Collaborative Development of a Self-Tracking Assisted Psychotherapy Treatment Concept for Refugees With Complex Posttraumatic Stress Disorder: Participatory Action Research
Bibliographic record
Abstract
BACKGROUND: Refugees are at high risk of severe mental health challenges due to exposure to war, torture, genocide, and childhood abuse. These experiences may lead to complex posttraumatic stress disorder (CPTSD), a condition that traditional treatments such as cognitive behavioral therapy and eye movement desensitization and reprocessing often struggle to treat adequately. Cultural complexity, limited relevance of standard interventions, and low adherence to therapeutic homework pose additional challenges. Self-tracking technologies offer a promising path for personalized mental health support in patients' everyday lives, but their integration into psychotherapy remains underexplored. OBJECTIVE: This study aimed to collaboratively develop a psychotherapeutic treatment concept for refugees with CPTSD by integrating a personalized, wearable self-tracking instrument, the One Button Tracker (OBT), into psychotherapy. The OBT allows patients to track subjective experiences in the moment they occur, offering a way to bridge therapy sessions and everyday life. METHODS: This study was conducted at a Danish trauma clinic specializing in treatment for refugees and veterans with posttraumatic stress disorder and CPTSD. A Participatory Action Research approach situated within the qualitative paradigm guided the process from November 2022 to April 2024. The codevelopment of the treatment concept involved therapists, patients, clinical psychology researchers, and human-computer interaction researchers (n=21). Qualitative data were gathered through patient interviews, therapist logbooks, and peer supervision sessions, and supplemented by self-tracking data from the OBT. RESULTS: Across 17 months, the team conducted 40 peer supervision sessions, 2 collaborative workshops, and 25 interviews with 9 patients who participated in therapy for 8 to 24 sessions. Self-tracking durations ranged from 22 to 366 days, covering 1 to 14 target phenomena per patient. The OBT was found to enhance patient engagement by supporting active symptom monitoring and reinforcing therapeutic interventions outside sessions. Therapists reported that the self-tracking data provided valuable insights into patients' lived experiences, supporting more personalized and context-sensitive interventions. The flexible use of the OBT also allowed patients to shift their focus from distressing symptoms to alternative coping strategies. Furthermore, the integration of self-tracking data strengthened the therapeutic alliance by improving communication and collaboration between patients and therapists. Some technical limitations affected data collection but did not substantially hinder the therapeutic process. CONCLUSIONS: This is the first study to use a Participatory Action Research approach to codevelop a psychotherapeutic treatment concept integrating self-tracking technology for refugees with CPTSD. Findings indicate that the OBT may improve patient engagement, increase adherence to therapeutic tasks, and strengthen the therapeutic alliance. The treatment concept shows promise as a transtheoretical and transdiagnostic approach, offering a flexible and personalized model for psychotherapy. Future research should refine the concept and examine its applicability across broader clinical contexts and populations.
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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 | 0.033 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| 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".