Participation in Decision Making as a Property of Complex Adaptive Systems: Developing and Testing a Measure

Author:

Anderson Ruth A.1,Plowman Donde2ORCID,Corazzini Kirsten1ORCID,Hsieh Pi-Ching3,Su Hui Fang3,Landerman Lawrence R.4,McDaniel Reuben R.5

Affiliation:

1. Duke University School of Nursing, DUMC Box 3322, Durham, NC 27710, USA

2. The University of Nebraska-Lincoln, College of Business Administration, Lincoln, NE 68508, USA

3. National Taipei University of Nursing and Health Sciences, Health and Nursing Service Administration Department, Beitou District, Taipei City 112, Taiwan

4. Duke University, Center for the Study Aging and Human Development, Durham, NC 27710, USA

5. The University of Texas at Austin, McCombs School of Business, Austin, TX 78705, USA

Abstract

Objectives.To (1) describe participation in decision-making as a systems-level property of complex adaptive systems and (2) present empirical evidence of reliability and validity of a corresponding measure.Method.Study 1 was a mail survey of a single respondent (administrators or directors of nursing) in each of 197 nursing homes. Study 2 was a field study using random, proportionally stratified sampling procedure that included 195 organizations with 3,968 respondents.Analysis.In Study 1, we analyzed the data to reduce the number of scale items and establish initial reliability and validity. In Study 2, we strengthened the psychometric test using a large sample.Results.Results demonstrated validity and reliability of the participation in decision-making instrument (PDMI) while measuring participation of workers in two distinct job categories (RNs and CNAs). We established reliability at the organizational level aggregated items scores. We established validity of the multidimensional properties using convergent and discriminant validity and confirmatory factor analysis.Conclusions.Participation in decision making, when modeled as a systems-level property of organization, has multiple dimensions and is more complex than is being traditionally measured. Managers can use this model to form decision teams that maximize the depth and breadth of expertise needed and to foster connection among them.

Funder

National Institute of Nursing Research

Publisher

Hindawi Limited

Subject

General Nursing

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