Gamified Mobile Computerized Cognitive Behavioral Therapy for Japanese University Students With Depressive Symptoms: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Evidence shows that computerized self-help interventions are effective for reducing symptoms of depression. One such intervention, SPARX, is a gamified mobile computerized cognitive behavioral therapy (cCBT) developed for adolescents in New Zealand, which was shown to be as effective as usual care for young people with mild-to-moderate symptoms of depression. However, gamified cCBT has not yet been tested in Japan. OBJECTIVE: This trial is designed to investigate whether a Japanese-adapted version of SPARX improves depressive symptoms in Japanese university students with mild-to-moderate depressive symptoms. METHODS: In this 7-week, multicenter, stratified, parallel-group, superiority randomized trial, participants will be allocated to either a treatment condition (SPARX) or a wait-list control condition. SPARX is a fully automated program, which will be delivered to the mobile phone or tablet device of the participants. SPARX is designed as an interactive fantasy game to guide the user through seven modules that teach key CBT strategies. All participants will be recruited from universities via advertisements on online bulletin boards, the campus newspaper, and posters. Participants in the treatment condition will use the SPARX program weekly. The primary outcome is the reduction of depressive symptoms (using Patient Health Questionnaires-9) measured at baseline and weekly: once after the 7-week intervention and once at a 1-month follow-up. Secondary outcomes include satisfaction with the program and satisfaction with life, measured by the Satisfaction With Life Scale; positive and negative moods, measured by the Profile of Mood States Second Edition; social functioning, measured by the EuroQol Instrument; rumination, measured by the Ruminative Responses Scale; and coping, measured by the Brief Coping Orientation to Problem Experienced Inventory. RESULTS: This study received funding from The Research Institute of Personalized Health Sciences, Health Sciences University of Hokkaido, and obtained institutional review board approval in September 2019. Data collection began in April 2019. CONCLUSIONS: Results of this trial may provide further evidence for the efficacy of gamified cCBT for the treatment of depression and, specifically, provide support for using SPARX with Japanese university students. TRIAL REGISTRATION: Japan Primary Registries Network UMIN000034354; https://tinyurl.com/uu7xd77. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15164.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".