Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness to participate among long-term hospitalized patients with schizophrenia

Psychiatry Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎

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Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness to participate among long-term hospitalized patients with schizophrenia Bo-Jian Wu a,b, Hsun-Yi Liao a, Hsing-Kang Chen a, Tsuo-Hung Lan b,c,d,e,n a

Department of Psychiatry, Yuli Hospital, Ministry of Health and Welfare, Hualien, Taiwan Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan c Department of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan d Department of Psychiatry, Taichung Veterans General Hospital, Taichung, Taiwan e Center for Neuropsychiatric Research, NHRI, Miaoli, Taiwan b

art ic l e i nf o

a b s t r a c t

Article history: Received 20 April 2015 Received in revised form 18 November 2015 Accepted 11 January 2016

Many studies discuss factors related to the decision-making capacity to consent to clinical research (DMC) of patients with schizophrenia. However, these studies rarely approached willingness to participate and the association between psychopharmacological properties (e.g., antipsychotic-induced side effects) and DMC. This study aimed to explore factors related to DMC and willingness to participate in patients with schizophrenia. All 139 patients with schizophrenia were assessed with the MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR) and other measures. A linear regression model was used to find the predictors of MacCAT-CR scores. A logistic regression model was used for exploring the predictors of willingness to participate. Patients with more severe negative symptoms performed poorly in DMC outcomes. In addition, females, those with fewer years of education and reduced cognitive function are more likely to experience difficulties in decision-making. Forty-three subjects (30.4%) chose to participate. Patients with higher level of positive symptoms, longer length of stay, higher burden of anticholinergics and users of atypical antipsychotics were more likely to participate in a clinical study which aimed to “enhance cognition”. These finding suggest that research investigators should consider many variables for patients who require more intensive screening for impaired DMC. & 2016 Elsevier Ireland Ltd. All rights reserved.

Keywords: MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR) Decision-making capacity Schizophrenia Taiwan Psychopathology Negative symptoms Psychopharmacology

1. Introduction Schizophrenia is a chronic debilitating disease affecting many domains of function, the core symptoms of which consist of impaired cognition; positive symptoms featuring hallucinations, delusions and loosening association; and negative symptoms including emotional apathy, social withdrawal and lack of drive (Crow, 1985; Gelder et al., 1996; Matza et al., 2006). Considerable attention has been devoted to decision-making capacities related to research (DMC) among schizophrenia patients, as these patients are noted to have more impaired DMC than nonpsychiatric comparison subjects (Cohen et al., 2004; Appelbaum, 2006; Jeste et al., 2006). To identify patients with impaired DMC necessitating further education and remediation is paramount; a useful screening n Corresponding author at: Department of Psychiatry, Taichung Veterans General Hospital, 160, Sec.3, Chung-Kang Rd, Taichung 40705, Taiwan. E-mail address: tosafi[email protected] (T.-H. Lan).

instrument with which to assess DMC is therefore needed for clinical practice and related research (Appelbaum, 2006). Thus, the MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR)(Appelbaum and Grisso, 2001) which includes 4 components: understanding, appreciation, reasoning and expression of a choice, was developed to evaluate the DMC of subjects in clinical studies, and this rating scale has been commonly used in people with schizophrenia (Carpenter et al., 2000; Dunn et al., 2002; Moser et al., 2002; Stroup et al., 2005). Among schizophrenia patients, clinical psychopathology was determined to be related to DMC in numerous studies (Moser et al., 2002; Kovnick et al., 2003; Stroup et al., 2005), several of which found that negative symptoms—rather than positive symptoms—were significantly associated with the understanding scores of the MacCAT-CR (Moser et al., 2002; Stroup et al., 2005; Candilis et al., 2008). However, our pilot study found both positive and negative symptoms to be significantly associated with the understanding and appreciation scores of the MacCAT-CR (Lan et al., 2013). Nevertheless, methodologies were limited by the heterogeneity of

http://dx.doi.org/10.1016/j.psychres.2016.01.020 0165-1781/& 2016 Elsevier Ireland Ltd. All rights reserved.

Please cite this article as: Wu, B.-J., et al., Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.020i

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subjects' characteristics (Stroup et al., 2005), relatively small sample sizes (Moser et al., 2002; Candilis et al., 2008), and a failure to use regression models to control for important related confounders, e.g., age and sex, in all previous research including our pilot study (Lan et al., 2013). In addition to psychopathology, educational level has been found to be associated with DMC in individuals with schizophrenia (Dunn et al., 2006b; Candilis et al., 2008), though inconsistent results were present (Palmer and Jeste, 2006). In a study enrolling hospitalized patients with schizophrenia, the duration of hospitalization was found to have a negative association with DMC (Kovnick et al., 2003). Moreover, a number of studies have revealed that cognitive deficit is associated with impaired DMC (Stroup et al., 2005; Palmer and Jeste, 2006; Dunn et al., 2007; Palmer and Savla, 2007). Of particular interest, factors related to cognition and memory that might lead to impaired DMC, such as dosages and types of antipsychotics (Faber et al., 2012), dosages of benzodiazepine and dosages of anticholinergics (Mintzer et al., 2010), have not been explored in prior studies. It is worth investigating whether the pharmacological properties of psychotropic agents affect DMC among schizophrenia patients because further effective strategies concerning the recruitment of research subjects might be tailored to patients on different regimes of treatment. Meanwhile, identifying factors associated with the decisions that participants make about whether to take part in a hypothetical study is an important step in providing useful clues in further studies designed to clarify subjects’ concerns and avoid misunderstandings during the process of recruitment. One study reported that the willingness to participate in schizophrenia research differed between those with prior research experience and those without (Kaminsky et al., 2003). Prior studies found the willingness to take part in a clinical study was negatively associated with levels of the perceived risk of participation (Roberts et al., 2002; Dunn et al., 2009), and positively with higher levels of education, higher cognitive function and lower psychotic level, and higher scores of MacCAT-CR on certain scales (Candilis et al., 2006). A study enrolling schizophrenia patients and psychiatrists indicated that monetary incentives, physicians’ recommendations and family preferences seemed to influence patients' participation decisions (Roberts et al., 2002). Yet there were unexplored issues in these studies: long-term hospitalized patients were not included, the effects of psychotropic medications on willingness remained unclear, and some of these studies did not use regression models to control for related confounders. In the U.S., at present, long-term hospitalization is rare. However, in certain East Asian countries, such as Taiwan, China, Japan and Korea, long-term hospitalization systems for mentally ill patients still exist (Phillips, 2001; Hanzawa, 2012). Compared with shorter-term inpatients, longer-term patients with severe mental illness have more striking features of “thought disorder” (Sakiyama et al., 2002), more pronounced cognitive deficits (Heinik, 1996; Sarto et al., 2002), more severe negative symptoms (Heinik, 1996) and poorer social functioning; all of which still persist even after patients are discharged (Harvey et al., 2010). A study in China found greater lengths of stay for schizophrenia patients are associated with more extensive negative symptoms and social isolation (Wu et al., 2013). These findings indicate long-term schizophrenia inpatients harbor unique characteristics that may affect their independent living. The issue of DMC thus warrants investigation among long-term hospitalized schizophrenia patients as they are faced with the aforementioned disadvantages in global functioning. To our knowledge, however, until just recently, only one study enrolling 27 long-term inpatients in the U.S. has explored the issue of DMC with MacCAT-CR (Kovnick et al., 2003).

The current study aimed to explore the relationship between a number of factors and DMC using a regression model among longtermed hospitalized schizophrenia patients. This study asked whether the severity of positive symptoms is negatively associated with DMC in a linear regression model; and (2) whether patients with higher daily doses of antipsychotics, benzodiazepines or anticholinergics present with impaired DMC. We also aimed to clarify unexplored factors related to subjects' DMC in prior studies, such as type of antipsychotics used and patients' willingness to participate in a hypothetical clinical study.

2. Methods 2.1. Participants Supplement 3 describes the background of the long-term stay of psychiatric patients in Taiwan and the nature of the study site and subjects in this study. We recruited patients in a public psychiatric hospital, Yuli hospital, Ministry of Health and Welfare in Taiwan which accommodates about 2500 long-term psychiatric patients (1) who met the diagnostic criteria for schizophrenia or schizoaffective disorder according to the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV); (2) whose scores on the Chinese version (Guo et al., 1988) of the Mini-Mental State Examination (MMSE) (Folstein et al., 1975) were greater than 20; and (3) who had at least 3 years of education. Participants were excluded from this study if they refused to be evaluated or had an acute psychotic episode that required a hospital transfer. The patient sample included 139 subjects. 2.2. Procedures Supplement 3 describes in detail the use of MacCAT-CR and relevant interventions safeguarding subjects' rights. The study design was reviewed by the Institutional Review Board (IRB) of Yuli Hospital. Before the study began, we explained the content of this research to subjects according to the principles of informed consent, in which a “hypothetical study” related to memory enhancement was emphasized. The study began in January 2011 and was completed in June 2012. 2.3. Measures 2.3.1. MacCAT-CR Participants were audio recorded during their assessment using the Chinese version (Lan et al., 2013) of the MacCAT-CR (Appelbaum and Grisso, 2001). A detailed validation of this Chinese version has been reported elsewhere (Lan et al., 2013). The MacCAT-CR was used herein to assess 4 components: an understanding of the nature of the research project and its procedures (5 sections, a total of 13 items); an appreciation for the effects of participation (3 sections); the ability to think rationally about participation (4 sections); and the ability to choose (1 item). Three research assistants who had been trained to conduct a semistructured MacCAT-CR interview according to standardized instructive sentences (Supplement 1), completed the interviews and audio recordings for all patients. The original authors of the MacCAT-CR (Appelbaum and Grisso, 2001) described a hypothetical 6-week double-blind placebo-controlled randomized trial, which we modified to an exploration of the effectiveness of a memory-enhancing drug for cognitive deficits (Appendix B). A certified psychiatrist (BJW) who had been trained to score the MacCAT-CR completed these ratings after listening to all of the interviews using the rating guidelines of a revised and validated back-translated Chinese version of the MacCAT-CR (Supplement

Please cite this article as: Wu, B.-J., et al., Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.020i

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2). Global MacCAT-CR scores were constituted from a summation of the scores of each component. In spite of the availability of MacCAT-CR, there is presently no consensus on where to set the cutoff for DMC adequacy on any of these measures because of disparity in the nature of studies. A study enrolling 91 schizophrenia patients used published MacCATCR-based standards to examine impaired DMC (Dunn et al., 2007). Three standards ranged in stringency in ascending order: understanding scores greater than 15 out of 26 points in an actual study of schizophrenia (Stroup et al., 2005), understanding scores greater than 20 out of 26 points in a hypothetical study of schizophrenia (Carpenter et al., 2000), and a multidimensional criterion in a hypothetical study of dementia, i.e., understanding scores greater than 17, appreciation scores greater than 4 and reasoning scores greater than 5 (Kim et al., 2001).The least stringent standard resulted in a total of 8% impaired DMC; at the intermediate standard, 19%; and at the most stringent standard, 57%. Based on these findings, the authors highlight the need for the refinement of an assessment procedure and improvements in the use of MacCAT-CR for screening purposes (Dunn et al., 2007). 2.3.2. Other measures Psychopathology was assessed using the Chinese version (Cheng et al., 1996) of the Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987). Cognitive function was assessed based on a Chinese version (Guo et al., 1988) of the Mini-Mental State Examination (MMSE) (Folstein et al., 1975). The maximum score of Chinese version of MMSE is 33, which adds 3 questions to augment the discriminant validity for those who have relatively few years of education. We converted the daily mean doses of antipsychotics, anticholinergics and benzodiazepine into a defined daily dose (DDD) (http://www.whocc.no/atc_ddd_index/). Antipsychotics were categorized into typical antipsychotics (TAs) and atypical antipsychotics (AAs) (Horacek et al., 2006). Patients on TAs and AAs were categorized as AA users. 2.4. Statistical analyses A bivariate Pearson correlation was performed among global MacCAT-CR scores and all covariates in regression models. A linear regression model was used to identify predictors of scores related to understanding, appreciation, reasoning and global MacCAT-CR performance. Since the types of participants' medication use were considered indicators of severity of schizophrenia patients, and these variables were included in the regression models. Finally, eleven variables included in the regression model were as follows: age and sex; years of education and hospitalization; MMSE scores; PANSS positive and negative scores; and psychopharmacological properties, such as the type of antipsychotics, the DDD of antipsychotics, benzodiazepine and anticholinergics. The sample size of the linear regression model was calculated based on a formula developed by some researchers (Tabachnick and Fidell, 2007). The minimum sufficient sample size was 138 participants; a number which is smaller than that of our present study (n ¼139). To examine the willingness of participation in a hypothetical study, group comparisons were conducted using an independent t-test for continuous variables and a chi-square test for categorical variables. A logistic regression model was used to explore the predictors of willingness to participate in clinical research. Twelve covariates included variables added to the linear regression model and global MacCAT-CR scores. The adequate sample size of the current study was sufficient for a logistic regression model according to a calculation formula proposed by a number of researchers (Peduzzi et al., 1996). SPSS version 19 (IBM company) was used to conduct a statistical analyses. The significance level was set at a value of 0.05 (two-tailed).

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Table 1 Participant characteristics and demographic data. Variables

Minimum Maximum Mean

S.D.

Age (years) Education (years) Gender (male, N, %) Expression of participation in study (N, %) Diagnosis (schizophrenia, N, %) Years of hospitalization Duration of mental illness (years) PANSS PANSS-positive score PANSS-negative score PANSS-general score MMSE Type of antipsychotics (atypicals, N, %) DDD of antipsychotics DDD of benzodiazepines DDD of anticholinergics Global MacCAT-CR score Understanding (sum of U1–U5) Appreciation (sum of A1–A3) Reasoning (sum of R1–R4) Expression of a choice

26.68 3 – –

74.52 16 – –

50.18 9.85 10.39 2.97 92 66.2 42 30.4

– 3.15 8.73 34 7 7 17 0 0 0 0 0 0 0 0 0

– 39.71 49.43 116 26 63 50 33 3 13 2 40 26 6 8 2

111 79.9 15.14 9.81 26.96 9.34 63.23 14.96 12.59 4.35 18.90 6.50 31.55 7.59 29.48 3.25 89 64 0.88 0.55 0.47 1.24 0.16 0.24 20.42 10.08 12.61 7.01 1.98 2.00 3.96 2.39 1.83 0.50

S.D ¼standard deviation; PANSS ¼Positive and Negative Syndromes Scales score MMSE ¼Mini-Mental Status Examination score DDD¼ defined daily dose

3. Results 3.1. Demographic data and other measured outcomes Table 1 presents demographic data and other measured outcomes. The mean age was 50.2 years. The mean duration of hospitalization and schizophrenia were 15.1 years and 26.9 years, respectively. The majority of participants were male (66.2%). All 111 subjects (82.8%) had been diagnosed with schizophrenia, while the remaining participants had been diagnosed with schizoaffective disorders. 3.2. Correlation between MacCAT-CR and other covariates Table S1 (Supplement files) shows a Pearson bivariate correlation among global MacCAT-CR and covariates in regression models. Global MacCAT-CR scores were positively correlated with MMSE and years of education, and negatively correlated with PANSS-positive subscales, negative scales and age. Except for a moderate correlation between hospitalization years and age (Pearson r ¼0.568), bivariate correlation coefficients were all less than 0.5. Table 2 and Tables S2–S6 (Supplement files) display the results of the linear regression models, in which multicollinearity did not exist according to the rule that values of tolerance were all greater than 0.1 and those of the variance inflation factor were all less than 10 for all covariates (O’Brien, 2007). Understanding scores were positively associated with the male sex (B ¼ 4.439, t¼3.349, p¼ 0.001), educational years (B ¼0.659, t¼3.138, p¼ 0.002) and MMSE (B ¼0.625, t ¼3.024, p ¼0.003), and negatively associated with PANSS negative subscales (B ¼  2.05, t¼  2.007, p¼ 0.048). Appreciation scores were positively associated with the male sex (B ¼1.18, t¼2.944, p ¼0.004) and educational years (B ¼0.173, t¼2.719, p ¼0.008) and were negatively associated with PANSS negative subscales (B ¼  0.083, t ¼  2.675, p ¼0.009). The severity of negative symptoms was negatively associated with reasoning scores (B ¼  0.11, t¼  2.711, p¼ 0.008). There were no covariates significantly associated with scores of expressing a choice. Global MacCAT-CR scores were positively associated with the male sex

Please cite this article as: Wu, B.-J., et al., Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.020i

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Table 2 Models predicting MacCAT-CR scores. Outcome Understanding

Appreciation

Reasoning Expressing a choice Global MacCAT-CR

Table 3 Characteristics between patients presenting different willingness to participate. B estimate

Sex (reference¼ female) MMSE Education (years) PANSS-negative score Sex (reference¼ female) Education (years) PANSS-negative score PANSS-negative score – Sex (reference¼ female) Education (years) MMSE PANSS-negative score

4.438 0.626 0.659  0.206 1.178 0.173  0.083  0.112 – 5.349 0.914 0.83  0.409

SE 1.318 0.201 0.209 0.102 0.399 0.063 0.031 0.041 – 1.882 0.298 0.287 0.145

t 3.367** 3.12** 3.157**  2.019* 2.952** 2.743**  2.701**  2.725** – 2.842** 3.067** 2.894**  2.813**

A linear regression model was used. All 11 variables, i.e., age, sex, PANSS positive scores, negative scores, MMSE scores, years of education and hospitalization, type of antipsychotics, defined daily dose of antipsychotics, anticholinergics and benzodiazepine were included in all models. The detailed results are presented in supplement files (Table S1–S5). Here, all covariates with a significance level less than 0.05 are presented in this table. S.E ¼standard error; MacCAT-CR ¼ MacArthur Competence Assessment Tool for Clinical Research; PANSS ¼ Positive and Negative Syndromes Scale score; MMSE ¼Mini-Mental Status Examination score. * **

p o 0.05. p o0.01.

(B ¼5.36, t¼ 2.839, p ¼0.006), educational years (B ¼0.91, t¼ 3.042, p ¼0.002) and MMSE (B¼ 0.79, t¼2.683, p ¼0.009), and negatively associated with PANSS negative subscales (B¼  0.406, t¼  2.785, p ¼0.007). No psychopharmacological properties, i.e., the type of antipsychotics and DDD of antipsychotics, benzodiazepine and anticholinergics, were observed to be significantly associated with any DMC outcomes.

Variables

unwilling (n¼ 96) Mean (SD)

willing (n¼ 43) Mean (SD)

Sex, male, n (%) Age (years) Education (years) Years of current hospitalization Global MacCAT-CR Atypical antipsychotics, n (%) DDD of antipsychotics DDD of benzodiazepine DDD of anticholinergics MMSE PANSS Positive subscales Negative subscales P1 Delusion P2 Conceptual disorganization P3 Hallucinatory behavior P4 Excitement P5 Grandiosity P6 Suspiciousness P7 Hostility N1 Blunted affect N2 Emotional withdrawal N3 Poor rapport N4 Passive/Social withdrawal N5 Difficulty in abstract thinking N6 Lack of spontaneity of conversation N7 Stereotyped thinking

50.5 (67.7) 45.4 (9.8) 10.6 (3.0) 14.2 (8.8) 21.5 (10.2) 55.0 (60.4) 0.92 (0.57) 0.57 (1.4) 0.14 (0.2) 29.6 (3.3) 62.3 (15.1) 12.1 (4.2) 18.9 (25.3) 1.9 (1.0) 1.6 (0.9) 2.0 (1.2) 1.6 (0.7) 1.5 (0.7) 1.8 (0.9) 1.4 (0.5) 2.6 (1.3) 3.1(1.1) 2.2 (1.1) 3.2 (1.2) 3.0 (1.4) 2.3 (1.0) 1.7 (0.9)

49.8 46.6 9.7 17.5 17.7 33.0 0.80 0.26 0.21 28.9 65.0 13.5 18.7 2.3 2. 1 2.2 1.5 1.8 1.8 1.5 2.6 3.0 2.2 3.1 3.4 2.3 1.9

(61.9) (9.6) (2.8) (11.6) (9.4)* (80.5)* (0.51) (0.5) (0.3) (3.0) (14.7) (4.5) (25.3) (1.2)* (1.0)** (1.1) (0.7) (1.1) (1.0) (0.8) (1.3) (1.1) (1.0) (1.2) (1.5) (1.0) (1.0)

Significant difference in these variables between the two groups using an independent t-test or chi-squared test. PANSS ¼ Positive and Negative Syndrome Scale; MMSE ¼ Mini-Mental Status Examination score. DDD¼ defined daily dose * **

p o0.05; p o 0.01.

3.3. Willingness to participate in a hypothetical clinical study 4. Discussion Nearly one-third of patients chose to participate in the hypothetical clinical study (n ¼43, 30.4%). Table 3 shows characteristics between patients presenting different levels of willingness to participate in the study. In a univariate analysis, in comparison to those on TAs, subjects on AAs were more likely to participate in the study (80.5% were willing vs. 60.4% were unwilling; χ2 ¼ 5.11, df¼ 1, p ¼0.024). Aside from those participants who decided to take part in the study but had lower scores in global MacCAT-CR (17.7 vs. 21.5, p ¼0.043), higher scores in PANSS P1: delusion (2.3 vs. 1.9, p ¼0.048) and P2: conceptual disorganization (2.1 vs. 1.6, p ¼0.009), there were no significant differences in variables between these two groups. Multicollinearity did not exist in the logistic regression model because bivariate correlation coefficients were all less than 0.7 (Yoo et al., 2014). Table 4 shows that patients with higher PANSS positive subscales (OR ¼1.191, 95% CI: 1.023–1.38), greater hospitalization years (OR ¼1.082, 95% CI: 1.01–1.16), or higher DDD of anticholinergics (OR¼ 13.56, 95% CI: 1.31–139.83) were more likely to participate in the study. Subjects on atypical antipsychotics were more likely to take part in the study than those who were on typical ones (OR ¼4.97, 95% CI: 1.25–19.76). A great number of subjects did not specify reason for agreeing and refusing to participate. Many subjects stated they possibly “get better memory” or “a cure for psychiatric illness” if they took part in the study. Participants who disclosed an aversion to the study expressed reasons such as “no need to take part a study”, or “worry about side effects” or “dislike being treated as a guinea pig”(Table 5). Table 5 displays reasons for agreeing and refusing to participate in a hypothetical study.

4.1. The correlation between DMC and other covariates From findings detailed in Table 2, we determined that no variables were significantly correlated with scores of expressing a choice. This result appeared to be in line with evidence from a prior study, which revealed that the expression of a choice was not correlated with any psychopathology or cognition variables and was non-differentiable in respect to DMC between the normal comparison group and patients with schizophrenia (Lan et al., 2013). In addition, there was a great number of variables of relevance to understanding scores, and exactly the same variables were found to be related to global MacCAT-CR scores. This phenomenon was in line with the finding that the psychometric properties of reasoning and appreciation components were not as robust as that of the understanding component (Dunn et al., 2006a). In regard to psychopathology and DMC, our study found that the PANSS negative subscales were negatively correlated to the 4 outcomes of DMC included in the regression model, i.e., understanding, appreciation, reasoning and global MacCAT-CR scores. These findings are in line with those of previous studies (Moser et al., 2002; Stroup et al., 2005). Our pilot study revealed that positive subscales were negatively associated with understanding and appreciation scores when assessing Pearson correlation coefficient (Lan et al., 2013). However, our current study showed that positive subscales were not correlated with any DMC scores in the regression model. One study recruiting 52 patients with schizophrenia found that positive symptoms were correlated with appreciation and reasoning scores when assessed by the Pearson

Please cite this article as: Wu, B.-J., et al., Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.020i

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Table 4 Logistic regression model predicting factors related to willingness to participate in the study.

Age Sex: male (reference: female) PANSS Positive subscales PANSS Negative subscales Antipsychotics type: AA (reference: TA) DDD of antipsychotics Education (years) MMSE DDD of benzodiazepine Hospitalization (years) Global MacCAT-CR DDD of anticholinergics

B

SE

Wald

df

p

OR

Lower

Upper

 0.025  0.942 0.175  0.049 1.604  0.905  0.208  0.057  0.161 0.078  0.014 2.607

0.032 0.797 0.078 0.056 0.704 0.609 0.118 0.107 0.445 0.036 0.036 1.190

0.584 1.396 5.061 0.758 5.198 2.207 3.122 0.286 0.131 4.832 0.147 4.798

1 1 1 1 1 1 1 1 1 1 1 1

0.445 0.237 0.024 0.384 0.023 0.137 0.077 0.593 0.718 0.028 0.701 0.028

0.976 0.390 1.188 0.952 4.871 0.405 0.812 0.944 0.851 1.082 0.986 13.564

0.916 0.082 1.023 0.853 1.251 0.123 0.645 0.766 0.356 1.009 0.918 1.242

1.039 1.860 1.380 1.063 18.951 1.335 1.023 1.165 2.035 1.160 1.059 121.748

Age, gender, global MacCAT-CR scores, PANSS positive scores, negative scores, MMSE scores, years of education, years of hospitalization, type of antipsychotics (typical antipsychotics and atypical antipsychotics), and the defined daily dose of antipsychotics, anticholinergics and benzodiazepine were included in the forward logistic regression model. SE ¼ standard error; OR ¼ odds ratio; Lower ¼ lower limit of 95% CI for odds ratio; Upper ¼ upper limit of 95% CI for odds ratio; MacCAT-CR ¼ MacArthur Competence Assessment Tool for Clinical Research; PANSS ¼Positive and Negative Syndromes Scale; MMSE¼ Mini-Mental Status Examination score TA ¼ typical antipsychotics; AA ¼atypical antipsychotics; DDD ¼defined daily dose

Table 5 Reasons for agreeing and refusing to participate in a hypothetical study. N Reasons for agreeing to participate 1. I will get a better memory 2. I will get improvement or a cure for psychiatric illness 3. The doctor and I will know whether this novel medicine can improve memory 4. I will be discharged from the hospital 5. I will find a job 6. No specific reason Reason for refusing to participate 1. I am fine. There is no need to take part in a study like this. 2. I worry about possible side effects 3. I do not want to have my blood taken 4. I do not want to take more medicine 5. I do not want to be used as a guinea pig 6. I have no time 7. No specific reason

%

12 27.3 7 15.9 3 6.8 2 4.5 1 2.3 16 36.4

18 18.3 17 17.3 17 17.3 9 9.2 9 9.2 6 6.1 22 22.4

correlation (Candilis et al., 2008). A study recruiting 27 hospitalized patients with schizophrenia (Kovnick et al., 2003) and another study enrolling 20 inpatients and 10 outpatients (Carpenter et al., 2000) revealed that scores related to a psychoticism item on the Brief Psychiatric Rating Scale (BPRS) were associated with understanding scores in a bivariate correlation. The disparity between the results of these three studies and ours can most likely be attributed to differences in statistical method: the bivariate correlation method in the former three studies and a regression model controlling for a series of confounders in the present study. In addition, though the study of Kovick et al. enrolled long-stay patients, their patients were assessed by BPRS instead of PANSS, the sample sized was much smaller than ours, and the length of hospitalization was much shorter than that of our subjects (7.33 years vs. 15.1 years). Our study also identified a negative correlation between MMSE score and the understanding and appreciation scores involved in the regression model. This finding is compatible with those of prior studies that reveal that cognition is related to DMC (Stroup et al., 2005; Dunn et al., 2007; Palmer and Savla, 2007; Candilis et al., 2008). Likewise, one study used an assessment similar to the MacCAT-CR, the MacArthur Competence Assessment Tool for Treatment (MacCAT-T) (Grisso et al., 1997), to measure assent to

receive treatment among patients with schizophrenia. This study showed that cognitive function is the primary predictor of DMC with regard to consent to treatment. These findings indicate that cognitive deficits determine whether patients with schizophrenia are able to make decisions concerning their participation (e.g., in clinical trials or cooperation with medical staff to receive treatment) as it relates to their rights, interests, risks and benefits. Thus, deciding how to provide a reliable process of review to resolve ethical issues for participants with impaired cognition in clinical studies is critical. Surprisingly, there was no association between any psychopharmacological properties and DMC outcomes. Our results can be explained at least in part by the finding that anticholinergics and benzodiazepine, such as scopolamine and triazolam, impair episodic memory rather than semantic memory (Mintzer et al., 2010); the latter being an important factor in patients’ ability to memorize the content of clinical trials in the MacCAT-CR. However, generalizability is limited by the characteristics of long-term hospitalized subjects in this study. We still hope that our findings can inspire future researchers to focus on this issue and conduct replication studies. One study determined that length of stay had an inverse correlation with DMC and did not identify any sex effect on DMC in schizophrenia patients (Kovnick et al., 2003). Conversely, this study did not obtain the same result. Diverse findings between the study of Kovnick et al. and ours may be accounted for by similar reasons as mentioned previously, i.e., larger sample size, longer length of stay and use of a regression model in our study. As we know, except for the study by Kovnick et al., no prior studies focused on the association between sex and DMC in schizophrenia. We found that sex played a key role in DMC in our study, revealing that female patients demonstrated more impaired DMC in regard to understanding, appreciation and global MacCAT-CR scores. Though some studies indicate that sex difference in clinical psychiatric presentation among schizophrenia patients may arise from the interplay between estrogen and psychosocial factors (Riecher-Rossler and Hafner, 2000; Canuso and Pandina, 2007), the reason for this outcome yet remains unclear. However, the finding that sex modifies DMC in schizophrenia has implications for the recruitment of subjects in a clinical study, and therefore warrants further exploration in the future.

Please cite this article as: Wu, B.-J., et al., Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.020i

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4.2. Factors related to the willingness to participate in a study Previous research has revealed that the willingness to participate was associated with lower levels of psychosis and cognitive impairment, better education and higher MacCAT-CR scores (Candilis et al., 2006). In contrast, in our study, patients with more severe positive symptoms and longer lengths of stay were more likely to agree to participate in the study. Additionally, negative symptoms, educational level and cognitive function were not correlated with a willingness to participate. It is also interesting to note that there were higher global MacCAT-CR scores among patients who agreed to take part in the study as reported by Candilis et al. (2006). Conversely, in the current study, the multivariate logistic regression model did not single out the DMC score as a predictor of willingness to participate. The disparity between the study by Candilis et al. and the present research might be explained by the following factors: (1) the difference in the topic of the trial, i.e., the former hypothetical study involved “the use of a novel antibiotic for a sore throat,” while our study was about “the use of a novel cognitive enhancer to improve memory”; (2) the difference in the percentage of agreement to participate: 63.5% in the former vs. 30.2% in our study; (3) the difference in sample size (45 vs. 139); and (4) the difference in subjects' nature and culture: the patients in the former study were younger (mean age¼38), included a mixture of outpatients and inpatients, and included mostly Caucasians. By contrast, our study involves mostly older (mean age¼50), longterm hospitalized Taiwanese patients; (5) our current study used regression model but the former study did not. To be noted, the relationships between the global MacCAT-CR scores and willingness of participation changed when the regression model was done. As we have mentioned, in the univariate analysis, outpatients agreeing to participate presented with higher global MacCAT-CR scores than those who chose to participate (21.5 vs. 17.7, t ¼2.04, p ¼0.043). However, similar finding was not revealed in the multivariate logistic regression model. This phenomenon might be partly explained by the fact that confounding effect related to positive symptoms comprising delusion and disorganized thought, which were significantly associated with willingness of participation in the univariate analysis shown in Table 3, was adjusted in the regression model. From Table 3, we see that patients with more severe delusions and disorganized thought were more likely to agree to participate. This finding is partly explained by the fact that delusional symptoms are associated with poor and/or delayed recognition and that disorganized symptoms are related to the impaired performance of working memory in patients with chronic schizophrenia (Schroder et al., 1996). Thus, we postulate, with an expectation of the improvement of their cognitive deficit, participants with more prominent delusions and disorganized thought were more likely to agree to participate in a hypothetical study designed for testing the efficacy of a novel medicine to alleviate cognitive deficit and impaired memory in schizophrenia patients. Furthermore, length of stay was found to be positively associated with willingness to participate in the study. One perspective anticipates that the formation of robust trust and rapport due to a long-time patient-physician relationship in the hospital may facilitate patients' agreement to participate in a clinical study. Another possible explanation is that, for institutionalized psychiatric patients, psychiatrists often have responsibility for patients' safety while also exercising authority (McCubbin and Cohen, 1999). With the best motivation to help patients, clinical paternalism presented by medical staff may strengthen patients' dependency, and patients' right to autonomy may be restricted (Chow and Priebe, 2013). Though lacking in empirical evidence, we anticipate that compared with short-stay patients or those in the community, long-term hospitalized patients may be more likely to be

influenced by staff members' paternalism and that the process of enrollment for a study is more inclined to be mistaken for “a kind suggestion or measure of good will,” thereby causing patients to lean toward choosing to take part in a study. Unexpectedly, patients on a treatment regimen of atypical antipsychotics were more likely to participate in a clinical study. This might be due to prior antipsychotic-switching experiences that gave patients a favorable response to trying atypical antipsychotics with fewer side effects or increased neurocognitive benefits (Dossenbach et al., 2004). Hence, patients were more likely to try a “novel drug” in a hypothetical study. However, we did not obtain the required evidence to test this hypothesis. Moreover, in spite of a notably wide confidence interval of standard error of odds ratio, our study found that people with a higher DDD of anticholinergics were more likely to agree to take part in the study. This phenomenon can in part be accounted for by the fact that patients with a higher anticholinergic burden have more impaired memory and are thus more likely to exhibit a lower response to cognitive training programs (Vinogradov et al., 2009). It is rational for people with a higher DDD of anticholinergics, accompanied by impaired memory, to have strong incentives to seek alternative treatments with which to improve their “memory deficit”. On the other hand, similar results may not be replicated if the aim of the hypothetical study is not related to “memory improvement” or “cognitive enhancement”. These findings have further implications for investigators. It is important to have insight into the hidden motives of those potential “novel medicine” seekers at the time of recruitment for an RCT that is related to a drug or novel intervention which may improve “some symptoms”. These seekers may consent to a study possibly due to a misconception that they will assuredly receive the “desired treatment” to alleviate their symptoms. Explicit explanations for the content of this study—and the adequate correction of misconceptions—are needed to ensure patient understanding and patients' ability to make competent decisions related to research consent. In short, the implication of our findings is that researchers should pay particular attention to people who consent to clinical research with impaired DMC, higher levels of positive symptoms, and longer lengths of stay. In addition, a more detailed explanation and disclosure should be provided to these individuals in the process of recruitment. 4.3. Strengths and limitations The strength of this study is that it is the first one to explore psychopharmacological properties related to DMC and the willingness to participate in a clinical study among long-term hospitalized patients with schizophrenia, such as the type of antipsychotics or amount of antipsychotics, sedatives and anticholinergics. Second, using a regression model to control for many confounders, we delineated the association between psychopathology and DMC outcomes. One possible limitation of this study is that the findings may only be generalized to stable longterm hospitalized schizophrenia patients. Second, we did not explore other factors related to the willingness to participate, such as prior research experience (Kaminsky et al., 2003; Candilis et al., 2006), level of perceived risk of participation (Roberts et al., 2002; Dunn et al., 2009), monetary incentives, doctors' suggestions and family preferences (Roberts et al., 2002). Lastly, rather than using an extensive neuropsychological battery composed of measures of attention, executive function, memory, and visuospatial function, our current study used MMSE—for which there are many limitations for clinical assessment. Total MMSE performance correlated significantly with only a minority of neuropsychological tests; such tests measure dementia—largely, cortical dementias such as Alzheimer's disease—and are less sensitive to non-cortical

Please cite this article as: Wu, B.-J., et al., Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.020i

B.-J. Wu et al. / Psychiatry Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎

cognitive deficits and exhibit ceiling effects in the detection of subtle brain abnormalities (Spencer et al., 2013). It should be noted that previous research found cognition assessed in most studies with a more comprehensive cognitive test battery rather than MMSE alone, is a stronger predictor of DMC than the severity of psychopathology or demographic factors (Palmer and Savla, 2007). In conclusion, long-term hospitalized schizophrenia patients who have disadvantages in many domains are likely to be vulnerable to coercion or undue influence. In our study, we found that long-stay schizophrenia patients with more severe negative symptoms performed poorly in DMC outcomes. In addition to these risk factors, females, patients with fewer years of education and those with reduced cognitive function deserve more attention

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because they are more likely to experience difficulties in decisionmaking. Patients with higher levels of positive symptoms—especially delusions and disorganized thought, longer lengths of stay, a higher burden of anticholinergics and users of atypical antipsychotics—were more likely to participate in a clinical study that aimed to “enhance cognition” or “improve memory deficit.” These findings suggest that IRBs and investigators should consider many variables for patients who require more intensive screening for impaired DMC. Mechanisms for the detection of misconceptions and adequate educational interventions to improve patients’ capabilities are needed to assist them in making competent decisions in the process of enrollment.

Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.psychres.2016.01.020.

Appendix B. MacCAT-CR and the content of the hypothetical study Numbers included in parenthesis after each section, subpart and item means the minimum score and maximum score Understanding (0–26) U1 Nature of project (0–8) (a) Research duration: 6 weeks (0–2) (b) A pill per day (0–2) (c) Blood checking per week (0–2) (d) Interview per week (0–2) U2 Primary purpose is for research (0–2) U3 Effects on individualized care (0–6) (a) Placebo (0–2) (b) Randomization (0–2) (c) Double blind (0–2) U4 Benefits/Risks/discomforts (0–8) (a) Societal benefit (0–2) (b) Personal benefit (0–2) (c) Muscle soreness (0–2) (d) Blood checking (0–2) U5 Ability to withdraw (0–2) Appreciation (0–6) A1 Object not personal benefit (0–2) A2 Possibility of reduced benefit (0–2) A3 Withdrawal possible (0–2) Reasoning (0–8) R1 Consequential reasoning (0–2) R2 Comparative reasoning (0–2) R3 Generating consequences (0–2) R4 Logical consistency (0–2) Expressing a choice (0–2)

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Please cite this article as: Wu, B.-J., et al., Psychopathology, psychopharmacological properties, decision-making capacity to consent to clinical research and the willingness.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.020i