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; meanage=13.9; 57% White) or remotely (n=1,467; 49% female, meanage=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: 17% of adolescent participants reported any level of substance use. Youth interviewed remotely reported more negative expectancies of alcohol and cannabis. In addition, those queried remotely were less likely to endorse use), sipping alcohol, eating cannabis), and reported less curiosity or intent to try alcohol, though these differences did not survive an adjustment for multiple testing. Effect sizes ranged from small to medium. Conclusions: Preliminary evidence suggests youth completing remote visits were more likely to disclose negative expectancies toward alcohol and cannabis. Effect sizes were modest, though 37 of 39 variables examined trended toward restricted reporting during remote sessions. 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).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".