A Systematic Review and Meta-Analysis of Mobile Devices and Weight Loss with an Intervention Content Analysis

Introduction: Overweight and obesity constitute leading global public health challenges. Tackling overweight and obesity by influencing human behaviour is a complex task, requiring novel emerging health psychology interventions. The aims of this review will be to determine whether mobile devices induce weight loss and improvements in diet and physical activity levels when compared with standard controls without a weight loss intervention or controls allocated to non-mobile device weight loss interventions. Methods: A systematic review on mobile devices and weight loss was conducted. The inclusion criteria were all randomized controlled trials with baseline and post-intervention weight measures in adult subjects >18 years of age without pre-specified co-morbidities. Mobile device specifications included modern, portable devices in the form of smartphones, PDAs, iPods, and Mp3 players. Cohen’s d for standardized differences in mean weight loss was calculated. A random effects meta-analysis was generated using Comprehensive meta-analysis software. Theories and intervention content were coded and analysed. Results: A total of 17 studies were identified, of which 12 were primary trials and 5 were secondary analyses. The meta-analysis generated a medium significant effect size of 0.430 (95% CI 0.252–0.609) (p-value ≤ 0.01), favouring mobile interventions. Throughout the systematic review, mobile devices were found to induce weight loss relative to baseline weight. When comparing them with standard no intervention controls as well as controls receiving non-mobile weight loss interventions, results favoured mobile devices for weight loss. Reductions in Body mass index, waist circumference, and percentage body fat were also found in the review. Improvements in the determinants of weight loss in the form of improved dietary intake and physical activity levels were also found. Theory appears to largely inform intervention design, with the most common theories being Social Cognitive Theory, Elaboration Likelihood Theory, Control Theory, and Goal Theory. The use of behavioural change techniques was widespread across the studies, with a minimum of five per intervention. Conclusion: Mobile devices appear to induce positive changes in the behavioural determinants of weight and subsequently are associated with weight loss. Mobile device interventions are heavily informed by theory and behaviour change techniques. The use of theory appears to effectively enhance levels of constructs targeted by interventions.

[1]  C. Abraham,et al.  A taxonomy of behavior change techniques used in interventions. , 2008, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[2]  Hannu Salonen Common theories , 2009, Math. Soc. Sci..

[3]  J. S. Sodhi,et al.  Using Internet and Mobile Phone Technology to Deliver an Automated Physical Activity Program: Randomized Controlled Trial , 2007, Journal of medical Internet research.

[4]  Conclusions , 1989 .

[5]  M. Carter,et al.  Adherence to a Smartphone Application for Weight Loss Compared to Website and Paper Diary: Pilot Randomized Controlled Trial , 2013, Journal of medical Internet research.

[6]  Diana Gosálvez Prados Global Burden of Disease Study 2010 , 2012 .

[7]  Andrew T. Kaczynski,et al.  Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program , 2013, J. Am. Medical Informatics Assoc..

[8]  Shlomo Berkovsky,et al.  Design and Pilot Results of a Mobile Phone Weight-Loss Application for Women Starting a Meal Replacement Programme , 2013, Journal of telemedicine and telecare.

[9]  Sean P Mullen,et al.  Increasing Physical Activity With Mobile Devices: A Meta-Analysis , 2012, Journal of medical Internet research.

[10]  W. DeKeseredy,et al.  Future directions , 2005, Psychiatric Quarterly.

[11]  M. Sevick,et al.  Self-monitoring in weight loss: a systematic review of the literature. , 2011, Journal of the American Dietetic Association.

[12]  J. McGough,et al.  Estimating the size of treatment effects: moving beyond p values. , 2009, Psychiatry (Edgmont (Pa. : Township)).

[13]  K. Patrick,et al.  A Text Message–Based Intervention for Weight Loss: Randomized Controlled Trial , 2009, Journal of medical Internet research.

[14]  S. Michie,et al.  Are interventions theory-based? Development of a theory coding scheme. , 2010, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[15]  M. Sevick,et al.  Using mHealth technology to enhance self-monitoring for weight loss: a randomized trial. , 2012, American journal of preventive medicine.

[16]  J. Sterne,et al.  The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials , 2011, BMJ : British Medical Journal.

[17]  Craig Lefebvre,et al.  Integrating Cell Phones and Mobile Technologies Into Public Health Practice: A Social Marketing Perspective , 2009, Health promotion practice.

[18]  L. Burke,et al.  Using a personal digital assistant for self-monitoring influences diet quality in comparison to a standard paper record among overweight/obese adults. , 2011, Journal of the American Dietetic Association.

[19]  Marci K Campbell,et al.  Pounds Off Digitally study: a randomized podcasting weight-loss intervention. , 2009, American journal of preventive medicine.

[20]  M. Whitehead,et al.  Developing the Policy Response to Inequities in Health: A Global Perspective , 2001 .

[21]  Matthew P. Normand,et al.  Increasing calorie expenditure through task clarification, goal-setting, self-monitoring, and feedback , 2008 .

[22]  Susan Michie,et al.  Using theories of behaviour change to inform interventions for addictive behaviours. , 2010, Addiction.

[23]  K. Reynolds,et al.  Global burden of obesity in 2005 and projections to 2030 , 2008, International Journal of Obesity.

[24]  D. Withrow,et al.  The economic burden of obesity worldwide: a systematic review of the direct costs of obesity , 2011, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[25]  M. Perugini,et al.  Can implementation intentions and text messages promote brisk walking? A randomized trial. , 2010, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[26]  P. Cudd,et al.  Interventions employing mobile technology for overweight and obesity: an early systematic review of randomized controlled trials , 2012, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[27]  Amalia Waxman,et al.  Who Global Strategy on Diet, Physical Activity and Health * , 2004, Food and nutrition bulletin.

[28]  Importance of the nature of comparison conditions for testing theory-based interventions: reply. , 2010, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[29]  M. Sevick,et al.  The Effect of Electronic Self‐Monitoring on Weight Loss and Dietary Intake: A Randomized Behavioral Weight Loss Trial , 2011, Obesity.

[30]  C. Abraham,et al.  Effective techniques in healthy eating and physical activity interventions: a meta-regression. , 2009, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[31]  Ryan J. Shaw,et al.  Short message service (SMS) text messaging as an intervention medium for weight loss: A literature review , 2012, Health Informatics J..

[32]  Kevin Patrick,et al.  Fruit and vegetable intake and eating behaviors mediate the effect of a randomized text-message based weight loss program. , 2013, Preventive medicine.

[33]  Marcie Hamilton Limitations , 2020, Terrorist Minds.

[34]  Marci K Campbell,et al.  Delivering Health Information via Podcast or Web: Media Effects on Psychosocial and Physiological Responses , 2013, Health communication.

[35]  Jing Wang,et al.  Physical activity self-monitoring and weight loss: 6-month results of the SMART trial. , 2011, Medicine and science in sports and exercise.

[36]  Charles Abraham,et al.  Specifying self-regulation intervention techniques in the context of healthy eating , 2008 .

[37]  G. Bennett,et al.  Using facebook and text messaging to deliver a weight loss program to college students , 2013, Obesity.

[38]  J. Higgins,et al.  Cochrane Handbook for Systematic Reviews of Interventions, Version 5.1.0. The Cochrane Collaboration , 2013 .

[39]  N. Barengo,et al.  Weight loss by mobile phone: a 1-year effectiveness study , 2009, Public Health Nutrition.

[40]  Alan D. Lopez,et al.  The Global Burden of Disease Study , 2003 .

[41]  C. Bias The Cochrane Collaboration's tool for assessing risk of bias in randomised trials , 2011 .

[42]  Lynnette Nathalie Lyzwinski An Examination of Obesity and Eating Disorder Prevention Programmes in Schools , 2022 .

[43]  Bonnie Spring,et al.  The Potential of Virtual Reality Technologies to Improve Adherence to Weight Loss Behaviors , 2011, Journal of diabetes science and technology.

[44]  David Ogilvie,et al.  Judging nudging: can nudging improve population health? , 2011, BMJ : British Medical Journal.

[45]  K. Patrick,et al.  Text4Diet: a randomized controlled study using text messaging for weight loss behaviors. , 2012, Preventive medicine.

[46]  D. Tate,et al.  Tweets, Apps, and Pods: Results of the 6-Month Mobile Pounds Off Digitally (Mobile POD) Randomized Weight-Loss Intervention Among Adults , 2011, Journal of medical Internet research.

[47]  G. L. Zimmerman,et al.  A 'stages of change' approach to helping patients change behavior. , 2000, American family physician.

[48]  Gösta Samuelson,et al.  Global strategy on diet, physical activity and health , 2004 .

[49]  P. Raven,et al.  Child, Adolescent and Family Refugee Mental Health: A Global Perspective , 1996 .

[50]  David Ogilvie,et al.  Behavior Change Techniques Used to Promote Walking and Cycling , 2013, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[51]  B. Spring,et al.  Integrating technology into standard weight loss treatment: a randomized controlled trial. , 2013, JAMA internal medicine.

[52]  R. Wise,et al.  How can drug addiction help us understand obesity? , 2005, Nature Neuroscience.

[53]  S. Michie,et al.  Using the Internet to Promote Health Behavior Change: A Systematic Review and Meta-analysis of the Impact of Theoretical Basis, Use of Behavior Change Techniques, and Mode of Delivery on Efficacy , 2010, Journal of medical Internet research.