The Effects of Online Self-management Interventions for Patients With Mood Disorders: Protocol for a Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Self-management has become important as a complementary approach to the recovery of patients with mood disorders, and the need for a remote intervention program has been revealed in relation to the COVID-19 pandemic. OBJECTIVE: The aim of this review is to systematically review the studies for evidence on the effects of online self-management interventions based on cognitive behavioral therapy or psychoeducation for patients with mood disorders and to verify the statistical significance of the effectiveness of the interventions. METHODS: A comprehensive literature search will be conducted using a search strategy in nine electronic bibliographic databases and will include all randomized controlled trial studies conducted up through December 2021. In addition, unpublished dissertations will be reviewed to minimize publication bias and to include a wider range of research. All steps in selecting the final studies to be included in the review will be performed independently by two researchers, and any discrepancies will be resolved through discussion. RESULTS: Institutional review board approval was not required because this study was not conducted on people. Systematic literature searches, data extraction, narrative synthesis, meta-analysis, and final writing of the systematic review and meta-analysis are expected to be completed by 2023. CONCLUSIONS: This systematic review will provide a rationale for the development of web-based or online self-management interventions for the recovery of patients with mood disorders and will be used as a clinically meaningful reference in terms of mental health management. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45528.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| grok | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| opus | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.073 | 0.079 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.020 | 0.031 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.075 | 0.008 |
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, unvalidatedLabeled directly by 3 models reading the full record.
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".