بهزیستی ذهنی، امید و نیازهای افراد با بیماری روانی جدی

Abstract Hope, as a basic resource in human life, may affect individuals' perceptions of subjective well-being (SWB). Further, understanding individuals' needs is essential to improving their SWB. It is unclear how the impact of hope on SWB may be mediated by needs. The current study aimed to examine a mediation model for the relation between hope and SWB among individuals with serious mental illness (SMI). Face-to-face structured interviews were conducted with 172 individuals with SMI. Instruments included the Personal Wellbeing Index, the Hope Scale, and the Camberwell Assessment of Needs. Hope and needs were predictive of 40% of the variability in SWB, with hope being a stronger predictor. Having no needs was positively predictive of SWB, while total number of needs was negatively predictive of SWB. Path analyses revealed a strong direct effect of hope on SWB and a weaker, though still strong, indirect effect mediated through needs. The results underscore the importance of hope in improving SWB and, consequently, enhancing the recovery process of individuals with SMI. Therefore, mental health services should focus on hope-building.

. Introduction During the last three decades, we have witnessed an increased interest in the field of quality of life (QoL) in medicine in general and in relation to mental disorders in particular (Bobes and Gonzalez, 1997 and World Health Organization, 2005). While in previous years the primary goal of mental health (MH) treatment was to control disease symptoms, at present the concept of outcome in psychiatry has been widened to include strategies for improving QoL (Ponizovsky et al., 2003, Bobes et al., 2005 and Kao et al., 2011). Researchers have asserted that QoL is a complex and intricate concept (Thorup et al., 2010). In the mental health field, most researchers have employed the definition of ‘health-related quality of life’ proposed by the World Health Organization Quality of Life (WHOQOL) Group: “an individual's perception of one's position in life in relation to goals, expectations, standards, and concerns in context of the culture and values systems in which one lives” (World Health Organization, 1998). Additional definitions of QoL have differentiated between objective and subjective QoL measures. However, among QoL theorist and researchers, greater importance is currently being placed on subjective measures, stressing that the ultimate test of a life worth living is how people feel about their QoL (Schalock, 1997). The focus of the current study is subjective QoL, or subjective well-being (SWB), which is defined as a normally positive state of mind that involves the whole life experience (Cummins et al., 2010). The terms QoL and SWB have often been used interchangeably (Keyes et al., 2002 and Ring et al., 2007). However, these are empirically distinct concepts, as SWB assesses QoL mainly through measures of happiness and/or satisfaction with life (Diener, 2000) while QoL may also include objective measures. SWB is a relatively stable mood-state for an individual. Normal levels of well-being are usually maintained, even in adverse conditions, through a psychological/neurological system of SWB homeostasis (Cummins, 2000 and Cummins et al., 2010). According to Cummins et al. (2010), the average set-point of SWB homeostasis among Western populations is about 75 on a 100-point scale. However, SWB is not absolute. If the level of challenge to SWB becomes too great, homeostasis fails and SWB drops below the set-point range (Cummins et al., 2010). When this occurs, normal feelings of positive well-being disappear and are replaced by depression (Cummins et al., 2007). Most studies in the mental health field have utilized a broad QoL terminology or the term ‘subjective QoL,’ rather than the more specific term of SWB. These studies have shown that psychiatric patients, especially those with schizophrenia, have low levels of subjective QoL in comparison to the general population (Bengtsson-Tops and Hansson, 1999 and Ponizovsky et al., 2003). The results of a fairly recent meta-analysis on QoL indicate that psychiatric symptoms have only a small relationship with QoL in schizophrenia (Eack and Newhill, 2007). The psychosocial (secondary) effects of mental illness (e.g., social support, self-esteem, self-efficacy) were found to have a greater impact on QoL (Ritsner, 2003 and Eack and Newhill, 2007). Studies have examined several psychosocial variables which may predict QoL in MH. For example, Thorup et al. (2010) found significant correlations between self-esteem, affective balance, and psychopathology, indicating that QoL was more closely related to the “inner world” than to material or outside issues, such as jobs and living situations. Other empirical studies have shown that such traits as mastery, autonomy, locus of control, sense of coherence in life, self-efficacy, and self-esteem are important predictors of SWB (Zissi et al., 1998, Ritsner et al., 2000 and Hansson and Björkman, 2007). An additional psychosocial variable that has an important influence on QoL is hope. 1.1. Hope and subjective well-being Hope is considered a basic personality trait (Snyder et al., 1991) and resource in human life (Kylma, 2005), as well as a healing force promoting well-being (Holdcraft and Williamson, 1991). Hope has been found to contribute to therapeutic efficacy and is consistently identified as an essential element for recovery from MI (Corrigan et al., 2004, Roe et al., 2004, Schrank and Slade, 2007 and Bonney and Stickley, 2008). Although the level of hope is highly variable among different individuals, it is considered to be a relatively enduring characteristic (Landeen and Seeman, 2000). Most definitions of hope include the idea of a positive future orientation (Landeen and Seeman, 2000). The current study is based on Snyder's definition of hope as a cognitive set that is based on a reciprocally derived sense of successful agency (goal-directed determination) and pathways (planning of ways to meet goals) (Snyder et al., 1991). The construct of hope reflects an individual's perceptions about his or her ability to conceptualize goals, develop strategies to reach those goals, and sustain the motivation to use the strategies (Snyder et al., 2003 and Resnick et al., 2005). The central element of hope is the positive expectancy of reaching goals that are deemed achievable to the individual (Snyder et al., 2006). Studies in different disability fields have utilized the hope construct as a predictor variable for life satisfaction (Chen and Crewe, 2009). The use of hope as a predictor variable is based on the conception of hope as an inner strength (Chang and DeSimone, 2001) and as a positive psychological variable that can predict positive outcomes, including greater life satisfaction (Kortte et al., 2010). The present study uses hope as a predictor of SWB. Several studies have examined the relationship between hope and QoL among individuals with SMI. A review study of the literature through 2008 identified 11 studies that examined hope as a predictor variable in mental health settings (Schrank et al., 2008). Three of these studies examined some aspects of well-being as the outcome variable. One study in a community mental health center found that higher hope was associated with greater SWB (Irving et al., 2004). In a study of 476 combat veterans in a PTSD unit who were examined pre- and post-treatment, it was found that more veterans with low levels of hope perceived their QoL to be better than did veterans with high levels of hope. One explanation for these unexpected results was the overall low level of hope expressed by all participants in the group (Johnson, 2001). In another study with 124 clients from university counseling centers, it was found that clients who reported higher levels of hope also reported higher SWB and lower symptom distress (Magyar-Moe, 2004). Since the above review, three additional studies are worth noting. A recent study conducted in Taiwan among 113 inpatients with schizophrenia found that depressive symptoms, parkinsonism side effects, hopelessness, and age at illness onset were the four strongest predictors of subjective QoL (Kao et al., 2011). Another study, conducted in Hong Kong (Ho et al., 2010), examined the recovery status of 201 outpatients with schizophrenia, using hope as one of ten recovery components, and found it to be a determinant of QoL. Finally, in a study conducted in Israel among 60 individuals with schizophrenia, hope was found to make a positive contribution to QoL, suggesting that increasing the hope of persons with schizophrenia may directly and positively increase their QoL (Hasson-Ohayon et al., 2009). Despite the importance of these studies, they have focused on different study questions than the current study. For example, some studies have focused on the construct of hopelessness rather than hope, which, although important, measures a degree of pessimism, rather than optimism (Kao et al., 2011). Methodologically, no study has utilized the Personal Wellbeing Index, which has recently been deemed as one of the most effective SWB instruments (Geyh et al., 2010). Finally, to the best of our knowledge, no study has examined how the impact of hope on QoL may be mediated by individual needs. 1.2. Needs and SWB Needs have been defined as “the requirements of individuals to enable them to achieve, maintain or restore an acceptable level of social independence or QoL” (Department of Health Social Services Inspectorate., 1991). Understanding the needs of persons with SMI is highly important, as these individuals are often faced with disadvantages in various social and personal areas of life (Bengtsson-Tops and Hansson, 1999), which are not limited to the disease itself (de Weert-van Oene et al., 2009). Needs can be seen as a state variable, and as such, it has been acknowledged that MH care should be based on patients' needs in order to improve their QoL (Slade, 2002). Moreover, needs assessment can form the basis of resource allocation and service delivery (Lasalvia et al., 2000) by uncovering unmet areas of need where there is an insufficient supply of treatment interventions (Wiersma and van Busschbach, 2001). Recent studies have examined the influence of met and unmet needs on the QoL of individuals with MI, using a broad QoL terminology rather than SWB. A number of these studies have established a relationship between unmet needs and lower QoL (Slade et al., 1999 and Lasalvia et al., 2005). For example, in a longitudinal study among 251 individuals with MI in Italy, improvement in QoL was achieved by a reduction in self-rated needs (Lasalvia et al., 2005). Similar findings have been reported in studies conducted in other parts of the world, such as Great Britain (Slade et al., 2005) and Sweden (Bengtsson-Tops and Hansson, 1999). Several studies have also shown that met needs are important predictors of QoL. In one such study among 265 mental health service recipients in Italy, patient-rated unmet needs, and to a lesser extent patient-rated met needs, were negatively associated with subjective QoL (Slade et al., 2004). Studies in the field of needs have stressed that the existence of a need is likely to be influenced by individual patient characteristics (McCrone et al., 2001), such as hope. Thus, the current study examined needs as a mediating factor between hope and SWB. 1.3. Study aims The current study has two main aims. The first aim is to examine SWB among individuals with SMI in Israel. According to the literature review, it is hypothesized that the level of SWB among people with SMI in Israel will be lower than the average in other Western populations. The second aim is to examine a mediation model for the relation between hope (as a predictor variable) and SWB (as a dependent variable). Specifically, we propose that hope is positively related to SWB and that this positive relationship is mediated by needs. According to Baron and Kenny (1986), four hypotheses can be inferred from a mediation model. This model (see Fig. 1) generated the following hypotheses: 1) hope will be positively related to SWB; 2) needs will be positively related to SWB; 3) hope will be positively related to needs; and 4) hope will be a positive predictor of SWB through the mediating variable of needs. Mediation model for SWB. Fig. 1. Mediation model for SWB.

3. Results 3.1. SWB and background variables The mean SWB score for the sample was found to be 61.6 (S.D. = 18.3). No statistically significant differences in SWB were found according to most background variables, including age, marital status, and GAF. However, statistically significant differences in SWB were found according to diagnosis. Participants diagnosed with schizophrenia reported a higher SWB (F(2, 166) = 3.09, p = 0.048) than individuals with other diagnoses. In terms of living environments, individuals living in hostels had a higher SWB score (M = 64.0, S.D. = 19.6) than individuals living in supported housing environments (M = 58.3, S.D. = 16.0) (t(159) = 2.02, p = 0.041). No differences were found in SWB for different types of daytime activities. 3.2. Path analysis model Findings show a strong positive correlation between hope and SWB (r = 0.57, p < 0.001). Further, bivariate analyses showed that both met and unmet needs were negatively related to SWB (met: r = − 0.16, p = 0.04; unmet: r = − 0.32, p < 0.001), and because the correlation between total needs (met and unmet needs together) and SWB had a similar direction and magnitude (r = − 0.36, p < 0.001), additional analyses were based on two need indices: no needs and total needs. A series of regression models was then estimated as follows in order to test for mediation: 1) regressing the mediator on the independent variable; 2) regressing the dependent variable on the independent variable; and 3) regressing the dependent variable on both the independent variable and on the mediator (Judd and Kenny, 1981). In order to calculate path coefficients three regressions were ran separately for no needs and for total needs (met and unmet needs together). In the first regression background variables were entered in the first step and needs in the second step. In the second regression, background variables were entered in the first step and hope in the second. Finally, in the third regression, background variables were entered in the first step and both needs and hope in the second step. Background variables included diagnosis (binary variable of schizophrenia vs. other diagnoses); living environment (binary variable of hostel vs. supported living); and day activity (two binary variables of sheltered vs. other day activity and open vs. other day activity). The results of the third regression for each no needs and total needs are presented in Table 2. For the sake of simplicity, the control variables are not shown. Table 2. Regression predicting SWB from needs and hope (N = 153). Independent variables Standardized regression coefficient SEB P R² No needs 0.27 0.35 0.000 Hope 0.48 2.09 0.000 0.401*** Total needs − 0.28 0.36 0.000 Hope 0.48 2.09 0.000 0.401*** Table options In terms of background variables, only living environment was found to be significant in the first regression model. None of the other background variables examined were found to be significant, nor was living environment found to be significant in the subsequent regressions. Therefore, they were dropped from further analysis. Results of the regression analyses showed that 18.5% and 19.3% of the variance in SWB were predicted by no needs and total needs, respectively. However, no needs and total needs were predictive of SWB in opposite directions, with no needs being a positive predictor (β = 0.38) and total needs a negative predictor (β = − 0.39) of SWB. Furthermore, hope was predictive of 33.9% of the variance in SWB. When placed together in a regression model (see Table 2), hope and needs were predictive of 40% of the variance in SWB, with hope being a stronger predictor of SWB. That is, hope increased the predictability of the model from 19% to 40%. Power estimate was calculated for testing the hypothesis of no change in r-squared due to hope above needs against the alternative hypothesis of increase of 0.21, at a significance level of 0.05, and a sample size of n = 153 and found to be at a satisfactory level (0.80). In the next step of the analysis, we examined the mediation model for the direct effect of hope on SWB and the effect of hope through needs. Two path-analysis models were constructed, one for the variable of no needs and the second for the variable of total needs. The results (see Fig. 2) show that the direct effect of hope on SWB was strong with Path coefficient of 0.52. The effect of hope, as mediated through needs, was lower with Path coefficient of 0.05 for no need and 0.06 for total need. It should be noted that the effects of no needs and total needs on SWB were in opposite directions, with no needs having a positive and total needs having a negative effect on SWB. Mediation models for SWB, using no needs and total needs. Fig. 2. Mediation models for SWB, using no needs and total needs.