Recommendations of Common Data Elements to Advance the Science of Self-Management of Chronic Conditions

Affiliations

¹ Delta Xi, Edward J. and Louise Mellen Professor of Nursing, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA. smm8@case.edu.
² Alpha Chi, Eta Nu, Professor and Associate Dean for Research, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
³ Assistant Dean for Research, Associate Professor, Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
⁴ Delta Mu, Beatrice Renfield Term Professor of Nursing, Professor, Section of Pulmonary, Critical Care and Sleep Medicine, Yale University, New Haven, CT, USA.
⁵ Clinical Advisor, Contractor, National Institute of Nursing Research, NIH, Bethesda, MD, USA.
⁶ Epsilon Theta, Professor, Associate Vice President for Community Health Engagement, University of Texas at Austin, Austin, TX, USA.
⁷ Gamma Epsilon, Professor and Chairperson, Department of Biobehavioral Nursing and Health Systems, University of Washington, Seattle, WA, USA.
⁸ Professor, Director of the PhD Program, Northeastern University, Boston, MA, USA.
⁹ Pi, Professor and Chair, Department of Pain and Translational Symptom Science, University of Maryland Baltimore, Baltimore, MD, USA.
¹⁰ Lota Omicron, Associate Professor, School of Nursing; Associate Professor, Department of Pediatrics, School of Medicine; Co-Director, P30 Center for Cognitive/Affective Symptom Science, Duke University, Durham, NC, USA.
¹¹ Mary Lou Willard French Professor of Oncology Nursing University of Michigan, Ann Arbor, MI, USA.
¹² Beta Epsilon and Theta Iota, Associate Professor, Duke University, Durham, NC, USA.
¹³ Alpha, Distinguished Professor Emerita, Indiana University School of Nursing, Indianapolis, IN and National Institute of Nursing Research, NIH, Bethesda, MD, USA.
¹⁴ Tau, Director, National Institute of Nursing Research, NIH, Bethesda, MD, USA.

PMID: 27486851
PMCID: PMC5490657
DOI: 10.1111/jnu.12233

Recommendations of Common Data Elements to Advance the Science of Self-Management of Chronic Conditions

Shirley M Moore et al. J Nurs Scholarsh. 2016 Sep.

. 2016 Sep;48(5):437-47.

doi: 10.1111/jnu.12233. Epub 2016 Aug 3.

Authors

Affiliations

¹ Delta Xi, Edward J. and Louise Mellen Professor of Nursing, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA. smm8@case.edu.
² Alpha Chi, Eta Nu, Professor and Associate Dean for Research, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
³ Assistant Dean for Research, Associate Professor, Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
⁴ Delta Mu, Beatrice Renfield Term Professor of Nursing, Professor, Section of Pulmonary, Critical Care and Sleep Medicine, Yale University, New Haven, CT, USA.
⁵ Clinical Advisor, Contractor, National Institute of Nursing Research, NIH, Bethesda, MD, USA.
⁶ Epsilon Theta, Professor, Associate Vice President for Community Health Engagement, University of Texas at Austin, Austin, TX, USA.
⁷ Gamma Epsilon, Professor and Chairperson, Department of Biobehavioral Nursing and Health Systems, University of Washington, Seattle, WA, USA.
⁸ Professor, Director of the PhD Program, Northeastern University, Boston, MA, USA.
⁹ Pi, Professor and Chair, Department of Pain and Translational Symptom Science, University of Maryland Baltimore, Baltimore, MD, USA.
¹⁰ Lota Omicron, Associate Professor, School of Nursing; Associate Professor, Department of Pediatrics, School of Medicine; Co-Director, P30 Center for Cognitive/Affective Symptom Science, Duke University, Durham, NC, USA.
¹¹ Mary Lou Willard French Professor of Oncology Nursing University of Michigan, Ann Arbor, MI, USA.
¹² Beta Epsilon and Theta Iota, Associate Professor, Duke University, Durham, NC, USA.
¹³ Alpha, Distinguished Professor Emerita, Indiana University School of Nursing, Indianapolis, IN and National Institute of Nursing Research, NIH, Bethesda, MD, USA.
¹⁴ Tau, Director, National Institute of Nursing Research, NIH, Bethesda, MD, USA.

PMID: 27486851
PMCID: PMC5490657
DOI: 10.1111/jnu.12233

Erratum in

ERRATA.
[No authors listed] [No authors listed] J Nurs Scholarsh. 2017 Nov;49(6):697. doi: 10.1111/jnu.12309. Epub 2017 May 31. J Nurs Scholarsh. 2017. PMID: 29068179 No abstract available.

Abstract

Purpose: Common data elements (CDEs) are increasingly being used by researchers to promote data sharing across studies. The purposes of this article are to (a) describe the theoretical, conceptual, and definition issues in the development of a set of CDEs for research addressing self-management of chronic conditions; (b) propose an initial set of CDEs and their measures to advance the science of self-management; and (c) recommend implications for future research and dissemination.

Design and methods: Between July 2014 and December 2015 the directors of the National Institute of Nursing Research (NINR)-funded P20 and P30 centers of excellence and NINR staff met in a series of telephone calls and a face-to-face NINR-sponsored meeting to select a set of recommended CDEs to be used in self-management research. A list of potential CDEs was developed from examination of common constructs in current self-management frameworks, as well as identification of variables frequently used in studies conducted in the centers of excellence.

Findings: The recommended CDEs include measures of three self-management processes: activation, self-regulation, and self-efficacy for managing chronic conditions, and one measure of a self-management outcome, global health.

Conclusions: The self-management of chronic conditions, which encompasses a considerable number of processes, behaviors, and outcomes across a broad range of chronic conditions, presents several challenges in the identification of a parsimonious set of CDEs. This initial list of recommended CDEs for use in self-management research is provisional in that it is expected that over time it will be refined. Comment and recommended revisions are sought from the research and practice communities.

Clinical relevance: The use of CDEs can facilitate generalizability of research findings across diverse population and interventions.

Keywords: Common data elements; research data harmonization; self-management.

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Recommendations of Common Data Elements to Advance the Science of Self-Management of Chronic Conditions

Affiliations

Recommendations of Common Data Elements to Advance the Science of Self-Management of Chronic Conditions

Authors

Affiliations

Erratum in

Abstract

References

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical

Miscellaneous