Clinical Takeaway
A digital therapeutic tailored specifically for people living with HIV showed feasibility and acceptability as a smoking cessation tool, addressing a population that carries a disproportionately high burden of tobacco use. This pilot trial supports the potential of app-based interventions to reach and engage PWH in evidence-based cessation treatment at scale. Clinicians working with HIV-positive patients who smoke should be aware that digital tools represent a practical, accessible complement to standard cessation counseling and pharmacotherapy.
#24 Population reach, feasibility and acceptability of digital therapeutics for smoking cessation among people living with HIV: Results of the Quitting Matters pilot trial.
Citation: Vilardaga R et al.. Population reach, feasibility and acceptability of digital therapeutics for smoking cessation among people living with HIV: Results of the Quitting Matters pilot trial.. Drug and alcohol dependence. 2026. PMID: 41512654.
Design: 5 Journal: 0 N: 1 Recency: 3 Pop: 2 Human: 1 Risk: -2
- Preclinical only
Abstract: INTRODUCTION: Tobacco use is disproportionately prevalent among people living with HIV (PWH) and is a significant contributor to morbidity and mortality in this population. Reaching communities of PWH to facilitate smoking cessation is challenging. Digital Therapeutics (DTx) can facilitate widespread implementation and adoption of smoking cessation treatments for PWH. METHODS: We compared the feasibility and acceptability (primary outcomes) and preliminary efficacy (secondary outcome) of a DTx tailored to PWH — Learn to Quit-HIV (LTQ-H) — versus a gold standard smoking cessation DTx (QuitGuide) in a remote pilot randomized controlled trial. All participants received nicotine replacement therapy and were assessed at weeks 4, 8, and 12. RESULTS: During a 13-month period, we remotely recruited a sample of PWH (n = 41) across the United States, with randomization leading to a higher proportion of LTQ-H users with high levels of cannabis use. Digital markers of DTx use indicated that compared to QuitGuide, assignment to LTQ-H led to significantly greater number of device interactions (3610 vs 2086; RR=93.14; 95 % CI: 14.70-590; p < 0.001), and a four-fold increase in mean interactions with active smoking cessation content (8.5 vs. 2.15; Cohen's d=0.91; p < 0.001). At week 12, in an adjusted model, LTQ-H resulted in numerically greater, but not statistically significant, biochemically verified 7-day point prevalence abstinence versus QuitGuide (18.2 % vs 15.8 %; aOR=6.97, 95 % CI: 0.65-74.33). CONCLUSIONS: While participants assigned to LTQ-H had proportionally more features known to predict low quit rates (e.g. cannabis use), LTQ-H showed promising population reach, device engagement, and smoking outcomes. A hybrid effectiveness-implementation trial will evaluate this novel DTx in a larger sample of PWH. IMPLICATIONS: The study highlights the potential of DTx to address the high prevalence of tobacco use among people with HIV. Compared to QuitGuide (gold standard DTx d
What This Study Teaches Us
A digital smoking cessation app tailored for people living with HIV (Learn to Quit-HIV) drove significantly more user engagement and interactions with cessation content than a standard app, even though the tailored version enrolled a higher-risk group with more cannabis use. At 12 weeks, both apps showed modest quit rates (18.2% vs 15.8%), with the difference not statistically significant despite the engagement advantage.
Why This Matters Clinically
Smoking remains a leading preventable cause of death in HIV-positive patients, and engagement is often the bottleneck in digital interventions. If a tailored app can hold attention better without yet proving superior quit rates, it may be worth testing in a larger trial, but clinicians should manage expectations that better engagement alone doesn’t guarantee better outcomes.
Study Snapshot
| Study Design | Remote randomized controlled pilot trial comparing two digital therapeutics for smoking cessation |
| Population | 41 people living with HIV recruited across the United States; baseline cannabis use was higher in the intervention group due to randomization imbalance |
| Intervention | Learn to Quit-HIV (LTQ-H, tailored app) versus QuitGuide (standard app); all participants received nicotine replacement therapy; 12-week follow-up |
| Primary Outcome | Feasibility and acceptability measured by digital engagement markers (app interactions and content use) |
| Key Result | LTQ-H generated 3610 device interactions versus 2086 for QuitGuide (RR=93.14) and 8.5 versus 2.15 interactions with smoking cessation content (p<0.001); 7-day quit rates at 12 weeks were 18.2% (LTQ-H) versus 15.8% (QuitGuide), not statistically significant |
Where This Paper Deserves Skepticism
The sample is tiny (n=41) and the quit rates in both arms are low, leaving limited statistical power to detect differences. The randomization itself created a confound: the intervention group started with proportionally more cannabis users, which the authors flag as a predictor of poor outcomes, yet they still claim promising results. The abstract provides no detail on retention rates, adherence to NRT, or whether the engagement difference persisted over time. With only 12 weeks of follow-up and no mention of long-term abstinence verification, durability is unknown.
Dr. Caplan’s Take
I find this study interesting but preliminary. The engagement boost is real and meaningful, which matters because many digital interventions fail simply because people don’t use them. But engagement without quit rates is a intermediate endpoint, not a clinical victory. The HIV population absolutely deserves tailored tools, and the authors are right that reach is a bottleneck. I’d watch for the larger effectiveness-implementation trial they mention, but I wouldn’t alter my current smoking cessation counseling for PWH based on this pilot alone. The combination of NRT plus structured behavioral support (whether digital or in-person) remains the baseline standard.
Clinical Bottom Line
A tailored digital smoking cessation app for HIV-positive patients shows better engagement than a standard app, but both yielded modest quit rates without a statistically significant difference. Reserve judgment until a larger, longer trial reports actual quit outcomes.
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