Treatment and prevention of common mental health problems: comparisons of four low-intensity interventions in a community outpatient setting
Bibliographic record
Abstract
Objective: Low-intensity interventions based on cognitive behavioral therapy are often used to scale up treatment volumes for common mental health problems. However, mode of delivery could have implications for outcomes. Methods: This was an observational study of adults seeking treatment in a naturalistic setting of outpatient community mental health services (N = 897). Depending on their problem description, patients were allocated to four different low-intensity interventions: group psychoeducation, group therapies, guided self-help, and one-to-one consultations. Pre-to posttreatment changes on the Patient Health Questionnaire–9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Work- and Social Adjustment Scale (WSAS) were estimated using linear mixed-effects models and propensity score weighted analyses. Results: The proportion of patients achieving clinically significant change (CSC), and time used to achieve CSC varied between interventions, with guided self-help showing the highest rates of CSC (53-66%, d = 0.62-1.04) and group psychoeducation being most time-effective intervention. For subclinical patients, guided self-help had the lowest rates of reliable deterioration (0–8%). Conclusion: Low-intensity interventions within routine community mental health care have acceptable outcomes. Mode of delivery appears to be important for rates of CSC, therapist time investment, and prevention of deterioration. Future studies should investigate which low-intensity interventions work for whom.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".