A Comparison of Remote Versus In-Person Assessments of Substance Use and Related Constructs Among Adolescents
Bibliographic record
Abstract
Objective. Underreporting of adolescent substance use is a known issue, with format of assessment (in-person vs. remote) a potentially important factor. We investigate whether being assessed remotely (via phone or videoconference) versus in-person affects youth report of substance use patterns, attitudes, and access, hypothesizing remote visits would garner higher levels of substance use reporting and more positive substance use attitudes.Methods. We used the Adolescent Brain and Cognitive DevelopmentSM [ABCD] Study data between 2021-2022 during the COVID-19 pandemic. Participants chose whether to complete assessments in-person (n=615; 49% female; mean age=13.9; 57% White) or remotely (n=1,467; 49% female, mean age=13.7; 49% White). Regressions predicted substance use patterns,attitudes, and access, by visit format, controlling for relevant sociodemographic factors. Effect sizes and standardized mean differences are presented.Results. While 17% of adolescent participants reported any level of substance use, those queried remotely were less likely to endorse use (OR=0.76, p=.04), sipping alcohol (OR=0.78, p=.08), or eating cannabis (OR=0.51, p=.05). Similarly, youth interviewed remotely reported less curiosity or intent to try alcohol, and more negative attitudes and expectancies around alcohol and, at times, cannabis use, with small to medium effect sizes.Conclusions. Preliminary evidence suggests youth completing remote visits were less likely to disclose any substance use, less e-cigarette access, less curiosity or intent to use alcohol, and more negative attitudes toward alcohol and cannabis. Notably, effect sizes were modest. Thus, format of substance use assessment should be controlled for, but balanced by other study needs (e.g., increasing accessibility of research to all sociodemographic groups).
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".