Subjective quality of life in outpatients with schizophrenia in Hong ...

Qual Life Res (2008) 17:27–36 DOI 10.1007/s11136-007-9285-2

Subjective quality of life in outpatients with schizophrenia in Hong Kong and Beijing: relationship to socio-demographic and clinical factors Yu-Tao Xiang Æ Yong-Zhen Weng Æ Chi-Ming Leung Æ Wai-Kwong Tang Æ Gabor S. Ungvari

Accepted: 12 November 2007 / Published online: 23 November 2007 Ó Springer Science+Business Media B.V. 2007

Abstract Purpose This study compared the subjective quality of life (SQOL) in schizophrenia patients living with their families in Hong Kong (HK) and Beijing (BJ) and explored the relationship between SQOL and basic socio-demographic and clinical factors. Materials and methods Two hundred and sixty-four clinically stable outpatients with schizophrenia were randomly selected in HK and 258 counterparts matched according to age, sex, age at onset, and length of illness in BJ. SQOL and psychiatric status were assessed with standard rating instruments. Results There was no significant difference in any of SQOL domains between the two cohorts after controlling for potentially confounding variables. Positive, depressive and anxiety symptoms and drug-induced extrapyramidal side effects (EPS) were all significantly correlated with SQOL. Multiple regression analysis revealed that only depressive symptoms predicted all SQOL domains in both groups. Having removed depressive symptoms from the model, positive symptoms predicted all domains, anxiety predicted all but social domains, use of benzodiazepines (BZD) predicted all but physical domains, EPS predicted

Y.-T. Xiang C.-M. Leung W.-K. Tang G. S. Ungvari Department of Psychiatry, Chinese University of Hong Kong, Hong Kong SAR, China Y.-T. Xiang Y.-Z. Weng Beijing Anding Hospital, Capital Medical University, Beijing, China Y.-T. Xiang (&) Department of Psychiatry, Shatin Hospital, Shatin, N.T. Hong Kong SAR, China e-mail: [email protected]

physical domain, and history of suicide predicted social domain in HK; anxiety predicted all domains, positive symptoms predicted all but physical domains, EPS, use of BZD and history of suicide all predicted physical domains, and length of illness predicted environmental domain in BJ. Conclusion Despite considerable differences between the two sites in terms of health care delivery and the economic conditions of the subjects, SQOL did not differ between HK and BJ. The conclusion is in line with previous studies that suggested that patients’ SQOL was independent of their living standard as long as it reached a certain minimum level. SQOL was more strongly related to the severity of depressive symptoms and had weak association with socio-demographic factors. Keywords Schizophrenia Quality of life China Depressive symptoms

Introduction As the largest country in the world with a population of approximately 1.3 billion, P.R. China (hereafter, China) has a fundamentally different mental health system in comparison to western countries [1]. An epidemiological survey in China found that the lifetime prevalence of schizophrenia was 6.55% [2]. Accordingly, there are about 8.52 million Chinese patients with schizophrenia. It is estimated that over 90% of them live with their families due to the lack of community residential facilities [3]. As there are relatively few psychiatric beds and mental health professionals in China, massive institutionalization and subsequent deinstitutionalization have never occurred there [4]. During the past decades, subjective quality of life (SQOL) has been increasingly used as an outcome

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measure to evaluate health services in clinical practice in general and in schizophrenia in particular [5]. Factors related to SQOL in schizophrenia have been extensively reported. Browne et al. [6] found that length of illness and the cumulative duration of hospitalization significantly correlated with SQOL. Law et al. [7] reported that SQOL was more related to negative symptoms and only weakly related to, or independent of, positive symptoms. Bechdolf et al. [8] investigated 66 schizophrenia patients and found that the strongest determinant of SQOL was depressive symptomatology. A survey that involved 227 inpatients with schizophrenia examined the relationship between SQOL and suicide attempts and found that dissatisfaction with SQOL was associated with repeated suicide attempts [9]. In addition, multi-center studies have indicated that cross-cultural or ethnical differences in schizophrenia with respect to SQOL also exist [10, 11]. However, the association between most sociodemographic factors and SQOL remains controversial due to differences in the selection and size of the samples, the characteristics of the settings, study designs, and assessment procedures and instruments. It should be noted that all of the abovementioned studies were conducted in Western countries where the prevailing Judeo-Christian culture places high value on independence and self-realization [12]. In East Asia, particularly in those countries and regions that are influenced by traditional Chinese culture, Confucian ideas that emphasize interdependence and group harmony within the family still predominate [13]. Therefore, it is unlikely that findings of studies conducted with Caucasian patients would be applicable to a non-Western culture like that of the Chinese. Hong Kong (HK) became a Special Administrative Region of China on 1 July 1997, after a century and a half of British administration. Therefore, it has had Westernstyle political and socio-cultural development and public health policy, which is different from the rest of China. However, behind its westernized fac¸ade, traditional Chinese socio-cultural factors remain strongly influential in HK. While there are many publications on SQOL in Western countries, no published study has focused on the SQOL of Chinese schizophrenia patients living with their families in the community even though they constitute the overwhelming majority of the estimated 7–8 million schizophrenia patients in China. The objectives of this study were (1) to measure and compare SQOL in Chinese schizophrenia patients between HK and Beijing (BJ) and (2) to explore the association of QOL with socio-demographic and clinical factors in the two sites.

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Methods Study settings and participants The study was conducted between January 2005 and July 2006. First, subjects in HK were randomly selected from patients with a diagnosis of schizophrenia attending the outpatient clinic of a university-affiliated general hospital with a catchment area of approximately 800,000 people. Then, their counterparts in Beijing, matched according to age, sex, age at onset and length of illness, were recruited from the Adult Psychiatric Outpatient Clinic at Beijing Anding Hospital, which caters to a population of approximately 3,000,000. Inclusion criteria were: (1) diagnosis of schizophrenia according to DSM-IV criteria; (2) age 18–60 years; (3) length of illness C5 years; (4) outpatients living with their families in the community who have been clinically stable for at least 3 months before recruitment. Clinical stability was defined as no change in the medication or other forms of treatment or an increase in the dose of drug(s) by no more than 50% over the past 3 months [14], and (5) Chinese ethnicity with fluency in Mandarin in BJ and Cantonese in HK. Exclusion criteria were: (1) major chronic medical or neurological condition(s) and (2) past or current significant drug/alcohol abuse other than tobacco. The reported effect size (correlation coefficient; r) between one of the potential predictors, the depressive item of the Brief Psychiatric Rating Scale (BPRS), and outcome measures such as physical health, psychological, social relationships and environmental domains of SQOL were 0.31, -0.39, -0.27 and -0.29, respectively, in a previous study in HK [12]. Based on these values, using power analysis [15], the minimum number of patients needed in each group would be 65, 40, 93 and 66, respectively (a = 0.05; power 0.80). The study protocol was approved by the Joint Chinese University of Hong Kong-New Territory East Cluster Clinical Research Ethics Committee and the Human Research and Ethics Committee of Beijing Anding Hospital. Written consent was obtained from each participant.

Outcome measures SQOL was assessed with the Hong Kong and Chinese versions of the World Health Organization Quality of Life Schedule-Brief (WHOQOL-BREF-CHN; WHOQOLBREF-HK) [16, 17] in BJ and HK, respectively, which both cover four domains: physical and psychological health, social relationships and environmental factors. Patients assess their satisfaction for each item during the

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past 2 weeks on a 5-point scale (from 1 = ‘‘very dissatisfied’’ to 5 = ‘‘very satisfied’’). Psychotic symptoms were assessed with the BPRS [18]. For this study, the following three mean scores of the BPRS were used: (1) positive symptoms of conceptual disorganization, suspiciousness, hallucinatory behavior, and unusual thought content; (2) negative symptoms of emotional withdrawal, motor retardation, blunted affect, and disorientation; and (3) symptoms of anxiety and tension. Extrapyramidal side effects (EPS) were measured by the Simpson and Angus Scale of Extrapyramidal Symptoms (SAS) [19] and the Barnes Akathisia Rating Scale (BARS) [20]. For the sake of brevity, in this study the sum scores of these scales were entered in the statistical analysis. The 17-item Hamilton Depression Rating Scale (HAMD) [21] was used to evaluate the presence and severity of depressive symptoms.

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identify factors predicting each of the SQOL domains. Setting the level of statistical significance at P \ 0.01 reduced the risk of type I error due to multiple tests in the regression analyses. As depression was reported to be one of the strongest predictors of SQOL in previous studies [7, 22], it might take up most of the variance associated with other potential predictors, forcing them out of the model. To avoid this scenario, multiple linear regressions were conducted twice, with and without depression. Categorical variables were included as dummy variables. In an attempt to avoid multi-collinearity, tolerance was used to measure the strength of linear relationships among the independent variables; a value of 0.6 or above was regarded as acceptable. Furthermore, a re-calculation of power based on the results was made using Cohen’s criteria [15].

Results Assessment The principal author assessed all subjects throughout the study. To check the consistency of his ratings, prior to the study an inter-rater reliability exercise of all clinical rating instruments was conducted with another qualified psychiatrist of 9 years’ clinical experience on 20 randomly selected schizophrenia patients. The intra-class correlation coefficients (ICC) for the positive, negative and anxiety scores of BPRS, and the SAS, BARS and HAM-D were 0.927, 0.92, 0.763, 0.927, 0.835 and 0.935, respectively.

Statistical analysis Data were analyzed using the Statistical Package for the Social Sciences (SPSS), Version 13. First, the comparisons between the two groups with regard to socio-demographic and clinical characteristics and SQOL were performed by independent samples t-test for data following normal distribution, Mann–Whitney U test for data which were not normally distributed, and v2 test for categorical variables. To compare the SQOL and control for the potential confounding influence of other variables between the two cohorts, analysis of covariance (ANCOVA) was carried out. Second, the relationship between socio-demographic and clinical factors and SQOL domains was measured with Pearson correlation analysis given that the data followed normal distribution; otherwise Spearman rank correlation analysis was employed. Because of the multiple tests, only correlation coefficients (r) above 0.20 at the 0.001 level were regarded as significant ones. Third, multiple linear regression analysis using the stepwise method was used to

Altogether 607 patients were approached in HK and BJ, of whom 522 agreed to participate in the study. There was no significant difference between the study subjects and those patients who refused to participate with regard to age, sex, and length of illness. Of the patients who refused to participate, 56 (65.9%) had a diagnosis of the paranoid subtype of schizophrenia. Similar to earlier findings [6], patients who refused participation were more paranoid. Table 1 shows the socio-demographic and clinical data of the subjects. There were significant differences between HK and BJ in terms of monthly income, employment status, percentage of health insurance coverage, use and doses of antipsychotic (AP), anticholinergic and anxiolytic drugs, BPRS negative score, and the total HAMD and EPS scores. BJ patients were more likely to attempt suicide. Except for the physical domain, all SQOL domains for the HK cohort had significantly poorer scores in comparison with those in BJ (Table 2). However, having controlled for the effect of the BPRS negative score and total HAMD and EPS scores in the ANCOVA, there was no significant difference in any SQOL domain between the two samples (Table 2). Table 3 shows the statistically significant correlations between socio-demographic and clinical factors and different SQOL domains. Positive, depressive and anxiety symptoms and EPS were all significantly correlated with SQOL. Results of multiple regression analyses with the stepwise method exploring the predictors of SQOL in the two sites are shown in Tables 4 and 5. All variables that showed significant bivariate correlation relationships to SQOL at a = 0.05 level and those that were described as predictors of SQOL in the literature [12, 23–28] including

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Table 1 Socio-demographic and clinical data of the study subjects HK cohort (n = 264)

BJ cohort (n = 258)

Statistics

Mean

Mean

T/Z

Age Educational level (years) Monthly income (HK$)

SD

SD

dfb

42.3

8.9

43.6

8.0

-1.73

520

9.3

3.6

9.6

2.7

-1.35

520

3,040

2,952

939

-11.9a

910

P 0.08 0.17 \0.001

Age at onset (years)

26.8

8.0

27.0

7.1

-0.32

520

0.74

Length of illness (years) Number of hospitalizations

15.5 2.5

8.3 2.5

16.8 2.0

8.2 1.7

-1.8 -1.47a

520

0.07 0.14

Dose of current AP (CPZeq)

254

193

290

-3.10a

177

0.002

BPRS positive

1.49

0.75

1.39

0.71

1.51

520

0.13

BPRS negative

1.60

0.82

1.34

0.54

4.21

520

\0.001

BPRS anxiety

1.52

0.65

1.47

0.63

0.95

520

Total HAMD score

5.20

4.34

4.07

3.98

-3.92a

Total EPS score

1.12

2.25

0.44

1.19

-3.97a

N Sex (men)

134

% 50.8

N

%

132

51.2

Employment status Unemployed

156

59.1

199

77.1

Employed

108

40.9

59

22.9

Marital status Single/divorced/separated/widowed Married/cohabitating Covered by insurance

208

78.8

195

56

21.2

63

24.4

214

82.9

264

100

96

0.009

\0.001 df

c

P

1

0.93

19.52

1

\0.001

0.76

1

0.38

75.6

Type of AP On typical AP only

v

2

0.34 \0.001

36.4

116

44.9 48.1

49.12

1

\0.001

47.16

2

\0.001

On atypical AP only

88

33.3

124

On APP

80

30.3

18

7.0

On antidepressant

22

8.3

12

4.7

2.91

1

0.088

On anticholinergic

143

54.2

103

39.9

10.63

1

0.001

On BZD History of suicide attempts

69 54

26.1 20.5

91 92

35.3 35.7

5.12 14.97

1 1

0.024 \0.001

History of crime or violence

45

17

56

21.7

1.81

1

0.178

a

Mann–Whitney U test

b

Two sample independent t-test

c

v2 test

AP, antipsychotic drug; BPRS, Brief Psychiatric Rating Scale; APP, antipsychotic polypharmacy; HAMD, Hamilton Depression Rating Scale; EPS, extrapyramidal symptoms; BZD, benzodiazepine

age, education level, marital status, monthly income, length of illness, number of hospitalizations, history of suicide, crime and/or violence, scores of the BPRS positive, negative and anxiety subscales, total scores of HAMD and EPS, use of typical and atypical APs, and antidepressant, benzodiazepine (BZD) and anticholinergic drugs were entered as independent variables, and each SQOL domain was entered as a dependent variable. All SQOL domains were significantly predicted by one or more clinical characteristics before and after removal of

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depressive symptoms from the model. Multiple regression analysis revealed that only depressive symptoms predicted all SQOL domains in both groups, while educational level predicted the social SQOL domain and use of benzodiazepines predicted the environmental domain of SQOL in HK. History of suicide attempts predicted the physical domain, anxiety predicted the psychological domain, positive symptoms predicted the social and environmental domains, and length of illness predicted the environmental domain of SQOL in BJ.

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Table 2 Comparison of SQOL between the two sites before and after controlling for the clinical scales SQOL domains

HK cohort (n = 264)

BJ cohort (n = 258)

Ta

df

P

Fb

df

P

Physical

14.01 (2.40)

14.31 (2.60)

-1.39

520

0.163

0.51

1, 513

0.47

Psychological

13.24 (2.75)

13.91 (2.45)

-2.91

520

0.004

2.03

1, 513

0.15

Social

12.84 (2.58)

13.32 (2.64)

-2.07

520

0.039

0.66

1, 513

0.42

Environmental

13.42 (2.22)

13.81 (2.29)

-1.98

520

0.048

0.72

1, 513

0.39

a

Two independent-sample t-test

b

ANCOVA with the BPRS negative score, total HAMD and EPS scores controlled for

Table 3 Spearman correlations between socio-demographic and clinical factors and SQOL domains Item

Physical QOL

Psychological QOL

Social QOL

Environmental QOL

BPRS positive

-0.36***

-0.39***

-0.32***

-0.30***

BPRS anxiety

-0.38***

-0.45***

-0.27***

0.32***

Total HAMD score

-0.55***

-0.60***

-0.39***

-0.40***

Total EPS score

-0.22***

-0.21***

-0.15***

0.12**

*** P \ 0.001 Only statistically significant independent variables with correlation coefficients (r) above 0.20 at 0.001 level are included

Having removed depressive symptoms from the model, positive symptoms predicted all four QOL domains, anxiety predicted all but the social domain, use of benzodiazepines predicted all but the physical domain, EPS predicted physical domain, and history of suicide predicted social domain in HK. In the BJ sample anxiety predicted all QOL domains, positive symptoms predicted all but the physical domain, EPS, use of benzodiazepines and history of suicide were all predictors of the physical domain, and length of illness predicted the environmental domain. The correlation coefficient (r) between one of the potential predictors, the depression item in the BPRS and SQOL outcome measures of its physical health, psychological, social relationships and environmental domains, were -0.46, -0.54, -0.34, and -0.39, respectively. Using Cohen’s method [15], the power was [0.99 in all cases at a = 0.05 (one-tailed).

Discussion This study examined the SQOL of Chinese schizophrenia outpatients living with their families in the community. To the best of our knowledge, this was the first study to explore SQOL and its correlates in outpatients with schizophrenia in China. Although the two samples were matched according to age, sex, age at onset and length of illness, there were still significant differences in monthly income, employment status, and percentage of health insurance coverage between the two sites. The discrepancies in monthly income, employment status and health insurance coverage

between the two sites are obviously due to the different socio-cultural and economic contexts. Two complex factors are of particular importance. First, in China, patients with psychiatric illnesses, particularly with schizophrenia, are traditionally seen by the lay public as threats to others. For this reason patients are more likely kept in rehabilitation wards in psychiatric hospitals or at home for a long period of time even if they are clinically stable [29]. At the same time, they are generally provided with public health insurance and basic living expenses by their respective organizations if they were employed prior to the onset of schizophrenia. As a result, most of these patients do not need to find a job. This kind of ‘care’ is a common phenomenon and accepted by the general public. A proportion of psychiatric patients have no choice but to accept this practice as well, because in most cases no other better options are available. The impact of this practice on psychiatric patients and patients’ attitudes towards this particular situation need to be further investigated. Second, currently in BJ comprehensive health insurance only covers employed patients rather than all residents; therefore, the above deliberations do not apply to unemployed residents and those who fall ill at an early age before securing a job [30]. These factors could account for, in part, the lower rate of employment and health insurance in the BJ cohort. In HK, mental health services provide follow-up at outpatient clinics for every local resident. In most cases, outpatients are required to attend the follow-up clinics. If they miss their appointment, they will be contacted by mental health professionals to clarify the reasons for defaulting. Currently in BJ and all over China, mental

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Table 4 Stepwise multiple regression analysis with each SQOL domain as dependent variable and demographic and clinical factors as predictors in HKa Dependent variable Physical SQOL

Psychological SQOL

Social SQOL

Environmental SQOL

a

With DEP as potential predictor

Adjusted R2 = 0.33; F(1,259) = 130.0; P \ 0.001

Without DEP as potential predictor

Adjusted R2 = 0.22; F(3,258) = 26.1; P \ 0.001 2

Predictor

b

T value

P

DEP

-0.57

-11.40

\0.001

Anxiety

-0.21

-3.36

0.001

Positive symptoms

-0.26

-4.61

\0.001

EPS

-0.18

-3.18

0.002


Adjusted R = 0.34; F(1,259) = 132.5; P \ 0.001

DEP

-0.58

-11.51

\0.001


Adjusted R2 = 0.22; F(3,258) = 25.4; P \ 0.001

Anxiety

-0.27

-4.73

\0.001

Positive symptoms

-0.24

-4.13

\0.001

Use of BZD

-0.19

-3.61

\0.001


Adjusted R2 = 0.20; F(2,258) = 33.7; P \ 0.001

DEP

-0.45

-7.99

\0.001

Educational level

-0.15

-2.69

0.007


Adjusted R2 = 0.14; F(3,258) = 15.1; P \ 0.001

Positive symptoms

-0.26

-4.48

\0.001

Use of BZD

-0.17

-2.95

0.003

History of suicide attempts

-0.16

-2.78

0.006

DEP

-0.38

-6.72

\0.001

Use of BZD

-0.16

-2.90

0.004


Adjusted R2 = 0.20; F(2,258) = 34.3; P \ 0.001


Adjusted R2 = 0.16; F(3,258) = 18.0; P \ 0.001

Positive symptoms

-0.21

-3.45

0.001

Use of BZD

-0.24

-4.25

\0.001

Anxiety

-0.18

-3.11

0.002

Only statistically significant predictors are reported

BZD, benzodiazepine; DEP, depressive symptoms

health care has been mainly hospital-based plagued by a shortage of professional staff. As a result, a substantial part of mental health support falls on the family [31]. Under such circumstances, psychiatric outpatients are supposed to regularly see their psychiatrists on a voluntary basis. Alternatively, patients’ caregivers are allowed to attend the clinics and purchase psychiatric drugs on the patients’ behalf in particular cases, such as living far away from the clinic, poor weather, or disabling medical conditions. For patients with relatively severe negative or depressive symptoms, and/or disabling EPS, caregivers need to attend the clinics since no community services are yet available in China. In this study, all participants were recruited from an Outpatient Department (OPD). Thus, the abovementioned differences in mental health care between the two sites could partly account for the differences in the scores of the BPRS negative symptoms and the total HAMD and EPS scores. An alternative explanation might be that due to the

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shortage of psychiatrists, clinically stable outpatients attend their clinics every 2–4 months in HK, which may be insufficient to identify the less conspicuous negative and/or depressive symptoms and subtle EPS; in contrast, patients are required to see their psychiatrists monthly, or even more frequently, in BJ. The difference between the two groups in type and doses of AP(s) and the use of anticholinergic and anxiolytic drugs could be due to the different characteristics of prescription practices influenced by costs of treatment, public health policies, health insurance, and different symptomatology: i.e., factors that all influence the use of AP(s) [32]. The puzzling finding that patients in BJ had more suicide attempts needs to be explored further. Having controlled for the differences in psychopathology, there was no significant difference in any of the SQOL domains between the two cohorts. The conclusion is in line with previous studies that suggested that patients’ SQOL

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Table 5 Stepwise multiple regression analysis with each SQOL domain as dependent variable and demographic and clinical factors as predictors in BJa Dependent variable Physical SQOL

Psychological SQOL

Social SQOL

Environmental SQOL

Predictor

b

T value

P


Adjusted R2 = 0.38; F(2,254) = 78.9; P \ 0.001

DEP

-0.57

-11.52

\0.001

History of suicide attempts

-0.14

-2.82

0.005


Adjusted R2 = 0.30; F(4,253) = 27.4; P \ 0.001

Anxiety

-0.33

-5.66

\0.001

EPS

-0.19

-3.32

0.001

Use of BZD

-0.16

-3.11

0.002

History of suicide

-0.15

-2.89

0.004


Adjusted R2 = 0.43; F(2,254) = 99.7; P \ 0.001

DEP

-0.48

-7.03

\0.001

Anxiety

-0.21

-3.11

0.002


Adjusted R2 = 0.36; F(2,255) = 71.9; P \ 0.001

Anxiety

-0.48

-8.44

\0.001

Positive symptoms

-0.19

-3.42

0.001


Adjusted R2 = 0.19; F(2,254) = 31.6; P \ 0.001

DEP

-0.31

-4.76

\0.001

Positive symptoms

-0.20

-3.06

0.002


Adjusted R2 = 0.16; F(2,255) = 26.1; P \ 0.001

Positive symptoms

-0.25

-3.83

\0.001

Anxiety

-0.23

-3.53

\0.001


Adjusted R2 = 0.21; F(3,253) = 23.7; P \ 0.001

DEP

-0.28

-4.45

\0.001

0.19

3.51

0.001

-0.20

-3.12

0.002

-0.25

-3.87

\0.001

0.18

3.30

0.001

-0.21

-3.22

0.001


Adjusted R2 = 0.18; F(3,254) = 20.0; P \ 0.001

Length of illness Positive symptoms Positive symptoms Length of illness Anxiety

a

Only statistically significant predictors are reported BZD, benzodiazepine; DEP, depressive symptoms

was independent of their living standard as long as it reached a certain minimum level [33]: i.e., there seems to be only weak association between SQOL and objective quality of life (QOL) [34]. Similar to earlier findings [33], only educational level was inversely correlated with the social SQOL domain in the HK group. The possible reason could be that these patients had relatively high expectations, but failed to find appropriate employment or were frequently offered work way below their educational level. This lends support to previous findings suggesting that socio-demographic data had no, or only weakly significant association with SQOL [23, 35, 36].

Depressive symptoms were found to negatively predict each SQOL domain in both cohorts, underscoring the important role depressive symptoms play in contributing to SQOL in clinically stable outpatients with schizophrenia. This finding is consistent with that of previous reports [7, 22, 37]. Use of BZD was negatively associated with the environmental SQOL domain in the HK group. This intriguing association needs to be further explored. Severe positive symptoms were found to predict a lower level of social and environmental domains of SQOL in the BJ group. This finding is contrary to the widely held view that SQOL is more related to negative symptoms and only weakly related to, or independent of, positive symptoms

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[6, 7, 23]. The discrepancy between the literature and our findings could be explained by the following reasons. First, the choice of psychopathology measures: in this study BPRS was used, which probably led to less power to detect subtle changes in symptomatology in comparison with more specific measurements for positive or negative symptoms. However, this assumption cannot explain the relatively strong association between positive symptoms and SQOL. The second reason could be the particular socio-cultural context. Traditional Confucian ideas remain influential in China and HK, which underline modesty or the ‘‘golden mean’’ (zhong yong zhi dao) and oppose polarity or the extreme. This principle is well exemplified in the public attitudes towards different psychotic symptoms. In China, the ‘‘causes’’ of negative symptoms are more likely to be attributed to social and psychological problems. As a result, patients with predominantly negative symptoms are usually better accepted. In contrast, popular wisdom in China is more sensitive to positive symptoms, especially to aggressive or violent behavior. Psychotic patients with these symptoms are usually more stigmatized and are committed to psychiatric hospitals since they are commonly believed to be threats to the society even if they are clinically stable. However, these are just speculations, and to date, no study has specifically explored the impact of Confucian culture on SQOL. Surprisingly, longer length of illness was associated with higher environmental SQOL in BJ, a finding that is just the opposite to earlier conclusions [6]. We have no clear explanation for this other than assuming that the majority of Chinese outpatients could learn to readily accept their fate and adjusted well to their new life situation. History of suicide attempts was negatively associated with SQOL in BJ, in line with results of previous studies [9]. It was suggested that depression and anxiety together contributed to SQOL [36]. To date, however, few studies [37] have focused on the contribution of anxiety to SQOL. This study suggested that anxiety could independently influence the psychological domain of SQOL in BJ, but it failed to find this association in HK. The impact of anxiety on SQOOL in schizophrenia warrants further investigations. Having removed depressive symptoms from the model, anxiety, positive symptoms, use of BZD and history of suicide could significantly predict SQOL in both groups, while length of illness predicted SQOL only in BJ. Broadly consistent with previous findings [6, 38], EPS was found to significantly predict SQOL in both BJ and HK. The major strength of this study is the large, randomly selected, ethnically homogenous sample in both sites. However, the results should be interpreted with caution for several methodological limitations. First, the study was

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cross-sectional; therefore, the exploration of causal relationship was rather tentative. Second, the results are applicable only to clinically stable schizophrenia outpatients living with their families in the community, precluding generalization to those living in residential facilities. Third, a relatively limited scope of variables was examined. In addition to socio-demographic and clinical data, a complex interaction of other factors, such as coping style, self-esteem, premorbid adjustment and a social support network could also play a substantial role in determining SQOL [7]. Fourth, the key factor limiting the scope of the comparison is the lack of full compatibility between the two samples. As a consequence, the results obtained in BJ apply only to those subjects who attend maintenance clinics and have similar socio-demographic and clinical characteristics to their HK counterparts. There are no data on the rest of the outpatient population in BJ with respect to their SQOL. Fifth, a potential limitation of the study was the use of the WHOQOL-BREF, a generic questionnaire that may not have detected subtle changes of SQOL in the specific population of schizophrenia patients. Therefore, more specific tools with sensitive gradations should be used in future studies. Finally, not having SQOL values for the general population in either site as a reference constituted a limitation.

Conclusion The results underline the deleterious effect of depressive symptoms on SQOL in even relatively clinically stable schizophrenia patients, suggesting that effective therapeutic interventions alleviating depressive symptoms for Chinese patients might be of considerable benefit in improving their SQOL. Depressive symptoms in schizophrenia should be targeted with antidepressants since most, if not all, antipsychotic agents do not treat the frequent depressive features of schizophrenia [39]. The positive association between SQOL and EPS warrants the more widespread use of APs with fewer side effects. In the light of recent, large-scale studies [40, 41] revealing that atypical APs were not significantly superior to conventional APs in improving efficacy and patients’ QOL, replacing traditional APs with the far more expensive atypical ones should be done judiciously, particularly in countries with limited health care expenditure. Because of its significant correlation with physical and social domains of SQOL, more attention should be paid to the history of suicide attempts in Chinese schizophrenia patients. Positive symptoms, anxiety and the use of BZD, as significant predictors of SQOL in both sites, should also attract the attention of clinicians and mental health policymakers in both HK and BJ.

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Further studies are warranted to explore psychiatric patients’ SQOL in different settings (inpatients versus outpatients) and in different areas (rural versus urban) of China and whether a generic questionnaire such as the WHOQOL-BREF is able to detect the minor changes in SQOL. Acknowledgements The authors would like to thank the staff of the Day Hospital at Shatin Hospital, the Li Ka Shing Psychiatric Outpatient Clinic at Prince of Wales Hospital and the General Outpatient Department at Beijing Anding Hospital for their assistance in the project.

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