To evaluate the effectiveness of wearable device interventions (eg, Fitbit) to improve physical activity (PA) outcomes (eg, steps/day, moderate to vigorous physical activity [MVPA]) in populations diagnosed with cardiometabolic chronic disease.
Data Source:
Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses, an electronic search of 5 databases (Medline, PsychINFO, Scopus, Web of Science, and PubMed) was conducted.
Study Inclusion and Exclusion Criteria:
Randomized controlled trials (RCTs) published between January 2000 and May 2018 that used a wearable device for the full intervention in adults (18+) diagnosed with a cardiometabolic chronic disease were included. Excluded trials included studies that used devices at pre–post only, devices that administered medication, and interventions with no prospective control group comparison.
Data Extraction:
Thirty-five studies examining 4528 participants met the inclusion criteria. Study quality and RCT risk of bias were assessed using the Cochrane Collaboration Tool.
Data Synthesis:
Meta-analyses to compute PA (eg, steps/day) and selected physical dispersion and summary effects were conducted using the raw unstandardized pooled mean difference (MD). Sensitivity analyses were examined.
Results:
Statistically significant increases in PA steps/day (MD = 2592 steps/day; 95% confidence interval [CI]: 1689-3496) and MVPA min/wk (MD = 36.31 min/wk; 95% CI: 18.33-54.29) were found for the intervention condition.
Conclusion:
Wearable devices positively impact physical health in clinical populations with cardiometabolic diseases. Future research using the most current technologies (eg, Fitbit) will serve to amplify these findings.
Centres for Disease Control and Prevention. Chronic diseases: The leading causes of death and disability in the United States. https://www.cdc.gov/chronicdisease/overview/index.htm. Published October 24, 2015. Accessed May 15, 2018.
WarburtonDENicolCWBredinSS. Health benefits of physical activity: the evidence. Can Med Assoc J. 2006;174(6):801–809.
11.
WarburtonDECharlesworthSIveyANettlefoldLBredinSS. A systematic review of the evidence for Canada’s Physical Activity Guidelines for Adults. Int J Behav Nutr Phys Act. 2010;7:39–39.
12.
ReinerMNiermannCJekaucDWollA. Long-term health benefits of physical activity—a systematic review of longitudinal studies. BMC Public Health. 2013;13:813.
PatelSParkHBonatoPChanLRodgersM. A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabil. 2012;9:21.
18.
CuroneDSeccoELTognettiA. Smart garments for emergency operators: the ProeTEX project. IEEE Trans Inf Technol Biomed. 2010;14(3):694–701.
19.
CoyleSLauK-TMoynaN. BIOTEX—Biosensing textiles for personalised healthcare management. IEEE Trans Inf Technol Biomed. 2010;14(2):364–370.
20.
AlletLKnolsRHShiratoKde BruinED. Wearable systems for monitoring mobility-related activities in chronic disease: a systematic review. Sensors. 2010;10(10):9026–9052.
21.
CaseMABurwickHAVolppKGPatelMS. Accuracy of smartphone applications and wearable devices for tracking physical activity data. JAMA. 2015;313(6):625–626.
22.
De BruinEDHartmannAUebelhartDMurerKZijlstraW. Wearable systems for monitoring mobility-related activities in older people: a systematic review. Clin Rehabil. 2008;22(10-11):878–895.
23.
MansiSMilosavljevicSBaxterGDTumiltySHendrickP. A systematic review of studies using pedometers as an intervention for musculoskeletal diseases. BMC Musculoskelet Disord. 2014;15:231.
24.
EvensonKRGotoMMFurbergRD. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015;12:159.
25.
Van RemoortelHGiavedoniSRasteY. Validity of activity monitors in health and chronic disease: a systematic review. Int J Behav Nutr Phys Act. 2012;9:84.
26.
LiberatiAAltmanDGTetzlaffJ. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6(7):e1000100.
27.
HigginsJPAltmanDGGøtzschePC. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.
28.
Review Manager 5.3 (RevMan5.3). Copenhagen, Denmark: Nordic Cochrane Centre. The Cochrane Collaboration; 2014.
29.
ValentineJCPigottTDRothsteinHR. How many studies do you need? A primer on statistical power for meta-analysis. J Educ Behav Stat. 2010;35(8):215–247.
30.
KarstoftKWindingKKnudsenSH. The effects of free-living interval-walking training on glycemic control, body composition, and physical fitness in type 2 diabetic patients: a randomized, controlled trial. Diabetes Care. 2013;36(2):228–236.
31.
MartinSSFeldmanDIBlumenthalRS. mActive: a randomized clinical trial of an automated mHealth intervention for physical activity promotion. J Am Heart Assoc. 2015;4(11):e002239.
32.
SangsterJFurberSAllman-FarinelliM. Effectiveness of a pedometer-based telephone coaching program on weight and physical activity for people referred to a cardiac rehabilitation program: a randomized controlled trial. J Cardiopulm Rehabil Prev. 2015;35(2):124–129.
33.
LuleyCBlaikAGötzA. Weight loss by telemonitoring of nutrition and physical activity in patients with metabolic syndrome for 1 year. J Am Coll Nutr. 2014;33(5):363–374.
34.
van der WeegenSVerweyRSpreeuwenbergM. It’s LiFe! Mobile and web-based monitoring and feedback tool embedded in primary care increases physical activity: a cluster randomized controlled trial. J Med Internet Res. 2015;17(1):e184.
35.
RossKMWingRR. Impact of newer self-monitoring technology and brief phone-based intervention on weight loss: a randomized pilot study. Obesity. 2016;24(8):1653–1659.
36.
HigginsJPTGreenS (eds.). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. http://handbook.cochrane.org. Accessed May 15, 2018.
37.
HedgesLVVeveaJL. Fixed-and random-effects models in meta-analysis. Psychol Methods. 1998;3(4):486–504.
38.
HedgesLVOlkinI. Statistical methods for meta-analysis. San Diego, CA: Academic Press; 1985.
39.
CoghillNCooperARThe effect of a home-based walking program on risk factors for coronary heart disease in hypercholesterolaemic men: a randomized controlled trial. Prev Med. 2008;46(6):545–551.
40.
FrederixIDriesscheNVHansenD. Increasing the medium-term clinical benefits of hospital-based cardiac rehabilitation by physical activity telemonitoring in coronary artery disease patients. Eur J Prev Cardiol. 2015;22(2):150–158.
41.
FrederixIHansenDConinxK. Medium-term effectiveness of a comprehensive internet-based and patient-specific telerehabilitation program with text messaging support for cardiac patients: randomized controlled trial. J Med Internet Res. 2015;17(7):e185. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4528085. Accessed September 30, 2017.
42.
GuiraudTGrangerRGremeauxV. Telephone support oriented by accelerometric measurements enhances adherence to physical activity recommendations in noncompliant patients after a cardiac rehabilitation program. Arch Phys Med Rehabil. 2012;93(12):2141–2147.
43.
HouleJDoyonOVadeboncoeurNTurbideGDiazAPoirierP. Innovative program to increase physical activity following an acute coronary syndrome: randomized controlled trial. Patient Educ Couns. 2011;85(3):e237–e244.
44.
KraalJJPeekNVan den Akker-Van MarleMEKempsHM. Effects of home-based training with telemonitoring guidance in low to moderate risk patients entering cardiac rehabilitation: short-term results of the FIT@Home study. Eur J Prev Cardiol. 2014;21(Suppl 2):26–31.
45.
VarnfieldMKarunanithiMLeeCK. Smartphone-based home care model improved use of cardiac rehabilitation in postmyocardial infarction patients: results from a randomised controlled trial. Heart. 2014;100(22):1770–1779.
46.
BentleyCLOtesileOBacigalupoR. Feasibility study of portable technology for weight loss and HbA1c control in type 2 diabetes. BMC Med Inform Decis Mak. 2016;16:92.
47.
De GreefKDeforcheBTudor-LockeCDe BourdeaudhuijI. A cognitive-behavioural pedometer-based group intervention on physical activity and sedentary behaviour in individuals with type 2 diabetes. Health Educ Res. 2010;25(5):724–736.
48.
HerzigKHAholaRLeppäluotoJJokelainenJJämsäTKeinänen-KiukaanniemiS. Light physical activity determined by a motion sensor decreases insulin resistance, improves lipid homeostasis and reduces visceral fat in high-risk subjects: preDiabEx study RCT. Int J Obes. 2014;38(8):1089–1096.
49.
KooBKHanKAAhnHJJungJYKimHCMinKW. The effects of total energy expenditure from all levels of physical activity vs. physical activity energy expenditure from moderate-to-vigorous activity on visceral fat and insulin sensitivity in obese type 2 diabetic women. Diabet Med. 2010;27(9):1088–1092.
50.
MaJYankVXiaoL. Translating the Diabetes Prevention Program lifestyle intervention for weight loss into primary care a randomized trial. JAMA Intern Med. 2013;173(2):113–121.
51.
SilfeeVPetosaRLaurentDSchaubTFochtB. Effect of a behavioral intervention on dimensions of self-regulation and physical activity among overweight and obese adults with type 2 diabetes: a pilot study. Psychol Health Med. 2016;21(6):715–723.
52.
SungKBaeS. Effects of a regular walking exercise program on behavioral and biochemical aspects in elderly people with type II diabetes. Nurs Health Sci. 2012;14(4):438–445.
53.
YatesTEdwardsonCLHensonJ. Walking away from type 2 diabetes: a cluster randomized controlled trial. Diabet Med. 2017;34(5):698–707.
54.
YatesTDaviesMGorelyTBullFKhuntiK. Effectiveness of a pragmatic education program designed to promote walking activity in individuals with impaired glucose tolerance. Diabetes Care. 2009;32(8):1404–1410.
55.
PaulaTPVianaLVNetoATLeitãoCBGrossJLAzevedoMJ. Effects of the DASH diet and walking on blood pressure in patients with type 2 diabetes and uncontrolled hypertension: a randomized controlled trial. J Clin Hypertens (Greenwich). 2015;17(11):895–901.
56.
De GreefKPDeforcheBIRuigeJB. The effects of a pedometer-based behavioral modification program with telephone support on physical activity and sedentary behavior in type 2 diabetes patients. Patient Educ Couns. 2011;84(2):275–279.
57.
DasguptaKRosenbergEJosephL; SMARTER Trial Group. Physician step prescription and monitoring to improve ARTERial health (SMARTER): a randomized controlled trial in patients with type 2 diabetes and hypertension. Diabetes Obes Metab. 2017;19(5):695–704.
58.
ShenoySGuglaniRSandhuJS. Effectiveness of an aerobic walking program using heart rate monitor and pedometer on the parameters of diabetes control in Asian Indians with type 2 diabetes. Prim Care Diabetes. 2010;4(1):41–45.
59.
BiddleSJHEdwardsonCLWilmotEG. A randomised controlled trial to reduce sedentary time in young adults at risk of type 2 diabetes mellitus: project STAND (Sedentary Time ANd Diabetes). PLoS One. 2015;10(12):e0143398.
60.
Cadmus-BertramLAMarcusBHPattersonRE. Randomized trial of a Fitbit-based physical activity intervention for women. Am J Prev Med. 2015;49(3):414–418.
61.
HartmanSJNelsonSHCadmus-BertramLAPattersonREParkerBAPierceJPTechnology- and phone-based weight loss intervention: pilot RCT in women at elevated breast cancer risk. Am J Prev Med. 2016;51(5):714–721.
62.
LyonsEJSwartzMCLewisZHMartinezEJenningsKFeasibility and acceptability of a wearable technology physical activity intervention with telephone counseling for mid-aged and older adults: a randomized controlled pilot trial. JMIR Mhealth Uhealth. 2017;5(3):e28.
63.
PetrellaRJStuckeyMIShapiroSGillDP. Mobile health, exercise and metabolic risk: a randomized controlled trial. BMC Public Health. 2014;14:1082.
64.
RenaultKMNørgaardKNilasL. The treatment of obese pregnant women (TOP) study: a randomized controlled trial of the effect of physical activity intervention assessed by pedometer with or without dietary intervention in obese pregnant women. Am J Obstet Gynecol. 2014;210(2):134.e1–134.e9.
65.
WangJBCadmus-BertramLANatarajanL. Wearable sensor/device (Fitbit One) and SMS text-messaging prompts to increase physical activity in overweight and obese adults: a randomized controlled trial. Telemed J E Health. 2015;21(10):782–792.
66.
WatsonABickmoreTCangeAKulshreshthaAKvedarJ. An internet-based virtual coach to promote physical activity adherence in overweight adults: randomized controlled trial. Eysenbach G, ed. J Med Internet Res. 2012;14(1):e1.
67.
TakahashiPYQuiggSMCroghanITSchroederDREbbertJO. Effect of pedometer use and goal setting on walking and functional status in overweight adults with multimorbidity: a crossover clinical trial. Clin Interv Aging. 2016;11:1099–1106.
68.
McCarneyRWarnerJIliffeSvan HaselenRGriffinMFisherP. The Hawthorne Effect: a randomised, controlled trial. BMC Med Res Methodol. 2007;7:30.
69.
FrankeRHKaulJD. The Hawthorne experiments: first statistical interpretation. Am Sociol Rev. 1978;43(5):623–643.
70.
MarshallSJLevySSTudor-LockeCE. Translating physical activity recommendations into a pedometer-based step goal. Am J Prev Med. 2009;36(5):410–415.
71.
Tudor-LockeCBassettDRJr. How many steps/day are enough?Sports Med. 2004;34(1):1–8.
72.
Tudor-LockeCCraigCLAoyagiY. How many steps/day are enough? For older adults and special populations. Int J Behav Nutr Phys Act. 2011;8:80.
73.
PirbaglouMKatzJMotamedM. Personal health coaching as a type 2 diabetes mellitus self-management strategy: A systematic review and meta-analysis of randomized controlled trials. Am J Health Promot. 2018;32(7):1613–1626.
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
