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26-02-2019 | Uitgave 6/2019

Quality of Life Research 6/2019

Multidimensionality of the PROMIS self-efficacy measure for managing chronic conditions

Tijdschrift:
Quality of Life Research > Uitgave 6/2019
Auteurs:
Mi Jung Lee, Sergio Romero, Craig A. Velozo, Ann L. Gruber-Baldini, Lisa M. Shulman
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s11136-019-02116-w) contains supplementary material, which is available to authorized users.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

Purpose

This study investigated the PROMIS Self-Efficacy Measure for Managing Chronic Conditions (PROMIS-SE) domain distributions and examined the factor structure of the PROMIS-SE.

Methods

A total of 1087 individuals with chronic conditions participated in this study. PROMIS-SE’s item banks and two short forms (eight-item and four-item) measuring five behavioral domains (daily activities(DA), Emotions(EM), medications and treatments(MT), social interactions(SS), and Symptoms(SX)) were examined. PROMIS-SE’s T-score ranges and distributions were examined to identify domain metric distributions and confirmatory factor analysis (CFA) was conducted to test a multidimensional model fit to the PROMIS-SE.

Results

PROMIS-SE domains showed different T-score ranges and distributions for item banks and two short forms across all five domains. While PROMIS-SE EM demonstrated the highest T-scores (least negatively skewed), MT had the lowest T-scores (most negatively skewed) for all three forms. In general, respondents were more likely to achieve highest self-efficacy ratings (very confident) for domains DA, MT, and SS as compared to domains EM and SX. CFA confirmed that a multidimensional model adequately fit all three PROMIS-SE forms.

Conclusion

Our results indicate that self-efficacy T-distributions are not consistent across domains (i.e., managing medications and treatments domain was more negatively skewed difficult than other domains), which is a requirement for making inter-domain comparisons. A multidimensional model could be used to enhance the PROMIS-SE’s estimate accuracy and clinical utility.

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