A Just-in-Time Adaptive Intervention (Shift) to Manage Problem Anger After Trauma: Co-Design and Development Study
Bibliographic record
Abstract
Background: Problem anger is common after experiencing trauma and is under-recognized relative to other posttraumatic mental health issues. Previous research has shown that digital mental health tools have significant potential to support individuals with problem anger after trauma. Objective: The objective of this study was to describe the co-design and development of a just-in-time adaptive intervention (JITAI) targeting problem anger in individuals who have experienced trauma. Methods: We used a participatory design process following the double-diamond framework. Phase 1 involved one-on-one qualitative interviews with trauma-exposed individuals with problem anger (n=10). Using an inductive approach (interpretative phenomenological analysis), we thematically coded interview data to create design principles for this population and generate potential content for the intervention. Phase 2 involved academic and clinical experts in trauma and experts in digital health reviewing the Phase 1 results and an evidence-based cognitive behavioral approach to treating anger. We then created intervention content and prototypes, which we then took to workshops with all participants for feedback, using group discussions and ratings of desirability and feasibility. Results: From Phase 1, core considerations for a JITAI included look and feel preferences, self-led and personalized support and content, and different support needed for each anger stage. A JITAI was developed with the following components: (1) personalized schedules and content onboarding; (2) psychoeducation about problem anger; (3) crisis support; (4) mood monitoring via anger check-ins; (5) self-led and personalized circuit breakers; (6) cognitive-behavioral based skills; (7) and a digital Coach embedded in the app. Some suggested features, such as social networking and sharing data with loved ones, were not pursued due to feasibility reasons relating to participant safety or technical costs. Conclusions: The resulting JITAI, termed "Shift," is the first digital mental health tool designed with end users to manage anger after trauma.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".