Outpatient Young Adults with Concurrent Disorders: A Naturalistic Study of Clinical Characteristics and DBT Skills Training Outcomes
Bibliographic record
Abstract
INTRODUCTION: This naturalistic study characterized clinical profiles of outpatient young adults with concurrent substance use and nonsubstance mental health symptoms in addition to evaluating reach and outcomes of a dialectical behaviour therapy skills training group. METHODS: Descriptive statistics were generated to characterize demographic and clinical profiles of young adults (N = 612) who initiated services at a psychiatric specialty clinic between June 2016 and January 2020. Chi-square, independent t-tests and logistic regression models were used to examine factors associated with engagement with dialectical behaviour therapy skills training group. Paired samples t-tests were utilized to evaluate psychiatric symptom and functional impairment outcomes associated with group completion. RESULTS: Self-report measures indicated a high rate of substance use and co-occurring nonsubstance mental health concerns in the sample as a whole. Young adults who engaged in group programming differed significantly from those who did not on several clinical and demographic variables; however, no variables were significantly associated with group engagement in regression models. While referral and attendance rates were relatively low (30.6% and 15.4% of total sample), for those completing dialectical behaviour therapy skills training group we observed positive pre-post change outcomes on measures of psychiatric symptoms and functioning (d = 0.35-0.69). CONCLUSION: Taken together, these findings provide initial support for offering dialectical behaviour therapy skills training as an adjunctive intervention for young adults with concurrent disorders. Future research identifying factors for enhancing engagement and examining outcome with more controlled conditions are warranted.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".