Relative Effectiveness of Online Cognitive Behavioural Therapy with Anxious or Depressed Young People: Rapid Review and Meta-analysis
Bibliographic record
Abstract
Global estimates suggest that 25% and 20% of youth have reported elevated symptoms of depression and anxiety, respectively, since the beginning of the COVID-19 pandemic compared to baseline functioning (Racine et al., 2021). Cognitive behavioural therapy (CBT) has been found to significantly benefit young people experiencing anxiety and depression (Christ et al., 2020). Pandemic-related protocols have led many mental health services to shift to online platforms. We wondered about the comparative efficacy of online versus offline CBT for young people between the ages of 10-25. We responded with a rapid review and meta-analysis of eight randomized controlled trial outcomes. The sample-weighted, between-group effect size, the standardized mean difference (d), was essentially zero at longest follow-up (nine months), indicating that online and offline CBT were equally effective for youth with depression and anxiety; both online and offline groups symptom alleviation rates of approximately 90%. Recognizing a lack of diversity in the samples led us to emphasize comparative meta-analyses across the most potentially vulnerable minoritized groups in future research. This would help social workers and allied mental health providers support diverse clients and decision makers navigate the troubled clinical and social policy waters of the pandemic and its aftermath.
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
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.003 | 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".