Acceptability of Yosa, a Mobile Health Application for Between-Session Therapy Support Among Patients and Therapists: A Cross-Sectional Survey Study (Preprint)
Bibliographic record
Abstract
Background: Completion of homework, defined as therapeutic activities assigned between sessions to reinforce skills and promote behavior change, is strongly linked to therapy outcomes. Yet, homework compliance remains low, potentially due to outdated delivery methods such as paper or email. Mobile health technologies may improve engagement by digitizing therapy tasks and tracking progress. Yosa is a mobile health app designed to facilitate homework delivery and enhance engagement between sessions for patients in therapy. Objective: The primary aim of this study was to evaluate the perceived acceptability of Yosa among licensed therapists and individuals currently receiving therapy. A secondary aim was to examine whether key Technology Acceptance Model (TAM) constructs predicted attitudes toward and intention to use Yosa. Qualitative feedback was also collected to inform iterative development and future deployment. Methods: Two cross-sectional surveys were conducted: study 1 with licensed therapists (N=45) and study 2 with current therapy patients (N=96). Participants viewed video demonstrations of Yosa, learned about Yosa's features, and rated the app on TAM constructs, including perceived usefulness, perceived ease of use, perceived risk, attitude toward, and intention to use Yosa, using 0-100 scales. For most constructs, higher scores reflected more favorable evaluations, whereas lower perceived risk scores reflected more favorable evaluations. Descriptive statistics and 95% CIs were generated for each construct in both samples, with scores interpreted relative to the neutral midpoint (50). Multiple regression analyses were conducted to examine predictors of attitude and intention to use. Qualitative feedback from the surveys was analyzed thematically. Results: Therapists and patients reported generally favorable perceptions of Yosa across TAM domains. Among therapists and patients, ratings of the perceived usefulness of the homework feature, therapy journal, and overall app; perceived ease of use; attitudes toward Yosa; and intention to use were all above the midpoint. Perceived risk scores were mild to moderate in patients and moderate in therapists, respectively. Regression analyses indicated that perceived usefulness was a positive predictor of both attitude toward and intention to use Yosa across therapists and patients, while perceived risk was negatively associated with these outcomes in several models. Qualitative themes included requests for additional features, usability enhancements, and data privacy concerns. Conclusions: Therapists and patients reported generally favorable perceptions of Yosa after reviewing descriptions and video demonstrations of the platform, particularly in terms of usefulness and ease of use, supporting favorable perceptions of its potential acceptability as a digital tool for between-session therapy support. Qualitative feedback informed refinements aimed at reducing perceived risks and enhancing the intention to use.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".