A Smartphone-Based Psychological Intervention for Nonsuicidal Self-Injury (Kalmer App): Protocol for a Multicenter Double-Blind Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Nonsuicidal self-injury (NSSI), defined as the deliberate, self-inflicted damage of body tissue without suicidal intent, is increasingly prevalent among adolescents and young adults and poses a major public health concern. Current treatments are often costly, difficult to access, and not tailored to the specific needs of young people. Mobile health (mHealth) interventions represent a promising avenue for scalable, accessible, and cost-effective support for NSSI, especially when combined with real-time assessments and personalized treatment strategies. OBJECTIVE: This randomized controlled trial will evaluate the effectiveness of Kalmer, a brief app-based intervention for reducing NSSI and improving emotional well-being. The study has 2 aims: (1) to evaluate a newly developed app-based intervention for adolescents and young adults engaging in NSSI and (2) to assess predictors of treatment outcomes for this app-based intervention. We hypothesize that participants receiving a mobile app-based brief intervention specifically tailored to address NSSI will show a greater reduction in NSSI frequency at the end of treatment and at follow-up than participants receiving a nonspecific app-based intervention. In this paper, we present our study protocol. METHODS: This 2-arm randomized controlled trial, lasting 6 weeks, will include 240 participants aged 14 to 24 years who engage in NSSI. The intervention app, Kalmer, was developed through iterative consultation with clinical and research experts and guided by survey results and evidence-based frameworks such as dialectical behavior therapy and cognitive behavioral therapy. The intervention will include 5 core components: distress tolerance, emotion regulation, mindfulness and self-compassion, interpersonal regulation, and problem-focused coping. The app will deliver multimedia-based ecological momentary interventions triggered by real-time ecological momentary assessments to tailor support to users' current contexts and needs. Participants are randomized to receive either the Kalmer intervention or a psychoeducational control app. The primary outcome will be NSSI frequency, assessed through self-report at baseline, 6 weeks after intervention, and at 1-month and 3-month follow-ups. RESULTS: Ethics approval was obtained in December 2022. As of January 2026, a total of 145 participants had consented to participate in the study and completed baseline assessments. Preliminary data show high app engagement and acceptability and positive user feedback regarding app usability and content. Recruitment is ongoing. CONCLUSIONS: This study will provide evidence on the effectiveness of a mobile app-based intervention for NSSI and will explore potential mechanisms of change, supporting the development of accessible digital mental health tools for adolescents and young adults. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number Registry ISRCTN63093907; https://www.isrctn.com/ISRCTN63093907. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/86413.
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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 | 0.028 | 0.030 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.089 | 0.016 |
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".