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The Selection, Use and Interpretation of Outcome Measures in Integrated Medicine and Health

14:00 - 17:00, Hibiscus B, Terrace Level

Workshop Handouts


Kathi Kemper (1), Gregg Gascon (2)


(1): Center for Integrative Health and Wellness, Ohio State University and Nationwide Children’s Hospital, United States

(2): Ohio State University Health Plan, United States


Integrative health focuses on optimizing overall health. Physical outcome measures (e.g. lab values and physical functioning measures) need to be supplemented by psychometrically sound self-report measures of the mental, emotional, social and spiritual domains of health in order to measure health outcomes comprehensively, holistically, and reliably. In order to detect the effects of such methods on a health domain of interest, researchers and clinicians need to experientially understand and apply the theory and practice of psychometrics. Psychometrics is the science that evaluates the attributes of psychological tests. Psychometric theory allows researchers to tap into outcomes of interest in a variety of health domains for patients, clinicians and payers alike. Three frameworks will be employed in this workshop: the structure for physical and mental measurements offered by McDowell (2006); the outcomes framework of Kane and Radosevich (2011); and the basic components of psychometric theory as described by Furr and Bacharach (2014) and DeVellis (2012). This approach provides a sound footing for researchers interested in using self-report outcome measures in extramurally-funded research. The workshop will provide a brief introduction to psychometric theory and offer participants the opportunity to complete, score, and interpret psychometric assessments in overall well-being and physical, mental, emotional, social, and spiritual health. It will provide participants with a set of practical steps and checklists, and a framework to understand the assessment landscape in an active group learning setting, so they are well equipped to collaborate on outcome research using optimal mutually agreeable measures.