A Brief Intervention With Instant Messaging or Regular Text Messaging Support in Reducing Alcohol Use
Bibliographic record
Abstract
Importance: Alcohol use is prevalent among university students. Mobile instant messaging apps could enhance the effectiveness of an alcohol brief intervention (ABI), but the evidence is scarce. Objective: To evaluate the effectiveness of an ABI plus 3 months of mobile chat-based instant messaging support for alcohol reduction in university students at risk of alcohol use disorder. Design, Setting, and Participants: In this randomized clinical trial, 772 students at risk of alcohol use disorder (Alcohol Use Disorders Identification Test [AUDIT] score ≥8) were recruited from 8 universities in Hong Kong between October 15, 2020, and May 12, 2022. Participants were randomly assigned 1:1 to either the intervention or control group. Interventions: Both groups received the same ABI at baseline, which consisted of face-to-face or video conferencing with research nurses who delivered personalized feedback based on the participant's AUDIT risk level, along with a 12-page booklet describing the benefits of alcohol reduction and the harmful effects of alcohol on health and social well-being. The intervention group then received 3 months of chat-based instant messaging support on alcohol reduction guided by behavioral change techniques. The control group received 3 months of short message service (SMS) messaging on general health topics. Main Outcomes and Measures: All outcomes were self-reported. The primary outcome was alcohol consumption in grams per week at 6 months of follow-up. By definition, 1 alcohol unit contains 10 g of pure alcohol. Secondary outcomes at the 6-month follow-up included changes in AUDIT score, weekly alcohol consumption, intention to drink in the next 30 days, drinking frequency and any binge or heavy drinking in the past 30 days, and self-efficacy of quitting drinking. The primary analysis followed the intention-to-treat principle, and linear regression (reported as unstandardized coefficient B) and logistic regression (reported as odds ratios) were used to compare the primary and secondary outcomes between the intervention and control groups. Results: The study included 772 students (mean [SD] age, 21.1 [3.5] years; 395 females [51.2%]) who were randomly assigned to either the intervention (n = 386) or control (n = 386) group. In the intention-to-treat analysis, the intervention group had lower alcohol consumption in grams per week (B, -11.42 g [95% CI, -19.22 to -3.62 g]; P = .004), a lower AUDIT score (B, -1.19 [95% CI, -1.63 to -0.34]; P = .003), reduced weekly alcohol unit consumption (B, -1.14 [95% CI, -1.92 to -0.36]; P = .004), and less intention to drink (odds ratio, 0.66 [95% CI, 0.47 to 0.92]; P = .01) at the 6-month follow-up compared with the control group. In analyses adjusted for baseline characteristics, interacting at least once with the research nurse on the instant messaging application resulted in lower estimated alcohol consumption in grams per week (adjusted B, -17.87 g [95% CI, -32.55 to -3.20 g]; P = .01), lower weekly alcohol unit consumption (adjusted B, -1.79 [95% CI, -3.25 to -0.32]; P = .02), and a lower AUDIT score (adjusted B, -0.53 [95% CI, -1.87 to -0.44]; P = .01) at 6 months. Conclusions and Relevance: Results of this randomized clinical trial indicate that mobile chat-based instant messaging support for alcohol reduction in addition to an ABI was effective in reducing alcohol consumption in university students in Hong Kong at risk of alcohol use disorder. Trial Registration: ClinicalTrials.gov Identifier: NCT04025151.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".