Video Game to Attenuate Pandemic-Related Stress From an Equity Lens: Development and Usability Study (Preprint)
Bibliographic record
Abstract
BACKGROUND The emergence of the novel coronavirus (COVID-19) has introduced additional pressures on an already fragile mental health care system due to a significant rise in depression, anxiety, and stress among Canadians. Although cognitive behavioral therapy (CBT) is known to be an efficacious treatment to reduce such mental health issues, few people have access to CBT in an engaging and sustainable manner. To address this gap, a collaboration between the Centre for Addiction and Mental Health (CAMH) and the National Research Council of Canada (NRC) developed CBT-based self-led, online, clinician-tested modules in the form of a video game, named Legend of Evelys, and evaluated its usability in the attenuation of a COVID-19–related increase in stress. OBJECTIVE We here present the conceptualization and design of new self-care modules in the form of a video game, its implementation in a technological infrastructure, and inclusivity and privacy considerations that informed the development. A usability study of the modules was performed to assess the video game’s usability, user engagement, and user perceptions. METHODS The development of the video game involved establishment of a technology infrastructure for secure implementation of the software for the modules and a clinician-led assessment of the clinical utility of these modules through two “whiteboard” sessions. The usability study was informed by a mixed methods sequential explanatory design to evaluate the intervention of the mobile app through two distinct phases: quantitative data collection using in-app analytics data and two surveys, followed by qualitative data collection by semistructured interviews. RESULTS A total of 32 participants trialed the app for 2 weeks. They used the video game an average of six times and rated the game as “good” based on the Systems Usability Scale score. In terms of stress reduction, the study demonstrated a significant difference in the participants’ Perceived Stress Scale score at baseline (mean 22.14, SD 6.187) compared with that at the 2-week follow-up (mean 18.04, SD 6.083; t27=3.628, P=.001). Qualitative interviews helped participants identify numerous functionality issues and provided specific recommendations, most of which were successfully integrated into the video game for future release. CONCLUSIONS Through this collaboration, we have established that it is possible to incorporate CBT exercises into a video game and have these exercises adopted to address stress. While video games are a promising strategy to help people with their stress and anxiety, there is a further need to examine the real-world effectiveness of the Legend of Evelys in reducing anxiety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".