Enhancing Distress Tolerance Skills in Adolescents With Anorexia Nervosa Through the BALANCE Mobile App: Feasibility and Acceptability Study
Bibliographic record
Abstract
Background: Anorexia nervosa is a severe psychiatric disorder with high morbidity and mortality, particularly among adolescents. Family-based treatment (FBT) is the leading evidence-based intervention for adolescent anorexia nervosa, involving parents in renourishment and behavior interruption. Despite its effectiveness, challenges in distress tolerance and emotion regulation during high-stress situations, such as mealtimes, contribute to suboptimal treatment outcomes, with only 35% to 50% of adolescents achieving full recovery. Enhancing distress tolerance skills during FBT may improve treatment responses and recovery rates. The BALANCE mobile app was developed to address this need, offering real-time, dialectical behavior therapy (DBT)-based distress tolerance skills to support adolescents and families during mealtimes. Objective: Our aim was to explore the feasibility and acceptability of a mobile app designed to deliver distress tolerance skills to adolescents with and adolescents without anorexia nervosa. When fully programmed and optimized, we plan to use the mobile app to improve distress tolerance during mealtimes for adolescents with anorexia nervosa undergoing FBT. Methods: BALANCE was developed collaboratively with Stanford University's Center for Biodesign, leveraging the expertise of clinical psychologists and using biodesign student input and the Stanford Spezi ecosystem. The app underwent an iterative development process, with feedback from adolescent users. The initial feasibility and acceptability of the app were assessed through self-reported questionnaires and structured interviews with 24 adolescents aged 12 to 18 years, including 4 diagnosed with anorexia nervosa and 20 healthy controls. Adolescents with anorexia nervosa specifically used the app during mealtimes, and healthy controls used it as needed. Participants assessed the app's usability, perceived effectiveness, and its impact on their distress tolerance. Results: The app demonstrated high usability and acceptability. Of 24 participants, 83% (n=20) reported enjoying the app, 88% (n=21) would recommend it to peers, and 100% (n=24) found it user-friendly. Adolescents with anorexia nervosa reported that BALANCE helped them manage stressful mealtimes more effectively, highlighting features such as guided meditation, breathing exercises, and gamification elements as particularly effective. Healthy controls provided additional feedback, confirming the app's broad appeal to the target audience and potential scalability. Preliminary findings suggest that BALANCE may enhance distress tolerance in adolescents with and adolescents without anorexia nervosa. Conclusions: BALANCE shows promise as an innovative mobile health intervention for enhancing distress tolerance in adolescents with anorexia nervosa. Its user-friendly design and tailored DBT-based skills make it a feasible tool for integration into FBT. Future research should explore its integration into clinical practice and its impact on treatment outcomes. As distress tolerance skills are relevant to a range of mental health conditions, future research may also expand BALANCE's application to broader adolescent 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".