Asian Nurs Res.  2017 Dec;11(4):297-303. 10.1016/j.anr.2017.11.004.

Validation of the Decisional Conflict Scale for Evaluating Advance Care Decision Conflict in Community-dwelling Older Adults

• Kim J
• Kim S
• Hong SW
• Kang SW
• An M

• KMID: 2416435
• DOI: http://doi.org/10.1016/j.anr.2017.11.004

Abstract

PURPOSE
Decisional conflict is a significant and important barrier in end-of-life care planning, and it is often encountered in health professionals' discussions with patients and their families. Little is known about the measurement of decisional conflict, and existing measures are not suitable for all contexts. In this study, psychometric properties of the Decisional Conflict Scale, which was translated for the first time into Korean [Korean version of DCS (K-DCS)], were examined.
METHODS
A sample of 273 community-dwelling elders was surveyed (mean age: 77.26 years; 80.2% women). Internal consistency reliability and stability reliability were tested by calculating Cronbach α and Pearson's correlation coefficients. Exploratory factor analysis and logistic regression analyses were performed to test validity.
RESULTS
Reliability of the K-DCS was acceptable with Cronbach α =.87; test-retest correlation r = .76. Factor analysis showed a two-factor structure with nine items: informed/values clarity and uncertainty. Concordance between K-DCS and the four treatment directives was significant (kappa values ≥.78). Controlling for age and gender, those with decision implementation were more likely to implement their decisions on tube feeding (odds ratio = 5.15, p = .033) and hospice care (odds ratio = 2.83, p = .017).
CONCLUSION
The K-DCS appears to be a valid measure to evaluate decisional conflict about advance directives in community-dwelling Korean older adults. Further validation of the K-DCS is warranted, though caution should be exercised in using subscales because of differences in decisional contexts.

Keyword

advance directives; community; elderly; psychometrics

MeSH Terms

Adult*
Advance Directives
Aged
Enteral Nutrition
Hospice Care
Humans
Logistic Models
Psychometrics
Uncertainty