Hurtful Gifts? Trauma and Growth Transmission Among Local Clinicians in Postearthquake Haiti
Bibliographic record
Abstract
Although working with trauma survivors can be a source of both deleterious and positive transformations in mental health professionals, little is known about the experience of clinicians in shared traumatic contexts, particularly in the Global South, where most humanitarian crises occur. In collective disasters or armed conflicts, the personal and professional experiences of mental health staff inform each other, situating the clinical space at the intersection between singular and collective spheres. Drawing on an intersubjective and socioecological perspective, this qualitative study explored the ways in which working in a shared traumatic context affected mental health and psychosocial staff in postearthquake Haiti. We interviewed 22 local mental health workers in the capital, Port-au-Prince, 2.5 years after the 2010 disaster. We coded and thematically analyzed interviews using an iterative process, based on grounded theory principles. Thematic analysis uncovered four dynamic poles in clinicians' narratives: balancing duty and desire to help, experiencing fragility and strength, negotiating separation and connection, and sharing hurt and hope. Our findings suggest clinicians considered their work mainly as a source of strength in the face of adversity, whereas experiences of trauma and growth transmissions were mutual and intimately intertwined. We discuss the complexities of clinical work in shared traumatic settings as well as the dynamic interplay between professionals' experiences of suffering and growth. We conclude with recommendations on ways to involve local mental health clinicians in postdisaster contexts while addressing the special needs that they may have to process their own trauma.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".