The five pillars of computational reproducibility: bioinformatics and beyond.

Computational reproducibility is a simple premise in theory, but is difficult to achieve in practice. Building upon past efforts and proposals to maximize reproducibility and rigor in bioinformatics, we present a framework called the five pillars of reproducible computational research. These include (1) literate programming, (2) code version control and sharing, (3) compute environment control, (4) persistent data sharing and (5) documentation. These practices will ensure that computational research work can be reproduced quickly and easily, long into the future. This guide is designed for bioinformatics data analysts and bioinformaticians in training, but should be relevant to other domains of study.

Eight characteristics of rigorous multilevel implementation research: a step-by-step guide.

BACKGROUND: Although healthcare is delivered in inherently multilevel contexts, implementation science has no widely endorsed methodological standards defining the characteristics of rigorous, multilevel implementation research. We identify and describe eight characteristics of high-quality, multilevel implementation research to encourage discussion, spur debate, and guide decision-making around study design and methodological issues. RECOMMENDATIONS: Implementation researchers who conduct rigorous multilevel implementation research demonstrate the following eight characteristics. First, they map and operationalize the specific multilevel context for defined populations and settings. Second, they define and state the level of each construct under study. Third, they describe how constructs relate to each other within and across levels. Fourth, they specify the temporal scope of each phenomenon at each relevant level. Fifth, they align measurement choices and construction of analytic variables with the levels of theories selected (and hypotheses generated, if applicable). Sixth, they use a sampling strategy consistent with the selected theories or research objectives and sufficiently large and variable to examine relationships at requisite levels. Seventh, they align analytic approaches with the chosen theories (and hypotheses, if applicable), ensuring that they account for measurement dependencies and nested data structures. Eighth, they ensure inferences are made at the appropriate level. To guide implementation researchers and encourage debate, we present the rationale for each characteristic, actionable recommendations for operationalizing the characteristics in implementation research, a range of examples, and references to make the characteristics more usable. Our recommendations apply to all types of multilevel implementation study designs and approaches, including randomized trials, quantitative and qualitative observational studies, and mixed methods. CONCLUSION: These eight characteristics provide benchmarks for evaluating the quality and replicability of multilevel implementation research and promote a common language and reference points. This, in turn, facilitates knowledge generation across diverse multilevel settings and ensures that implementation research is consistent with (and appropriately leverages) what has already been learned in allied multilevel sciences. When a shared and integrated description of what constitutes rigor is defined and broadly communicated, implementation science is better positioned to innovate both methodologically and theoretically.

Guidelines for the Assessment of Efficacy of Clinical Hypnosis Applications.

Research on the efficacy of hypnosis applications continues to grow, but there remain major gaps between the science and clinical practice. One challenge has been a lack of consensus on which applications of hypnosis are efficacious based on research evidence. In 2018, 6 major hypnosis organizations collaborated to form the Task Force for Establishing Efficacy Standards for Clinical Hypnosis. This paper describes a Guideline for the Assessment of Efficacy of Clinical Hypnosis Applications developed by the Task Force, which makes 10 specific recommendations. The guideline is intended to be a tool for those who want to assess the quality of existing evidence on the efficacy of clinical hypnosis for any particular indication. The paper also discusses methodological issues in the interpretation and implementation of these guidelines. Future papers will report on the other products of the Hypnosis Efficacy Task Force, such as best practice recommendations for outcomes research in hypnosis and an international survey of researchers and clinicians on current practice and attitudes about hypnosis.