Adherence to Psychological First Aid after Exposure to a Traumatic Event at Work among EMS Workers: A Qualitative Study
Bibliographic record
Abstract
Managing post-traumatic stress reactions in the first few days after exposure to a potentially traumatic event in the course of one's work remains a challenge for first responder organizations such as Emergency Medical Services (EMS). Psychological First Aid (PFA) is an evidence-informed approach to reducing initial distress and promoting short- and long-term coping strategies among staff in the aftermath of exposure. PFA provided by peer helpers is considered a promising solution for first responder organizations. Unfortunately, first responders may encounter stigma and barriers to mental health care. Therefore, a deeper investigation is needed regarding adherence over time to implemented PFA intervention. The purpose of this study is to qualitatively explore factors that influence adherence to PFA intervention of recipients and peer helpers. EMS workers (n = 11), working as PFA peer helpers for one year, participated in semi-structured interviews. Data were analyzed using thematic analysis; intercoder reliability (κ = 0.91) was also used. Researchers identified four themes and 11 subthemes influencing adherence to PFA intervention: (1) individual perceptions and attitudes of peer helpers and recipients about pfa intervention; (2) perceived impacts on peer helpers and recipients; (3) organizational support to pfa intervention; and (4) congruence with the occupational culture. Study findings herein suggest that it is conceivable to act on various factors to improve adherence to PFA intervention among peer helpers and recipients within EMS organization. This could lead to enhanced understanding of the challenges involved in sustaining a peer led PFA program for first responders.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".