TY - JOUR
T1 - Use of the Smoking Cessation App Ex-Smokers iCoach and Associations With Smoking-Related Outcomes Over Time in a Large Sample of European Smokers
T2 - Retrospective Observational Study
AU - Mansour, Marthe Bl
AU - Busschers, Wim B.
AU - Crone, Mathilde R.
AU - van Asselt, Kristel M.
AU - van Weert, Henk C.
AU - Chavannes, Niels H.
AU - Meijer, Eline
N1 - Funding Information: The authors would like to thank Claudia Put and Stevens de Peuter for providing them with the iCoach data set. Publisher Copyright: ©Marthe BL Mansour, Wim B Busschers, Mathilde R Crone, Kristel M van Asselt, Henk C van Weert, Niels H Chavannes, Eline Meijer.
PY - 2023/8/22
Y1 - 2023/8/22
N2 - BACKGROUND: Digital interventions are increasingly used to support smoking cessation. Ex-smokers iCoach was a widely available app for smoking cessation used by 404,551 European smokers between June 15, 2011, and June 21, 2013. This provides a unique opportunity to investigate the uptake of a freely available digital smoking cessation intervention and its effects on smoking-related outcomes. OBJECTIVE: We aimed to investigate whether there were distinct trajectories of iCoach use, examine which baseline characteristics were associated with user groups (based on the intensity of use), and assess if and how these groups were associated with smoking-related outcomes. METHODS: Analyses were performed using data from iCoach users registered between June 15, 2011, and June 21, 2013. Smoking-related data were collected at baseline and every 3 months thereafter, with a maximum of 8 follow-ups. First, group-based modeling was applied to detect distinct trajectories of app use. This was performed in a subset of steady users who had completed at least 1 follow-up measurement. Second, ordinal logistic regression was used to assess the baseline characteristics that were associated with user group membership. Finally, generalized estimating equations were used to examine the association between the user groups and smoking status, quitting stage, and self-efficacy over time. RESULTS: Of the 311,567 iCoach users, a subset of 26,785 (8.6%) steady iCoach users were identified and categorized into 4 distinct user groups: low (n=17,422, 65.04%), mild (n=4088, 15.26%), moderate (n=4415, 16.48%), and intensive (n=860, 3.21%) users. Older users and users who found it important to quit smoking had higher odds of more intensive app use, whereas men, employed users, heavy smokers, and users with higher self-efficacy scores had lower odds of more intensive app use. User groups were significantly associated with subsequent smoking status, quitting stage, and self-efficacy over time. For all groups, over time, the probability of being a smoker decreased, whereas the probability of being in an improved quitting stage increased, as did the self-efficacy to quit smoking. For all outcomes, the greatest change was observed between baseline and the first follow-up at 3 months. In the intensive user group, the greatest change was seen between baseline and the 9-month follow-up, with the observed change declining gradually in moderate, mild, and low users. CONCLUSIONS: In the subset of steady iCoach users, more intensive app use was associated with higher smoking cessation rates, increased quitting stage, and higher self-efficacy to quit smoking over time. These users seemed to benefit most from the app in the first 3 months of use. Women and older users were more likely to use the app more intensively. Additionally, users who found quitting difficult used the iCoach app more intensively and grew more confident in their ability to quit over time.
AB - BACKGROUND: Digital interventions are increasingly used to support smoking cessation. Ex-smokers iCoach was a widely available app for smoking cessation used by 404,551 European smokers between June 15, 2011, and June 21, 2013. This provides a unique opportunity to investigate the uptake of a freely available digital smoking cessation intervention and its effects on smoking-related outcomes. OBJECTIVE: We aimed to investigate whether there were distinct trajectories of iCoach use, examine which baseline characteristics were associated with user groups (based on the intensity of use), and assess if and how these groups were associated with smoking-related outcomes. METHODS: Analyses were performed using data from iCoach users registered between June 15, 2011, and June 21, 2013. Smoking-related data were collected at baseline and every 3 months thereafter, with a maximum of 8 follow-ups. First, group-based modeling was applied to detect distinct trajectories of app use. This was performed in a subset of steady users who had completed at least 1 follow-up measurement. Second, ordinal logistic regression was used to assess the baseline characteristics that were associated with user group membership. Finally, generalized estimating equations were used to examine the association between the user groups and smoking status, quitting stage, and self-efficacy over time. RESULTS: Of the 311,567 iCoach users, a subset of 26,785 (8.6%) steady iCoach users were identified and categorized into 4 distinct user groups: low (n=17,422, 65.04%), mild (n=4088, 15.26%), moderate (n=4415, 16.48%), and intensive (n=860, 3.21%) users. Older users and users who found it important to quit smoking had higher odds of more intensive app use, whereas men, employed users, heavy smokers, and users with higher self-efficacy scores had lower odds of more intensive app use. User groups were significantly associated with subsequent smoking status, quitting stage, and self-efficacy over time. For all groups, over time, the probability of being a smoker decreased, whereas the probability of being in an improved quitting stage increased, as did the self-efficacy to quit smoking. For all outcomes, the greatest change was observed between baseline and the first follow-up at 3 months. In the intensive user group, the greatest change was seen between baseline and the 9-month follow-up, with the observed change declining gradually in moderate, mild, and low users. CONCLUSIONS: In the subset of steady iCoach users, more intensive app use was associated with higher smoking cessation rates, increased quitting stage, and higher self-efficacy to quit smoking over time. These users seemed to benefit most from the app in the first 3 months of use. Women and older users were more likely to use the app more intensively. Additionally, users who found quitting difficult used the iCoach app more intensively and grew more confident in their ability to quit over time.
KW - European smokers
KW - digital smoking cessation intervention
KW - engagement
KW - mobile phone
KW - smoker characteristics
KW - smoking cessation app
KW - smoking-related outcomes
KW - trajectories of use patterns
KW - user groups
UR - http://www.scopus.com/inward/record.url?scp=85168518249&partnerID=8YFLogxK
U2 - https://doi.org/10.2196/45223
DO - https://doi.org/10.2196/45223
M3 - Article
C2 - 37606969
SN - 2291-5222
VL - 25
SP - e45223
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
M1 - e45223
ER -