfaction (Baker, Jodrey, &Intagliata, 1992; Earls & Nelson, 1988; Nelson, Hall, Squire, & Walsh-Bowers, 1992; Nelson et al., 1995; Hall & Nelson, 1996). Moreover,consumer/survivors report that friends and living companions are thepeople with whom they most often socialize and engage in recreationalactivities (Nelson et al., 1992). Social support networks are one impor-tant source of fulfilment of consumer/survivors’ ª growthº needs accord-ing to Earls and Nelson (1988). When a person’s growth needs are met,he or she experiences positive affect, as the above literature demon-strates.

Another important aspect of community residences concerns the dif-ferences in power between residents and staff, manifested on a daily


basis in staff management-style and degree of resident control.Kruzich and Berg (1985) found that rigidity of routine, block treat-ment and depersonalization of residents, and social distance betweenresidents and staff were inversely related to residents’ self-sufficiency.Segal and Moyles (1979) found that consumer/survivors residing insettings with a staff-centred management style showed more depen-dency than consumer/survivors living in settings with a more resident-centred management style. In a study of group homes, McCarthy andNelson (1991) found that resident control in decision-making was di-rectly related to subjective quality of life and level of independentfunctioning. They also observed that democratic management, whichinvolved staff discussion and negotiation with residents regarding res-idents’ problem behaviours, was associated with their subjective qual-ity of life. These findings have been replicated in subsequent research(Nelson et al., 1995). Overall, these findings can best be understood interms of empowerment theory. When consumer/survivors have someactual control over decision-making and participate actively in theirsettings, they experience control, personal growth, and well-being.

There are some important limitations to much of this literature.First, because the research is associational in nature, it is not possibleto state with any degree of certainty which housing characteristicscause which types of outcomes. Second, most of the literature is basedon cross-sectional rather than temporal designs, so that potentialcausal effects between the variables cannot be examined. Finally, theobserved relationships between housing characteristics and adaptationcould be due to other unexamined variables, such as individual differ-ences in gender, age, education, and income, which often are not statis-tically controlled in data analyses. Frequently consumer/survivors whohave relatively high levels of functioning and education and who areyounger reside in housing with the most desirable characteristics (e.g.,apartments or group homes), whereas older, less educated lower func-tioning people are more likely to reside in some type of sheltered-carefacility. Those studies which have controlled for personal characteris-tics (e.g., Kruzich & Berg, 1985) or used longitudinal designs and con-trolled for earlier adaptation (Baker & Douglas, 1990) have found thathousing characteristics add significantly to the prediction of adapta-tion beyond individual differences and/or prior adaptation.

The purpose of this paper is to examine, in two ways, the relation-ship between several housing qualities and different dimensions ofconsumer/survivor adaptation. First, we use a longitudinal design tocontrol for the effects of individual difference variables and prior adap-


tation and to examine the potential causal role of housing characteris-tics on consumer/survivors’ adaptation. Second, we test specific theo-retical predictions regarding which housing characteristics might berelated to which dimensions of adaptation:

1. Based on the two-factor theory of emotional well-being, socialnetwork support is related to positive affect, but not to other di-mensions of adaptation.

2. Based on the two-factor theory, physical problems with housingand lack of privacy (i.e., not having one’s own room) are related tonegative affect, but not to other dimensions of adaptation.

3. Based on the theory of understaffing, the larger the size of theresidence (i.e., the number of people living in the setting), thelower the level of personal empowerment (perceived control andindependent functioning).

4. Based on empowerment theory, the higher the degrees of resi-dent control and democratic management in the residences, thehigher the level of personal empowerment (perceived control andindependent functioning).

METHOD

Research Context and Design

Participants were recruited from 29 settings (apartments, group homes, and board-and-care facilities) in several communities in southwestern Ontario. The settings pro-vide housing for people with severe and long-term psychiatric disabilities, but individ-uals who are violent or who have a recent history of drug or alcohol abuse are ineligi-ble. The researchers initially met with staff and mental health workers to explain thenature of the study. After the latter identified potential participants, research assis-tants (RAs) contacted interested residents either in-person or by phone. The RAs ex-plained the purpose of the study, what participation would entail, and the rights ofparticipants (i.e., confidentiality, the right to refuse to answer questions, the right towithdraw at any time). Further, the RAs gave the residents a letter reiterating thesepoints and asked them to sign a consent form if they agreed to participate. Partici-pants completed an Adaptation to Community Living Assessment and a Social Net-work Assessment at the initial interview (T1), and they completed these two assess-ments and a Housing Environment Assessment at a follow-up interview conducted oneyear later (T2). Participants were also paid $10 for each of the interview schedulesthey completed.

Sample

A total of 173 people completed the T1 interview, and 107 completed both T1 and T2interviews for an attrition rate of 38%. The reasons for attrition are: 33 people moved;


19 withdrew; eight were rehospitalized at the time of the T2 interview; four died; onewas evicted; and one was too disoriented to do the T2 interview. We compared the 107people who completed the interviews at both T1 and T2 with the 66 people who com-pleted only the T1 interview on gender, age, education, monthly income, marital sta-tus, size of social network segments, measures of emotional well-being, perceived con-trol, and independent functioning. Participants in the final sample did not differsignificantly from participants in the attrition group on any variables examined. Thus,the final sample of 107 residents appears to be fairly representative of the larger,initial sample of 173.

The sample comprised 57.9% men and 42.1% women, who ranged in age from 20 to73 (X 4 37.4). Slightly more than half of the participants had completed their highschool education or beyond (52.3%); the majority had a gross monthly income of lessthan $750 (66.3%); most were single, separated, divorced, or widowed (91.6%); and allwere White.

Interview Process

Roughly two-thirds of the interviews were conducted by two RAs, both women with anM.A. in Community Psychology. The remaining interviews were conducted by sevenwomen and three men with a degree in Psychology or Social Work. Interviews wereconducted mainly in the residences, but on some occasions in nearby coffee shops ormental health offices. The interviewers attempted to make the respondents feel ascomfortable as possible, letting them know that they were in control of what theychose to share or not share. A few participants talked about the interviews as beingtests and hoped they were giving the ª rightº answers. In those instances, the respon-dents were assured that the interviewers were interested in the opinions of the partici-pants, and that there were no ª rightº answers. All participants were sent interim andfinal summaries of the study’s findings.

Measures of Social Support Network and Housing Characteristics

Participants were asked to list the people important to them in the following networksegments: family, peers (living companions and friends), and professionals (includinghousing staff). Participants were also asked how many people lived in their residence(as a measure of residence size) and whether or not they had their own room (as ameasure of privacy).

To construct a measure of Housing Concerns with the physical comfort of the resi-dence, several items were taken from the Rating Scale of Moos and Lemke’s (1979)Multiphasic Environmental Assessment Procedure (MEAP). The items (e.g., ª Does itever smell bad here?º ) were answered on a ª yesº or ª noº basis. Cronbach’s alpha was.73 for this 15-item measure.

A slightly modified version of the Resident Control scale of the MEAP was used.Residents were asked the extent to which they were involved in decision-making (e.g.,selecting new residents) on a three-point scale: ª staff controlº (1 point), ª shared con-trolº (2 points), ª resident controlº (3 points). This 10-item scale had an alpha of .88.

A scale to assess Staff Management-Style was adapted from the Tolerance for Devi-ance scale of the MEAP. Residents were asked which style staff would use to respondto potential problems involving residents (e.g., ª verbally threatening another resi-dentº ). The response options were a Democratic style in which staff engages resi-dent(s) in problem-solving, an Authoritarian style in which staff intimidates orthreatens residents, or a Permissive style where nothing is said or done. The numberof times the Democratic category was used by participants is summed to obtain a scorefor this measure. The alpha for Democratic Style was .72.


Measures of Adaptation

Items measuring Positive Affect and Negative Affect (emotional well-being) weretaken from Diener and Emmons (1985). The five items for each factor were rated on afive-point scale of frequency of occurrence ª over the past weekº from ª not at allº toª everyday.º The alphas for Positive Affect were .90 at T1 and .89 at T2, and .77 at T1and .81 at T2 for Negative Affect.

Pearlin and Schooler’s (1978) seven-item Mastery scale was used to measure resi-dents’ perceptions of control over life circumstances (personal empowerment). Theitems were rated on a four-point scale from ª strongly agree º to ª strongly disagree.º Thealphas were .73 at T1 and .78 at T2.

A second measure of personal empowerment was a six-item Independent Function-ing scale developed by Rappaport and his colleagues (1985), which we adapted to as-sess residents’ independent functioning in areas of daily living, such as money man-agement, housekeeping, and meal preparation. Each item was rated on a three-pointscale: others’ responsibility (1 point), shared responsibility (2 points), own respon-sibility (3 points). Residents and staff, with residents’ consent, completed this mea-sure. Staff and resident versions were highly correlated at T1 (r 4 .64). The alphas forthe resident version, which we used in this study, were .73 at T1 and .75 at T2.

Data Analysis

The data were analyzed in two ways. First, Pearson correlation coefficients were cal-culated between the demographic, social network, and housing variables at T2 and theadaptation measures at T2. Gender, education, and income were dummy-coded for allthe analyses. Second, regression analyses were performed to determine if the socialnetwork and housing variables added to the prediction of the T2 adaptation measuresafter controlling for demographic variables and T1 adaptation. Four stepwise multipleregression models were estimated, one for each of the four T2 adaptation measures.The independent variables were entered in blocks, with demographic variables en-tered on the first block, the T1 adaptation measure on the second block, and the socialnetwork and housing variables on the third block. The F to entry level was set at p .05.

RESULTS

Correlations between the demographic, social network, and housingvariables at T2 and the T2 adaptation measures showed that genderand income were not significantly correlated with any of the adapta-tion measures. Age was significantly inversely related to Negative Af-fect (r 4 1.26, p , .01) and Independent Functioning (r 4 1.34, p ,.01); older residents reported lower levels of negative feelings and in-dependence than younger residents. Education was directly related toMastery (r 4 .27, p , .01) and Independent Functioning (r 4 .35, p ,.01); residents with higher levels of education reported more perceivedcontrol and independence than residents with lower levels of educa-tion. Consistent with the first hypothesis, the size of a person’s peernetwork was directly related to Positive Affect (r 4 .20, p , .05). How-


ever, neither of the other two social network measures was related toPositive Affect. Also, the size of participants’ family networks was di-rectly related to Mastery (r 4 .22, p , .05).

Housing Concerns (r 4 .22, p , .05) and not having one’s own room(r 4 .21, p , .05) were directly related to Negative Affect, which sup-ports the second hypothesis. Unexpectedly, not having one’s own roomwas related to lower levels of Independent Functioning (r 4 .37, p ,.01). The number of residents in participants’ housing was inverselyrelated to their levels of Independent Functioning (r 4 1.61, p , .01),supporting the third hypothesis. The larger the size of the facility, thelower was participants’ level of independence. Resident Control wasdirectly related to consumer/survivors’ level of Independent Function-ing (r 4 .49, p , .01), which supports the fourth hypothesis. Contraryto our predictions, Democratic Staff Management Style was not signif-icantly related to participants’ level of Independent Functioning, andthe number of residents, Resident Control, and Democratic Style werenot significantly related to the other index of empowerment, Mastery.

The results of the multiple regression analyses are presented in Ta-ble 1. The four regression models accounted for between 33% and 67%of the variance in the prediction of adaptational outcomes. For PositiveAffect, only the prior level of Positive Affect was a significant predic-tor. Age was inversely related to Negative Affect, although it was nolonger significant after variables on subsequent blocks entered theequation. As predicted, Housing Concerns and not having one’s ownroom added to the prediction of Negative Affect, after controlling forprior Negative Affect. Level of education had a significant direct effecton Mastery. Also, unexpectedly, Housing Concerns added to the predic-tion of Mastery, after controlling for prior Mastery. Finally, both ageand education level significantly predicted Independent Functioning.Moreover, as predicted, the number of residents in consumer/survivors’housing added to the prediction of Independent Functioning, after con-trolling for earlier levels of Independent Functioning.

DISCUSSION

Qualified support for our first hypothesis that network support wouldbe related to positive affect was obtained. Social support, as measuredby peer network size, was significantly correlated with positive affect.However, this association did not hold in the regression analysis. Per-haps our measure of network support was not the best indicator of

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social support. Measures of enacted support (how often support is pro-vided) are more strongly related to positive affect than measures of thenumber of people providing support (as we used in this study) (Earls &Nelson, 1988; Nelson et al., 1992; Nelson et al., 1995). Thus, we sug-gest that future longitudinal research testing the relationship betweensocial support and positive affect use measures of enacted support.

Both the correlational and regression analyses supported our secondhypothesis that housing concerns and a lack of privacy would be di-rectly related to residents’ experiences of negative affect. These resultsconfirm and extend those of previous studies (Baker & Douglas, 1990;Earls & Nelson, 1988; Nelson et al., 1995; Newman et al., 1994). Thelongitudinal design and controls for demographic factors and earlierlevels of negative affect suggest a possible causal role for housing con-cerns and lack of privacy on negative affect. However, research usingexperimental or quasi-experimental designs is needed to clarify theissue of causality.

Together, these findings confirm the utility of the two-factor theory ofemotional well-being for the adaptation of consumer/survivors (Earls &Nelson, 1988). Physical housing concerns and the social housing envi-ronment differentially influence positive and negative affect in predict-able ways that are consistent with this theory. Housing that is physi-cally comfortable and provides private space helps to meet people’sbasic needs for security, and, in so doing, reduces negative affect. Socialnetwork support, on the other hand, may help to meet people’s growthneeds, thus accelerating positive affect.

These results, in conjunction with existing research, have implica-tions for policy and practice. One important ingredient of the preferredhousing environment is the privacy of having one’s own room. Clearly,there is a close relationship between the size of a residence, measuredin terms of number of bedrooms, the number of residents filling bed-spaces, and privacy. Even in small, well-kept supportive residences, aratio of two or more residents per bedroom must be regarded as unsat-isfactory (cf. McCarthy & Nelson, 1993). Thus, we advocate that resi-dents have their own rooms. Also, consumer/survivors must have ade-quate income so that they can afford to live in housing that is of adecent physical quality. Substandard rooming homes will only furtheraggravate consumer/survivors’ emotional adaptation (Capponi, 1992).Further, it is important for supportive housing coordinators to encour-age the development of relatively large social support networks for res-idents that comprise, in the first instance, peers and, to a lesser ex-tent, professionals.


An additional dimension of the physical housing environment that isclosely related to the social interaction of residents is the number ofliving companions. The theory of understaffing suggests that as resi-dences increase in size, they become less of a home and more of aª holding facilityº (Nelson & Smith Fowler, 1987). In a smaller, lesspopulated residence, there are likely to be few, if any, staff to performdaily living tasks for residents. This situation affords the opportunityfor residents to take a more active role in doing their own cooking andcleaning, for example. However, in contrast, in larger, more institu-tional settings, such routine tasks are staff-oriented activities. Consis-tent with the theory of understaffing and previous research (Hellmanet al., 1985; Kruzich & Berg, 1985), participants from larger resi-dences in our sample reported lower levels of independent functioning.Both the correlational and regression analyses clearly support this hy-pothesis with respect to independent functioning, but not with respectto mastery. Again, this finding has clear implications for policy andpractice. Large, congregate facilities that have an institutional-likequality to them should be discontinued. Instead, consumer/survivorsshould receive the financial and social support that they need to obtainnormal housing in the community of their choosing (Hogan & Carling,1992; Newman et al., 1994).

The physical and social dimensions of housing conditions coalesce inthe style of management adopted by housing staff. We hypothesizedthat residences in which staff respond to resident problems witha democratic management-style and in which residents contribute todecision-making on matters such as setting house rules are likely topromote independent functioning and feelings of mastery. The correla-tional results confirmed that resident control, but not staff manage-ment-style, was positively related to level of independent functioning.However, this relationship was not evident in the regression analyses.The number of residents living in a setting is the only housing variableto show both correlational and causal relationships with independentfunctioning. Because settings with more residents generally tend to belarger and have more staff control, it is likely that the causal effect ofresident control is embodied in the regression parameter for the num-ber of residents.

The fact that resident control, not staff management-style, was re-lated to independent functioning may indicate that the resident con-trol measure is a more sensitive indicator of decision-making in a resi-dence. The items in the resident control scale refer to actual decisions(e.g., meal planning), while the staff management-style scale items re-


fer to potential problems with residents (e.g., one resident threateninganother), which may never occur and are therefore difficult for resi-dents to answer. Also, neither scale was significantly associated withthe measure of Mastery. Thus, resident control seems to be more im-portant for residents’ ability to function independently rather thantheir global feeling of control. Issues of control and decision-making inresidences for psychiatric consumer/survivors clearly need more elab-oration and study, as the results of various studies are inconsistent(Kruzich & Berg, 1985; McCarthy & Nelson, 1993; Segal & Moyles,1979).

Overall, housing concerns, privacy, and the number of individualsliving in a supportive housing unit all significantly predict specific di-mensions of community adaptation. These effects are consistent withtheory and, more importantly, they comprise factors that are modifia-ble by intervention through careful planning and monitoring. In addi-tion to the above observations, there are consistent and strong tempo-ral effects evident in our data on all dimensions of communityadaptation. These effects suggest that efforts made by housing staffto foster adaptation upon entry of individuals into a residence willstrengthen the prospects for consumer/survivors to integrate mean-ingfully into the community. However, before absorbing the findingsinto housing policy, it is important to examine two crucial influenceson adaptation, namely management-style and resident control, morethoroughly than was the case in our study. Moreover, as others haveindicated (Newman et al., 1994), factors that describe the residentialneighbourhood setting may also contribute positively or negatively toachieving the goal of community adaptation. Accordingly, we echo thecall for renewed efforts in developing controlled temporal research de-signs that allow monitoring of consumer/survivors’ adaptation overtime.

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the relationship between housing characteristics, emotional well-being and the personal empowerment...

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