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Institutional review boards (IRBs) have been criticized for inconsistency and lack of transparency in decision-making, problems that undermine both trust in their ability to protect human research participants and respect for their decisions among researchers. The absence of robust documentation of their decisions and the inability or unwillingness to share those decisions together represent a missed opportunity for IRBs to learn from one another and advance debates about challenging ethical issues. The concept of IRB precedent, modeled upon the system of legal precedent, has been proposed as a potential solution to these problems. In theory, an IRB faced with a review decision could look back at previous IRB decisions, either its own or those of other boards, made in similar studies or circumstances to guide the present decision. Some IRBs attempt this informally within their institution, but few examples of a structured system of IRB precedent have been described in the literature, and none has been widely adopted. This article describes a pilot project to summarize IRB decisions in a way that could facilitate their use as precedent by creating a documentation tool that meets four criteria—comprehensiveness, validity, searchability, and efficiency. Though this process turned out to be more challenging than expected, we identified key features of such a tool that holds promise for future development and could promote more consistent, robust IRB decision-making and advance discourse in human research ethics.

Despite the importance of institutional review boards (IRBs) in protecting human subjects participating in research and the well-known benefits of performance measurements, there has been no systematic assessment of the quality and performance of IRBs. The IRB community has frequently cited the lack of credible metrics for measuring human subject protections and the quality of IRB ethics reviews as reasons for not measuring the quality and performance of IRBs. However, the IRB, with its well-defined missions, functions, structure, and procedures, should be readily amendable to performance measurements. In this brief commentary, I analyzed potential barriers for measuring the quality of IRBs and proposed ways to overcome these barriers.

Single institutional review board (IRB) review of multisite research increased in frequency over a decade ago with a proliferation of master IRB reliance agreements supporting statewide and regional consortia and disease- and population-specific networks. Although successful, the increasing number of agreements presented significant challenges and illuminated potential benefits of a single, nationwide agreement. Anticipated changes in federal regulations highlighted the need to systematize and simplify IRB reliance. To address these challenges, the NIH National Center for Advancing Translational Sciences funded a project to establish a national IRB reliance network that would support national adoption of single IRB (sIRB) review. The Streamlined, Multisite, Accelerated Resources for Trials (SMART) IRB Platform launched in July 2016 to facilitate dissemination, adoption, and implementation of a collaboratively developed master IRB reliance agreement and supportive tools and resources. More than 580 institutions have joined SMART IRB’s Master Common Reciprocal Institutional Review Board Authorization Agreement and begun using the SMART IRB platform to support sIRB arrangements. Here, we describe the tenets of the agreement and operational benefits and challenges of its use. SMART IRB’s early success affirms the utility of collaborative, flexible, and centralized approaches to supporting sIRB review while highlighting the need for further national harmonization.

Performance measurement leads to quality improvement, because performance measurement can identify areas of vulnerability to guide quality improvement activities. Recommendations from empirical institutional review board (IRB) performance measurement data on research approval criteria, expedited review protocols, exempt protocols, and IRB continuing review requirements published over the past 10 years are reviewed here to improve the quality and efficiency of IRBs. Implementation of these recommendations should result in improvements that can be evaluated by follow-up performance measurements.

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.

Tribal Institutional Review Boards (TIRBs) in the United States assert their rights within sovereign nations by developing ethical research processes that align with tribal values to protect indigenous knowledge systems and their community from cultural appropriation, exploitation, misuse, and harm. We reviewed six TIRB applications and processes to gain a better understanding about their requirements and research ethics. We located 48 activated and deactivated TIRBs in a database, mapped them in relation to tribal reservation lands, and then conducted in-depth content analysis. Our analysis demonstrates the importance of building relationships, becoming fully acquainted with the TIRB's operating environment before seeking research approval, and issues related to tribal data management practices.

The parallel rise of pervasive data collection platforms and computational methods for collecting, analyzing, and drawing inferences from large quantities of user data has advanced social computing research, investigating digital traces to understand mediated behaviors of individuals, groups, and societies. At the same time, methods employed to access these data have raised questions about ethical research practices. This article provides insights into U.S. institutional review boards’ (IRBs) attitudes and practices regulating social computing research. Through descriptive and inferential analysis of survey data from staff at 59 IRBs at research universities, we examine how IRBs evaluate the growing variety of studies using pervasive digital data. Findings unpack the difficulties IRB staff face evaluating increasingly technical research proposals while highlighting the belief in their ability to surmount these difficulties. They also indicate a lack of consensus among IRB staff about what should be reviewed and a willingness to work closely with researchers.

   With the rise in obesity and bariatric procedures worldwide, there has been a surge in new and innovative procedures that has been increasingly offered to patients. In this position statement, IFSO highlights the importance of surgical ethics in innovation and when offering new procedures. Furthermore, the task force reviewed the current literature to describe which procedures can be offered as mainstream outside research protocols versus those that are still investigational and need further data.

Undergraduate research as a high-impact practice demonstrates many positive benefits for students, but little research has delved into the impact of ethical training for research, in particular submitting Institutional Review Board (IRB) protocols to determine if the study meets ethical standards for the treatment of human subjects. This study explored if students in two experimental and one nonexperimental research methods class benefited from increased knowledge of research ethics and how to apply them in daily-life situations if they participated in various aspects of IRB protocol procedures either as part of a class-based research project or by completing an IRB protocol activity for developing a hypothetical program to help families. Some students in all three classes had previously engaged in a 4-hr online extended training [the Collaborative Institutional Training Initiative (CITI) Program] in research ethics focused on the Belmont Report principles of beneficence, respect, and justice, but not in IRB protocols. Students were given a pre- and posttest to assess knowledge in both research and daily-life settings for applying the Belmont Report research ethics principles. Results indicate students gained greater knowledge of research ethics when they completed IRB protocol training during a class-based undergraduate research or program-design project, even if they had already completed some extended case-based training in the CITI Program. Results are discussed in terms of the value of using modified IRB protocol approaches as a high-impact practice to teach ethics in research and daily life to students.

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.