Big Data in Children’s Healthcare Research Wins Conditional Support from Underrepresented Groups

Big data has transformed how modern medicine discovers disease patterns, predicts health risks, and tailors treatments to individual patients. Yet the enormous datasets that power these advances are built from the health records of real people, and the voices of those least often asked about the trade-offs are frequently the ones with the most at stake. Children and young people, along with other underserved communities, have historically been sidelined in biomedical research, both as participants and as decision-makers. A new systematic review published in PLOS Digital Health offers the most comprehensive picture to date of how these groups actually feel about their data being used in paediatric healthcare research, and the answer is more nuanced than a simple yes or no.

The research team, led by investigators including Charlotte Burdge and Anna Moore, conducted a mixed-methods systematic review that searched seven major bibliographic databases: ASSIA, CINAHL, EMBASE, MEDLINE, PsycINFO, Scopus, and Web of Science, supplemented by grey literature sources. Their goal was to capture the perceptions, attitudes, and concerns of children and young people, particularly those from underserved groups, as well as parents and carers who often act as proxy decision-makers for minors. According to the authors, this is the first review to systematically examine these perspectives specifically in the context of big data in paediatric healthcare research, a gap that has grown more urgent as data-driven approaches reshape everything from vaccine safety monitoring to mental health prediction.

After screening the literature, the team included seventeen studies representing the views of 6,261 participants. Of these, at least 4,710 were children and young people and 1,443 were parents or carers, with one study not reporting participant numbers separately by group. Study quality was assessed using the Mixed Methods Appraisal Tool, a validated instrument for evaluating the methodological rigour of qualitative, quantitative, and mixed-methods research. Findings were then integrated through narrative synthesis, a technique that allows researchers to combine insights from heterogeneous study designs without forcing them into a statistical meta-analysis. This methodological care matters because the included studies spanned diverse populations, data types, and research questions, and the review’s conclusions rest on how faithfully those individual studies captured participant voices.

The headline finding is that underrepresented groups express broadly favourable, but distinctly conditional, support for big data approaches in paediatric healthcare research. This is not blanket approval, nor is it reflexive rejection. Instead, participants across the included studies weighed the promise of data-driven medicine against concrete risks they could articulate with striking clarity. Willingness to share data was shaped by participant characteristics, lived experience, and, perhaps most powerfully, trust in the institutions asking for that data. For communities that have experienced discrimination or exclusion from healthcare systems, trust is not an abstract consideration; it is the gatekeeper that determines whether consent feels meaningful or coerced.

What motivated participants to support data sharing was remarkably consistent across studies. Perceived benefits included societal and public health gains, the opportunity to empower others who share similar experiences, and the advancement of scientific progress. For young people living with chronic conditions or mental health challenges, the idea that their data could help future patients like themselves transformed an abstract privacy calculation into a concrete act of solidarity. Parents and carers, meanwhile, often weighed their protective instincts against the possibility that research using their children’s data could spare other families the hardships they had endured. This altruistic dimension of data sharing, the review suggests, is a resource that researchers and policymakers have underused when designing consent processes and public engagement campaigns.

Against these benefits, participants raised concerns that clustered around several recurring themes. Privacy was paramount, particularly the risk of re-identification, in which supposedly anonymised data can be linked back to individuals through combinations of seemingly harmless details. Participants also worried about data misuse, commercial exploitation by technology companies or pharmaceutical firms, and limited transparency in how data governance decisions are made. These are not vague anxieties but technically informed objections. Re-identification risk is a genuine scientific problem, demonstrated repeatedly in studies showing that individuals can be singled out from anonymised datasets using combinations of birth date, postcode, and other quasi-identifiers. The fact that young people and their carers independently flagged this issue suggests a public understanding of data science that is more sophisticated than many consent frameworks assume.

The conditions participants attached to their support form perhaps the most actionable part of the review. Acceptable data use, in their view, required robust anonymisation, independent ethical oversight, and developmentally appropriate consent processes. That last condition deserves particular attention. Standard consent forms are typically written for adults with high health literacy, and they rarely account for the cognitive and emotional development of adolescents who may be legally able to consent to some aspects of research participation while still relying on carers for others. Developmentally appropriate consent means designing information flows that match a young person’s capacity to understand what is being shared, with whom, and for what purpose. It also means recognising that parents and carers, while legally responsible, do not always speak for their children’s interests, and that young people themselves want a voice in decisions about their own data.

The review’s implications extend beyond paediatrics. As health systems worldwide digitise records and research consortia aggregate data across borders, the governance frameworks being built today will determine whether data-driven medicine narrows or widens existing health inequities. The authors argue that embedding inclusive governance practices and engaging underrepresented communities in research design will be essential to ensuring that data-driven paediatric research is both ethical and equitable. In practical terms, this could mean involving young people and carers in drafting data access policies, creating accessible summaries of how datasets are used, and establishing independent oversight bodies with community representation. The alternative, treating consent as a one-time legal formality, risks reproducing the very exclusions the review documents.

There are limits worth noting. Seventeen studies and roughly six thousand participants is a meaningful evidence base, but the populations captured in the included research may not represent the full diversity of underserved groups, and narrative synthesis, while flexible, cannot quantify the strength of particular concerns across studies. The review also reflects the state of the literature up to its search date, and public attitudes toward data sharing have been shown to shift with news events, policy changes, and personal experience. Still, the consistency of the core findings, conditional support contingent on trust, transparency, and genuine choice, gives the conclusions considerable weight.

What emerges from this review is a clear message for the research community: the public, including its youngest and most marginalised members, is not asking researchers to abandon big data. They are asking to be trusted with the truth about how their information is used, protected by systems they can verify, and included in the decisions that shape research on their own lives. Meeting those conditions is not a bureaucratic hurdle but the foundation on which the next generation of data-driven paediatric medicine will either earn its social licence or lose it. As health data becomes one of the most valuable resources in science, the groups this review centres on have made it clear that their support is available, but only on terms they can understand and endorse.

Subject of Research: Public perceptions of big data use in children and young people's healthcare research

Article Title: Perceptions, attitudes, and concerns of underrepresented groups regarding the use of big data in children and young people’s healthcare research – A systematic literature review

Article References: Burdge, C., Burn, A.-M., Zhang, L., Menon, S., Kaminska, K., Wallace-Hanlon, S., Fischer, M., Evans, C., Fonagy, P., Wiedemann, A., Young, J., Moore, A., & Anderson, J. K. (2026). Perceptions, attitudes, and concerns of underrepresented groups regarding the use of big data in children and young people’s healthcare research – A systematic literature review. PLOS Digital Health, 5(10), e0001434. https://doi.org/10.1371/journal.pdig.0001434

Image Credits: AI Generated

DOI: 10.1371/journal.pdig.0001434

Keywords: big data, paediatric healthcare, systematic review, data privacy, informed consent, health equity, underrepresented groups, data governance, children and young people, medical research ethics, public attitudes, anonymisation