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      Effectiveness of a community-based intervention for people with schizophrenia and their caregivers in India (COPSI): a randomised controlled trial

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          Observational evidence suggests that community-based services for people with schizophrenia can be successfully provided by community health workers, when supervised by specialists, in low-income and middle-income countries. We did the COmmunity care for People with Schizophrenia in India (COPSI) trial to compare the effectiveness of a collaborative community-based care intervention with standard facility-based care.


          We did a multicentre, parallel-group, randomised controlled trial at three sites in India between Jan 1, 2009 and Dec 31, 2010. Patients aged 16–60 years with a primary diagnosis of schizophrenia according to the tenth edition of the International Classification of Diseases, Diagnostic Criteria for Research (ICD-10-DCR) were randomly assigned (2:1), via a computer-generated randomisation list with block sizes of three, six, or nine, to receive either collaborative community-based care plus facility-based care or facility-based care alone. Randomisation was stratified by study site. Outcome assessors were masked to group allocation. The primary outcome was a change in symptoms and disabilities over 12 months, as measured by the positive and negative syndrome scale (PANSS) and the Indian disability evaluation and assessment scale (IDEAS). Analysis was by modified intention to treat. This study is registered as an International Standard Randomised Controlled Trial, number ISRCTN 56877013.


          187 participants were randomised to the collaborative community-based care plus facility-based care group and 95 were randomised to the facility-based care alone group; 253 (90%) participants completed follow-up to month 12. At 12 months, total PANSS and IDEAS scores were lower in patients in the intervention group than in those in the control group (PANSS adjusted mean difference −3·75, 95% CI −7·92 to 0·42; p=0·08; IDEAS −0·95, −1·68 to −0·23; p=0·01). However, no difference was shown in the proportion of participants who had a reduction of more than 20% in overall symptoms (PANSS 85 [51%] in the intervention group vs 44 [51%] in the control group; p=0·89; IDEAS 75 [48%] vs 28 [35%]). We noted a significant reduction in symptom and disability outcomes at the rural Tamil Nadu site (−9·29, −15·41 to −3·17; p=0·003). Two patients (one in each group) died by suicide during the study, and two patients died because of complications of a road traffic accident and pre-existing cardiac disease. 18 (73%) patients (17 in the intervention group) were admitted to hospital during the course of the trial, of whom seven were admitted because of physical health problems, such as acute gastritis and vomiting, road accident, high fever, or cardiovascular disease.


          The collaborative community-based care plus facility-based care intervention is modestly more effective than facility-based care, especially for reducing disability and symptoms of psychosis. Our results show that the study intervention is best implemented as an initial service in settings where services are scarce, for example in rural areas.


          Wellcome Trust.

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          Most cited references 25

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          The positive and negative syndrome scale (PANSS) for schizophrenia.

          The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
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            Internalized stigma of mental illness: psychometric properties of a new measure.

            The study evaluated the Internalized Stigma of Mental Illness (ISMI) scale, designed to measure the subjective experience of stigma, with subscales measuring Alienation, Stereotype Endorsement, Perceived Discrimination, Social Withdrawal and Stigma Resistance. The ISMI was developed in collaboration with people with mental illnesses and contains 29 Likert items. The validation sample included 127 mental health outpatients. Results showed that the ISMI had high internal consistency and test-retest reliability. Construct validity was supported by comparisons against scales measuring related constructs with the same methodology. As expected, the ISMI had positive correlations with measures of stigma beliefs and depressive symptoms, and it had negative correlations with measures of self-esteem, empowerment and recovery orientation. Factor analyses of the joint set of items from the ISMI and each scale supported the distinction between constructs. Having a validated measure of internalized stigma may encourage clinicians to include stigma reduction as a verifiable treatment goal in addition to symptom reduction.
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              Design and analysis of clinical trials with clustering effects due to treatment.

              Where patients receive therapy as a group, there are good theoretical reasons to believe that variation in the outcome will be smaller for patients treated in the same group than for patients treated in different groups. Similarly, where different therapists treat different groups of patients, outcome for patients treated by the same therapist may differ less than outcome for patients treated by different therapists. Clinical trials evaluating such therapies need to consider this potential lack of independence. As with cluster-randomized trials, this has implications for the precision of treatment effects estimates and statistical power. There are nevertheless differences between clustering due to the organization of treatment and that due to randomization. In cluster-randomized trials the distribution of cluster sizes in each treatment arm should be similar as a consequence of randomization unless there is differential loss to follow-up. With clustering due to therapy group or therapist, cluster size may differ systematically between treatment arms, due to size of therapy groups or differing health professional caseload. Intra-cluster correlation may also differ between treatment arms. The implications of differential cluster size and intracluster correlation for design and analysis will be illustrated by data from two trials, the first comparing nurse practitioner care with general practitioner care, and the second comparing a group therapy with individual treatment as usual. The special case where a group therapy or therapist is compared with an unclustered treatment is examined in detail using a simulation study. The implications of differential clustering effects for sample size and power are addressed. It is argued that the design and analysis of this type of trial should take account of possible heterogeneity in cluster size and intracluster correlation.

                Author and article information

                Lancet Publishing Group
                19 April 2014
                19 April 2014
                : 383
                : 9926
                : 1385-1394
                [a ]Sangath, Goa, India
                [b ]Schizophrenia Research Foundation, Chennai, India
                [c ]Parivartan, Satara, India
                [d ]King's College London, Institute of Psychiatry, Health Service and Population Research Department, London, UK
                [e ]Centre for Global Mental Health, Health Service and Population Research Department, London, UK
                [f ]Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
                [g ]Schizophrenia Research Foundation, Chennai, India
                [h ]Medical Research Council Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, UK
                [i ]Centre for Global Mental Health, London School of Hygiene & Tropical Medicine, London, UK
                [j ]Public Health Foundation of India, New Delhi, India
                Author notes
                [* ]Correspondence to: Prof Graham Thornicroft, Centre for Global Mental Health, Institute of Psychiatry, King's College London, London SE5 8AF, UK graham.thornicroft@ 123456kcl.ac.uk

                Joint last authors

                © 2014 Chatterjee et al. Open Access article distributed under the terms of CC BY-NC-ND

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