{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T03:35:32Z","timestamp":1783740932955,"version":"3.55.0"},"reference-count":64,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T00:00:00Z","timestamp":1758067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Migration is a global phenomenon that significantly impacts individuals' psychological wellbeing. Migrants often face a range of psychological stressors due to displacement, adjustment challenges, and trauma. Understanding how mental health indicators cluster in this population is essential for developing effective interventions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Aims<\/jats:title><jats:p>This study aimed to identify latent psychological profiles among migrants in T\u00fcrkiye based on positive (life satisfaction, psychological wellbeing, resilience) and negative (depression, anxiety, stress) mental health indicators and to examine the demographic predictors of these profiles.<\/jats:p><\/jats:sec><jats:sec><jats:title>Sample<\/jats:title><jats:p>The study included 436 adult migrants aged 18 to 64 residing in various provinces of T\u00fcrkiye. A purposive sampling method was used to ensure diversity in characteristics such as gender, age, socioeconomic status, education level, and geographic location.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>Participants completed validated self-report measures of life satisfaction, psychological wellbeing, resilience, depression, anxiety, and stress. Confirmatory factor analyses and reliability tests were conducted. Latent Profile Analysis (LPA) was used to identify distinct psychological profiles, and multinomial logistic regression was employed to examine demographic predictors of profile membership.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Four distinct psychological profiles were identified: (1) Moderate wellbeing and moderate risk, (2) high wellbeing and low risk, (3) high risk, and (4) low risk but moderate wellbeing. Age, gender, socioeconomic status, and education level were significant predictors of profile membership, while marital status was not. Higher age and lower income increased the likelihood of being in the high-risk group, whereas higher education was associated with better psychological outcomes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The findings highlight heterogeneity in migrants' psychological adjustment and underscore the importance of considering demographic diversity in mental health interventions. Tailored, culturally sensitive approaches may enhance the wellbeing and resilience of migrant populations.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpsyg.2025.1643759","type":"journal-article","created":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T05:37:31Z","timestamp":1758087451000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Mental health profiles of migrants: a latent profile analysis of life satisfaction, psychological wellbeing, resilience and risk indicators"],"prefix":"10.3389","volume":"16","author":[{"given":"Fatma","family":"Co\u015fkun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Semra","family":"Kiye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,9,17]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1007\/s40615-019-00677-7","article-title":"Healthy immigrants? 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