A Multimedia Support Skills Intervention for Female Partners of Male Smokeless Tobacco Users: Use and Perceived Acceptability
Bibliographic record
Abstract
Background: UCare is a new multimedia (website+booklet) intervention for women who want their male partner to quit their use of smokeless tobacco. The intervention is based on research showing that perceived partner responsiveness to social support is highest when the supporter conveys respect, understanding, and caring in their actions. The website included both didactic and interactive features, with optional video components, and special activities to help women develop empathy for nicotine addiction. The booklet reinforced the website content, encouraged women to use the website, and served both as a physical reminder of the intervention and a convenient way to share the information with her partner. Objective: The objective of this study was to describe the utilization and acceptability of a multimedia intervention among women seeking to support their partner in quitting smokeless tobacco. Lessons learned with respect to design considerations for online interventions are also summarized. Methods: We present the evaluation of the intervention components' use and usefulness in a randomized trial. Results: In the randomized clinical trial, more than 250,000 visits were made to the website in a 2-year period, with the vast majority from mobile devices. Of the 552 women randomized to receive the intervention, 96.9% (535/552) visited the website at least once, and 30.8% (170/552) completed the core website component, "The Basics." About half of the women (287/552) used the interactive "Take Notes" feature, and 37% (204/552) used the checklists. Few women used the post-Basics features. At 6 weeks, 40.7% (116/285) reported reading the printed and mailed booklet. Website and booklet use were uncorrelated. User ratings for the website and booklet were positive overall. Conclusions: Intervention website designers should consider that many users will access the program only once or twice, and many will not complete it. It is also important to distinguish between core and supplemental features and to consider whether the primary purpose is training or support. Furthermore, printed materials still have value. Trial Registration: ClinicalTrials.gov NCT01885221; https://clinicaltrials.gov/ct2/show/NCT01885221 (Archived by WebCite at http://www.webcitation.org/6zdIgGGtx).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".