Improved Medication Adherence and Frequency of Blood Glucose Self-Testing Using an m-Health Platform Versus Usual Care in a Multisite Randomized Clinical Trial Among People with Type 2 Diabetes in India
Abstract
BACKGROUND: In 2015, India had an estimated 69.2 million people with diabetes and a national prevalence of 8.7%. Evidence is mounting for the benefits of telemedicine in diabetes care, but remains limited on mobile-health (m-Health) interventions. INTRODUCTION: This study assessed the impact of an m-Health diabetes platform on clinical outcomes, patient-reported outcomes, patient and provider satisfaction, and app usage. MATERIALS AND METHODS: This open-label, two-arm parallel study enrolled 91 people at 3 sites in India, aged 18-65, with type 2 diabetes, and an A1c between 7.5% and 12.5% (58-113 mmol/mol). Participants were randomly assigned 1:1 to m-Health or usual care and observed for 6 months. All received free visits, laboratory tests, transportation fees, and strips and lancets. Intervention participants received the m-Health app and a mobile phone data stipend. RESULTS: A1c change was previously reported as statistically significant. Significantly more participants in intervention than control had improved medication adherence (39.0% vs. 12.8%; p = 0.03) and increased frequency of blood glucose (BG) self-testing (39.0% vs. 10.3%; p = 0.01) at 6 months from baseline. No other outcomes were significantly different. Among m-Health users, 75% of participants actively used the app at week 24. Participants entered 29,668 medications and 2,575 BG readings, sent 497 messages, and received 890 messages. Most participants (80%) were satisfied with all aspects of the app and all seven providers rated the software very acceptable. DISCUSSION: Participants assigned to m-Health had increased medication adherence and frequency of BG testing compared with usual care participants. CONCLUSIONS: This tool could be an effective way to expand access to quality chronic disease care and improve outcomes.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Researchers evaluated a range of measures that aligned with their target chronic condition, such as blood glucose, weight, symptoms, patient-reported outcomes, diary entries, and steps.
“Researchers evaluated a range of measures that aligned with their target chronic condition, such as blood glucose [56,60,61,64,73], weight [56,73,74], symptoms [66,68,69], patient-reported outcomes [38,46,52,65,71], diary entries [47,66], and steps [51].”
From A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review (2019) · cites this paper as [64]
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587 · see citing works
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.191 · Cited by 43,925 · see citing works
Stratton, I. M. (2000) · BMJ · doi:10.1136/bmj.321.7258.405 · Cited by 9,059 · see citing works
The summary of diabetes self-care activities measure: results from 7 studies and a revised scale.
Toobert, D. J., Hampson, S. E., & Glasgow, R. E. (2000) · Diabetes Care · doi:10.2337/diacare.23.7.943 · Cited by 2,561 · see citing works
The Health Belief Model and Sick Role Behavior
Becker, M. H. (1974) · Health Education Monographs · doi:10.1177/109019817400200407 · Cited by 2,327 · see citing works
Free, C., Phillips, G., Galli, L., Watson, L., Felix, L., Edwards, P., Patel, V., & Haines, A. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001362 · Cited by 1,766 · see citing works
Assessment of Diabetes-Related Distress
Polonsky, W. H., Anderson, B. J., Lohrer, P. A., Welch, G., Jacobson, A. M., Aponte, J. E., & Schwartz, C. E. (1995) · Diabetes Care · doi:10.2337/diacare.18.6.754 · Cited by 1,497 · see citing works
Peyrot, M., Barnett, A. H., Meneghini, L. F., & Schumm‐Draeger, P. ‐. (2012) · Diabetic Medicine · doi:10.1111/j.1464-5491.2012.03605.x · Cited by 655 · see citing works
Quinn, C. C., Shardell, M. D., Terrin, M. L., Barr, E. A., Ballew, S. H., & Gruber-Baldini, A. L. (2011) · Diabetes Care · doi:10.2337/dc11-0366 · Cited by 650 · see citing works
McGuire, B. E., Morrison, T. G., Hermanns, N., Skovlund, S. E., Eldrup, E., Gagliardino, J. J., Kokoszka, A., Matthews, D. R., Pibernik-Okanović, M., Rodríguez‐Saldaña, J., et al. (2009) · Diabetologia · doi:10.1007/s00125-009-1559-5 · Cited by 424 · 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
Prevalence of Dyslipidemia in Urban and Rural India: The ICMR–INDIAB Study
Joshi, S., Anjana, R. M., Deepa, M., Pradeepa, R., Bhansali, A., Dhandhania, V. K., Joshi, P. P., Ranjit Unnikrishnan, I., Nirmal, E., Subashini, R., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096808 · Cited by 403 · see citing works
Ramachandran, A., Snehalatha, C., Ram, J., Selvam, S., Simon, M., Nanditha, A., Shetty, A. S., Godsland, I. F., Chaturvedi, N., Majeed, A., et al. (2013) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(13)70067-6 · Cited by 330 · see citing works
Pal, K., Eastwood, S. V., Michie, S., Farmer, A. A., Barnard, M., Peacock, R., Wood, B., Edwards, P. J., & Murray, E. (2014) · Diabetes Care · doi:10.2337/dc13-1386 · Cited by 227 · see citing works
Mohr, D. C., Schueller, S. M., Riley, W. T., Brown, C. H., Cuijpers, P., Duan, N., Kwasny, M. J., Stiles-Shields, C., & Cheung, K. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4391 · Cited by 216 · see citing works
Telemedicine Application in the Care of Diabetes Patients: Systematic Review and Meta-Analysis
Marcolino, M. S., Maia, J. X., Alkmim, M. B. M., Boersma, E., & Ribeiro, A. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0079246 · Cited by 215 · see citing works
Sepah, S. C., Jiang, L., & Peters, A. L. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4052 · Cited by 206 · see citing works
Sepah, S. C., Jiang, L., & Peters, A. L. (2014) · The Diabetes Educator · doi:10.1177/0145721714531339 · Cited by 139 · see citing works
Worswick, J., Wayne, S. C., Bennett, R., Fiander, M., Mayhew, A., Weir, M. C., Sullivan, K. J., & Grimshaw, J. M. (2013) · Systematic Reviews · doi:10.1186/2046-4053-2-26 · Cited by 130 · see citing works
Shetty, A. S., Snehalatha, C., Nanditha, A., Raj, R. K. C., & Ramachandran, A. (2011) · PubMed · Cited by 128 · see citing works
Akhtar, S., Mohan, V., Shah, S., Joshi, S., Seshiah, V., Bk, S., Banerjee, S., Wangnoo, S., Kumar, A. M. V., Kalra, S., et al. (2014) · Indian Journal of Endocrinology and Metabolism · doi:10.4103/2230-8210.129715 · Cited by 127 · see citing works
Self-citationQuality of Diabetes Care in the Middle- and High-Income Group Populace
Nagpal, J., & Bhartia, A. (2006) · Diabetes Care · doi:10.2337/dc06-0783 · Cited by 108 · see citing works
The Empirical Evidence for the Telemedicine Intervention in Diabetes Management
Bashshur, R. L., Shannon, G. W., Smith, B. R., & Woodward, M. A. (2015) · Telemedicine and e-Health · doi:10.1089/tmj.2015.0029 · Cited by 102 · see citing works
Primary Care Providers’ Perceptions of Home Diabetes Telemedicine Care in the IDEATel Project
Tudiver, F. G., Wolff, L. T., Morin, P. C., Teresi, J. A., Palmas, W., Starren, J. B., Shea, S. A., & Weinstock, R. S. (2007) · The Journal of Rural Health · doi:10.1111/j.1748-0361.2006.00068.x · Cited by 44 · see citing works
Medication adherence program: Adherence challenges and interventions in type 2 diabetes
Odegard, P. S., Carpinito, G., & Christensen, D. B. (2013) · Journal of the American Pharmacists Association · doi:10.1331/japha.2013.12065 · Cited by 43 · see citing works
Jagannathan, R., Selvam, S., Snehalatha, C., Nanditha, A., Simon, M., Shetty, A. S., Godsland, I. F., Johnston, D. G., & Ramachandran, A. (2014) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2014.09.043 · Cited by 33 · see citing works
Kleinman, N. J., Shah, A., Shah, S., Phatak, S., & Viswanathan, V. (2016) · Diabetes Care · doi:10.2337/dc16-0869 · Cited by 21 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Scherrenberg, M., Wilhelm, M., Hansen, D., Völler, H., Cornelissen, V., Frederix, I., Kemps, H., & Dendale, P. (2021) · European Journal of Preventive Cardiology · doi:10.1177/2047487320939671 · Cited by 251 · see citing works
Liu, K., Xie, Z., & Or, C. K. (2020) · JMIR mHealth and uHealth · doi:10.2196/15779 · Cited by 181 · see citing works
Aminuddin, H. B., Jiao, N., Jiang, Y., Hong, J., & Wang, W. (2021) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2019.02.003 · Cited by 157 · see citing works
Moschonis, G., Siopis, G., Jung, J., Eweka, E., Willems, R., Kwasnicka, D., Asare, B. Y.-A., Kodithuwakku, V., Verhaeghe, N., Vedanthan, R., et al. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(22)00233-3 · Cited by 149 · 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
Pham, Q., Graham, G., Carrion, C., Morita, P. P., Seto, E., Stinson, J. N., & Cafazzo, J. A. (2019) · JMIR mHealth and uHealth · doi:10.2196/11941 · Cited by 131 · see citing works
Mao, Y., Lin, W., Wen, J., & Chen, G. (2020) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2020-001225 · Cited by 108 · see citing works
The Empirical Evidence for the Telemedicine Intervention in Diabetes Management
Bashshur, R. L., Shannon, G. W., Smith, B. R., & Woodward, M. A. (2015) · Telemedicine and e-Health · doi:10.1089/tmj.2015.0029 · Cited by 102 · see citing works
Stevens, S., Gallagher, S., Andrews, T., Ashall-Payne, L., Humphreys, L., & Leigh, S. (2022) · Frontiers in Clinical Diabetes and Healthcare · doi:10.3389/fcdhc.2022.936752 · Cited by 84 · see citing works
Efficacy of telemedicine on glycaemic control in patients with type 2 diabetes: A meta-analysis
De Groot, J., Wu, D., Flynn, D., Robertson, D., Grant, G., & Sun, J. (2021) · World Journal of Diabetes · doi:10.4239/wjd.v12.i2.170 · Cited by 77 · see citing works
Pecorelli, N., Fiore, J. F., Kaneva, P., Somasundram, A., Charlebois, P., Liberman, A. S., Stein, B. L., Carli, F., & Feldman, L. S. (2018) · Surgical Endoscopy · doi:10.1007/s00464-017-5920-3 · Cited by 68 · see citing works
Hossain, M. M., Tasnim, S., Sharma, R., Sultana, A., Shaik, A. F., Faizah, F., Kaur, R., Uppuluri, M., Sribhashyam, M., & Bhattacharya, S. (2019) · DIGITAL HEALTH · doi:10.1177/2055207619896153 · Cited by 57 · see citing works
Hangaard, S., Laursen, S. H., Andersen, J. D., Kronborg, T., Vestergaard, P., Hejlesen, O., & Udsen, F. W. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211064633 · Cited by 55 · see citing works
Enricho Nkhoma, D., Jenya Soko, C., Joseph Banda, K., Greenfield, D., Li, Y.-C. (., & Iqbal, U. (2021) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2020-100291 · Cited by 46 · see citing works
Shrivastava, T. P., Goswami, S., Gupta, R., & Goyal, R. K. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211060060 · Cited by 46 · see citing works
El-Gayar, O., Ofori, M., & Nawar, N. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103839 · Cited by 45 · see citing works
Jiang, Y., Ramachandran, H. J., Teo, J. Y. C., Leong, F. L., Lim, S. T., Nguyen, H. D., & Wang, W. (2022) · Journal of Advanced Nursing · doi:10.1111/jan.15178 · Cited by 40 · see citing works
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
Liu, K., & Xia, Y. (2025) · Digital Health · doi:10.1177/20552076251326126 · Cited by 7 · see citing works
Tang, T. S., Sidhu, R., Halani, K., Elliott, T., Sohal, P., & Garg, A. (2022) · Canadian Journal of Diabetes · doi:10.1016/j.jcjd.2021.11.003 · Cited by 7 · see citing works
- Authors
- Kleinman, N. J., Shah, A., Shah, S., Phatak, S., & Viswanathan, V.
- Affiliations
- Gather Health LLC, Hong Kong.
- Diabetes Action Centre, Mumbai, India.
- DHL Research Centre, Ahmedabad, India.
- Prof. M. Viswanathan Diabetes Research Centre, Chennai, India.
- Corresponding author
- Kleinman, Nora J.
- Venue
- Telemedicine and e-Health
- Publisher
- SAGE Publications
- Published
- 2017-09
- Volume
- 23
- Issue
- 9
- Pages
- 733-740
- ISSN
- 1530-5627 (ISSN-L)
- 1556-3669
- OpenAlex
- W2598477829
- Cited by
- 116
- References
- 27
- Citations by year
- 2026: 10 · 2025: 11 · 2024: 15 · 2023: 22 · 2022: 9 · 2021: 19 · 2020: 12 · 2019: 6 · 2018: 9 · 2017: 3
- FWCI
- 13.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Telemedicine Journal and e-Health (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Diabetes Action Research and Education Foundation
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- type 2 diabetes, mobile health, medication adherence, self-monitoring of blood glucose, glycemic control, HbA1c, telemedicine, diabetes self-management, patient satisfaction, app usage, chronic care, India
- MeSH terms
- Patient Reported Outcome Measures, Adolescent, Adult, Aged, Blood Glucose, Diabetes Mellitus, Type 2, Female, Glycated Hemoglobin, Humans, Hypoglycemic Agents, India, Male, Middle Aged, Self Care, Socioeconomic Factors, Drug Monitoring, Patient Satisfaction, Young Adult, 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
