One-year recovery rates for young people with depression and/or anxiety not receiving treatment: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: To systematically review 1-year recovery rates for young people experiencing depression and/or anxiety who are not receiving any specific mental health treatment. DESIGN: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, Embase, PsycINFO, Web of Science and Global Health were searched for articles published from 1980 through to August 2022. ELIGIBILITY CRITERIA: Articles were peer-reviewed, published in English and had baseline and 1-year follow-up depression and/or anxiety outcomes for young people aged 10-24 years without specific treatment. DATA EXTRACTION AND SYNTHESIS: Three reviewers extracted relevant data. Meta-analysis was conducted to calculate the proportion of individuals classified as recovered after 1 year. The quality of evidence was assessed by the Newcastle-Ottawa Scale. RESULTS: Of the 17 250 references screened for inclusion, five articles with 1011 participants in total were included. Studies reported a 1-year recovery rate of between 47% and 64%. In the meta-analysis, the overall pooled proportion of recovered young people is 0.54 (0.45 to 0.63). CONCLUSIONS: The findings suggest that after 1 year about 54% of young people with symptoms of anxiety and/or depression recover without any specific mental health treatment. Future research should identify individual characteristics predicting recovery and explore resources and activities which may help young people recover from depression and/or anxiety. PROSPERO REGISTRATION NUMBER: CRD42021251556.
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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 | 0.030 | 0.076 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.049 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".