COALESCE Team Science eLearning Modules: Team Science Research Process in Behavioral Science (Module 2)

2011 ◽  
Author(s):  
Bonnie Spring ◽  
Arlen C. Moller ◽  
Holly Falk-Krzesinski
Keyword(s):  
Behavioral Science ◽  
Science Research ◽  
Research Process ◽  
Team Science

scholarly journals Enhancing reproducibility using interprofessional team best practices

2020 ◽  
pp. 1-8 ◽  
Author(s):  
Betsy Rolland ◽  
Elizabeth S. Burnside ◽  
Corrine I. Voils ◽  
Manish N. Shah ◽  
Allan R. Brasier
Keyword(s):  
Best Practices ◽  
Science Research ◽  
Research Process ◽  
Reproducible Research ◽  
Scientific Integrity ◽  
Team Science ◽  
Translational Science ◽  
Preclinical Research ◽  
Minimal Impact ◽  
The Impact

Abstract The pervasive problem of irreproducibility of preclinical research represents a substantial threat to the translation of CTSA-generated health interventions. Key stakeholders in the research process have proposed solutions to this challenge to encourage research practices that improve reproducibility. However, these proposals have had minimal impact, because they either 1. take place too late in the research process, 2. focus exclusively on the products of research instead of the processes of research, and/or 3. fail to take into account the driving incentives in the research enterprise. Because so much clinical and translational science is team-based, CTSA hubs have a unique opportunity to leverage Science of Team Science research to implement and support innovative, evidence-based, team-focused, reproducibility-enhancing activities at a project’s start, and across its evolution. Here, we describe the impact of irreproducibility on clinical and translational science, review its origins, and then describe stakeholders’ efforts to impact reproducibility, and why those efforts may not have the desired effect. Based on team-science best practices and principles of scientific integrity, we then propose ways for Translational Teams to build reproducible behaviors. We end with suggestions for how CTSAs can leverage team-based best practices and identify observable behaviors that indicate a culture of reproducible research.

Context in Action and How to Study It

2019 ◽  
Keyword(s):  
Social Science Research ◽  
Science Research ◽  
Research Process ◽  
Care Patient ◽  
Organizational Life ◽  
Integration Of Care ◽  
Research Experiences ◽  
Organization And Management ◽  
Care Outcomes ◽  
Definition Of

The concept of context is a cornerstone of a large part of social science research, particularly in organization and management studies, yet it has received little theoretical and methodological attention in lieu of its relevance. This book offers a definition of context as a theoretical construct, a discussion of the methodological implications of this, and a framework for how to reflect upon and operationalize the role of context in the different stages of a research process, from formulating research questions to analyzing and writing about results. The chapters presented here integrate lessons derived from various research experiences across the complex and dynamic field of health care. Contributors share their experiences with theorizing about and empirically studying significant organizational phenomena such as implementation of policy, organizational change, integration of care, patient involvement, human-technology interactions in practice, and the interplay between work environment and care outcomes in eldercare. These contributions exemplify how a nuanced approach to context might unfold in different fields, through different designs, methods, and analytical lenses. Relevant to researchers and practitioners, within both healthcare, organization and management studies, and the social sciences more broadly, this book leaves the reader with a practical framework from which to carry out contextual research and analysis and a gain deeper understanding of the significance of context in organizational life.

An Introduction to Statistical Models for Networks

2020 ◽  
pp. 218-233
Author(s):  
Valentina Kuskova ◽  
Stanley Wasserman
Keyword(s):  
Social System ◽  
Exponential Family ◽  
Behavioral Science ◽  
Social Science Research ◽  
Science Research ◽  
Uniform Distributions ◽  
The Social ◽  
Special Cases ◽  
Social And Behavioral Science ◽  
Network Methods

Network theoretical and analytic approaches have reached a new level of sophistication in this decade, accompanied by a rapid growth of interest in adopting these approaches in social science research generally. Of course, much social and behavioral science focuses on individuals, but there are often situations where the social environment—the social system—affects individual responses. In these circumstances, to treat individuals as isolated social atoms, a necessary assumption for the application of standard statistical analysis is simply incorrect. Network methods should be part of the theoretical and analytic arsenal available to sociologists. Our focus here will be on the exponential family of random graph distributions, p*, because of its inclusiveness. It includes conditional uniform distributions as special cases.

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