An Outcome in Need of Clarity

8/13/2019 An Outcome in Need of Clarity

1/10The American Journal of Occupational Therapy 181

An Outcome in Need of Clarity: Building a Predictive Modelof Subjective Quality of Life for Persons With Severe MentalIllness Living in the Community

Peiying Sarah Chan, Terry Krupa,

J. Stuart Lawson, Shirley Eastabrook

PURPOSE. The study purpose was to construct a predictive model of subjective quality of life for personswith severe mental illness living in the community with particular attention to participation in occupations.

METHOD. Persons with severe mental illness (N= 154) rated their subjective quality of life. Several mea-sures for each of the following categories of variables were completed: demographics, clinical, social partici-

pation, and self-measured well-being. Regression analysis was used to determine the significant predictors for

each category and then to build the predictive model from these significant variables.

RESULTS. Symptom distress accounted for the most variance (33%) in subjective quality of life, followedby psychological integration (3%) and physical integration (2%).

CONCLUSIONS. The study suggests that occupational therapists should attend to subjective experience ofsymptoms to influence quality of life. Therapists are also in a good position to address their clients sense of

belonging to their communities and to enable community participation.

Chan, P. S., Krupa, T., Lawson, J. S., & Eastabrook, S. (2005). An outcome in need of clarity: Building a predictive model of

subjective quality of life for persons with severe mental illness living in the community. American Journal of

Occupational Therapy, 59, 181190.

Q

uality of life has emerged as an important indicator of community adjustment

for those with severe mental illness. A response to the notion that avoiding hos-pitalization is not, by itself, a meaningful measure of successful community adjust-

ment, quality of life is viewed as a construct with the potential to capture impor-

tant aspects of the community life experience. In the profession of occupational

therapy the construct has gained prominence because the experience of participa-

tion in occupations is considered to be closely associated with quality of life

(Laliberte-Rudman, Yu, Scott, & Pajouhandeh, 2000; Mayers, 2000; Velde, 2001).

The quality of life construct has been developed as a complex interaction

between multiple dimensions including the illness experience (Achat et al., 1998), an

individuals state of physical, psychological, and social well-being (Ferrans & Powers,

1985; Lehman, 1983), satisfaction with life activities and relations and opportunities

for autonomy (Keith & Schalock, 1994), and consistency between personal percep-tions of the consistency between goals hopes and current situations (Hinds, 1990).

Objective conditions of community life, such as those reflected in societal

standards for finances, housing, friendships, work, and safety are considered inte-

gral to quality of life, in that it is assumed that an individuals status in these areas

will impact on the sense of well-being in the community (De Souza, 2000).

Studies by occupational therapists support the view that both subjective and objec-

tive factors are part of the experience of quality of life (Laliberte-Rudman et al.,

2000; Mayers, 2000).

Although the relationship between objective and subjective aspects of quality

of life seems intuitively logical, the nature of this relationship remains somewhatof a puzzle. For example, individuals who appear to be living in objectively poor

Peiying Sarah Chan, MSc, OT Reg (Ont), NRCS, is

Doctoral Student, Department of Physiological Sciences,

College of Veterinary Medicine, University of Florida,Gainesville, Florida. At the time of the study Ms. Chan was

a graduate student in the School of Rehabilitation Therapy

at Queens University, Kingston, Ontario, Canada.

Terry Krupa, PhD, OT Reg(Ont), is Associate Professor

and Chair, Occupational Therapy Program, School of

Rehabilitation Therapy, Faculty of Health Sciences,

Queens University, Kingston, Ontario, Canada KL7

3N6;[email protected]

J. Stuart Lawson, PhD, is Professor, Department of

Psychiatry, Queens University, Kingston, Ontario, Canada.

Shirley Eastabrook, PhD, RN, is Assistant Professor,

School of Nursing, Faculty of Health Sciences, Queens

University, Kingston, Ontario, Canada.


2/10182 March/April 2005, Volume 59, Number 2

conditions may still give high ratings to their experience of

subjective quality of life. (Fakoury & Priebe, 2002; Ruggeri,

Bisoffi, Fontecedro, & Warner, 2001). This suggests that

there may be several mediating influences on the subjective

state of well-being as it is experienced by persons with severe

mental illness in the community. It appears that the subjec-

tive experience and objective indicators of quality of life are

distinct constructs (Ruggeri et al., 2001), both of which are

required to provide a complete picture of the life circum-

stances of service recipients.

Subjective quality of life, or an individuals own per-

ception of well-being, happiness or satisfaction, is an

important aspect of a client-centred service system. From an

occupational therapy perspective, subjective quality of life,

along with material life circumstance and activity and role

performance, is one of the key dimensions of the quality of

life construct. Subjective quality of life suggests that the

evaluation of quality of life in occupational therapy should

include objective observations of behaviours and life cir-cumstances and self-report measures that attempt to cap-

ture the individuals experience of well-being.

Previous research has indicated a lack of understanding

of the factors that influence subjective quality of life of indi-

viduals with serious mental illness living in the community

(Ruggeri et al., 2001; Ruggeri, Gater, Bisoffi, Barbui, &

Tansella, 2002). Prince and Prince (2001) stress that clari-

fying the construct is essential if evaluations of community

services for persons with serious mental illness are to con-

tinue to use change in subjective quality of life as evidenceof successful intervention. This is an important concern for

occupational therapists who expect to see changes in the

subjective experience of quality of life as a result of inter-

ventions that engage individuals in meaningful activities.

Building and testing predictive models of subjective

quality of life is one way to develop conceptual clarity. In

this paper we present the results of a study in which we

examined determinants of subjective sense of quality of life

for individuals with severe mental illness who were receiv-

ing community-based mental health services. Consistent

with the domain of occupational therapy, we were particu-larly interested in building a predictive model of subjective

quality of life that included involvement in everyday occu-

pations. The findings of the study are discussed in relation-

ship to the construct of subjective quality of life and the

implications for occupational therapy practice.

Method

This study was a secondary analysis of data from a 4-year

study examining the processes and outcomes of fourAssertive Community Treatment (ACT) teams in South-

eastern Ontario (Krupa, Eastabrook, & Gerber, 1998).

Together these teams serve approximately 370 individuals

in two small cities and their adjoining rural areas.

ACT has received international attention as an effective

community-based program for individuals with severe

mental illness who have been heavy users of mental health

services. Originally developed in the 1970s, the ACT model

was designed as an alternative to hospital-based treatments,

enhancing community adjustment by providing continu-

ous and 24-hour, in vivo services for illness management,

daily living, work and leisure activities, and crisis manage-

ment (Stein & Test, 1980). The model has been widely

researched and disseminated internationally.

The ACT model has been subject to standardization in

order to ensure consistency in its implementation. Two

standardized fidelity measurements were used to ensure that

services offered by the four teams were consistent with stan-

dard ACT practice guidelines: The Index of Fidelity of

ACT (McGrew, Bond, Deitzen, & Salyers, 1994) and theCritical Components of ACT Interview (McGrew & Bond,

1995). The larger study received university research ethics

approval and informed consent was obtained from all par-

ticipants. The data of 154 randomly recruited clients from

the four ACT teams were available for use in this study.

The mean age of the study participants was 43 years

(SD= 11) with a range from 17 to 68 years. Eighty-seven

percent were presently single, and 78% were living in pri-

vate houses or apartments in the community. Sixty-three

percent had a secondary school education, whereas 28%had some post-secondary education. Schizophrenia (56%),

and mood disorders (21%) were the most prevalent diag-

noses. The mean age of the clients at first hospitilization was

26 (SD= 9). The mean length of time that the clients par-

ticipated in ACT programs was 38 months (SD= 33). This

demographic profile is consistent with the characteristics of

individuals with severe mental illness living in the commu-

nity and served by ACT.

Quality of Life Model

We developed a predictive model to capture the multidi-

mensional nature of the subjective quality of life construct.

The model was constructed from a review of quality of life

research studies in the area of psychiatry, ACT, community

mental health, and psychosocial occupational therapy.

Specifically, we examined these studies to isolate variables

that are believed to influence subjective quality of life. This

lead to the identification of 25 potential predictor variables

that were than organized into categories to form a model.

The model comprised four categories of potential predictorvariables:



(1) Demographics: This category included variables that

are social descriptors of the participants and comprised

age, gender, marital status, education level, residential

status, length of stay in the program, and age at the first

psychiatric hospitalization.

(2) Clinical variables: This category described the partici-

pants health situation. Clinical variables comprised

diagnosis, clinical symptoms, days in hospital, physical

health, alcohol and drug use, functional status, and

medication compliance.

(3) Social participation variables: This category comprised

variables related to actual participation in the activities,

events and locations in the community. Social partici-

pation variables included physical aspects and social

aspects of community integration, community resource

use, contact with family, contact with friends, and time

spent in productive activities.

(4) Self-measured variables of well-being: This category

referred to the sense of well-being in a variety of lifedomains, and comprised the participants perception of

the availability of social support, sense of personal em-

powerment, psychological aspects of community integra-

tion, and the personal experience of symptom distress.

Data Collection

Information was collected by trained research assistants

using a standardized research protocol. The training includ-

ed measures of interrater reliability for the instruments.Table 1 summarizes data collection instruments in relation

to the proposed predictive model.

The independent variable, subjective quality of life,

was measured as the average of the two global well-being

scores on the Quality of Life Interview (QOLI; Lehman,

1988). The QOLI is widely used in the mental health field

and has proven to have good psychometric properties

(Nieuwenhuizen, Schene, Boevink, & Wolf, 1997).

Global well-being is rated on a seven point scale ranging

from 1 terrible to 7 delighted. Although the QOLI

contains several subscales measuring subjective and objec-tive quality of life in eight domains, we selected alternate

measurements instruments that were consistent with our

conceptual model and provided a more complete assess-

ment of specific variables. For example, the QOLI health

domain lacks specificity with respect to symptoms associ-

ated with mental illness, and the daily activities domain

includes only a small number of activities as evidence of

actual participation in the community.

Demographics were collected from the ACT health

records and interviews with the participants and case man-agers. Diagnoses were extracted from clinical records.

A modified version of the Canadian Toolkit for

Psychosocial Outcomes (Evaluation Centre @ HSRI, 1995;

Ontario Federation of Community Mental Health and

Addictions Programs, 2000) was used to collect the infor-

mation about the following domains for the previous 9-

month period: nature of the type of living situation (private

house or apartment, shelter, boarding home, foster home,

rooming house, group home or co-op, retirement home,

long-term-care facility, correctional facility, specialty hospi-

tal, psychiatric hospital, general hospital, chronic care hos-

pital, or on the street); days spent in hospital; physical

health problems (1 = no physical health problem, 5 = severe

or complete incapacity due to physical health problem);

medication compliance (1 = most of the time, 3 = less than

half the time); and number of hours spent by participants

in any paid or unpaid productive activities.

A Community Services and Support Programs Log

was developed to measure the number of hours in the pre-

vious month during which a participant used communityservices and support programs, beyond those provided by

ACT. The log was designed for use by several models of

community mental health service delivery and based on

Beecham and Knapps (1992) Consumer Service Receipt

Interview and a societal costing instrument developed by

Table 1. Summary of the Quality of Life Model and Measurements

Category Variables Measurements

Demographics Age, gender, educational ACT records

level, marital status,length of time in the

program, age at first

psychiatric hospitalization,

residential status PSR toolkitResidential log

Clinical Diagnosis, ACT records

symptoms, BPRS-E

days in hospital, Hospitalization Log

alcohol use, Alcohol Use Scale

drug use, Drug Use Scale

functional status Multinomah Community

Ability ScaleAdjustment

to Living

Physical health, PSR ToolkitHealth,

medication compliance Education, and LegalDomains

Social Time spent on productive PSR ToolkitEmployment

participation activities, Domain

Community resource use, Community Resource Use

Physical integration, Scale

Social integration, Physical Integration Scale

Contact with family, Social Integration Scale

Contact with friends

Self-measured Social support, Social Support Scale

well-being Empowerment, Empowerment Scale

Symptom distress, Symptom Distress Scale

Psychological integration Psychological Integration

Scale



Wolff, Helminiak, & Diamond (1995; see Dewa, Horgan,

Russell, & Keates, 2001).

The Expanded Brief Psychiatric Rating Scale (BPRS-E;

Lukoff, Nuechterlein, & Ventura, 1986) was used to rate

24 psychiatric symptoms (1 = not present, 7 = extremely

severe). The BPRS is widely used in psychiatric research and

has been shown to have good psychometric properties.

The Alcohol Use and Drug Use Scales (Drake &

Wallach, 1989), were used to measure clinicians ratings of

participants substance use in the previous 6 months (1 =

abstinent, 5 = dependence with institutionalization). Both

the alcohol and drug scale are reported to have good sensi-

tivity and specificity when used by case managers following

clients with mental illness in the community (Drake et al.,

1990; Drake & Wallach, 1989).

The adjustment to living subscale of the Multnomah

Community Ability Scale (MCAS; Barker, Barron,

McFarland, Bigelow, & Carnahan, 1994) was used to mea-

sure clinicians ratings of the functional level of participants,specifically their ability to money management, acceptance

of illness and independence in daily living. Ratings on the

MCAS range from 1 (almost never) to 5 (almost always).

The MCAS has good psychometric properties (Barker et

al., 1994).

Three distinct scales were used to measure different

aspects of self-report of community integration as proposed

by Aubry and Myner (1996) The Physical Integration Scale

(Segal & Aviram, 1978) a 12-item scale was used to mea-

sure the frequency of activities (0 = never, 4 = very often)outside the household over the previous month across a

variety of settings and locations (e.g., eating in a restaurant,

visiting a library, walking in the park). The Social

Integration Scale (Aubry, Tefft, & Currie, 1995) was used

to measure the frequency and nature of social contacts with

neighbors. The scale has 13 items ranging from 1 = never to

5 = frequently. The Psychological Integration Scale

(Perkins, Florin, Rich, Wandersman, & Chais, 1990) was

used to measure participants beliefs and feelings about their

neighborhood and neighbors, including their sense of emo-

tional investment, feelings of influence, and sense ofbelonging. The 12 items are rated as yes or no.

Cronbachs alpha for internal consistency for the three

scales, respectively, are reported to be .73, .87, and .71

(Aubry & Myner, 1996).

The total score of the Social Provision Scale (Cutrona

& Russell, 1987) was used to measure the participants per-

ceptions of availability of, and level of trust and comfort

with, his or her social network. Two individual questions in

the Friendship Network Scale (Humphreys & Noke, 1997)

were used to measure the participants frequency of contactwith their family and friends over the past month.

The Symptom Distress Scale was used to gather infor-

mation regarding the participants experience of being

bothered by psychiatric symptoms during the previous 7

days (0 = not at all, 5 = extremely). The scale is a combina-

tion of 15 items from the Symptom Checklist (Nguyen,

Attkisson, & Stegner, 1983) and 5 items from the anxiety

dimension of the SCL-90 (Derogatis & Cleary, 1977).

Although psychometric information is not yet available, the

SDS is currently in use as a consumer-oriented outcome

measure in a number of states (Teague, Ganju, Hornik,

Johnaon, & McKinney, 1997; Ohio Department of Mental

Health, 1998).

Finally, empowerment was measured by a scale that

combined Rosenbergs (1965) well-known 10-item Self-

Esteem Scale and Rogers, Chamberlin, Ellison, & Creans

(1997) power/powerlessness scale, using a 5-point measure-

ment (strongly agree to strongly disagree). The reliability,

construct validity, and responsiveness to mental health pop-

ulations of the Rosenberg scale has been supported empiri-cally (Arns & Linney, 1993; Morse, Calsyn, Allen,

Tempelhoff, & Smith, 1992; Van Dongen, 1996). Initial

psychometric study of the empowerment scale demonstrat-

ed adequate internal consistency and evidence for validity

(Rogers et al., 1997).

Data Analysis

The data were initially analyzed to ensure that the underly-

ing assumptions of regression analysis were met. Frequency

distributions for the scores of the dependent variabledemonstrated a range of responses and a normal distribu-

tion of quality-of-life residuals. Variable inflation values

were checked and the correlation coefficients among pre-

dictor variables were found not to be so high as to suggest

collinearity. Finally, the data were checked for non-zero

variance in each independent variable and a linear relation-

ship of the predictor variables and the outcome variable was

retained.

We selected the forced-entry, stepwise regression

model. Although we selected variables based on a theoreti-

cal framework, the analysis was still exploratory and a theo-retically based hierarchical ordering of predictor variables

was not possible. The analysis was executed in two phases.

In the first phase, a forced entry regression analysis was con-

ducted for the demographic variables. Demographic vari-

ables were forced in because of their potential as modifying

factors. Clinical, social participation, and self-measured

well-being variables were entered as three separated blocks.

The variables within each block were analyzed using the

stepwise method in order to select the predictors from each

block that significantly contributed to the regression equa-tion. When entering the variables as a block using stepwise



inclusion, the statistical program develops the most parsi-

monious model, beginning with the variable with the high-

est correlations, subsequently entering variables with the

highest partial correlations and eliminating those variables

that no longer contribute significantly to the prediction.

In the second phase of the analysis the demographic

variables were again analyzed as a block using the forced

entry method, while the predictors from phase 1 were ana-

lyzed as a block using the stepwise method. Those predic-

tors that significantly contributed to the regression equation

were selected as the best predictors of the ACT clients qual-

ity of life. This procedure allowed us to examine quality of

life from the perspective of our proposed conceptual model

while maintaining a reasonable subject-variable ratio

throughout the analysis.

Results

Scores on the independent variable showed a wide range ofresponses to ratings of subjective global well-being. Forty-

three percent of the respondents rated they were satisfied (or

more then satisfied), 28% had mixed feelings, and 29% indi-

cated that they were dissatisfied (or more) with their lives.

Table 2 presents a summary of the results of the phase

1 analysis. None of the demographic variables made a sig-

nificant contribution to the regression equation, F(7, 122)

= 1.008, ns). The clinical symptom variable as rated by the

score on the BPRS-E was the only predictor from the clin-

ical category which significantly contributed to the regres-sion equation, F(1, 121) = 24.931,p < .05. The incremen-

tal variance accounted for by the BPRS score was 16.1%.

Physical integration was the only variable from the social

participation category that significantly contributed to the

regression equation, F(1, 120) = 5.157,p < .05. The incre-

mental variance that was accounted for by the physical inte-

gration variable was 3.2%. Two variables from the subjec-

tive measures of well-being category made a significant

contribution to the regression equation. Symptom distress

had a significant incremental contribution, F(1, 119) =

30.839,p < .05. and accounted for an incremental predic-

tive variance of 15.5%. Psychological integration had a sig-

nificant incremental contribution to the equation, F(1,

118) = 4.928,p < .05. The incremental predictive variance

of the psychological integration variable was 2.4%.

Table 3 presents a summary of the phase 2 analysis.

Demographics still did not significantly contribute to the

variance of the outcome variable. Symptom distress was the

predictor that contributed most to the final equation. The

correlation coefficient between this model and the outcome

variable was .571. In this regression model, the symptom

distress variable accounted for 32.6% of the variance of theoutcome variable, F(1, 134) = 64.729, p < .05. The psy-

chological integration variable was next strongest significant

predictor. It accounted for an incremental 3.3% of the vari-

ance in the outcome variable F(1, 133) = 6.866. Physical

integration was the third strongest predictor, F(1, 132) =

5.195 accounting for 2.4% of the variance.

In summary, three variables were included in the final

regression equation as the most predictive variables (symp-

tom distress, psychological integration, and physical inte-

gration) accounting for, respectively, 32.6%, 3.3%, and2.4% of the variance. Clinical symptoms that significantly

contributed to the equation in the phase 1 analysis no

longer made a significant contribution to the final equation.

It appears that the predictive capacity of the clinical symp-

tom variable was subsumed under other significant predic-

tors in this second phase of analysis.Table 2. Summary of the Results of Phase 1 Analysis (N= 130)

Model R2 R2 change B value df Fchange Sig.*

1 .055 .055 (7, 122) 1.008 .429 (ns)

2 .216 .161 .0156 (1, 121) 24.931 .000*

3 .248 .032 .04415 (1, 120) 5.157 .025*

4 .403 .155 .0435 (1, 119) 30.879 .000*5 .427 .024 .08933 (1, 118) 4.928 .028*

*Significant level: p .05

Model 1. Predictors: (constant), age, sex, marital status, educational level, age

at the first psychiatric hospitalization, length of stay, residential status

Model 2. Predictors: (constant) age, sex, marital status, educational level, age

at the first psychiatric hospitalization, length of stay, residential status, BPRS


at the first psychiatric hospitalization, length of stay, residential status, BPRS,

physical integration


at the first psychiatric hospitalization, length of stay, residential status, BPRS,

physical integration, symptom distress


at the first psychiatric hospitalization, length of stay, residential status, BPRS,physical integration, symptom distress, psychological integration

Table 3. Summary of the Results of Phase 2 Analysis (N= 136)

Final Model

Model R2 R2 change B value df Fchange Sig.*

1 .321 .326 .0495 (1, 134) 64.729 .000*

2 .349 .033 .09677 (1, 133) 6.866 .010*

3 .369 .024 .04721 (1, 132) 5.195 .024*

Excluded

Variable Tto enter df

BPRS 1.551 (1,131)

*Significant level: p .05

Model 1. Predictors: (constant), symptom distress

Model 2. Predictors: (constant), symptom distress, psychological integration

Model 3. Predictors: (constant), symptom distress, psychological integration,physical integration



Discussion

This is an exploratory study of a predictive model of sub-

jective quality of life among persons with severe mental ill-

ness living in the community. The study participants were

all served by ACT Teams. ACT is designed to meet the

needs of individuals who have been high users of intensive

health services and caution should be exercised in general-

izing these findings across community mental health. The

study has several limitations. As we were unable to access

data related to the characteristics of the entire ACT popu-

lation served by the four teams we cannot assume that the

sample is representative. Previous studies completed on this

specific sample of ACT clients suggested that their rates of

substance use are lower then expected (Eastabrook et al.,

2003; Gerber, Krupa, Eastabrook, Gargaro, 2003), and

this may account for the poor predictive capacity of this

variable. Finally, the study uses a snapshot of subjective

quality of life at one point in time and therefore may bebiased by factors such as mood, social expectations, and

recent events that have been known to influence subjective

quality of life. Future studies that use longitudinal analysis

or time sampling strategies of subjective quality of life

would serve to reduce this bias and examine the stability of

our predictive model.

The most powerful predictor of subjective quality of

life was symptom distress that accounted for a large portion

(33%) of the variance. Studies that examine clinical symp-

toms in relation to quality of life typically use objective rat-ings by trained researchers. In our model, the predictive

capacity of clinical symptoms as rated by an outside observ-

er was appropriated by the predictive capacity of self-report-

ed symptom distress, suggesting that there is something to

be gained by including the personal experience of symp-

toms. This distinction between objective clinical measures

and subjective responses to pathology of disorder is consis-

tent with trends in quality-of-life research related to persis-

tent physical disease (Miller, 2000).

Psychiatric symptoms have been found to have a rela-

tionship to subjective quality of life for those with seriousmental illness, both in studies using quantitative research

designs (Evenson & Vieweg, 1998) and in qualitative stud-

ies examining the perspectives of recipients of community

mental health services (DeSouza, 2000; Laliberte-Rudman

et al., 2000). Although this study did not examine the par-

ticular symptom or symptom distress patterns associated

with quality of life, other studies have suggested that mood

symptoms, in particular depression and anxiety, are associ-

ated with lower subjective quality-of-life scores (Ruggeri,

Gater, Bisoffi, Barbui, & Tansell, 2002). An occupationaltherapy study by Goldberg, Brintnell, & Goldberg (2002),

found that depression accounted for more of the variance of

quality of life then engagement in meaningful activities.

In the current study psychological integration emerged

as a predictor of subjective quality of life. Although there

were no studies found that directly examined the relation-

ship between psychological integration and subjective qual-

ity of life, a common perspective in studies of community

life with serious mental illness is the extent to which indi-

viduals perceive rejection, and are marginalized in the com-

munity (Davidson, & Staynor, 1997; Prince & Prince,

2002). The variable psychological integration appears to be

similar to the theme of connecting and belonging that

emerged in a qualitative study by occupational therapists

exploring the perspectives of individuals with schizophrenia

regarding factors important to quality of life (Laliberte-

Rudman et al., 2000).

Physical integration was the only variable that emerged

as a significant predictor in the social participation catego-

ry of the quality of life model. Previous occupational thera-py research has suggested that participation in activities is

related to quality of life (Laliberte-Rudman et al., 2000).

These findings are, however, confounded by different inter-

pretations of meaningful activity, varying from participa-

tion in a range of selected activities (Goldberg, Brintell, &

Godlberg, 2002), specific activities such as horticulture

(Perrins-Margalis, Ruglectic, Schepis, Stepanski, & Walsh,

2000), to participation in valued roles (Eklund, 2001). To

date there has been little attention paid to the extent to

which actual participation in everyday community settingsaffects subjective quality of life. This is a remarkable omis-

sion in view of published research suggesting that the com-

munity lives of individuals with serious mental illness do

not demonstrate activity patterns that are consistent with

satisfaction and well-being (Krupa, McLean, Eastabrook,

Bonham, & Baksh, 2003).

Employment and social contacts did not emerge as pre-

dictive variables in the social participation category,

although they have been identified as important factors by

persons with mental illness (Laliberte-Rudman et al., 2000;

Mayers, 2000). The physical integration measure used inthis study asked participants about their participation in a

variety of community settings, including work. This broad

conceptualization of community participation may have

displaced the predictive power of employment and social

contact by including an array of contacts and activities that

more comprehensively represents the community lives of

persons with serious mental illness.

Two of three final predictors (i.e., symptom distress and

psychological integration) were variables of self-measured

well-being in the predictive model. This is consistent withprevious findings examining quality of life in severe mental



illness (Roeder-Wanner, Oliver, & Priebe, 1997; Trauer,

Duckmanton, & Chiu, 1998). This relationship between

subjective quality of life and self-rated well-being may be

influenced by methodology, because relationships might be

expected to be higher when common methods (i.e., self-

appraisal) are used to measure variables (Nunnally &

Bernstein, 1994). Fakhoury & Priebe (2002) demonstrated

that different subjective evaluation criteria may not be fully

distinct and that they may reflect the presence of a single,

underlying self-appraisal factor that requires further con-

ceptual development and research.

Our predictive model accounted for approximately

38% of the variation in subjective global quality of life. It is

likely that important variables were excluded from our qual-

ity-of-life model. For example, we did not include any data

related to finances. The study sample primarily received

fixed amounts of disability benefits with little variation in

total individual income. Studies have shown a startling lack

of relationship between economic status, self-appraisals offinancial well-being in the community, and overall subjec-

tive ratings of quality of life (Trauer et al., 1998), even

though individuals with mental illness have identified these

as important factors (Laliberte-Rudman et al., 2000,

Mayers, 2000). Conceptualizing economic well-being in a

model of subjective quality of life is an important challenge

for researchers and service providers. Its absence under-

mines our ability to recognize that the community lives of

individuals with mental illness as characterized by poverty

and systemic financial constraints that are probably deeplyembedded in the experience of subjective quality of life

(Krupa, Lagarde, & Carmichael, 2003).

Satisfaction with services was also not included,

although this may influence subjective well-being.

Fakhoury & Priebe (2002) argue that any model of subjec-

tive quality of life should include neuropsychological evalu-

ation of executive functioning. They speculate that such

psychobiological factors may predispose individuals to

inflated positive measures of subjective experience in

response to only small improvements in their life circum-

stances. Similarly, coping and adaptation have been associ-ated with the experience of subjective quality of life in

health-related conditions, perhaps by affecting health out-

comes, reframing the health experience, and readjusting

expectations (OConnor, 1993).

It may be that subjective sense of quality of life is influ-

enced by context. For example, it has been suggested that

individuals with severe mental illness will judge their quali-

ty of life relative to changes in life circumstance (Prince &

Prince, 2001). If this is the case, then conceptualizing a sub-

jective quality of life in a manner that is useful to commu-nity mental health services may involve the development of

multiple predictive models that consider changing life con-

texts. The participants in this study were largely individuals

who had been receiving ACT services in the community for

some time and this may help to explain why community

integration emerged as positive predictors. It may be, for

example, that factors such as residential status will be rela-

tively more important in the context of pending or recent

discharge from hospital. Consistent with previous findings

in the occupational therapy and community mental health

literature, this study suggests the importance of this multi-

dimensional perspective on subjective quality of life in

research and service delivery.

The importance of symptom distress as a predictor of

subjective quality of life lends support to clinical practices

that are both geared to reducing symptoms of mental illness

and working directly with the individuals appraisal and

experience of symptoms. For example, approaches focused

on influencing personal appraisal of symptoms such as

developing acceptable meanings for symptoms, anxiety andstress management techniques and developing behavioural

controls to reduce symptoms all capitalize on the clients

ability to examine and change their appraisals of experience.

The study also suggests the importance of service recip-

ients sense of belonging and integration within their com-

munities. Occupational therapists on community mental

health teams such as ACT work in natural community envi-

ronments and are in a good position to understand and

influence the processes of marginalization that leave a service

recipient feeling disconnected. The study suggests that occu-pational therapists examine to the extent to which individu-

als experience their activities and efforts influential within

the context of their local communities. For example, thera-

pists may direct interventions toward the persons experience

of discrimination or disadvantage, the internalized sense of

stigma, or towards the development of occupational partici-

pation that is meaningful in the community context.

Occupational therapists are also in a good position to

attend to the extent to which service recipients are actually

engaging in the activities, places, and situations that consti-

tute community life, a factor that appears to be related tosubjective quality of life. Although the specific nature of

occupational engagement is highly individual, occupational

therapy research has highlighted the importance of occupa-

tional participation that is characterized by personal mean-

ing, purpose, providing connections with others, and facil-

itating a sense of personal control as particularly salient in

promoting subjective quality of life in the context of severe

mental illness (Laliberte-Rudman et al., 2000).

Therapists are encouraged to use caution in their appli-

cation of the model. Although this predictive model con-tributes to our understanding of subjective quality of life in



severe mental illness, a great deal of the variance of the con-

struct was not accounted for by the model. Perhaps one of

the most important benefits of such predictive models is the

promotion of well-developed theoretical frameworks to

explain potential relationships between therapeutic inter-

ventions and approaches and complex outcomes. It is

hoped that the model will serve this function and facilitate

theory-based practice and research related to subjective

quality of life in occupational therapy.

Conclusions

In this study the predictors that were associated with sub-

jective quality of life of persons with severe mental illness

living in the community were symptom distress, psycho-

logical integration, and physical integration. The three pre-

dictor variables together explained 38.3% of the variance of

subjective quality of life. The study contributes to our

understanding of construct of subjective quality of life by

developing a model that captured the complexity of the

construct, including its relationship to aspects of daily occu-

pation. The study suggests that occupational therapists

should attend to the clients subjective experience of symp-

toms, sense of community belonging and community par-

ticipation to influence quality of life.

Acknowledgments

This project was funded by the Ontario Ministry of Health

and Long-Term Care in collaboration with the Ontario

Mental Health Foundation, the Centre for Addictions and

Mental Health, and the Canadian Mental Health

Association-Ontario. The authors thank the two anony-

mous reviewers for their feedback and suggestions.

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