Evaluating the Efficacy of Automated Smoking Treatment for People With HIV: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Smoking prevalence rates among people with HIV are nearly 3 times higher than those in the general population. Nevertheless, few smoking cessation trials targeting smokers with HIV have been reported in the literature. Efforts to develop and evaluate sustainable, low-cost, and evidence-based cessation interventions for people with HIV are needed. Given the widespread proliferation of mobile phones, the potential of using mobile health apps to improve the reach and efficacy of cessation interventions is promising, but evidence of efficacy is lacking, particularly among people with HIV. OBJECTIVE: This study will consist of a 2-group randomized controlled trial to evaluate a fully automated smartphone intervention for people with HIV seeking cessation treatment. METHODS: Participants (N=500) will be randomized to receive either standard treatment (ST; 250/500, 50%) or automated treatment (AT; 250/500, 50%). ST participants will be connected to the Florida Quitline and will receive nicotine replacement therapy in the form of transdermal patches and lozenges. This approach, referred to as Ask Advise Connect, was developed by our team and has been implemented in numerous health systems. ST will be compared with AT, a fully automated behavioral treatment approach. AT participants will receive nicotine replacement therapy and an interactive smartphone-based intervention that comprises individually tailored audiovisual and text content. The major goal is to determine whether AT performs better in terms of facilitating long-term smoking abstinence than the more resource-intensive ST approach. Our primary aim is to evaluate the efficacy of AT in facilitating smoking cessation among people with HIV. As a secondary aim, we will explore potential mediators and moderators and conduct economic evaluations to assess the cost and cost-effectiveness of AT compared with ST. RESULTS: The intervention content has been developed and finalized. Recruitment and enrollment will begin in the fall of 2021. CONCLUSIONS: There is a critical need for efficacious, cost-effective, and sustainable cessation treatments for people with HIV who smoke. The AT intervention was designed to help fill this need. If efficacy is established, the AT approach will be readily adoptable by HIV clinics and community-based organizations, and it will offer an efficient way to allocate limited public health resources to tobacco control interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05014282; https://clinicaltrials.gov/ct2/show/NCT05014282. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/33183.
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 | 0.054 | 0.053 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.011 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.101 | 0.017 |
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".