Gepubliceerd in:
07-06-2017
Distinguishing appraisal and personality influences on quality of life in chronic illness: introducing the quality-of-life Appraisal Profile version 2
Gepubliceerd in: Quality of Life Research | Uitgave 10/2017
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Background
Cognitive appraisal of quality of life (QOL) differs across individuals in ways that explain otherwise paradoxical findings, such as similar QOL ratings among individuals in highly divergent health states. Although warranted by a growing body of evidence, routine assessment of appraisal in QOL research has been impeded by measurement challenges. This study describes the QOL Appraisal Profile-version 2 (QOLAPv2), a new measure that addresses these challenges.
Methods
A heterogeneous, on-line cohort of chronic disease patients and caregivers completed the QOLAPv2, along with demographics, PROMIS10 and Brief NEO Personality Inventory (NEO-PI). Analyses address the psychometric properties and construct validity of this new measure using principal components, bivariate, canonical correlation, and linear regression analyses.
Results
Analysis including 4173 respondents yielded 12 second-order QOLAPv2 principal components. Appraisal components varied with age and disease duration. Appraisals involving “Wellness,” “Health,” and “Recent Challenges” were correlated with QOL and with NEO-PI scales of “Agreeableness” and “Conscientiousness.” Canonical correlation analysis revealed that QOL scales were associated with appraisals involving “Spirituality,” “Anticipating Decline,” and “Lightness of Being.” Appraisal dimensions of “Relationships,” “Maintaining Roles,” “Independence,” “Pursuing Dreams,” and “Lightness of Being” were also associated with personality scales. Appraisal measures accounted for significantly more variance in QOL than personality and demographics alone.
Conclusions
Findings corroborate the Rapkin and Schwartz QOL appraisal theory. QOL appraisal measures correlate as expected with personality scales, and explain more variance in QOL than does personality. The QOLAPv2 can be used across populations to provide insight into patients’ concerns, salient experiences, and comparators.