Technology-based and supervised exercise interventions for individuals with type 2 diabetes: randomized controlled trial
Abstract
Aims The purpose of this study was to estimate, for people with type 2 diabetes (T2D), the extent to which glycemic control was affected by a 12-week program using mobile app and wearable smartwatch in comparison to supervised exercise training.Methods This study was a stratified, randomized, assessor-blind, controlled, pragmatic trial with three parallel groups which were supervised, mobile app and wearable smartwatch. Individually tailored exercise regimens delivered through a supervisor, mobile app and wearable smartwatch. Programs consisted of aerobic, resistance exercises, calisthenic, flexibility, balance, and coordination exercises. Primary outcome was change in glycemic control (HbA1c); secondary outcome was Six Minute Walk Test; and explanatory outcomes were exercise behaviour, muscle function, and physical capacity. The groups were contrasted for change in HbA1c and absolute reduction of ≥0.5% (Minimal Important Change). Linear and logistic regressions were used to compare the groups and generalized estimated equations were used to analyze the explanatory outcomes.Results In total, 90 people were randomized, 6 were lost over 12 weeks, leaving 84 with outcome data. The difference in HbA1c did not differ between the supervised and the technology groups combined and between the mobile app and smartwatch group. Proportions of people achieving a clinically meaningful difference on HbA1c between the supervised and technology groups were similar (46% vs 43%) and the associated OR was 0.87 (95%CI:0.34-2.28). Within the two technology groups, proportions of people achieving a clinically meaningful difference in HbA1c were 48% in the mobile app and 38% in the smartwatch groups and the associated OR was 0.65 (95%CI:0.21-2.03). The groups did not differ on secondary and explanatory outcomes.Conclusions The results of our trial provide evidence that all outcomes have improved in all groups regardless of the exercise delivery method. Considering the supervised programs are not available for everybody, technological options are crucial to implement to help individuals self-manage most aspects of their diabetes.
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Digital wearable devices contribute not only by recording or prompting exercise, but also by embedding behavior regulation into everyday life and supporting the initiation, adjustment, and maintenance of exercise behaviors.
“In this sense, digital wearable devices contribute not only by recording or prompting exercise, but also by embedding behavior regulation into everyday life and supporting the initiation, adjustment, and maintenance of exercise behaviors (14, 15).”
Reward mechanisms, progress tracking, and achievement feedback may help sustain engagement.
“Reward mechanisms, progress tracking, and achievement feedback may help sustain engagement (15, 21–24)”
Real-time feedback enhances the intervention potential of digital wearable devices by transforming data into actionable information through reminders, notifications, trend displays, and progress summaries.
“Real-time feedback further enhances the intervention potential of digital wearable devices by transforming data into actionable information through reminders, notifications, trend displays, and progress summaries (15, 17, 21, 22).”
Family involvement, peer comparison, clinician interaction, and remote feedback may broaden the social context of exercise behavior.
“while family involvement, peer comparison, clinician interaction, and remote feedback may broaden the social context of exercise behavior (14, 15, 19).”
Several structured and supervised interventions resulted in improved liver function, including reductions in hepatic enzyme levels (ALT, γ-GT), better scores on indices of non-alcoholic fatty liver disease (NAFLD), suggesting a decrease in ectopic liver fat.
“In addition, several interventions resulted in improved liver function, including reductions in hepatic enzyme levels (ALT, γ-GT), as well as better scores on indices of non-alcoholic fatty liver disease (NAFLD), suggesting a decrease in ectopic liver fat [22,37].”
No significant differences in HbA1c outcomes were observed between participants in supervised exercise programmes and those using mobile applications or smartwatches.
“As noted by Timurtas et al., no significant differences in HbA1c outcomes were observed between participants in supervised exercise programmes and those using mobile applications or smartwatches.”
The high resource demands of supervised programmes raise concerns regarding their scalability, economic sustainability, and accessibility, particularly within healthcare systems with limited resources or among socioeconomically disadvantaged populations.
“Moreover, the high resource demands of supervised programmes raise important concerns regarding their scalability, economic sustainability, and accessibility, particularly within healthcare systems with limited resources or among socioeconomically disadvantaged populations [37].”
Advanced devices, when appropriately implemented, may achieve comparable clinical outcomes to traditional supervised models.
“This finding suggests that advanced devices, when appropriately implemented, may achieve comparable clinical outcomes to traditional supervised models [37].”
Cites
2 retracted
An overview of randomization techniques: An unbiased assessment of outcome in clinical research
Suresh, K. (2011) · Journal of Human Reproductive Sciences · doi:10.4103/0974-1208.82352 · Cited by 1,070 · see citing works
RetractedZolfaghari, M., Mousavifar, S. A., & Haghani, H. (2012) · Journal of Diabetes & Metabolic Disorders · doi:10.1186/2251-6581-11-7 · Cited by 47 · see citing works
RetractedInternational physical activity questionnaire: 12-country reliability and validity
CRAIG, C. L., MARSHALL, A. L., SJ??STR??M, M., BAUMAN, A. E., BOOTH, M. L., AINSWORTH, B. E., PRATT, M., EKELUND, U., YNGVE, A., SALLIS, J. F., et al. (2003) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000078924.61453.fb · Cited by 21,619 · see citing works
IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040
Ogurtsova, K., Fernandes, J. D. D. R., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., Cavan, D. A., Shaw, J. E., & Makaroff, L. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.03.024 · Cited by 6,977 · see citing works
Diagnosis and classification of diabetes mellitus
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc10-s062 · Cited by 5,491 · see citing works
Toward an Emotion Nuanced Sensemaking Perspective of Organizational Consultation
Lundberg, C. C. (2000) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-60752-837-120251015 · Cited by 3,340 · see citing works
Holland, A. E., Spruit, M. A., Troosters, T., Puhan, M. A., Pepin, V., Saey, D., McCormack, M. C., Carlin, B. W., Sciurba, F. C., Pitta, F. D. O., et al. (2014) · European Respiratory Journal · doi:10.1183/09031936.00150314 · Cited by 2,558 · see citing works
Using Pedometers to Increase Physical Activity and Improve Health: A Systematic Review
Bravata, D. M., Smith-Spangler, C., Sundaram, V., Gienger, A. L., Lin, N., Lewis, R., Stave, C. D., Olkin, I., & Sirard, J. R. (2007) · JAMA · doi:10.1001/jama.298.19.2296 · Cited by 2,064 · see citing works
Colberg, S. R., Sigal, R. J., Fernhall, B., Regensteiner, J. G., Blissmer, B. J., Rubin, R. R., Chasan-Taber, L., Albright, A. L., & Braun, B. (2010) · Diabetes Care · doi:10.2337/dc10-9990 · Cited by 1,955 · see citing works
Reliability and validity of grip and pinch strength evaluations
Mathiowetz, V. G., Weber, K., Volland, G., & Kashman, N. (1984) · The Journal Of Hand Surgery · doi:10.1016/s0363-5023(84)80146-x · Cited by 1,861 · see citing works
The PRECIS-2 tool: designing trials that are fit for purpose
Loudon, K., Treweek, S., Sullivan, F., Donnan, P., Thorpe, K. E., & Zwarenstein, M. (2015) · BMJ · doi:10.1136/bmj.h2147 · Cited by 1,846 · see citing works
Davies, M. J., D’Alessio, D. A., Fradkin, J., Kernan, W. N., Mathieu, C., Mingrone, G., Rossing, P., Tsapas, A., Wexler, D. J., & Buse, J. B. (2018) · Diabetologia · doi:10.1007/s00125-018-4729-5 · Cited by 1,455 · see citing works
Markland, D., & Tobin, V. (2004) · Journal of Sport and Exercise Psychology · doi:10.1123/jsep.26.2.191 · Cited by 1,444 · see citing works
Physical Activity/Exercise and Type 2 Diabetes
Sigal, R. J., Kenny, G. P., Wasserman, D. H., Castaneda-Sceppa, C., & White, R. D. (2006) · Diabetes Care · doi:10.2337/dc06-9910 · Cited by 949 · see citing works
Twelve-year trends in the prevalence and risk factors of diabetes and prediabetes in Turkish adults
Satman, İ., Ömer, B., Tütüncü, Y., Kalaça, S., Gedik, S., Dınççağ, N., Karşıdağ, K., Genç, S., Telci, A., Canbaz, B., et al. (2013) · European Journal of Epidemiology · doi:10.1007/s10654-013-9771-5 · Cited by 788 · see citing works
Orrow, G., Kinmonth, A.-L., Sanderson, S., & Sutton, S. (2012) · BMJ · doi:10.1136/bmj.e1389 · Cited by 739 · see citing works
Brickwood, K.-J., Watson, G., O'Brien, J., & Williams, A. D. (2019) · JMIR mHealth and uHealth · doi:10.2196/11819 · Cited by 690 · see citing works
Heart Rate and Exercise Intensity During Sports Activities
Karvonen, J., & Vuorimaa, T. (1988) · Sports Medicine · doi:10.2165/00007256-198805050-00002 · Cited by 610 · see citing works
The Sit and Reach—A Test of Back and Leg Flexibility
Wells, K. F., & Dillon, E. K. (1952) · Research Quarterly American Association for Health Physical Education and Recreation · doi:10.1080/10671188.1952.10761965 · Cited by 581 · see citing works
Effectiveness of Telerehabilitation in Physical Therapy: A Rapid Overview
Pamela Serón, S., Oliveros, M. J., Gutiérrez-Arias, R. E., Fuentes-Aspe, R., Torres‐Castro, R., Merino-Osorio, C., Nahuelhual, P., Quiroz, J. I., Jalil, Y., Solano, R., et al. (2021) · Physical Therapy · doi:10.1093/ptj/pzab053 · Cited by 577 · see citing works
Reference Values for a Multiple Repetition 6-Minute Walk Test in Healthy Adults Older Than 20 Years
Gibbons, W. J., Fruchter, N., Sloan, S., & Levy, R. D. (2001) · Journal of Cardiopulmonary Rehabilitation · doi:10.1097/00008483-200103000-00005 · Cited by 550 · see citing works
Marcus, B. H., & Simkin, L. R. (1994) · Medicine & Science in Sports & Exercise · doi:10.1249/00005768-199411000-00016 · Cited by 411 · see citing works
Hou, C., Carter, B., Hewitt, J., Francisa, T., & Mayor, S. (2016) · Diabetes Care · doi:10.2337/dc16-0346 · Cited by 411 · see citing works
Quinn, C. C., Clough, S. S., Minor, J. M., Lender, D., Okafor, M. C., & Gruber-Baldini, A. (2008) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0283 · Cited by 406 · see citing works
Cradock, K. A., ÓLaighin, G., Finucane, F. M., Gainforth, H. L., Quinlan, L. R., & Ginis, K. A. M. (2017) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-016-0436-0 · Cited by 343 · see citing works
Changing Physical Activity Behavior in Type 2 Diabetes
Avery, L., Flynn, D., van Wersch, A., Sniehotta, F. F., & Trenell, M. I. (2012) · Diabetes Care · doi:10.2337/dc11-2452 · Cited by 340 · see citing works
Schwingshackl, L., Missbach, B., Dias, S., König, J., & Hoffmann, G. (2014) · Diabetologia · doi:10.1007/s00125-014-3303-z · Cited by 264 · see citing works
Beinart, N., Norton, S., Dowling, D., Gavriloff, D., Vari, C., Weinman, J. A., & Godfrey, E. L. (2016) · Physiotherapy · doi:10.1016/j.physio.2016.11.001 · Cited by 262 · see citing works
Gal, R., May, A. M., van Overmeeren, E. J., Simons, M., & Monninkhof, E. M. (2018) · Sports Medicine - Open · doi:10.1186/s40798-018-0157-9 · Cited by 257 · see citing works
(1992) · Annals of Internal Medicine · doi:10.7326/0003-4819-117-4-352_1 · Cited by 190 · see citing works
Candidate reference methods for hemoglobin A1c based on peptide mapping
Kobold, U., Jeppsson, J., Dülffer, T., Finke, A., Hoelzel, W., & Miedema, K. (1997) · Clinical Chemistry · doi:10.1093/clinchem/43.10.1944 · Cited by 180 · see citing works
Grace, A., Chan, E., Giallauria, F., Graham, P. L., & Smart, N. A. (2017) · Cardiovascular Diabetology · doi:10.1186/s12933-017-0518-6 · Cited by 174 · see citing works
Connelly, J., Kirk, A., Masthoff, J., & MacRury, S. (2013) · Diabetic Medicine · doi:10.1111/dme.12289 · Cited by 169 · see citing works
Systematic Review of Mobile Health Applications in Rehabilitation
Nussbaum, R., Kelly, C. J., Quinby, E., Mac, A., Parmanto, B., & Dicianno, B. E. (2018) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2018.07.439 · Cited by 163 · see citing works
Smartphone-Based Technology in Diabetes Management
Doupis, J., Festas, G., Tsilivigos, C., Efthymiou, V., & Kokkinos, A. D. (2020) · Diabetes Therapy · doi:10.1007/s13300-020-00768-3 · Cited by 140 · see citing works
Baskerville, R., Ricci‐Cabello, I., Roberts, N., & Farmer, A. (2017) · Diabetic Medicine · doi:10.1111/dme.13331 · Cited by 131 · see citing works
Hou, C., Xu, Q., Diao, S., Hewitt, J., Li, J., & Carter, B. (2018) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.13307 · Cited by 127 · see citing works
Estrada, E., Ferrer, E. E., & Pardo, A. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02696 · Cited by 125 · see citing works
Tate, D. F., Lyons, E., & Valle, C. G. (2015) · Diabetes Spectrum · doi:10.2337/diaspect.28.1.45 · Cited by 119 · see citing works
Differences in interpretation of haemoglobin A1c values among diabetes care professionals.
Lenters‐Westra, E., Schindhelm, R. K., Bilo, H. J. G., Groenier, K. H., & Slingerland, R. J. (2014) · PubMed · Cited by 92 · see citing works
Weering, M. D.-V., Jansen-Kosterink, S. M., Frazer, S. W. T., & Vollenbroek-Hutten, M. M. R. (2017) · Frontiers in Medicine · doi:10.3389/fmed.2017.00208 · Cited by 74 · see citing works
Wu, X., Kee, J. C. Y., Threapleton, D. E., Ma, R. C. W., Lam, V., Lee, E. K. P., Wong, S. Y. S., & Chung, V. C. (2018) · Obesity Reviews · doi:10.1111/obr.12669 · Cited by 73 · see citing works
McMillan, K. A., Kirk, A. F., Hewitt, A., & MacRury, S. M. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816656018 · Cited by 48 · see citing works
Höchsmann, C., Walz, S. P., Schäfer, J., Holopainen, J. P., Hanssen, H., & Schmidt‐Trucksäss, A. (2017) · Trials · doi:10.1186/s13063-017-1853-3 · Cited by 45 · see citing works
Empowering Diabetes Self-Management Through Technology and Nurse Health Coaching
Miyamoto, S., Henderson, S., Fazio, S., Saconi, B., Thiede, E., Greenwood, D. A., & Young, H. M. (2019) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721719879421 · Cited by 32 · see citing works
Phillips, S. A., Ali, M. M., Modrich, C., Oke, S., Elokda, A. S., Laddu, D., & Bond, S. (2018) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2018.12.007 · Cited by 26 · see citing works
Telerehabilitation intervention for type 2 diabetes
Durutürk, N. (2020) · World Journal of Diabetes · doi:10.4239/wjd.v11.i6.218 · Cited by 26 · see citing works
Support for diabetes using technology: a pilot study to improve self-management.
Hunt, C. W., Sanderson, B., & Ellison, K. J. (2014) · PubMed · Cited by 24 · see citing works
Usability of Mobile Health Application for Individuals with Type 2 Diabetes Mellitus and Clinicians
Timurtaş, E., & Polat, M. G. (2020) · Clinical and Experimental Health Sciences · doi:10.33808/clinexphealthsci.599548 · Cited by 7 · see citing works
Self-citationTimurtaş, E. (2022) · Haydarpaşa Numune medical journal (Online) · doi:10.14744/hnhj.2022.48295 · Cited by 4 · see citing works
Relationship between age and Hba1c in Turkish patients
Acar, B., Ünübol, M., & Şenel, E. (2014) · Endocrine Abstracts · doi:10.1530/endoabs.35.p343 · Cited by 1 · see citing works
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Tarricone, R., Petracca, F., Svae, L., Cucciniello, M., & Ciani, O. (2024) · eBioMedicine · doi:10.1016/j.ebiom.2024.105091 · Cited by 26 · see citing works
Chua, R. E. C., Lau, Y., Ang, W. W., Boey, A. A. Y. F., & Lau, S. T. (2024) · Journal of Diabetes · doi:10.1111/1753-0407.70002 · Cited by 14 · see citing works
Peng, P., Zhang, N., Huang, J., Jiao, X., & Shen, Y. (2023) · Endocrine Practice · doi:10.1016/j.eprac.2023.02.004 · Cited by 12 · see citing works
Laffi, A., Persiani, M., Piras, A., Meoni, A., & Raffi, M. (2025) · Healthcare · doi:10.3390/healthcare13192422 · Cited by 9 · see citing works
Liu, K., & Xia, Y. (2025) · Digital Health · doi:10.1177/20552076251326126 · Cited by 7 · see citing works
Sun, W., Xie, D., Hou, W., Zhang, M., Wang, C., Wang, Z., Yang, H., Xu, G., & Dai, H. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1871682
- Authors
- Timurtas, E., Inceer, M., Mayo, N., Karabacak, N., Sertbas, Y., & Polat, M. G.
- Affiliations
- McGill University Health Centre (CA)
- Marmara University (TR)
- Corresponding author
- Inceer, Mehmet
- Mayo, Nancy
- Karabacak, Neslihan
- Venue
- Primary care diabetes
- Publisher
- Elsevier BV
- Published
- 2022-02
- Volume
- 16
- Issue
- 1
- Pages
- 49-56
- ISSN
- 1751-9918 (ISSN-L)
- OpenAlex
- W4200035234
- Cited by
- 30
- References
- 51
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 12 · 2023: 5
- FWCI
- 4.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Primary care diabetes (publishedVersion)
- PubMed (publishedVersion)
- Dspace Repository (Marmara Üniversitesi) (submittedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- type 2 diabetes, glycemic control, HbA1c, supervised exercise, mobile health apps, smartwatches, exercise intervention, diabetes self-management, exercise behavior, muscle function, physical capacity, minimal important change
- MeSH terms
- Diabetes Mellitus, Type 2, Exercise Therapy, Humans, Technology, Exercise, Mobile Applications
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