Couple-Focused Smartphone Intervention to Reduce Problem Drinking: Pilot Randomized Control Trial
Bibliographic record
Abstract
BACKGROUND: Alcohol use disorder is among the most pervasive substance use disorders in the United States, with a lifetime prevalence of 30%. Recommended treatment options include evidence-based behavioral interventions; smartphone-based interventions confer a number of benefits such as portability, continuous access, and stigma avoidance; and research suggests that interventions involving couples may outperform those for patients only. In this context, a behavioral intervention delivered to couples through smartphones may serve as an effective adjunct to alcohol use disorder treatment. OBJECTIVE: This pilot study aimed to (1) evaluate the feasibility of comparing a patient-only (Addiction version of the Comprehensive Health Enhancement Support System; A-CHESS) versus a couple-focused (Partner version of the Comprehensive Health Enhancement Support System; Partner-CHESS) eHealth app for alcohol misuse delivered by smartphone, (2) assess perceptions about and use of the 2 apps, and (3) examine initial indications of differences in primary clinical outcomes between patient groups using the 2 apps. Broadly, these aims serve to assess the feasibility of the study protocol for a larger randomized controlled trial. METHODS: A total of 33 romantic couples were randomized to 6 months of A-CHESS app use (active treatment control) or Partner-CHESS app use (experimental). Couples comprised a patient with current alcohol use disorder (25/33, 76% male) and a romantic partner (26/33, 79% female). Patients and partners in both arms completed outcome measure surveys at 0, 2, 4, and 6 months. Primary outcomes were patients' percentage of days with heavy drinking and percentage of days with any drinking, measured by timeline follow back. Secondary outcomes included app use and perceptions, and multiple psychosocial variables. RESULTS: At 6 months, 78% (14/18) of Partner-CHESS patients and 73% (11/15) of A-CHESS patients were still using the intervention. The apps were rated helpful on a 5-point scale (1=not at all helpful, 5=extremely helpful) by 89% (29/33) of both Partner-CHESS patients (mean 3.7, SD 1) and partners (mean 3.6, SD 0.9) and by 87% (13/15) of A-CHESS patients (mean 3.1, SD 0.9). At 6 months, Partner-CHESS patients had a nonsignificantly lower percentage of days with heavy drinking compared with A-CHESS patients (β=-17.4, 95% CI -36.1 to 1.4; P=.07; Hedges g=-0.53), while the percentage of drinking days was relatively equal between patient groups (β=-2.1, 95% CI -24.8 to 20.7; P=.85; Hedges g=-0.12). CONCLUSIONS: Initial results support the feasibility of evaluating patient-only and couple-focused, smartphone-based interventions for alcohol misuse. Results suggest that both interventions are perceived as helpful and indicate maintained engagement of most participants for 6 months. A future, fully powered trial is warranted to evaluate the relative effectiveness of both interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04059549; https://clinicaltrials.gov/ct2/show/NCT04059549.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".