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. Author manuscript; available in PMC: 2025 May 1.
Published in final edited form as: Behav Sleep Med. 2023 Sep 6;22(3):319–328. doi: 10.1080/15402002.2023.2255328

Race as a Potential Moderator of the Association between Dysfunctional Beliefs about Sleep and Global Sleep Health

Spencer A Nielson 1, Natalie D Dautovich 1, Joseph M Dzierzewski 2,*
PMCID: PMC10915100  NIHMSID: NIHMS1929459  PMID: 37671826

Abstract

Objectives:

Dysfunctional beliefs about sleep are associated with components of sleep health but their association with global sleep health is understudied. Beliefs about sleep may systematically vary by race, which may influence the association between dysfunctional beliefs about sleep and global sleep health. This study aimed to investigate whether race influences the association between dysfunctional beliefs about sleep and global sleep health.

Methods:

Data were collected as part of an online survey. Participants were Black (n=181) and White (n=179) adults who were matched on age, self-reported sex, and level of education. Global sleep health was measured using the RU-SATED and dysfunctional beliefs about sleep were measured using the DBAS-16. Moderation analyses were conducted to investigate whether race moderated the association between DBAS-16 total and subscale scores and RU-SATED total scores.

Results:

Race moderated the associations between DBAS-16 total score and subscale scores and RU-SATED total score (b=0.54,p<.001). Higher DBAS-16 scores were significantly associated with lower RU-SATED scores in the White sample while this association was not significant in the Black sample, except for the Sleep Expectations subscale, where the association was not significant in the White sample and it was significant in the Black sample.

Conclusions:

These findings highlight that the association between dysfunctional beliefs about sleep and global sleep health may systematically vary by race which may have implications for promoting sleep health equity in racial minority populations through clinical and advocacy work. Future studies are needed to investigate what specific factors may be impacting these unique associations.

Keywords: Sleep health, Racial minorities, Dysfunctional Beliefs about Sleep, Racial Disparities

Global sleep health is a multidimensional construct that includes various dimensions including regularity, satisfaction, alertness/sleepiness, timing, efficiency, and duration (Buysse, 2014; Dzierzewski, Donovan, et al., 2021). Sleep health conceptualizes sleep from a health perspective rather than from a deficit perspective, and views sleep as a health behavior that is influenced by biological, psychological, and social factors (Ando & Kawakami, 2012; Baglioni et al., 2011; Baron et al., 2017; Bistricky et al., 2021; Calhoun et al., 2011; Cappuccio et al., 2011; Dzierzewski, Sabet, et al., 2021; Hoevenaar-Blom et al., 2011; Lallukka et al., 2018). One potential psychological factor that may be associated with sleep health is an individual’s beliefs about their sleep. Dysfunctional beliefs about sleep are theorized to play an essential part in the maintenance of insomnia disorder, a disorder which can involve disruptions in dimensions of sleep health, most especially in efficiency, alertness, and duration (Thakral et al., 2020). Although dysfunctional beliefs about sleep have been most frequently studied in relation to insomnia, a small body of research has linked these beliefs with components of sleep health including worse sleep quality, increased sleepiness, and shorter sleep duration (Schneider et al., 2019; Song et al., 2022; Williams et al., 2017). Conceptually, dysfunctional beliefs about sleep could have a broader impact on sleep health, however, less is known about how dysfunctional beliefs about sleep are associated with global sleep health. Further investigation about the association between dysfunctional beliefs about sleep and global sleep health may elucidate this association, which may then inform future efforts to promote sleep health generally.

Because sleep health aims to account for biological, psychological, and social factors, there is increasing recognition of role of social and cultural factors on sleep processes and sleep-related behaviors (Grandner et al., 2016). Racial disparities in sleep have been observed across various studies, demonstrating significant differences in aspects of sleep health including differences in total sleep time, sleep quality, and sleep timing. For example, individuals who identify as Black have been observed to experience shorter sleep duration, poorer sleep timing, and poorer sleep quality than individuals who identify as White (Carnethon et al., 2016; Chen et al., 2015; Chung et al., 2021; Dzierzewski, Sabet, et al., 2021). Importantly, these disparities have been observed across the lifespan, including in school-aged children (Guglielmo et al., 2018). Moreover, these racial disparities in sleep and sleep health behaviors are associated with poorer health and functioning, including increased cardiometabolic risk and changes in blood pressure, hypertension, obesity, and diabetes (Grandner et al., 2016). Although race may be a proxy for broader systemic influences on sleep, such as systemic racism, racial disparities in sleep are an important target for researchers as they investigate factors relating to sleep health and how to promote greater sleep health equity in specific populations (Grandner et al., 2016).

Research investigating racial differences in dysfunctional beliefs about sleep have been limited, with one study finding increased dysfunctional beliefs about sleep in Black women when compared with White women (Grandner et al., 2013). Specifically, this study found that the sample of Black women were more likely to endorse that sleep was not important for health and that napping and having a TV in the bedroom were not harmful for sleep (Grandner et al., 2013). Some studies have demonstrated that increased dysfunctional beliefs about sleep within Black samples are associated with less frequent sleep hygiene behaviors and increased risk for obstructive sleep apnea (Nam et al., 2018; Williams et al., 2017). Race is an important context to include while investigating associations between dysfunctional beliefs about sleep and sleep health because it is currently unknown whether this association systematically varies by racial identity. Moreover, investigating whether this association systematically differs by race may allow researchers to have a starting point in investigating specific aspects of race or culture (e.g., sociocultural aspects of race, discrimination, neighborhood factors, etc.) that may be influencing the association between dysfunctional beliefs about sleep and sleep health (Grandner et al., 2016).

This study aimed to investigate whether the association between dysfunctional beliefs about sleep and sleep health varies by race by comparing this association between individuals who identify as Black and individuals who identify as White. Based on previous research, it was hypothesized that individuals who identified as Black would have increased dysfunctional beliefs about sleep, especially in the domains of sleep expectations, compared to White individuals. Moreover, it was hypothesized that the direction of the association would not systematically vary by race and that there would be a negative association between dysfunctional beliefs about sleep and global sleep health in Black individuals and White individuals.

Methods

Procedures

Data were collected through an online survey investigating sleep across the lifespan (ages 18-99) conducted in July and August 2020. Participants were recruited through Amazon’s Mechanical Turk (MTurk), provided electronic informed consent, and filled out a survey through Qualtrics where they responded to questionnaires regarding their sleep, pain, mental health, social functioning, and physical health, among others. On average, participants took 34.78 minutes to complete the survey. An online survey was an ideal environment for data collection because these data were collected during the COVID-19 pandemic and this procedure allowed for safe data collection. MTurk has demonstrated similar reliability as traditional survey methods, including paper and pencil methods (Buhrmester et al., 2011). Participants were informed of the purpose of the study and provided their informed consent. Participants were compensated $1.00 for their participation in the study. It has been observed that compensation amounts do not affect the quality of data received through MTurk (Buhrmester et al., 2011). Two validity checks were incorporated into the survey to ensure that participants were paying attention and responding honestly throughout the survey. First, in the middle of the survey participants were asked to give a specific answer to a question presented. Second, participants were asked to self-report their age at the beginning of the survey and then asked to report their birth year at the end. Consistency between self-reported age and birth year were checked to ensure that participants were consistent throughout the survey. Procedures and protocols for this study were reviewed and approved by the Institutional Review Board at Virginia Commonwealth University and was carried out in accordance with the Declaration of Helsinki.

Sample

Participants were drawn from a pool of 999 adults who were recruited through MTurk. Inclusion criteria for recruiting the 999 participants for the overall study included: (1) being 18 years of age or older, (2) residence within the United States of America, and (3) self-reported sex such that there were an equal number of men and women who were recruited into the study. Included in these analyses were individuals who identified as Black (n = 181) and individuals who identified as White who matched those who identified as Black on age (with a fuzz factor of 5), sex, and level of education (n = 179). Although individuals of other races and ethnicities were recruited into the study, the sample sizes for these groups were not large enough to conduct between-group analyses.

Measures

Dysfunctional Beliefs about Sleep Scale-16 (DBAS):

The Dysfunctional Beliefs about Sleep scale is a 16-item self-report questionnaire designed to assess several aspects of an individual's dysfunctional beliefs about sleep and has four subscales: sleep expectation, consequences of insomnia, worry about sleep, and medication (Morin et al., 2007). Each item asks participants to rate how much a statement corresponds to their personal beliefs (e.g., “I need 8 hours of sleep to feel refreshed and function well during the day”). Each item is rated on a 0-10 scale with 0 indicating “strongly disagree” and 10 indicating “strongly agree”. The average score of each subscale and the average score across all items were used for these analyses (Morin et al., 2007). Higher scores indicate increased dysfunctional beliefs about sleep. The Cronbach’s alpha for this measure in the current sample was 0.950.

RU-SATED Sleep Health Scale:

The RU-SATED self-report questionnaire (Buysse, 2014; Ravyts et al., 2021) is a 6-item scale designed to operationalize global sleep health by assessing various dimensions of sleep health including: regularity (consistent bedtime and waketime), satisfaction (feeling satisfied with quality of sleep), alertness during the day (able to make it through the day without needing to doze), timing (asleep or trying to fall asleep between 2:00AM and 4:00AM), efficiency (less than 30 minutes of wake time during the night), and duration (getting 7 to 9 hours of sleep per day). Participants are asked to report the frequency of how often they follow the above sleep health guidelines on a 3-point Likert type scale ranging from 0 (Rarely/Never) to 2 (Usually/Always). Higher scores indicate better sleep health. The Cronbach’s alpha for this measure in the current sample was 0.588.

Analyses

Analyses were conducted using SPSS v. 28. Moderation analyses were conducted using Hayes’ (2021) PROCESS macro for SPSS version 4. Prior to running the analyses, all assumptions of moderation were assessed. The moderator for each analysis was race (i.e., Black and White). The first moderation analysis examined whether and how race moderated the association between the DBAS-16 total score and RU-SATED total score. Subsequent moderation analyses were conducted using the same settings to investigate whether and how race moderated the association between each subscale of the DBAS-16 (i.e., sleep expectation, consequences of insomnia, worry about sleep, and medication) and RU-SATED total score.

Results

Participant demographics are reported in Table 1. In brief, participants were mostly middle-aged (Mage = 43.7) and male (59.6%) with a 4-year bachelor’s degree (53%). Black participants endorsed significantly more dysfunctional beliefs about sleep (t = −5.07, p <.001) and had significantly higher scores on each subscale of the DBAS-16 (all p’s <.001). There were no significant group differences between the Black and White participants in global sleep health (p > .05).

Table 1.

Demographic characteristics of the Black (n = 181) and White (n = 179) samples.

Characteristic (M (SD)) Black White Score
Range		 χ 2 , t,
F 		df p
Age, years 43.7 (15) 43.7 (16) 0.001 358 .999
Sex, female (n(%)) 59 (32.6%) 59 (32.8%) 0.031 - .985
Sex, male (n(%)) 108 (59.7%) 107 (59.8%) - - -
Sex, other (n(%)) 14 (7.7%) 13 (7.2%) - - -
Education, 4-year bachelor's (n(%)) 96 (53%) 96 (53.6%) 0.029 - .999
RU-SATED, total score 7.29 (2.1) 7.31 (2.6) 0-12 0.101 358 .920
DBAS, total score 6.7 (2) 5.6 (2.1) 0-10 −5.07 358 <.001
DBAS, Sleep Expectation subscale 7.2 (1.8) 6.5 (2.1) 0-10 −3.28 358 .001
DBAS, Consequences of Insomnia subscale 6.8 (2.1) 5.6 (2.3) 0-10 −5.43 358 <.001
DBAS, Worry About Sleep subscale 13.1 (4.7) 10.6 (5.1) 0-10 −4.79 358 <.001
DBAS, Medication subscale 6.5 (2.4) 5.4 (2.5) 0-10 −3.86 358 <.001
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Notes. DBAS = Dysfunctional Beliefs About Sleep Scale-16. Following established conventions, the average score across all items was used for the DBAS total score and the average score for each subscale was used for the subscale score.

Prior to conducting the moderation analyses, assumptions of moderation were checked. All variables were normally distributed and there was one univariate outlier detected, which was subsequently removed. Multivariate outliers were checked using Mahalanobis distance, with values above 13.82 indicating the presence of a multivariate outlier. There was one multivariate outlier detected and this outlier was subsequently removed, making the analysis sample 181 Black individuals and 179 White individuals who were matched on age, self-reported sex, and level of education. Multicollinearity was checked with bivariate correlations and no correlations were above 0.60, thereby indicating no evidence of multicollinearity. The residuals were also checked using a plot of the standardized residuals and the assumptions of normality, linearity, and homoscedasticity were all met.

To investigate whether and how race moderated the association between the DBAS-16 total score and global sleep health, Hayes’ (2021) PROCESS macro (Model 1) was used to generate 5,000 bootstrapped confidence intervals of the conditional effect. Because participants were matched on age, sex, and level of education, these potential confounding variables were not added to the analyses. The model was significant (R2 = .081, F (3,356) = 10.51, p <.001). DBAS total scores significantly predicted RU-SATED total score (b = −0.44, 95% CI [−0.60, −0.28], p <.001). Race significantly predicted RU-SATED total score and the interaction between DBAS total score and race was significant as well (b = −3.13, 95% CI [−4.63, −1.64], p <.001; b = 0.54, 95% CI [0.31, 0.77], p <.001, respectively). The interaction effect is visualized in Figure 1. There was a significant negative association between DBAS total scores and RU-SATED total score in the White sample and a non-significant positive association in the Black sample (b = −0.44, 95% CI [−0.60, −0.28], p <.001; b = 0.10, 95% CI [−0.07, 0.26], p =.255, respectively).

Figure 1.

Figure 1.

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The association between the DBAS total score and RU-SATED total score as moderated by race. The Black sample is represented with the solid black line, while the White sample is represented with the dashed black line. The asterisk indicates a significant association.

To investigate whether and how race moderated the association between the DBAS-16 subscale scores and global sleep health, Hayes’ (2021) PROCESS macro (Model 1) was used to generate 5,000 bootstrapped confidence intervals of the conditional effect. Each subscale analysis was conducted separately, such that each analysis had a subscale score as the predictor variable, race as the moderator variable, and RU-SATED total score as the outcome variable. Results are shown in Table 2, while the interaction effects are visualized in Figure 2 (panels a-d). Each overall model was significant. In each model the subscale score significantly predicted RU-SATED total score except for the Sleep Expectations subscale score. Moreover, race significantly predicted RU-SATED total scores in each model and the interaction term between the subscale score and race was significant in all models. In each interaction there was a significant negative association between the subscale score and RU-SATED total score in the White sample, and a non-significant positive association in the Black sample (Consequences of Insomnia: b = −3.10, 95% CI [−4.58, −1.61], p <.001; b = 0.52, 95% CI [0.30, 0.74], p <.001, respectively, Worry About Sleep: b = −2.39, 95% CI [−3.65, −1.12], p <.001; b = 0.22, 95% CI [0.12, 0.32], p <.001, respectively, Medication: b = −2.21, 95% CI [−3.48, −0.94], p <.001; b = 0.38, 95% CI [0.19, 0.58], p <.001, respectively), except for the Sleep Expectations subscale where there was a non-significant negative association in the White sample and a significant positive association between Sleep Expectation subscale scores and RU-SATED total score in the Black sample (b = −0.04, 95% CI [−0.20, 0.13], p =.638; b = 0.29, 95% CI [0.09, 0.49], p =.004; respectively).

Table 2.

Multiple regression using each subscale of the DBAS-16 to predict global sleep health as moderated by race (Black or White).

Variable b SE t
Constant 7.57 0.58 13.13***
Sleep Expectations Subscale −0.04 0.08 −0.47
Race −2.38 0.94 −2.53*
Race x Subscale Interaction 0.33 0.13 2.53*
Constant 9.49 0.46 20.42***
Consequences of Insomnia Subscale −0.39 0.08 −5.04***
Race −3.10 0.76 −4.10***
Race x Subscale Interaction 0.52 0.11 4.58***
Constant 9.68 0.40 24.40***
Worry About Sleep Subscale −0.22 0.03 −6.60***
Race −2.39 0.64 −3.72***
Race x Subscale Interaction 0.22 0.05 4.48***
Constant 8.87 0.42 21.18***
Medication Subscale −0.29 0.07 −4.08***
Race −2.21 0.65 −3.43***
Race x Subscale Interaction 0.38 0.10 3.84***
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Notes. *p <.05, **p <.01, ***p <.001. Each model included an individual subscale and was run in a separate analysis.

Figure 2:

Figure 2:

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The association between each subscale total score and RU-SATED total score as moderated by race. The Black sample is represented with the solid black line, while the White sample is represented with the dashed black line. The asterisks indicate a significant association.

Discussion

This study aimed to investigate whether race influenced the association between dysfunctional beliefs about sleep and global sleep health. Black participants endorsed significantly higher dysfunctional beliefs about sleep than White participants. The association between dysfunctional beliefs about sleep, each subscale score of the dysfunctional beliefs about sleep scale, and global sleep health systematically varied by race—Black or White. Specifically, there was a significant negative association in the White sample and a non-significant positive association in the Black sample in each model except for the Sleep Expectations subscale, where there was a non-significant negative association in the White sample and a significant positive association between Sleep Expectations subscale scores and RU-SATED total scores in the Black sample. This study adds to the field by demonstrating that the association between dysfunctional beliefs about sleep and global sleep health may systematically vary by race. This finding may have potential implications for public health initiatives that are aimed at promoting sleep health equity in racial minority populations and communities. Moreover, a key component of cognitive behavioral therapy for insomnia is addressing dysfunctional beliefs about sleep. If dysfunctional beliefs about sleep are not associated with poorer sleep health in Black individuals, as the findings from this study may suggest, then addressing those beliefs within the context of treatment may need to be modified. Importantly, these results need to be replicated and extended to other contexts, such as investigating whether an insomnia diagnosis affects these associations, to investigate these potential implications.

The association between dysfunctional beliefs about sleep and global sleep health in Black individuals is understudied. In one study of 252 Black individuals, increased dysfunctional beliefs about sleep were related to poorer sleep quality, an important aspect of sleep health (Nam et al., 2018). A qualitative study of beliefs about sleep in community dwelling Black individuals found that most believed that sleep was essential for good mental and physical health, but also found that many reported not getting enough sleep (Baron et al., 2019). Moreover, this study also found that many participants reported that TV helped them fall asleep and that napping and consuming caffeine were good for coping with lack of sleep, practices that are often thought to exacerbate sleep difficulties (Baron et al., 2019). Another qualitative study which investigated beliefs about sleep among Black women found that many believed that napping and having a TV in the bedroom were not harmful for sleep, practices that are commonly thought to exacerbate sleep difficulties (Grandner et al., 2013). However, there were no significant differences between the White women and Black women in this study in self-reported sleep quality, sleepiness, or duration. As such, it may be possible that beliefs which are thought to lead to sleep difficulties in one population may not have the same effect in other populations. This is further supported by the findings of the current study which observed that beliefs about sleep which are commonly thought to be “dysfunctional” were not associated with poorer sleep health in Black individuals. Thus, beliefs about sleep which are commonly viewed as dysfunctional may not be dysfunctional for all individuals, especially across races and cultures. As such, when working with clients, it would be prudent to investigate whether the beliefs an individual holds about their sleep are contributing to their poorer sleep health, rather than assuming that it must be the case. Moreover, further investigation is needed to determine how beliefs about sleep systematically vary by race and culture and how those beliefs interact with an individual’s sleep health.

One limitation of the current study is the cross-sectional design, which limits ability to draw any inferences regarding direction of associations (i.e., whether dysfunctional beliefs about sleep lead to poorer sleep health or vice versa). Moreover, this study did not include measures that may have been helpful in elucidating whether other factors, such as acculturation and other sociocultural, psychosocial, or socioeconomic factors, may be influencing the association between dysfunctional beliefs about sleep and global sleep health (Causadias et al., 2018). However, secondary data fits the exploratory nature of this study, as it aimed to investigate whether race influences the association between dysfunctional beliefs about sleep and global sleep health. The RU-SATED scale had a low Cronbach’s alpha, which suggests a low agreement between the items and may have increased the Type II error rate. However, it is important to note that a lower Cronbach’s alpha is somewhat expected for this scale, as it aims to operationalize a broad construct whose dimensions may have differing levels of association with one another.

This study utilizes a convenience sample recruited from the internet, which may limit the generalizability of the results, especially because access to MTurk may not be equally distributed across various groups. However, a convenience sample is well-suited for this study because of its exploratory and hypothesis-generating nature, as it aimed to explore whether the association between sleep health and beliefs about sleep is moderated by race (Jager et al., 2017). Another potential limitation of the current study is that only individuals who identified as Black and White were included, as other races and ethnicities may demonstrate alternative patterns of results. Follow-up studies should be conducted to investigate what aspects of race, such as sociocultural aspects, experiences with discrimination, acculturation, and other psychosocial and socioeconomic factors, may be influencing this association (Ahn et al., 2021). Moreover, few studies have investigated sleep health disparities in other racial and ethnic minorities generally and, as such, investigations into whether other races and ethnicities demonstrate similar or alternative patterns of results are needed (Ahn et al., 2021). Another potential limitation of this study is that there have been no studies done to investigate if the measures used in the present study are valid specifically for Black individuals. This is important because some important aspects of the constructs of interest may be different across cultures (Okazaki & Sue, 1995). Indeed, given that this study demonstrated no association between dysfunctional beliefs about sleep and poorer sleep health in Black individuals, it may be that the DBAS measure is not tapping into the same latent construct of dysfunctional beliefs about sleep in Black individuals. As such, further research is needed to investigate this issue.

This study aimed to investigate whether race impacts the association between dysfunctional beliefs about sleep and global sleep health. Race significantly influenced the association between dysfunctional beliefs about sleep and global sleep health. Investigating what aspects of race may be impacting this association, including sociocultural, psychosocial, or socioeconomic factors (Ahn et al., 2021) will add to the field’s knowledge base and may inform future interventions designed to promote sleep health in the general population.

Conflicts of Interest and Source of Funding:

This work was supported by the National Institute on Aging of the National Institutes of Health under Award Number K23AG049955 (PI: Dzierzewski). The authors report no conflicts of interest. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Dautovich serves as a sleep consultant for the National Sleep Foundation and Merck Sharp & Dohme Corp. Dr. Dzierzewski served on an advisory panel for Eisai Pharmaceuticals.

Data Availability Statement:

Data are available upon reasonable request to corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data are available upon reasonable request to corresponding author.

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