A First Glimpse at the Latent Structure of Sleep Valuation Using a Sleep Valuation Item Bank

Nat Sci Sleep. 2023 Mar 21:15:127-137. doi: 10.2147/NSS.S386838. eCollection 2023.

Abstract

Introduction: Sleep valuation is the relative worth individuals place on sleep. Our prior study using a Sleep Valuation Item Bank (SVIB) showed that sleep valuation relates to age, gender, and health status. In this study, the psychometric properties of the SVIB and its latent factor structure were explored. We also investigated how sleep valuation factors relate to demographic, psychological, and sleep features.

Methods: Participants (N = 854) were recruited through TurkPRIME and completed a survey consisting of demographic, psychological, and sleep-related questions. The distributional properties of the SVIB items were quantified. Cronbach's alpha and correlation analyses were used to assess the internal consistency and test-retest reliability of SVIB items. Iterated principal factoring with a Promax rotation was used on the SVIB to explore its latent factor structure. Multiple regression analyses were used to investigate the variables associated with each factor.

Results: The factor analysis identified 29 items with factor loadings ≥0.4 on four major factors, tentatively called (1) sleep wanting, (2) sleep prioritizing, (3) sleep onset preference, and (4) sleep devaluation. While women had higher sleep wanting and lower sleep devaluation scores than men, they had lower sleep prioritizing. Older individuals tended to value sleep less but also devalued it less than younger participants. Finally, although both individuals with insomnia and depression devalued sleep, depressed individuals prioritized it more than those who were less depressed, while individuals with insomnia symptoms wanted sleep and preferred sleep onset more than those with less insomnia symptoms.

Discussion: The current SVIB captures broad dimensions of sleep valuation (wanting, prioritizing, preferring) and sleep devaluation. These broad dimensions had distinct patterns across person-level factors. Recognition of individual differences in sleep valuation may help target sleep health advocacy efforts and individualized treatment approaches, including for those with depression or insomnia.

Keywords: depression; insomnia; sleep health; sleep quality; sleep valuation.