The DOI matches its Crossref record; 147 of the 147 references it cites were found in a registry or an index.
Challenges in the development of digital public health interventions and mapped solutions: Findings from a scoping review
Open accessAbstract
Background: “Digital public health” has emerged from an interest in integrating digital technologies into public health. However, significant challenges which limit the scale and extent of this digital integration in various public health domains have been described. We summarized the literature about these challenges and identified strategies to overcome them. Methods: We adopted Arksey and O’Malley's framework (2005) integrating adaptations by Levac et al. (2010). OVID Medline, Embase, Google Scholar, and 14 government and intergovernmental agency websites were searched using terms related to “digital” and “public health.” We included conceptual and explicit descriptions of digital technologies in public health published in English between 2000 and June 2020. We excluded primary research articles about digital health interventions. Data were extracted using a codebook created using the European Public Health Association's conceptual framework for digital public health. Results and analysis: Overall, 163 publications were included from 6953 retrieved articles with the majority (64%, n = 105) published between 2015 and June 2020. Nontechnical challenges to digital integration in public health concerned ethics, policy and governance, health equity, resource gaps, and quality of evidence. Technical challenges included fragmented and unsustainable systems, lack of clear standards, unreliability of available data, infrastructure gaps, and workforce capacity gaps. Identified strategies included securing political commitment, intersectoral collaboration, economic investments, standardized ethical, legal, and regulatory frameworks, adaptive research and evaluation, health workforce capacity building, and transparent communication and public engagement. Conclusion: Developing and implementing digital public health interventions requires efforts that leverage identified strategies to overcome diverse challenges encountered in integrating digital technologies in public health.
Overview
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
Cites
Statistics
Verification
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 cited source says what the claim attributes to it.
In the citing paper
“The sustainability of digital health interventions, particularly with limited public health funding, remains challenging [141,142].”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414
PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
Tricco, A. C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., et al. (2018) · Annals of Internal Medicine · doi:10.7326/m18-0850 · Cited by 43,565 · cited 1×
“Our reports adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for scoping reviews.(13) Data sources”
MethodScoping studies: towards a methodological framework
Arksey, H., & O'Malley, L. (2005) · International Journal of Social Research Methodology · doi:10.1080/1364557032000119616 · Cited by 36,742 · cited 1×
“We followed Arksey and O ’ Malley ’ s framework for scoping reviews, 11 with adaptations suggested by Levac et al.. 12 Our reports adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for scoping reviews.”
MethodScoping studies: advancing the methodology
Levac, D., Colquhoun, H., & O'Brien, K. K. (2010) · Implementation Science · doi:10.1186/1748-5908-5-69 · Cited by 15,268 · cited 1×
“We followed Arksey and O’Malley’s framework for scoping reviews,(11) with adaptations suggested by Levac et al..(12) Our reports adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for scoping reviews.”
MethodUnderstanding digital transformation: A review and a research agenda
Vial, G. (2019) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2019.01.003 · Cited by 7,337 · cited 1×
“9 However, public health action requires wide-ranging public engagement, a population health perspective, and prompt information exchange and cooperation across diverse organizations and public health agencies.”
BackgroundMoorhead, S. A., Hazlett, D. E., Harrison, L., Carroll, J. K., Irwin, A., & Hoving, C. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.1933 · Cited by 2,517
Deep Learning for Health Informatics
Ravì, D., Wong, C., Deligianni, F., Berthelot, M., Andreu-Perez, J., Lo, B., & Yang, G.-Z. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2636665 · Cited by 2,000 · cited 3×
“24,39,40 43 Health equity.”
BackgroundEysenbach, G. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1157 · Cited by 1,351 · cited 2×
“52,154 There is an ethical imperative to implement such strategies as misinfor-mation and disinformation ampli fi ed through digital technology has signi fi cant public health consequences.”
BackgroundDigital technologies in the public-health response to COVID-19
Budd, J., Miller, B. S., Manning, E. M., Lampos, V., Zhuang, M., Edelstein, M., Rees, G., Emery, V. C., Stevens, M. M., Keegan, N., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1011-4 · Cited by 1,195 · cited 1×
“163,164 However, we remain con fi - dent that the broad challenges and strategies identi fi ed in this review remain relevant in our current context.”
BackgroundArtificial intelligence and the future of global health
Schwalbe, N., & Wahl, B. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30226-9 · Cited by 956 · cited 7×
“Further, the iterative and fast-paced evolution of digital technologies is not matched by current research methods which are often rigid and slow to adapt.(27,36,43,45,77,82,83,88,89) There is also a lack of widely agreed-upon standards for assessing outcomes(55,90) and reliable outcome measures that extend beyond use…”
BackgroundInfluentialHarnessing Social Media for Health Promotion and Behavior Change
Korda, H., & Itani, Z. (2011) · Health Promotion Practice · doi:10.1177/1524839911405850 · Cited by 939 · cited 2×
“48,92 Reliance on non-validated user-provided information was also said to reduce chances of successful follow-up in cases of attrition 93 and reduce the representativeness of data.”
BackgroundMichie, S., Yardley, L., West, R., Patrick, K., & Greaves, F. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7126 · Cited by 865 · cited 8×
“35,48,77,82,83,86,90,91 Further, interventions were frequently implemented on a small scale and their associated evaluations were described as poorly generalizable.”
BackgroundInfluentialDigital disease detection - harnessing the Web for public health surveillance
Brownstein, J. S., Freifeld, C. C., & Madoff, L. C. (2009) · New England Journal of Medicine · doi:10.1056/nejmp0900702 · Cited by 819 · cited 1×
“56, 69, 104, 105 The nature of such platforms that Unreliability of available data.”
BackgroundGood intentions are not enough: how informatics interventions can worsen inequality
Veinot, T. C., Mitchell, H., & Ancker, J. S. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy052 · Cited by 704 · cited 2×
“44,72,134,145 Transparent communication and public engagement.”
BackgroundQuantifying the body: monitoring and measuring health in the age of mHealth technologies
Lupton, D. A. (2013) · Critical Public Health · doi:10.1080/09581596.2013.794931 · Cited by 698 · cited 1×
“Articles suggested that digital technologies may propagate a reductionist view on public health that ignores underlying social, economic, environmental, and commercial determinants of health, reducing their effectiveness.(17,38,41,42,87,106,112) Further, inherent biases in assumptions and algorithms facilitating techn…”
BackgroundCrawford, A., & Serhal, E. (2020) · Journal of Medical Internet Research · doi:10.2196/19361 · Cited by 630 · cited 1×
“157,158 Leveraging these key pillars as a central aspect of a digital public health strategy can be an effective starting point to ensure the successful development of the fi eld.”
BackgroundSocial Media in Disaster Risk Reduction and Crisis Management
Alexander, D. (2013) · Science and Engineering Ethics · doi:10.1007/s11948-013-9502-z · Cited by 593 · cited 2×
“89,116,125 Further, the unreliability of unvalidated or anonymous user-generated and/or observational data 52,56,79,80,83,91,92,118,126 – 128 were said to bias reports.”
BackgroundSocial Internet Sites as a Source of Public Health Information
Vance, K. K., Howe, W., & Dellavalle, R. P. (2009) · Dermatologic Clinics · doi:10.1016/j.det.2008.11.010 · Cited by 519
Salathé, M., Bengtsson, L., Bodnar, T. J., Brewer, D. D., Brownstein, J. S., Buckee, C., Campbell, E. M., Cattuto, C., Khandelwal, S., Mabry, P. L., et al. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002616 · Cited by 500 · cited 2×
“25,37,54,73,110,136 The public health workforce has not been supported to develop these capacities at the same pace as the push for development of the technologies required in digital public health.”
BackgroundThe digital revolution and its impact on mental health care
Bucci, S., Schwannauer, M., & Berry, N. (2019) · Psychology and Psychotherapy: Theory, Research and Practice · doi:10.1111/papt.12222 · Cited by 444 · cited 4×
“24,39,40 43 Health equity.”
BackgroundInfluentialSocial Media and Emergency Preparedness in Response to Novel Coronavirus
Merchant, R. M., & Lurie, N. (2020) · JAMA · doi:10.1001/jama.2020.4469 · Cited by 425
Infodemiology and Infoveillance
Eysenbach, G. (2011) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2011.02.006 · Cited by 420 · cited 1×
“52,154 There is an ethical imperative to implement such strategies as misinfor-mation and disinformation ampli fi ed through digital technology has signi fi cant public health consequences.”
BackgroundM-health and health promotion: The digital cyborg and surveillance society
Lupton, D. (2012) · Social Theory & Health · doi:10.1057/sth.2012.6 · Cited by 411 · cited 1×
“Articles suggested that digital technologies may propagate a reductionist view on public health that ignores underlying social, economic, environmental, and commercial determinants of health, reducing their effectiveness.(17,38,41,42,87,106,112) Further, inherent biases in assumptions and algorithms facilitating techn…”
BackgroundStellefson, M., Paige, S. R., Chaney, B. H., & Chaney, J. D. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17041153 · Cited by 399 · cited 1×
“67 This also involves wide-ranging collaboration and action among government agencies, in partnership with other stakeholders, to ensure that data governance and accountability frameworks are adaptable, proactive, and person-centered.”
BackgroundBig data analytics to improve cardiovascular care: promise and challenges
Rumsfeld, J. S., Joynt, K. E., & Maddox, T. M. (2016) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2016.42 · Cited by 398 · cited 1×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
Opportunities and challenges of Web 2.0 for vaccination decisions
Betsch, C., Brewer, N. T., Brocard, P., Davies, P., Gaissmaier, W., Haase, N., Leask, J., Renkewitz, F., Renner, B., Reyna, V. F., et al. (2012) · Vaccine · doi:10.1016/j.vaccine.2012.02.025 · Cited by 391 · cited 2×
“56, 69, 104, 105 The nature of such platforms that Unreliability of available data.”
BackgroundDefining Terms for Integrated (Multi-Inter-Trans-Disciplinary) Sustainability Research
Stock, P. V., & Burton, R. J. F. (2011) · Sustainability · doi:10.3390/su3081090 · Cited by 375
Media Health Literacy, eHealth Literacy, and the Role of the Social Environment in Context
Levin‐Zamir, D., & Bertschi, I. C. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15081643 · Cited by 368
Back to the Future: Achieving Health Equity Through Health Informatics and Digital Health
Brewer, L. C., Fortuna, K. L., Jones, C., Walker, R., Hayes, S. N., Patten, C. A., & Cooper, L. A. (2020) · JMIR mHealth and uHealth · doi:10.2196/14512 · Cited by 367
Social Media– and Internet-Based Disease Surveillance for Public Health
Aiello, A. E., Renson, A., & Zivich, P. N. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094402 · Cited by 363 · cited 1×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
Rethinking Communication in the E-health Era
Neuhauser, L., & Kreps, G. L. (2003) · Journal of Health Psychology · doi:10.1177/1359105303008001426 · Cited by 355 · cited 5×
“35,48,77,82,83,86,90,91 Further, interventions were frequently implemented on a small scale and their associated evaluations were described as poorly generalizable.”
BackgroundMethodInfluentialHealth promotion in the digital era: a critical commentary
Lupton, D. (2015) · Health Promotion International · doi:10.1093/heapro/dau091 · Cited by 346 · cited 1×
“Articles suggested that digital technologies may propagate a reductionist view on public health that ignores underlying social, economic, environmental, and commercial determinants of health, reducing their effectiveness.(17,38,41,42,87,106,112) Further, inherent biases in assumptions and algorithms facilitating techn…”
BackgroundGuo, C., Ashrafian, H., Ghafur, S., Fontana, G., Gardner, C., & Prime, M. S. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-00314-2 · Cited by 345 · cited 1×
“7,8 Many of these challenges apply to digital health generally and are not speci fi c to digital public health.”
BackgroundBig Data in Public Health: Terminology, Machine Learning, and Privacy
Mooney, S. J., & Pejaver, V. (2018) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040617-014208 · Cited by 325 · cited 2×
“These technologies were said to sometimes draw false associations and conclusions, perpetuate stigma, and widen health disparities.(28,36,113,114)”
BackgroundHeldman, A. B., Schindelar, J., & Weaver, J. B. (2013) · Public health reviews · doi:10.1007/bf03391698 · Cited by 293 · cited 1×
“Overall, the authors suggest that these challenges result in poor health behaviors and over-medicalization of common health problems,(56,62,77,80,108) with public health practitioners struggling to control the messaging within these fast-moving media platforms.(95)”
BackgroundGunasekeran, D. V., Tseng, R. M. W. W., Tham, Y. C., & Wong, T. Y. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00412-9 · Cited by 292
Digital Health Equity as a Necessity in the 21st Century Cures Act Era
Rodriguez, J. A., Clark, C. R., & Bates, D. W. (2020) · JAMA · doi:10.1001/jama.2020.7858 · Cited by 289 · cited 1×
“22,73,118,132,138,139 More robust computing infrastructure, 25,64,132,138 including high-bandwidth, low-latency computer networks and clusters of machines for computation 19,25,60 are required to take advantage of high-volume data.”
BackgroundEthical challenges of big data in public health
Vayena, E., Salathé, M., Madoff, L. C., & Brownstein, J. S. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1003904 · Cited by 268
Enhancing disease surveillance with novel data streams: challenges and opportunities
Althouse, B. M., Scarpino, S. V., Ancel, L. W., Ayers, J. W., Bargsten, M., Baumbach, J., Brownstein, J. S., Castro, L. A., Clapham, H., Cummings, D. A. T., et al. (2015) · EPJ Data Science · doi:10.1140/epjds/s13688-015-0054-0 · Cited by 231
Artificial Intelligence for infectious disease Big Data Analytics
Wong, Z. S.-Y., Zhou, J., & Zhang, Q. (2018) · Infection Disease & Health · doi:10.1016/j.idh.2018.10.002 · Cited by 230
Grand Challenges in Digital Health
Kostkova, P. (2015) · Frontiers in Public Health · doi:10.3389/fpubh.2015.00134 · Cited by 227 · cited 4×
“6,7,115,155 For example, privacy and security issues have been documented in relation to public health surveillance.”
BackgroundInfluentialWeb-Based Interventions for Behavior Change and Self-Management: Potential, Pitfalls, and Progress
Murray, E. (2012) · Medicine 2.0 · doi:10.2196/med20.1741 · Cited by 219 · cited 1×
“New methodology suitable for the peculiar pace of development and application of digital technologies, with appropriate measures of health outcomes, are also required to advance research and evaluation in digital public health.(21,27,40,48,58,77,146,149,152) Mechanisms for actively sharing these methods were emphasize…”
MethodBig Data’s Role in Precision Public Health
Dolley, S. (2018) · Frontiers in Public Health · doi:10.3389/fpubh.2018.00068 · Cited by 216 · cited 10×
“21,27,40,48,58,77,146,149,152 Mechanisms for actively sharing these methods were emphasized, including networks and inter-sectorial communities of practice.”
BackgroundMethodInfluentialZhang, X., Pérez‐Stable, E. J., Bourne, P. E., Peprah, E. K., Duru, O. K., Breen, N., Berrigan, D. A., Wood, F. B., Jackson, J. S., Wong, D. W. S., et al. (2017) · Ethnicity & Disease · doi:10.18865/ed.27.2.95 · Cited by 196 · cited 9×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
BackgroundInfluentialHow to govern the digital transformation of health services
Ricciardi, W., Barros, P. P., Bourek, A., Brouwer, W. B. F., Kelsey, T., Lehtonen, L., (EXPH), E. P. O. E. W. O. I. I. H., Anastasy, C., Barros, P. P., Barry, M. M., et al. (2019) · European Journal of Public Health · doi:10.1093/eurpub/ckz165 · Cited by 190
Public health for the people: participatory infectious disease surveillance in the digital age
Wójcik, O. P., Brownstein, J. S., Chunara, R., & Johansson, M. A. (2014) · Emerging Themes in Epidemiology · doi:10.1186/1742-7622-11-7 · Cited by 187 · cited 1×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
One Digital Health: A Unified Framework for Future Health Ecosystems
Benis, A., Tamburis, O., Chronaki, C. E., & Moen, A. (2021) · Journal of Medical Internet Research · doi:10.2196/22189 · Cited by 186
mHealth approaches to child obesity prevention: successes, unique challenges, and next directions
Tate, E. B., Spruijt‐Metz, D., O’Reilly, G. A., Jordan‐Marsh, M., Gotsis, M., Pentz, M. A., & Dunton, G. F. (2013) · Translational Behavioral Medicine · doi:10.1007/s13142-013-0222-3 · Cited by 180 · cited 7×
“21,27,40,48,58,77,146,149,152 Mechanisms for actively sharing these methods were emphasized, including networks and inter-sectorial communities of practice.”
BackgroundInfluentialPublic health digitalization in Europe
Odone, A., Buttigieg, S., Ricciardi, W., Muscat, N. A., & Staines, A. S. (2019) · European Journal of Public Health · doi:10.1093/eurpub/ckz161 · Cited by 178 · cited 4×
“These identified solutions which we refer to as key pillars of digital public health, validate suggestions made by the European Public Health Association (EUPHA).(2) These pillars must be closely considered in tandem with the foundational principles guiding public health practice to create a clear agenda for the ongoi…”
BackgroundResultInfluentialSocial media for health promotion and weight management: a critical debate
Jane, M., Hagger, M. S., Foster, J. K., Ho, S. S., & Pal, S. (2018) · BMC Public Health · doi:10.1186/s12889-018-5837-3 · Cited by 157 · cited 1×
“Articles suggested that digital technologies may propagate a reductionist view on public health that ignores underlying social, economic, environmental, and commercial determinants of health, reducing their effectiveness.(17,38,41,42,87,106,112) Further, inherent biases in assumptions and algorithms facilitating techn…”
BackgroundBublitz, F. M., Oetomo, A., Sahu, K. S., Kuang, A., Fadrique, L. X., Velmovitsky, P. E., da Nobrega, R. M., & Morita, P. P. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16203847 · Cited by 156
Iyamu, I. O., Xu, A. X. T., Gómez-Ramírez, O., Ablona, A., Chang, H.-J., McKee, G. R., & Gilbert, M. (2021) · JMIR Public Health and Surveillance · doi:10.2196/30399 · Cited by 149 · cited 1×
“Our methods and findings about the definition of the field have been described in detail elsewhere.(5,10) Here we focus on the challenges and recommended solutions to support the development and implementation of digital public health interventions.”
MethodSelf-citationExploring the Potential of Web 2.0 to Address Health Disparities
Gibbons, M. C., Fleisher, L. G., Slamon, R. E., Bass, S. B., Kandadai, V., & Beck, J. R. (2011) · Journal of Health Communication · doi:10.1080/10810730.2011.596916 · Cited by 146
Ethical aspects of digital health from a justice point of view
Brall, C., Schröder‐Bäck, P., & Maeckelberghe, E. L. M. (2019) · European Journal of Public Health · doi:10.1093/eurpub/ckz167 · Cited by 133 · cited 5×
“66,77,148 Standardized reporting systems and requirements, 22,77,145 data quality standards, and shared digital architecture 22,23,77,144,145 were suggested as mechanisms to ensure reliable and interoperable data systems to foster improved use of data for decision making.”
BackgroundInfluentialFonseka, T. M., Bhat, V., & Kennedy, S. H. (2019) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867419864428 · Cited by 126 · cited 2×
“The transdisciplinary nature of digital public health interventions and the diversity of regulatory bodies involved in their development and implementation further reinforces the inadequacy of existing policy interventions.(22,32,54,77)”
BackgroundThe use of social media in public health surveillance
Fung, I. C., Tse, Z. T. H., & Fu, K. (2015) · Western Pacific surveillance response journal · doi:10.5365/wpsar.2015.6.1.019 · Cited by 122
Digital health interventions: widening access or widening inequalities?
McAuley, A. (2014) · Public Health · doi:10.1016/j.puhe.2014.10.008 · Cited by 120
Using Artificial Intelligence in Infection Prevention
Fitzpatrick, F., Doherty, A., & Lacey, G. (2020) · Current treatment options in infectious diseases/Current treatment options in infectious disease · doi:10.1007/s40506-020-00216-7 · Cited by 119 · cited 2×
“Further disease and/or areaspecific funding for digital interventions(99,131) and ad hoc design of these systems were said to result in multiple isolated systems developed by different agencies and technology providers.(4,27,31,133) The development and implementation of piecemeal interventions with limited funding tha…”
BackgroundBig Data and the Global Public Health Intelligence Network (GPHIN)
Dion, M., AbdelMalik, P., & Mawudeku, A. (2015) · Canada Communicable Disease Report · doi:10.14745/ccdr.v41i09a02 · Cited by 108 · cited 2×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
BackgroundBig Bad Data: Law, Public Health, and Biomedical Databases
Hoffman, S., & Podgurski, A. (2013) · The Journal of Law Medicine & Ethics · doi:10.1111/jlme.12040 · Cited by 101 · cited 2×
“122 Further, data quality issues, including incomplete data, were said to be a challenge, 24,40,120,123,124 especially for big data in public health surveillance and research, where noisy data (i.e. poor quality data) reduces ef fi ciency.”
BackgroundAdvancing Global Health Research Through Digital Technology and Sharing Data
Lang, T. A. (2011) · Science · doi:10.1126/science.1199349 · Cited by 96 · cited 9×
“98 Many public health agencies lack access to such computing or IT power.”
BackgroundInfluentialSARS and Population Health Technology
Eysenbach, G. (2003) · Journal of Medical Internet Research · doi:10.2196/jmir.5.2.e14 · Cited by 89 · cited 1×
“89,116,125 Further, the unreliability of unvalidated or anonymous user-generated and/or observational data 52,56,79,80,83,91,92,118,126 – 128 were said to bias reports.”
BackgroundSocial media and health promotion
Norman, C. D. (2012) · Global Health Promotion · doi:10.1177/1757975912464593 · Cited by 89 · cited 2×
“55 Where there are standards, public health professionals have been shown to have sub-optimal awareness of existing data reporting standards 22 and data quality requirements across systems.”
BackgroundThe role of public health informatics in enhancing public health surveillance.
Savel, T. G., & Foldy, S. L. (2012) · PubMed · Cited by 88
Ethics in Public Health Research
Myers, J. E., Frieden, T. R., Bherwani, K. M., & Henning, K. J. (2008) · American Journal of Public Health · doi:10.2105/ajph.2006.107706 · Cited by 85
Digital and social media opportunities for dietary behaviour change
McGloin, A. F., & Eslami, S. (2014) · Proceedings of The Nutrition Society · doi:10.1017/s0029665114001505 · Cited by 85
Re-Prioritizing Digital Health and Health Literacy in Healthy People 2030 to Affect Health Equity
Jackson, D. N., Trivedi, N. S., & Baur, C. (2020) · Health Communication · doi:10.1080/10410236.2020.1748828 · Cited by 84 · cited 1×
“27,53,145,148 Such partnerships were also deemed important for creating coherent and coordinated interoperability, governance, and research frameworks, and garnering required resources, knowledge, and capacities to harness the potential of digital public health interventions.”
BackgroundFive Crucial Challenges in Digital Health
Cummins, N., & Schuller, B. W. (2020) · Frontiers in Digital Health · doi:10.3389/fdgth.2020.536203 · Cited by 84 · cited 4×
“6,7,115,155 For example, privacy and security issues have been documented in relation to public health surveillance.”
BackgroundInfluentialYasnoff, W. A., Overhage, J. M., Humphreys, B. L., & LaVenture, M. (2001) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2001.0080535 · Cited by 81 · cited 9×
“22,32,54,77 Paucity of high-quality evidence.”
BackgroundInfluentialMcKee, M., van Schalkwyk, M. C., & Stückler, D. (2019) · European Journal of Public Health · doi:10.1093/eurpub/ckz160 · Cited by 81 · cited 3×
“21,26,33,35,38,40,73,74 Widespread lack of digital health equity implementation frameworks and rigorous evaluation of the equity impacts of these digital technologies may further complicate equity challenges.”
BackgroundSchootman, M., Nelson, E. J., Werner, K., Shacham, E., Elliott, M., Ratnapradipa, K. L., Lian, M., & McVay, A. B. (2016) · International Journal of Health Geographics · doi:10.1186/s12942-016-0050-z · Cited by 80 · cited 2×
“89,116,125 Further, the unreliability of unvalidated or anonymous user-generated and/or observational data 52,56,79,80,83,91,92,118,126 – 128 were said to bias reports.”
BackgroundImproving the public health impact of eHealth and mHealth interventions
Grady, A., Yoong, S., Sutherland, R., Lee, H., Nathan, N., & Wolfenden, L. (2018) · Australian and New Zealand Journal of Public Health · doi:10.1111/1753-6405.12771 · Cited by 79 · cited 2×
“– 87 Articles noted the inad-equacy of cost – analysis evidence, speci fi cally the costs of these interventions to individuals and health systems, 36,64,77 and the mostly retrospective use of data in existing research that may be biased or have missing data.”
BackgroundA Global Digital Citizen Science Policy to Tackle Pandemics Like COVID-19
Katapally, T. R. (2020) · Journal of Medical Internet Research · doi:10.2196/19357 · Cited by 79 · cited 2×
“17,98”
BackgroundLee, E. W. J., & Viswanath, K. (2020) · Journal of Medical Internet Research · doi:10.2196/16377 · Cited by 77
Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference
Lee, E. C., Asher, J., Goldlust, S., Kraemer, J. D., Lawson, A. B., & Bansal, S. (2016) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiw344 · Cited by 75
Artificial Intelligence in Global Health —A Framework and Strategy for Adoption and Sustainability
Hadley, T. D., Pettit, R. W., Malik, T., Khoei, A. A., & Salihu, H. M. (2020) · International Journal of Maternal and Child Health and AIDS · doi:10.21106/ijma.296 · Cited by 75
Shaw, N. T., & McGuire, S. (2017) · Journal of Innovation in Health Informatics · doi:10.14236/jhi.v24i2.940 · Cited by 74 · cited 2×
“30,40,117,136,149 Further, recommendations involved integrating research and evaluation in all stages of development and implementation of digital interventions.”
BackgroundGlossary for public health surveillance in the age of data science
Chioléro, A., & Buckeridge, D. L. (2020) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2018-211654 · Cited by 72 · cited 3×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
BackgroundDigital public health and COVID-19
Murray, C. J. L., Alamro, N., Hwang, H. Y., & Lee, U. (2020) · The Lancet Public Health · doi:10.1016/s2468-2667(20)30187-0 · Cited by 70 · cited 1×
“Yet, resistance to these new approaches within public health and the tendency to suppress data especially with suboptimal interventions, introduce additional challenges that must be navigated.(3) The speed of technological development must also be considered in these frameworks.”
BackgroundAl-Surimi, K. M., Khalifa, M., Bahkali, S., El‐Metwally, A., & Househ, M. S. (2016) · Advances in experimental medicine and biology · doi:10.1007/5584_2016_132 · Cited by 69
Trending now: future directions in digital media for the public health sector
Burke‐Garcia, A., & Scally, G. (2014) · Journal of Public Health · doi:10.1093/pubmed/fdt125 · Cited by 68 · cited 2×
“35,48,77,82,83,86,90,91 Further, interventions were frequently implemented on a small scale and their associated evaluations were described as poorly generalizable.”
BackgroundCombining Health Data Uses to Ignite Health System Learning
Buchan, I. E., & Ainsworth, J. D. (2015) · Methods of Information in Medicine · doi:10.3414/me15-01-0064 · Cited by 65 · cited 4×
“22,37,43,63,64,73,98,99,123,131,135 Public health agencies are said to have challenges with engaging and retaining highly demanded tech-savvy public health analysts.”
BackgroundInfluentialPublic Health in the Era of Social Media
Abroms, L. C. (2019) · American Journal of Public Health · doi:10.2105/ajph.2018.304947 · Cited by 64 · cited 1×
“56, 69, 104, 105 The nature of such platforms that Unreliability of available data.”
BackgroundA “big data” approach to HIV epidemiology and prevention
Young, S. D. (2014) · Preventive Medicine · doi:10.1016/j.ypmed.2014.11.002 · Cited by 63 · cited 2×
“89,116,125 Further, the unreliability of unvalidated or anonymous user-generated and/or observational data 52,56,79,80,83,91,92,118,126 – 128 were said to bias reports.”
BackgroundDrivers of Emerging Infectious Disease Events as a Framework for Digital Detection
Olson, S. H., Benedum, C. M., Mekaru, S. R., Preston, N. D., Mazet, J. A. K., Joly, D. O., & Brownstein, J. S. (2015) · Emerging infectious diseases · doi:10.3201/eid2108.141156 · Cited by 59 · cited 3×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
BackgroundDisease surveillance data sharing for public health: the next ethical frontiers
Kostkova, P. (2018) · Life Sciences Society and Policy · doi:10.1186/s40504-018-0078-x · Cited by 57 · cited 2×
“21,27,40,48,58,77,146,149,152 Mechanisms for actively sharing these methods were emphasized, including networks and inter-sectorial communities of practice.”
BackgroundLu, Z. (2009) · Drug Healthcare and Patient Safety · doi:10.2147/dhps.s7180 · Cited by 55
Big Data and Health Economics: Strengths, Weaknesses, Opportunities and Threats
Collins, B. (2015) · PharmacoEconomics · doi:10.1007/s40273-015-0306-7 · Cited by 53 · cited 1×
“24,39,40 43 Health equity.”
Nemzoff, C., Ruiz, F. J., Chalkidou, K., Mehndiratta, A., Guinness, L., Cluzeau, F., & Shah, H. A. (2021) · BMJ Global Health · doi:10.1136/bmjgh-2020-004549 · Cited by 53 · cited 2×
“162 Further, for pragmatic policies to be made and implemented appropriately, public health policy makers, practitioners, and researchers will require continued education on new working methods in a digital environment.”
BackgroundFour equity considerations for the use of artificial intelligence in public health
Smith, M. J., Axler, R. E., Bean, S., Rudzicz, F., & Shaw, J. (2020) · Bulletin of the World Health Organization · doi:10.2471/blt.19.237503 · Cited by 52 · cited 1×
“Further, inherent biases in assumptions and algorithms facilitating technologies like artificial intelligence, big data, and social media in public health were reported to potentially make them counterproductive to public health goals.(21,28,36,47,113,114) These technologies were said to sometimes draw false associati…”
BackgroundMacro Trends and the Future of Public Health Practice
Erwin, P. C., & Brownson, R. C. (2016) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-031816-044224 · Cited by 50 · cited 1×
“27,36,43,45,77,82,83,88,89 There is also a lack of widely agreed-upon standards for assessing outcomes 55,90 and reliable outcome measures that extend beyond user engagement metrics.”
BackgroundOnline Technologies for Health Information and Education: A Literature Review
Gill, H. K., Gill, N. K., & Young, S. D. (2013) · Journal of Consumer Health on the Internet · doi:10.1080/15398285.2013.780542 · Cited by 45 · cited 1×
“26,31,32,35,33 34 Additional ethical barriers include the potential identi fi cation of individual disease risks and exposures through digital technologies without clear remedies, 36 – 38 perpetuation of stigma through data collection methods that do not acknowledge the existing context.”
BackgroundBehavioral Interventions Using Consumer Information Technology as Tools to Advance Health Equity
Henry, S. B., Marden, S., Arteaga, S. S., Liu, L. G., Keselman, A., Le, P., Creber, R. M., Powell‐Wiley, T. M., Schnall, R., Tabor, D. C., et al. (2019) · American Journal of Public Health · doi:10.2105/ajph.2018.304646 · Cited by 45 · cited 3×
“Further, the iterative and fast-paced evolution of digital technologies is not matched by current research methods which are often rigid and slow to adapt.(27,36,43,45,77,82,83,88,89) There is also a lack of widely agreed-upon standards for assessing outcomes(55,90) and reliable outcome measures that extend beyond use…”
BackgroundNaslund, J. A., & Aschbrenner, K. A. (2019) · Evidence Based Mental Health · doi:10.1136/ebmental-2018-300034 · Cited by 44 · cited 2×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
BackgroundInnovative Uses of Electronic Health Records and Social Media for Public Health Surveillance
Eggleston, E., & Weitzman, E. R. (2014) · Current Diabetes Reports · doi:10.1007/s11892-013-0468-7 · Cited by 43 · cited 2×
“122 Further, data quality issues, including incomplete data, were said to be a challenge, 24,40,120,123,124 especially for big data in public health surveillance and research, where noisy data (i.e. poor quality data) reduces ef fi ciency.”
BackgroundAccess and authorisation in a Glocal e-Health Policy context
Scott, R. E., Jennett, P., & Yeo, M. (2004) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2003.11.020 · Cited by 42 · cited 3×
“Articles described challenges with policy keeping pace with evolving digital technologies in public health, 20,23,26,40,50,63,64,75 – 79 resulting in reactive policies that are restrictive (often limiting data exchange), inadequate to support the development and implementation of digital…”
BackgroundCommunicable Disease Surveillance Ethics in the Age of Big Data and New Technology
Gilbert, G. L., Degeling, C., & Johnson, J. (2019) · Asian Bioethics Review · doi:10.1007/s41649-019-00087-1 · Cited by 42 · cited 1×
“4,22,64,103,141 Standards for evaluating the impact of digital technologies on health outcomes are also suboptimal.”
BackgroundCarney, T. J., & Kong, A. Y. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.02.011 · Cited by 41 · cited 2×
“21,38,40,46,73,85,89,91,101,116,125,129,130 Fragmented, isolated, and unsustainable systems.”
BackgroundApplications of Electronic Health Information in Public Health: Uses, Opportunities and Barriers
Tomines, A., Readhead, H., Readhead, A., & Teutsch, S. (2013) · eGEMs (Generating Evidence & Methods to improve patient outcomes) · doi:10.13063/2327-9214.1019 · Cited by 40
Hayes, J., Maughan, D. L., & Grant‐Peterkin, H. (2016) · The British Journal of Psychiatry · doi:10.1192/bjp.bp.114.161067 · Cited by 40 · cited 1×
“36,64,108,136 Suboptimal design and implementation of digital technologies.”
BackgroundUsing Social Media to Target Cancer Prevention in Young Adults: Viewpoint
Sarkar, U., Le, G. M., Lyles, C. R., Ramo, D. E., Linos, E., & Bibbins-Domingo, K. B. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8882 · Cited by 40 · cited 4×
“35,48,77,82,83,86,90,91 Further, interventions were frequently implemented on a small scale and their associated evaluations were described as poorly generalizable.”
BackgroundInfluentialTranslational Health Disparities Research in a Data-Rich World
Breen, N., Berrigan, D. A., Jackson, J. S., Wong, D. W. S., Wood, F. B., Denny, J. C., Zhang, X., & Bourne, P. E. (2019) · Health Equity · doi:10.1089/heq.2019.0042 · Cited by 40
A National Agenda for Public Health Informatics
Yasnoff, W. A., Overhage, J. M., Humphreys, B. L., LaVenture, M., Goodman, K. W., Gatewood, L. C., Ross, D. A., Reid, J. A., Hammond, E. W., Dwyer, D. M., et al. (2001) · Journal of Public Health Management and Practice · doi:10.1097/00124784-200107060-00002 · Cited by 39 · cited 3×
“19 Articles suggest that such curricula may be made open through communities of practice and interdisciplinary workforce exchanges to foster equitable knowledge uptake.”
BackgroundGómez-Ramírez, O., Iyamu, I. O., Ablona, A., Watt, S., Xu, A. X. T., Chang, H.-J., & Gilbert, M. (2021) · Canadian Journal of Public Health · doi:10.17269/s41997-021-00487-7 · Cited by 39
Self-citationTranslational Health Disparities Research in a Data-Rich World
Breen, N., Jackson, J. S., Wood, F. B., Wong, D. W. S., & Zhang, X. (2019) · American Journal of Public Health · doi:10.2105/ajph.2019.304951 · Cited by 38
Khoury, M. J., Engelgau, M. M., Chambers, D., & Mensah, G. A. (2018) · Public Health Genomics · doi:10.1159/000501465 · Cited by 38 · cited 1×
“122 Further, data quality issues, including incomplete data, were said to be a challenge, 24,40,120,123,124 especially for big data in public health surveillance and research, where noisy data (i.e. poor quality data) reduces ef fi ciency.”
BackgroundStoove, M. A., & Pedrana, A. E. (2014) · Preventive Medicine · doi:10.1016/j.ypmed.2014.03.008 · Cited by 37 · cited 3×
“35,48,77,82,83,86,90,91 Further, interventions were frequently implemented on a small scale and their associated evaluations were described as poorly generalizable.”
BackgroundFuller, D., Buote, R., & Stanley, K. G. (2017) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2017-209608 · Cited by 37 · cited 1×
“The overly enthusiastic assumption that digital technologies provide a catchall solution to public health challenges without due consideration of alternative approaches and foundational principles of public health was noted.(18,38,40,111) Articles suggested that digital technologies may propagate a reductionist view o…”
BackgroundNorman, C. D., & Yip, A. L. (2012) · PubMed · Cited by 36
Big data in healthcare: a discussion on the big challenges
Stylianou, A., & Talias, Μ. A. (2016) · Health and Technology · doi:10.1007/s12553-016-0152-4 · Cited by 36 · cited 2×
“22,23,26,28,50,103,121,131,132 This partly results from privacy and con fi dentiality concerns, 22,37 and infrastructure/capacity gaps.”
BackgroundWere, M. C., Sinha, C., & Catalani, C. (2019) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocz071 · Cited by 36 · cited 2×
“44,72,134,145 Transparent communication and public engagement.”
Using Social Media for Research and Public Health Surveillance
Eke, P. I. (2011) · Journal of Dental Research · doi:10.1177/0022034511415277 · Cited by 33 · cited 1×
“89,116,125 Further, the unreliability of unvalidated or anonymous user-generated and/or observational data 52,56,79,80,83,91,92,118,126 – 128 were said to bias reports.”
BackgroundPublic Trust and Privacy in Shared Electronic Health Records
Rynning, E. (2007) · European Journal of Health Law · doi:10.1163/092902707x211668 · Cited by 33 · cited 6×
“54 Governance challenges in supporting interjurisdictional digital interventions were also highlighted, 20,22,29,30,50 especially for technologies not requiring in-person attendance.”
BackgroundInfluentialBig Data for Public Health Policy-Making: Policy Empowerment
Mählmann, L., Reumann, M., Evangelatos, N. G., & Brand, A. M. (2017) · Public Health Genomics · doi:10.1159/000486587 · Cited by 32 · cited 5×
“66,77,148 Standardized reporting systems and requirements, 22,77,145 data quality standards, and shared digital architecture 22,23,77,144,145 were suggested as mechanisms to ensure reliable and interoperable data systems to foster improved use of data for decision making.”
BackgroundInfluentialDigital Segmentation of Priority Populations in Public Health
Evans, W. D., Thomas, C. N., Favatas, D., Smyser, J., & Briggs, J. (2019) · Health Education & Behavior · doi:10.1177/1090198119871246 · Cited by 31 · cited 2×
“35,48,77,82,83,86,90,91 Further, interventions were frequently implemented on a small scale and their associated evaluations were described as poorly generalizable.”
BackgroundSmith, P. M. (2007) · Critical Public Health · doi:10.1080/09581590701244954 · Cited by 29 · cited 2×
“159,160 However, we must note that achieving transdis-ciplinary partnerships will be challenging given differences in vocabulary across disciplines and varied epistemological viewpoints that guide practice and research.”
BackgroundConsumer health informatics: From genomics to population health
McDaniel, A. M., Schutte, D. L., & Keller, L. O. (2008) · Nursing Outlook · doi:10.1016/j.outlook.2008.06.006 · Cited by 27 · cited 2×
“22,37,43,63,64,73,98,99,123,131,135 Public health agencies are said to have challenges with engaging and retaining highly demanded tech-savvy public health analysts.”
BackgroundThe Relevance of Health Literacy to mHealth.
Kreps, G. L. (2017) · PubMed · Cited by 27
Ölvingson, C., Hallberg, J., Timpka, T., & Lindqvist, K. S. (2002) · Journal of Biomedical Informatics · doi:10.1016/s1532-0464(02)00527-0 · Cited by 26 · cited 2×
“122 Further, data quality issues, including incomplete data, were said to be a challenge, 24,40,120,123,124 especially for big data in public health surveillance and research, where noisy data (i.e. poor quality data) reduces ef fi ciency.”
BackgroundThe public health informatics infrastructure: anticipating its role in cancer
Shortliffe, E. H., & Sondik, E. J. (2006) · Cancer Causes & Control · doi:10.1007/s10552-006-0028-4 · Cited by 25 · cited 2×
“22,133,137 Infrastructure gaps.”
BackgroundCyber-management of people with chronic disease: A potential solution to eHealth challenges
Laakso, E., Armstrong, K., & Usher, W. T. (2011) · Health Education Journal · doi:10.1177/0017896911408813 · Cited by 24 · cited 3×
“Where there are standards, public health professionals have been shown to have suboptimal awareness of existing data reporting standards(22) and data quality requirements across systems.(36,64,108,136)”
BackgroundThe Promise of Direct-to-Consumer Telehealth for Disaster Response and Recovery
Uscher‐Pines, L., Fischer, S. H., & Chari, R. (2016) · Prehospital and Disaster Medicine · doi:10.1017/s1049023x16000558 · Cited by 23
Using Social Media and Internet Data for Public Health Surveillance: The Importance of Talking
Hartley, D. (2014) · Milbank Quarterly · doi:10.1111/1468-0009.12039 · Cited by 22 · cited 1×
“22,36,134,140 Standards in vocabulary and health information exchange and coordination are lacking, resulting in suboptimal interoperability of varied systems relevant to public health functions.”
BackgroundCawcutt, K. A., Marcelin, J. R., & Silver, J. K. (2019) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2019.231 · Cited by 22 · cited 1×
“25,37,54,73,110,136 The public health workforce has not been supported to develop these capacities at the same pace as the push for development of the technologies required in digital public health.”
BackgroundBig Data: transforming drug development and health policy decision making
Alemayehu, D., & Berger, M. L. (2016) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-016-0144-x · Cited by 21 · cited 2×
“26,66,98,124,138,149 Open science, equity-based frameworks were also recommended with a focus on including outcomes for marginalized populations in publications.”
BackgroundGlobal mHealth policy arena: status check and future directions
Malvey, D. M., & Slovensky, D. J. (2017) · mHealth · doi:10.21037/mhealth.2017.09.03 · Cited by 21 · cited 6×
“54 Governance challenges in supporting interjurisdictional digital interventions were also highlighted, 20,22,29,30,50 especially for technologies not requiring in-person attendance.”
BackgroundInfluentialSexual and reproductive health and rights and mHealth in policy and practice in South Africa
Waldman, L., & Stevens, M. (2015) · Reproductive Health Matters · doi:10.1016/j.rhm.2015.06.009 · Cited by 20 · cited 3×
“22,32,54,77 Paucity of high-quality evidence.”
BackgroundBridging Radiology and Public Health: The Emerging Field of Radiologic Public Health Informatics
Mollura, D. J., Carrino, J. A., Matuszak, D. L., Mnatsakanyan, Z. R., Eng, J., Cutchis, P. N., Babin, S. M., Sniegoski, C., & Lombardo, J. S. (2008) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2007.08.020 · Cited by 19
Public Health Informatics: The Nature of the Field and Its Relevance to Health Promotion Practice
Kukafka, R. (2004) · Health Promotion Practice · doi:10.1177/1524839904270389 · Cited by 18
Health Cyberinfrastructure for Collaborative Use-Inspired Research and Practice
Chismar, W. G., Horan, T. A., Hesse, B. W., Feldman, S. S., & Shaikh, A. R. (2011) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2011.01.002 · Cited by 17
Ethical issues when using social media for health outside professional relationships
DeCamp, M. W. (2015) · International Review of Psychiatry · doi:10.3109/09540261.2014.1001726 · Cited by 16
Andreassen, O. A. (2017) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32561 · Cited by 16 · cited 2×
“21,73,121,147 Further, standardized ethical, legal, and regulatory frameworks are required to ensure seamless, secure data exchanges between health agencies and authorities.”
BackgroundAligning Health Informatics Across the Public Health Enterprise
Kirkwood, J., & Jarris, P. E. (2012) · Journal of Public Health Management and Practice · doi:10.1097/phh.0b013e31824eb919 · Cited by 15 · cited 3×
“22,37,43,63,64,73,98,99,123,131,135 Public health agencies are said to have challenges with engaging and retaining highly demanded tech-savvy public health analysts.”
BackgroundICT and patient roles; contradictions in e-health policy
Andreassen, H. (2012) · Health Policy and Technology · doi:10.1016/j.hlpt.2012.04.002 · Cited by 15 · cited 2×
“122,142 Mapped solutions to overcome technical and nontechnical challenges Potential solutions, as described in the literature, are summarized in Table 3.”
BackgroundGrande, S. W., & Sherman, L. D. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9434 · Cited by 14 · cited 1×
“21,26,33,35,38,40,73,74 Widespread lack of digital health equity implementation frameworks and rigorous evaluation of the equity impacts of these digital technologies may further complicate equity challenges.”
BackgroundAssessing the Public Health Impact of the mHealth App Business
Freudenberg, N. (2017) · American Journal of Public Health · doi:10.2105/ajph.2017.304083 · Cited by 13 · cited 3×
“This may be further exacerbated through the economic incentive to target high-income users with commercial digital health interventions.(71) Other equity challenges described include disparities in the impact of overlooked potential consequences of digital technologies, such as data privacy breaches, data misuse, and…”
BackgroundIyamu, I. O., Gómez-Ramírez, O., Xu, A. X. T., Chang, H.-J., Haag, D., Watt, S., & Gilbert, M. (2021) · JMIR Research Protocols · doi:10.2196/27686 · Cited by 13
Self-citationQuantifying the Modern City: Emerging Technologies and Big Data for Active Living Research
Adlakha, D. (2017) · Frontiers in Public Health · doi:10.3389/fpubh.2017.00105 · Cited by 12
Digital government and public health.
Fountain, J. E. (2004) · PubMed · Cited by 11
Creating a pandemic of health: What is the role of digital technologies?
Jadad, A. R. (2016) · Journal of Public Health Policy · doi:10.1057/s41271-016-0016-1 · Cited by 11
Harnessing digital data and data science to achieve 90–90–90 goals to end the HIV epidemic
Strathdee, S. A., Nobles, A. L., & Ayers, J. W. (2019) · Current Opinion in HIV and AIDS · doi:10.1097/coh.0000000000000584 · Cited by 11 · cited 1×
“33–35,56,69,104,105 The nature of such platforms that leverage user-generated content(35,51,62,106) with relative anonymity(51,107) and unclear guidelines(43,105) were said to spread unverified and often questionable information.(34,43,51,52,108) Further, information overload on the public and the burden of health-inf…”
BackgroundChapter 3: Public Health Applications
Kopp, S., Shuchman, R. A., Strecher, V. J., Gueye, M., Ledlow, J., Philip, T., & Grodzinski, A. R. (2002) · Telemedicine Journal and e-Health · doi:10.1089/15305620252933383 · Cited by 10
Big Data, Large-Scale Text Analysis, and Public Health Research
Chowkwanyun, M. (2019) · American Journal of Public Health · doi:10.2105/ajph.2019.304965 · Cited by 10 · cited 1×
“135 Considering the heterogeneity of data required for public health functions, reporting standards are required to effectively pool data; however, these standards are yet to be developed.”
BackgroundTechnology-based health promotion: Current state and perspectives in emerging gig economy
Morales, J., Inupakutika, D., Kaghyan, S., Akopian, D., Yin, Z., Evans, M., & Parra-Medina, D. M. (2019) · Journal of Applied Biomedicine · doi:10.1016/j.bbe.2019.07.006 · Cited by 9 · cited 1×
“43,94 Resource and economic interest barriers.”
Institutional Entrepreneurship for Digital Public Health Promotion: Challenges and Opportunities
Reyes, G. D. L. (2019) · Health Education & Behavior · doi:10.1177/1090198119871245 · Cited by 9
Landry, M., & Singh, P. (2019) · WHO South-East Asia Journal of Public Health · doi:10.4103/2224-3151.264848 · Cited by 8
Achieving Value in Population Health Big Data
Bu, D. D., Liu, S. H., Liu, B., & Li, Y. (2020) · Journal of General Internal Medicine · doi:10.1007/s11606-020-05869-0 · Cited by 4 · cited 1×
“22,23,26,28,50,103,121,131,132 This partly results from privacy and con fi dentiality concerns, 22,37 and infrastructure/capacity gaps.”
Background
Flagged first, then by citations
Research works printed but not linked: 22
- World Health Organization (WHO), 2020, Draft global strategy on digital health 2020–2024
- Public Health England, 2017, Digital-first public health: public health England’s digital strategy
- Canadian Public Health Association, The Canadian Public Health Association, Canadian Public Health Association, 2017, Public health: a conceptual framework
- Veritas Health Innovation. Covidence systematic review software, www.covidence.org.
- Deny S, The Health Foundation
- Kreps GL, 2017, Stud Health Technol Inform, 240, 347
- Murray E, 2012, Med 20, 1, e3
- Norman CD, 2012, Stud Health Technol Inform, 172, 54
- EXPH, Report on Assessing the impact of digital transformation of health services, expert panel on effective ways of investing in health (EXPH)
- Fountain JE, 2004, Prev Chronic Dis, 1, 1
- Heldman MPH AB, 2013, Public Health Rev, 35, 1
- Savel TG, 2012, MMWR Surveill Summ, 61, 20
- UNICEF Health Section Implementation Research and Delivery Science Unit and the Office of Innovation Global Innovation Centre, 2018, UNICEF’s approach to digital health
- Canadian Institutes for Health Research, 2019, AI For public health equity: workshop report
- Kostkova P, Proceedings of the 22nd International Conference on World Wide Web - WWW ‘13 Companion, 687
- Topol, E, 2019, The topol review. Preparing the healthcare workforce to deliver the digital future. An independent report on behalf of the Secretary of State for Health and Social Care
- UNFPA, World Health Organization (WHO), Accelerator discussion paper 6: data and digital health
- Rachadell JJ, 2020, Digital health in 2019. A summary report of the track of digital health at the 12th European Public Health conference 2019 in Marseille
- World Health Organization (WHO), 2018, Digital technologies: shaping the future of primary health care
- World Health Organization (WHO), 2018, Towards a roadmap for the digitalization of national health systems in Europe
- European Commission, Communication from the commission: guidance on apps supporting the fight against COVID-19 pandemic in relation to data protection 2020/C 124 I/01
- European Observatory on Health Systems and Policies & Hamilton, Clayton, Eurohealth, 25
Cited by
Sorted by citations
Erku, D., Khatri, R. B., Endalamaw, A., Wolka, E., Nigatu, F., Zewdie, A., & Assefa, Y. A. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20196854 · Cited by 200
“In addition to comprehensive training for PHC providers, continuous monitoring, updates, and quality assurance mechanisms must be embedded within these digital interventions in order to maximize the benefits of digital tools while minimizing the potential risks [85].”
Abell, B., Naicker, S., Rodwell, D., Donovan, T., Tariq, A., Baysari, M., Blythe, R., Parsons, R., & McPhail, S. M. (2023) · Implementation Science · doi:10.1186/s13012-023-01287-y · Cited by 131
“Ideally, hospital-system and research stakeholders need to identify constructs that have been shown to influence implementation processes and outcomes, understand potential mechanisms of change, and identify potential barriers and facilitators to successful implementation [13, 14].”
BackgroundJolles, M. P., Fort, M. P., & Glasgow, R. E. (2024) · International Journal for Equity in Health · doi:10.1186/s12939-024-02130-6 · Cited by 88
“Most often, complex health-related interventions are implemented in dynamic and diverse contexts [7, 43, 44].”
BackgroundTHE IMPACT OF BIG DATA ON HEALTHCARE PRODUCT DEVELOPMENT: A THEORETICAL AND ANALYTICAL REVIEW
Ogundipe, D. O. (2024) · International Medical Science Research Journal · doi:10.51594/imsrj.v4i3.932 · Cited by 80
Digital Literacy 5.0 to Enhance Multicultural Education
Anurogo, D., Ramba, H. L., Putri, N. D., & Putri, U. M. P. (2023) · Multicultural Islamic Education Review · doi:10.23917/mier.v1i2.3414 · Cited by 103
Metadata
- Authors
- Iyamu, I., Gómez-Ramírez, O., Xu, A. X., Chang, H.-J., Watt, S., Mckee, G., & Gilbert, M.
- Affiliations
- University of British Columbia (CA)
- BC Centre for Disease Control (CA)
- British Columbia Centre for Disease Control, Vancouver, BC, Canada
- Corresponding author
- Gilbert, Mark
- Venue
- DIGITAL HEALTH
- Publisher
- SAGE Publications
- Published
- 2022-01
- Volume
- 8
- Pages
- 205520762211022
- ISSN
- 2055-2076 (ISSN-L)
- PMC
- PMC9152201
- OpenAlex
- W4282924562
- Cited by
- 118
- References
- 147
- Citations by year
- 2026: 23 · 2025: 45 · 2024: 29 · 2023: 20 · 2022: 1
- FWCI
- 4.59
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Digital Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Foundation for Population and Public Health at the British Columbia Center for Disease Control
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Public Health Policies and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Healthcare Systems and Practices
- Keywords
- digital public health, digital health interventions, implementation barriers, health equity, health policy, data infrastructure, workforce capacity, intersectoral collaboration, political commitment, citizen participation, digital integration
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