Cited by 150Mobile Health and mHealth ApplicationsDigital Mental Health InterventionsMobile Learning in Education

A meta‐analysis of overall effects of weight loss interventions delivered via mobile phones and effect size differences according to delivery mode, personal contact, and intervention intensity and duration

Open access
Schippers, M., Adam, P. C. G., Smolenski, D. J., Wong, H. T. H., de Wit, J. B. F.·2017·Obesity Reviews

Abstract

Summary: Weight loss interventions are delivered through various mediums including, increasingly, mobile phones. This systematic review and meta‐analysis assesses whether interventions delivered via mobile phones reduce body weight and which intervention characteristics are associated with efficacy. The study included randomised controlled trials assessing the efficacy of weight loss interventions delivered via mobile phones. A meta‐analysis to test intervention efficacy was performed, and subgroup analyses were conducted to determine whether interventions' delivery mode(s), inclusion of personal contact, duration and interaction frequency improve efficacy. Pooled body weight reduction (d = −0.23; 95% confidence interval = −0.38, −0.08) was significant. Interventions delivered via other modes in addition to the mobile phone were associated with weight reduction. Personal contact and more frequent interactions in interventions were also associated with greater weight reduction. In conclusion, the current body of evidence shows that interventions delivered via mobile phones produce a modest reduction in body weight when combined with other delivery modes. Delivering interventions with frequent and personal interactions may in particular benefit weight loss results.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/obr.12492

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The meta-analysis by Schippers et al reported that mobile apps with personal interaction tools (messages, calls, email, or in-person meetings) are more effective for weight loss than automated interaction.

    “The meta-analysis by Schippers et al [90] reported that mobile apps with personal interaction tools (messages, calls, email, or in-person meetings) are more effective for weight loss than automated interaction.”

    From Digital Health Interventions to Prevent Type 2 Diabetes Mellitus: Systematic Review (2025) · cites this paper as [90]

    In “Stratification by personal contact” (page not available), the meta-analysis reports significantly greater weight-loss effects for mobile-phone interventions with personal contact than for those without it. “Characteristics of included studies” identifies non-automated messages, emails, calls and face-to-face contact as examples. The paper does not specifically compare mobile apps with personal interaction tools against apps with automated interaction; its comparison is broader—mobile-phone interventions with versus without personal contact. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 26

  1. Ng M, Fleming T, Robinson M et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384: 766-781.
  2. Hruby A, Hu FB. The epidemiology of obesity: a big picture. Pharmacoeconomics 2015; 33: 673-689.
  3. Sabin MA, Kao KT, Juonala M, Baur LA, Wake M. Viewpoint article: childhood obesity -looking back over 50 years to begin to look forward. J Paediatr Child Health 2015; 51: 82-86.
  4. Lim SS, Vos T, Flaxman AD et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2013; 380: 2224-2260.
  5. Withrow D, Alter D. The economic burden of obesity world- wide: a systematic review of the direct costs of obesity. Obes Rev 2011; 12: 131-141.
  6. Franz MJ, VanWormer JJ, Crain AL et al. Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. J Am Diet Assoc 2007; 107: 1755-1767.
  7. Preziosa A, Grassi A, Gaggioli A, Riva G. Therapeutic applica- tions of the mobile phone. Br J Guid Counc 2009; 37: 313-325.
  8. Teixeira PJ, Carraça EV, Marques MM et al. Successful behav- ior change in obesity interventions in adults: a systematic review of self-regulation mediators. BMC Med 2015; 13: 1.
  9. McPhail S, Schippers M. An evolving perspective on physical activity counselling by medical professionals. BMC Fam Pract 2012; 13: 1-8.
  10. Fanning J, Mullen SP, McAuley E. Increasing physical activity with mobile devices: a meta-analysis. J Med Internet Res 2012; 14: e161.
  11. Coons MJ, DeMott A, Buscemi J et al. Technology interven- tions to curb obesity: a systematic review of the current literature. Curr Cardiovasc Risk Rep 2012; 6: 120-134.
  12. Bort-Roig J, Gilson ND, Puig-Ribera A, Contreras RS, Trost SG. Measuring and influencing physical activity with smartphone technology: a systematic review. Sports Med 2014; 44: 671-686.
  13. Stephens J, Allen J. Mobile phone interventions to increase physical activity and reduce weight: a systematic review. J Cardiovasc Nurs 2013; 28: 320.
  14. Bacigalupo R, Cudd P, Littlewood C, Bissell P, Hawley M, Buckley WH. Interventions employing mobile technology for over- weight and obesity: an early systematic review of randomized controlled trials. Obes Rev 2013; 14: 279-291.
  15. Khokhar B, Jones J, Ronksley PE, Armstrong MJ, Caird J, Rabi D. Effectiveness of mobile electronic devices in weight loss among overweight and obese populations: a systematic review and meta-analysis. BMC Obes 2014; 1: 1.
  16. Lyzwinski LN. A systematic review and meta-analysis of mobile devices and weight loss with an intervention content analysis. J Pers Med 2014; 4: 311-385.
  17. Siopis G, Chey T, Allman-Farinelli M. A systematic review and meta-analysis of interventions for weight management using text messaging. J Hum Nutr Diet 2015; 28: 1-15.
  18. Norman GJ, Kolodziejczyk JK, Adams MA, Patrick K, Marshall SJ. Fruit and vegetable intake and eating behaviors medi- ate the effect of a randomized text-message based weight loss program. Prev Med 2013; 56: 3-7.
  19. Patrick K, Norman GJ, Davila EP et al. Outcomes of a 12-month technology-based intervention to promote weight loss in adolescents at risk for type 2 diabetes. J Diabetes Sci Technol 2013; 7: 759-770.
  20. Lin PH, Wang Y, Levine E et al. A text messaging-assisted ran- domized lifestyle weight loss clinical trial among overweight adults in Beijing. Obesity 2014; 22: E29-E37.
  21. Shaw RJ, Bosworth HB, Silva SS et al. Mobile health messages help sustain recent weight loss. Am J Med 2013; 126: 1002-1009.
  22. Shapiro JR, Koro T, Doran N et al. Text4Diet: a randomized controlled study using text messaging for weight loss behaviors. Prev Med 2012; 55: 412-417.
  23. Hebden L, Cook A, Ploeg H, King L, Bauman A, Allman- Farinelli M. A mobile health intervention for weight management among young adults: a pilot randomised controlled trial. J Hum Nutr Diet 2014; 27: 322-332.
  24. Glynn LG, Hayes PS, Casey M et al. Effectiveness of a smartphone application to promote physical activity in primary care: the SMART MOVE randomised controlled trial. Br J Gen Pract 2014; 64: e384-ee91.
  25. Burke LE, Conroy MB, Sereika SM et al. The effect of electronic self-monitoring on weight loss and dietary intake: a randomized be- havioral weight loss trial. Obesity 2011; 19: 338-344.
  26. Egger M, Smith GD, Schneider M, Minder C. Bias in meta- analysis detected by a simple, graphical test. BMJ 1997; 315: 629-634.

Cited by

Sorted by citations

Authors
Schippers, M., Adam, P. C. G., Smolenski, D. J., Wong, H. T. H., & de Wit, J. B. F.
Affiliations
  • UNSW Sydney (AU)
  • National Center for Telehealth & Technology Tacoma WA USA
  • Centre for Social Research in Health, UNSW Australia Sydney Australia
Corresponding author
Schippers, M.
Venue
Obesity Reviews
Publisher
Wiley
Published
2017-02-10
Volume
18
Issue
4
Pages
450-459
ISSN
  • 1467-7881 (ISSN-L)
  • 1467-789X
OpenAlex
W2586413427
Cited by
150
References
18
Citations by year
2026: 8 · 2025: 14 · 2024: 20 · 2023: 17 · 2022: 11 · 2021: 21 · 2020: 16 · 2019: 28 · 2018: 11 · 2017: 4
FWCI
2.84
Type
journal article
Language
en
Open access
Locations
  • Obesity Reviews (publishedVersion)
  • PubMed (publishedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • Utrecht University Repository (Utrecht University) (submittedVersion)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Keywords
weight loss interventions, weight loss, intervention delivery mode, personal contact, interaction frequency, intervention intensity, intervention duration, obesity treatment, mobile health
MeSH terms
Humans, Obesity, Primary Prevention, Time Factors, Weight Loss, Health Behavior, Randomized Controlled Trials as Topic, Cell Phone, Text Messaging, Mobile Applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review