Evidence-based Interventions for Youth With Concurrent Mental Health and Substance Use Disorders: A Scoping Review: Interventions fondées sur des données probantes pour les jeunes atteints de troubles concomitants de santé mentale et liés à l’usage de substances psychoactives : une étude de la portée
Bibliographic record
Abstract
BackgroundMental health and substance use disorders typically onset during youth and commonly co-occur. Integrated treatment of two or more co-existing mental health and substance use disorders (i.e., concurrent disorders) is increasingly prevalent in real-world clinical settings. However, the depth of the evidence base on best practices remains unclear.ObjectivesThis scoping review aimed to identify, map and summarize peer-reviewed studies of interventions for concurrent disorders in youth.MethodsSix electronic health databases were systematically searched, in addition to a hand search of the reference lists of relevant systematic reviews. Only peer-reviewed studies of interventions treating concurrent disorders (i.e., simultaneous treatment of two or more disorders) in youth (10-29 years old) were eligible. Two independent reviewers conducted screening and data extraction. Results were charted according to studies employing pharmacological and non-pharmacological interventions.ResultsThirty peer-reviewed studies were included, 19 (63.3%) were randomized controlled trials (RCTs). Most studies enrolled participants with an unspecified substance use disorder (n=17, 56.7%), while alcohol use was the primary substance use disorder in seven (23.3%) studies, followed by cannabis use disorder in six (20.0%) studies. Mood disorders (e.g., depression, dysthymia) were the most common concurrent mental health disorders comprising 15 (50%) studies, followed by nine (30.0%) studies of behavioural disorders (e.g., ADHD) and five (16.7%) studies of unspecified psychiatric disorders. Eighteen (60.0%) studies (n=1,699 participants) investigated the effectiveness of various non-pharmacological interventions, while 12 (40.0%) studies examined pharmacotherapies (n=765 participants).ConclusionAlthough several RCTs were identified, substantial clinical and methodological heterogeneity was evident among the studies (e.g., patients with multiple disorders, and multi-faceted interventions). Smaller systematic reviews focused on specific interventions (e.g., behavioural therapies) and concurrent disorders (e.g., depression and substance use) may be warranted. Due to considerable heterogeneity, more RCTs are needed before conducting larger systematic reviews or meta-analyses.Plain Language Summary TitleEvidence-based interventions for youth with concurrent mental health and substance use disorders: A scoping review.
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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 | 0.025 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".