Patient-Centered Communication (PCC) scale: Psychometric analysis and validation of a health survey measure.

PLoS One

Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, United States of America.

Published: January 2023

AI Article Synopsis

  • Patient-centered communication (PCC) is a crucial aspect of patient-centered care that has been linked to improved health behaviors and outcomes, prompting the National Cancer Institute to assess its measurement in cancer survivors.
  • A seven-item PCC scale was developed and included in the Health Information National Trends Survey (HINTS), and this study analyzed data from 2018 to evaluate its reliability and validity across the general US adult population.
  • The results showed that the PCC scale is internally consistent, unidimensional, and valid, making it a useful tool for both broader research and specific studies focused on understanding clinical interactions and health outcomes.

Article Abstract

Introduction: Patient-centered communication (PCC) is one important component of patient-centered care and seen as a goal for most clinical encounters. Previous research has shown that higher PCC is related to an increase in healthy behaviors and less morbidity, among other outcomes. Given its importance, the National Cancer Institute (NCI) commissioned a monograph in 2007 to synthesize the existing literature on PCC and determine measurement objectives and strategies for measuring this construct, with a particular focus on cancer survivors. Based on this effort, a seven-item PCC scale was included on the Health Information National Trends Survey (HINTS), a probability-based survey of the US adult population. This study used HINTS data collected in 2018 to evaluate the psychometric properties of the PCC scale for the general US adult population including measures of reliability and validity.

Results: Through an exploratory factor analysis, the seven-item PCC scale was shown to be unidimensional with good internal consistency (Cronbach's alpha = .92). A confirmatory factor analysis verified the factor structure. Other construct validity metrics included known groups and discriminant validity. Known group comparisons were conducted for several sociodemographic factors and health self-efficacy confirming a priori assumptions. Discriminant validity tests with measures of social support and anxiety/depression showed relatively weak associations.

Conclusions: The psychometric properties of this scale demonstrate its scientific utility for both surveillance research and other smaller-scale studies. Given its association with many health outcomes, it can also be used to better understand the dynamics in a clinical encounter.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803193PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0279725PLOS

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