Does providing a brief internet intervention for hazardous alcohol use to people seeking online help for depression reduce both alcohol use and depression symptoms among participants with these co-occurring disorders? Study protocol for a randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Hazardous alcohol consumption is common among people experiencing depression, often acting to exacerbate depressive symptoms. While many people with these co-occurring disorders do not seek face-to-face treatment, they do seek help online. There are effective internet interventions that target hazardous alcohol consumption or depression separately but none that combine these online interventions without the involvement of a therapist. In order to realise the potential of internet interventions, we need to develop an evidence base supporting the efficacy of internet interventions for co-occurring depression and hazardous alcohol use without any therapist involvement. This study aims to evaluate the effects on drinking, and on depressive symptoms, of combining an internet intervention targeting hazardous alcohol consumption with one for depression. METHODS AND ANALYSIS: A double blinded, parallel group randomised controlled trial will be used. Participants with current depression who also drink in a hazardous fashion (n=986) will be recruited for a study to 'help improve an online intervention for depression'. Participants will be randomised either to receive an established online intervention for depression (MoodGYM) or to receive MoodGYM plus a brief internet intervention for hazardous alcohol consumption (Check Your Drinking; CYD). Participants will be contacted 3 and 6 months after receiving the interventions to assess changes in drinking and depression symptoms. It is predicted that participants receiving the CYD intervention in addition to MoodGYM will report greater postintervention reductions in alcohol consumption and depressive symptoms compared with those who received MoodGYM only. Hypothesised mediation and moderation effects will also be investigated. Using an intention-to-treat basis for the analyses, the hypotheses will be tested using a generalised linear hypothesis framework, and longitudinal analyses will use either generalised linear mixed modelling or generalised estimating equation approach where appropriate. ETHICS AND DISSEMINATION: This research comprises the crucial first steps in developing lower-cost and efficacious internet interventions for people suffering from depression who also drink in a hazardous fashion-promoting the widespread availability of care for those in need. This study has been approved by the standing ethics review committee of the Centre for Addiction and Mental Health, and findings will be disseminated in the form of at least one peer-reviewed article and presentations at conferences. TRIAL REGISTRATION NUMBER: NCT03421080; Pre-results.
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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 | 0.034 | 0.036 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.079 | 0.013 |
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".