Multilevel associations between skills use, engagement, and treatment outcome in self-guided internet-delivered dialectical behavior therapy for substance use disorders
Bibliographic record
Abstract
Abstract Internet-delivered dialectical behavior therapy (iDBT) represents a scalable and accessible treatment approach for individuals with substance use disorders (SUDs), yet little is known about the mechanisms of change and the role of engagement in this format. This study examined within- and between-person associations between changes in skills-based constructs (mindfulness, DBT skills use, emotion dysregulation) and two treatment outcomes (SUD severity and functional disability) across a 12-week self-guided iDBT program. The moderating role of treatment engagement was also evaluated. 72 participants with past year SUDs were randomized to immediate or delayed iDBT and completed assessments at baseline and weeks 4, 8, and 12. Multilevel models were used to assess within- and between-person associations between skills and outcomes over time. Several indices of engagement were used including treatment acceptability, usability, and hours/days spent on iDBT. SUD severity and functional disability significantly decreased over the 12-week period. Within-person increases in emotion dysregulation were associated with higher SUD severity and disability, while higher levels of mindfulness between-persons were associated with lower disability. DBT skills were not significantly associated with outcomes. Greater within-person treatment acceptability (cognitive engagement) moderated reductions in SUD severity over time. Findings support the role of emotion dysregulation and mindfulness emerging as key correlates of treatment response. Treatment perceptions such as acceptability and usefulness may enhance outcomes, along with behavioural engagement. Future work should refine measurement of DBT skill acquisition and investigate longer-term functional impacts of digital DBT interventions. Author Summary In this study, we sought to understand potential mechanisms mechanisms of change in self-guided internet-delivered dialectical behavioural therapy (DBT) for individuals with substance use disorders. Using multilevel modeling, we evaluated the within- and between-person variation in three targets (mindfulness, DBT skills, and emotion dysregulation) over the treatment and follow-up period of 12 weeks and examined their association with treatment response (defined as substance use severity and functional disability). We then examined cognitive and behavioral facets of engagement as moderators of treatment response as well. With few DBT digital tools in existance, this study provides preliminary evidence that self-guided internet-delivered DBT tools can improve treatment targets similar to standard individual and group DBT formats. Overall, the study provides novel evidence on how several variables may enhance treatment outcome for individuals with substance use disorders, thereby informing future digital intervention trials.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".