Key Elements of mHealth Interventions to Successfully Increase Physical Activity: Meta-Regression

被引:54
作者
Eckerstorfer, Lisa, V [1 ]
Tanzer, Norbert K. [1 ]
Vogrincic-Haselbacher, Claudia [1 ]
Kedia, Gayannee [1 ]
Brohmer, Hilmar [1 ]
Dinslaken, Isabelle [1 ]
Corcoran, Katja [1 ,2 ]
机构
[1] Karl Franzens Univ Graz, Inst Psychol, Univ Pl 1, A-8010 Graz, Austria
[2] BioTechMed Graz, Graz, Austria
来源
JMIR MHEALTH AND UHEALTH | 2018年 / 6卷 / 11期
基金
奥地利科学基金会;
关键词
exercise; physical activity; mHealth; behavior change; meta-analysis; meta-regression; RANDOMIZED CONTROLLED-TRIAL; BEHAVIOR-CHANGE TECHNIQUES; TEXT MESSAGES; SMARTPHONE APPLICATION; HEALTH BEHAVIORS; PRIMARY-CARE; ADULTS; WALKING; IMPROVE; PEOPLE;
D O I
10.2196/10076
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Mobile technology gives researchers unimagined opportunities to design new interventions to increase physical activity. Unfortunately, it is still unclear which elements are useful to initiate and maintain behavior change. Objective: In this meta-analysis, we investigated randomized controlled trials of physical activity interventions that were delivered via mobile phone. We analyzed which elements contributed to intervention success. Methods: After searching four databases and science networks for eligible studies, we entered 50 studies with N=5997 participants into a random-effects meta-analysis, controlling for baseline group differences. We also calculated meta-regressions with the most frequently used behavior change techniques (behavioral goals, general information, self-monitoring, information on where and when, and instructions on how to) as moderators. Results: We found a small overall effect of the Hedges g=0.29, (95% CI 0.20 to 0.37) which reduced to g=0.22 after correcting for publication bias. In the moderator analyses, behavioral goals and self-monitoring each led to more intervention success. Interventions that used neither behavioral goals nor self-monitoring had a negligible effect of g=0.01, whereas utilizing either technique increased effectiveness by Delta g=0.31, but combining them did not provide additional benefits (Delta g=0.36). Conclusions: Overall, mHealth interventions to increase physical activity have a small to moderate effect. However, including behavioral goals or self-monitoring can lead to greater intervention success. More research is needed to look at more behavior change techniques and their interactions. Reporting interventions in trial registrations and articles need to be structured and thorough to gain accurate insights. This can be achieved by basing the design or reporting of interventions on taxonomies of behavior change.
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页数:17
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共 98 条
  • [1] Lifestyle Intervention Using an Internet-Based Curriculum with Cell Phone Reminders for Obese Chinese Teens: A Randomized Controlled Study
    Abraham, Anisha A.
    Chow, Wing-Chi
    So, Hung-Kwan
    Yip, Benjamin Hon-Kei
    Li, Albert M.
    Kumta, Shekhar M.
    Woo, Jean
    Chan, Suk-Mei
    Lau, Esther Yuet-Ying
    Nelson, E. Anthony S.
    [J]. PLOS ONE, 2015, 10 (05):
  • [2] An Adaptive Physical Activity Intervention for Overweight Adults: A Randomized Controlled Trial
    Adams, Marc A.
    Sallis, James F.
    Norman, Gregory J.
    Hovell, Melbourne F.
    Hekler, Eric B.
    Perata, Elyse
    [J]. PLOS ONE, 2013, 8 (12):
  • [3] Randomized Controlled Pilot Study Testing Use of Smartphone Technology for Obesity Treatment
    Allen, Jerilyn K.
    Stephens, Janna
    Himmelfarb, Cheryl R. Dennison
    Stewart, Kerry J.
    Hauck, Sara
    [J]. JOURNAL OF OBESITY, 2013, 2013
  • [4] A Mobile Health Lifestyle Program for Prevention of Weight Gain in Young Adults (TXT2BFiT): Nine-Month Outcomes of a Randomized Controlled Trial
    Allman-Farinelli, Margaret
    Partridge, Stephanie Ruth
    McGeechan, Kevin
    Balestracci, Kate
    Hebden, Lana
    Wong, Annette
    Phongsavan, Philayrath
    Denney-Wilson, Elizabeth
    Harris, Mark F.
    Bauman, Adrian
    [J]. JMIR MHEALTH AND UHEALTH, 2016, 4 (02): : 408 - 419
  • [5] [Anonymous], NUMB SMARTPH US US 2
  • [6] [Anonymous], 2018, NUMB MOB PHON US WOR
  • [7] Assessment of study quality for systematic reviews: a comparison of the Cochrane Collaboration Risk of Bias Tool and the Effective Public Health Practice Project Quality Assessment Tool: methodological research
    Armijo-Olivo, Susan
    Stiles, Carla R.
    Hagen, Neil A.
    Biondo, Patricia D.
    Cummings, Greta G.
    [J]. JOURNAL OF EVALUATION IN CLINICAL PRACTICE, 2012, 18 (01) : 12 - 18
  • [8] Borenstein M., 2009, Introduction to meta-analysis, DOI DOI 10.1002/9781119558378
  • [9] Measuring and Influencing Physical Activity with Smartphone Technology: A Systematic Review
    Bort-Roig, Judit
    Gilson, Nicholas D.
    Puig-Ribera, Anna
    Contreras, Ruth S.
    Trost, Stewart G.
    [J]. SPORTS MEDICINE, 2014, 44 (05) : 671 - 686
  • [10] Randomized Trial of a Fitbit-Based Physical Activity Intervention for Women
    Cadmus-Bertram, Lisa A.
    Marcus, Bess H.
    Patterson, Ruth E.
    Parker, Barbara A.
    Morey, Brittany L.
    [J]. AMERICAN JOURNAL OF PREVENTIVE MEDICINE, 2015, 49 (03) : 414 - 418