The Effect of Contextual Risk Factors on the Effectiveness of Brief Personality‐Targeted Interventions for Adolescent Alcohol Use and Misuse: A Cluster‐Randomized Trial
Bibliographic record
Abstract
BACKGROUND: A range of school-based prevention programs has been developed and used to prevent, delay, or reduce alcohol use among adolescents. Most of these programs have been evaluated at the community-level impact. However, the effect of contextual risk factors has rarely been considered in the evaluation of these programs. The aim of this study was to investigate the potential moderating effects of 2 important contextual risk factors (i.e., socioeconomic status [SES] and peer victimization) on the effectiveness of the school-based personality-targeted interventions (Preventure program) in reducing adolescent alcohol use over a 2-year period using a cluster-randomized trial. METHODS: High-risk adolescents were identified using personality scores on the Substance Use Risk Profile Scale and randomized to intervention and control groups. Two 90-minute cognitive behavioral therapy-based group sessions targeted 1 of 4 personality risk profiles: Anxiety Sensitivity, Hopelessness, Impulsivity, or Sensation Seeking. Multilevel linear modeling of alcohol use, binge drinking, and drinking-related harm was conducted to assess the moderating effect of baseline peer victimization and SES. RESULTS: Results indicated that the Preventure program was equally beneficial to all adolescents, regardless of SES and victimization history, in terms of their alcohol outcomes and related harm. Receiving the intervention was additionally beneficial for adolescents reporting peer victimization regarding their alcohol-related harm compared to nonvictimized youth (β = -0.29, SE = 0.11, p = 0.014). CONCLUSIONS: Findings suggest that the content of personality-targeted interventions is beneficial for all high-risk youth regardless of their SES or experience of peer victimization. The current study suggests that using targeted approaches, such as targeting underlying personality risk factors, may be the most appropriate substance use prevention strategy for high-risk youth, as it is beneficial for all high-risk youth regardless of their contextual risk factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".