在伊朗女性样本中,基于一般健康因素的社会功能障碍预测的多层感知模型建模
Sajjad Bagheri1, Sarvenaz Taridashti2, Hojjatollah Farahani3
1Clinical Psychology, Department of Psychology, Hakim-Toos Institute of Higher Education, Mashhad, Iran.
Frontiers in psychiatry
|January 1, 2024
概括
认知功能,焦虑和抑郁症显著预测经济弱势妇女的社会功能障碍. 教育和年龄的影响力较小,突出了有针对性的支持和干预的关键领域.
科学领域:
- 社会科学 社会科学 社会科学
- 心理学 心理学 心理学
- 公共卫生 公共卫生
背景情况:
- 社会功能障碍是弱势群体的一个重大问题.
- 在经济上处于劣势,单身或寡妇女性面临独特的挑战,影响他们的福祉.
- 确定预测因素对于开发有效的干预措施至关重要.
研究的目的:
- 调查来自伊朗低经济阶层的单身或寡妇女性社会功能障碍的预测因素.
- 评估多层感知器 (MLP) 神经网络模型在预测社会功能障碍方面的性能.
主要方法:
- 一项涉及伊朗霍拉桑省780名女性 (20-70岁) 的面对面研究.
- 通过GHQ-28问卷和临床面试收集的数据超过12个月在2022年.
- 使用IBM SPSS v27和多层感知器 (MLP) 神经网络模型进行分析.
主要成果:
- 在识别社会功能障碍方面,MLP模型表现出高准确度和灵敏度.
- 认知功能,焦虑和抑郁被确定为关键预测因素.
- 在这个群体中,教育和年龄对社会功能障碍的预测重要性较低.
结论:
- 认知功能,焦虑和抑郁是影响这群人口中的社会功能障碍的关键因素.
- MLP建模对社会科学研究和预测社会功能障碍有希望.
- 研究结果支持针对弱势妇女制定有针对性的干预措施和政策.
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