Identification of Users for a Smoking Cessation Mobile App: Quantitative Study

Area of Science:

• Digital Health
• Behavioral Science
• Public Health

Background:

• The proliferation of mobile applications for smoking cessation highlights the potential of mobile health (mHealth) technology in supporting cessation efforts.
• Understanding end-user characteristics is crucial for developing effective dissemination strategies to enhance user satisfaction and adherence to cessation apps.

Purpose of the Study:

• To characterize the potential end users of a specific mobile health (mHealth) smoking cessation application.
• To identify user attributes associated with the intention to use and attitude towards mHealth smoking cessation apps.

Main Methods:

• A quantitative study surveyed 955 Dutch smokers and ex-smokers recruited from addiction care facilities and hospitals.
• Data collected included demographics, smoking behavior, personal innovativeness, and intention/attitude towards a cessation app using a 5-point Likert scale.
• Univariate and multivariate ordinal logistic regression analyses were performed to examine associations between user characteristics and app usage intention/attitude.

Main Results:

• Nicotine dependence (Fagerstrom Test of Nicotine Dependence score) and a higher number of previous quit attempts were positively associated with both intention to use and attitude towards cessation apps.
• Personal innovativeness also showed a positive correlation with intention to use and attitude towards the cessation app.
• Demographic characteristics, such as age and education level, were not significantly associated with the intention to use or attitude towards the cessation app in the multivariate model.

Conclusions:

• User engagement with mHealth smoking cessation apps is primarily influenced by factors related to smoking behavior (nicotine dependence, quit attempts) and personal innovativeness, rather than general demographic characteristics.
• These findings suggest that tailoring app content and features to address specific user needs related to nicotine dependence and cessation history may be more effective than broad demographic targeting.
• The study underscores the importance of app-specific content over general user profiles in predicting the adoption and effectiveness of mHealth interventions for smoking cessation.