The development and evaluation of a virtual, asynchronous, trauma-focused treatment program for adult survivors of childhood interpersonal trauma
Bibliographic record
Abstract
BACKGROUND: The long-term mental and physical health implications of childhood interpersonal trauma on adult survivors is immense, however, there is a lack of available trauma-focused treatment services that are widely accessible. This study, utilizing a user-centered design process, sought feedback on the initial design and development of a novel, self-paced psychoeducation and skills-based treatment intervention for this population. AIMS: To explore the views and perspectives of adult survivors of childhood interpersonal trauma on the first two modules of an asynchronous trauma-focused treatment program. METHODS: Fourteen participants from our outpatient hospital service who completed the modules consented to provide feedback on their user experience. A thematic analysis of the three focus groups was conducted. RESULTS: Four major themes emerged from the focus groups: (1) technology utilization, (2) module content, (3) asynchronous delivery, and (4) opportunity for interactivity. Participants noted the convenience of the platform and the use of multimedia content to increase engagement and did not find the modules to be emotionally overwhelming. CONCLUSIONS: Our research findings suggest that an asynchronous virtual intervention for childhood interpersonal trauma survivors may be a safe and acceptable way to provide a stabilization-focused intervention on a wider scale.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".