A web-based mental health platform in individuals seeking specialized mental health care services: multi-centre pragmatic randomized controlled trial (Preprint)
Bibliographic record
Abstract
BACKGROUND Web-based self-directed mental health applications are rapidly emerging as a solution to health service gaps and unmet needs for information and support. OBJECTIVE The aim of this study was to determine if a multi-component web-based moderated mental health application could benefit individuals with mental health symptoms severe enough to warrant specialized mental health care. METHODS A multi-centre, 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, 16 years of age 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. 812 participants were randomized 2:1 to receive immediate (ITG) or delayed (DTG) access for 3 months to the Big White WallTM, a web-based multi-component mental health intervention based in the United Kingdom and New Zealand. The primary outcome was total score on the Recovery Assessment Scale, revised (RAS-r) measuring 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 EQ-5D-5L, and the Community Integration Questionnaire (CIQ). 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 446 (55%) at 3 months; 48% of ITG participants, and 69% of DTG participants. Only 58% 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. CLINICALTRIAL Clinicaltrials.gov NCT02896894. Registered on 31 August 2016 (retrospectively registered). https://clinicaltrials.gov/ct2/show/NCT02896894
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".