A Text Message–Based Intervention for Weight Loss: Randomized Controlled Trial

By K. Patrick, F. Raab, M. Adams, Lindsay Dillon, Marion F. Zabinski, C. Rock, W. Griswold, Gregory J. Norman. Journal of Medical Internet Research, 2009

700 citations recorded by the source corpus.

Background To our knowledge, no studies have evaluated whether weight loss can be promoted in overweight adults through the use of an intervention that is largely based on daily SMS (Short Message Service: text) and MMS (Multimedia Message Service: small picture) messages transmitted via mobile phones. Objective This paper describes the development and evaluation of a text message–based intervention designed to help individuals lose or maintain weight over 4 months. Methods The study was a randomized controlled trial, with participants being exposed to one of the following two conditions, lasting 16 weeks: (1) receipt of monthly printed materials about weight control; (2) an intervention that included personalized SMS and MMS messages sent two to five times daily, printed materials, and brief monthly phone calls from a health counselor. The primary outcome was weight at the end of the intervention. A mixed-model repeated-measures analysis compared the effect of the intervention group to the comparison group on weight status over the 4-month intervention period. Analysis of covariance (ANCOVA) models examined weight change between baseline and 4 months after adjusting for baseline weight, sex, and age. Results A total of 75 overweight men and women were randomized into one of the two groups, and 65 signed the consent form, completed the baseline questionnaire, and were included in the analysis. At the end of 4 months, the intervention group (n = 33) lost more weight than the comparison group (−1.97 kg difference, 95% CI −0.34 to −3.60 kg, P = .02) after adjusting for sex and age. Intervention participants’ adjusted average weight loss was 2.88 kg (3.16%). At the end of the study, 22 of 24 (92%) intervention participants stated that they would recommend the intervention for weight control to friends and family. Conclusions Text messages might prove to be a productive channel of communication to promote behaviors that support weight loss in overweight adults. Trial Registration Clinicaltrials.gov NCT00415870; http://clinicaltrials.gov/ct2/show/NCT00415870 (Archived by WebCite at http://www.webcitation.org/5dnolbkFt)

Subfields: Applied Psychology, General Health Professions, Pharmacy

View Paper: https://www.semanticscholar.org/paper/177de944010baa3045e89a57c4f1978fe3ca15f5

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Citations in the corpus

One Step at a Time: The Effects of an Early Literacy Text Messaging Program for Parents of Preschoolers (2014, positive): “2 provision of well-designed texts can improve weight loss (Patrick et al., 2009), medication”
Using facebook and text messaging to deliver a weight loss program to college students (2013, result): “In addition, our text response rates were comparable to other studies in both college students and adults (35,36) indicating good compliance and utilization.”
A Behavior Change Model for Internet Interventions (2009, background): “The use of prompts has significant potential, particularly given the possible integration of mobile phones, PDAs, pagers, and other wireless devices that can all be employed in the deliverance of prompts [29, 30].”
Bewell: A smartphone application to monitor, model and promote wellbeing (2011, background): “In [6], the investigators propose a system that combines self-report with a medical practitioner observing the trends and providing advice via email.”
Group-driven Reinforcement Learning for Personalized mHealth Intervention (2017, background): “Based on that, the aim is to provide in-time interventions to device users according to their ongoing status and changing needs, helping users to lead healthier lives, such as reducing the alcohol abuse [5,19] and the obesity management [15].”
Mapping mHealth Research: A Decade of Evolution (2013, background): “The final sample for the full-text review included 117 [17-133] articles out of the 352 described above.”
An Actor-Critic Contextual Bandit Algorithm for Personalized Interventions using Mobile Devices (2014, background): “The focuses of other studies include physical activity [5, 6], obesity/weight management [7], etc.”
A Batch, Off-Policy, Actor-Critic Algorithm for Optimizing the Average Reward (2016, background): “…2013), eating disorders (Bauer et al., 2012), alcohol use (Witkiewitz et al., 2014; Gustafson et al., 2014), mental illness (Depp et al., 2010; Ben-Zeev et al., 2013), obesity/weight management (Patrick et al., 2009) and other chronic disorders (Granholm et al., 2012; Kristjansdottir et al., 2013).”
Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework (2015, background): “, 2014), smoking cessation (Riley, Obermayer, & Jean-Mary, 2008), obesity (Patrick et al., 2009), and mental illnesses (Ben-Zeev, Brenner, et al.”
Adherence to a Smartphone Application for Weight Loss Compared to Website and Paper Diary: Pilot Randomized Controlled Trial (2013, background): “4 kg (95% CI -1 to 1) in the control group [7].”