Morally injurious events among aid workers: examining the indirect effect of negative cognitions and self-care in associations with mental health indicators
Bibliographic record
Abstract
Introduction: Potentially morally injurious events (PMIE) are events that violate one's deeply held moral values or beliefs, and that have the potential to create significant inner conflict and psychological distress. PMIE have been recognized as an important psychological risk factor in many high-risk occupational groups. However, no study to date has investigated how PMIE relate to the mental health of aid workers. Furthermore, little is known about the mechanisms by which PMIE might be associated with mental health indicators. Methods: = 8.17). They completed an online questionnaire about their PMIE, trauma history, and mental health. A structural equation model was constructed to examine the roles of negative cognitions and subsequent self-care behaviors in the relationship between PMIE and PTSD symptoms, depression symptoms, and posttraumatic growth, above and beyond the contribution of potentially traumatic events. Results: Within the model, the indirect effect through negative cognitions fully accounted for the associations between PMIE and symptoms of PTSD and depression. For the association between PMIE and posttraumatic growth, two indirect effects emerged: the first through negative cognitions and subsequent self-care and, the second, through self-care alone. Discussion: This study highlighted PMIE as a novel psychological risk factor for aid workers and pointed to two possible mechanisms by which these events may lead to PTSD, depression, and posttraumatic growth. This study adds to the current understanding of how high-risk occupational groups adapt psychologically to PMIE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".