A systematic review and meta-analysis on the efficacy of Internet-delivered behavioral activation
Bibliographic record
Abstract
BACKGROUND: Behavioral activation (BA) is an evidence-based treatment for depression which has attracted interest and started to accumulate evidence for other conditions when delivered face-to-face. Due to its parsimoniousness, it is suitable to be delivered via the Internet. The goal of this systematic review and meta-analysis was to examine evidence from randomized controlled trials (RCTs) to determine the efficacy of Internet-based BA and assess the quality of this evidence. METHODS: Studies were identified from electronic databases (EMBASE, ISI Web of Knowledge, Medline, CINHAL, PsychINFO, Cochrane) and reference lists of included studies. Two reviewers independently screened articles for inclusion and extracted data. They assessed the quality of evidence for each outcome using The Grading of Recommendations Assessment, Development and Evaluation framework. RESULTS: Nine RCTs on different forms of depression were included with 2157 adult participants. Random effects meta-analyses showed that in non-clinical settings, guided Internet-based BA was non-inferior to other forms of behavioral therapy and mindfulness (mainly very low to low quality evidence) and superior to physical activity (very low quality evidence), psychoeducation/treatment as usual (moderate quality evidence) and waitlist (low quality evidence) at reducing depression and anxiety outcomes at post-treatment and short follow-up. LIMITATIONS: The poor quality of some of the findings means that results should be cautiously interpreted. CONCLUSIONS: Evidence for the efficacy of Internet-based BA as a treatment for depression is promising. However, high quality studies with longer follow-ups are needed to increase confidence in findings and determine its efficacy in clinical settings and other conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".