A Smartphone App Designed to Help Cancer Patients Stop Smoking: Results From a Pilot Randomized Trial on Feasibility, Acceptability, and Effectiveness

Abstract

Background Persistent smoking after a cancer diagnosis predicts worse treatment outcomes and mortality, but access to effective smoking cessation interventions is limited. Smartphone apps can address this problem by providing a highly accessible, low-cost smoking cessation intervention designed for patients with a recent cancer diagnosis. Objective This study aimed to summarize our development process and report the trial design, feasibility, participant acceptability, preliminary effectiveness, and impact on processes of change (eg, cancer stigma) of the first-known smoking cessation smartphone app targeted for cancer patients. Methods We used an agile, user-centered design framework to develop a fully automated smartphone app called Quit2Heal that provided skills training and stories from cancer survivors focusing on coping with internalized shame, cancer stigma, depression, and anxiety as core triggers of smoking. Quit2Heal was compared with the National Cancer Institute’s QuitGuide, a widely used stop smoking app for the general population, in a pilot double-blinded randomized trial with a 2-month follow-up period. Participants were 59 adult smokers diagnosed with cancer within the past 12 months and recruited through 2 cancer center care networks and social media over a 12-month period. The most common types of cancer diagnosed were lung (21/59, 36%) and breast (10/59, 17%) cancers. The 2-month follow-up survey retention rate was 92% (54/59) and did not differ by study arm (P=.15). Results Compared with QuitGuide participants, Quit2Heal participants were more satisfied with their assigned app (90% [19/21] for Quit2Heal vs 65% [17/26] for QuitGuide; P=.047) and were more likely to report that the app assigned to them was made for someone like them (86% [18/21] for Quit2Heal vs 62% [16/26] for QuitGuide; P=.04). Quit2Heal participants opened their app a greater number of times during the 2-month trial period, although this difference was not statistically significant (mean 10.0, SD 14.40 for Quit2Heal vs mean 6.1, SD 5.3 for QuitGuide; P=.33). Self-reported 30-day point prevalence quit rates at the 2-month follow-up were 20% (5/25) for Quit2Heal versus 7% (2/29) for QuitGuide (odds ratio 5.16, 95% CI 0.71-37.29; P=.10). Quit2Heal participants also showed greater improvement in internalized shame, cancer stigma, depression, and anxiety, although these were not statistically significant (all P>.05). Conclusions In a pilot randomized trial with a high short-term retention rate, Quit2Heal showed promising acceptability and effectiveness for helping cancer patients stop smoking. Testing in a full-scale randomized controlled trial with a longer follow-up period and a larger sample size is required to test the effectiveness, mediators, and moderators of this promising digital cessation intervention. Trial Registration ClinicalTrials.gov NCT03600038; https://clinicaltrials.gov/ct2/show/NCT03600038

Update on Cyber Health Psychology: Virtual Reality and Mobile Health Tools in Psychotherapy, Clinical Rehabilitation, and Addiction Treatment

“…Another application studied was Quit2Heal , in comparison with the QuitGuide of the US National Cancer Institute, by Bricker et al [ 31 ]. In this case, the sample was composed exclusively of cancer patients, and the application showed “promising acceptability and efficacy in helping cancer patients to quit smoking”.…”

Feature-Level Analysis of a Smoking Cessation Smartphone App Based on a Positive Psychology Approach: Prospective Observational Study

“…These expectations were reinforced with proactive push notifications. The iCanQuit app [ 70 ] also had prescriptive clarity: a set number of modules were required to be completed. Both apps had high app engagement over time.…”

Design Frameworks for Mobile Health Technology

“…A variety of users or stakeholders participated in these studies, including patients, caregivers, healthcare professionals, seniors, university students, veterans, and other mHealth technology users (see Table 2). Overall, the sample sizes were small: five of the studies had twenty or less participants (Buman et al, 2016;Farao et al, 2020;Goldstein et al, 2017 ;van Agteren et al, 2018;Zucchelli et al, 2021), three had more than 50 participants (Bricker et al, 2020;Portz et al, 2020;Halttu & Oinas-Kukkonen, 2017, one of which had more than 100 participants (n=147) (Halttu & Oinas-Kukkonen, 2017).…”

“…Among the various frameworks, the Persuasive System Design Framework was applied in three studies (i.e.,Halttu & Oinas-Kukkonen, 2017;Kelders, Kok, Ossebaard, & Van Gemert-Pijnen, 2012;Oinas-Kukkonen, & Harjumaa, 2009). In the latest studies, user-centered framework(Bricker et al, 2020;Farao et al, 2020), human-centered iterative design principles(Morse et al, 2021;Portz et al, 2020) and participatory design framework(Zucchelli et al, 2021) were applied.…”