Research experience and career factors in relation to mental health problems: Prevalence, risk factors, and machine learning-based predictive estimates.

Background: Mental health issues, including depression, anxiety, and insomnia, are increasingly prevalent among university students and graduates, especially those involved in academic research. The impact of research-related characteristics on mental health remains underexplored. Aim: We examined t...

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Publicado en:	International Journal of Social Psychiatry Vol. 72; no. 2; pp. 294 - 311
Autores principales:	Mamun, Mohammed A., Huraira, Md. Abu, Begum, Momotaj, Hasan, MD. Hamed, Khan, Md. Maruf, Faruk, Md. Omar, Kibria, Mohammad, Aktar, Sabrina, Muntashir, Naoroj, Das, Pronab, Rahman, Sadikur, Siddiky, Aysha, Hasan, Md. Mehedi, Wazed, Rubiya, Das, Milan Kumar, Akter, Sharmin, Haque, Anonna, Ferdaus, Jannatul, Hasan, Md Emran, ALmerab, Moneerah Mohammad
Formato:	Artículo
Publicado:	Sage Publications Inc. Mar2026
Materias:	Bangladesh Mental illness risk factors Mental depression risk factors Mental health Anxiety Experience Students College graduates Psychology of college students Social support Psychosocial factors Vocational guidance Mental depression Disease risk factors Psychiatric epidemiology Risk assessment Random forest algorithms Scale analysis (Psychology) Boosting algorithms Research funding Prediction models Cronbach's alpha Data analysis Receiver operating characteristic curves Insomnia Statistical sampling Questionnaires Logistic regression analysis Disease prevalence Descriptive statistics Severity of illness index Chi-squared test Support vector machines Research Geographic information systems Statistics Machine learning Data analysis software Confidence intervals Comparative studies
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