Evaluating the Quality of Research Ethics Review and Oversight: A Systematic Analysis of Quality Assessment Instruments

Lynch, Holly Fernandez; Abdirisak, Mohamed; Bogia, Megan; Clapp, Justin T.

doi:10.1080/23294515.2020.1798563

Cited by 13 publications

(10 citation statements)

References 24 publications

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“…RECs’ diverging interpretations may result in disharmonious evaluations and decisions across committees, which could negatively affect researchers’ trust in the oversight system, data sharing practices, and research collaborations ( Ballantyne & Schaefer, 2020 ; Dove & Garattini, 2018 ; van den Hoonaard & Hamilton, 2016 ). Although a lack of transparency about evaluation procedures and inconsistencies across RECs’ judgments are not exclusive to big data research ( Lynch et al, 2020 ), our findings show that these limitations in REC practices continue to hamper research.…”

Section: Discussionmentioning

confidence: 79%

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Ferretti

Ienca

Velarde

et al. 2021

Journal of Empirical Research on Human Research Ethics

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Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological novelty, and limited auditability of these approaches. To better understand the challenges facing RECs, we explored the perspectives and attitudes of the members of the seven Swiss Cantonal RECs via semi-structured qualitative interviews. Our interviews reveal limited experience among REC members with the review of big data research, insufficient expertise in data science, and uncertainty about how to mitigate big data research risks. Nonetheless, RECs could strengthen their oversight by training in data science and big data ethics, complementing their role with external experts and ad hoc boards, and introducing precise shared practices.

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Section: Discussionmentioning

confidence: 79%

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Ferretti

Ienca

Velarde

et al. 2021

Journal of Empirical Research on Human Research Ethics

View full text Add to dashboard Cite

show abstract

“…The wide range of big data research could exacerbate this existing issue. Having more research to assess and less time to accomplish the task may negatively impact the quality of the ERC's output, as well as increase the time needed for review [66]. Consequently, researchers might carry out potentially risky studies because the relevant ethical issues of those studies were overlooked.…”

Section: Persistent Weaknessesmentioning

confidence: 99%

Ethics review of big data research: What should stay and what should be reformed?

et al. 2021

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Background Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts. Main text In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC’s scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC’s way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science. Conclusions We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.

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“…Relevant manuals of ethics along with ethics protocols of the study have been provisioned from the beginning of this study in the line of core values as Ethics by design and Ethics by default. However, apart from these minimum requirements, and the alignment with international guidelines and codes of conduct such as Ethical Guidelines for Health-related Research Involving Humans (World Health Organization) 7 and Standards and Operational Guidance for Ethics Review of Health-Related Research with Human Participants [66], more demanding issues emerged according to data processing of ageing workers' workability through adaptive personalized ICT tools.…”

Section: The Smartframework Use Casementioning

confidence: 99%

Smart Workplaces for older adults: coping ‘ethically’ with technology pervasiveness

Segkouli

Giakoumis

Votis

et al. 2021

Univ Access Inf Soc

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Pervasive technologies such as Artificial Intelligence, Virtual Reality and the Internet of Things, despite their great potential for improved workability and well-being of older workers, entail wide ethical concerns. Aligned with these considerations we emphasize the need to present from the viewpoint of ethics the risks of personalized ICT solutions that aim to remedy health and support the well-being of the ageing population at workplaces. The ethical boundaries of digital technologies are opaque. The main motivation is to cope with the uncertainties of workplaces' digitization and develop an ethics framework, termed SmartFrameWorK, for personalized health support through ICT tools at workplace environments. SmartFrameWorK is built upon a five-dimensional approach of ethics norms: autonomy, privacy, transparency, trustworthiness and accountability to incite trust in digital workplace technologies. A typology underpins these principles and guides the ethical decision-making process with regard to older worker particular needs, context, data type-related risks and digital tools' use throughout their lifecycle. Risk analysis of pervasive technology use and multimodal data collection, highlighted the imperative for ethically aware practices for older workers' activity and behaviour monitoring. The SmartFrameWorK methodology has been applied in a case study to provide evidence that personalized digital services could elicit trust in users through a well-defined framework. Ethics compliance is a dynamic process from participants' engagement to data management. Defining ethical determinants is pivotal towards building trust and reinforcing better workability and well-being in older workers.

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Evaluating the Quality of Research Ethics Review and Oversight: A Systematic Analysis of Quality Assessment Instruments

Cited by 13 publications

References 24 publications

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Ethics review of big data research: What should stay and what should be reformed?

Smart Workplaces for older adults: coping ‘ethically’ with technology pervasiveness

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