Images that speak: A Portuguese Photovoice study on the psychosocial experience of a migrant population from Cape Verde after a first episode of psychosis
Bibliographic record
Abstract
Several migrant populations have been identified worldwide as high-risk groups for psychosis because of their experience of social adversity. Recent evidence suggests that the local contexts in which these populations live should be addressed in their complexity to take into account individual and larger societal environmental aspects. This study aimed to assess the lived experiences of a group of migrant Cape Verdean patients, who had been recently hospitalized for a first episode of psychosis in a mental health service on the outskirts of Lisbon, Portugal. The study used Photovoice, a qualitative participatory research method in which people's experiences are documented through photography. Six individuals were recruited, and five weekly sessions were conducted to collect data that were analyzed thematically. Emergent themes addressed two main categories of well-being and illness. Participant concepts of well-being were rooted in a definition of freedom encompassing cultural expression, conveyed by familiar environments and supporting communities. Cultural differences may be experienced as important obstacles for well-being and can be associated with feelings of oppression and guilt. Participants' accounts focused on positive aspects of life despite illness and on personal concepts of recovery. The study findings contribute to knowledge of the dynamics of migrants' social experience and underscore the importance of socially and culturally informed mental healthcare institutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".