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Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model.

Yin S, Njai R, Barker L, Siegel PZ, Liao Y - Popul Health Metr (2016)

Bottom Line: In addition, use of the one-factor model showed stability, with no changes being detected from 2001 to 2013.Instead of using four individual items to measure HRQOL, it is feasible to study overall HRQOL via factor analysis with one underlying construct.The resulting summary score of HRQOL may be used for health evaluation, subgroup comparison, trend monitoring, and risk factor identification.

View Article: PubMed Central - PubMed

Affiliation: SciMetrika, LLC, 100 Capitola Drive, Durham, NC 27701 USA.

ABSTRACT

Background: Health-related quality of life (HRQOL) is a multi-dimensional concept commonly used to examine the impact of health status on quality of life. HRQOL is often measured by four core questions that asked about general health status and number of unhealthy days in the Behavioral Risk Factor Surveillance System (BRFSS). Use of these measures individually, however, may not provide a cohesive picture of overall HRQOL. To address this concern, this study developed and tested a method for combining these four measures into a summary score.

Methods: Exploratory and confirmatory factor analyses were performed using BRFSS 2013 data to determine potential numerical relationships among the four HRQOL items. We also examined the stability of our proposed one-factor model over time by using BRFSS 2001-2010 and BRFSS 2011-2013 data sets.

Results: Both exploratory factor analysis and goodness of fit tests supported the notion that one summary factor could capture overall HRQOL. Confirmatory factor analysis indicated acceptable goodness of fit of this model. The predicted factor score showed good validity with all of the four HRQOL items. In addition, use of the one-factor model showed stability, with no changes being detected from 2001 to 2013.

Conclusion: Instead of using four individual items to measure HRQOL, it is feasible to study overall HRQOL via factor analysis with one underlying construct. The resulting summary score of HRQOL may be used for health evaluation, subgroup comparison, trend monitoring, and risk factor identification.

No MeSH data available.


Related in: MedlinePlus

Final one-factor model for the CDC HRQOL-4, BRFSS 2013. Standardized factor loadings from the latent construct (represented by the large oval) to its measures (represented by rectangles) are shown beside the single-headed arrows. The small ovals represent error variances unexplained by the model. The curved double-headed arrow represents correlations between error variances
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Fig1: Final one-factor model for the CDC HRQOL-4, BRFSS 2013. Standardized factor loadings from the latent construct (represented by the large oval) to its measures (represented by rectangles) are shown beside the single-headed arrows. The small ovals represent error variances unexplained by the model. The curved double-headed arrow represents correlations between error variances

Mentions: An initial model with four paths from one factor to the four CDC HRQOL-4 items was first evaluated by CFA. The four items had factor loadings that ranged from 0.46 to 0.87, larger than the minimal acceptable cutoff value of ±0.3 [26]. The goodness of fit statistics indicate that the model is acceptable but could be improved upon (RMSEA = 0.086, CFI = 0.90, TLI = 0.70, SRMR = 0.03, CD = 0.85). To determine whether the model could be improved, a post-hoc model modification was performed. We found that adding an error correlation path between the physically unhealthy day item and the mentally unhealthy day item substantially improved the goodness of fit between model and data. Thus, a final model was proposed (Fig. 1). The minimal factor loading was increased from 0.46 to 0.54. The goodness of fit statistics were also greatly improved (RMSEA = 0.039, CFI = 0.99, TLI = 0.94, SRMR = 0.01, CD = 0.89).Fig. 1


Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model.

Yin S, Njai R, Barker L, Siegel PZ, Liao Y - Popul Health Metr (2016)

Final one-factor model for the CDC HRQOL-4, BRFSS 2013. Standardized factor loadings from the latent construct (represented by the large oval) to its measures (represented by rectangles) are shown beside the single-headed arrows. The small ovals represent error variances unexplained by the model. The curved double-headed arrow represents correlations between error variances
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4940947&req=5

Fig1: Final one-factor model for the CDC HRQOL-4, BRFSS 2013. Standardized factor loadings from the latent construct (represented by the large oval) to its measures (represented by rectangles) are shown beside the single-headed arrows. The small ovals represent error variances unexplained by the model. The curved double-headed arrow represents correlations between error variances
Mentions: An initial model with four paths from one factor to the four CDC HRQOL-4 items was first evaluated by CFA. The four items had factor loadings that ranged from 0.46 to 0.87, larger than the minimal acceptable cutoff value of ±0.3 [26]. The goodness of fit statistics indicate that the model is acceptable but could be improved upon (RMSEA = 0.086, CFI = 0.90, TLI = 0.70, SRMR = 0.03, CD = 0.85). To determine whether the model could be improved, a post-hoc model modification was performed. We found that adding an error correlation path between the physically unhealthy day item and the mentally unhealthy day item substantially improved the goodness of fit between model and data. Thus, a final model was proposed (Fig. 1). The minimal factor loading was increased from 0.46 to 0.54. The goodness of fit statistics were also greatly improved (RMSEA = 0.039, CFI = 0.99, TLI = 0.94, SRMR = 0.01, CD = 0.89).Fig. 1

Bottom Line: In addition, use of the one-factor model showed stability, with no changes being detected from 2001 to 2013.Instead of using four individual items to measure HRQOL, it is feasible to study overall HRQOL via factor analysis with one underlying construct.The resulting summary score of HRQOL may be used for health evaluation, subgroup comparison, trend monitoring, and risk factor identification.

View Article: PubMed Central - PubMed

Affiliation: SciMetrika, LLC, 100 Capitola Drive, Durham, NC 27701 USA.

ABSTRACT

Background: Health-related quality of life (HRQOL) is a multi-dimensional concept commonly used to examine the impact of health status on quality of life. HRQOL is often measured by four core questions that asked about general health status and number of unhealthy days in the Behavioral Risk Factor Surveillance System (BRFSS). Use of these measures individually, however, may not provide a cohesive picture of overall HRQOL. To address this concern, this study developed and tested a method for combining these four measures into a summary score.

Methods: Exploratory and confirmatory factor analyses were performed using BRFSS 2013 data to determine potential numerical relationships among the four HRQOL items. We also examined the stability of our proposed one-factor model over time by using BRFSS 2001-2010 and BRFSS 2011-2013 data sets.

Results: Both exploratory factor analysis and goodness of fit tests supported the notion that one summary factor could capture overall HRQOL. Confirmatory factor analysis indicated acceptable goodness of fit of this model. The predicted factor score showed good validity with all of the four HRQOL items. In addition, use of the one-factor model showed stability, with no changes being detected from 2001 to 2013.

Conclusion: Instead of using four individual items to measure HRQOL, it is feasible to study overall HRQOL via factor analysis with one underlying construct. The resulting summary score of HRQOL may be used for health evaluation, subgroup comparison, trend monitoring, and risk factor identification.

No MeSH data available.


Related in: MedlinePlus