A Web-Based Mental Health Platform for Individuals Seeking Specialized Mental Health Care Services: Multicenter Pragmatic Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Web-based self-directed mental health applications are rapidly emerging to address health service gaps and unmet needs for information and support. OBJECTIVE: The aim of this study was to determine if a multicomponent, moderated Web-based mental health application could benefit individuals with mental health symptoms severe enough to warrant specialized mental health care. METHODS: A multicenter, pragmatic randomized controlled trial was conducted across several outpatient mental health programs affiliated with 3 hospital programs in Ontario, Canada. Individuals referred to or receiving treatment, aged 16 years or older, with access to the internet and an email address, and having the ability to navigate a Web-based mental health application were eligible. A total of 812 participants were randomized 2:1 to receive immediate (immediate treatment group, ITG) or delayed (delayed treatment group, DTG) access for 3 months to the Big White Wall (BWW), a multicomponent Web-based mental health intervention based in the United Kingdom and New Zealand. The primary outcome was the total score on the Recovery Assessment Scale, revised (RAS-r) which measures mental health recovery. Secondary outcomes were total scores on the Patient Health Questionnaire-9 item (PHQ-9), the Generalized Anxiety Disorder Questionnaire-7 item (GAD-7), the EuroQOL 5-dimension quality of life questionnaire (EQ-5D-5L), and the Community Integration Questionnaire. An exploratory analysis examined the association between actual BWW use (categorized into quartiles) and outcomes among study completers. RESULTS: Intervention participants achieved small, statistically significant increases in adjusted RAS-r score (4.97 points, 95% CI 2.90 to 7.05), and decreases in PHQ-9 score (-1.83 points, 95% CI -2.85 to -0.82) and GAD-7 score (-1.55 points, 95% CI -2.42 to -0.70). Follow-up was achieved for 55% (446/812) at 3 months, 48% (260/542) of ITG participants and 69% (186/270) of DTG participants. Only 58% (312/542) of ITG participants logged on more than once. Some higher BWW user groups had significantly greater improvements in PHQ-9 and GAD-7 relative to the lowest use group. CONCLUSIONS: The Web-based application may be beneficial; however, many participants did not engage in an ongoing way. This has implications for patient selection and engagement as well as delivery and funding structures for similar Web-based interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT02896894; https://clinicaltrials.gov/ct2/show/NCT02896894 (Archived by WebCite at http://www.webcitation.org/78LIpnuRO).
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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 | 0.030 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".