Effectiveness of mobile app-assisted self-care interventions for improving patient outcomes in type 2 diabetes and/or hypertension: systematic review and meta-analysis of randomized controlled trials

Liu, Kaifeng; Xie, Zhenzhen; Or, Calvin Kalun

doi:10.2196/15779

Cited by 181Mobile Health and mHealth ApplicationsDiabetes Management and EducationDigital Mental Health Interventions

Effectiveness of mobile app-assisted self-care interventions for improving patient outcomes in type 2 diabetes and/or hypertension: systematic review and meta-analysis of randomized controlled trials

Open access

Liu, Kaifeng, Xie, Zhenzhen, Or, Calvin Kalun·2020·JMIR mHealth and uHealth

DOI 10.2196/15779PMC PMC7435643

Published version of a preprint

Open this paper in CoChat — free account Open PDF

Abstract

BACKGROUND: Mobile app-assisted self-care interventions are emerging promising tools to support self-care of patients with chronic diseases such as type 2 diabetes and hypertension. The effectiveness of such interventions requires further exploration for more supporting evidence. OBJECTIVE: A systematic review and meta-analysis of randomized controlled trials (RCTs) were conducted to examine the effectiveness of mobile app-assisted self-care interventions developed for type 2 diabetes and/or hypertension in improving patient outcomes. METHODS: ) levels, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Changes in other clinical-, behavioral-, knowledge-, and psychosocial-related outcomes were included as secondary outcomes. Primary outcomes and objective secondary outcomes that were reported in at least two trials were meta-analyzed; otherwise, a narrative synthesis was used for data analysis. RESULTS: levels (standardized mean difference [SMD] -0.44, 95% CI -0.59 to -0.29; P<.001), SBP (SMD -0.17, 95% CI -0.31 to -0.03, P=.02), and DBP (SMD -0.17, 95% CI -0.30 to -0.03, P=.02). Subgroup analyses for primary outcomes showed that several intervention features were supportive of self-management, including blood glucose, blood pressure, and medication monitoring, communication with health care providers, automated feedback, personalized goal setting, reminders, education materials, and data visualization. In addition, 8 objective secondary outcomes were meta-analyzed, which showed that the interventions had significant lowering effects on fasting blood glucose levels and waist circumference. A total of 42 secondary outcomes were narratively synthesized, and mixed results were found. CONCLUSIONS: Mobile app-assisted self-care interventions can be effective tools for managing blood glucose and blood pressure, likely because their use facilitates remote management of health issues and data, provision of personalized self-care recommendations, patient-care provider communication, and decision making. More studies are required to further determine which combinations of intervention features are most effective in improving the control of the diseases. Moreover, evidence regarding the effects of these interventions on the behavioral, knowledge, and psychosocial outcomes of patients is still scarce, which warrants further examination.

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.

Integrity signals

Registry

Crossref · 10.2196/15779

Cites

68 of 68 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.

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 effect size for HbA1c was similar to those reported in other systematic reviews (SMD range −0.31 to −0.44, MD range −0.40% to −0.49%).
“This effect size was similar to those reported in other systematic reviews (SMD range −0.31 to −0.44, MD range −0.40% to −0.49%).10,15,16,18”
From Effective behavioral change techniques in m-health app supported interventions for glycemic control among patients with type 2 diabetes: A meta-analysis and meta-regression analysis of randomized controlled trials (2025) · cites this paper as [10]
The Discussion (Principal Findings) says this review’s HbA1c effect (SMD −0.44; MD −0.49%) was similar to previous reviews, and gives those reviews’ MD range as −0.40% to −0.49%. It gives their SMD range as −0.30 to −0.40, not the claimed −0.31 to −0.44; −0.44 is this review’s own estimate. (LLM, conf=0.88)
Experimental — accuracy not yet measured
To utilize these types of BCTs, interventions usually included features such as self-monitoring of blood glucose, exercise, and diet; educational materials; and patient-healthcare provider communication.
“To utilize these types of BCTs, interventions usually included features such as self-monitoring of blood glucose, exercise, and diet; educational materials; and patient–healthcare provider communication.10,13,27”
From Effective behavioral change techniques in m-health app supported interventions for glycemic control among patients with type 2 diabetes: A meta-analysis and meta-regression analysis of randomized controlled trials (2025) · cites this paper as [10]
Table 4 in Results (page not supplied) lists blood-glucose, diet, and physical-activity logging, education materials, and communication with health care providers as intervention features. The Discussion says all reviewed interventions had more than one feature. Our copy does not establish that the listed features were usually included or explicitly link them to the cited sentence’s BCTs. (LLM, conf=0.82)
Experimental — accuracy not yet measured
The findings of this review can be applied to patients with hypertension with comorbidities, as confirmed by previous meta-analyses conducted among hypertensive patients with other chronic conditions.
“Nevertheless, the findings of this review can be applied to patients with hypertension with comorbidities, as confirmed by previous meta-analyses conducted among hypertensive patients with other chronic conditions.”
From Effectiveness of digital health interventions on blood pressure control, lifestyle behaviours and adherence to medication in patients with hypertension in low-income and middle-income countries: a systematic review and meta-analysis of randomised controlled trials (2024) · cites this paper as [41]
The Introduction says diabetes and hypertension frequently coexist, and the Results (Trial Characteristics) include a trial involving patients with both conditions. The Results (Subgroup Analysis for Primary Outcomes by Disease Type) report a systolic blood-pressure reduction among hypertensive patients, but do not establish that the findings apply to hypertensive patients with comorbidities generally. The Discussion (Principal Findings) compares its result with previous reviews of hypertensive patients without saying those reviews studied patients with other chronic conditions. (LLM, conf=0.82)
Experimental — accuracy not yet measured
We chose 2007 as the starting year because most m-health apps were released after 2007.
“We chose 2007 as the starting year because most m-health apps were released after 2007.10,27”
From Effective behavioral change techniques in m-health app supported interventions for glycemic control among patients with type 2 diabetes: A meta-analysis and meta-regression analysis of randomized controlled trials (2025) · cites this paper as [10]
Mobile app interventions significantly reduced HbA1c (SMD -0.44, 95% CI -0.59 to -0.29).
“Mobile app interventions significantly reduced HbA1c (SMD -0.44, 95% CI: -0.59 to -0.29)”
From Digital diabetes management technologies for type 2 diabetes: a systematic review of home-based care interventions (2025) · cites this paper as [13]

Self-check

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

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

Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139 · see citing works
Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722 · see citing works
GRADE: an emerging consensus on rating quality of evidence and strength of recommendations
Guyatt, G. H., Oxman, A. D., Vist, G. E., Kunz, R., Falck-Ytter, Y., Alonso-Coello, P., & Schünemann, H. J. (2008) · BMJ · doi:10.1136/bmj.39489.470347.ad · Cited by 23,305 · see citing works
Usability Engineering
(1993) · Elsevier eBooks · doi:10.1016/c2009-0-21512-1 · Cited by 5,533 · see citing works
2009 updated method guidelines for systematic reviews in the Cochrane Back Review Group
Furlan, A. D., Pennick, V., Bombardier, C., & van Tulder, M. (2009) · Spine · doi:10.1097/brs.0b013e3181b1c99f · Cited by 1,663 · see citing works
Health App Use Among US Mobile Phone Owners: A National Survey
Krebs, P., & Duncan, D. T. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4924 · Cited by 1,274 · see citing works
Hypertension and Antihypertensive Therapy as Risk Factors for Type 2 Diabetes Mellitus
Gress, T. W., Nieto, F. J., Shahar, E., Wofford, M. R., & Brancati, F. L. (2000) · New England Journal of Medicine · doi:10.1056/nejm200003303421301 · Cited by 1,202 · see citing works
A Systematic Review of Healthcare Applications for Smartphones
Mosa, A. S. M., Yoo, I., & Sheets, L. (2012) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-12-67 · Cited by 1,184 · see citing works
How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX
Boulos, M. N. K., Wheeler, S., Tavares, C., & Jones, R. B. (2011) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-10-24 · Cited by 1,071 · see citing works
The Smartphone in Medicine: A Review of Current and Potential Use Among Physicians and Students
Ozdalga, E., Ozdalga, A., & Ahuja, N. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.1994 · Cited by 654 · see citing works
Cluster-Randomized Trial of a Mobile Phone Personalized Behavioral Intervention for Blood Glucose Control
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
A Systematic Review of Patient Acceptance of Consumer Health Information Technology
Or, C. K. L., & Karsh, B.-T. (2009) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2888 · Cited by 586 · see citing works
Self-citation
Descriptions of Barriers to Self-Care by Persons with Comorbid Chronic Diseases
Bayliss, E. A. (2003) · The Annals of Family Medicine · doi:10.1370/afm.4 · Cited by 537 · see citing works
A Systematic Review of Reviews Evaluating Technology-Enabled Diabetes Self-Management Education and Support
Greenwood, D. A., Gee, P. M., Fatkin, K. J., & Peeples, M. (2017) · Journal of Diabetes Science and Technology · doi:10.1177/1932296817713506 · Cited by 526 · see citing works
Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis: Mobile phone intervention and glycaemic control
Liang, X., Wang, Q., Yang, X., Cao, J., Chen, J., Mo, X., Huang, J., Wang, L., & Gu, D. (2011) · Diabetic Medicine · doi:10.1111/j.1464-5491.2010.03180.x · Cited by 515 · see citing works
Patients’ perceived barriers to active self-management of chronic conditions
Jerant, A. F., von Friederichs-Fitzwater, M. M., & Moore, M. (2004) · Patient Education and Counseling · doi:10.1016/j.pec.2004.08.004 · Cited by 472 · see citing works
Do Mobile Phone Applications Improve Glycemic Control (HbA1c) in the Self-management of Diabetes? A Systematic Review, Meta-analysis, and GRADE of 14 Randomized Trials
Hou, C., Carter, B., Hewitt, J., Francisa, T., & Mayor, S. (2016) · Diabetes Care · doi:10.2337/dc16-0346 · Cited by 411 · see citing works
WellDoc <sup>™</sup> Mobile Diabetes Management Randomized Controlled Trial: Change in Clinical and Behavioral Outcomes and Patient and Physician Satisfaction
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
Mobile Applications for Diabetes Self-Management: Status and Potential
El-Gayar, O., Timsina, P., Nawar, N., & Eid, W. (2013) · Journal of Diabetes Science and Technology · doi:10.1177/193229681300700130 · Cited by 370 · see citing works
Clinical usefulness and cost effectiveness of home blood pressure telemonitoring: meta-analysis of randomized controlled studies
Omboni, S., Gazzola, T., Carabelli, G., & Parati, G. (2013) · Journal of Hypertension · doi:10.1097/hjh.0b013e32835ca8dd · Cited by 313 · see citing works
A Mobile Health Intervention for Self-Management and Lifestyle Change for Persons With Type 2 Diabetes, Part 2: One-Year Results From the Norwegian Randomized Controlled Trial RENEWING HEALTH
Holmen, H., Torbjørnsen, A., Wahl, A. K., Jenum, A. K., Småstuen, M. C., Årsand, E., & Ribu, L. (2014) · JMIR mHealth and uHealth · doi:10.2196/mhealth.3882 · Cited by 294 · see citing works
Efficacy of mobile apps to support the care of patients with diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials
Bonoto, B. C., de Araújo, V. E., Godói, I. P., de Lemos, L. L. P., Godman, B., Bennie, M., Diniz, L. M., & Junior, A. A. G. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.6309 · Cited by 294 · see citing works
Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy
Wu, Y., Yao, X., Vespasiani, G., Nicolucci, A., Dong, Y., Kwong, J., Li, L., Sun, X., Tian, H., & Li, S. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.6522 · Cited by 283 · see citing works
T2DM Self-Management via Smartphone Applications: A Systematic Review and Meta-Analysis
Cui, M., Wu, X., Mao, J., Wang, X., & Nie, M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0166718 · Cited by 269 · 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
Valuable Features in Mobile Health Apps for Patients and Consumers: Content Analysis of Apps and User Ratings
Mendiola, M. F., Kalnicki, M., & Lindenauer, S. (2015) · JMIR mhealth and uhealth · doi:10.2196/mhealth.4283 · Cited by 214 · see citing works
Effect of Home Blood Pressure Telemonitoring With Self-Care Support on Uncontrolled Systolic Hypertension in Diabetics
Logan, A. G., Irvine, M. J., McIsaac, W. J., Tisler, A., Rossos, P. G., Easty, A., Feig, D. S., & Cafazzo, J. A. (2012) · Hypertension · doi:10.1161/hypertensionaha.111.188409 · Cited by 210 · see citing works
DialBetics: A Novel Smartphone-based Self-management Support System for Type 2 Diabetes Patients
Waki, K., Fujita, H., Uchimura, Y., Omae, K., Aramaki, E., Kato, S., Lee, H., Kobayashi, H., Kadowaki, T., & Ohe, K. (2014) · Journal of Diabetes Science and Technology · doi:10.1177/1932296814526495 · Cited by 203 · see citing works
Health Coaching Reduces HbA1c in Type 2 Diabetic Patients From a Lower-Socioeconomic Status Community: A Randomized Controlled Trial
Wayne, N., Perez, D. F., Kaplan, D. M., & Ritvo, P. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4871 · Cited by 192 · see citing works
The Influence of Wireless Self-Monitoring Program on the Relationship Between Patient Activation and Health Behaviors, Medication Adherence, and Blood Pressure Levels in Hypertensive Patients: A Substudy of a Randomized Controlled Trial
Kim, J. Y., Wineinger, N. E., & Steinhubl, S. R. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5429 · Cited by 180 · see citing works
Correction: Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy
Wu, Y., Yao, X., Vespasiani, G., Nicolucci, A., Dong, Y., Kwong, J. S. W., Li, L., Sun, X., Tian, H., & Li, S. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.8789 · Cited by 176 · see citing works
Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis
McLean, G., Band, R., Saunderson, K., Hanlon, P., Murray, E., Little, P., McManus, R. J., Yardley, L., & Mair, F. S. (2016) · Journal of Hypertension · doi:10.1097/hjh.0000000000000859 · Cited by 168 · see citing works
A Ubiquitous Chronic Disease Care system using cellular phones and the internet
Yoo, H. J., Park, M. S., Kim, T. N., Yang, S. J., Cho, G. J., Hwang, T. G., Baik, S. H., Choi, D. S., Park, G. H., & Choi, K. M. (2009) · Diabetic Medicine · doi:10.1111/j.1464-5491.2009.02732.x · Cited by 161 · see citing works
Mobile apps to support the self-management of hypertension: systematic review of effectiveness, usability, and user satisfaction
Alessa, T., Abdi, S., Hawley, M. S., & de Witte, L. (2018) · JMIR mhealth and uhealth · doi:10.2196/10723 · Cited by 160 · see citing works
Specific hypertension smartphone application to improve medication adherence in hypertension: a cluster-randomized trial
Contreras, E. M., Márquez‐Rivero, S., García, E. R., García-Ramos, L. L., Vilas, J. C. P., Suárez, A. B., Diez, C. G., Gil-Guillén, V. F., Claros, N. M., & Compliance Group of Spanish Society of Hypertension (SEH-LELHA) (2018) · Current Medical Research and Opinion · doi:10.1080/03007995.2018.1549026 · Cited by 140 · see citing works
Utilization of a Cloud-Based Diabetes Management Program for Insulin Initiation and Titration Enables Collaborative Decision Making Between Healthcare Providers and Patients
Hsu, W. C., Lau, K. H. K., Huang, R., Ghiloni, S., Le, H., Gilroy, S., Abrahamson, M., & Moore, J. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0160 · Cited by 135 · see citing works
Telemonitoring and Mobile Phone-Based Health Coaching Among Finnish Diabetic and Heart Disease Patients: Randomized Controlled Trial
Karhula, T., Vuorinen, A.-L., Rääpysjärvi, K., Pakanen, M., Itkonen, P., Tepponen, M., Junno, U.-M., Jokinen, T., van Gils, M., Lähteenmäki, J., et al. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4059 · Cited by 131 · see citing works
Overcoming clinical inertia: a randomized clinical trial of a telehealth remote monitoring intervention using paired glucose testing in adults with type 2 diabetes
Greenwood, D. A., Blozis, S. A., Young, H. M., Nesbitt, T. S., & Quinn, C. C. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4112 · Cited by 128 · see citing works
Mobile Phone–Based Telemedicine Practice in Older Chinese Patients with Type 2 Diabetes Mellitus: Randomized Controlled Trial
Sun, C., Sun, L., Xi, S., Zhang, H., Wang, H., Feng, Y., Deng, Y., Wang, H., Xiao, X., Wang, G., et al. (2019) · JMIR mHealth and uHealth · doi:10.2196/10664 · Cited by 124 · see citing works
Active Assistance Technology Reduces Glycosylated Hemoglobin and Weight in Individuals With Type 2 Diabetes: Results of a Theory-Based Randomized Trial
Orsama, A.-L., Lähteenmäki, J., Harno, K., Kulju, M., Wintergerst, E., Schachner, H., Stenger, P., Leppänen, J., Kaijanranta, H., Salaspuro, V., et al. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0056 · Cited by 117 · see citing works
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
Kleinman, N. J., Shah, A., Shah, S., Phatak, S., & Viswanathan, V. (2017) · Telemedicine and e-Health · doi:10.1089/tmj.2016.0265 · Cited by 116 · see citing works
Phone-based intervention for blood pressure control among Ghanaian stroke survivors: A pilot randomized controlled trial
Sarfo, F. S., Treiber, F. A., Gebregziabher, M., Adamu, S., Nichols, M. G., Singh, A., Obese, V., Sarfo‐Kantanka, O., Sakyi, A., Adu‐Darko, N., et al. (2018) · International Journal of Stroke · doi:10.1177/1747493018816423 · Cited by 116 · see citing works
Reducing Blood Pressure With Internet-Based Interventions: A Meta-analysis
Liu, S., Dunford, S. D., Leung, Y. W., Brooks, D., Thomas, S. G., Eysenbach, G., & Nolan, R. P. (2013) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2013.02.007 · Cited by 113 · see citing works
Mobile phone health apps for diabetes management: Current evidence and future developments
Goyal, S., & Cafazzo, J. A. (2013) · QJM · doi:10.1093/qjmed/hct203 · Cited by 107 · see citing works
Usability Study of a Computer-Based Self-Management System for Older Adults with Chronic Diseases
Or, C. K., & Tao, D. (2012) · JMIR Research Protocols · doi:10.2196/resprot.2184 · Cited by 100 · see citing works
Self-citation
Prevalence, Demographic Correlates, and Perceived Impacts of Mobile Health App Use Amongst Chinese Adults: Cross-Sectional Survey Study
Xie, Z., Nacioglu, A., & Or, C. K. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9002 · Cited by 79 · see citing works
Self-citation
Does the use of consumer health information technology improve outcomes in the patient self-management of diabetes? A meta-analysis and narrative review of randomized controlled trials
Or, C. K. L., & Tao, D. (2014) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2014.01.009 · Cited by 76 · see citing works
Self-citation
A 3-Month Randomized Controlled Pilot Trial of a Patient-Centered, Computer-Based Self-Monitoring System for the Care of Type 2 Diabetes Mellitus and Hypertension
Or, C. K., & Tao, D. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0437-1 · Cited by 75 · see citing works
Self-citation
A Feasible and Efficacious Mobile-Phone Based Lifestyle Intervention for Filipino Americans with Type 2 Diabetes: Randomized Controlled Trial
Bender, M. S., Cooper, B. A., Park, L. G., Padash, S., & Arai, S. R. (2017) · JMIR Diabetes · doi:10.2196/diabetes.8156 · Cited by 70 · see citing works
Dulce Wireless Tijuana: A Randomized Control Trial Evaluating the Impact of Project Dulce and Short-Term Mobile Technology on Glycemic Control in a Family Medicine Clinic in Northern Mexico
Anzaldo-Campos, M. C., Contreras, S. C., Vargas-Ojeda, A. C., Menchaca-Díaz, R., Fortmann, A. L., & Philis‐Tsimikas, A. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0283 · Cited by 68 · see citing works
Human factors and ergonomics in home care: Current concerns and future considerations for health information technology
Or, C. K., Valdez, R. S., Casper, G. R., Carayon, P., Burke, L. J., Brennan, P. F., & Karsh, B. (2009) · Work · doi:10.3233/wor-2009-0867 · Cited by 64 · see citing works
Self-citation
Association Between Raised Blood Pressure and Dysglycemia in Hong Kong Chinese
Cheung, B. M. Y., Wat, N. M. S., Tso, A. W. K., Tam, S., Thomas, G. N., Leung, G. M., Tse, H., Woo, J., Janus, E. D., Lau, C., et al. (2008) · Diabetes Care · doi:10.2337/dc08-0405 · Cited by 62 · see citing works
Mobile Diabetes Intervention for Glycemic Control in 45- to 64-Year-Old Persons With Type 2 Diabetes
Quinn, C. C., Shardell, M. D., Terrin, M. L., Barr, E. A., Park, D., Shaikh, F., Guralnik, J. M., & Gruber‐Baldini, A. L. (2014) · Journal of Applied Gerontology · doi:10.1177/0733464814542611 · Cited by 61 · see citing works
A 12-week pilot study of acceptance of a computer-based chronic disease self-monitoring system among patients with type 2 diabetes mellitus and/or hypertension
Yan, M., & Or, C. K. (2017) · Health Informatics Journal · doi:10.1177/1460458217724580 · Cited by 60 · see citing works
Self-citation
Video consultations as add-on to standard care among patients with type 2 diabetes not responding to standard regimens: a randomized controlled trial
Hansen, C. R., Perrild, H., Koefoed, B. G., & Zander, M. (2017) · European Journal of Endocrinology · doi:10.1530/eje-16-0811 · Cited by 53 · see citing works
A mHealth-based care model for improving hypertension control in stroke survivors: Pilot RCT
Lakshminarayan, K., Westberg, S. M., Northuis, C. A., Fuller, C. C., Ikramuddin, F. S., Ezzeddine, M. A., Scherber, J., & Speedie, S. M. (2018) · Contemporary Clinical Trials · doi:10.1016/j.cct.2018.05.005 · Cited by 51 · see citing works
Telehealth—An Effective Delivery Method for Diabetes Self-Management Education?
Fitzner, K., & Moss, G. (2013) · Population Health Management · doi:10.1089/pop.2012.0054 · Cited by 45 · see citing works
Stepwise Self-Titration of Oral Glucose-Lowering Medication Using a Mobile Telephone-Based Telehealth Platform in Type 2 Diabetes: A Feasibility Trial in Primary Care
Nagrebetsky, A., Larsen, M. E., Craven, A., Turner, J., McRobert, N., Murray, E., Gibson, O., Neil, A., Tarassenko, L., & Farmer, A. A. (2013) · Journal of Diabetes Science and Technology · doi:10.1177/193229681300700115 · Cited by 43 · see citing works
Usability Testing of a Smartphone Application for Delivering Qigong Training
Cheung, D. S. T., Or, C. K. L., So, M. K. P., & Tiwari, A. (2018) · Journal of Medical Systems · doi:10.1007/s10916-018-1048-9 · Cited by 40 · see citing works
Self-citation
Factors in the 4-week Acceptance of a Computer-Based, Chronic Disease Self-Monitoring System in Patients with Type 2 Diabetes Mellitus and/or Hypertension
Yan, M., & Or, C. K. (2017) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2017.0064 · Cited by 39 · see citing works
Self-citation
An ICT-Based Diabetes Management System Tested for Health Care Delivery in the African Context
Takenga, C., Berndt, R.-D., Musongya, O., Kitero, J., Katoke, R., Molo, K., Kazingufu, B., Meni, M., Vikandy, M., & Takenga, H. (2014) · International Journal of Telemedicine and Applications · doi:10.1155/2014/437307 · Cited by 38 · see citing works
Effects of consumer-oriented health information technologies in diabetes management over time: a systematic review and meta-analysis of randomized controlled trials
Tao, D., Wang, T., Wang, T., Liu, S., & Qu, X. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx014 · Cited by 31 · see citing works
Heuristic evaluation and simulated use testing of infusion pumps to inform pump selection
Liu, K., Chan, F.-Y., Or, C. K., Sun, D. T., Lai, W.-S., & So, H. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.07.011 · Cited by 27 · see citing works
Self-citation
The Use of eHealth Applications in Hong Kong: Results of a Random-Digit Dialing Survey
Cheung, D. S. T., Or, C. K., So, M. K. P., Ho, K., & Tiwari, A. (2019) · Journal of Medical Systems · doi:10.1007/s10916-019-1422-2 · Cited by 27 · see citing works
Self-citation
The Impact of a Mobile Diabetes Health Intervention on Diabetes Distress and Depression Among Adults: Secondary Analysis of a Cluster Randomized Controlled Trial
Quinn, C. C., Swasey, K. K., Crabbe, J. C. F., Shardell, M. D., Terrin, M. L., Barr, E. A., & Gruber‐Baldini, A. L. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.8910 · Cited by 25 · see citing works
Designing a technology enhanced practice for home nursing care of patients with congestive heart failure.
Casper, G. R., Karsh, B., Or, C. K., Carayon, P., Grenier, A.-S., & Brennan, P. F. (2005) · PubMed Central · Cited by 20 · see citing works
Self-citation
The Influence of Computer Experience and Screen Size on Use Performance and Perceptions of a Tablet-Based Chronic Illness Self-Management System for Older Adults
Tao, D., Or, C. K. L., & Li, K. (2014) · Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care · doi:10.1177/2327857914031008 · Cited by 8 · see citing works
Self-citation
Effects of Consumer-Facing Technologies on Patient Engagement, Behavior Change, and Type 2 Diabetes–Related Health Outcomes
Dyer, J. S. (2013) · Diabetes Spectrum · doi:10.2337/diaspect.26.2.98 · Cited by 4 · see citing works

Flagged first, then by citations

1 of the 69 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

[20]Higgins JPT Green S Cochrane Handbook for Systematic Reviews of Interventions, Version 5.1.0 2011 Hoboken John Wiley & Sons
[66]Shneiderman B Plaisant C Designing the User Interfaces: Strategies for Effective Human-Computer Interaction 2010 New York Pearson Education

Sorted by citations

Problems and Barriers Related to the Use of Digital Health Applications: Scoping Review
Giebel, G. D., Speckemeier, C., Abels, C., Plescher, F., Börchers, K., Wasem, J., Blase, N., & Neusser, S. (2023) · Journal of Medical Internet Research · doi:10.2196/43808 · Cited by 238 · see citing works
An examination of the socio-demographic correlates of patient adherence to self-management behaviors and the mediating roles of health attitudes and self-efficacy among patients with coexisting type 2 diabetes and hypertension
Xie, Z., Liu, K., Or, C., Chen, J., Yan, M., & Wang, H. (2020) · BMC Public Health · doi:10.1186/s12889-020-09274-4 · Cited by 184 · see citing works
Self-citation
Effective Behavior Change Techniques in Digital Health Interventions for the Prevention or Management of Noncommunicable Diseases: An Umbrella Review
Mair, J. L., Salamanca-Sanabria, A., Augsburger, M., Frese, B. F., Abend, S., Jakob, R., Kowatsch, T., & Haug, S. (2023) · Annals of Behavioral Medicine · doi:10.1093/abm/kaad041 · Cited by 157 · see citing works
The role of adherence in patients with chronic diseases
Burnier, M. (2023) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2023.07.008 · Cited by 146 · see citing works
Effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain: A systematic review and meta-analysis of randomized controlled trials
Chen, T., Or, C. K., & Chen, J. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa282 · Cited by 98 · see citing works
Self-citation
mHealth Interventions for Self-management of Hypertension: Framework and Systematic Review on Engagement, Interactivity, and Tailoring
Cao, W., Milks, M., Liu, X.-F., Gregory, M. E., Addison, D., Zhang, P., & Li, L. (2022) · JMIR mHealth and uHealth · doi:10.2196/29415 · Cited by 93 · see citing works
Effectiveness of digital health interventions on blood pressure control, lifestyle behaviours and adherence to medication in patients with hypertension in low-income and middle-income countries: a systematic review and meta-analysis of randomised controlled trials
Boima, V., Doku, A., Agyekum, F., Tuglo, L. S., & Agyemang, C. (2024) · EClinicalMedicine · doi:10.1016/j.eclinm.2024.102432 · Cited by 82 · see citing works
The role of trust and habit in the adoption of mHealth by older adults in Hong Kong: a healthcare technology service acceptance (HTSA) model
Liu, J. Y. W., Sorwar, G., Rahman, M. S., & Hoque, M. R. (2023) · BMC Geriatrics · doi:10.1186/s12877-023-03779-4 · Cited by 78 · see citing works
A longitudinal examination of tablet self-management technology acceptance by patients with chronic diseases: Integrating perceived hand function, perceived visual function, and perceived home space adequacy with the TAM and TPB
Liu, K., Or, C. K., So, M. K. P., Cheung, B. M. Y., Chan, B. K. P., Tiwari, A., & Tan, J. (2021) · Applied Ergonomics · doi:10.1016/j.apergo.2021.103667 · Cited by 62 · see citing works
Self-citation
Mobile phone interventions to improve health outcomes among patients with chronic diseases: an umbrella review and evidence synthesis from 34 meta-analyses
Sun, S., Simonsson, O., McGarvey, S. T., Torous, J. B., & Goldberg, S. B. (2024) · The Lancet Digital Health · doi:10.1016/s2589-7500(24)00119-5 · Cited by 57 · see citing works
A “No-Code” App Design Platform for Mobile Health Research: Development and Usability Study
Liu, S., La, H., Willms, A., & Rhodes, R. E. (2022) · JMIR Formative Research · doi:10.2196/38737 · Cited by 55 · see citing works
Assessment of Hypertension Control Among Adults Participating in a Mobile Technology Blood Pressure Self-management Program
Gazit, T., Gutman, M., & Beatty, A. L. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.27008 · Cited by 57 · see citing works
Impact of DSMES app interventions on medication adherence in type 2 diabetes mellitus: systematic review and meta-analysis
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
Human Factors Engineering and User-Centered Design for Mobile Health Technology: Enhancing Effectiveness, Efficiency, and Satisfaction
Or, C. K., Holden, R. J., & Valdez, R. S. (2022) · Automation, collaboration, and e-services · doi:10.1007/978-3-031-10788-7_6 · Cited by 48 · see citing works
Self-citation
Acceptance of mHealth by Elderly Adults: A Path Analysis
Xie, Z., & Or, C. K. (2020) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181320641174 · Cited by 46 · see citing works
Self-citation
On the efficacy of behavior change techniques in mHealth for self-management of diabetes: A meta-analysis
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
An umbrella review of effectiveness and efficacy trials for app-based health interventions
Chong, S. O. K., Pedron, S., Abdelmalak, N., Laxy, M., & Stephan, A. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00981-x · Cited by 45 · see citing works
Digital health applications and the fast-track pathway to public health coverage in Germany: challenges and opportunities based on first results
Lantzsch, H., Eckhardt, H., Campione, A., Busse, R., & Henschke, C. (2022) · BMC Health Services Research · doi:10.1186/s12913-022-08500-6 · Cited by 44 · see citing works
Use of Mobile Apps for Self-care in People With Parkinson Disease: Systematic Review
Lee, J., Yeom, I., Chung, M. L., Kim, Y., Yoo, S., & Kim, E.-Y. (2021) · JMIR mhealth and uhealth · doi:10.2196/33944 · Cited by 41 · see citing works
Lifestyle Intervention With Smartphone App and isCGM for People at High Risk of Type 2 Diabetes: Randomized Trial
Kitazawa, M., Takeda, Y., Hatta, M., Horikawa, C., Sato, T., OSAWA, T., Ishizawa, M., Suzuki, H., Matsubayashi, Y., Fujihara, K., et al. (2023) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgad639 · Cited by 40 · see citing works
Efficacy of a WeChat-Based Multimodal Digital Transformation Management Model in New-Onset Mild to Moderate Hypertension: Randomized Clinical Trial
Wang, Y., Guo, F., Wang, J., Li, Z., Tan, W., Xie, M., Yang, X., Duan, S., Song, L., Cheng, S., et al. (2023) · Journal of Medical Internet Research · doi:10.2196/52464 · Cited by 44 · see citing works
Heart Failure-Smart Life: a randomized controlled trial of a mobile app for self-management in patients with heart failure
Choi, E., Park, J., Min, D., Ahn, S., & Ahn, J. (2023) · BMC Cardiovascular Disorders · doi:10.1186/s12872-023-03039-8 · Cited by 41 · see citing works
Leveraging digital technology for social connectedness among adults with chronic conditions: A systematic review
Wright, P. J., Raynor, P. A., Bowers, D., Combs, E. M., Corbett, C. F., Hardy, H., & Patel, K. (2023) · DIGITAL HEALTH · doi:10.1177/20552076231204746 · Cited by 39 · see citing works
The Effect of Mobile eHealth Education to Improve Knowledge, Skills, Self-Care, and Mobile eHealth Literacies Among Patients With Diabetes: Development and Evaluation Study
Guo, S. H.-M., Lin, J., Hsing, H.-C., Lee, C., & Chuang, S. (2023) · Journal of Medical Internet Research · doi:10.2196/42497 · Cited by 37 · see citing works
The Quality of Health Apps and Their Potential to Promote Behavior Change in Patients With a Chronic Condition or Multimorbidity: Systematic Search in App Store and Google Play
Bricca, A., Pellegrini, A., Zangger, G., Ahler, J. R., Jäger, M., & Skou, S. T. (2021) · JMIR mhealth and uhealth · doi:10.2196/33168 · Cited by 35 · see citing works
Behavior Change Techniques Used in Self-Management Interventions Based on mHealth Apps for Adults With Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials
Zhou, Y., Li, S., Huang, R.-Q., Ma, H.-M., Wang, A., Tang, X., Pei, R.-Y., & Piao, M.-H. (2024) · Journal of Medical Internet Research · doi:10.2196/54978 · Cited by 34 · see citing works
Development and evaluation of DiabeText, a personalized mHealth intervention to support medication adherence and lifestyle change behaviour in patients with type 2 diabetes in Spain: A mixed-methods phase II pragmatic randomized controlled clinical trial
Zamanillo‐Campos, R., Fiol-deRoque, M. A., Serrano-Ripoll, M. J., Mira-Martínez, S., & Ricci‐Cabello, I. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105103 · Cited by 31 · see citing works
Psychometric Testing of the Self-care of Hypertension Inventory Version 3.0
Dickson, V. V., Fletcher, J., & Riegel, B. J. (2021) · The Journal of Cardiovascular Nursing · doi:10.1097/jcn.0000000000000827 · Cited by 32 · see citing works
Effect of an Integrative Mobile Health Intervention in Patients With Hypertension and Diabetes: Crossover Study
Oh, S. W., Kim, K. K., Kim, S. S., Park, S.-K., & Park, S. (2021) · JMIR mhealth and uhealth · doi:10.2196/27192 · Cited by 32 · see citing works
A New Taxonomy for Technology-Enabled Diabetes Self-Management Interventions: Results of an Umbrella Review
Greenwood, D. A., Litchman, M. L., Isaacs, D., Blanchette, J. E., Dickinson, J. K., Hughes, A., Colicchio, V. D., Ye, J., Yehl, K., Todd, A., et al. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211036430 · Cited by 31 · see citing works
mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis
Ryan, S., Chasaide, N. N., Hanrahan, S. O., Corcoran, D., Caulfield, B., & Argent, R. (2022) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/34355 · Cited by 32 · see citing works
Effect of a Multicomponent Intervention Delivered on a Web-Based Platform on Hypertension Control: A Cluster Randomized Clinical Trial
Zhou, H., Wang, X., Yang, Y., Chen, Z., Zhang, L., Zheng, C., Shao, L., Tian, Y., Cao, X., Hu, Z., et al. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.45439 · Cited by 30 · see citing works
Development of a behavior change intervention to improve physical activity adherence in individuals with metabolic syndrome using the behavior change wheel
Chen, D., Zhang, H., Cui, N., Song, F., Tang, L., Shao, J., Wu, J., Guo, P., Liu, N., Wang, X., et al. (2022) · BMC Public Health · doi:10.1186/s12889-022-14129-1 · Cited by 29 · see citing works
Effects of mobile apps intervention on medication adherence and type 2 diabetes mellitus control: A systematic review and meta-analysis
Chong, C. J., Makmor‐Bakry, M., Hatah, E., Tahir, N. A. M., & Mustafa, N. (2023) · Journal of Telemedicine and Telecare · doi:10.1177/1357633x231174933 · Cited by 29 · see citing works
Review and Analysis of German Mobile Apps for Inflammatory Bowel Disease Management Using the Mobile Application Rating Scale: Systematic Search in App Stores and Content Analysis
Gerner, M., Vuillerme, N., Aubourg, T., Meßner, E.-M., Terhorst, Y., Hörmann, V., Ganzleben, I., Schenker, H., Schett, G. A., Atreya, R. N., et al. (2022) · JMIR mhealth and uhealth · doi:10.2196/31102 · Cited by 28 · see citing works
Effectiveness of mobile application interventions for stroke survivors: systematic review and meta-analysis
Cao, W., Kadir, A. A., Tang, W., Wang, J., Yuan, J., & Hassan, I. I. (2024) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02391-1 · Cited by 32 · see citing works
Hypertension and mobile application for self-care, self-efficacy and related knowledge
Dwairej, L. A., & Ahmad, M. M. (2022) · Health Education Research · doi:10.1093/her/cyac012 · Cited by 27 · see citing works
Personal Goals, Barriers to Self-Management and Desired mHealth Application Features to Improve Self-Care in Multi-Ethnic Asian Patients with Type 2 Diabetes: A Qualitative Study
Yoon, S., Kwan, Y. H., Phang, J. K., Tan, W. B., & Low, L. L. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192215415 · Cited by 26 · see citing works
Estimating the impact of engagement with digital health interventions on patient outcomes in randomized trials
Nelson, L. A., Spieker, A. J., Mayberry, L. S., McNaughton, C., & Greevy, R. A. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab254 · Cited by 23 · see citing works
Digital Health Technology in Diabetes Management in the Asia–Pacific Region: A Narrative Review of the Current Scenario and Future Outlook
Gardner, D. S.-L., Saboo, B., Kesavadev, J., Mustafa, N., Villa, M. L., Mahoney, E., & Bajpai, S. (2025) · Diabetes Therapy · doi:10.1007/s13300-025-01692-0 · Cited by 24 · see citing works
Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis
Xie, Z., Chen, J., & Or, C. K. (2022) · Journal of Medical Internet Research · doi:10.2196/25959 · Cited by 20 · see citing works
Self-citation
User Engagement and Weight Loss Facilitated by a Mobile App: Retrospective Review of Medical Records
Valinskas, S., Nakrys, M., Aleknavičius, K., Jonusas, J., & Lileikienė, A. (2023) · JMIR Formative Research · doi:10.2196/42266 · Cited by 20 · see citing works
The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials
Tanhapour, M., Peimani, M., Kalhori, S. R. N., Nasli‐Esfahani, E., Shakibian, H., Mohammadzadeh, N., & Qorbani, M. (2023) · Acta Diabetologica · doi:10.1007/s00592-023-02133-9 · Cited by 18 · see citing works
Consumers’ Preferences for Purchasing mHealth Apps: Discrete Choice Experiment
Xie, Z., & Or, C. K. (2023) · JMIR mhealth and uhealth · doi:10.2196/25908 · Cited by 17 · see citing works
Self-citation
Design and development of a smartphone app for hypertension management: An intervention mapping approach
Lobo, E. H., Karmakar, C. K., Abdelrazek, M., Abawajy, J., Chow, C. K., Zhang, Y., Kabir, M. A., Daryabeygi‐Khotbehsara, R., Maddison, R., & Islam, S. M. S. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1092755 · Cited by 21 · see citing works
Assessing the technical feasibility of a flexible, integrated Internet-of-things connected for asthma (C4A) system to support self-management: a mixed method study exploring patients and healthcare professionals perspectives
Hui, C. Y., McKinstry, B., McLean, S., Buchner, M., & Pinnock, H. (2022) · JAMIA Open · doi:10.1093/jamiaopen/ooac110 · Cited by 16 · see citing works
Review and content analysis of mobile apps for inflammatory bowel disease management using the mobile application rating scale (MARS): Systematic search in app stores
Jannati, N., Salehinejad, S., Kuenzig, M. E., & Peña-Sánchez, J. N. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105249 · Cited by 13 · see citing works
Experience Sampling and Programmed Intervention Method and System for Planning, Authoring, and Deploying Mobile Health Interventions: Design and Case Reports
Cunha, B. C. R., Rodrigues, K. R. D. H., Zaine, I., da Silva, E. A. N., Viel, C. C., & Pimentel, M. D. G. C. (2021) · Journal of Medical Internet Research · doi:10.2196/24278 · Cited by 15 · see citing works
Evaluating Effectiveness of mHealth Apps for Older Adults With Diabetes: Meta-Analysis of Randomized Controlled Trials
Azevedo, R. F. L., Varzino, M., Steinman, E., & Rogers, W. A. (2025) · Journal of Medical Internet Research · doi:10.2196/65855 · Cited by 17 · see citing works
Contextualizing Visualizations of Digital Health Information among Young and Older Adults Based on Eye-Tracking
Liu, K., Su, P., Wang, H., & Tao, D. (2022) · Sustainability · doi:10.3390/su142416506 · Cited by 14 · see citing works
Self-citation
Effectiveness of mHealth Interventions to Improve Pain Intensity and Functional Disability in Individuals With Hip or Knee Osteoarthritis: A Systematic Review and Meta-analysis
Mapinduzi, J., Ndacayisaba, G., Verbrugghe, J., Timmermans, A. A. A., Kossi, O., & Bonnechère, B. (2024) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2024.06.008 · Cited by 14 · see citing works
Identification of challenges and leveraging mHealth technology, with need-based solutions to empower self-management in type 2 diabetes: a qualitative study
Dsouza, S. M., Venne, J., Shetty, S., & Brand, H. (2024) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-024-01414-9 · Cited by 14 · see citing works
Benchmarking the clinical outcomes of Healthentia SaMD in chronic disease management: a systematic literature review comparison
Kyriazakos, S. A., Pnevmatikakis, A., Kostopoulou, K., Ferrière, L., Thibaut, K., Giacobini, E., Pastorino, R., Gorini, M., & Fenici, P. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1488687 · Cited by 14 · see citing works
Experience of using a smartphone WeChat applet for dental anxiety assessment and preoperative evaluation: A nationwide multicenter study
Huang, X., Zeng, J., Zhao, N., Fan, L., Ruan, D.-J., Wang, J., Hong, X., & Yu, C. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.900899 · Cited by 13 · see citing works
Effectiveness of educational interventions on hypertensive patients’ self-management behaviours: an umbrella review protocol
Ukoha-Kalu, B. O., Isah, A., Biambo, A. A., Samaila, A., Abubakar, M. M., Kalu, U. A., & Soyiri, I. N. (2023) · BMJ Open · doi:10.1136/bmjopen-2023-073682 · Cited by 22 · see citing works
The Effect of Mobile Application Follow‐Up on Treatment Compliance and Self‐Care Management in Patients With Hypertension: Randomized Controlled Trial
Keskin, A. Y., Şolpan, N. Ö., & Değirmenci, H. (2024) · Public Health Nursing · doi:10.1111/phn.13476 · Cited by 12 · see citing works
Klinio mobile app for diabetes self-care: A pilot study of HbA1c improvement in type 2 diabetes patients
Jonusas, J., Aleknavičius, K., & Valinskas, S. (2023) · Smart Health · doi:10.1016/j.smhl.2023.100404 · Cited by 12 · see citing works
The Practicality of Mobile Applications in Healthcare Administration and COVID-19 Pandemic
Zamri, N., & Mohideen, F. B. S. (2021) · Ulum Islamiyyah · doi:10.33102/uij.vol33no1.300 · Cited by 12 · see citing works
A systematic review of user-based usability testing practices in self-care mHealth apps
Sharma, S., & Kumar, B. A. (2025) · Digital Health · doi:10.1177/20552076251374184 · Cited by 15 · see citing works
Psychosocial Determinants of Recommended Lifestyle Behaviors among Hypertensive Patients: An Integrative Literature Review
Suriyawong, W., Kao, T. A., Robbins, L. B., Ling, J., & Malete, L. (2022) · Western Journal of Nursing Research · doi:10.1177/01939459221144177 · Cited by 11 · see citing works
Comparing the effects of self- care education by lecture and smartphone application on self-efficacy of patients with thalassemia
Kharaman-nia, F., Rezaei, H., Roustaei, N., Etemadfar, P., & Hosseini, N. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02097-4 · Cited by 11 · see citing works
Remote monitoring for long-term physical health conditions: an evidence and gap map
de Bell, S., Zhelev, Z., Shaw, N., Bethel, A. C., Anderson, R., & Coon, J. T. (2023) · Health and Social Care Delivery Research · doi:10.3310/bvcf6192 · Cited by 12 · see citing works
Effects of anthropomorphic design on comprehension of self-monitoring test results: Integrating evidence of eye-tracking and event-related potential
Su, P., & Liu, K. (2024) · Displays · doi:10.1016/j.displa.2024.102664 · Cited by 11 · see citing works
Self-citation
Harnessing an Artificial Intelligence–Based Large Language Model With Personal Health Record Capability for Personalized Information Support in Postsurgery Myocardial Infarction: Descriptive Qualitative Study
Yang, T.-T., Zheng, H.-X., Cao, S., Jing, M.-L., Ju, H., Zuo, Y., Chen, Q., & Zhang, J.-J. (2025) · Journal of Medical Internet Research · doi:10.2196/68762 · Cited by 12 · see citing works
A systematic literature review for understanding the effectiveness of advanced techniques in diabetes self-care management
Alsayed, A. O., Ismail, N. A., Hasan, L., Syed, A. H., Embarak, F. M., & Da’u, A. (2023) · Alexandria Engineering Journal · doi:10.1016/j.aej.2023.08.026 · Cited by 16 · see citing works
Evaluating a WeChat-Based Health Behavioral Digital Intervention for Patients With Hypertension: Protocol for a Randomized Controlled Trial
Sun, T., Zhao, H., Ding, Z., Xie, H., Ma, L., Zhang, Y., Wang, Y., Yang, Y., Xu, C., Sun, Y., et al. (2023) · JMIR Research Protocols · doi:10.2196/46883 · Cited by 11 · see citing works
The effects of multifactorial pharmacist-led intervention protocol on medication optimisation and adherence among patients with type 2 diabetes: A randomised control trial
El-Deyarbi, M., Ahmed, L. A., King, J., Abubackar, S., Juboori, A. A., Mansour, N. A., & Aburuz, S. (2024) · F1000Research · doi:10.12688/f1000research.146517.1 · Cited by 9 · see citing works
How do self-motivation and social motivation contribute to consumers’ acceptance of m-health services?
Tao, D., & Liu, K. (2024) · Health Policy and Technology · doi:10.1016/j.hlpt.2024.100878 · Cited by 9 · see citing works
Self-citation
Assessing intention to use mobile phone–based self-management support among adults with type 2 diabetes in Saudi Arabia: A cross-sectional study
Alosaimi, H., Alshammari, M. K., Al-Otaibi, M., Alhejaili, S., Alshammari, B., Khalaf, A., Hajea, A., Saleh, R., Aldhafiri, F. J., AbuShahin, A., et al. (2025) · Digital Health · doi:10.1177/20552076241308993 · Cited by 10 · see citing works
Reviewing the User-Centered Design Process for a Comprehensive Gastroesophageal Reflux Disease (GERD) App
Kim, M. J., Schroeder, S., Chan, S., Hickerson, K., & Lee, Y. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19031128 · Cited by 11 · see citing works
Untitled work
(2023) · doi:10.1007/978-3-031-48306-6_10 · Cited by 9 · see citing works
Perceptions of pharmacists and other healthcare professionals on marketed mobile applications used for self-management by type 2 diabetic patients: A systematic review
Vukmirović, D., Krajnović, D., & Odalović, M. (2023) · Tropical Journal of Pharmaceutical Research · doi:10.4314/tjpr.v22i4.27 · Cited by 8 · see citing works
A Comprehensive Review of Modern Methods to Improve Diabetes Self-Care Management Systems
Alsayed, A. O., Ismail, N. A., Hasan, L., & Embarak, F. M. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0140920 · Cited by 9 · see citing works
Towards optimizing exercise prescription for type 2 diabetes: modulating exercise parameters to strategically improve glucose control
Marcotte‐Chénard, A., & Little, J. P. (2024) · Translational Exercise Biomedicine · doi:10.1515/teb-2024-2007 · Cited by 9 · see citing works
Effective behavioral change techniques in m-health app supported interventions for glycemic control among patients with type 2 diabetes: A meta-analysis and meta-regression analysis of randomized controlled trials
Liu, K., & Xia, Y. (2025) · Digital Health · doi:10.1177/20552076251326126 · Cited by 7 · see citing works
“10,15,16,18 It was also considered clinically meaningful because a decrease in HbA1c by 0.3% was associated with a lower risk of diabetic complications.”
InfluentialSelf-citation
Effects of information framing cues and age on the comprehension of personal health records for self-care behaviors: an eye-tracking study
Liu, K., Sun, Z., Ren, X., & Tao, D. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaf085 · Cited by 7 · see citing works
Self-citation
Effect of mobile structured educational applications on self-care management in diabetes mellitus patients
Karingga, D. D., & Efendi, F. (2023) · Gaceta Médica de Caracas · doi:10.47307/gmc.2023.131.2.3 · Cited by 7 · see citing works
Facilitators of and barriers to the use of a computer-based self-monitoring system by type 2 diabetic and/or hypertensive patients
Yan, M., Or, C. K., Xie, Z., & Liu, H. (2023) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2023.103509 · Cited by 7 · see citing works
Self-citation
Empowering patients with comorbid diabetes and hypertension through a multi-component intervention of mobile app, health coaching and shared decision-making: Protocol for an effectiveness-implementation of randomised controlled trial
Kwan, Y. H., Yoon, S., Tai, B. C., Tan, C. S., Phang, J. K., Tan, W. B., Tan, N. C., Tan, C. Y. L., Koot, D., Quah, Y. L., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296338 · Cited by 8 · see citing works
Primary Technology Enhanced Care Home HbA1c Testing (PTEC HAT) programme: a feasibility pilot study in Singapore
Tyagi, S., Koh, G. C., Lee, E. S., Ong, K. P., Heng, R., Er, L. H., Oh, E., Teo, V. H. Y., & Ng, D. W. L. (2024) · BMC Family Practice · doi:10.1186/s12875-024-02373-w · Cited by 7 · see citing works
Automated Personalized Self-care Program for Patients With Type 2 Diabetes Mellitus: A Pilot Trial
Park, G., Lee, H., Lee, Y., Kim, M. S., Jung, S., Khang, A. R., & Yi, D. (2024) · Asian Nursing Research · doi:10.1016/j.anr.2024.04.003 · Cited by 8 · see citing works
Willingness to pay for health apps, its sociodemographic correlates, and reasons for being unwilling to pay
Liu, H., Xie, Z., & Or, C. K. (2024) · Digital Health · doi:10.1177/20552076241248925 · Cited by 7 · see citing works
Self-citation
A prospective observational study evaluating the use of remote patient monitoring in ED discharged COVID-19 patients in NYC
Oh, S. M., Nair, S., Casler, A., Nguyen, D., Forero, J. P., Joco, C., Kubert, J., Esses, D., Adams, D. B., Jariwala, S. P., et al. (2022) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2022.02.035 · Cited by 7 · see citing works
E-MunDiabetes
Negreiros, F. D. D. S., Flor, A. C., de Araújo, A. L., Cestari, V. R. F., Florêncio, R. S., Moreira, T. R., Araújo, S. T., da Silva, L. M. S., & Moreira, T. M. M. (2022) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000000881 · Cited by 7 · see citing works
KetoCycle mobile app for ketogenic diet: a retrospective study of weight loss and engagement
Valinskas, S., Aleknavičius, K., & Jonusas, J. (2022) · BMC Nutrition · doi:10.1186/s40795-022-00539-2 · Cited by 7 · see citing works
Effect of a structured educational intervention delivered through a mobile application on glycated haemoglobin and self-efficacy in adolescents with type 1 diabetes mellitus: a systematic review and meta-analysis
Rubab, H., Aziz, F., Gul, R. B., & Froelicher, E. S. (2025) · BMJ Open · doi:10.1136/bmjopen-2024-093798 · Cited by 6 · see citing works
Design, development and evaluation of a mobile-based self-care application for patients with COVID-19 not requiring hospitalization; a study of Northwest of Iran
Heydari, M., Mehraeen, E., Javaherikiyan, E., Mehrabi, N., Langarizadeh, M., Aghamohammadi, V., Moghaddam, H. R., & Nasiri, K. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02381-3 · Cited by 6 · see citing works
Effects of emotional design and age on learning performance of self-care instructions for diabetes: Evidence from eye-tracking and heart rate variability
Liu, K., Li, J., Pengbo, S., & Tao, D. (2024) · Displays · doi:10.1016/j.displa.2024.102947 · Cited by 6 · see citing works
Self-citation
The effects of presentation format and presentation dynamics on the comprehension of personal health information among young and middle-older aged adults
Tao, D., Wu, Y., Liu, K., & Qin, M. (2025) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2025.103727 · Cited by 6 · see citing works
Self-citation
Effective behavior change techniques in digital health interventions targeting non-communicable diseases: an umbrella reviewPreprint
Mair, J. L., Salamanca-Sanabria, A., Frese, B. F., Jakob, R., Kowatsch, T., & Haug, S. (2023) · doi:10.31219/osf.io/n4sav · Cited by 6 · see citing works
Achieving Blood Pressure Goals and Addressing Inequities in Blood Pressure Management After Stroke
Bushnell, C. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.123.031307 · Cited by 6 · see citing works
Recommendations for Designing a Digital Health Tool for Blindness Prevention Among High-Risk Diabetic Retinopathy Patients: Qualitative Focus Group Study of Adults With Diabetes
Frimpong, A. A., Granados, A., Chang, T., Fu, J. J., Moore, S. G., Applebaum, S. S., Adepoju, B., Kaur, M., Krishnan, V. H., Levi, A., et al. (2025) · JMIR Formative Research · doi:10.2196/65893 · Cited by 4 · see citing works
Determinants of continuous use intention of smart healthcare services: Evidence from a commitment-trust theory perspective
Liu, K., Li, Q., & Tao, D. (2025) · Health Informatics Journal · doi:10.1177/14604582251381156 · Cited by 7 · see citing works
Self-citation
Between regulatory functions and emotional burden: balancing engagement in digital health interventions for self-care in chronic illness
Lemmo, D., Bianco, R., Mezza, F., Luca, V. D., Illario, M., Iaccarino, G., & Freda, M. F. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1685934 · Cited by 5 · see citing works
Control of cardiovascular risk factors with tailored recommendations: A randomized controlled trial
Barroso, M., Zomeño, M. D., Díaz, J. L., Pérez-Fernández, S., Martí‐Lluch, R., Cordón, F., Ramos, R., Cabezas, C., Salvador, G., Castell, C., et al. (2020) · Preventive Medicine · doi:10.1016/j.ypmed.2020.106302 · Cited by 5 · see citing works
A Smartphone-Based Application to Assist Insulin Titration in Patients Undergoing Basal Insulin-Supported Oral Antidiabetic Treatment
Tews, D., Gouveri, E., Simon, J., & Marck, C. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221090521 · Cited by 5 · see citing works
Hypertension doctors’ awareness and practice of medication adherence in hypertensive patients: a questionnaire-based survey
Liu, T., Zhao, X., Huang, M., Yang, Y. X., Chen, Z., He, X., Li, X., & Jiang, W. (2023) · PeerJ · doi:10.7717/peerj.16384 · Cited by 5 · see citing works
Heuristic smartphone usability evaluations of the mobile application NANDA, nursing interventions classification, and nursing outcomes classification customized for nursing home registered nurses
Shin, J. H., & Jung, S. O. (2022) · International Journal of Nursing Knowledge · doi:10.1111/2047-3095.12403 · Cited by 5 · see citing works
Advancing Virtual at-Home Care for Community Health Center Patients Using Patient Self-Care Tools, Technology, and Education
Modica, C., Lewis, J. H., & Bay, R. C. (2024) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s443973 · Cited by 5 · see citing works
Digital diabetes management technologies for type 2 diabetes: a systematic review of home-based care interventions
Abdul Latif el Ejel, B., Sattar, S., Fatima, S. B., Khan, H. N., Ali, H., Iftikhar, A., Sarwer, M. A., & Mushtaq, M. (2025) · Cureus · doi:10.7759/cureus.84177 · Cited by 4 · see citing works

T2DM Self-Management via Smartphone Applications: A Systematic Review and Meta-Analysis
Cui, M., Wu, X., Mao, J., Wang, X., & Nie, M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0166718 · Cited by 269 · see citing works
Prognostic effectiveness of interactive vs. non-interactive mobile app interventions in type 2 diabetes: a systematic review and meta-analysis
Tang, Z., Zhao, L., Li, J., Yang, Y., Liu, F., Li, H., Yang, Z., Qin, S., & Li, X. (2024) · Archives of Public Health · doi:10.1186/s13690-024-01450-x · Cited by 10 · see citing works
Effectiveness of Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review
Amalindah, D., Winarto, A., & Rahmi, A. H. (2020) · DOAJ (DOAJ: Directory of Open Access Journals) · doi:10.20473/jn.v15i2.18897
PDB64 Use of Mobile Health Intervention for the Self-Management in Patients with Diabetes Mellitus: A Systematic Literature Review and Meta-Analysis of Randomized Controlled Trials
Adil, M., Fischer, T. A., Schmalhofer, C., & Bonduelle, D. (2020) · Value in Health · doi:10.1016/j.jval.2020.08.661
Effectiveness of smartphone-based self-management interventions on self-efficacy, self-care activities, health-related quality of life and clinical outcomes in patients with type 2 diabetes: A systematic review and meta-analysis
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

Authors: Liu, K., Xie, Z., & Or, C. K.
Affiliations: University of Hong Kong (HK)
Corresponding author: Or, Calvin Kalun
ORCID: Liu, Kaifeng
Xie, Zhenzhen
Or, Calvin Kalun
Venue: JMIR mHealth and uHealth
Publisher: JMIR Publications Inc.
Published: 2020-08-04
Volume: 8
Issue: 8
Pages: e15779
ISSN: 2291-5222 (ISSN-L)
DOI: 10.2196/15779
PMC: PMC7435643
OpenAlex: W3021141263
Cited by: 181
References: 69
Citations by year: 2026: 20 · 2025: 29 · 2024: 39 · 2023: 40 · 2022: 34 · 2021: 14 · 2020: 4
FWCI: 4.40
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
Locations: JMIR mhealth and uhealth (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: University of Hong Kong
Topics: Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Keywords: mobile health apps, self-care interventions, type 2 diabetes, hypertension, glycemic control, blood pressure control, chronic disease self-management, medication adherence, automated feedback, personalized goal setting, remote patient monitoring, patient-provider communication, waist circumference
MeSH terms: Diabetes Mellitus, Type 2, Humans, Hypertension, Self Care, Randomized Controlled Trials as Topic, 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

Effectiveness of mobile app-assisted self-care interventions for improving patient outcomes in type 2 diabetes and/or hypertension: systematic review and meta-analysis of randomized controlled trials

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Self-check

Cites

Cited by

Related

Record

About these checks