Multilayer perceptron modeling for social dysfunction prediction based on general health factors in an Iranian women sample.

Autor:	Bagheri S; Clinical Psychology, Department of Psychology, Hakim-Toos Institute of Higher Education, Mashhad, Iran., Taridashti S; Industrial and Organizational Psychology, Department of Psychology, Montclair State University, Montclair, NJ, United States., Farahani H; Department of Psychology, Tarbiat Modares University, Tehran, Iran., Watson P; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom., Rezvani E; Clinical Psychology, Department of Psychology, Hakim-Toos Institute of Higher Education, Mashhad, Iran.
Jazyk:	angličtina
Zdroj:	Frontiers in psychiatry [Front Psychiatry] 2023 Dec 14; Vol. 14, pp. 1283095. Date of Electronic Publication: 2023 Dec 14 (Print Publication: 2023).
DOI:	10.3389/fpsyt.2023.1283095
Abstrakt:	In the year 2022, this research conducted an in-person study involving 780 single or widowed women, aged between 20 and 70, falling within the bottom three economic deciles and possessing varying levels of education. All participants held educational qualifications below a high school diploma and were beneficiaries of charitable financial support in Khorasan province, Iran. The study aimed to investigate the predictive factors of social dysfunction in this specific demographic. Data collection spanned a 12-month period throughout 2022, with participants completing the GHQ-28 questionnaire during their visits to the charity office. Clinical in-person interviews were also conducted to gather comprehensive data. Data analysis was carried out using IBM SPSS version 27. The research employed a Multilayer Perceptron (MLP) neural network model, considering an extensive set of input factors and covariates. These factors included cognitive functioning, anxiety, depression, age, and education levels. The MLP model exhibited robust performance, achieving high overall accuracy and sensitivity in identifying cases of high social dysfunction. The findings emphasized the significance of cognitive functioning, anxiety, and depression as pivotal predictors of social dysfunction within this specific demographic, while education and age displayed relatively lower importance. The normalized importance scores provided a relative measure of each covariate's impact on the model's predictions. These results furnish valuable insights for the development of targeted interventions and evidence-based policies aimed at addressing social dysfunction and promoting societal well-being among economically disadvantaged, single or widowed women. Notably, the research underscores the potential of MLP modeling in social science research and suggests avenues for further research and refinement to enhance the model's predictive accuracy, particularly for cases of low social dysfunction. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MB declared a past collaboration with the authors to the handling editor. (Copyright © 2023 Bagheri, Taridashti, Farahani, Watson and Rezvani.)
Databáze:	MEDLINE
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