Frontiers in Public Health (Nov 2024)
Development and validation of the Integrative Vitality Scale
Abstract
IntroductionVitality is a construct based on traditional vitalism, and is a concept similar to energy (Qi), passion, and motivation as the essential power possessed by organisms. Recently, various methods and tools have been designed to evaluate vitality as a health indicator. This study aimed to develop and validate an Integrative Vitality Scale (IVS) based on traditional Eastern medicine and modern psychology.MethodsWe conducted two online surveys and one pre-post comparison with Korean adults. Descriptive statistics and factor analysis were performed for scale development, and correlation and regression analysis were performed for validation.ResultsExploratory (n = 348) and confirmatory (n = 349) factor analyses showed that two subfactors (physical and psychological vitality) best represented integrative vitality. The IVS-total and subscales had good internal consistency (α = 0.89–.094) and test-retest reliability (r = 0.71–0.80). Ten health-related experts (e.g., doctors, clinical psychologists, and counselors) evaluated the IVS as having excellent content validity. The IVS-total and subscales had a high correlation with existing vitality-related scales but a low correlation with pathological symptoms such as hypomania, suggesting convergent and discriminant validity. The IVS-total and subscales were negatively correlated with depression and fatigue but positively correlated with well-being and quality of life, suggesting criterion validity. The IVS had additional predictive power for depression, fatigue, and well-being even after controlling for existing vitality-related scales, suggesting incremental validity. Finally, after 16 weeks of mindfulness training (n = 28), IVS-total and subscales significantly increased.DiscussionThese findings suggested that the IVS is a valid and reliable tool for assessing physical and psychological vitality. Furthermore, the IVS could be used as a clinical indicator to predict symptoms related to low energy, such as depression and fatigue, and as an indicator of sustainable well-being.
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