Associations Between Engagement and Outcomes in the SmokefreeTXT Program: A Growth Mixture Modeling Analysis.
Nicotine Tob Res
; 21(5): 663-669, 2019 04 17.
Article
em En
| MEDLINE
| ID: mdl-29668984
ABSTRACT
INTRODUCTION:
Smoking continues to be a leading cause of preventable death. Mobile health (mHealth) can extend the reach of smoking cessation programs; however, user dropout, especially in real-world implementations of these programs, limit their potential effectiveness. Research is needed to understand patterns of engagement in mHealth cessation programs.METHODS:
SmokefreeTXT (SFTXT) is the National Cancer Institute's 6-8 week smoking cessation text-messaging intervention. Latent growth mixture modeling was used to identify unique classes of engagement among SFTXT users using real-world program data from 7090 SFTXT users. Survival analysis was conducted to model program dropout over time by class, and multilevel modeling was used to explore differences in abstinence over time.RESULTS:
We identified four unique patterns of engagement groups. The largest percentage of users (61.6%) were in the low-engagers declining group; these users started off with low level of engagement and their engagement decreased over time. Users in this group were more likely to drop out from the program and less likely to be abstinent than users in the other groups. Users in the high engagers-maintaining group (ie, the smallest but most engaged group) were less likely to be daily smokers at baseline and were slightly older than those in the other groups. They were most likely to complete the program and report being abstinent.CONCLUSIONS:
Our findings show the importance of maintaining active engagement in text-based cessation programs. Future research is needed to elucidate predictors of the various levels of engagement, and to assess whether strategies aimed at increasing engagement result in higher abstinence rates. IMPLICATIONS The current study enabled us to investigate differing engagement patterns in non-incentivized program participants, which can help inform program modifications in real-world settings. Lack of engagement and dropout continue to impede the potential effectiveness of mHealth interventions, and understanding patterns and predictors of engagement can enhance the impact of these programs.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Participação do Paciente
/
Abandono do Hábito de Fumar
/
Envio de Mensagens de Texto
/
Fumar Tabaco
/
Fumantes
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Aspecto:
Patient_preference
Limite:
Adult
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
Nicotine Tob Res
Assunto da revista:
SAUDE PUBLICA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Moldávia