“The facilitator is not a bystander”: exploring the perspectives of interdisciplinary experts on trauma research
Bibliographic record
Abstract
Objective: This study investigates the concepts, knowledge, and guiding principles that inform the practice of professionals researching trauma or working directly with individuals who have lived and living experiences of trauma. These aspects are explored with the aim of identifying current practices and potential gaps which may contribute to more trauma-informed biomarker-based research approaches. Method: The perspectives of experts were explored through semi-structured interviews with seven participants; these individuals represented trauma research, clinical practice, and trauma-informed physical activity domains. Results: A thematic analysis of the collected data revealed three focal areas highlighted by participants from all disciplines: "If I want to know trauma in the body of a person I need to know the person's language" which related to experiences of discussing trauma with clients; "What all people need is a safe place" relayed the importance of safety for participants working with the trauma expert; and "the facilitator is not a bystander" framing trauma-related work as a collaborative process between participants and their care providers. Conclusion: Evidence of formal implementation of trauma-informed practices within research settings is lacking. This gap is identified within background literature, while the importance of implementing these practices is emphasized by the participants of this study. This presents an opportunity to apply the insights of the interviewed experts toward advancing trauma research methodologies. Adapting biomarker-based research methodologies to fit a trauma- and violence-informed model may have benefits for the quality of participant experiences, research data, and knowledge of effective interventions.
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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 | 0.104 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.026 | 0.037 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".