Cited by 816Mobile Health and mHealth ApplicationsMobile Learning in EducationSocial Media in Health Education

The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

Mobile Text Messaging for Health: A Systematic Review of Reviews

Open access

Hall, Amanda K., Cole-Lewis, Heather, Bernhardt, Jay M.·2015·Annual Review of Public Health

DOI 10.1146/annurev-publhealth-031914-122855PMC PMC4406229

Open this paper in CoChat — free account

Abstract

The aim of this systematic review of reviews is to identify mobile text-messaging interventions designed for health improvement and behavior change and to derive recommendations for practice. We have compiled and reviewed existing systematic research reviews and meta-analyses to organize and summarize the text-messaging intervention evidence base, identify best-practice recommendations based on findings from multiple reviews, and explore implications for future research. Our review found that the majority of published text-messaging interventions were effective when addressing diabetes self-management, weight loss, physical activity, smoking cessation, and medication adherence for antiretroviral therapy. However, we found limited evidence across the population of studies and reviews to inform recommended intervention characteristics. Although strong evidence supports the value of integrating text-messaging interventions into public health practice, additional research is needed to establish longer-term intervention effects, identify recommended intervention characteristics, and explore issues of cost-effectiveness.

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 · 10.1146/annurev-publhealth-031914-122855

Cites

46 of 46 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?

Self-check

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

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

Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000097 · Cited by 64,042
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000100 · Cited by 28,164
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.06.005 · Cited by 19,575
The Effect of Riding as an Alternative Treatment for Children with Cerebral Palsy: A Systematic Review and Meta-Analysis
Wang, G., Ma, R., Qiao, G., Wada, K., Aizawa, Y., & Satoh, T. (2015) · Integrative Medicine International · doi:10.1159/000368408 · Cited by 18,762
The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-4-200908180-00136 · Cited by 10,349
Untitled work
(2000) · Cited by 9,198
Adherence to Long-Term Therapies: Evidence for Action
Geest, S. D., & Sabate, E. J. (2003) · European Journal of Cardiovascular Nursing · doi:10.1016/s1474-5151(03)00091-4 · Cited by 6,310

Show all 46 references

Research works printed but not linked: 10

AHRQ (Agency Healthc. Res. Qual.), 2014, Methods Guide for Effectiveness and Comparative Effectiveness Reviews.
de Jongh T, 2012, Cochrane Database Syst. Rev., 12, 12
Garrard J, 2010, Health Sciences Literature Review Made Easy
Horvath T, 2012, Cochrane Database Syst. Rev., 3, CD009756
Int. Telecommun. Union, 1985, Telecommun. J., 52, 67
Int. Telecommun. Union, 2014, The World in 2014: ICT Facts and Figures.
Mukund Bahadur K-C, 2010, Stud. Health Technol. Inform., 160, 530
Shaw R, 2014, Diabetes Technol. Ther., 16, S59
Vodopivec-Jamsek V, 2012, Cochrane Database Syst. Rev., 12, CD007457
Whittaker R, 2012, Cochrane Database Syst. Rev., 11, CD006611

Sorted by citations

American Association of Clinical Endocrinologists and American College of Endocrinology Comprehensive Clinical Practice Guidelines For Medical Care of Patients with Obesity
Garvey, W. T., Mechanick, J. I., Brett, E. M., Garber, A. J., Hurley, D. L., Jastreboff, A. M., Nadolsky, K., Pessah-Pollack, R., & Plodkowski, R. (2016) · Endocrine Practice · doi:10.4158/ep161365.gl · Cited by 1,914
The Heavy Burden of Obesity
OECD (2019) · OECD health policy studies · doi:10.1787/67450d67-en · Cited by 1,227
Conversational Agents in Health Care: Scoping Review and Conceptual Analysis
Tudor Car, L., Dhinagaran, D. A., Kyaw, B. M., Kowatsch, T., Joty, S., Theng, Y.-L., & Atun, R. (2020) · Journal of Medical Internet Research · doi:10.2196/17158 · Cited by 553
“A series of systematic reviews on the use of text messaging for different health disorders have shown that text messaging is an effective and acceptable health care intervention [28,29].”
Background
What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions.
Iribarren, S. J., Cato, K., Falzon, L., & Stone, P. W. (2017) · PLOS ONE · doi:10.1371/journal.pone.0170581 · Cited by 519
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
Effectiveness of mHealth interventions for patients with diabetes: An overview of systematic reviews
Kitsiou, S., Paré, G., Jaana, M., & Gerber, B. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0173160 · Cited by 415
Fundamentals for Future Mobile-Health (mHealth): A Systematic Review of Mobile Phone and Web-Based Text Messaging in Mental Health.
Berrouiguet, S., Baca-García, E., Brandt, S., Walter, M., & Courtet, P. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5066 · Cited by 332
The use of e-health and m-health tools in health promotion and primary prevention among older adults: a systematic literature review.
Kampmeijer, R., Pavlova, M., Tambor, M., Golinowska, S., & Groot, W. (2016) · BMC Health Services Research · doi:10.1186/s12913-016-1522-3 · Cited by 328
2017 national standards for diabetes self-management education and support
Beck, J., Greenwood, D. A., Blanton, L., Bollinger, S. T., Butcher, M. K., Condon, J. E., Cypress, M., Faulkner, P., Fischl, A. H., Francis, T., et al. (2017) · Diabetes Care · doi:10.2337/dci17-0025 · Cited by 348
Prescribable mHealth apps identified from an overview of systematic reviews
Byambasuren, O., Sanders, S., Beller, E., & Glasziou, P. (2018) · npj Digital Medicine · doi:10.1038/s41746-018-0021-9 · Cited by 291
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
2017 National Standards for Diabetes Self-Management Education and Support
Beck, J. K., Greenwood, D. A., Blanton, L., Bollinger, S. T., Butcher, M. K., Condon, J. E., Cypress, M., Faulkner, P., Fischl, A. H., Francis, T., et al. (2018) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721718754797 · Cited by 301
Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials
Goldberg, S. B., Lam, S. U., Simonsson, O., Torous, J., & Sun, S. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000002 · Cited by 237
“, text message-based interventions) have been studied even longer [8].”
Background
Implementation strategies for health systems in low-income countries: an overview of systematic reviews
Tomás Pantoja, C., Opiyo, N., Lewin, S. A., Paulsen, E., Ciapponi, A., Wiysonge, C. S., Herrera, C. A., Gabriel Rada, G., Peñaloza, B., Dudley, L., et al. (2017) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd011086.pub2 · Cited by 272
The effectiveness of e-& mHealth interventions to promote physical activity and healthy diets in developing countries: A systematic review
Müller, A. M., Alley, S., Schoeppe, S., & Vandelanotte, C. (2016) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-016-0434-2 · Cited by 213
A systematic review of smartphone applications for smoking cessation
Haskins, B. L., Lesperance, D., Gibbons, P. W., & Boudreaux, E. D. (2017) · Translational Behavioral Medicine · doi:10.1007/s13142-017-0492-2 · Cited by 229
Co-design of mHealth Delivered Interventions: A Systematic Review to Assess Key Methods and Processes
Eyles, H. C., Jull, A., Dobson, R., Firestone, R. T., Whittaker, R., Morenga, L. T., Goodwin, D., & Mhurchú, C. N. (2016) · Current Nutrition Reports · doi:10.1007/s13668-016-0165-7 · Cited by 222
The Digital Divide and Health Disparities in China: Evidence From a National Survey and Policy Implications
Hong, Y. A., Zhou, Z., Fang, Y., & Shi, L. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7786 · Cited by 217
Using feedback through digital technology to disrupt and change habitual behavior: A critical review of current literature
Hermsen, S., Frost, J., Renes, R. J., & Kerkhof, P. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.12.023 · Cited by 194
2017 National Standards for Diabetes Self-Management Education and Support
Beck, J. K., Greenwood, D. A., Blanton, L., Bollinger, S. T., Butcher, M. K., Condon, J. E., Cypress, M., Faulkner, P., Fischl, A. H., Francis, T., et al. (2017) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721717722968 · Cited by 208
The Impact of Automated Brief Messages Promoting Lifestyle Changes Delivered Via Mobile Devices to People with Type 2 Diabetes: A Systematic Literature Review and Meta-Analysis of Controlled Trials
Arambepola, C., Ricci‐Cabello, I., Manikavasagam, P., Roberts, N. W., French, D., & Farmer, A. A. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5425 · Cited by 197
An overview of GeoAI applications in health and healthcare
Boulos, M. N. K., Peng, G., & VoPham, T. (2019) · International Journal of Health Geographics · doi:10.1186/s12942-019-0171-2 · Cited by 209
Meet us on the phone: mobile phone programs for adolescent sexual and reproductive health in low-to-middle income countries
Ippoliti, N. B., & L’Engle, K. (2017) · Reproductive Health · doi:10.1186/s12978-016-0276-z · Cited by 163
Smart cup: A minimally-instrumented, smartphone-based point-of-care molecular diagnostic device
Liao, S.-C., Peng, J., Mauk, M. G., Awasthi, S., Song, J., Friedman, H. M., Bau, H. H., & Liu, C. (2016) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2016.01.073 · Cited by 176
Telemedicine as the New Outpatient Clinic Gone Digital: Position Paper From the Pandemic Health System REsilience PROGRAM (REPROGRAM) International Consortium (Part 2)
Bhaskar, S. M. M., Bradley, S., Chattu, V. K., Adisesh, A., Nurtazina, A., Kyrykbayeva, S., Sakhamuri, S. M., Moguilner, S., Pandya, S., Schroeder, S., et al. (2020) · Frontiers in Public Health · doi:10.3389/fpubh.2020.00410 · Cited by 188
The effectiveness of mobile-health behaviour change interventions for cardiovascular disease self-management: A systematic review
Dale, L. P., Dobson, R., Whittaker, R., & Maddison, R. (2015) · European Journal of Preventive Cardiology · doi:10.1177/2047487315613462 · Cited by 180
Effects of a Self-directed Web-Based Strengthening Exercise and Physical Activity Program Supported by Automated Text Messages for People With Knee Osteoarthritis
Nelligan, R. K., Hinman, R. S., Kasza, J., Crofts, S., & Bennell, K. L. (2021) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2021.0991 · Cited by 174
Older adults and mobile technology: Factors that enhance and inhibit utilization in the context of behavioral health
Kuerbis, A., Mulliken, A., Muench, F. J., Moore, A. A., & Gardner, D. S. (2017) · Mental Health and Addiction Research · doi:10.15761/mhar.1000136 · Cited by 174
Exploring the Role of In-Person Components for Online Health Behavior Change Interventions: Can a Digital Person-to-Person Component Suffice?
Santarossa, S., Kane, D., Senn, C. Y., & Woodruff, S. J. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8480 · Cited by 172
Awareness and Use of mHealth Apps: A Study from England
Kayyali, R., Peletidi, A., Ismail, M. F., Hashim, Z., Bandeira, P., & Bonnah, J. (2017) · Pharmacy · doi:10.3390/pharmacy5020033 · Cited by 158
Dulce Digital: An mHealth SMS-Based Intervention Improves Glycemic Control in Hispanics With Type 2 Diabetes
Fortmann, A. L., Gallo, L. C., Garcia, M. I., Taleb, M., Euyoque, J. A., Clark, T., Skidmore, J., Ruiz, M., Dharkar-Surber, S., Schultz, J., et al. (2017) · Diabetes Care · doi:10.2337/dc17-0230 · Cited by 169
Patient reminder and recall interventions to improve immunization rates
Jacobson Vann, J. C., Jacobson, R. M., Coyne-Beasley, T., Asafu-Adjei, J. K., & Szilagyi, P. G. (2018) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd003941.pub3 · Cited by 396
Unpacking mHealth interventions: A systematic review of behavior change techniques used in randomized controlled trials assessing mHealth effectiveness
DUGAS, M. A., Gao, G. G., & Agarwal, R. (2020) · Digital Health · doi:10.1177/2055207620905411 · Cited by 159
Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine
Kuwabara, A. M., Su, S., & Krauss, J. (2019) · American Journal of Lifestyle Medicine · doi:10.1177/1559827619892547 · Cited by 169
The connecting health and technology study: a 6-month randomized controlled trial to improve nutrition behaviours using a mobile food record and text messaging support in young adults
Kerr, D. A., Harray, A. J., Pollard, C. M., Dhaliwal, S. S., Delp, E. J., Howat, P. A., Pickering, M. R., Ahmad, Z., Meng, X., Pratt, I., et al. (2016) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-016-0376-8 · Cited by 147
Advantages and limitations of virtual online consultations in a NHS acute trust: the VOCAL mixed-methods study
Shaw, S. E., Wherton, J. P., Vijayaraghavan, S., Morris, J. H., Bhattacharya, S., Hanson, P., Campbell-Richards, D., Ramoutar, S., Collard, A., Hodkinson, I., et al. (2018) · Health Services and Delivery Research · doi:10.3310/hsdr06210 · Cited by 147
Randomised controlled trial of a text messaging intervention for reducing processed meat consumption: The mediating roles of anticipated regret and intention
Carfora, V., Caso, D., & Conner, M. T. (2017) · Appetite · doi:10.1016/j.appet.2017.06.025 · Cited by 151
More Than a Text Message: Dismantling Digital Triggers to Curate Behavior Change in Patient-Centered Health Interventions
Muench, F. J., & Baumel, A. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7463 · Cited by 148
Mobile health technology: a novel tool in chronic disease management
Fan, K., & Zhao, Y. (2021) · Intelligent Medicine · doi:10.1016/j.imed.2021.06.003 · Cited by 150
Tailored mobile text messaging interventions targeting type 2 diabetes self-management: A systematic review and a meta-analysis
Sahin, C., Courtney, K. L., Naylor, P., & E Rhodes, R. (2019) · DIGITAL HEALTH · doi:10.1177/2055207619845279 · Cited by 133
A systematic review of musculoskeletal complaints, symptoms, and pathologies related to mobile phone usage
Zirek, E., Mustafaoğlu, R., Yasacı, Z., & Griffiths, M. D. (2020) · Musculoskeletal Science and Practice · doi:10.1016/j.msksp.2020.102196 · Cited by 132
Text Message Interventions for Physical Activity: A Systematic Review and Meta-Analysis
Smith, D. M. Y., Duque, L., Huffman, J. C., Healy, B. C., & Celano, C. M. (2019) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2019.08.014 · Cited by 139
Text Messaging for Exercise Promotion in Older Adults From an Upper-Middle-Income Country: Randomized Controlled Trial
Müller, A. M., Khoo, S., & Morris, T. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5235 · Cited by 135
The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association
Maddox, T. M., Albert, N. M., Borden, W. B., Curtis, L. H., Ferguson, T. B., Kao, D. P., Marcus, G. M., Peterson, E. D., Redberg, R. F., Rumsfeld, J. S., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000480 · Cited by 126
The App Behavior Change Scale: Creation of a Scale to Assess the Potential of Apps to Promote Behavior Change
McKay, F. H., Slykerman, S., & Dunn, M. (2018) · JMIR mhealth and uhealth · doi:10.2196/11130 · Cited by 117
Bridging the digital health divide: a narrative review of the causes, implications, and solutions for digital health inequalities
Western, M. J., Smit, E. S., Gültzow, T., Neter, E., Sniehotta, F. F., Malkowski, O. S., Wright, C., Busse, H., Peuters, C., Rehackova, L., et al. (2025) · Health Psychology and Behavioral Medicine · doi:10.1080/21642850.2025.2493139 · Cited by 116
Cross-sectional survey evaluating Text4Mood: mobile health program to reduce psychological treatment gap in mental healthcare in Alberta through daily supportive text messages
Agyapong, V. I. O., Mrklas, K., Juhás, M., Omeje, J., Öhinmaa, A., Dursun, S. M., & Greenshaw, A. J. (2016) · BMC Psychiatry · doi:10.1186/s12888-016-1104-2 · Cited by 119
A text message away: ICTs as a tool to improve food security
Nakasone, E., & Torero, M. A. (2016) · Agricultural Economics · doi:10.1111/agec.12314 · Cited by 115
The Comparative Effectiveness of Mobile Phone Interventions in Improving Health Outcomes: Meta-Analytic Review
Yang, Q., & Van Stee, S. K. (2019) · JMIR mHealth and uHealth · doi:10.2196/11244 · Cited by 113
Randomized controlled trial of a messaging intervention to increase fruit and vegetable intake in adolescents: Affective versus instrumental messages.
Carfora, V., Caso, D., & Conner, M. (2016) · British Journal of Health Psychology · doi:10.1111/bjhp.12208 · Cited by 111
Old-fashioned technology in the era of “bling”: is there a future for text messaging in health care?
Willcox, J. C., Dobson, R., & Whittaker, R. (2019) · Journal of Medical Internet Research · doi:10.2196/16630 · Cited by 95
Correlational study and randomised controlled trial for understanding and changing red meat consumption: The role of eating identities
Carfora, V., Caso, D., & Conner, M. T. (2017) · Social Science & Medicine · doi:10.1016/j.socscimed.2017.01.005 · Cited by 114
Economic Evaluation of Text-Messaging and Smartphone-Based Interventions to Improve Medication Adherence in Adolescents with Chronic Health Conditions: A Systematic Review
Badawy, S. M., & Kuhns, L. M. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.6425 · Cited by 104
The association of health literacy with adherence in older adults, and its role in interventions: a systematic meta-review
Geboers, B., Brainard, J. S., Loke, Y. K., Jansen, C., Salter, C., Reijneveld, S. A., & de Winter, A. F. (2015) · BMC Public Health · doi:10.1186/s12889-015-2251-y · Cited by 112
Randomized controlled pilot trial of supportive text messages for patients with depression
Agyapong, V. I. O., Juhás, M., Ohinmaa, A. E., Omeje, J., Mrklas, K., Suen, V. Y. M., Dursun, S. M., & Greenshaw, A. J. (2017) · BMC Psychiatry · doi:10.1186/s12888-017-1448-2 · Cited by 102
Effectiveness of a text-messaging-based smoking cessation intervention (“Happy Quit”) for smoking cessation in China: A randomized controlled trial
Liao, Y., Wu, Q., Kelly, B. C., Zhang, F., Tang, Y., Wang, Q., Ren, H., Hao, Y., Yang, M., Cohen, J. E., et al. (2018) · PLoS Medicine · doi:10.1371/journal.pmed.1002713 · Cited by 100
Effectiveness of short message services and voice call interventions for antiretroviral therapy adherence and other outcomes: A systematic review and meta-analysis
Amankwaa, I., Boateng, D., Quansah, D. Y., Akuoko, C. P., & Evans, C. (2018) · PLOS ONE · doi:10.1371/journal.pone.0204091 · Cited by 98
Features, outcomes, and challenges in mobile health interventions for patients living with chronic diseases: A review of systematic reviews
Triantafyllidis, A. K., Kondylakis, H., Votis, K., Tzovaras, D. K., Maglaveras, N., & Rahimi, K. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.103984 · Cited by 104
Clients’ perceptions and experiences of targeted digital communication accessible via mobile devices for reproductive, maternal, newborn, child, and adolescent health: a qualitative evidence synthesis
Ames, H. M., Glenton, C., Lewin, S. A., Tamrat, T., Akama, E., & Leon, N. (2019) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd013447 · Cited by 103
Behavior Change Text Messages for Home Exercise Adherence in Knee Osteoarthritis: Randomized Trial
Bennell, K. L., Nelligan, R. K., Schwartz, S., Kasza, J., Kimp, A. J., Crofts, S., & Hinman, R. S. (2020) · Journal of Medical Internet Research · doi:10.2196/21749 · Cited by 103
Visualizing Collaboration Characteristics and Topic Burst on International Mobile Health Research: Bibliometric Analysis
Shen, L., Xiong, B., Li, W., Lan, F., Evans, R. D., & Zhang, W. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9581 · Cited by 99
A salt-reduction smartphone app supports lower-salt food purchases for people with cardiovascular disease: Findings from the SaltSwitch randomised controlled trial
Eyles, H. C., McLean, R., Neal, B. C., Jiang, Y., Doughty, R. N., McLean, R. M., & Mhurchú, C. N. (2017) · European Journal of Preventive Cardiology · doi:10.1177/2047487317715713 · Cited by 91
Effect of Mobile Phone Text Message Reminders on Routine Immunization Uptake in Pakistan: Randomized Controlled Trial
Kazi, A. M., Ali, M. T., Zubair, K., Kalimuddin, H., Kazi, A. N., Iqbal, S. P., Collet, J., & Ali, A. (2018) · JMIR Public Health and Surveillance · doi:10.2196/publichealth.7026 · Cited by 94
Taking mHealth Forward: Examining the Core Characteristics
Davis, T. L., DiClemente, R. J., & Prietula, M. J. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.5659 · Cited by 88
Using codesign to develop a culturally tailored, behavior change mHealth intervention for indigenous and other priority communities: A case study in New Zealand
Verbiest, M. E. A., Corrigan, C., Dalhousie, S., Firestone, R. T., Funaki, T., Goodwin, D., Grey, J., Henry, A., Humphrey, G., Jull, A., et al. (2018) · Translational Behavioral Medicine · doi:10.1093/tbm/iby093 · Cited by 98
A 3-Arm randomised controlled trial of Communicating Healthy Beginnings Advice by Telephone (CHAT) to mothers with infants to prevent childhood obesity
Wen, L.-M., Rissel, C., Baur, L., Hayes, A., Xu, H., Whelan, A., Hua, M., Shaw, M., & Phongsavan, P. (2017) · BMC Public Health · doi:10.1186/s12889-016-4005-x · Cited by 75
Design Considerations for Mobile Health Applications Targeting Older Adults
Li, C., Neugroschl, J. A., Zhu, C. W., Aloysi, A. S., Schimming, C., Cai, D., Grossman, H. T., Martin, J. K., Sewell, M. C., Loizos, M., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200485 · Cited by 83
Effects of Mobile Text Messaging on Glycemic Control in Patients With Coronary Heart Disease and Diabetes Mellitus
Huo, X., Krumholz, H. M., Bai, X., Spatz, E. S., Ding, Q., Horak, P. W., Zhao, W., Gong, Q., Zhang, H., Yan, X., et al. (2019) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.119.005805 · Cited by 83
The Effect of Nursing Quality Improvement and Mobile Health Interventions on Infant Sleep Practices
Moon, R. Y., Hauck, F. R., Colson, E. R., Kellams, A. L., Geller, N. L., Heeren, T., Kerr, S. M., Drake, E., Tanabe, K. O., McClain, M., et al. (2017) · JAMA · doi:10.1001/jama.2017.8982 · Cited by 80
Automated vs. Human Health Coaching
Mitchell, E. G., Maimone, R., Cassells, A. N., Tobin, J. N., Davidson, P., Smaldone, A. M., & Mamykina, L. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449173 · Cited by 78
Lifestyle Intervention Enabled by Mobile Technology on Weight Loss in Patients With Nonalcoholic Fatty Liver Disease: Randomized Controlled Trial
Lim, S. L., Johal, J., Ong, K. W., Han, C. Y., Chan, Y. H., Lee, Y. M., & Loo, W. M. (2020) · JMIR mhealth and uhealth · doi:10.2196/14802 · Cited by 79
Digital Solutions for Community and Primary Health Workers: Lessons From Implementations in Africa
Owoyemi, A., Osuchukwu, J. I., Azubuike, C., Ikpe, R. K., Nwachukwu, B. C., Akinde, C. B., Biokoro, G. W., Ajose, A. B., Nwokoma, E. I., Mfon, N. E., et al. (2022) · Frontiers in Digital Health · doi:10.3389/fdgth.2022.876957 · Cited by 78
Evaluation of technology use in education: Findings from a critical analysis of systematic literature reviews
Lai, J. W. M., & Bower, M. (2020) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12412 · Cited by 92
ICTs and development in developing countries: A systematic review of reviews
Lwoga, E. T., & Sangeda, R. Z. (2018) · The Electronic Journal of Information Systems in Developing Countries · doi:10.1002/isd2.12060 · Cited by 89
Lay health supporters aided by mobile text messaging to improve adherence, symptoms, and functioning among people with schizophrenia in a resource-poor community in rural China (LEAN): A randomized controlled trial
Xu, D. R., Xiao, S., He, H., Caine, E. D., Gloyd, S. S., Simoni, J. M., Hughes, J. P., Nie, J., Lin, M., He, W., et al. (2019) · PLoS Medicine · doi:10.1371/journal.pmed.1002785 · Cited by 85
Key facets to build up eHealth and mHealth interventions to enhance physical activity, sedentary behavior and nutrition in healthy subjects – an umbrella review
(2020) · doi:10.1186/s12889-020-09700-7 · Cited by 77
Interventions for improving coverage of childhood immunisation in low- and middle-income countries
Oyo-Ita, A. E., Oduwole, O. A., Arikpo, D., Effa, E., Esu, E., Balakrishna, Y., Chibuzor, M. T., Oringanje, C. M., Nwachukwu, C. E., Wiysonge, C. S., et al. (2023) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008145.pub4 · Cited by 95
Assistive Conversational Agent for Health Coaching: A Validation Study
Fadhil, A., Wang, Y., & Reiterer, H. (2019) · Methods of Information in Medicine · doi:10.1055/s-0039-1688757 · Cited by 77
Mobile Technology Interventions for Asthma Self-Management: Systematic Review and Meta-Analysis
Miller, L., Schüz, B., Walters, J., & Walters, E. H. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.7168 · Cited by 75
“Can you see my screen?” Addressing Racial and Ethnic Disparities in Telehealth
Haynes, N., Ezekwesili, A. C., Nunes, K. L., Gumbs, E., Haynes, M., & Swain, J. D. (2021) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-021-00685-5 · Cited by 78
Unpacking the Black Box: A Formative Research Approach to the Development of Theory-Driven, Evidence-Based, and Culturally Safe Text Messages in Mobile Health Interventions
Maar, M. A., Yeates, K., Tóth, Z., Barron, M., Boesch, L., Hua‐Stewart, D., Liu, P. P., Perkins, N. J., Sleeth, J., Wabano, M. J., et al. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.4994 · Cited by 75
Patient education for people with multiple sclerosis-associated fatigue: A systematic review
Wendebourg, M. J., Heesen, C., Finlayson, M. L., Meyer, B., Pöttgen, J., & Köpke, S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0173025 · Cited by 81
The Use of Chatbots in Oncological Care: A Narrative Review
Wang, A., Qian, Z., Briggs, L., Cole, A. P., Reis, L. O., & Trinh, Q.-D. (2023) · International Journal of General Medicine · doi:10.2147/ijgm.s408208 · Cited by 73
Theory-Based Text-Messaging to Reduce Methamphetamine Use and HIV Sexual Risk Behaviors Among Men Who Have Sex with Men: Automated Unidirectional Delivery Outperforms Bidirectional Peer Interactive Delivery
Reback, C. J., Fletcher, J. B., Swendeman, D. A., & Metzner, M. (2019) · AIDS and Behavior · doi:10.1007/s10461-018-2225-z · Cited by 72
The Impact of Economic Recessions on Depression, Anxiety, and Trauma-Related Disorders and Illness Outcomes—A Scoping Review
Guerra, O., & Eboreime, E. (2021) · Behavioral Sciences · doi:10.3390/bs11090119 · Cited by 88
Effects of Telephone and Short Message Service Support on Infant Feeding Practices, “Tummy Time,” and Screen Time at 6 and 12 Months of Child Age
Wen, L. M., Rissel, C. E., Xu, H., Taki, S., Buchanan, L., Bedford, K., Phongsavan, P., & Baur, L. A. (2020) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2020.0215 · Cited by 69
Mobile phone messaging for illicit drug and alcohol dependence: A systematic review of the literature
Tofighi, B., Nicholson, J., McNeely, J., Muench, F. J., & Lee, J. D. (2017) · Drug and Alcohol Review · doi:10.1111/dar.12535 · Cited by 73
The Future of Orthopaedic Care: Promoting Psychosocial Resiliency in Orthopaedic Surgical Practices
Zale, E. L., Ring, D., & Vranceanu, A. (2018) · Journal of Bone and Joint Surgery · doi:10.2106/jbjs.17.01159 · Cited by 75
Awareness development and usage of mobile health technology among individuals with hypertension in a rural community of Bangladesh: randomized controlled trial
Jahan, Y., Rahman, M. M., Faruque, A. S. G., Chisti, M. J., Kazawa, K., Matsuyama, R., & Moriyama, M. (2020) · Journal of Medical Internet Research · doi:10.2196/19137 · Cited by 67
“However, while a significant number of studies focused on chronic disease prevention, particularly cardiovascular disease prevention by utilization of SMS text messaging, or on diabetes management [19], there are limited studies on BP outcomes [24].”
A Theory-Based Exercise App to Enhance Exercise Adherence: A Pilot Study
Voth, E. C., Oelke, N. D., & Jung, M. E. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.4997 · Cited by 72
A Randomized Controlled Pilot Trial of Different Mobile Messaging Interventions for Problem Drinking Compared to Weekly Drink Tracking
Muench, F. J., van Stolk‐Cooke, K., Kuerbis, A., Stadler, G., Baumel, A., Shao, S., McKay, J. R., & Morgenstern, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0167900 · Cited by 73
Text message behavioral interventions: from here to where?
Suffoletto, B. P. (2015) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2015.09.012 · Cited by 69
A systematic review with meta‐analyses of text message‐delivered behaviour change interventions for weight loss and weight loss maintenance
Skinner, R., Gonet, V., Currie, S., Hoddinott, P., & Dombrowski, S. U. (2020) · Obesity Reviews · doi:10.1111/obr.12999 · Cited by 63
Behavioral Nudges as Patient Decision Support for Medication Adherence: The ENCOURAGE Randomized Controlled Trial
Horne, B. D., Muhlestein, J. B., LAPPE, D. L., May, H. T., Le, V. T., Bair, T. L., Babcock, D., Bride, D. L., Knowlton, K. U., & Anderson, J. L. (2021) · American Heart Journal · doi:10.1016/j.ahj.2021.11.001 · Cited by 66
SMS behaviour change communication and eVoucher interventions to increase uptake of cervical cancer screening in the Kilimanjaro and Arusha regions of Tanzania: a randomised, double-blind, controlled trial of effectiveness
Erwin, E., Aronson, K. J., Day, A. G., Ginsburg, O., Macheku, G. S., Feksi, A. T., Oneko, O., Sleeth, J., Magoma, B., West, N., et al. (2019) · BMJ Innovations · doi:10.1136/bmjinnov-2018-000276 · Cited by 65
Acceptance and Commitment Therapy Delivered via a Mobile Phone Messaging Robot to Decrease Postoperative Opioid Use in Patients With Orthopedic Trauma: Randomized Controlled Trial (Preprint)
Anthony, C. A., Rojas, E. O., Keffala, V., Glass, N. A., Shah, A. S., Miller, B. J., Hogue, M., Willey, M. C., Karam, M., & Marsh, J. L. (2020) · doi:10.2196/preprints.17750 · Cited by 64
“This technology demonstrates high efficacy as part of the treatment of conditions ranging from hypertension to substance abuse [24-26], and it has also proved effective in increasing perioperative communication after hip and knee arthroplasty [27] and collecting pain and opioid medication data from patients following…”
Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature
Donevant, S. B., Dawson, R. M., Culley, J. M., Habing, B., & Adams, S. A. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy104 · Cited by 64
Scoping review and evaluation of SMS/text messaging platforms for mHealth projects or clinical interventions
Iribarren, S. J., Brown, W., Giguere, R., Stone, P., Schnall, R., Staggers, N., & Carballo-Diéguez, A. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.01.017 · Cited by 62
Feasibility and acceptability of telehealth coaching to promote healthy eating in chronic kidney disease: a mixed-methods process evaluation
Kelly, J. T., Warner, M. M., Conley, M. M., Reidlinger, D. P., Hoffmann, T., Craig, J. C., Tong, A., Reeves, M. M., Johnson, D. W., Palmer, S. C., et al. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-024551 · Cited by 61
Life-span differences in the uses and gratifications of tablets: Implications for older adults
Magsamen‐Conrad, K., Dowd, J., Abuljadail, M. H., Alsulaiman, S. A., & Shareefi, A. O. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.05.024 · Cited by 62

Authors: Hall, A. K., Cole-Lewis, H., & Bernhardt, J. M.
Affiliations: University of Washington (US)
Columbia University (US)
The University of Texas at Austin (US)
ORCID: Cole-Lewis, Heather
Bernhardt, Jay M.
Venue: Annual Review of Public Health
Publisher: Annual Reviews
Published: 2015-03-18
Volume: 36
Issue: 1
Pages: 393-415
ISSN: 0163-7525 (ISSN-L)
1545-2093
DOI: 10.1146/annurev-publhealth-031914-122855
PMC: PMC4406229
OpenAlex: W2118907952
Cited by: 815
References: 46
Citations by year: 2026: 32 · 2025: 52 · 2024: 65 · 2023: 67 · 2022: 89 · 2021: 94 · 2020: 94 · 2019: 93 · 2018: 84 · 2017: 85 · 2016: 42 · 2015: 17
FWCI: 13.65
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Annual Review of Public Health (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: University of Washington (T15LM007442)
National Institutes of Health
U.S. National Library of Medicine (T15LM007079, T15LM007442)
Topics: Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Social Sciences › Health › Social Media in Health Education
Keywords: text messaging, health behavior change, diabetes self-management, weight loss, physical activity, smoking cessation, medication adherence, antiretroviral therapy, public health interventions, cost-effectiveness
MeSH terms: Health Promotion, Humans, Program Evaluation, Cell Phone, Medication Adherence, Text Messaging, Weight Reduction Programs

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

Mobile Text Messaging for Health: A Systematic Review of Reviews

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks