Does screening mode matter? A repeated cross-sectional study of computer self-administered vs. clinician-administered screening of youth substance use in pediatric primary care
Bibliographic record
Abstract
Introduction Universal youth substance use screening in pediatric primary care enables early detection and intervention, which, in turn, can help decrease the risk of problematic substance use. Screening mode [electronic self-administered survey (SA) vs. clinician-administered interview (CA)] may influence whether substance use is reported and, therefore, clinical decisions about whether and how to intervene. Methods We performed a secondary data analysis of substance use screening responses collected between 2018 and 2022 from individuals aged 12–20 years who were seen at 314 US pediatric practices utilizing the Comprehensive Health and Decision Information System (CHADIS) online clinical process support system. Patients responded to the Car, Relax, Alone, Forget, Family/Friends, and Trouble (CRAFFT), a well-validated adolescent substance use screening tool that measures past-12-month alcohol, cannabis, and other substance use (“anything else to get high”). We compared substance use rates by screening mode (SA vs. CA) using logistic regression modeling with generalized estimating equations to account for data clustering within practices and patients, controlling for US region, sex, submission year, and patient age in days. We stratified analyses by age group (12–13; 14–15; 16–17; 18–20 years) and sex (male vs. female). Results Data represented 201,134 screening responses among N = 130,688 patients. Patients were 50.9% female; 31.3% were from the Northeast, 6.7% from the Midwest, 52.7% from the South, and 9.4% from the West. Of the screening responses, 24.6% were from 12–13-year-olds, 29.5% from 14–15-year-olds, 28.7% from 16–17-year-olds, and 17.2% from 18–20-year-olds. Mode for the screening responses was 74.9% SA and 25.1% CA. Compared with CA screening, SA screening was associated with significantly higher adjusted odds of report of any substance use (adjusted odds ratio, 95% confidence interval by age group: 12–13 years 1.75, 1.43–2.15; 14–15 years 1.21, 1.11–1.33; 16–17 years 1.32, 1.24–1.41; 18–20 years 1.48, 1.39–1.58). Alcohol and cannabis, the most prevalent past-12-month substances used among all age groups, demonstrated similar patterns when examined individually. Report of other substance use only differed by screening mode among 12–13-year-olds, but overall, prevalence was low (0.1%–2.1%). Conclusion Electronic self-administered screening was associated with higher rates of reported substance use compared with clinician-administered interviews among youth being seen in primary care, suggesting that self-administered screening may improve substance use detection.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".