Engagement with a digital therapeutic for smoking cessation designed for persons with psychiatric illness fully mediates smoking outcomes in a pilot randomized controlled trial

Abstract

Understanding the mechanisms of change of digital therapeutics is a critical step to improve digital health outcomes and optimize their development. Access to and engagement with digital content is arguably a core mechanism of change of these interventions. However, the mediational role of app engagement has been largely unexamined. To evaluate the mediational effect of engaging with a digital therapeutic for smoking cessation designed for adults with psychiatric disorders. Secondary analysis of a pilot clinical trial of 62 adults with serious mental illness who were randomized to receive either a tailored digital therapeutic (Learn to Quit) or a digital therapeutic for the general public (NCI QuitGuide). Engagement was captured using background analytics of app utilization, including (a) number of interactions with app content, (b) minutes/day of app use, and (c) number of days used. The main outcome was reductions in cigarettes per day from baseline to the four-month endpoint. Mediational analysis followed the Preacher and Hayes bootstrap method. Number of application interactions fully mediated reductions in cigarettes per day in the Learn to Quit application but not in QuitGuide (Average Causal Mediation Effect = .31, p = .02). Minutes/day of app use played an uncertain role, and number of days used was not a significant mediator. Results suggest that one of the mechanisms of action of the Learn to Quit device, engagement with theory-based content, functioned as intended. Future research of digital therapeutics should emphasize granular approaches to evaluating apps’ mechanisms of action.

An examination of neurocognition and theory of mind as predictors of engagement with a tailored digital therapeutic in persons with serious mental illness

“…In summary, LTQ's design appears to effectively predict engagement with a digital therapeutic among individuals with SMI after rigorously controlling for cognitive factors. As shown elsewhere ( Browne et al, 2021 ), this finding is important since engagement with this digital therapeutic mediated clinical outcomes. Further, this tailored digital therapeutic seemed to comparably engage a broad range of individuals with different demographics and clinical characteristics from the target population.…”

“…To this end, apps are increasingly utilized in the treatment of SMI in a variety of ways (e.g., stand-alone interventions, symptom monitoring, adjunctive therapeutic support) with demonstrated feasibility and efficacy ( Batra et al, 2017 ; Ben-Zeev et al, 2018 ; Bucci et al, 2018 ; Depp et al, 2016 ; Eisner et al, 2019 ; Firth and Torous, 2015 ; Fortuna et al, 2018 ; Liu et al, 2019 ). Yet, there is variable engagement with apps among users with SMI (e.g., a small subset of users often account for a large proportion of app engagement) and the real-world uptake of smartphone apps by clinics and users remains relatively low ( Torous et al, 2017 ; Torous et al, 2018 ), which is concerning given that app engagement is linked with improved outcomes ( Ben-Zeev et al, 2018 ; Best et al, 2019 ; Browne et al, 2021 ; Harvey et al, 2020 ). Therefore, knowledge of the putative barriers to app engagement in this population is necessary to guide strategies for facilitating adequate uptake.…”

Mechanisms of Smartphone Apps for Cigarette Smoking Cessation: Results of a Serial Mediation Model From the iCanQuit Randomized Trial

“…Despite their high population-level reach, very little is known about the potential mediators underlying the efficacy of smartphone apps for smoking cessation [ 6 ]. In the broader literature on digital interventions (eg, websites and SMS text messaging) for smoking cessation, we are aware of only 3 randomized controlled trials (RCTs) that reported on their mechanisms of action—with each showing support for the theoretical models guiding their interventions (eg, self-efficacy) [ 7 - 9 ].…”

“…In parallel with studies on psychological mechanisms of action, digital intervention researchers have been studying the role of intervention engagement as a process that predicts treatment outcomes [ 6 , 7 , 24 , 25 ]. Our previous study has shown that, in the SmartQuit app that preceded the iCanQuit app, engagement with the intervention and its specific ACT components was predictive of smoking cessation.…”

Smoking Cessation Apps for People with Schizophrenia: How Feasible Are m-Health Approaches?

“…Our study identified 15 potential papers; of those, five interventions were delivered online [ 20 , 21 , 22 , 23 , 24 ], one detailed the development of an app [ 25 ], and one study only recruited people with mood disorders [ 26 ], so they were excluded from this review. The remaining eight studies [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ] were included and focused on a variety of apps (Quitpal, Kick.it, QuitGuide, Learn To Quit (LTQ), and quitSTART). The key features of these app and apps interfaces, we could detect, are presented in Table 2 and Table 3 , respectively.…”