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\"Lenny gets jealous when Mike makes the school baseball team, but together they and Other Mike stumble upon a stealing signals scandal that could go further up than anyone knows\"-- Provided by publisher.
Book
Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0
Improving the reproducibility of biomedical research is a major challenge. Transparent and accurate reporting is vital to this process; it allows readers to assess the reliability of the findings and repeat or build upon the work of other researchers. The ARRIVE guidelines (Animal Research: Reporting In Vivo Experiments) were developed in 2010 to help authors and journals identify the minimum information necessary to report in publications describing in vivo experiments. Despite widespread endorsement by the scientific community, the impact of ARRIVE on the transparency of reporting in animal research publications has been limited. We have revised the ARRIVE guidelines to update them and facilitate their use in practice. The revised guidelines are published alongside this paper. This explanation and elaboration document was developed as part of the revision. It provides further information about each of the 21 items in ARRIVE 2.0, including the rationale and supporting evidence for their inclusion in the guidelines, elaboration of details to report, and examples of good reporting from the published literature. This document also covers advice and best practice in the design and conduct of animal studies to support researchers in improving standards from the start of the experimental design process through to publication.
Journal Article
An Overview of Intellectual Disability: Definition, Diagnosis, Classification, and Systems of Supports (12th ed.)
The American Association on Intellectual and Developmental Disabilities (AAIDD) has published terminology and classification manuals since 1921. Their goals over the last 100 years have been consistent: To fulfill the Association's continued responsibility to be the primary repository of intellectual disability-related research and best practices; to publish a scientific definition of intellectual disability (ID) and its assumptions based on research and one that provides a long, stable definitional history; to provide a singular focus on ID and the lives of people with ID and their families; and to communicate professional standards, ethics, and best practices regarding diagnosis, classification, and planning supports. Consistent with these historical goals, the goals of the 12th edition of the AAIDD manual (Schalock et al. 2021) are to: (a) integrate material published in the 11th edition (Schalock et al., 2010) of the AAIDD manual with post-2010 developments and historical markers; (b) develop a user-friendly manual that combines the theoretical and conceptual thoroughness of a manual with the practical aspects of a user's guide; (c) describe a systematic approach to the diagnosis, optional subgroup classification, and planning of supports for people with intellectual disability based on conceptual models, a clear rationale and purpose, and evidence-based practices; (d) combine current empirical knowledge and best practices into an integrative approach to intellectual disability; and (e) provide practice guidelines that frame best practices, increase understanding, and facilitate precise, valid, and effective decisions, recommendations, and actions. The content of the 12th edition reflects the transformation that is occurring in the field of ID. This transformation, which is occurring to various degrees internationally, is characterized by using precise terminology, incorporating a functional and holistic approach to ID, embracing the supports model and evidence-based practices, implementing outcome evaluation, empowering individuals and families, understanding better the multidimensional properties of context, and incorporating an explicit notion of professional responsibility (Schalock et al., in press). As a result of this transformation, the manual contains both modifications of previous concepts and terminology, and the addition of new terms and concepts. These modifications and additions are reflected in the definition of intellectual disability, the evidence-based approach to diagnosis and optional postdiagnosis subgroup classification, the operationalization of systems of supports, and the incorporation of an integrative approach to ID. Throughout the manual, human functioning is viewed from a systems perspective towards understanding human functioning, which includes human functioning dimensions, interactive systems of supports, and human functioning outcomes.
Journal Article
Closing the Productivity Gap: Improving Worker Productivity Through Public Relative Performance Feedback and Validation of Best Practices
Public relative performance feedback (RPF) on an individual worker’s productivity metrics is used in various organizations with the hopes of improving worker productivity, but its effects are not well understood. We examine whether public RPF could be leveraged to facilitate adoption of best practices in an organization by enabling the validation of best practices shared by identifiable top performers. We use data from two emergency departments, both of which shared best practices for improving productivity and one of which changed from privately to publicly disclosing RPF to physicians. The public disclosure of RPF allowed workers to identify their top-performing coworkers, which in turn enabled the identification and validation of best practices within the work group. We find that the intervention is associated with a 10.9% improvement in physician productivity. We also find evidence for a significant reduction in variation in productivity across providers, which stems from bottom-ranked workers exhibiting differentially large improvements in productivity. These effects hold without sacrificing system-level performance, service quality, or worker attrition. Our results suggest that public disclosure of RPF, along with the validation of the best practices being shared, can improve worker productivity.
The online supplement is available at
https://doi.org/10.1287/mnsc.2017.2745
.
This paper was accepted by Serguei Netessine, operations management.
Journal Article
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Machine learning (ML) has played an increasing role in the hydrological sciences. In particular, Long Short-Term Memory (LSTM) networks are popular for rainfall–runoff modeling. A large majority of studies that use this type of model do not follow best practices, and there is one mistake in particular that is common: training deep learning models on small, homogeneous data sets, typically data from only a single hydrological basin. In this position paper, we show that LSTM rainfall–runoff models are best when trained with data from a large number of basins.
Journal Article
Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices
Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome. Simultaneous quantification of many metabolites within complex mixtures can additionally be complicated by ion suppression, fragmentation and the presence of isomers. Here we present guidelines covering sample preparation, replication and randomization, quantification, recovery and recombination, ion suppression and peak misidentification, as a means to enable high-quality reporting of liquid chromatography– and gas chromatography–mass spectrometry-based metabolomics-derived data.This Perspective, from a large group of metabolomics experts, provides best practices and simplified reporting guidelines for practitioners of liquid chromatography– and gas chromatography–mass spectrometry-based metabolomics.
Journal Article
Marketing survey research best practices: evidence and recommendations from a review of JAMS articles
Survey research methodology is widely used in marketing, and it is important for both the field and individual researchers to follow stringent guidelines to ensure that meaningful insights are attained. To assess the extent to which marketing researchers are utilizing best practices in designing, administering, and analyzing surveys, we review the prevalence of published empirical survey work during the 2006–2015 period in three top marketing journals—Journal of the Academy of Marketing Science (JAMS), Journal of Marketing (JM), and Journal of Marketing Research (JMR)—and then conduct an in-depth analysis of 202 survey-based studies published in JAMS. We focus on key issues in two broad areas of survey research (issues related to the choice of the object of measurement and selection of raters, and issues related to the measurement of the constructs of interest), and we describe conceptual considerations related to each specific issue, review how marketing researchers have attended to these issues in their published work, and identify appropriate best practices.
Journal Article
Common principles and best practices for engineering microbiomes
Despite broad scientific interest in harnessing the power of Earth’s microbiomes, knowledge gaps hinder their efficient use for addressing urgent societal and environmental challenges. We argue that structuring research and technology developments around a design–build–test–learn (DBTL) cycle will advance microbiome engineering and spur new discoveries of the basic scientific principles governing microbiome function. In this Review, we present key elements of an iterative DBTL cycle for microbiome engineering, focusing on generalizable approaches, including top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyse microbiome function. These approaches can be used to harness microbiomes for broad applications related to medicine, agriculture, energy and the environment. We also discuss key challenges and opportunities of each approach and synthesize them into best practice guidelines for engineering microbiomes. We anticipate that adoption of a DBTL framework will rapidly advance microbiome-based biotechnologies aimed at improving human and animal health, agriculture and enabling the bioeconomy.
Journal Article
MetPy
MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skew T and GEMPAK-like plotting, station model plots, and support for parsing a variety of meteorological data formats. The general road map for future planned development for MetPy is also discussed.
Journal Article
A Review of the Quality Indicators of Rigor in Qualitative Research
Attributes of rigor and quality and suggested best practices for qualitative research design as they relate to the steps of designing, conducting, and reporting qualitative research in health professions educational scholarship are presented. A research question must be clear and focused and supported by a strong conceptual framework, both of which contribute to the selection of appropriate research methods that enhance trustworthiness and minimize researcher bias inherent in qualitative methodologies. Qualitative data collection and analyses are often modified through an iterative approach to answering the research question. Researcher reflexivity, essentially a researcher’s insight into their own biases and rationale for decision-making as the study progresses, is critical to rigor. This article reviews common standards of rigor, quality scholarship criteria, and best practices for qualitative research from design through dissemination.
Journal Article