卡纳塔克邦北部国家妇女之家囚犯的精神病发病率和相关的心理社会因素

Saudhamini Bhat, S. Hiremath, Wasuki Upadhyaya, S. Mangalwedhe, Mahesh Desai
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摘要

背景:性别是决定心理健康和精神疾病的一个重要因素。由于缺乏家庭支持、围绕精神疾病的耻辱、分离、情绪压力、经济依赖、家庭暴力、性侵犯和人口贩运,妇女特别容易受到精神健康障碍的影响。贫困或无家可归的妇女患精神疾病的风险高得不成比例。目的:确定精神疾病的流行程度和相关的社会心理决定因素在国营妇女之家的囚犯中。背景和设计:这是一项单中心、横断面描述性研究。招募了卡纳塔克邦北部一所州立妇女之家符合纳入和排除标准的囚犯。材料和方法:使用半结构化形式对80名参与者进行心理社会方面的评估。使用MINI-PLUS 5.0版本对囚犯进行精神疾病筛查,并使用国际疾病分类-10确认诊断。采用适当的统计工具进行分析。结果:大多数参与者(78.75%)被诊断患有某种精神疾病。最常见的精神疾病是精神病(35%),其次是情感性障碍,如重度抑郁症(15%)、双相情感障碍(10%)、躯体化障碍(7.5%)、心境恶劣(6.5%)和焦虑症(5%)。被评估的一些社会心理因素,即婚姻状况、就业状况和家庭支持不足,与精神疾病发病率显著相关。结论:本研究的重点是精神病发病率,整体临床概况,以及许多社会心理因素对这一弱势群体心理健康的影响。为了改善这一弱势群体的总体心理健康,需要更好的政策制定、及时的精神病学干预和康复。
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Psychiatric morbidity and associated psycho-social factors among inmates of state home for women in Northern Karnataka
Context: Gender is an important factor in determining mental health and mental disease. Women are particularly vulnerable to mental health disorders due to a lack of family support, stigma surrounding mental illness, separation, emotional stress, financial dependency, domestic violence, sexual assault, and human trafficking. Destitute or homeless women have a disproportionately high risk of mental illness. Aims: To determine the prevalence of psychiatric illness and related psychosocial determinants among inmates of a state-run home for women. Settings and Design: This is a single-center, cross-sectional descriptive study. Inmates of a state home for women in the northern part of Karnataka who met the inclusion and exclusion criteria were recruited. Materials and Methods: Eighty participants were evaluated using semi-structured proforma for psycho-social aspects. MINI-PLUS version 5.0 was used to screen the inmates for psychiatric morbidity and the diagnosis was confirmed using the International Classification of Diseases-10. Appropriate statistical tools were applied for the analysis. Results: Majority of the participants (78.75%) were diagnosed to have some psychiatric illness. The most common psychiatric morbidity was psychosis (35%), followed by affective disorders such as major depressive disorder (15%), bipolar disorders (10%), somatization disorders (7.5%), dysthymia (6.5%), and anxiety disorder (5%). Some of the psychosocial factors assessed, namely, marital status, employment status, and poor family support were significantly associated with psychiatric morbidity. Conclusion: This research focuses on psychiatric morbidity, overall clinical profile, and the impact of numerous psychosocial factors on mental health in this vulnerable population. To enhance the general mental health of such a vulnerable group, better policymaking, timely psychiatric interventions, and rehabilitation are required.
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