Qualitative focus group study of interprofessional healthcare providers to inform the development of a virtual psychoeducational training program for the treatment of childhood interpersonal trauma
Bibliographic record
Abstract
The shortage of adequately trained healthcare providers (HCPs) able to treat adults who have experienced childhood interpersonal trauma (CIT) is a pressing concern. This study explored HCPs’ training needs for a trauma-focused psychoeducational group intervention and the potential barriers and facilitators to accessing such training. Three 1-hour focus group sessions were conducted with HCPs (n = 17) from two urban and one rural community healthcare organization serving diverse populations in Ontario, Canada, including under-housed people, women struggling with mental health and addiction, and LGBTQ+ populations. On average, participants had 2.4 years in their current role and 18.1 years of mental health field experience. Thematic analysis revealed key findings: a strong clinical need for trauma services, accessible training programs, and broadly applicable interventions relevant for diverse populations. Notably, participants emphasized the clinical advantages and increased accessibility of a virtual training programs focused on psychoeducational treatment interventions, particularly within community-based healthcare settings. This study highlights the potential of a virtual psychoeducational training programs for HCPs to address this critical gap in healthcare provision for individual with CIT. It also underscores the need to move beyond training program development and focus on implementation and sustainability of interventions in clinical practice.
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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".