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. Author manuscript; available in PMC: 2023 Aug 15.
Published in final edited form as: J Affect Disord. 2022 May 18;311:440–445. doi: 10.1016/j.jad.2022.05.092

The role of beliefs about sleep in nightly perceptions of sleep quality across a depression continuum

Alison E Carney a,*, Delainey L Wescott b, Nicole E Carmona a, Colleen E Carney a, Kathryn A Roecklein b
PMCID: PMC9523734  NIHMSID: NIHMS1838060  PMID: 35597468

Abstract

Background:

Poor sleep quality is common in depression, but complaints of poor sleep quality are not necessarily tied to objective sleep, and the construct of sleep quality remains poorly understood. Previous work suggests that beliefs about sleep may influence sleep quality appraisals, as might sleep variability from night to night.

Objective:

We tested whether beliefs about sleep predict daily sleep quality ratings above and beyond nightly variability of actigraphy and diary-assessed sleep over the course of multiple nights.

Methods:

Eighty-eight participants aged 18–65 years across a depressive continuum completed sleep diaries and reported their sleep quality and mood each morning; actigraphy was also completed for 67 of those participants. Multilevel models were used to test previous night’s total sleep time and sleep efficiency as predictors of self-reported sleep quality (VAS-SQ) and mood (VAS-M), and whether unhelpful beliefs about sleep predicted VAS-SQ and VAS-M above and beyond the sleep variables.

Results:

Individuals across a depression continuum with greater unhelpful beliefs about sleep reported worse sleep quality and worse mood upon awakening, even when accounting for nightly variation in actigraphy or diary assessed total sleep time and sleep efficiency.

Conclusions:

These results suggest that people are influenced by unhelpful sleep beliefs when making judgements about sleep quality and mood, regardless of how well they slept the previous night. Working with these unhelpful sleep beliefs in cognitive behavioral therapy can thus promote better sleep and mood in people across the depressive continuum.

Keywords: Unhelpful sleep beliefs, Sleep quality, Sleep perception, Depression, Actigraphy

1. Introduction

Complaints of poor sleep quality are common in depression (Nutt et al., 2008) and are associated with a worsened sense of well-being (Lemola et al., 2013). However, the construct of subjective sleep quality is poorly understood (Hartmann et al., 2015; Harvey et al., 2008). Studies show that subjective sleep is dissociable from objective measures of sleep (e.g., polysomnography) in those with depression (Argyropoulos et al., 2003; Armitage et al., 1997; Rotenberg et al., 2000), and that subjective sleep quality is more closely related to self-reported sleep symptoms and mood than it is to objective sleep indices (Grandner et al., 2006; Hartmann et al., 2015). These findings raise questions about what the construct of subjective sleep quality actually refers to, and the factors that contribute to the way that people with depression perceive their sleep quality.

According to cognitive theory, unhelpful beliefs about sleep negatively impact how people perceive their sleep (Harvey, 2002). Specifically, people who hold rigid and unhelpful beliefs about sleep tend to worry about their sleep and monitor their environment for evidence of sleep loss (e.g., watching the clock to calculate sleep time); they are then more likely to notice confirmatory evidence and report experiencing greater sleep difficulties (Harvey, 2002; Tang and Harvey, 2004, 2006; Semler and Harvey, 2004, 2005, 2006). Unhelpful beliefs about sleep are well-documented in depression (Carney et al., 2014; Cook et al., 2021; Roecklein et al., 2013) and tend to be rigid, overgeneralized, and/or exaggerated in nature, such as the belief that a poor night’s sleep will interfere with sleep for the rest of the week, or the belief that 8 h of sleep are needed to feel refreshed and be able to function the following day (Morin et al., 2007; Carney et al., 2007).

Previous work shows that people who report experiencing sleep difficulties also tend to endorse more unhelpful beliefs about sleep than those without sleep complaints, regardless of the presence of objective sleep disturbance (Edinger et al., 2000). Studies also show that unhelpful beliefs about sleep are a closer predictor of fatigue severity than actigraphy-assessed sleep (Carney et al., 2014), suggesting that beliefs about sleep are more important in how people feel during the day than the duration of sleep they obtain the night prior. This empirical evidence suggests that unhelpful beliefs about sleep impact how people perceive their sleep and the way that they feel during the day (Carney et al., 2014; Edinger et al., 2000; Harvey, 2002).

Intraindividual (i.e., within-person) sleep variability may also be relevant to how people appraise their sleep quality. Studies show that intraindividual variability in sleep relates to self-reported fatigue (Harris et al., 2021; Smith et al., 2015), subjective well-being Lemola et al., 2013), and life satisfaction (Ness and Saksvik-Lehouillier, 2018). However, a remaining question is whether night-to-night variability in sleep relates to subjective sleep-quality. As there are individual differences in sleep needs (Chaput et al., 2018), identifying factors that contribute to sleep perception requires the assessment of intraindividual, or within-person, variability. Assessment of within-person variability in sleep quality also exposes nuance that otherwise may not have been detected using between-subjects analyses (e.g., Akerstedt et al., 2014; Harris et al., 2021; Pilz et al., 2018; Russell et al., 2016). For example, global perceptions of sleep quality may be subject to negative retrospective bias (e.g., Pilz et al., 2018), a problem that is especially relevant in depression (Podsakoff et al., 2003). Thus, testing the variability in the relationship between unhelpful sleep beliefs and sleep quality over the course of multiple nights is important in understanding factors that contribute to sleep perception in individuals with depression.

The central aim of this paper was to test whether unhelpful beliefs about sleep predict subjective sleep quality in individuals across a depression continuum, even when accounting for nightly variations in sleep length and sleep efficiency. We first explored whether intraindividual variations in total sleep time and sleep efficiency related to daily sleep quality ratings. As people with depression tend to adopt the belief that “more is better” when it comes to sleep (Carney et al., 2011; Roecklein et al., 2013), we expected that people would rate their sleep quality and mood upon awakening as better after nights when they slept longer and more efficiently, relative to their average. We then tested whether between-subject differences in unhelpful beliefs about sleep predicted daily sleep quality ratings above and beyond intraindividual variability in total sleep time and sleep efficiency. We hypothesized that unhelpful beliefs about sleep would predict daily subjective sleep quality ratings even when accounting for actigraphy-assessed sleep and diary-assessed sleep. As a secondary aim, we also examined whether intraindividual variations in sleep and unhelpful beliefs about sleep related to self-reported mood upon awakening. Given the research that supports a bidirectional relationship between sleep and mood (Baglioni et al., 2011), we expected that the findings would be consistent for both subjective sleep quality and mood upon awakening, such that unhelpful beliefs about sleep would predict both sleep quality and mood ratings.

2. Methods

2.1. Participants

Participants (N = 88) with either seasonal affective disorder (SAD), nonseasonal major depressive disorder (MDD), or nonseasonal, never depressed controls between the ages of 18 and 65 years were recruited via the Pitt+Me® Research Participant Registry from 2013 to 2019. To meet inclusion criteria for the SAD group, individuals were required to: (1) meet DSM-5 criteria for Major Depressive Disorder with Seasonal Pattern, assessed using the Structured Clinical Interview for DSM-5 (SCID; First, 2015), (2) have a total score ≥ 20 on the 29-item Structured Interview Guide for the Hamilton Rating Scale for Depression—Seasonal Affective Disorder Version (SIGH-SAD; Williams et al., 1992), and (3) have a score ≥ 5 on the SIGH-SAD subscale assessing atypical depressive symptoms, based on criteria outlined by Terman et al. (1990). Similarly, to meet criteria for the MDD group, participants were required to meet DSM-5 criteria for nonseasonal Major Depressive Disorder based on the SCID. Participants in the control group had no current or lifetime history of any depressive disorder. Participants were excluded if they reported any of the following: a substance-induced mood disorder or bipolar disorder on the SCID; sleep disordered breathing or narcolepsy on a self-report health questionnaire; or shift work 12 or more times in the past year on a self-report screening questionnaire. All participants provided informed consent.

2.2. Measures

2.2.1. Clinical assessment

All participants underwent a clinical assessment to determine if they met the study’s inclusion criteria. The Structured Clinical Interview for DSM-5 Research Version, Patient Edition With Psychotic Screen (First, 2015) was used to assess for lifetime mood disorder diagnoses and to screen for the aforementioned exclusionary criteria. The assessment was conducted by a graduate student or trained research assistant. The SCID is a widely used semi-structured interview that assesses current and lifetime Axis I Disorders, with good psychometric properties. Additionally, the SIGH-SAD (Williams et al., 1992) was used evaluate the severity of seasonal affective disorder symptoms (SAD). The SIGH-SAD is a semi-structured interview guide including 29 items that correspond to the 21-item Hamilton Rating Scale for Depression with 8 additional items assessing atypical depression symptoms. The SIGH-SAD is commonly used in the clinical assessment of SAD has been shown to have high interrater reliability (Rohan et al., 2016).

2.2.2. Dysfunctional beliefs and attitudes about sleep—16 item (DBAS-16)

The DBAS-16 (Morin et al., 2007) was included as a measure of unhelpful sleep-related beliefs, including beliefs about the consequences of insomnia, worries about sleep, expectations and causal attributions for insomnia. The 16 items are rated on a Likert scale ranging from 0 (strongly disagree) to 10 (strongly agree), and a mean item score is calculated with higher scores denoting more rigid beliefs about sleep. The DBAS-16 has good psychometric properties across both clinical and research samples, including internal consistency and convergent validity with other insomnia-related measures, and has demonstrated sensitivity and specificity for differentiating those with and without clinical levels of unhelpful sleep beliefs (Morin et al., 2007; Carney et al., 2010). Scores on the DBAS were included as a predictor of perceived sleep quality and mood upon waking.

2.2.3. Sleep diaries

Participants completed an electronic version of the Pittsburgh Sleep Diary (Monk et al., 1994) for an average of 8.9 nights (SD = 4.6) which included questions about the previous night’s sleep as well as daytime functioning on awakening. Participants were instructed to complete the sleep diaries each morning upon awakening to report on the previous night’s sleep. Specifically, participants answered questions about the previous night’s bedtime, time of sleep attempt, sleep onset latency (SOL), number of awakenings, wake after sleep onset (WASO), final wake time, risetime, and naps. From these questions, the following sleep indices were calculated: nightly time in bed (duration from bedtime to risetime), total sleep time (duration from sleep attempt to wake time, minus SOL and WASO), and sleep efficiency (total sleep time divided by time in bed). Additionally, the sleep diaries included four visual analogue scales (VAS) assessing perceived sleep quality (VAS-SQ) and mood (VAS-M). Each VAS was bipolar and consisted of a slider that was coded from 0 to 100. VAS-SQ was anchored by the terms “very bad” and “very good;” VAS-M was anchored by “very tense” and “very calm.”

2.2.4. Actigraphy

In addition to completing sleep diaries, actigraphy was included as an objective measure of total sleep time and sleep efficiency. Participants wore an Actiwatch Spectrum (Philips Respironics, Bend, OR, USA) on their nondominant wrist for an average of 11.8 nights (SD = 3.6). Data were recorded continuously and sampled in 30-s epochs. Sleep-wake variables were extracted using the Actiware software program (Philips Respironics) with total activity counts above the threshold sensitivity value of 40 counts/per epoch. Rest intervals were manually set using sleep diary information, event markers, and/or a cut-off of activity below 40 counts.

2.3. Procedure

Interested participants who provided informed consent to participate in the study were invited to complete a semi-structured interview, questionnaires, sleep diaries and actigraphy measures as part of their participation in the present study. All participants were assessed during the winter, between December 21st and March 21st. Those who were found eligible based on the clinical assessment went on to complete a battery of questionnaires including the DBAS-16 (and others not reported herein). At the end of their study visit, they were provided with the Actiwatch and instructions for electronic sleep diaries. Participants returned all study materials to the lab on completion after a maximum of 20 days. Ethics approval for all study procedures was provided by the Institutional Board at the University of Pittsburgh, and the research was conducted in accordance with the Declaration of Helsinki.

2.4. Statistical analyses

All statistical procedures were conducted using R Studio 1.1.463 (R Core Team, 2017). Unadjusted means and standard deviations of sleep and demographic variables were calculated. The ICCs for sleep quality and mood upon waking measured by the sleep diaries, 0.42 and 0.52 respectively, suggest that approximately half of the variance in these variables is accounted for by within-person variability. To account for multiple observations across several of our measures (i.e., actigraphy and sleep diary variables) within each participant, we used multilevel models with participant ID as a random effect to test previous night’s total sleep time and sleep efficiency as predictors of self-reported sleep quality (VAS-SQ) or mood (VAS-M). Separate analyses were conducted for actigraphy and sleep diary variables. Level 1 predictors included person-mean centered total sleep time and sleep efficiency to account for nightly variation in participants’ sleep. Level 2 predictors included between-person total sleep time and sleep efficiency (i.e., person-average across all observations), DBAS-16 scores, age and gender. Separate models including cross-level interactions between DBAS-16 scores and nightly total sleep time, and DBAS-16 scores and nightly sleep efficiency were entered and tested. Non-significant interaction terms were removed to accurately interpret estimates. Models were fitted with the nlme package using restricted maximum likelihood (REML; Pinheiro et al., 2022).

3. Results

3.1. Sample description

Of the 88 participants included in the study, 67 participants provided actigraphy data for analysis. Table 1 shows the sleep and demographic characteristics of the sample, disaggregated by group. Of note, the average DBAS-16 score exceeded clinical cut-off of 4, suggesting clinically significant unhelpful sleep beliefs in the current sample.

Table 1.

Demographic and sleep descriptive statistics for the samples.

SAD S-SAD MDD Control Total
Full sample
N 24 23 22 19 88
Age M(SD) 40.8 (13.4) 39.7 (13.6) 41.8 (15.3) 46.5 (13.8) 41.9 (14.1)
Women n (%) 21 (88%) 19 (83%) 15 (68%) 15 (79%) 70 (79%)
Men n (%) 3 (12%) 4 (14%) 7 (32%) 4 (21%) 18 (21%)
DBAS16 5.9 (1.5) 4.2 (1.4) 4.9 (1.6) 4.1 (1.2) 4.8 (1.6)
Sleep quality 48.4 (24.6) 56.1 (23.5) 57.1 (26.0) 70.3 (19.0) 57.8 (24.6)
Mood upon waking 50.0 (25.5) 57.5 (24.7) 62.3 (25.3) 74.0 (18.3) 60.6 (25.2)
Sleep diary total sleep time 7.3 (1.6) 7.1 (1.9) 7.3 (1.6) 6.9 (1.4) 7.2 (1.7)
Sleep diary efficiency 83% (13%) 84% (12%) 84% (11%) 83% (12%) 84% (12%)
# Sleep diary nights 8.2 (4.9) 9.6 (4.8) 8.3 (3.5) 9.8 (5.0) 8.9 (4.6)
Subsample with actigraphy
N 16 17 17 17 67
Age M(SD) 40.2 (13.4) 40.0 (13.9) 42.2 (15.5) 46.6 (14.3) 42.3 (14.3)
Women n (%) 14 (88%) 14 (82%) 12 (71%) 13 (76%) 53 (79%)
Men n (%) 2 (12%) 3 (18%) 5 (29%) 4 (24%) 14 (21%)
DBAS16 6.0 (1.5) 4.4 (1.4) 4.8 (1.4) 4.2 (1.2) 4.8 (1.5)
Sleep quality 46.4 (23.9) 55.9 (22.4) 58.1 (26.9) 71.5 (18.8) 58.2 (24.7)
Mood upon waking 50.5 (24.2) 56.6 (25.2) 64.1 (25.8) 74.9 (17.6) 61.6 (25.1)
Actigraphy total sleep time 7.5 (1.6) 7.3 (1.5) 7.5 (1.2) 7.5 (1.5) 7.4 (1.4)
Actigraphy efficiency 88% (5%) 88% (5%) 89% (5%) 89% (6%) 88% (5%)
# Actigraphy nights 12.0 (3.3) 12.2 (3.8) 11.2 (3.2) 11.6 (4.4) 11.8 (3.6)
Sleep diary total sleep time 7.3 (1.6) 7.1 (1.8) 7.3 (1.6) 7.1 (1.5) 7.2 (1.6)
Sleep diary efficiency 83% (12%) 83% (13%) 84% (9%) 83% (13%) 83% (12%)
# Sleep diary nights 10.4 (4.1) 12.0 (3.8) 9.9 (3.1) 12.0 (4.3) 11.2 (3.9)
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SAD – Seasonal Affective Disorder; S-SAD – Subsyndromal Seasonal Affective Disorder; MDD – Nonseasonal Depression; DBAS-16 – Dysfunctional Beliefs and Attitudes about Sleep.

3.2. Sleep quality

Using actigraphy, the longer (b = 0.04; β = 0.09; SE = 0.01; p = 0.002) and more efficient (b = 0.73; β = 0.11; SE = 0.20; p = 0.004) a person slept relative to their average, the better sleep quality they reported. These findings were replicated using sleep diary-assessed total sleep time (b = 0.04; β = 0.13; SE = 0.01; p = 0.013) and sleep efficiency (b = 0.57; β = 0.22; SE = 0.07; p < 0.001). Between-person sleep diary-assessed total sleep time was also significant; individuals who reported longer total sleep times on sleep diaries also reported greater sleep quality ratings (b = 0.08; β = 0.20; SE = 0.03; p = 0.006). Individuals with greater unhelpful sleep beliefs reported worse sleep quality even when accounting for nightly variation in actigraphy-assessed total sleep time and efficiency (b = −4.17; β = −0.24; SE = 1.37; p = 0.005; see Fig. 1) but not when accounting for diary-assessed total sleep time and sleep efficiency (b = −2.29; β = −0.21; SE = 1.16; p > 0.05). Neither cross-level interactions were significant and were removed prior to interpretation of within and between-person effects (see Table 2).

Fig. 1.

Fig. 1.

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Unhelpful sleep beliefs as a predictor of sleep quality with regression line controlling for sleep duration parameters.

Note: DBAS-16 – Dysfunctional Beliefs and Attitudes about Sleep; Standard errors for specific cut-offs are indicated by the vertical lines.

Table 2.

Multilevel models with unhelpful beliefs about sleep as a predictor of nightly sleep quality and mood upon awakening.

Sleep quality
 Mood upon waking
b (SE) 95% CI b (SE) 95% CI
Actigraphy Intercept 13.08 (40.63) −66.73–92.90 15.17 (41.48) −66.32–96.67
Total sleep time within-person 0.04** (0.01) 0.01–0.06 0.05*** (0.01) 0.03–0.07
Total sleep time between-person 0.05 (0.04) −0.03–0.14 0.09* (0.04) 0.00–0.17
Sleep efficiency within-person 0.73*** (0.20) 0.33–1.14 0.27 (0.20) −0.11 — 0.65
Sleep efficiency between-person 0.40 (0.55) −0.71–1.50 0.20 (0.57) −0.93–1.33
DBAS-16 −4.17** (1.37) −6.92 to −1.43 −3.57* (1.42) −6.40 to −0.74
Gender −2.74 (2.57) −7.89–2.40 −4.77 (2.66) −10.08–0.54
Age 0.27 (0.15) −0.03–0.56 0.36* (0.15) 0.06–0.67
Random effects
 σ2 327.72 119.72–370.32 298.77 264.51–337.48
 τ00 224.83 144.65–349.43 247.00 162.83–374.69
 N (Observations) 67 (587) 67 (587)
Sleep diary Intercept −10.72 (21.32) −52.58–31.14 18.67 (23.44) −27.35–64.69
Total sleep time within-person 0.04** (0.01) 0.02–0.06 0.04*** (0.01) 0.02–0.06
Total sleep time between-person 0.08** (0.03) 0.02–0.14 0.05 (0.03) −0.02–0.11
Sleep efficiency within-person 0.57*** (0.07) 0.42–0.72 0.24** (0.07) 0.08–0.38
Sleep efficiency between-person 0.41 (0.25) −0.09–0.92 0.22 (0.27) −0.32–0.77
DBAS-16 −2.29 (1.16) −4.59–0.02 −3.16* (1.28) −5.70 to −0.61
Gender −0.85 (2.26) −5.35–3.65 −1.51 (2.50) −6.48–3.46
Age 0.28* (0.13) 0.02–0.54 0.45** (0.14) 0.16–0.74
Random effects
 σ2 296.13 266.62–328.91 291.97 262.79–324.39
 τ00 220.29 152.52–318.17 280.40 194.89–434.76
 N (Observations) 88 (786) 88 (786)
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DBAS-16 – Dysfunctional Beliefs and Attitudes about Sleep.

p < .05.

p < .01.

p < .001.

3.3. Mood upon waking

Consistent with sleep quality findings, longer total sleep time relative to a person’s average, assessed using actigraphy (b = 0.05; β = 0.13; SE = 0.01; p < 0.001) and sleep diary (b = 0.04; β = 0.13; SE = 0.01; p < 0.001), was associated with better mood on awakening. Between-person actigraphy-assessed total sleep time was also significant; individuals who slept longer on average via actigraphy reported greater sleep quality ratings (b = 0.09; β = 0.19; SE = 0.04; p = 0.043) than those with shorter total sleep times. Whereas more efficient sleep relative to a person’s average measured by sleep diaries was associated with better mood upon waking (b = 0.24; β = 0.09; SE = 0.07; p = 0.002), sleep efficiency measured via actigraphy was not associated with better mood upon waking (b = 0.27; β = 0.04; SE = 0.20; p > 0.05). Individuals with greater unhelpful sleep beliefs reported worse mood upon waking even when accounting for nightly variation in actigraphy (b = −3.57; β = −0.21; SE = 1.42; p = 0.014) or diary-assessed (b = −3.16; β = −0.18; SE = 1.28; p = 0.016) total sleep time and sleep efficiency. Cross-level interactions were not significant and were removed prior to interpretation of within and between-person effects (see Table 2).

4. Discussion

Our main finding is that unhelpful beliefs about sleep predict self-reports of poor sleep quality and low mood upon awakening over the course of multiple nights, even when actual sleep duration from the previous night is taken into account. These are some of the first data to convincingly show that self-reports of sleep quality and negative mood in depression are, at least in part, a function of beliefs about sleep separate from actual behaviorally measured sleep duration and quality.

The finding that unhelpful beliefs about sleep predict self-reports of sleep quality, even when accounting for nightly variation in actigraphy-assessed sleep, suggests that, in depression, people with unhelpful beliefs about sleep may be less attuned to nightly variations in their sleep, and instead make global, belief-congruent appraisals of their sleep quality the next morning. This is further supported by our finding that unhelpful beliefs predict sleep quality when accounting for nightly variation in actigraphy-assessed sleep, but not when accounting for nightly variation in diary-assessed sleep. Given that sleep-diaries are completed retrospectively and rely heavily on one’s perception of the previous night of sleep, it makes sense that diary-assessed sleep relates to sleep quality ratings and remain a significant predictor when accounting for unhelpful beliefs about sleep. Together, our results suggest that people with depression who hold unhelpful beliefs about sleep tend to report experiencing worse sleep quality over the course of multiple nights, regardless of nightly variability in objective (i.e., actigraphy-assessed) sleep.

Our study supports cognitive theory and previous studies that emphasize the mechanistic role of unhelpful beliefs about sleep in driving sleep complaints (Edinger et al., 2000; Harvey, 2002). For example, the current results align with Edinger and colleagues’ 2000 study, which showed that regardless of evidence of objective sleep disturbance, people who endorse greater unhelpful beliefs about sleep also tend to also endorse sleep difficulties. The findings also provide nuance to the previously noted discrepancies between objective sleep (i.e., polysomnography) and subjective sleep (i.e., sleep diary-assessed sleep) in depression (Argyropoulos et al., 2003; Armitage et al., 1997; Rotenberg et al., 2000), and the finding that mood is a stronger predictor of self-reported sleep quality than actigraphy- or polysomnography-assessed sleep (Grandner et al., 2006; Hartmann et al., 2015). Together, the results suggest that the way in which people with depression appraise their sleep quality is, at least in part, reflective of their sleep beliefs.

Our study also shows that when people with depression sleep longer and more efficiently relative to their own nightly average, they tend to report having better sleep quality and feeling better upon awakening, suggesting that intraindividual variability in sleep is indeed relevant in sleep quality perception. Moreover, people who report sleeping longer on average on their sleep diaries also report having better sleep quality. These findings support the idea that people with depression make belief-congruent appraisals of their sleep quality. For instance, the finding that longer total sleep time was associated with better subjective sleep quality may be indicative of the widely held belief that “more is better” when it comes to sleep (Carney et al., 2014; Cook et al., 2021; Roecklein et al., 2013). Overall, these findings suggest that interindividual variability in sleep is important in sleep quality perception and supports the role of unhelpful beliefs about sleep in sleep quality perception.

The current results add to an existing body of literature that supports the importance of addressing unhelpful beliefs about sleep in depression. Sleep difficulties are a commonly reported symptom of depression and often go unaddressed in standard depression treatments (Carney et al., 2014). Moreover, unhelpful beliefs about sleep and sleep difficulties are frequently reported residual symptoms following cognitive therapy for depression, and they confer increased cognitive risk for depression relapse in the future (Carney et al., 2011). Although traditional depression therapies do not address unhelpful sleep-related beliefs, studies show improvements in unhelpful-sleep beliefs are associated with sustained depression remission (Bei et al., 2018), and that people tend to make more balanced sleep-quality appraisals after receiving treatment that targets unhelpful beliefs about sleep (Janků et al., 2020). Notably, the existing treatment studies in this area are limited to patients presenting with depression and insomnia, and further work is needed to test the hypothesis that treating unhelpful sleep beliefs in depression treatment would also be helpful for people with depression and other sleep-related problems. Together, unhelpful beliefs about sleep are associated with better sleep quality perceptions in depression, and our findings suggest that targeting unhelpful beliefs about sleep may be relevant when treating people with depression who complain of poor sleep.

The most notable strength of this study is that we assessed the relation between unhelpful beliefs about sleep, sleep quality, and mood over the course of multiple nights. While previous studies have used cross-sectional designs to show that unhelpful beliefs about sleep relate to sleep complaints (Edinger et al., 2000), our study is the first to show this relationship over the course of multiple nights. Given that there are well-documented issues associated with retrospective reporting bias in depression research (Podsakoff et al., 2003), and the nuance that is exposed in within-subjects analyses in sleep research (e.g., Harris et al., 2021), examining the associations between unhelpful beliefs about sleep and sleep quality over the course of multiple nights was an important next step to understanding the mechanistic role of unhelpful beliefs about sleep in sleep quality appraisals in depression.

A second strength of the study is that we assessed sleep using both actigraphy and sleep diaries. Actigraphy-assessed sleep and sleep-diary assessed sleep are separate constructs. Whereas actigraphy measures movement to estimate sleep, sleep diaries rely on experiential estimates. It is particularly notable that the results across the two methodologies converged, which increases our confidence in these findings.

The findings should also be interpreted with the following limitations in mind. First, our sample included people with a range of depressive symptomatology, including participants with seasonal affective disorder, nonseasonal major depressive disorder, and those without depression or a history of depression. Although this may limit conclusions about the generalizability of the results with respect to specific patient groups, our dimensional approach also conferred the benefits of sound variability across our measures and increased statistical power. To expand on these findings, further research should test whether these findings replicate in specific depression profiles, such as in people with nonseasonal major depressive disorder and those with seasonal affective disorder. A second limitation of our study is that we did not use the Consensus Sleep Diary, which is the recommended sleep diary by experts in the field (Carney et al., 2012). The Consensus Sleep Diary was not used in this study because the parent study of which the current data is drawn from commenced prior to the introduction of the Consensus Sleep Diary. However, sleep metrics assessed in this study are largely consistent with the Consensus Sleep Diary (Carney et al., 2012; Monk et al., 1994).

In conclusion, our findings suggest that unhelpful beliefs about sleep are important in how people appraise their sleep quality. They further suggest that individuals who hold unhelpful sleep beliefs may be less attuned to nightly changes in their sleep length, perhaps due to a global perception of poor sleep.

Acknowledgements

We express our gratitude to the individuals that participated in our research to make this manuscript possible.

Role of funding sources

We report that no funding agencies were involved in this study’s design, analyses, results, or conclusions.

Footnotes

CRediT authorship contribution statement

AC wrote the introduction and discussion of the manuscript. DW undertook the statistical analyses and results. NC wrote the methods section of the manuscript and provided intellectual contributions the paper. CC provided intellectual contributions to the paper. KR oversaw all operations and conducted a final quality check for publication. All authors contributed to and approved the final manuscript.

Declaration of competing interest

The authors declare no conflicts of interest.

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