Springer 2006

Quality of Life Research (2006) 15: 515–526 DOI 10.1007/s11136-005-2808-9

Determinants of changes in perceived quality of life in the course of schizophrenia Michael Ritsner1,2, Anatoly Gibel1 & Yael Ratner1 1 Sha’ar Menashe Mental Health Center, Mobile Post Hefer 38814, Hadera, Israel (E-mail: ritsner@ shaar-menashe.org.il); 2Bruce Rappaport Faculty of Medicine, Technion, Haifa, Israel Accepted in revised form 4 September 2005

Abstract This study aimed to identify factors that influence changes in satisfaction with quality of life (QOL) of schizophrenia patients. Baseline and follow up data for 148 schizophrenia patients were obtained at hospital admission and 16 months later. Relationships between changes over time in the general QOL index, and various factors were investigated using factor, multiple regression, and partial correlation analyses. Findings indicate that baseline levels of activation symptoms, emotional distress, task oriented coping, selfesteem and friend support together explain 41% of the variability in the general QOL index 16 months later. Changes in the general QOL of schizophrenia patients over time is associated with anergia, and paranoid symptoms, emotional distress, side effects, self-esteem, emotion and avoidance related coping styles, expressed emotion, and other social support. Determinants of change in QOL of patients were different being in hospital or out of hospital in the real world. No significant association of age, education, and follow up duration, with general QOL. Based on obtained data three types of overlapping factors were defined: (1) distressing, and protective; (2) primary and secondary; and (3) factors that remained constant or changed over time. Presented data are discussed within the framework of the Distress/Protection model of QOL. The conceptualization of three types of factors influencing QOL outcomes in this model demonstrates their predictive value, and may assist investigators and mental health workers in the interpretation of QOL data that may be used to improve patients’ QOL outcomes. Key words: Distress/Protection model, Factors, psychosocial, Follow up study, Predictors, Psychopathology, Quality of life, Schizophrenia

Introduction Health-related quality of life (QOL) has become an important outcome measure in the treatment of psychiatric disorders. Most conceptualizations of QOL include dimensions of physical functioning, social functioning, role functioning, mental health and general health perceptions, with important concepts such as energy, fatigue, pain, and cognitive functioning included in these broader categories [1]. These physical, psychological, and social

domains of health, are seen as distinct areas that are influenced by a person’s experiences, beliefs, expectations, and perceptions [2]. While QOL is a heterogeneous concept, there is no universal operational definition of QOL. Patients’ statements on satisfaction with major life domains of daily functioning are relevant indicators of subjective QOL [3–4]. Comprehensive reviews of empirical QOL studies in schizophrenia were recently published [5–9]. Briefly, satisfaction of schizophrenia patients

516 with QOL is clearly correlated with a number of distressing factors, including expression of depressive and negative symptoms [10–14], and side effects of antipsychotic agents [12, 15–17]. Severity of schizophrenia symptoms explained from 32% [18] to 19% [19] and 10.1% [17] of variability in subjective QOL. Self-reported distress caused by neuroleptic side-effects were among other indicators of QOL [17–18]. Various protective factors have been identified and have been found to play a significant role in QOL outcomes, among these are self-esteem, self-efficacy, coping with stressful situations, personality traits, expressed emotion and social support [10, 14, 20–23]. The contribution of protective (or stress process related) factors explained 20.9% of the variability in subjective QOL [17]. The relationship between changes over time in distress and protective factors in schizophrenia patients and the level of QOL remains unclear. Reported longitudinal data demonstrated that a change in global QOL scores was inversely correlated with a change in depression severity [4, 24–27]. Bow-Thomas and associates (1999) found that psychosis and paranoia components (Brief Psychiatric Rating Scale, BPRS) are important predictors of QOL at stabilization (but not during acute exacerbation). Huppert et al. [28] followed 53 stabilized outpatients diagnosed with schizophrenia or schizoaffective disorder every three months for a period of one year. They found that changes in anxiety, as rated using the BPRS, were inversely associated with QOL ratings, and the relationships were stronger than relationships of QOL with any other core symptoms of schizophrenia, including depression. Finally, in contrast to cross-sectional data, several researchers found no significant variation between severity of symptoms and subjective QOL [29–31]. Malla et al. [31] showed that significant improvement in most dimensions of QOL at one year were generally independent of changes in symptoms. There are several possible limitations in the above-mentioned longitudinal studies. First, narrow focus relating life dissatisfaction primarily to symptom severity did not include evaluation of protective factors such as self-constructs, coping styles, and social support, and second, sample sizes of patients studied were small.

There is no exclusive model for interpretation of QOL outcomes. Several conceptual models have been proposed to interpret QOL outcomes in schizophrenia. For example, according to the ‘basic clinical’ model [32], QOL is one’s perception of the outcome of interaction between psychotic symptom severity, side effects, including subjective responses to antipsychotic agents, and the level of psychosocial performance. QOL models, such as the vulnerability-stress-coping model [33], and a mediational model [34–35] underscore the importance of psychological processes in the QOL construct. However, these models are generally descriptive rather than analytically predictive, and need further development, testing and validation. Based on cross-sectional multidimensional data obtained for patients with major psychoses the Distress/Protection (DP) model factors influencing QOL was conceptualized [10]. This model postulated that subjective QOL is an outcome of the interaction of an array of distress factors, on the one hand, and protective factors, on the other, and suggests that satisfaction with QOL decreases if distress/clinical factors outweigh protective factors, and vice versa. The DP model was applied for analysis of relationships between QOL levels and major psychoses [10, 36], schizophrenia [37], side effects of antipsychotic agents [17], coping styles [22], temperament factors [38], suicide behavior [39], and sleep quality [40]. The purpose of this study was: (a) to explore the relationships between changes over time in general QOL and related variables, (b) to determine predictors of changes in satisfaction with QOL from baseline through the end of study, and (c) to integrate types of QOL related factors into the DP model.

Method Data collection The study sample was drawn from a database of patients participating in the Sha’ar Menashe Longitudinal Study of Quality of Life. A detailed description of the design, data collection, measures, cross-sectional and longitudinal findings of this study has been reported elsewhere [10, 37]. Briefly, data concerning adult schizophrenia

517 patients was collected at two time points: (1) initial assessment was obtained on admission to hospital settings of one center (Sha’ar Menashe Mental Health Center; at exacerbation phase), and (2) follow up assessment was obtained at stabilization phase (defined as a clinically stable period that lasted at least 6 months, when each positive PANSS item scored <4), but no less than 12 months after the initial assessment. Patients with comorbid mental retardation, organic brain diseases, severe physical disorders, drug/alcohol abuse, and those with low comprehension skills were not enrolled. During this naturalistic study all patients were treated with a variety of antipsychotic medications (conventional, atypical neuroleptics, and combination) and additional medications (benzodiazepines, antidepressants, and mood stabilizers) as clinically indicated. They did not take place in special rehab programs. The study was approved by the Sha’ar Menashe Internal Review Board and the Israel Ministry of Health. All participants signed informed consent for participation in the study, after receiving a comprehensive explanation of study procedures. Participants For the present study data at baseline and at the last follow up assessment for 148 schizophrenia patients were used. The study sample was 81.8% male (N=121), with mean age 38.2 years (SD=9.5, range 18–60), 97 (65.5%) people were single, 25 (16.9%) were married, and the rest 26 (17.6%) were divorced, separated or widowed. Mean extent of education was 10.2 years (SD=2.7); 84 (56.8%) lived independently, 43 (29.0%) in a group home and 21(14.2%) with their families. Ninety six patients (64.5%) were unemployed. Mean age of applying for psychiatric care was 22.9 years (SD=7.1), mean duration of disorder was 15.0 years (SD=9.1); mean number of hospitalizations was 7.8 (SD=4.5). One hundred and four patients presented with paranoid type, 27 with residual type, 8 with disorganized type, 8 with undifferentiated type, and 1 with catatonic type of schizophrenia. The patients were followed up for a mean of 16.7 (SD=4.8) months after baseline assessment. At follow up, 59 patients were reassessed during the same hospitalization, 48 – at discharge from an additional

admission, and 41 – in outpatient clinics. Patients were treated with a variety of antipsychotic medications (61% conventional, 19% atypical neuroleptics, and 20% combination) and additional medications (26% benzodiazepines, 15% antidepressants, and 15% mood stabilizers) as clinically indicated. Patients treated with conventional antipsychotic agents had been treated continuously for at least 28.7 months (SD=13.7), whereas the mean duration of administration of atypical drugs was 21.9 months (SD=6.8). We did not find any between group differences in dosage of adjunctive antidepressants, anxiolytics or mood stabilizers (data not shown). All patients were physically healthy, with recent normal physical examinations, and had normal blood and urine laboratory test results. During the follow-up period these 148 patients were characterized by a reduction in severity of paranoid and depressive symptoms, emotional distress, and involuntary movements, improvement in two QOL domains (subjective feelings and leisure activities), rater-observed insight, emotional coping, self-esteem, expressed emotions of patients’ relatives, perceived support from family and significant others. However, ratings of negative and general psychopathology, anergia, thought, and activation symptoms, self-reported insight, adverse events, somatic distress and friend support scores did not change significantly during the follow-up period (see details: [37]).

Measures Diagnosis was based on a face-to-face interview, medical records, and a consensus between two senior psychiatrists. Background and demographic characteristics, family and personal psychiatric history, details of the present illness, medications, general medical history and current laboratory tests were also evaluated. The Quality of Life Enjoyment and Satisfaction Questionnaire was administered to assess perceived QOL. It is a self-report questionnaire; responses are scored on a 1- to 5-point scale, with higher scores indicating better QOL (Q-LES-Q), [41]. The Q-LES-Q was validated and shows a good capacity to evaluate QOL of the patients with major psychoses [42]. In the current study,

518 we used the general QOL index (Cronbach’s a=0.93). Assessment of distressing factors was done using the following rating scales and questionnaires. The Positive and Negative Syndrome Scale (PANSS) was used for clinical assessments. Two symptom models were constructed from the 30 PANSS items: a three-factor model was established with positive, negative, and general psychopathological scale scores, and a five-factor model with anergia, thought, activation, paranoid, and depression factor scores [43]. For assessment of insight for illness, the Insight and Treatment Attitudes Questionnaire (ITAQ) [44] and the Insight Self-report Scale (IS), [45] were employed. The ITAQ is a rater-observed scale, total ITAQ score is used as a global measure of insight and can range from 0 to 22. High scores indicate good insight. The Insight Self-report Scale is an 8-item self-report inventory developed to measure three aspects of subjective experience of insight: awareness of illness, need for treatment and attribution (re-labeling) of symptoms. Low scores indicate poor insight. The presence and severity of adverse effects of medication as well as psychological responses to them were measured with the Abnormal Involuntary Movement Scale (AIMS), [46] and Distress Scale for Adverse Symptoms (DSAS), [17]. Three DSAS indices related to adverse events were computed: Number of Adverse Symptoms (NAS), Mental Distress Index (MDI), and Somatic Distress Index (SDI). Higher index scores indicate a greater number of adverse events (NAS) and higher distress levels are attributed to a given side effect (MDI, SDI). Inter-rater reliability scores for these rating scales were established by calculating intraclass correlation coefficients (ICC) in 22 patients who were assessed by two raters. All ICCs for PANSS, AIMS, ITAQ and DSAS dimensions were significant (p<0.001) and varied between 0.78 and 0.95. The Talbieh Brief Distress Inventory (TBDI) is a 24-item self-report instrument used to measure emotional distress [42, 47]. Responses are scored on a 0 to 4-point scale, with higher scores indicating greater intensity of distress, and particular symptom severity. A TBDI index that is the average of all 24 items was computed. The Somatization Scale is derived from the Brief Symptom Inventory [48]. The BSI-somatization scale

(BSI-S) reflects distress arising from perceptions of bodily dysfunction (somatic distress). Protective (or stress process related, SPR) factors were examined using the following self-report instruments. Task-, emotion- and avoidance-oriented coping styles were evaluated with the Coping Inventory for Stressful Situations (CISS) [49]. The General Self-Efficacy Scale is a 10-item standard abridged version of the GSES for evaluating a sense of personal competence in stressful situations [50]. The Rosenberg Self-Esteem scale is a wellknown 10-item self-report questionnaire for measuring self-esteem and self-regard (RSES) [51]. The Expressed Emotion Scale is a 38-item questionnaire designed to assess the levels of criticism, hostility, and emotional over-involvement expressed by a psychiatric patient’s relative, as perceived by the patient (EES), [52]. The Multidimensional Scale of Perceived Social Support (MSPSS), [53] was used as a measure of a social support. The MSPSS is a psychometric instrument used to assess emotional support and the degree of satisfaction with perceived social support from family, friends and significant others. For the present sample, self-report instruments demonstrated high reliability (Cronbach’s a): IS (0.82), DSAS indices (0.79–0.87), TBDI index (0.92), BSI-S (0.80), CISS dimensions (0.77–0.89), GSES (0.88), RSES (0.80), EES (0.75), and MSPSS (0.91). Data analysis In the present study, factor, multiple regression and partial correlation analyses were applied. An exploratory factor analysis was performed to identify the main factors associated with changes in the general QOL index. The principle axis method of factor analysis with varimax rotated factor matrix was performed to identify the factors associated with the changes in QOL index. The eigenvalues are used to determine how many factors to retain. One rule-of-thumb is to retain those factors whose eigenvalues are greater than one. Variables with an absolute loading greater than the amount set in the minimum loading option (>0.3) were selected. Multiple regression analysis was employed for two predictions: (a) for changes in general QOL scores during the follow up period from changes in

519 independent variables during the same period, and (b) general QOL index scores at follow up from the set of independent variables at initial examination. The model¢s predictions were examined using a series of regression analyses with step-wise backward selection of the following independent variables: PANSS (anergia, thought, activation, paranoid, and depression factors), IS subscales (‘‘relabel’’, awareness, needs), AIMS, DSAS indices, TBDI index, BSI-S, CISS, GSES, RSES, EES and MSPSS (family, friends, others support scores). In the final step of analysis three variables (age, education, and follow up duration) were controlled. Partial correlation analysis was applied in order to indicate the primary and secondary QOL related factors. Pearson correlation coefficients were calculated between changes in the QOL ratings and related factors over time. Associations of QOL index scores with gender, marital status, antipsychotic agents and changes in treatment setting was tested with an analysis of variance (ANOVA). The NCSS-2000 PC program was used for all analyses [54]. Mean values with standard deviation (SD) are presented. Significance of changes over time in the key variables between baseline and third evaluations was tested using paired t-test.

Results

the follow up period had similar QOL index scores both at initial (F=1.84, df=2,148, p=0.16), and at follow up (F=0.31, df=2,148, p=0.73) assessments. General QOL levels did not relate to gender (F=0.01, df=1,148, p=0.99), length of follow up examination (F=1.21, df=1,148, p=0.27), and marital status (F=0.34, df=2,148, p=0.71 for initial examinations and F=0.01, df=2,148, p=0.99 for follow up examination). The main factors To identify the main factors associated with changes in the general QOL index, we performed an exploratory factor analysis. Variables with an absolute loading greater than the amount set in the minimum loading option (>0.3) were selected (17 of the 30 initial variables were removed to avoid augmenting scores). Three factors were identified on the highest eigenvalues (2.34, 2.00, and 1.58, respectively; see Table 1). The first factor with harmful effect on QOL included only severity of symptoms (‘distress factor’), the second with protective effect was constructed using coping styles and social support (‘coping factor’), and the third with also protective effect included self-efficacy, self-esteem (all positive loadings), and emotional distress (with negative loading) (‘personality related factor’), and the general QOL index. Correspondingly, the factors accounted for 39.6%, 33.8%, and 26.6% of the total variance among the 13 measures.

Changes in general QOL Predictors Satisfaction with general QOL appears to be slightly, but statistically significantly improved during the follow up period: from 3.4±0.7 to 3.5±0.7 (95% confidential interval for changes ranged 0.02–0.28, paired t=2.3, p<0.05). Correlation coefficients between changes in the QOL index and age, length of education, age of illness onset, number of admissions, duration of disorder and of last hospitalization were not significant (all r<0.15, p>0.05). ANOVA shows that changes in QOL index scores during the follow up period did not differ between patients treated with conventional, atypical and combined antipsychotics (F=0.45, df=2,148, p=0.64). Likewise, patients who remained in the same hospitalization, were readmitted or treated in outpatient clinics during

The first regression model predicts the changes in general QOL index scores over time from changes in values of key variables between two assessments selected through step-wise procedure. Table 2 presents three obtained regression models to predict changes in general QOL scores during follow up of patients who were reassessed during the same hospitalization (‘hospitalized’), at discharge from an additional admission (‘discharged’), and in outpatient clinic (‘outpatients’). As can be seen, fluctuations in satisfaction with QOL among these subgroups were influenced by different patterns of predictors that accounted for 30–67% of change in variance. This model suggests that a reduction in paranoid severity, and emotional distress together

520 Table 1. Eigenvectors, factor loadings and communalities of two factors after rotation of changes in variable values over time Change in variables over time

Factor 1 (eigenvalue=2.34) ‘distress factor’

Factor 2 (eigenvalue=2.00) ‘coping factor’

Factor 3 (eigenvalue=1.58) ‘personality related factor’

Factor loadingsa Communalities Factor loadingsa Communalities Factor loadingsa Communalities Anergia factorb Thought factorb Activation factorb Paranoid factorb Depression factorb Task related copingc Emotion related copingc Avoidance related copingc Social supportd Self-efficacye Self-esteemf Emotional distressg General QOL indexh a

0.5539 0.7046 0.7698 0.8201 0.4321 )0.1244 0.1058 )0.0951 0.0248 )0.1069 )0.0785 0.1533 )0.0977

0.3068 0.4965 0.5926 0.6726 0.1867 0.0154 0.0112 0.0090 0.0006 0.0114 0.0061 0.0235 0.0095

0.0018 0.0033 0.1104 0.0556 0.0882 )0.8219 )0.6661 )0.8116 )0.3012 )0.2786 )0.1054 )0.0499 )0.1258

)0.0764 )0.0435 )0.1113 )0.0867 )0.2251 0.2650 )0.1326 0.1866 0.2103 0.5781 0.5384 )0.5475 0.6380

0.0000 0.0000 0.0121 0.0030 0.0077 0.6755 0.4437 0.6587 0.0907 0.0776 0.0111 0.0024 0.0158

0.0058 0.0018 0.0124 0.0075 0.0506 0.0702 0.0176 0.0348 0.0442 0.3342 0.2899 0.2997 0.4071

Variables with an absolute loading greater than the amount set in the minimum loading option (>0.30) were selected. PANSS; cCISS; dMSPSS; eGSES; fRSES; gTBDI; hQ-LES-Q.

b

Table 2. Summary of multiple regression analysis to predict changes in general QOL scores during follow up of patients who were reassessed during the same hospitalization, at discharge from an additional admission, and in outpatient clinic p

Partial R2 (%)

Inpatients (N=59) Model’s properties: R2=0.52, Adj.R2=0.45, F=6.8, df=7,59; p<0.001 Paranoid factor )0.30 2.7 Emotional distress )0.41 3.4 Self-esteem 0.27 2.4 Other support 0.25 2.3 Age (years) 0.12 1.1 Education (years) )0.04 0.3 Follow up duration (months) 0.08 0.9

0.009 0.001 0.017 0.023 0.25 0.74 0.39

12.7 18.5 10.8 9.9 2.6 0.2 1.4

Patients were reassessed at discharge from an additional admission (N=48) Model’s properties: R2=0.30, Adj.R2=0.22, F=3.6, df=5,48; p=0.008 Anergia factor )0.25 2.1 Emotional distress )0.49 3.7 Age (years) )0.01 0.07 Education (years) )0.18 1.4 Follow up duration (months) 0.06 0.48

0.049 0.001 0.94 0.17 0.63

8.5 25.0 0.01 0.4 0.5

Outpatients (N=41) Model’s properties: R2=0.67, Adj.R2=0.56, F=6.1, df=8,41; p<0.001 Anergia factor )0.38 2.8 Side effects (DSAS) )0.49 4.1 Emotional related coping )0.47 3.1 Avoidance related coping 0.68 4.4 Expressed emotion 0.33 2.9 Age (years) 0.15 1.0 Education (years) 0.09 0.6 Follow up duration (months) )0.02 0.2

0.009 0.001 0.005 0.001 0.008 0.29 0.55 0.87

22.9 38.3 25.9 42.0 23.3 0.03 0.01 0.001

Change in independent variables

b

with increasing self-esteem and other support ratings were associated with improvement in the general QOL index among hospitalized patients

t-value

during follow-up. A decrease in anergia factor and emotional distress scores accounts for 8.5% and 25% of better perception of subjective QOL of

521 patients discharged at follow up assessment. For outpatient group regression analysis indicates four negative (anergia, distress, side effects, and emotional related coping style) and two positive (avoidance coping, expressed emotion) predictors associated with improvement of QOL over study time. The second regression model predicts QOL index scores at follow up from a selected set of key variables at the initial examination. This model indicates that ratings at the initial assessment of the activation factor (b =0.17, t=2.4, p<0.05, partial R2=4.1%), emotional distress (b=)0.36, t=4.2, p<0.001, partial R2=11.6%), task coping task coping (b =0.14, t=2.0, p<0.05, partial R2=2.8%) and self-esteem (b =0.16, t=2.0, p<0.05, partial R2=2.7%) accounted for 41% of the general QOL scores at the follow up examination (model’s properties: R2=0.41, Adj. R2=0.37, F=10.7, df=9,148; p<0.0001). Particularly, emotional distress (accounting for 11.6% of the variance) inversely associated with improvement of the QOL index over time, while the impact of the depression factor did not reach a significant level (b=)0.14, t=1.9, p>0.05, partial R2=2.7%). Higher activation factors, task coping, self-esteem and friend support predicted better satisfaction with life quality after 16 months (they account for 4.1%, 2.8%, 2.7% and 2.9% of QOL index scores at follow up examination, respectively). Age, education and follow-up duration did not influence on changes in general QOL. Primary and secondary factors In order to indicate the primary and secondary QOL related factors it was proposed that when changes in secondary factors are removed from the correlation matrix, the partial correlation between changes in both the primary factor and QOL index remain statistically significant. Partial correlation analysis is summarized in Table 3. As can be seen, only correlations between fluctuations in QOL and emotional (r=)0.42, p<0.001) and somatic distress (r=)0.34, p<0.001) remained statistically significant when the effects of all symptoms, medication side effects, insight and SPR factors were partialled out. The correlations of QOL with paranoid and depression symptoms lost their sig-

nificance after adjusting for adverse effects, distress, coping styles and self-construct scores. The relationships between changes in awareness and in QOL index scores also did not remain significant when intervening variables such as emotional distress, coping and self-constructs were controlled. Emotional distress and expressed emotion showed their influence on correlation between adverse effects and the QOL index. In addition, regression analysis also revealed findings regarding the contribution of primary and secondary factors to changes in quality of life (Table 2). Among primary factors, change in selfesteem scores account for 10.8%, in other support score account for 9.9%, in emotion coping style accounted for 25.9%, and in expressed emotion accounted for 23.3% of the variance in change general QOL index scores. Secondary factors such as paranoid and anergia ratings accounted for 8.5–22.9%, emotional distress accounted for 18.5% and 25%, side effects accounted for 38.3% of the variance in changes in general QOL domain scores during the follow up period.

Discussion Overall, obtained findings indicate that (a) baseline levels of activation symptoms, emotional distress, task oriented coping, self-esteem and friend support together explain 41% of the variability in the general QOL index 16 months later; (b) changes in the general QOL of schizophrenia patients over time is associated with anergia, and paranoid symptoms, emotional distress, side effects, self-esteem, coping styles, expressed emotion, and other social support; (c) determinants of change in QOL were different being in hospital or out of hospital in the real world; and (d) no significant association of age, education, and follow up duration, with general QOL. This study, based on repeated measures, suggests that at least three overlapping types of factors should be considered in the Distress/ Protection model for the interpretation of QOL outcomes (see Figure 1). The first type of factors was derived by analysis on both cross-sectional [10, 38–40] and current longitudinal data. They include opposite factors with distressing (severity of symptoms, distress, side effects, insight, poor

)0.19*

)0.18* )0.30*** )0.28*** )0.23** )0.36*** )0.33*** )0.21*

)0.11 )0.33*** )0.12

)0.39*** )0.33*** )0.24** )0.40*** )0.34*** )0.17* )0.40*** )0.31*** )0.18* )0.40*** )0.35*** ()0.18*) ()0.24**) ()0.42***) ()0.34***)

)0.18* )0.09

)0.24** )0.20* )0.14

)0.12 )0.21* )0.13 ()0.21*) ()0.19*) ()0.20*)

Paranoid symptomsa Depressiona Awarenessb Adverse effectsd: NAS MDI Emotional distressf Somatic distressg

Notes: aPANSS – Positive and Negative Syndromes Scale; bIS – Insight Self-report Scale; cITAQ – Insight and Treatment Attitudes Questionnaire; dDSAS-Distress Scale for Adverse Symptoms (NAS – Number Adverse Symptoms; MDI – Mental Distress Index); eAbnormal Involuntary Movement Scale (AIMS); fTBDI – Talbieh Brief Distress Inventory; gBSI – Brief Symptom Inventory; hISS – Coping Inventory for Stressful Situations; iCSES – General Self-Efficacy Scale; jRSES – Rosenberg Self-Esteem Scale; kEES – Expressed Emotion Scale; lMSPSS – Multidimensional Scale of Perceived Social Support. r – correlation coefficient. Significance: *p<0.05, **p<0.01, ***p<0.001.

)0.20* )0.42*** )0.34*** )0.16 )0.44*** )0.35***

)0.21* )0.19* )0.17* )0.20* )0.21* )0.12* )0.18* )0.16 )0.16 )0.11 )0.06 )0.14 )0.13 )0.17* )0.14 )0.20* )0.21* )0.12 )0.20* )0.20* )0.15 )0.13 )0.12 )0.12 )0.14 )0.08 )0.18*

Self-constructsi, Coping stylesh Somatic distressg Emotional distressf Adverse effectsd,e c

Insightb, Depressiona Paranoida

Partial correlation coefficients with changes in QOL index after adjusting for: Negative indicators of QOL (r before adjusting for variables)

Table 3. Pearson’s correlations between changes in QOL index and changes in selected indicators after adjusting for studied variables

j

Expressed emotionk

Social supportl

522 sleep quality, emotion coping, repeated suicide attempts, harm avoidance) and protective (task and avoidance coping styles, social support, selfefficacy, self-esteem) effects on QOL level. The protective factors are considered important factors in individual responses to stressful life events [55, 56] while potentially mediating the effects of stressors on QOL outcomes [35]. Since these factors included variables that are closely associated with a construct of satisfaction with QOL it might also be defined as a ‘primary factor’. Contribution of symptom severity and protective factors was similar for both longitudinal and cross-sectional study designs [17–19]. Next type of factors included primary and secondary factors. Primary factors are those usually considered personal characteristics, such as selfesteem, self-efficacy, coping styles, expressed emotion, and perceived social support. These factors are defined as the closest to the subjective well being construct [57] and they determine subjective QOL of subjects and whether or not he is ill, while secondary factors are directly related to the illness and include clinical symptoms, emotional and somatic distress, medication side effects and insight to illness. We believe that secondary factors influence subjective QOL via primary factors. According regression analysis contribution of primary factors (self-esteem, other support, emotion coping, expressed emotion) account for 10–26%, whereas secondary factors (paranoid and anergia symptoms, emotional distress, side effects) ratings accounted for 8–38% of the variance in changes in general QOL domain scores during the follow up period. In agreement with previous longitudinal studies [4, 24, 28, 58] we found positive correlation between improvements in general QOL and a reduction in severity of depressive and paranoid symptoms. However, in previous studies the contribution of these symptoms to fluctuations of QOL ratings was overestimated because it did not account for the influence of additional QOL related factors. Indeed, when ratings of side effects, distress, coping styles, and self-constructs were partialled out, the correlations of change in the general QOL index with changes in severity of paranoid and depression symptoms lost their significance. These results suggest that no symptom dimensions are closely associated with QOL

523

Figure 1. The Distress/Protection model of quality of life in schizophrenia.

constructs and that there is a confounding relationship between measures of symptoms, adverse effects of antipsychotic agents, distress and coping mechanisms [17, 55]. This study found that reductions in both self-reported distress scores is strongly associated with improvement in perceived QOL that support cross-sectional findings [10, 17, 59]. As expected, a reduction in the severity of adverse or side effects (NAS, MDI) during the follow-up period was correlated with improvement in general QOL, supporting findings from crosssectional investigations [15, 17, 60–61]. Partial correlation analysis showed that a change in the Mental Distress Index (MDI) attributed to medication side effects was associated with changes in general QOL scores rather than with changes in the Number of Adverse Symptoms (NAS). Contradictory findings have been previously reported regarding the relationship between insight and subjective QOL. While most researchers did not find an association between insight and QOL scores [10, 62–64], others report that insight is positively [65] or inversely [66] associated with

QOL. Consistent with most previous cross-sectional findings we found no significant association between rater-assessed insight and fluctuations in QOL over time. However, when a self-report scale was used, a slight negative correlation between awareness and the general QOL index was revealed. More precise analysis of insight and, in particular, self-reported insight is important in clarifying the factors involved in QOL in schizophrenia. Third type, we sought QOL related factors that changed or did not, over time. A different sample or a longer follow up period may reveal changeability in this type of QOL related factors. In the present study, a change in general QOL during a follow-up period does not seem to be associated with change in the treatment setting or the type of antipsychotic agents used. Finally, consistent with several cross-sectional results [28, 68–70], an association between changes in general QOL during a follow-up period and sociodemographic (sex, age, marital status, length of education) and background (age of illness onset,

524 number of admissions, duration of disorder and of last hospitalization) variables failed to reach significant levels. A longer follow up period may reveal significant associations of sociodemographic and background variables with QOL. There are several limitations in evaluating these results. First, in the current study we did not analyze the effects of specific stressful life events and daily hassles. Second, because the follow up data were received partly from inpatients, we cannot generalize our findings to patients in a more stable outpatient phase where a study of these relationships would be even more useful. Findings of this study have important clinical implications. They emphasize the necessity of understanding and treating not only the core symptoms of schizophrenia but also the primary factors influencing changes in QOL over time. In order to adjust the clinician’s goals to the patients’ subjective needs, our intervention and rehabilitation programs should be directed to promote feelings of self efficacy, self-esteem, social support, and utilization of adjusting and/or coping strategies. Future studies should examine the effect of cognitive and emotional impairment on the appraisal of perceived quality of life in schizophrenia.

Acknowledgements We are grateful to Ms. Rena Kurs for editing the manuscript. We also thank our research assistant Ms. Michal Z’ada.

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Address for correspondence: M. Ritsner, Mobile Post Hefer 38814, Sha’ar Menashe Mental Health Center, Hadera, Israel Phone: +972-4-6278750; Fax: +972-4-6278045 E-mail: [email protected]