Supporting your colleagues: yes, but how? Exploring the positive and negative support offered by colleagues to child protection workers exposed to a potentially traumatic event at work
Bibliographic record
Abstract
Background Child protection workers (CPWs) are frequently exposed to potentially traumatic events (PTE) at work. These events have many psychological and organizational consequences. Without adequate intervention, these effects can persist and worsen over time. Social support is known to be a determining factor in the recovery of individuals exposed to a PTE, particularly support from colleagues in the work setting. However, little is known about how this support from colleagues manifests itself after a PTE or how it is perceived by the individual involved. Objective The current study sought to explore the support offered by colleagues after a PTE and identify supportive actions perceived as either positive or negative by the victims Method Semi-structured interviews were conducted with 30 CPWs in the Montreal area of Canada, all of whom had been exposed to a PTE within the previous 0-30 days. The interviews were analyzed using thematic analysis Results Supportive actions reported by participants fell into four categories: emotional, instrumental, informational or evaluation support. Regardless of whether participants received one or multiple types of support, emotional support emerged as the most appreciated according to the participants’ experiences. Positive support offered by colleagues aligned with the key principles of early post-traumatic intervention, while negative support was mainly explained by a lack of organizational resources and a work-culture that trivialized violence. Conclusion. The study suggests that organizations should prioritize approaches that recognize and validate emotions before introducing other types of support.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".