IRB Decision‐Making about Minimal Risk Research with Pregnant Participants

2021 ◽  
Vol 43 (5) ◽  
pp. 2-17
Author(s):  
Amina White ◽  
Christine Grady ◽  
Margaret Little ◽  
Kristen Sullivan ◽  
Katie Clark ◽  
...  
Keyword(s):  
Decision Making ◽  
Minimal Risk ◽  
Risk Research

scholarly journals Review: necessary for protection even in minimal-risk research

Nature ◽  
2009 ◽  
Vol 458 (7237) ◽  
pp. 404-404
Author(s):  
David B. Resnik
Keyword(s):  
Minimal Risk ◽  
Risk Research

scholarly journals Systematic review of clinician-directed nudges in healthcare contexts

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e048801
Author(s):  
Briana S Last ◽  
Alison M Buttenheim ◽  
Carter E Timon ◽  
Nandita Mitra ◽  
Rinad S Beidas
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Assessment Tool ◽  
Risk Of Bias ◽  
Minimal Risk ◽  
Clinical Decisions ◽  
Snowball Sampling ◽  
Healthcare Settings ◽  
Default Options

ObjectiveNudges are interventions that alter the way options are presented, enabling individuals to more easily select the best option. Health systems and researchers have tested nudges to shape clinician decision-making with the aim of improving healthcare service delivery. We aimed to systematically study the use and effectiveness of nudges designed to improve clinicians’ decisions in healthcare settings.DesignA systematic review was conducted to collect and consolidate results from studies testing nudges and to determine whether nudges directed at improving clinical decisions in healthcare settings across clinician types were effective. We systematically searched seven databases (EBSCO MegaFILE, EconLit, Embase, PsycINFO, PubMed, Scopus and Web of Science) and used a snowball sampling technique to identify peer-reviewed published studies available between 1 January 1984 and 22 April 2020. Eligible studies were critically appraised and narratively synthesised. We categorised nudges according to a taxonomy derived from the Nuffield Council on Bioethics. Included studies were appraised using the Cochrane Risk of Bias Assessment Tool.ResultsWe screened 3608 studies and 39 studies met our criteria. The majority of the studies (90%) were conducted in the USA and 36% were randomised controlled trials. The most commonly studied nudge intervention (46%) framed information for clinicians, often through peer comparison feedback. Nudges that guided clinical decisions through default options or by enabling choice were also frequently studied (31%). Information framing, default and enabling choice nudges showed promise, whereas the effectiveness of other nudge types was mixed. Given the inclusion of non-experimental designs, only a small portion of studies were at minimal risk of bias (33%) across all Cochrane criteria.ConclusionsNudges that frame information, change default options or enable choice are frequently studied and show promise in improving clinical decision-making. Future work should examine how nudges compare to non-nudge interventions (eg, policy interventions) in improving healthcare.

scholarly journals Expert Perspectives on Oversight for Unregulated mHealth Research: Empirical Data and Commentary

2020 ◽  
Vol 48 (S1) ◽  
pp. 138-146 ◽  
Author(s):  
Laura M. Beskow ◽  
Catherine M. Hammack-Aviran ◽  
Kathleen M. Brelsford ◽  
P. Pearl O'Rourke
Keyword(s):  
Empirical Data ◽  
Qualitative Interviews ◽  
Ethical Conduct ◽  
Evidence Based ◽  
Minimal Risk ◽  
Diverse Group ◽  
Research Risks ◽  
Risk Research ◽  
Current Systems

In qualitative interviews with a diverse group of experts, the vast majority believed unregulated researchers should seek out independent oversight. Reasons included the need for objectivity, protecting app users from research risks, and consistency in standards for the ethical conduct of research. Concerns included burdening minimal risk research and limitations in current systems of oversight. Literature and analysis supports the use of IRBs even when not required by regulations, and the need for evidence-based improvements in IRB processes.

Attribute Reduction Algorithm on Balancing Profit and Risk

2013 ◽  
Vol 411-414 ◽  
pp. 1919-1922 ◽  
Author(s):  
De Xing Wang ◽  
Jie Long Xu ◽  
Yun Zhang
Keyword(s):  
Decision Making ◽  
Heuristic Search ◽  
Social Life ◽  
Search Algorithm ◽  
Attribute Reduction ◽  
Theoretic Model ◽  
Minimal Risk ◽  
Economic Activities ◽  
Heuristic Search Algorithm ◽  
Maximal Profit

Usually it is taken grant that we achieve the maximal profit and the minimal risk in industry, agriculture, economic activities and social life. It is an important problem in a decision-making process on how to balance profit and risk and find out practical decision-making ways. This paper builds a decision-theoretic model which can balance profit and risk and provide a heuristic search algorithm of the attribute reduction. This algorithm takes the profit and cost as the heuristic function and outputs an optimal attribute set. At last, the example shows that the proposed algorithm is correct and efficient.

scholarly journals Personalized Law and Fundamental Rights

2020 ◽  
Vol 1 (4) ◽  
pp. 56-73
Author(s):  
Tembot Z. Misostishkhov
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Legal Education ◽  
Fundamental Rights ◽  
Legal Positivism ◽  
Decision Making Process ◽  
Minimal Risk ◽  
Legal Norms ◽  
The Public

In recent years, scholars have focused increased attention on the idea of personalized law. It suggests the creation and enforcement of individualized legal norms based on the algorithmic processing of data in the similar manner companies personalize their services using Big Data tools. The article aims to define the role and position of personalized law and to evaluate the risks and consequences of personalization in the context of the emerging digital economy. The research analyses the theoretical grounds of personalized law and justifies its interpretation from the perspective of Hart’s legal positivism striking a balance between the sociological facticity of law and normativism. The study reveals the content, essential features of personalized law and defines its concept. The author analyses the correlation of personalized law with fundamental rights, thus evaluating the risks and consequences of personalization. Particularly, the errors of the approximation of a person’s actual will could occur as part of algorithmic decision-making thereby resulting in discrimination. It appears reasonable that at the beginning, algorithmic personalization should cover only those domains which have the minimal risk of the violation of fundamental norms and of intrusion into the field of social debates. The study underscores, that the transparency of the public sector and of the data-based algorithmic decision-making process is crucial in the context of personalized law, but nevertheless could debase its idea due to opportunistic practices. The issues identified during the research lead one to suggest that professionals who have both legal education and expertise in computer sciences would be in demand in the future. Such professionals could perform the role of independent experts and neutral authority monitoring compliance with data subject’s rights.

scholarly journals Conditional Recommendations for Specific Dietary Ingredients as an Approach to Chronic Musculoskeletal Pain: Evidence-Based Decision Aid for Health Care Providers, Participants, and Policy Makers

Pain Medicine ◽  
2019 ◽  
Vol 20 (7) ◽  
pp. 1430-1448 ◽  
Author(s):  
Courtney Boyd ◽  
Cindy Crawford ◽  
Kevin Berry ◽  
Patricia Deuster ◽  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Musculoskeletal Pain ◽  
Health Care Providers ◽  
Self Care ◽  
Chronic Musculoskeletal Pain ◽  
Sufficient Evidence ◽  
Evidence Based ◽  
Minimal Risk ◽  
Care Providers

Abstract Objective Approximately 55–76% of Service members use dietary supplements for various reasons; although such use has become popular for a wide range of pain conditions, decisions to use supplements are often driven by information that is not evidence-based. This work evaluates whether the current research on dietary ingredients for chronic musculoskeletal pain provides sufficient evidence to inform decisions for practice and self-care, specifically for Special Operations Forces personnel. Methods A steering committee convened to develop research questions and factors required for decision-making. Key databases were searched through August 2016. Eligible systematic reviews and randomized controlled trials were assessed for methodological quality. Meta-analysis was applied where feasible. GRADE was used to determine confidence in the effect estimates. A decision table was constructed to make evidence-informed judgments across factors required for decision-making, and recommendations were made for practice and self-care use. Results Nineteen dietary ingredients were included. Conditional evidence-based recommendations were made for the use of avocado soybean unsaponifiables, capsaicin, curcuma, ginger, glucosamine, melatonin, polyunsaturated fatty acids, and vitamin D. In these cases, desirable effects outweighed undesirable effects, but there was uncertainty about the trade-offs, either because the evidence was low quality or because benefits and downsides were closely balanced. Conclusions The evidence showed that certain dietary ingredients, when taken as part of a balanced diet and/or as a supplement (e.g., pill, tablet, capsule, cream), may alleviate musculoskeletal pain with no to minimal risk of harm. This finding emphasizes and reinforces the critical importance of shared decision-making between Operators and their health care providers.

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