Returning Individual Research Results to Participants

Downey, Autumn; Busta, Emily R.; Mancher, Michelle; Botkin, Jeffrey R.

doi:10.17226/25094

Cited by 58 publications

(49 citation statements)

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“…In teaching, I demonstrate the importance of this step by having students complete a Data Evaluability Characteristics Worksheet (Table 1). The worksheet includes questions and concepts derived both from research and from materials developed as part of a consensus report on whether and how to return individual-specific test results to research participants (National Academies of Sciences, Engineering, and Medicine, 2018).…”

Section: Identifying Critical Context: the Data Evaluability Charactementioning

confidence: 99%

Helping People Know Whether Measurements Have Good or Bad Implications: Increasing the Evaluability of Health and Science Data Communications

Zikmund‐Fisher

2019

Policy Insights from the Behavioral and Brain Sciences

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Patients, policy makers, and the public have access to many types of health and scientific data relevant to various individual and societal decisions. Yet, these audiences often struggle with the meaning and the potential usefulness of those data, so they may choose not to engage with the data at all. Scientific and health data are generally difficult to interpret, yet presentations often implicitly assume that the recipient has the necessary contextual knowledge to identify the data's meaning. To address this problem, designers of data communications should go beyond considering audience characteristics (e.g., numeracy) and focus more on increasing information evaluability (a concept from the judgment and decision-making literatures). The challenge is understanding which data characteristics guide people's ability to extract meaning from data in a given situation. Prioritizing use-relevant contextual information (e.g., by defining action thresholds, comparison standards, meaningful categories, and/ or significant differences) is the single best thing experts can do to improve data communication effectiveness. Doing so increases the chances that the patient, public, or policy maker audience does not just know what their numbers are but also what they mean.

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Section: Identifying Critical Context: the Data Evaluability Charactementioning

confidence: 99%

Helping People Know Whether Measurements Have Good or Bad Implications: Increasing the Evaluability of Health and Science Data Communications

Zikmund‐Fisher

2019

Policy Insights from the Behavioral and Brain Sciences

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“…On the other hand, a recent NAS report urges researchers to return individual-specific results to participants and to take steps to improve the quality of data to support this activity. 14 Why not view a commitment to designing MICs for clinical use as consistent with this trend in policy? MIC designers must also weigh possible benefits to current patients from a resource tailored to clinical needs against possible benefits to future patients from a resource focused on research.…”

Section: Discussionmentioning

confidence: 99%

What is a Medical Information Commons?

Bollinger¹,

Zuk²,

Majumder³

et al. 2019

J. Law. Med. Ethics

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A 2011 National Academies of Sciences report called for an “Information Commons” and a “Knowledge Network” to revolutionize biomedical research and clinical care. We interviewed 41 expert stakeholders to examine governance, access, data collection, and privacy in the context of a medical information commons. Stakeholders' attitudes about MICs align with the NAS vision of an Information Commons; however, differences of opinion regarding clinical use and access warrant further research to explore policy and technological solutions.

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“…The ethical and legal obligations of researchers to return information of health relevance to participants have received significant attention of late, particularly in genomics research (National Academies of Sciences, Engineering, and Medicine [NASEM], 2018b). The basic ethical principle is that researchers should return analytically valid, clinically valid, and actionable information to participants (Knoppers et al, 2015, p. 556).…”

Section: Capacity Issues In Data-intensive Researchmentioning

confidence: 99%

A Tale of Two Capacities: Including Children and Decisionally Vulnerable Adults in Biomedical Research

2019

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The participation of individuals who lack decision-making capacity is essential for advancing genomics research and neuroscience, but raises ethical and legal challenges relating to vulnerability, consent, and exclusion. Capacity differences between populations and individuals, the dynamics of capacity over time, and evolving legal consent and capacity regimes all raise uncertainty for researchers, institutional review boards, and policy makers. We review international ethical and legal best practices for including children and decisionally vulnerable adults in health research. Research ethics norms and literature tend to split such groups into narrow silos, which results in inconsistency and conceptual confusion, or to lump them together, which fails to take into account morally relevant differences. Through a narrative review of international norms, we identify challenges common to both groups, while drawing out distinctions reflecting their opposite capacity trajectories. Our comparison between these two populations clarifies underlying ethical concepts and offers opportunities for critique. Children need protection to foster their long-term autonomy, while decisionally vulnerable adults need to be provided with support in order to exercise their autonomy. This leads to differences in how researchers determine who lacks capacity, who has authority to consent, and what criteria guide such decision-making. We also consider how capacity issues color contemporary research governance debates over broad consent, data protection compliance, data sharing, and the return of individual research results and incidental findings.

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Returning Individual Research Results to Participants

Cited by 58 publications

References 0 publications

Helping People Know Whether Measurements Have Good or Bad Implications: Increasing the Evaluability of Health and Science Data Communications

Helping People Know Whether Measurements Have Good or Bad Implications: Increasing the Evaluability of Health and Science Data Communications

What is a Medical Information Commons?

A Tale of Two Capacities: Including Children and Decisionally Vulnerable Adults in Biomedical Research

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