Caregiver and Youth Characteristics That Influence Trust in Digital Health Platforms in Pediatric Care: Mixed Methods Study
Open accessPublished version of a preprint
Abstract
Background: Combining patient-generated health data and digital health platforms may improve patient experience and population health, mitigate rising health care costs, reduce clinician burnout, and enable health equity. However, lack of trust may be a notable barrier to the data-sharing required by such platforms. Understanding sociodemographic, health, and personal characteristics will enable developers and implementers of such technologies to consider these in their technical design requirements. Objective: This study aims to understand relationships between sociodemographic characteristics of caregivers of children or adolescents and trust in and willingness to use digital platforms to store and share personal health information for clinical care and research. Methods: This study used a mixed methods approach, including surveys of caregivers of youth aged <18 years living in Canada or the United States and youth aged 16 to 17 years living in Canada, as well as web-based bulletin board discussions to further explore topics of trust in data sharing. Sociodemographic and survey data were tabulated and explored using proportional odds ordinal regression models. Comments from web-based group discussions were analyzed thematically using a coding approach to identify issues important to the participants. Results: Survey data from 1128 caregivers (female participants: n=549, 48.7%; 36-50 years old: n=660, 58.5%; Canadian: n=603, 53.5%; urban population: n=494, 43.8%) were collected, of which 685 (60.7%) completed all questions. Data from 173 youth (female participants: n=73, 42.2%; urban population: n=94, 54.3%) were collected, of which 129 (74.6%) completed all questions, and data were available for analysis. Furthermore, among 40 participants, 23 (58%) caregivers contributed to the web-based discussion boards. Related to trust, living in a rural area (vs urban; odds ratio [OR] 0.66, 95% CI 0.46-0.95) resulted in lower concern for data privacy and security, while having an undergraduate (OR 1.82, 95% CI 1.30-2.55) or graduate degree (vs secondary or trade school; OR 2.50, 95% CI 1.68-3.73) resulted in higher levels of concern. Living with a chronic disease (OR 1.81, 95% CI 1.35-2.44) increased levels of concern regarding data privacy and security. Interestingly, those with chronic disease were more willing to use digital platforms for clinical care and share personal health information for not-for-profit research. Caregivers were most concerned about data breaches involving data from their children but also highlighted that digital platforms would allow for better coordination of care for their children. Conclusions: Our research confirms the willingness of caregivers and youth to use digital platforms for both clinical care delivery and research and suggests that the value of a digital platform may outweigh the risks of its use. Engagement of end users in co-designing such platforms has the potential to enhance digital trust. However, digital trust varies across sociodemographic groups; therefore, diverse end user engagement is necessary when designing digital applications.
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
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 design and development of the platform were guided by extensive formative research, including multiple rounds of usability testing with end-users.
“The design and development of the platform were guided by extensive formative research [31,33], including multiple rounds of usability testing (manuscripts in preparation) with end-users (i.e., patients and caregivers living with T1D and their HCP).”
From Caregiver experiences of an integrative patient-centered digital health application for pediatric type 1 diabetes care: Findings from a pilot clinical trial (2025) · cites this paper as [31]
The Discussion (Conclusions and Future Directions; page unavailable) says this study’s caregiver and youth findings will inform the prioritization of TrustSphere’s features and its iterative co-design. The Methods (Data Collection; page unavailable) describe surveys and a discussion board, but the paper does not report multiple rounds of usability testing. The citing sentence attributes that testing to manuscripts in preparation, not specifically to this source. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThe platform was developed using user-centered and participatory design approaches with multiple rounds of iterative user feedback.
“It was developed following a survey conducted with parents and youth (ages 16–17 years) to gain insight into their perspectives on digital trust [31] and to apply user-centered and participatory design approaches during the platform’s development, incorporating multiple rounds of iterative user feedback [32–34].”
From Caregiver experiences of an integrative patient-centered digital health application for pediatric type 1 diabetes care: Findings from a pilot clinical trial (2025) · cites this paper as [31]
The collaboration with end users throughout the platform development process likely contributed to users reporting high usefulness and acceptable usability.
“Our collaboration with end users throughout the platform development process [31,33] likely contributed to users reporting high usefulness and acceptable usability, as this co-creation approach has been recognized as essential for successful digital health technology development [36,37].”
From Caregiver experiences of an integrative patient-centered digital health application for pediatric type 1 diabetes care: Findings from a pilot clinical trial (2025) · cites this paper as [31]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Standards for Reporting Qualitative Research: A Synthesis of Recommendations
O’Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., & Cook, D. A. (2014) · Academic Medicine · doi:10.1097/acm.0000000000000388 · Cited by 12,211 · see citing works
The Triple Aim: Care, Health, And Cost
Berwick, D. M., Nolan, T. W., & Whittington, J. (2008) · Health Affairs · doi:10.1377/hlthaff.27.3.759 · Cited by 5,136 · see citing works
From Triple to Quadruple Aim: Care of the Patient Requires Care of the Provider
Bodenheimer, T., & Sinsky, C. (2014) · The Annals of Family Medicine · doi:10.1370/afm.1713 · Cited by 3,462 · see citing works
A Consensus-Based Checklist for Reporting of Survey Studies (CROSS)
Sharma, A., Minh Duc, N. T., Luu Lam Thang, T., Nam, N. H., Ng, S. J., Abbas, K. S., Huy, N. T., Marušić, A., Paul, C. L., Kwok, J., et al. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-021-06737-1 · Cited by 2,292 · see citing works
Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006) · Psychology and Aging · doi:10.1037/0882-7974.21.2.333 · Cited by 2,113 · see citing works
The Quintuple Aim for Health Care Improvement: A New Imperative to Advance Health Equity
Nundy, S., Cooper, L. A., & Mate, K. S. (2022) · JAMA · doi:10.1001/jama.2021.25181 · Cited by 834 · see citing works
O’Connor, S., Hanlon, P., O’Donnell, C. A., Garcia, S., Glanville, J., & Mair, F. S. (2016) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-016-0359-3 · Cited by 636 · see citing works
A systematic review of barriers to data sharing in public health
van Panhuis, W. G., Paul, P., Emerson, C., Grefenstette, J., Wilder, R., Herbst, A. J., Heymann, D., & Burke, D. S. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-1144 · Cited by 579 · see citing works
The next generation of evidence-based medicine
Subbiah, V. (2023) · Nature Medicine · doi:10.1038/s41591-022-02160-z · Cited by 570 · see citing works
Laffel, L. M., Kanapka, L. G., Beck, R. W., Bergamo, K., Clements, M. A., Criego, A., DeSalvo, D. J., Goland, R., Hood, K., Liljenquist, D., et al. (2020) · JAMA · doi:10.1001/jama.2020.6940 · Cited by 443 · see citing works
Patterson, C., Karuranga, S., Salpea, P., Saeedi, P., Dahlquist, G., Soltész, G., & Ogle, G. (2019) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2019.107842 · Cited by 440 · see citing works
Gordon, N. P., & Hornbrook, M. C. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5105 · Cited by 369 · see citing works
Kelton, K., Fleischmann, K. R., & Wallace, W. A. (2007) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20722 · Cited by 274 · see citing works
Elements of Trust in Digital Health Systems: Scoping Review
Adjekum, A., Blasimme, A., & Vayena, E. (2018) · Journal of Medical Internet Research · doi:10.2196/11254 · Cited by 231 · see citing works
Factors that influence public engagement with eHealth: A literature review
Hardiker, N. R., & Grant, M. J. (2010) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2010.10.017 · Cited by 207 · see citing works
Analysis of Internet Users’ Level of Online Privacy Concerns
O’Neil, D. (2001) · Social Science Computer Review · doi:10.1177/089443930101900103 · Cited by 165 · see citing works
Perspectives of Patients About Artificial Intelligence in Health Care
Khullar, D., Casalino, L. P., Qian, Y., Lu, Y., Krumholz, H. M., & Aneja, S. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.10309 · Cited by 164 · see citing works
van Kessel, R., Hrzic, R., O’Nuallain, E., Weir, E. M., Wong, B. L. H., Anderson, M., Baron‐Cohen, S., & Mossialos, E. A. (2021) · Journal of Medical Internet Research · doi:10.2196/33819 · Cited by 160 · see citing works
Filkins, B. L., Kim, J. Y., Roberts, B., Armstrong, W., Miller, M. A., Hultner, M. L., Castillo, A., Ducom, J. C., Topol, E. J., & Steinhubl, S. R. (2016) · PubMed Central · Cited by 157 · see citing works
Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status
Robbins, R., Krebs, P. M., Jagannathan, R., Jean‐Louis, G., & Duncan, D. T. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.7832 · Cited by 144 · see citing works
A New Privacy Paradox: Young People and Privacy on Social Network SitesPreprint
Blank, G., Bolsover, G., & Dubois, E. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2479938 · Cited by 139 · see citing works
ISPAD Clinical Practice Consensus Guidelines 2022: Diabetes technologies: Glucose monitoring
Tauschmann, M., Forlenza, G. P., Hood, K. K., Cardona‐Hernandez, R., Giani, E., Hendrieckx, C., DeSalvo, D. J., Laffel, L. M., Saboo, B., Wheeler, B. J., et al. (2022) · Pediatric Diabetes · doi:10.1111/pedi.13451 · Cited by 111 · see citing works
What does it mean to trust a health system?
Abelson, J., Miller, F. A., & Giacomini, M. K. (2009) · Health Policy · doi:10.1016/j.healthpol.2008.11.006 · Cited by 106 · see citing works
User‐centered design for technology‐enabled services for eating disorders
Graham, A. K., Wildes, J. E., Reddy, M. C., Munson, S. A., Taylor, C. B., & Mohr, D. C. (2019) · International Journal of Eating Disorders · doi:10.1002/eat.23130 · Cited by 103 · see citing works
Taylor, M. L., Thomas, E. E., Vitangcol, K. J., Marx, W., Campbell, K. L., Caffery, L. J., Haydon, H. M., Smith, A. C., & Kelly, J. T. (2022) · Journal of Telemedicine and Telecare · doi:10.1177/1357633x221119620 · Cited by 96 · see citing works
Nebeker, C., Lagare, T., Takemoto, M., Lewars, B., Crist, K., Bloss, C. S., & Kerr, J. (2016) · Translational Behavioral Medicine · doi:10.1007/s13142-016-0426-4 · Cited by 85 · see citing works
Guendelman, S., Broderick, A., Mlo, H., Gemmill, A., & Lindeman, D. A. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7736 · Cited by 76 · see citing works
Beyond theming: Making qualitative studies matter
Thorne, S. E. (2020) · Nursing Inquiry · doi:10.1111/nin.12343 · Cited by 74 · see citing works
Seltzer, E., Goldshear, J. L., Guntuku, S. C., Grande, D., Asch, D. A., Klinger, E. V., & Merchant, R. M. (2019) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-019-0886-9 · Cited by 69 · see citing works
Digital Health Technologies Enabling Partnerships in Chronic Care Management: Scoping Review
Wannheden, C., Åberg-Wennerholm, M., Dahlberg, M., Revenäs, Å., Tolf, S., Eftimovska, E., & Brommels, M. (2022) · Journal of Medical Internet Research · doi:10.2196/38980 · Cited by 58 · see citing works
What Is Trust? Ethics and Risk Governance in Precision Medicine and Predictive Analytics
Adjekum, A., Ienca, M., & Vayena, E. (2017) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2017.0156 · Cited by 57 · see citing works
Public Attitudes to Digital Health Research Repositories: Cross-sectional International Survey
Vilaza, G. N., Coyle, D., & Bardram, J. E. (2021) · Journal of Medical Internet Research · doi:10.2196/31294 · Cited by 14 · see citing works
Estcourt, S., Epton, J., Epton, T., Vaidya, B., & Daly, M. E. (2016) · Research Involvement and Engagement · doi:10.1186/s40900-016-0050-y · Cited by 13 · see citing works
Altruism: Choices of healthy and chronically ill children
Seagle, H., Jessee, P. O., & Nagy, M. C. (2002) · Early Child Development and Care · doi:10.1080/03004430215097 · Cited by 9 · see citing works
Baffoe-Bonnie, M. S. (2022) · Social Science & Medicine · doi:10.1016/j.socscimed.2022.115353 · Cited by 8 · see citing works
Barriers to Successful Health Information Exchange Systems in Canada and the USA
Almoaber, B., & Amyot, D. J. (2016) · International Journal of Healthcare Information Systems and Informatics · doi:10.4018/ijhisi.2017010104 · Cited by 6 · see citing works
Growing Use and Confidence in Artificial Intelligence for Care Delivery
Gordon, W. J. (2022) · NEJM Catalyst · doi:10.1056/cat.22.0095 · Cited by 4 · see citing works
Mikles, S. P., Snyder, L. E., Kientz, J. A., & Turner, A. M. (2020) · PubMed Central · Cited by 1 · see citing works
Flagged first, then by citations
1 of the 39 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Du, Y., Fan, J.-Y., Liu, G.-Z., Yang, Z., Lei, Y., & Guo, Y. (2025) · JMIR mhealth and uhealth · doi:10.2196/73903 · Cited by 4 · see citing works
Fang, H., Xian, R., Li, J., Li, Y., Liu, E., Zhao, Y., & Hu, Y. (2024) · Journal of Medical Internet Research · doi:10.2196/60324 · Cited by 3 · see citing works
Sezgın, E., Jackson, D., Hussain, S.-A., Kocaballi, A. B., Richardson, C., Skeens, M. A., Fosler‐Lussier, E., Ewing, A. P., Donneyong, M. M., & Pai, A. L. H. (2026) · PLOS Digital Health · doi:10.1101/2025.06.16.25329054 · Cited by 3 · see citing works
What are patient perspectives on privacy and trust in digital genomic tools? A qualitative study
Jha, V., Saeedi, S., Clausen, M., Assamad, D., Grewal, S. K., Hirjikaka, D., Lee, W., Luca, S., Shaw, A., Hayeems, R. Z., et al. (2025) · Journal of Genetic Counseling · doi:10.1002/jgc4.70025 · Cited by 2 · see citing works
Down the Digital Delta: Health Information Inequities Among Rural Mississippi Caregivers
Nadorff, D. K., Anreddy, S., Sergi, K., Ahonle, Z. J., Stouffer, C., Hemphill, T., & Buys, D. R. (2025) · Healthcare · doi:10.3390/healthcare13182361 · Cited by 2 · see citing works
Amed, S., Pinkney, S., Abdulhussein, F. S., Virani, A., Zachariuk, C., Tamana, S. K., Muralidharan, S., Görges, M., Barrett, B., van Rooij, T., et al. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000861 · Cited by 1 · see citing works
Self-citationAbrishami, M., Bayat, M., & Some, E. S. (2025) · JMIR Perioperative Medicine · doi:10.2196/75899
Bridging the gaps in Universal Health Coverage using Digital Health Citizenship
Jain, R., & Dasgupta, R. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000913
Marca, V. L., Chatty, T., Tandon, A. A., & Drummond, C. K. (2026) · Computers · doi:10.3390/computers15020109
Cahyati, P., Ihsan, M., & Sasmita, E. (2025) · Jurnal Ilmu Kesehatan Nusantara · doi:10.67963/jiken.v2i2.68
IODINE SUPPLEMENTATION IN CHILDHOOD: PREVENTING THYROID DISORDERS IN THE ERA OF PRECISION MEDICINE
Porwolik, A., Porwolik, H., Szydłowski, R., Cyran, P., & Bodera, M. (2026) · International Journal of Innovative Technologies in Social Science · doi:10.31435/ijitss.2(50).2026.5466
Bladt, L., Bael, A. M., Segers, N., Moerloose, K. D., Klockaerts, K., Florin, H.-J., Campenhout, L. D. E. V., Wachter, S. D., Vermandel, A., Baets, K. D., et al. (2026) · Frontiers in Pediatrics · doi:10.3389/fped.2026.1959698
- Authors
- Chow, E., Virani, A., Pinkney, S., Abdulhussein, F. S., van Rooij, T., Görges, M., Wasserman, W., Bone, J., Longstaff, H., & Amed, S.
- Affiliations
- University of British Columbia (CA)
- BC Children's Hospital Research Institute (CA)
- BC Children's Hospital (CA)
- Provincial Health Services Authority (CA)
- Corresponding author
- Amed, Shazhan
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2024-10-28
- Volume
- 26
- Pages
- e53657
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC11555442
- OpenAlex
- W4403817026
- Cited by
- 12
- References
- 39
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 1
- FWCI
- 3.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Children's Hospital Foundation
- BC Children's Hospital
- Michael Smith Health Research BC
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Keywords
- pediatric care, caregivers, adolescents, youth, patient-generated health data, health data sharing, data privacy and security, sociodemographic factors, urban-rural differences, chronic disease, health literacy, health equity, health information technology adoption, research data sharing, clinician burnout, health care costs, patient experience
- MeSH terms
- Digital Health, Adolescent, Adult, Canada, Child, Female, Humans, Male, Middle Aged, Pediatrics, Surveys and Questionnaires, United States, Caregivers, Information Dissemination, Trust
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