When can the Child Speak for Herself? The Limits of Parental Consent in Data Protection Law for Health Research

In safe hands: child health data storage, linkage and consent for use

While there is potential for societal benefit from linkage and integration of large datasets, there are gaps in our understanding of the implications for children and young people, and limited inclusion of their views within this discourse. We aimed to understand the views and expectations of children, young people and their parents/caregivers in Aotearoa New Zealand regarding child health data storage, linkage and consent for use. This qualitative study included 24 Māori and non-Māori children, young people and their families across five focus groups, recruited from a community-based health service. A mixed Māori and non-Māori research team facilitated participant recruitment and data collection. Child, adolescent and parent/caregiver groups were held separately. Sessions were audio-recorded and the verbatim transcripts were analysed thematically. We identified three themes: (i) I am more than a number: seeing patients as people; (ii) In safe hands: data as power; and (iii) What are your intentions with my data? Consent as an active relationship. A key challenge was the reductive and stigmatizing potential of data integration for minoritised groups. Hypothetical discussions of data sharing and linkage were contingent on trust between the participant and the health professional, with negotiated data ownership. Consent was conceived as an active relationship needing renewal and renegotiation as children reached adulthood. Current consent processes for ongoing use of child data require further deliberation. Without a strong ethical and child rights-based approach to issues of child health data management, consent and linkage, we risk exacerbating health inequities and experiences of breach of trust.

Strikes and Gutters: Biomarkers and anthropometric measures for predicting diagnosed diabetes mellitus in adults in low- and middle-income countries

The management of diabetes necessitates the requirement of reliable health indices, specifically biomarkers and anthropometric measures, to detect the presence or absence of the disease. Nevertheless, limited robust empirical evidence exists regarding the optimal metrics for predicting diabetes in adults, particularly within low- and middle-income countries. This study investigates objective and subjective indices for screening diabetes in these countries.

METHODS

Data for this study was sourced from surveys conducted among adults (aged 18 years and above) in seventeen (17) countries. Self-reported diabetes status, fifty-four biomarkers, and twenty-six core and twenty-eight estimated anthropometric indices, including weight, waist circumference, body mass index, glycaemic triglycerides, and fasting blood glucose, were utilised to construct lasso regression models.

RESULTS

The study revealed variances in diabetes prediction outcomes across different countries. Central adiposity measures, fasting plasma glucose and glycaemic triglycerides demonstrated superior predictive capabilities for diabetes when compared to body mass index. Furthermore, fasting plasma or blood glucose, serving as a biomarker, emerged as the most accurate predictor of diabetes.

CONCLUSIONS

These findings offer critical insights into both general and context-specific tools for diabetes screening. The study proposes that fasting plasma glucose and central adiposity indices should be considered as routine screening tools for diabetes, both in policy interventions and clinical practice. By identifying adults with or at higher risk of developing diabetes and implementing appropriate interventions, these screening tools possess the potential to mitigate diabetes-related complications in low- and middle-income countries.

What does the best interests principle of the convention on the rights of the child mean for paediatric healthcare?

The present review analyses the implications of the best interests of the child principle, which is one of the most widely discussed principles of medical ethics and human rights, for paediatric healthcare. As a starting point, it presents the interpretation of the best interests principle by the United Nations Committee on the Rights of the Child. On this basis, it points out possible fields of application of the best interests principle with regard to paediatric healthcare and discusses the potential difficulties in the application of the best interests principle. Based on this, it illustrates the implications of the best interests principle for paediatric healthcare through four case studies, which look at ethical dilemmas in paediatric gynaecology, end-of-life care, HIV care and genetic testing.   Conclusion: The best interests principle requires action, inter alia, by health policymakers, professional associations, hospital managers and medical teams to ensure children receive the best possible healthcare. Whilst the best interests principle does not provide a conclusive solution to all ethical dilemmas in paediatric healthcare (as illustrated by the case studies), it provides children, medical teams, parents and families, and clinical ethicists with an indispensable framework for health care centred on the rights of the child. What is Known: • The best interests principle is one of the most widely discussed principles of medical ethics and human rights and one of the four general principles of the Convention on the Rights of the Child. What is New: • The present review discusses possible fields of application and potential difficulties of the best interests principle with regard to paediatric healthcare. • Based on this, it illustrates the implications of the best interests principle for paediatric healthcare through four case studies, which look at ethical dilemmas in paediatric gynaecology, end-of-life care, HIV care and genetic testing.

Digital Mega-Studies as a New Research Paradigm: Governing the Health Research of the Future

'Digital Mega-Studies' are entirely or extensively digitised, longitudinal, population-scale initiatives, collecting, storing, and making available individual-level research data of different types and from multiple sources, shaped by technological developments and unforeseeable risks over time. The Australian 'Gen V' project exemplifies this new research paradigm. In 2019, we undertook a multidisciplinary, multi-stakeholder process to map Digital Mega-Studies' key characteristics, legal and governance challenges and likely solutions. We conducted large and small group processes within a one-day symposium and directed online synthesis and group prioritisation over subsequent weeks. We present our methods (including elicitation, affinity mapping and prioritisation processes) and findings, proposing six priority governance principles across three areas-data, participation, trust-to support future high-quality, large-scale digital research in health.

Coming Out to Play: Privacy, Data Protection, Children's Health, and COVID-19 Research

The COVID-19 pandemic has underscored the need for new ways of thinking about data protection. This is especially so in the case of health research with children. The responsible use of children's data plays a key role in promoting children's well-being and securing their right to health and to privacy. In this article, we contend that a contextual approach that appropriately balances children's legal and moral rights and interests is needed when thinking about data protection issues with children. We examine three issues in health research through a child-focused lens: consent to data processing, data retention, and data protection impact assessments. We show that these issues present distinctive concerns for children and that the General Data Protection Regulation provides few bright-line rules. We contend that there is an opportunity for creative approaches to children's data protection when child-specific principles, such as the best interests of the child and the child's right to be heard, are put into dialogue with the structure and logic of data protection law.

Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap

Despite the application of advanced statistical and pharmacometric approaches to pediatric trial data, a large pediatric evidence gap still remains. Here, we discuss how to collect more data from children by using real-world data from electronic health records, mobile applications, wearables, and social media. The large datasets collected with these approaches enable and may demand the use of artificial intelligence and machine learning to allow the data to be analyzed for decision making. Applications of this approach are presented, which include the prediction of future clinical complications, medical image analysis, identification of new pediatric end points and biomarkers, the prediction of treatment nonresponders, and the prediction of placebo-responders for trial enrichment. Finally, we discuss how to bring machine learning from science to pediatric clinical practice. We conclude that advantage should be taken of the current opportunities offered by innovations in data science and machine learning to close the pediatric evidence gap.