The Psychosocial Impact of Migration on Family Roles and Identity
Bibliographic record
Abstract
Objective: Migration significantly affects individuals and families, reshaping identities, roles, and psychosocial well-being. This study aimed to explore the nuanced psychosocial impacts of migration on family roles and identity, seeking to understand the complexities of adjustment, identity transformation, and emotional well-being within the migratory context. Methods and Materials: Employing a qualitative research design, this study conducted semi-structured interviews with 24 participants from various migratory backgrounds. Theoretical saturation was achieved, ensuring a comprehensive exploration of the experiences and perceptions of migrants. Thematic analysis was employed to identify and categorize the primary themes and concepts emerging from the data, focusing on the psychosocial dimensions of migration. Findings: Three main themes were identified: Adjustment and Adaptation, Identity and Belonging, and Emotional and Psychological Well-being. Under Adjustment and Adaptation, categories such as Cultural Integration, Educational Challenges, Employment and Financial Stability, and Social Networks and Community Support were explored. Identity and Belonging encompassed Family Role Dynamics, Personal Identity Transformation, and Interactions with the Host Society. Emotional and Psychological Well-being included Stress and Coping Mechanisms, Intergenerational Conflicts, Loss and Grief, and Hope and Resilience, each providing insights into the emotional and psychological experiences of migrants. Conclusion: The study highlighted the profound and multifaceted psychosocial impacts of migration on individuals and families, revealing the challenges and adaptations necessary for cultural integration, the renegotiation of identity and family roles, and the emotional and psychological experiences encountered. These findings underscore the necessity for supportive policies and practices that address the complex needs of migrants, facilitating smoother integration and promoting well-being.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".