An e–Mental Health Resource for COVID-19–Associated Stress Reduction: Mixed Methods Study of Reach, Usability, and User Perceptions
Bibliographic record
Abstract
BACKGROUND: COVID-19 and its public health response are having a profound effect on people's mental health. To provide support during these times, Canada's largest mental health and addiction teaching hospital (Centre for Addiction and Mental Health [CAMH]) launched the Mental Health and COVID-19 Pandemic website on March 18, 2020. This website was designed to be a nonstigmatizing psychoeducational resource for people experiencing mild to moderate distress due to COVID-19 and the public health response to the pandemic. OBJECTIVE: The aim of this study was to examine the reach, usability, and user perceptions of the CAMH Mental Health and COVID-19 Pandemic website. METHODS: This study used a mixed methods sequential explanatory design approach, which consisted of the following 2 distinct phases: (1) quantitative data collection and analysis and (2) qualitative semistructured interviews. In phase 1, we analyzed Google Analytics data to understand how many people visited the website and which were the most visited pages. We conducted a survey to identify users' sociodemographic backgrounds, and assess the usability of the website using the System Usability Scale and users' subjective stress levels using the Perceived Stress Scale (PSS-10). For phase 2, we conducted semistructured interviews to explore user experiences; user motivation, engagement, satisfaction, and perception of the stress reduction strategies; reflections of the website's functionality, ease of use, navigation, and design; and recommendations for improvement. RESULTS: Google Analytics results showed 146,978 unique users from June 2020 to March 2021. Most users were from Canada (130,066, 88.5%). Between February 20, 2021, and June 4, 2021, 152 users completed the survey. Most users identified as white, female, and having at least a college degree. Based on the PSS-10 scores, most participants were experiencing moderate to high stress when they visited the website. Users rated the usability of the website as acceptable. Ten users completed in-depth interviews between May 2021 and June 2021. Positive feedback related to the content was that the website was a trustworthy source of mental health information with helpful evidence-based stress reduction strategies. Areas for improvement included the text heavy design of the website, wider dissemination/marketing, and greater accessibility of the website to meet the needs of diverse populations. CONCLUSIONS: Adding stress reduction resources to a website from a well-respected institution may be a practical method to increase awareness and access to evidence-based stress reduction resources during times of crisis, where there is severe disruption to usual health care contacts. Efforts to ensure that these resources are more widely accessed, especially by diverse populations, are needed.
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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 | 0.027 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".