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. 2023 Nov 29;9(12):e22668.
doi: 10.1016/j.heliyon.2023.e22668. eCollection 2023 Dec.

Measuring population health and quality of life: Developing and testing of the significant quality of life measure (SigQOLM)

Affiliations

Measuring population health and quality of life: Developing and testing of the significant quality of life measure (SigQOLM)

Mohamad Adam Bujang et al. Heliyon. .

Abstract

Quality of life (QOL) should ideally be determined by a broader spectrum of measurable parameters. This study aims to develop and validate a study instrument that is designed to determine a holistic measure of health and non-health aspects of QOL, and it is called the 'Significant Quality of Life Measure' (SigQOLM). This study involves five phases which aim to (i) explore and understand the subject matter content, (ii) develop a questionnaire, (iii) assess its content validity and face validity, (iv) conduct a pilot study, and lastly (v) perform a field-test by using the questionnaire. For the field-testing phase, a cross-sectional study was conducted which elicited responses from healthcare workers via a self-administered survey for all the SigQOLM items. Based on the results, the overall framework of the SigQOLM consists of four elements, 18 domains with 69 items. The element of "Health" is measured by nine domains, while "Relationships", "Functional activities, and "Survival" are measured by three domains respectively. The SigQOLM has been developed successfully and then validated with a high level of reliability, validity, and overall model fit. Therefore, the SigQOLM will provide researchers and policymakers another viable option to elicit a more comprehensive outcome measure of QOL which shall then enable them to implement specific interventions for improving the QOL of all the people, both healthy or otherwise.

Keywords: Health; Quality of life; Questionnaire development; Reliability; Validity.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
The framework of SigQOLM.

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