The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
A content analysis of smartphone–based applications for hypertension management
Abstract
Smartphone-based medical applications (apps) can facilitate self-management of hypertension (HTN). The content and consumer interaction metrics of HTN-related apps are unknown. In this cross-sectional study to ascertain the content of medical apps designed for HTN management, we queried Google Play and Apple iTunes using the search terms "hypertension" and "high blood pressure." The top 107 apps were analyzed. Major app functionalities including tracking (for blood pressure [BP], pulse, weight, body mass index), medical device (to measure pulse or BP), general information on HTN, and medication adherence tools were recorded along with consumer engagement parameters. Data were collected from May 28 to May 30, 2014. A total of 72% of the apps had tracking function, 22% had tools to enhance medication adherence, 37% contained general information on HTN, and 8% contained information on Dietary Approaches to Stop Hypertension (DASH) diet. These data showed that a majority of apps for HTN are designed primarily for health management functions. However, 14% of Google Android apps could transform the smartphone into a medical device to measure BP. None of these apps employed the use of a BP cuff or had any documentation of validation against a gold standard. Only 3% of the apps were developed by healthcare agencies such as universities or professional organizations. In regression models. the medical device function was highly predictive of greater number of downloads (odds ratio, 97.08; P < .001) and positive consumer reviews (Incidence rate ratios, 1204.39; P < .001). A large majority of medical apps designed for HTN serve health management functions such as tracking blood pressure, weight, or body mass index. Consumers have a strong tendency to download and favorably rate apps that are advertised to measure blood pressure and heart rate, despite a lack of validation for these apps. There is a need for greater oversight in medical app development for HTN, especially when they qualify as a medical device.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“and for comparing antihypertensive treatments in clinical trials [118]”
Citations
Cites
Heart Disease and Stroke Statistics—2013 Update: A Report From the American Heart Association
Go, A. S., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Borden, W. B., Bravata, D. M., Dai, S., Ford, E. S., Fox, C. S., et al. (2013) · Circulation · doi:10.1161/cir.0b013e31828124ad · Cited by 5,292
Global Burden of Cardiovascular Diseases
Yusuf, S., Reddy, S., Ôunpuu, S., & Anand, S. S. (2001) · Circulation · doi:10.1161/hc4601.099487 · Cited by 3,014
Free, C., Phillips, G., Galli, L., Watson, L., Felix, L., Edwards, P., Patel, V., & Haines, A. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001362 · Cited by 1,766
Yusuf, S., Reddy, S., Ôunpuu, S., & Anand, S. (2001) · Circulation · doi:10.1161/hc4701.099488 · Cited by 1,141
McManus, R. J., Mant, J., Haque, M. S., Bray, E. P., Bryan, S., Greenfield, S. M., Jones, M. I., Jowett, S., Little, P., Penaloza, C., et al. (2014) · JAMA · doi:10.1001/jama.2014.10057 · Cited by 408
Uhlig, K., Patel, K., Ip, S., Kitsios, G. D., & Balk, E. M. (2013) · Annals of Internal Medicine · doi:10.7326/0003-4819-159-3-201308060-00008 · Cited by 368
McManus, D. D., Lee, J., Maitas, O., Esa, N., Pidikiti, R., Carlucci, A., Harrington, J., Mick, E., & Chon, K. H. (2013) · Heart Rhythm · doi:10.1016/j.hrthm.2012.12.001 · Cited by 253
FDA Regulation of Mobile Health Technologies
Cortez, N. G., Cohen, I. G., & Kesselheim, A. S. (2014) · New England Journal of Medicine · doi:10.1056/nejmhle1403384 · Cited by 229
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
Are video sharing Web sites a useful source of information on hypertension?
Kumar, N., Pandey, A., Venkatraman, A., & Garg, N. (2014) · Journal of the American Society of Hypertension · doi:10.1016/j.jash.2014.05.001 · Cited by 191
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Items 201–207 of 207
Wang, Z., Li, C., Huang, W., Chen, Y., Li, Y., Huang, L., Zhang, M., Wu, D., Wang, L., 段会龙, et al. (2021) · Figshare · doi:10.6084/m9.figshare.13633254
Wang, Z., Li, C., Huang, W., Chen, Y., Li, Y., Huang, L., Zhang, M., Wu, D., Wang, L., 段会龙, et al. (2021) · Figshare · doi:10.6084/m9.figshare.13633251
Ford, K., Bellis, M. A., Judd, N., Griffith, N., & Hughes, K. (2022) · Figshare · doi:10.6084/m9.figshare.20047164
Ramdani, S., Benkaddour, N. E. H., Chergui, I., & Haddiya, I. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-18894-6_10
Ansah, E., Koomson, V. J., Kpodonu, J., Vidzro, S. E., Tetteh, J., Swaray, S. M., Tang, A., Kpodonu, J., Tettey, M. M., & Edwin, F. (2026) · International Journal of Hypertension · doi:10.1155/ijhy/5512077
Development and validation of a digital hypertension risk prediction model for urban Indian adultsPreprint
Rakesh, M., Sunil Kumar, D., Prakash, G. H., Ravali, A., Yadav, D., Gopi, A., & Manirsha, P. V. (2026) · Research Square · doi:10.21203/rs.3.rs-10377899/v1
Symptom Prediction in Chronic Disease Management with Machine Learning Methods
Wu, H., Cui, L., Yang, Y., Chen, J., Deng, N., & Fan, Z. (2026) · Learning and analytics in intelligent systems · doi:10.1007/978-3-032-26620-0_22
Metadata
- Authors
- Kumar, N., Khunger, M., Gupta, A., & Garg, N.
- Affiliations
- Cambridge Health Alliance (US)
- All India Institute of Medical Sciences (IN)
- The University of Texas Southwestern Medical Center (US)
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Kumar, Nilay
- Venue
- Journal of the American Society of Hypertension
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 9
- Issue
- 2
- Pages
- 130-136
- ISSN
- 1878-7436 (ISSN-L)
- 1933-1711
- OpenAlex
- W2036308618
- Cited by
- 208
- References
- 17
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 11 · 2023: 13 · 2022: 27 · 2021: 19 · 2020: 26 · 2019: 26 · 2018: 32 · 2017: 18 · 2016: 13 · 2015: 5
- FWCI
- 22.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Society of Hypertension (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Blood Pressure and Hypertension Studies
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- hypertension, mobile application, mobile health, self-management, blood pressure tracking, medication adherence, medical device validation, customer engagement, DASH diet
- MeSH terms
- Smartphone, Blood Pressure, Cross-Sectional Studies, Database Management Systems, Equipment Design, Humans, Hypertension, Self Care, Telemedicine, 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
