High‐ versus low‐intensity internet interventions for alcohol use disorders: results of a three‐armed randomized controlled superiority trial
Bibliographic record
Abstract
AIMS: To test the efficacy of a therapist-guided high-intensity internet intervention compared with an unguided low-intensity internet intervention among individuals with alcohol use disorder. DESIGN: A three-group randomized controlled trial with follow-up assessments post-treatment (12 weeks) and 6 months post-randomization (primary end-point). SETTINGS: General population sample in Sweden. PARTICIPANTS: A total of 166 on-line self-referred adults (49% males) with a score of 14 (females)/16 (males) or more on the Alcohol Use Disorders Identification Test, a preceding week alcohol consumption of 11 (females)/14 (males) or more standard drinks and an alcohol use disorder according to a diagnostic interview. INTERVENTIONS AND COMPARATORS: Both the high- (n = 72) and low-intensity internet interventions (n = 71) consisted of modules based on relapse prevention. Controls were on a waiting-list (n = 23), and were only followed until the post-treatment follow-up. Participants were randomized at a 7 : 7 : 2 ratio. MEASUREMENTS: Primary outcome was self-reported alcohol consumption in the preceding week measured as (1) number of standard drinks and (2) number of heavy drinking days at the 6-month follow-up. FINDINGS: Alcohol use disorders were largely in the severe category (74.7%), with the majority of participants having had alcohol problems for more than 5 years. Attrition was 13 and 22% at the post-treatment and 6-month follow-up, respectively. At the 6-month follow-up, an intent-to-treat analysis showed no significant differences in alcohol consumption between the high- and low-intensity interventions [standard drinks d = -0.17, 95% confidence interval (CI) = -0.50 to 0.16; heavy drinking days: d = -0.07, 95% CI = -0.40 to 0.26]. Prevalence of negative effects was somewhat low (8-14%) in both intervention groups, as was deterioration (3-5%). CONCLUSIONS: At 6-month follow-up, there were no significant differences between a therapist-guided high-intensity internet intervention and an unguided low-intensity internet intervention in reducing alcohol consumption among individuals with an alcohol use disorder.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".