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BACKGROUND: Estimates of psychiatric morbidity in the community will help service development. Participation of trained nonspecialist health-care providers will facilitate scaling up of services in resource-limited settings. AIMS: This study aimed to estimate the prevalence of priority mental health problems in populations served by the District Mental Health Program (DMHP). SETTINGS AND DESIGN: This is a population-based cross-sectional survey. MATERIALS AND METHODS: We did stratified cluster sampling of households in five districts of Kerala. Trained Accredited Social Health Activists (ASHAs) identified people who had symptoms suggestive of schizophrenia or bipolar disorder. Clinicians evaluated the information collected by the ASHAs and designated individuals as probable cases of psychosis or noncases. Screening instruments such as General Health Questionnaire-12, CAGE questionnaire, and Everyday Abilities Scale for India were used for identifying common mental disorders (CMDs), clinically significant alcohol-related problems, and functional impairment. RESULTS: We found 12.43% of the adult population affected by mental health conditions. We found CMD as most common with a prevalence of 9%. The prevalence of psychosis was 0.71%, clinically significant alcohol-related problems was 1.46%, and dementia and other cognitive impairments was 1.26%. We found informant-based case finding to be useful in the identification of psychosis. CONCLUSIONS: Mental health problems are common. Nonspecialist health-care providers can be trained to identify psychiatric morbidity in the community. Their participation will help in narrowing the treatment gap. Embedding operational research to DMHP will make scaling up more efficient.
RESUMO
BACKGROUND: Depression is the most common mental health problem in late-life. We need more information about the incidence and prevalence of major and minor syndromes of depression in older people. This will help in service development. AIMS: To estimate the prevalence of depressive disorders among community resident older people in Kerala, India and to identify factors associated with late-life depression. MATERIALS AND METHODS: Two hundred and twenty community resident older subjects were assessed for depression by clinicians trained in psychiatry. They used a symptom checklist based on International Classification of Diseases Tenth Revision (ICD-10) Diagnostic criteria for research for Depression and Montgomery Asberg Depression Rating Scale for assessment of symptoms. A structured proforma was used to assess sociodemographic characteristics and medical history. The point prevalence of depression was estimated. Univariate analysis and subsequent binary logistic regression were carried out to identify factors associated with depression. RESULTS: Prevalence of any ICD-10 (World Health Organization, 1992) depressive episode was 39.1% (95% confidence interval [CI] 32.6-45.9). There was significant correlation between depression and female gender (odds ratio [OR] 2.33; 95% CI 1.07-5.06) and history of a significant life event in the previous year (OR 2.39; 95% CI 1.27-4.49). CONCLUSION: High prevalence rate of late-life depression is indicative of high burden due to depression among older people in the community. Better awareness among primary care clinicians can result in better detection and management of late-life depression.
RESUMO
BACKGROUND: Combination of ill health and poverty poses special challenges to health care providers. Mental illness and costs are linked in terms of long-term treatment and lost productivity, and it affects social development. The purpose of the present study is to assess the economic burden of poor families when a family member needs hospitalization due to psychosis. MATERIALS AND METHODS: The information was gathered from caregivers of 100 psychotic inpatients of Medical College Hospital of Kerala during a period of 6 months. Data regarding components of expenses such as cost of medicine, laboratory investigations, food, travel, and other miscellaneous expenses during their inpatient period were collected by direct personal interview using specially designed proforma. The data were analyzed using Epi-info software. The patients below the poverty line (BPL) were compared with those above poverty line (APL). RESULTS: There was no significant difference between patients from BPL and APL in respect of amounts spent on the studied variables except for laboratory investigations during the hospital stay. CONCLUSIONS: The results showed that the studied subjects are facing financial difficulties not only due to hospitalization, but also due to the recurrent expense of their ongoing medication. The study recommends the need of financial support from the government for the treatment of psychotic patients.
RESUMO
BACKGROUND: Though there are several recommended guidelines for treating schizophrenia, in routine clinical practice, these are not followed. AIM: To conduct an audit of the prescription pattern of antipsychotic drugs in patients with schizophrenia, in a tertiary care centre in India, during a period of 1 year and compare it with Maudsley guidelines and Clinical practice guidelines for Psychiatrists in India (IPS guidelines). MATERIALS AND METHODS: Data were collected from the case records, compiled, and analyzed. The concordance or discordance with Maudsley and IPS guidelines were studied. RESULTS: The demographic variables of the patients and the prescription pattern of drugs were analyzed. The correlations between supramaximal and sub-threshold dosage of drugs to the gender, age, duration of illness, and combination of drugs were examined. CONCLUSIONS: Polypharmacy of antipsychotics is common. 31% of patients were on combination of typical and atypical antipsychotics. 4% of patients were receiving supramaximal dose of antipsychotics and all of them were on combination (P =<0.03, x(2)). 24% of patients were on sub-threshold doses. 83% were not on anticholinergic drugs.
