Willingness to Exchange Health Information via Mobile Devices: Findings From a Population-Based Survey
Open accessAbstract
PURPOSE: The rapid proliferation of mobile devices offers unprecedented opportunities for patients and health care professionals to exchange health information electronically, but little is known about patients' willingness to exchange various types of health information using these devices. We examined willingness to exchange different types of health information via mobile devices, and assessed whether sociodemographic characteristics and trust in clinicians were associated with willingness in a nationally representative sample. METHODS: We analyzed data for 3,165 patients captured in the 2013 Health Information National Trends Survey. Multinomial logistic regression analysis was conducted to test differences in willingness. Ordinal logistic regression analysis assessed correlates of willingness to exchange 9 types of information separately. RESULTS: Participants were very willing to exchange appointment reminders (odds ratio [OR] = 6.66; 95% CI, 5.68-7.81), general health tips (OR = 2.03; 95% CI, 1.74-2.38), medication reminders (OR = 2.73; 95% CI, 2.35-3.19), laboratory/test results (OR = 1.76; 95% CI, 1.62-1.92), vital signs (OR = 1.63; 95% CI, 1.48-1.80), lifestyle behaviors (OR = 1.40; 95% CI, 1.24-1.58), and symptoms (OR = 1.62; 95% CI, 1.46-1.79) as compared with diagnostic information. Older adults had lower odds of being more willing to exchange any type of information. Education, income, and trust in health care professional information correlated with willingness to exchange certain types of information. CONCLUSIONS: Respondents were less willing to exchange via mobile devices information that may be considered sensitive or complex. Age, socioeconomic factors, and trust in professional information were associated with willingness to engage in mobile health information exchange. Both information type and demographic group should be considered when developing and tailoring mobile technologies for patient-clinician communication.
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Previous research relating to the use of personal electronic health records has demonstrated less public and professional appetite than anticipated.
“Previous research relating to the use of personal electronic health records has demonstrated less public and professional appetite than anticipated [22,44].”
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Cites
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925 · see citing works
A multivariate technique for multiply imputing missing values using a sequence of regression models
Raghunathan, T. E., Lepkowski, J. M., Hoewyk, J. V., & Solenberger, P. W. (2001) · Survey methodology · Cited by 1,981 · see citing works
Trust in Physicians and Medical Institutions: What Is It, Can It Be Measured, and Does It Matter?
Hall, M. A., Dugan, E., Zheng, B., & Mishra, A. K. (2001) · Milbank Quarterly · doi:10.1111/1468-0009.00223 · Cited by 1,491 · see citing works
Rubin, D. B. (1976) · Biometrika · doi:10.2307/2335739 · Cited by 946 · see citing works
Multiple-Imputation Inferences with Uncongenial Sources of Input
Meng, X. (1994) · Statistical Science · doi:10.1214/ss/1177010269 · Cited by 761 · see citing works
Measuring Patients’ Trust in their Primary Care Providers
Hall, M. A., Zheng, B., Dugan, E., Camacho, F., Kidd, K. E., Mishra, A., & Balkrishnan, R. (2002) · Medical Care Research and Review · doi:10.1177/1077558702059003004 · Cited by 661 · see citing works
Socio-economic status of the patient and doctor–patient communication: does it make a difference?
Willems, S., De Maesschalck, S., Deveugele, M., Derese, A., & De Maeseneer, J. (2005) · Patient Education and Counseling · doi:10.1016/j.pec.2004.02.011 · Cited by 582 · see citing works
Cancer patients' trust in their physician—a review
Hillen, M. A., de Haes, J. C. J. M., & Smets, E. M. A. (2010) · Psycho-Oncology · doi:10.1002/pon.1745 · Cited by 342 · see citing works
Schillinger, D., Barton, L. R., Karter, A. J., Wang, F. M., & Adler, N. E. (2006) · Public Health Reports · doi:10.1177/003335490612100305 · Cited by 295 · see citing works
Developing Predictive Models of Health Literacy
Martin, L. T., Ruder, T., Escarce, J. J., Ghosh‐Dastidar, B., Sherman, D., Elliott, M. N., Bird, C. E., Fremont, A. M., Gasper, C., Culbert, A., et al. (2009) · Journal of General Internal Medicine · doi:10.1007/s11606-009-1105-7 · Cited by 223 · see citing works
Duggan, M., & Fox, S. (2012) · Issue Lab (Candid) · Cited by 199 · see citing works
On weighting the rates in non‐response weights
Little, R. J. A., & Vartivarian, S. (2003) · Statistics in Medicine · doi:10.1002/sim.1513 · Cited by 159 · see citing works
Mobile personal health records: An evaluation of features and functionality
Kharrazi, H. H. K., Chisholm, R., VanNasdale, D. A., & Thompson, B. S. (2012) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2012.04.007 · Cited by 147 · see citing works
Patient Interest in Sharing Personal Health Record Information
Zulman, D. M., Nazi, K. M., Turvey, C., Wagner, T. H., Woods, S. S., & An, L. C. (2011) · Annals of Internal Medicine · doi:10.7326/0003-4819-155-12-201112200-00002 · Cited by 139 · see citing works
Wen, K., Kreps, G. L., Zhu, F., & Miller, S. M. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1668 · Cited by 132 · see citing works
Public attitudes toward health information exchange: perceived benefits and concerns.
Dimitropoulos, L. L., Patel, V., Scheffler, S., & Posnack, S. L. (2011) · PubMed · Cited by 111 · see citing works
Self-citationAtienza, A. A., Zarcadoolas, C., Vaughon, W. L., Hughes, P., Patel, V., Chou, W. S., & Pritts, J. (2015) · Journal of Health Communication · doi:10.1080/10810730.2015.1018560 · Cited by 105 · see citing works
Self-citationLubetkin, E. I., Lu, W.-H., & Gold, M. R. (2010) · Journal of Health Care for the Poor and Underserved · doi:10.1353/hpu.0.0350 · Cited by 99 · see citing works
Patel, V., Dhopeshwarkar, R. V., Edwards, A. M., et al. (2010) · Journal of Medical Systems · doi:10.1007/s10916-010-9566-0 · Cited by 90 · see citing works
Self-citationConsumer experience with and attitudes toward health information technology: a nationwide survey
Ancker, J. S., Silver, M. D., Miller, M. C., et al. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001062 · Cited by 86 · see citing works
Atienza, A. A., & Patrick, K. (2011) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2011.01.008 · Cited by 76 · see citing works
Self-citationHealth Care Consumers' Preferences Around Health Information Exchange
Dhopeshwarkar, R. V., Kern, L. M., O’Donnell, H. C., et al. (2012) · The Annals of Family Medicine · doi:10.1370/afm.1396 · Cited by 67 · see citing works
Healthcare Consumers’ Attitudes Towards Physician and Personal Use of Health Information Exchange
O’Donnell, H. C., Patel, V., Kern, L. M., Barrón, Y., Teixeira, P. A., Dhopeshwarkar, R. V., & Kaushal, R. (2011) · Journal of General Internal Medicine · doi:10.1007/s11606-011-1733-6 · Cited by 59 · see citing works
Self-citationPatel, V., Dhopeshwarkar, R. V., Edwards, A. M., et al. (2011) · Informatics for Health and Social Care · doi:10.3109/17538157.2011.554930 · Cited by 57 · see citing works
Self-citationBeckjord, E. B., Rechis, R., Nutt, S., Shulman, L., & Hesse, B. W. (2011) · Journal of Oncology Practice · doi:10.1200/jop.2011.000324 · Cited by 43 · see citing works
The Promise of Digital (Mobile) Health in Cancer Prevention and Treatment
Panayi, N., Mars, M. M., & Burd, R. (2013) · Future Oncology · doi:10.2217/fon.13.42 · Cited by 32 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Rutten L, Hesse BW, Moser RP, Kreps G, eds. Building the Evidence Base in Cancer Communication. Cresskill, NJ: Hampton Press; 2011.
Cited by
Sorted by citations
Lennon, M. R., Bouamrane, M.-M., Devlin, A. M., O'Connor, S., O'Donnell, C., Chetty, U., Agbakoba, R., Bikker, A., Grieve, E., Finch, T., et al. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6900 · Cited by 264 · see citing works
The state of Cancer Care in America, 2017: a report by the American Society of Clinical Oncology
The American Society of Clinical Oncology (2017) · Journal of Oncology Practice · doi:10.1200/jop.2016.020743 · Cited by 204 · see citing works
eHealth in the future of medications management: personalisation, monitoring and adherence
Car, J., Tan, W. S., Huang, Z., Sloot, P., & Franklin, B. D. (2017) · BMC Medicine · doi:10.1186/s12916-017-0838-0 · Cited by 179 · see citing works
Barriers and benefits to using mobile health technology after operation: a qualitative study
Abelson, J. S., Kaufman, E., Symer, M., Peters, A., Charlson, M., & Yeo, H. (2017) · Surgery · doi:10.1016/j.surg.2017.05.007 · Cited by 73 · see citing works
Mobile health apps and recovery after surgery: what are patients willing to do?
Abelson, J. S., Symer, M., Peters, A., Charlson, M., & Yeo, H. (2017) · The American Journal of Surgery · doi:10.1016/j.amjsurg.2017.06.009 · Cited by 64 · see citing works
Kumar, D., Hemmige, V., Kallen, M. A., Giordano, T. P., & Arya, M. (2019) · Cureus · doi:10.7759/cureus.4104 · Cited by 43 · see citing works
Santa Maria, D., Padhye, N., Businelle, M., Yang, Y., Jones, J., Sims, A., & Lightfoot, M. (2021) · Journal of Medical Internet Research · doi:10.2196/26704 · Cited by 36 · see citing works
“EMA-informed JITAIs build off of the willingness to disclose personal information electronically through EMAs [73], overcome geographic and organizational barriers to reaching the underserved [74], require few agency resources, are easily accessible to youth, address personalized prevention care,…”
Lee, D. D., Arya, L. A., Andy, U. U., Sammel, M. D., & Harvie, H. S. (2019) · Female Pelvic Medicine & Reconstructive Surgery · doi:10.1097/spv.0000000000000668 · Cited by 21 · see citing works
Agri, F., Hahnloser, D., Demartines, N., & Hübner, M. (2020) · Colorectal Disease · doi:10.1111/codi.14998 · Cited by 16 · see citing works
- Authors
- Serrano, K. J., Yu, M., Riley, W. T., Patel, V., Hughes, P., Marchesini, K., & Atienza, A. A.
- Affiliations
- National Institutes of Health (US)
- National Cancer Institute (US)
- United States Department of Health and Human Services (US)
- Venue
- The Annals of Family Medicine
- Publisher
- Annals of Family Medicine
- Published
- 2016-01-01
- Volume
- 14
- Issue
- 1
- Pages
- 34-40
- ISSN
- 1544-1709 (ISSN-L)
- 1544-1717
- PMC
- PMC4709153
- OpenAlex
- W2237568987
- Cited by
- 89
- References
- 26
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 6 · 2023: 6 · 2022: 9 · 2021: 7 · 2020: 12 · 2019: 14 · 2018: 9 · 2017: 10 · 2016: 7
- FWCI
- 24.80
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- The Annals of Family Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- mobile health, health information exchange, patient willingness, mobile devices, patient-clinician communication, clinician trust, sensitive health data, appointment reminders, medication reminders, laboratory findings, sociodemographic factors, older adults, socioeconomic factors, Health Information National Trends Survey
- MeSH terms
- Adolescent, Adult, Age Factors, Aged, Cross-Sectional Studies, Educational Status, Humans, Male, Middle Aged, Physician-Patient Relations, Surveys and Questionnaires, Socioeconomic Factors, United States, Logistic Models, Odds Ratio, Telemedicine, Disclosure, Information Dissemination, Trust, Young Adult, Health Records, Personal
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