Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking
Open accessAbstract
A new class of patient-driven health care services is emerging to supplement and extend traditional health care delivery models and empower patient self-care. Patient-driven health care can be characterized as having an increased level of information flow, transparency, customization, collaboration and patient choice and responsibility-taking, as well as quantitative, predictive and preventive aspects. The potential exists to both improve traditional health care systems and expand the concept of health care though new services. This paper examines three categories of novel health services: health social networks, consumer personalized medicine and quantified self-tracking.
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The quantified self movement is the driving force behind wearable technologies involving acquisition of data on daily activities, sport performance, and health status.
“The “quantified self” movement is the driving force behind wearable technologies involving acquisition of data on daily activities, sport performance, and health status.1”
From Wearables in Medicine (2018) · cites this paper as [1]
In “Quantified self-tracking,” the paper describes wearable devices with automated collection of activity-related measures, including energy expenditure, and discusses health monitoring. It does not establish that the quantified self movement is the driving force behind wearable technology or specifically identify sport performance as a use. (LLM, conf=0.84)
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Cites
Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness
Eysenbach, G. (2008) · Journal of Medical Internet Research · doi:10.2196/jmir.1030 · Cited by 1,143 · see citing works
What do we mean by partnership in making decisions about treatment?
Charles, C. A., Whelan, T. J., & Gafni, A. (1999) · BMJ · doi:10.1136/bmj.319.7212.780 · Cited by 624 · see citing works
Lithium delays progression of amyotrophic lateral sclerosis
Fornai, F., Longone, P., Cafaro, L., Kastsiuchenka, O., Ferrucci, M., Manca, M. L., Lazzeri, G., Spalloni, A., Bellio, N., Lenzi, P., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0708022105 · Cited by 550 · see citing works
Frost, J. H., & Massagli, M. P. (2008) · Journal of Medical Internet Research · doi:10.2196/jmir.1053 · Cited by 533 · see citing works
The cost of biopharmaceutical R&D: is biotech different?
DiMasi, J. A., & Grabowski, H. G. (2007) · Managerial and Decision Economics · doi:10.1002/mde.1360 · Cited by 517 · see citing works
Waldrop, M. M. (2008) · Scientific American · doi:10.1038/scientificamerican0508-68 · Cited by 165 · see citing works
Measuring function in advanced ALS: validation of ALSFRS‐EX extension items
Wicks, P. J., Massagli, M. P., Wolf, C., & Heywood, J. (2009) · European Journal of Neurology · doi:10.1111/j.1468-1331.2008.02434.x · Cited by 82 · see citing works
Cassman, M., Arkin, A. P., Doyle, F., Katagiri, F., Lauffenburger, D. A., & Stokes, C. L. (2007) · Springer eBooks · doi:10.1007/978-1-4020-5468-6 · Cited by 20 · see citing works
Lewis, R. A. (2007) · Nature · doi:10.1038/nj7164-940a · Cited by 1 · see citing works
Flagged first, then by citations
5 of the 14 references couldn’t be matched to a known paper.
Research works printed but not linked: 9
- [10]Wicks P PatientsLikeMe for ALS/MND Presented at the 18th International ALS/MND Symposium Toronto, Canada December 1–3, 2007(http://blog.patientslikeme.com/2007/12/07/patientslikeme-at-the-toronto-alsmnd-symposium).
- [27]Tapscott D Williams AD Wikinomics 1st Ed Penguin Group New York, NY, USA 2006 7 9
- [28]Charles C Whelan T Gafni A What do we mean by partnership in making decisions about treatment? Brit. Med. J 1999 319 780 782 10488014 PMC1116606
- [30]Bosworth A A Modest Proposal: New Products and Services to Fix Health Care Presented at the Connected Health Symposium Boston, MA, USA October 28, 2008
- [32]Charles C Whelan T Gafni, A. What do we mean by partnership in making decisions about treatment? Brit. Med. J 1999 319 780 782 10488014 PMC1116606
- [33]Vogt E Kuperberg J Creating a Partnership Model for Health Education and Health Care Presented at the 1996 Partnerships for Networked Consumer Health Information Conference Racncho Mirage, CA, USA May 12–14, 1996
- [35]Millar J A Shared Care Model for Complex Chronic Disease Care: A Community of Practice Presented at the PHSA Navigation Workshop Vancouver, British Columbia, Canada February 23, 2004 9 10
- [36]Charles C Whelan T Gafni A What do we mean by partnership in making decisions about treatment? Brit. Med. J 1999 319 780 782 10488014 PMC1116606
- [38]Waldrop M Science 2.0: Great New Tool, or Great Risk Scientific American 2008 http://www.sciam.com/article.cfm?id=science-2-point-0-great-new-tool-or-great-risk(accessed January 9, 2008) 18444327
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Swan, M. (2013) · Big Data · doi:10.1089/big.2012.0002 · Cited by 931 · see citing works
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Wicks, P., Massagli, M., Frost, J., Brownstein, C., Okun, S., Vaughan, T., Bradley, R., & Heywood, J. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1549 · Cited by 603 · see citing works
Yetisen, A. K., Martinez‐Hurtado, J. L., Ünal, B., Khademhosseini, A., & Butt, H. (2018) · Advanced Materials · doi:10.1002/adma.201706910 · Cited by 569 · see citing works
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Appelboom, G., Camacho, E., Abraham, M. E., Bruce, S. S., Dumont, E. L., Zacharia, B. E., D’Amico, R. S., Slomian, J., Reginster, J., Bruyère, O., et al. (2014) · Archives of Public Health · doi:10.1186/2049-3258-72-28 · Cited by 445 · see citing works
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Ben-Zeev, D., Scherer, E. A., Wang, R., Xie, H., & Campbell, A. T. (2015) · Psychiatric Rehabilitation Journal · doi:10.1037/prj0000130 · Cited by 429 · see citing works
Sharon, T. (2017) · Philosophy & Technology · doi:10.1007/s13347-016-0215-5 · Cited by 428 · see citing works
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Lupton, D. (2015) · Health Promotion International · doi:10.1093/heapro/dau091 · Cited by 346 · see citing works
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Clawson, J., Pater, J. A., Miller, A., Mynatt, E. D., & Mamykina, L. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2807554 · Cited by 312 · see citing works
Ancker, J. S., Witteman, H. O., Hafeez, B., Provencher, T., de Graaf, M. V., & Wei, E. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4209 · Cited by 277 · see citing works
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Barrett, M., Oborn, E., & Orlikowski, W. (2016) · Information Systems Research · doi:10.1287/isre.2016.0648 · Cited by 269 · see citing works
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Swan, M. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.1988 · Cited by 262 · see citing works
Self-citationInnovative technologies and social inequalities in health: A scoping review of the literature
Weiss, D., Rydland, H. T., Øversveen, E., Jensen, M. R., Solhaug, S., & Krokstad, S. (2018) · PLOS ONE · doi:10.1371/journal.pone.0195447 · Cited by 240 · see citing works
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van der Eijk, M., Faber, M. J., Aarts, J. W., Kremer, J. A., Munneke, M., & Bloem, B. R. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2476 · Cited by 238 · see citing works
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Wiesner, M., & Pfeifer, D. (2014) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph110302580 · Cited by 237 · see citing works
Welcome, M. O. (2011) · Journal of Pharmacy And Bioallied Sciences · doi:10.4103/0975-7406.90100 · Cited by 223 · see citing works
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de Soto, B. G., Agustí-Juan, I., Joss, S., & Hunhevicz, J. (2019) · International Journal of Construction Management · doi:10.1080/15623599.2019.1616414 · Cited by 218 · see citing works
Hassan, L., Dias, A., & Hamari, J. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2018.12.004 · Cited by 217 · see citing works
Lin, X., & Kishore, R. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120574 · Cited by 213 · see citing works
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Lupton, D. A. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2483549 · Cited by 213 · see citing works
Park, A., Conway, M., & Chen, A. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.09.001 · Cited by 206 · see citing works
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Feng, S., Mäntymäki, M., Dhir, A., & Salmela, H. (2021) · Journal of Medical Internet Research · doi:10.2196/25171 · Cited by 179 · see citing works
Singhal, A., Neveditsin, N., Tanveer, H., & Mago, V. (2024) · JMIR Medical Informatics · doi:10.2196/50048 · Cited by 172 · see citing works
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Fotopoulou, A., & O’Riordan, K. (2016) · Health Sociology Review · doi:10.1080/14461242.2016.1184582 · Cited by 166 · see citing works
Hamari, J., Hassan, L., & Dias, A. (2018) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-018-9200-2 · Cited by 143 · see citing works
Shin, G. D., Feng, Y., Jarrahi, M. H., & Gafinowitz, N. (2018) · JAMIA Open · doi:10.1093/jamiaopen/ooy048 · Cited by 141 · see citing works
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Lowe, S., & OLaighin, G. M. (2013) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2013.11.010 · Cited by 139 · see citing works
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Platt, J. E., Raj, M., & Wienroth, M. (2019) · Journal of Medical Internet Research · doi:10.2196/17026 · Cited by 135 · see citing works
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Lomborg, S., & Frandsen, K. (2015) · Information Communication & Society · doi:10.1080/1369118x.2015.1067710 · Cited by 129 · see citing works
Gallagher-Thompson, D., Tzuang, Y. M., Au, A., Brodaty, H., Charlesworth, G., Gupta, R., Lee, S. E., Losada, A., & Shyu, Y.-I. (2012) · Clinical Gerontologist · doi:10.1080/07317115.2012.678190 · Cited by 128 · see citing works
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Lupton, D. A. (2013) · IEEE Technology and Society Magazine · doi:10.1109/mts.2013.2286431 · Cited by 127 · see citing works
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Aquino, R. P., Barile, S., Grasso, A., & Saviano, M. (2018) · Futures · doi:10.1016/j.futures.2018.03.002 · Cited by 127 · see citing works
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Hofmann, B. (2016) · Medicine Health Care and Philosophy · doi:10.1007/s11019-016-9693-6 · Cited by 122 · see citing works
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Schulte‐Mecklenbeck, M., Johnson, J. G., Böckenholt, U., Goldstein, D. G., Russo, J. E., Sullivan, N. J., & Willemsen, M. C. (2017) · Current Directions in Psychological Science · doi:10.1177/0963721417708229 · Cited by 122 · see citing works
A framework for self-experimentation in personalized health
Karkar, R., Zia, J. K., Vilardaga, R., Mishra, S. R., Fogarty, J. A., Munson, S. A., & Kientz, J. A. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv150 · Cited by 117 · see citing works
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Sharma, A., Singh, A., Gupta, V., & Arya, S. K. (2022) · Sensors & Diagnostics · doi:10.1039/d2sd00005a · Cited by 117 · see citing works
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Green, L. W., Sim, L. J., & Breiner, H. (2014) · Cited by 114 · see citing works
Al-Kahtani, N. K., Alrawiai, S., Al-Zahrani, B. M., Abumadini, R. A., Aljaffary, A. A., Hariri, B. A., Alissa, K. A., Alakrawi, Z., & Alumran, A. K. (2022) · Digital Health · doi:10.1177/20552076221117742 · Cited by 114 · see citing works
Patient-Reported Outcome Measures in Safety Event Reporting: PROSPER Consortium Guidance
Banerjee, A. K., Okun, S., Edwards, I. R., Wicks, P. J., Smith, M. Y., Mayall, S. J., Flamion, B., Cleeland, C. S., & Basch, E. (2013) · Drug Safety · doi:10.1007/s40264-013-0113-z · Cited by 113 · see citing works
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Juengst, E. T., Flatt, M. A., & Settersten, R. A. (2012) · The Hastings Center Report · doi:10.1002/hast.65 · Cited by 113 · see citing works
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Morley, J., & Floridi, L. (2019) · Science and Engineering Ethics · doi:10.1007/s11948-019-00115-1 · Cited by 112 · see citing works
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Ashrafzadeh, S., & Hamdy, O. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2018.09.005 · Cited by 111 · see citing works
IT-Enabled Self-Monitoring for Chronic Disease Self-Management: An Interdisciplinary Review
Jiang, J., & Cameron, A. (2020) · MIS Quarterly · doi:10.25300/misq/2020/15108 · Cited by 108 · see citing works
Goal-oriented visualizations of activity tracking
Santos, J. L., Govaerts, S., Verbert, K., & Duval, E. (2012) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2330601.2330639 · Cited by 106 · see citing works
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Zikmund‐Fisher, B. J., Exe, N. L., & Witteman, H. O. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3241 · Cited by 104 · see citing works
Subhan, M. A., Parveen, F., Shah, H., Yalamarty, S. S. K., Ataide, J. A., & Torchilin, V. P. (2023) · Cancers · doi:10.3390/cancers15082204 · Cited by 103 · see citing works
Almalki, M., Gray, K. M., & Martin-Sanchez, F. J. (2015) · Health Information Science and Systems · doi:10.1186/2047-2501-3-s1-s1 · Cited by 100 · see citing works
Adapting Standards: Ethical Oversight of Participant-Led Health Research
Vayena, E., & Tasioulas, J. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001402 · Cited by 96 · see citing works
Network Dynamics: How Can We Find Patients Like Us?
Yan, L., Peng, J., & Tan, Y. (2011) · Information Systems Research · doi:10.1287/isre.2015.0585 · Cited by 93 · see citing works
Digital social networks and health
Lefebvre, R. C., & Bornkessel, A. S. (2013) · Circulation · doi:10.1161/circulationaha.112.000897 · Cited by 90 · see citing works
Luppa, P. B., Bietenbeck, A., Beaudoin, C. A., & Giannetti, A. E. (2016) · Biotechnology Advances · doi:10.1016/j.biotechadv.2016.01.003 · Cited by 89 · see citing works
Rethinking Health: ICT-Enabled Services to Empower People to Manage Their Health
Honka, A. M., Kaipainen, K., Hietala, H., & Saranummi, N. (2011) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2011.2174217 · Cited by 89 · see citing works
Sagl, G., Resch, B., & Blaschke, T. (2015) · Sensors · doi:10.3390/s150717013 · Cited by 87 · see citing works
Life transitions and online health communities
Massimi, M., Bender, J. L., Witteman, H. O., & Ahmed, O. H. (2014) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/2531602.2531622 · Cited by 86 · see citing works
Person Centered Care and Personalized Medicine: Irreconcilable Opposites or Potential Companions?
El-Alti, L., Sandman, L., & Munthe, C. (2017) · Health Care Analysis · doi:10.1007/s10728-017-0347-5 · Cited by 85 · see citing works
Wearing, Thinking, and Moving: Testing the Feasibility of Fitness Tracking with Urban Youth
Schaefer, S. E., Ching, C. C., Breen, H., & German, J. B. (2016) · American Journal of Health Education · doi:10.1080/19325037.2015.1111174 · Cited by 82 · see citing works
After the Revolution? Ethical and Social Challenges in ‘Personalized Genomic Medicine‘
Juengst, E. T., Settersten, R. A., Fishman, J. R., & McGowan, M. L. (2012) · Personalized Medicine · doi:10.2217/pme.12.37 · Cited by 81 · see citing works
The Quantified Patient in the Doctor's Office
West, P. A., Giordano, R., Kleek, M. G. V., & Shadbolt, N. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858445 · Cited by 81 · see citing works
Sharing Patient-Generated Data in Clinical Practices: An Interview Study.
Zhu, H., Colgan, J. C., Reddy, M. C., & Choe, E. K. (2016) · PubMed Central · Cited by 80 · see citing works
Connected Car: Quantified Self becomes Quantified Car
Swan, M. (2015) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan4010002 · Cited by 78 · see citing works
Self-citationHealth by numbers? Exploring the practice and experience of datafied health
Smith, G. J. D., & Vonthethoff, B. (2016) · Health Sociology Review · doi:10.1080/14461242.2016.1196600 · Cited by 78 · see citing works
A Blockchain-based Architecture Framework for Secure Sharing of Personal Health Data
Amofa, S. K., Sifah, E. B., Agyekum, K. O.-B. O., Smahi, A., Xia, Q., Gee, J. C., & Gao, J. (2018) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2018.8531160 · Cited by 78 · see citing works
Including all voices in international data-sharing governance
Kaye, J. S., Terry, S. F., Juengst, E. T., Coy, S., Harris, J. R., Chalmers, D., Dove, E. S., Budin‐Ljøsne, I., Adebamowo, C., Ogbe, E., et al. (2018) · Human Genomics · doi:10.1186/s40246-018-0143-9 · Cited by 76 · see citing works
Varma, N., Cygankiewicz, I., Turakhia, M. P., Heidbuchel, H., Hu, Y.-F., Chen, L. Y., Couderc, J.-P., Cronin, E. M., Estep, J. D., Grieten, L., et al. (2021) · Circulation: Arrhythmia and Electrophysiology · doi:10.1161/circep.120.009204 · Cited by 74 · see citing works
“…to meet, share their experiences, discuss treatment, and receive and provide support from peers, patient organizations, or HCPs (Fox 2011, Swan 2009, Swan 2012).31–33 While crowdsourcing via the internet and social networks allows collective sharing and exchange of information from a…”
BackgroundMachine Intelligence in Healthcare and Medical Cyber Physical Systems: A Survey
Shishvan, O. R., Zois, D., & Soyata, T. (2018) · IEEE Access · doi:10.1109/access.2018.2866049 · Cited by 73 · see citing works
Measuring Information Preferences
Ho, E., Hagmann, D., & Loewenstein, G. F. (2018) · Management Science · doi:10.1287/mnsc.2019.3543 · Cited by 73 · see citing works
Heyen, N. B. (2019) · Public Understanding of Science · doi:10.1177/0963662519888757 · Cited by 72 · see citing works
Warrington, L., Absolom, K. L., & Velikova, G. (2015) · Acta Oncologica · doi:10.3109/0284186x.2014.995778 · Cited by 72 · see citing works
The internet user profile of Italian families of patients with rare diseases: a web survey
Tozzi, A. E., Mingarelli, R., Agricola, E., Gonfiantini, M., Pandolfi, E., Carloni, E., Gesualdo, F., & Dallapiccola, B. (2013) · Orphanet Journal of Rare Diseases · doi:10.1186/1750-1172-8-76 · Cited by 71 · see citing works
Visualization of Human Behavior Data
Marcengo, A., & Rapp, A. (2013) · Advances in data mining and database management book series · doi:10.4018/978-1-4666-4309-3.ch012 · Cited by 71 · see citing works
Is there a role for social technologies in collaborative healthcare?
Bacigalupe, G. (2011) · Families Systems & Health · doi:10.1037/a0022093 · Cited by 70 · see citing works
Bloem, B. R., & Stocchi, F. (2011) · European Journal of Neurology · doi:10.1111/j.1468-1331.2011.03532.x · Cited by 68 · see citing works
Sanger, P. C., Hartzler, A. L., Lordon, R. J., Armstrong, C. A., Lober, W. B., Evans, H. L., & Pratt, W. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv183 · Cited by 67 · see citing works
Clinical technology specialists
Ben-Zeev, D., Drake, R., & Marsch, L. (2015) · BMJ · doi:10.1136/bmj.h945 · Cited by 66 · see citing works
Effect of Social Media in Health Care and Orthopedic Surgery
Saleh, J., Robinson, B. S., Kugler, N. W., Illingworth, K. D., Patel, P., & Saleh, K. J. (2012) · Orthopedics · doi:10.3928/01477447-20120327-05 · Cited by 66 · see citing works
Andersen, T. O., Langstrup, H., & Lomborg, S. (2020) · Journal of Medical Internet Research · doi:10.2196/15873 · Cited by 65 · see citing works
Slevin, P., Kessie, T., Cullen, J., Butler, M. W., Donnelly, S. C., & Caulfield, B. (2019) · QJM · doi:10.1093/qjmed/hcz241 · Cited by 65 · see citing works
Shared Minds: How Patients Use Collaborative Information Sharing via Social Media Platforms
Yan, L., Yan, X., Tan, Y., & Sun, S. X. (2012) · Production and Operations Management · doi:10.1111/poms.12895 · Cited by 65 · see citing works
Activity trackers, prior motivation, and perceived informational and motivational affordances
Jarrahi, M. H., Gafinowitz, N., & Shin, G. D. (2017) · Personal and Ubiquitous Computing · doi:10.1007/s00779-017-1099-9 · Cited by 64 · see citing works
Towards precision medicine; a new biomedical cosmology
Vegter, M. W. (2018) · Medicine Health Care and Philosophy · doi:10.1007/s11019-018-9828-z · Cited by 63 · see citing works
The relevance of health literacy to mHealth
Kreps, G. L. (2017) · Information Services and Use · doi:10.3233/isu-170828 · Cited by 62 · see citing works
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Pravettoni, G., & Triberti, S. (2019) · Springer eBooks · doi:10.1007/978-3-030-27994-3 · Cited by 62 · see citing works
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- Authors
- Swan, M.
- Affiliations
- Futures Group (United States) (US)
- Corresponding author
- Swan, Melanie
- ORCID
- Swan, Melanie
- Venue
- International Journal of Environmental Research and Public Health
- Publisher
- MDPI AG
- Published
- 2009-02-05
- Volume
- 6
- Issue
- 2
- Pages
- 492-525
- ISSN
- 1660-4601 (ISSN-L)
- PMC
- PMC2672358
- OpenAlex
- W2054712596
- Cited by
- 730
- References
- 14
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 17 · 2023: 30 · 2022: 37 · 2021: 53 · 2020: 53 · 2019: 62 · 2018: 67 · 2017: 66 · 2016: 70 · 2015: 73 · 2014: 64 · 2013: 46 · 2012: 35
- FWCI
- 44.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Environmental Research and Public Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Innovation in Digital Healthcare Systems
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- health social networks, patient self-care, health data transparency, models of care, patient empowerment
- MeSH terms
- Delivery of Health Care, Patient Participation, Patients, Social Support, Models, Organizational
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