Exploring and Validating Performance Measurement Domains of Community Pharmacists Using Structural Equation Modeling: Implications and Recommendations for Research

Theophilus Ehidiamen Oamen *

Department of Business Management, Texila American University, Guyana.

Banjo Moshood Lawal

Department of Social Sciences Education, Faculty of Education, University of Ilorin, Ilorin, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

Background: Structural equation modeling (SEM) is a widely used quantitative technique among social and management science researchers. Self-reported questionnaires are in prevalent use among researchers in pharmacy management. But validity and measurement invariance measures of questionnaires are not commonly reported in research studies.

Objectives: To determine the construct validity and invariance validity of the research instrument. To provide guidelines for applying confirmatory factor analysis (CFA) in pharmacy management research.

Methods: A cross-sectional study with an anonymously structured questionnaire randomly administered to six hundred community pharmacists in southwestern, Nigeria. The CFA algorithm in SEM software was used to develop a measurement model and test hypotheses.

Results: The measurement model satisfied the model and construct validity benchmarks. The measurement invariance parameters were adequate.

Conclusion: The study concluded that the theoretically developed constructs- economic, operational, and social performance were valid representations of theory. Mandatory inclusion of validity and measurement invariance test reporting in pharmacy management research is advocated.

Keywords: Behavioral research, confirmatory factor analysis, social pharmacy, measurement invariance, model fit, multigroup analysis, structural equation modeling, pharmacy management


How to Cite

Oamen , Theophilus Ehidiamen, and Banjo Moshood Lawal. 2023. “Exploring and Validating Performance Measurement Domains of Community Pharmacists Using Structural Equation Modeling: Implications and Recommendations for Research”. Journal of Scientific Research and Reports 29 (1):38-47. https://doi.org/10.9734/jsrr/2023/v29i11726.

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