A randomized trial of brief web-based prevention of unhealthy alcohol use: Participant self-selection compared to a male young adult source population
Bibliographic record
Abstract
BACKGROUND: How much a randomized controlled trial (RCT) sample is representative of or differs from its source population is a challenging question, with major implications for generalizability of results. It is particularly crucial for freely-available web-based interventions tested in RCTs since they are designed to reach broad populations and could increase health disparities if they fail to reach the more vulnerable individuals. We assessed the representativeness of a sample of participants in a primary/secondary prevention web-based brief intervention RCT in relation to its source population. Then we compared those recruited to those not recruited in the RCT. METHODS: There is a mandatory army recruitment process in Switzerland at age 19 for men. Between August 2010 and July 2011, 12,564 men (source population) attended two recruitment centers and were asked to answer a screening questionnaire on alcohol use. Among 11,819 (94.1%) who completed it, 7027 (59.5%) agreed to participate in a longitudinal cohort study with regular assessments. In 2012, these participants were invited to a web-based brief intervention RCT. Participation was not dependent on the presence or quantity of alcohol use. We assessed the representativeness of the RCT sample in relation to the source population and compared participants recruited/not recruited in the RCT with respect to education level and alcohol use. RESULTS: < 0.0001). Differences on alcohol use measures and education were similarly found when those recruited in the RCT were compared to those who were not, including in a multivariable model, showing independent associations between less unhealthy alcohol use and higher education and recruitment in the RCT. CONCLUSIONS: RCT participants differed from other members of the source population, with those participating in the RCT having higher prevalence of any alcohol use but lower levels of consumption and lower prevalence of indicators of unhealthy alcohol use. Individuals with higher education were overrepresented in the RCT sample. Selection bias may exist at both ends of the drinking spectrum and individuals with some indicators of greater vulnerability were less likely to participate. Results of web-based studies may not adequately generalize to the general population.Trial registration: The trial was registered at current controlled trials: ISRCTN55991918.
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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".