The Effects of Trauma-Informed Care Delivered by Healthcare Professionals on Patient Outcomes in Out-of-Hospital Settings: A Systematic Review
Bibliographic record
Abstract
This poster presents a systematic review exploring the effects of trauma-informed care (TIC) delivered by healthcare professionals on patient outcomes in out-of-hospital settings. The review was conducted in accordance with the PRISMA 2020 reporting guidelines. Eligible studies included all primary research designs that examined the delivery of TIC by healthcare professionals and reported patient care outcomes such as perceived benefit, efficacy, or engagement.A comprehensive search strategy was applied across multiple databases, including CINAHL, AMED, MEDLINE, Embase, and Google Scholar. The search used consistent terminology and Boolean operators relevant to trauma-informed care and prehospital or community-based healthcare.Thematic analysis was undertaken to explore patterns and relationships across the studies, and risk of bias was assessed using the Joanna Briggs Institute (JBI) critical appraisal tools. Five studies met the final inclusion criteria, comprising qualitative and mixed-methods designs conducted in the UK, USA, and Canada.Four key themes were identified: improved patient experiences, enhanced patient–professional relationships, reduced re-traumatisation and vicarious trauma among staff, and the importance of system-wide training and cultural change to embed TIC effectively. While TIC shows promise across various healthcare settings, there remains limited evidence of its impact in out-of-hospital environments.No new data were collected for this study, and ethical approval was not required. The review was carried out in accordance with established systematic review methodology to ensure rigour and transparency.This poster was presented at the <b>College of Paramedics Annual Research Conference 2025</b>, held in <b>Birmingham on Wednesday, 9th July 2025</b>.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".