Poor sleep and cognitive bias

J Sleep Res. (2015) 24, 535–542

Poor sleep quality is associated with a negative cognitive bias and decreased sustained attention C H R I S T I N A M . G O B I N , J O N A T H A N B . B A N K S , A N A I . F I N S and JAIME L. TARTAR Division of Social and Behavioral Sciences and Center for Psychological Studies, Nova Southeastern University, Fort Lauderdale, FL, USA

Keywords International Affective Picture System, Cognition, Emotion Processing, Negativity Bias Correspondence Jaime L. Tartar, Nova Southeastern University, Farquhar College of Arts and Sciences, Division of Social and Behavioral Sciences, 3301 College Avenue, Fort Lauderdale, FL 33314, USA. Tel.: +1-954-262-8192; Fax: +1-954-262-3760; e-mail: [email protected] Accepted in revised form 22 March 2015; received 3 October 2014 DOI: 10.1111/jsr.12302

SUMMARY

Poor sleep quality has been demonstrated to diminish cognitive performance, impair psychosocial functioning and alter the perception of stress. At present, however, there is little understanding of how sleep quality affects emotion processing. The aim of the present study was to determine the extent to which sleep quality, measured through the Pittsburg Sleep Quality Index, influences affective symptoms as well as the interaction between stress and performance on an emotional memory test and sustained attention task. To that end, 154 undergraduate students (mean age: 21.27 years, standard deviation = 4.03) completed a series of measures, including the Pittsburg Sleep Quality Index, the Sustained Attention to Response Task, an emotion picture recognition task and affective symptom questionnaires following either a control or physical stress manipulation, the cold pressor test. As sleep quality and psychosocial functioning differ among chronotypes, we also included chronotype and time of day as variables of interest to ensure that the effects of sleep quality on the emotional and non-emotional tasks were not attributed to these related factors. We found that poor sleep quality is related to greater depressive symptoms, anxiety and mood disturbances. While an overall relationship between global Pittsburg Sleep Quality Index score and emotion and attention measures was not supported, poor sleep quality, as an independent component, was associated with better memory for negative stimuli and a deficit in sustained attention to non-emotional stimuli. Importantly, these effects were not sensitive to stress, chronotype or time of day. Combined, these results suggest that individuals with poor sleep quality show an increase in affective symptomatology as well as a negative cognitive bias with a concomitant decrease in sustained attention to non-emotional stimuli.

INTRODUCTION Although diminished cognitive performance after impaired sleep is a well-described phenomenon, little is known about the impact of poor sleep on emotion processing. However, poor sleep quality appears to be a critical factor in maintaining proper emotional functioning. For example, sleep disturbances are found in up to 80% of individuals with major depressive disorder, and poor sleep quality predicts the onset of major depression (Selvi et al., 2010). Despite the clear associations between sleep disturbances and impaired cognitive and psychopathological functioning, it is not known how sleep quality influences daytime cognitive processing of ª 2015 European Sleep Research Society

emotional stimuli. It is possible that poor sleep quality creates a cognitive bias in memory and interpretation for emotionally negative stimuli. This is similar to what is seen in clinical affective disorders – individuals with clinical affective disorders demonstrate increased sensitivity to emotionally negative stimuli (reviewed in Exelmans and Van Den Bulck, 2014; Hamann et al., 1999). In fact, a cognitive negativity bias towards emotionally negative stimuli is implicated in clinical depression (Watters and Williams, 2011). For example, a negative memory bias exists for emotional stimuli in clinically depressed patients who, relative to non-depressed controls, are more likely to remember sad faces (Ridout et al., 2003). These biases are also realized in semantic memory tasks

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where individuals with depression show a clear negative cognitive bias with better memory performance for negative words, especially when they are instructed to initially (during memory encoding) relate emotionally negative words to themselves (Bradley and Mathews, 1983; Denny and Hunt, 1992; Watkins et al., 1992). Like depression, emotionally negative biases are also seen in those with clinical anxiety. However, these biases are associated typically with enhanced automatic attention to threatening stimuli (Hamann et al., 1999). Findings of a memory advantage for negative stimuli in anxious individuals are mixed. Some studies show a clear memory advantage for negative stimuli in anxious individuals (Breck and Smith, 1983; Claeys, 1989), while other studies failed to find a memory advantage in anxious individuals (Bradley and Mathews, 1983; Mogg et al., 1989). Although sleep disturbances and increased sensitivity to emotionally negative stimuli are both thought to serve as risk factors for mood disorders, it is unclear if sleep loss is related directly to an increased emotional negative cognitive bias. It is possible that sleep loss directly alters the processing of emotional information, as sleep loss leads to emotional dysfunction with exaggerated responses to negative stimuli (Tempesta et al., 2010) and increased risk-taking behaviour (McKenna et al., 2007). Moreover, similar to findings in individuals with mood disorders, these sleep loss-associated impairments appear in spite of blunted affect (Talbot et al., 2010), impaired recognition of human emotions (Van Der Helm et al., 2010) and decreased emotional expressiveness (Minkel et al., 2011). An increased negative cognitive bias as a result of poor sleep quality is also likely, as emotion processing after sleep loss appears to be disinhibited, with increased sensitivity to emotional stimuli and increased ‘moodiness’ such as increased irritability, anger and hostility (Durmer and Dinges, 2005; Killgore, 2010; McCoy and Strecker, 2011; Taylor et al., 2013; Tsuchiyama et al., 2013). This is unlike sleep disturbance changes in cognitive processing such as attention and memory, where there is an obvious decrease in performance after sleep loss. In other words, the loss of function with non-emotional tasks appears to be associated with a general increase in emotionality. This agrees with the finding that following sleep loss prefrontal cortex (PFC)dependent sustained attention tasks are predominantly compromised (Lim and Dinges, 2008) and that attentional demands of emotional distractors can overwhelm PFC regions related to cognitive functioning and executive control (Chuah et al., 2010). The current study aimed to expand on these findings by testing the hypothesis that, relative to those with good sleep quality, those with poor sleep quality would show a greater negative cognitive bias measured through an increase in memory for emotionally negative pictures. We also tested the hypothesis that a PFC-dependent task of sustained attention would be compromised in those with poor sleep quality compared to those with good sleep quality. This is critical, as sleep impairments have been shown previously to cause

impairments in (non-emotional) sustained attention. Next, we tested the idea that an increase in affective symptoms in those with poor sleep quality would be related to a negative cognitive bias. We also ensured that we tested for potential confounding effects of stress sensitivity and chronotype. Because sleep loss lowers the threshold for the perception of stress (Minkel et al., 2012a) and can increase stress sensitivity (Meerlo et al., 2008), we examined the potential effect of stress on emotional and non-emotional task performance. Finally, as evening chronotypes show more psychological disturbances such as anxiety and depression (Hidalgo et al., 2009; Levandovski et al., 2011) and also report higher stress perception (Roeser et al., 2012), we ensured that any effects of sleep quality on emotional and non-emotional task performance were not attributable to time of day or chronotype effects. METHOD Participants A sample of 154 students [mean age = 21.27 years, standard deviation (SD) = 4.03, 104 females] completed all the tasks for this study. They were compensated with either 2 h of research credit for an introductory psychology course or a $20 Target gift card. A computer error resulted in the failure to save one participant’s data for the SART task. Also, one participant did not complete the Profile of Mood States (POMS) questionnaire. Both these participants’ other data were analysed for the study. In addition, two participants’ data were removed from the emotional task because they failed to complete the task as requested. Ethical approval was granted by the Nova Southeastern University Institutional Review Board, and written informed consent was provided by all the participants. Measures Sleep quality Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) (Buysse et al., 1989), a self-report instrument comprised of 19 items evaluating seven components of sleep over the past month: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, daytime dysfunction and use of sleep medications. Some of the items require open-ended responses that are recoded using a four-point scale; other questions require that respondents rate items using fourpoint Likert scales. The seven components can be summed to yield a global score that ranges from 0 to 21. Generally, higher scores indicate poorer sleep quality, and a global score greater than 5 is suggestive of poor sleep quality. The instrument exhibits adequate psychometric properties (Buysse et al., 1989). ª 2015 European Sleep Research Society

Sleep quality effects on attention and emotion Emotional memory A total of 120 negative and 120 neutral pictures were selected from the International Affective Picture System (IAPS). The IAPS is a collection of positive, negative and neutral pictures with standardized valences and ratings for each image (Lang et al., 2008). Only negative pictures with a valence of 3 or less were chosen as the negative stimuli for this study (mean valence rating = 2.36). The neutral pictures chosen for this study were selected in accordance with a valence rating of between 4 and 6 (mean valence rating = 5.20). Performance on this task was used as our measure of negative cognitive bias. We operationalized a negative cognitive bias as an increase in the correct recognition of negative images. This is in agreement with previous work that used increase in memory for negative stimuli as an indication of negative cognitive bias (Bradley and Mathews, 1983; Denny and Hunt, 1992; Watkins et al., 1992). Sustained attention Sustained attention was examined using the Sustained Attention to Response Task (SART). The SART is a Go/NoGo task in which participants must respond rapidly to all presented non-target stimuli but withhold a response to infrequent target stimuli (Robertson et al., 1997). In this SART task, the non-target stimuli consisted of numbers ranging from 1 to 9, with the exception of 3, which served as the target stimuli. The SART consisted of 1080 trials, composed of 960 non-target trials and 120 target trials. Target trials were presented randomly during the task. Accuracy on the task was measured as the total number of times that participants correctly withheld a response to the target trials. The SART took approximately 25 min to complete. Stress The stress manipulation was carried out using the coldpressor test (CPT). The CPT is a widely used and wellvalidated approach of inducing general stress. It was administered as a between-subjects measure with randomized assignment in which participants in the stress condition submerged their non-dominant hand in a bucket of ice-cold water (at most 5 °C) for at least 1 min (Lovallo, 1975). In the non-stress condition, participants submerged their non-dominant hand in lukewarm water (~25 °C) for at least 1 min. The four-item Visual Analog Scale (VAS) was used to as a manipulation check in order to determine if the participants perceived the cold/control pressor test to be stressful. A higher total score indicates greater subjective stress. Affective symptom questionnaires Transient mood states and depression, as well as state and trait anxiety, were assessed using the POMS, Center for Epidemiologic Studies Depression Scale (CES-D) and State– ª 2015 European Sleep Research Society

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Trait Anxiety Inventory (STAI) questionnaires, respectively. The POMS is a psychometrically sound instrument (McNair et al., 1971). The full-length version used in this study consists of 65 adjectives rated by participants on a five-point Likert scale that asked participants about their mood in the past week. The 65 items yield six subscales: anger–hostility, confusion–bewilderment, depression–dejection, fatigue–inertia, tension–anxiety and vigour–activity. A Total Mood Disturbance (TMD) score is also calculated based on the scores of each subscale. The CES-D is a short self-report measure shown to be reliable and valid across a variety of demographic characteristics in the general population (Radloff, 1977). This measure consists of 20 items asking questions about the frequency of symptoms associated with depression in the past week, with items rated on a four-point Likert scale. A score of 16 or greater is indicative of possible depression. The STAI is composed of 20 questions that tap stable aspects of an individual’s general predisposition to experience anxiety symptoms and 20 items that focus on transitory emotional/anxious arousal. Items are rated on a four-point Likert scale. The instrument shows adequate reliability and validity (Spielberger et al., 1983). The Morningness–Eveningness Questionnaire (MEQ) is a widely administered selfreport measure composed of 19 items used to determine if one’s peak sleepiness and alertness is in the morning or in the evening (Horne and Ostberg, 1976). Procedure Participants completed the MEQ online prior to coming in for the study. Each participant’s MEQ was scored to determine his/her chronotype. Participants were then assigned randomly to a morning or evening (09:00 or 21:00 hours) timeslot and a stress or non-stress condition. In the stress condition, participants completed the CPT. In the non-stress condition, participants completed the control pressor test. After the CPT or control test, each participant completed the VAS questionnaire. Next, participants rated a series of 120 picture stimuli (60 emotionally negative and 60 neutral pictures), presented from the IAPS in randomized order, without knowing that they would be tested later on their memory for those pictures. They were instructed to rate on a scale of 0–9 how positive, negative or neutral they perceived the pictures to be. A rating of 0 was ‘very negative’, 5 was ‘neutral’ and 9 was ‘very positive’. Rating the pictures ensured that the participants were paying attention to the pictures. Participants then completed the 25-min SART. Participants were then presented with the original 120-picture stimuli in addition to 120 new picture stimuli (60 new negative and 60 new neutral pictures) in randomized order. A response screen instructed the participants to indicate, via key press, whether each picture shown was either old (one from the previous exposure session; by pressing the ‘1’ key) or novel (by pressing the ‘2’ key). Finally, participants provided responses to the POMS, CES-D, STAI, PSQI and demographic questionnaires.

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Analyses A series of regression analyses were conducted to determine the effect of sleep quality (good versus poor) as measured by the PSQI total score and each of the components on target accuracy for the SART measure and on each of the emotional task measures (the percentage of correct recognition for negative and neutral stimuli and the percentage of false alarms for negative and neutral stimuli). To assess this, the subjective sleep quality component on the PSQI was first made categorical. This component assesses sleep quality using four different options: very good, good, bad and very bad. The choices ‘very good’ and ‘good’ were collapsed into an overall categorization of ‘good’ sleep quality. The remaining selections, ‘bad’ and ‘very bad’, were grouped together to create an overall classification of ‘poor’ sleep quality. Linear regressions were conducted to determine if the PSQI total score was a predictor of different affective symptom variables. Correlations between the affective symptom variables and the cognitive measures were examined. A mediation analysis was conducted to determine if the impact of sleep quality on the percentage of correct recognition for negative pictures was moderated by target accuracy. In addition, a stress manipulation check was conducted via analysis of variance (ANOVA) to determine an effect of the stress group on the VAS. Next, a series of one-way ANOVAs were conducted to assess the effect of stress on each of the SART measures and each of the emotional task measures. One-way ANOVAs were also conducted to determine the effect of MEQ (morning, intermediate and evening chronotypes) on the PSQI total score, CES-D, POMS subscales, POMS TMD score and STAI. Finally, separate 3 9 2 9 2 factorial ANOVAs were conducted to determine the effect of MEQ (morning, intermediate and evening chronotypes), stress (stress versus non-stress condition) and time tested (09:00 hours versus 21:00 hours) on each the SART measures as well as each of the emotional task measures. RESULTS

negative pictures relative to those with good sleep quality, as seen in Table 1. To test the hypothesis that the impact of subjective sleep quality on the percentage of correct recognition of negative pictures was due to depressive symptomology, trait anxiety or mood, a series of moderation analyses were conducted using the PROCESS MACRO in SPSS (Carciofo et al., 2014). In each analysis, we examined the interaction between subjective sleep quality and the affective symptom questionnaires. The interactions between subjective sleep quality and depressive symptomology, trait anxiety and mood were not found to be significant predictors, all Ps > 0.05. To determine if the impact of poor sleep quality on negative picture recognition was due to an increase in general overresponsiveness, we conducted similar regression analyses examining predictors of the percentage of correct recognition of neutral pictures, and false alarms for both negative and neutral pictures. Neither the overall PSQI score nor any of the PSQI components were found to be significant predictors for correct recognition of neutral pictures or false alarms for negative or neutral pictures, all Ps > 0.05. A linear regression showed that sleep quality, measured by the PSQI total score, was a significant predictor of total mood disturbances (b = 0.34, t = 4.39, P < 0.001), measured by the POMS total score. Additional linear regressions showed that from the POMS subscales, subjective sleep quality was a significant predictor of greater depressive symptoms (b = 0.30, t = 3.87, P < 0.001), greater tension (b = 0.20, t = 2.49, P = 0.01), less vigour (b = 0.36, t = 4.78, P < 0.001), greater confusion (b = 0.30, t = 3.84, P < 0.001) and greater fatigue (b = 0.30, t = 3.84, P < 0.001). Sleep quality was also found to be a significant predictor of greater depressive symptoms (b = 0.40, t = 5.34, P < 0.001), as measured by the CES-D total score. Finally, subjective sleep quality was shown to be a significant predictor of greater state

Table 1 The effects of sleep quality on the SART and the emotion task

Sleep quality and emotion A linear regression showed that the PSQI total score was not a significant predictor of the percentage of correct recognition for the negative pictures. To determine if any of the components serve as significant predictors of the percentage of correct recognition for the negative pictures, a standard multiple regression was conducted with the following scales entered as predictors: PSQI sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, sleep medication and daytime dysfunction. The regression was significant (R2 = 0.10, F(7,144) = 2.17, P < 0.05), with two significant predictors, subjective sleep quality (b = 0.21, t = 2.34, P < 0.05) and sleep medication (b = 0.19, t = 2.28, P < 0.05). Those with poor subjective sleep quality had a higher percentage of correct recognition for the

Dependent variable SART Emotion task

Target ACC Hits for neutral stimuli FA for neutral stimuli Hits for negative stimuli FA for negative stimuli

Good sleep quality

Poor sleep quality

Means

Means

a

SD

b

SD

66.88 86.85

24.61 13.47

52.25 83.90

23.82 11.91

13.14

13.47

16.10

11.90

84.87a

10.67

88.79b

6.67

10.79

6.54

13.45

9.20

Means between columns with differing superscripts are significantly different at P < 0.05 ACC, accuracy; RT, reaction time; FA, false alarms; SART, Sustained Attention to Response Task; SD, standard deviation.

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Sleep quality effects on attention and emotion anxiety (b = 0.21, t = 2.62, P = 0.01) and trait anxiety (b = 0.40, t = 5.36, P < 0.001), as measured by the STAI. Linear regressions showed that neither subjective sleep quality nor greater depressive symptoms, as measured by the CES-D total score, predicted ratings of neutral or negative pictures, all Ps > 0.05. Sleep quality and attention A linear regression showed that the PSQI total score was not a significant predictor for the SART target accuracy. To determine if any of the components serve as significant predictors of SART target accuracy a standard multiple regression was conducted with the following scales entered as predictors: PSQI sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, sleep medication and daytime dysfunction. The regression was significant (R2 = 0.127, F(7,145) = 3.01, P < 0.01), with subjective sleep quality serving as the only significant predictor of SART target accuracy (b = 0.33, t = 3.78, P < 0.001). Participants who reported good subjective sleep quality were better able to withhold their response to the target stimuli than those who reported poor subjective sleep quality, as seen in Table 1. Several significant correlations were found between the measures of anxiety, mood and depressive symptomatology and the percentage of correct recognition for negative and neutral pictures and target accuracy in the SART task. Target accuracy on the SART task was related to both state anxiety (r(152) = 0.18, P < 0.05) and the total POMS score (r(152) = 0.22, P < 0.01). Finally, target accuracy on the SART was related to the percentage of correctly recognized negative (r(151) = 0.19, P < 0.05) but not neutral pictures (r(152) = 0.08, P > 0.05). The relationship between target accuracy on the SART and the percentage of correct recognition for negative pictures is of interest, as both were predicted by the sleep quality components on the PSQI. As a result, we conducted a mediation analysis to determine if target accuracy on the SART mediated the relationship between sleep quality and negative picture recognition. Using the PROCESS MACRO in SPSS with 2000 bootstrapped samples for confidence intervals (Hayes, 2013), a significant indirect effect on sleep quality on correct negative picture recognition [indirect effect = 1.51, 95% bootstrapped confidence interval (CI): 3.131, 0.587], such that subjective sleep quality had a significant negative effect on target accuracy on the SART (b = 14.82, t(1) = 3.40, P < 0.001), and target accuracy on the SART impacted correct negative picture recognition (b = 0.10, t(1) = 3.23, P < 0.005). However, when controlling for the indirect effect, a significant direct effect was still evident (direct effect = 5.42, t = 3.11, P < 0.01, 95% bootstrapped CI: 1.97, 887). Chronotype and stress sensitivity factors A stress measure manipulation check was performed by looking at the effect of the stress condition on the VAS. A oneª 2015 European Sleep Research Society

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way ANOVA conducted to determine the effect of the stress group on the total VAS score revealed a significant difference, F(1,152) = 57.65, P < 0.000, gp² = 0.28. The stress group reported feeling more stressed (mean = 12.05, SD = 2.84) compared to the non-stress group (mean = 8.77, SD = 2.49). No significant effects of stress were found on target accuracy for the SART measure or on the emotional task measures (the percentage of correct recognition and the percentage of false alarms for negative and neutral picture stimuli), all Ps > 0.05. A significant one-way ANOVA revealed an effect of MEQ (morning, intermediate and evening chronotypes) on sleep quality (measured by the PSQI total score) in which evening chronotypes reported worse sleep quality compared with morning and intermediate chronotypes, F(2,153) = 6.52, P < 0.01, gp2 = 0.08, as seen in Table 2. Another one-way ANOVA revealed a significant effect of the CES-D in which evening chronotypes reported more depressive symptoms than morning and intermediate chronotypes, F(2,151) = 4.11, P < 0.05, gp2 = 0.05, as seen in Table 2. One-way ANOVAs also revealed a significant effect of MEQ on the tension (F(2,150) = 4.67, P < 0.05, gp2 = 0.06) and confusion (F(2,150) = 5.37, P < 0.01, gp2 = 0.07) subscales of the POMS as well as on the total POMS score (F(2,150) = 3.35, P < 0.05, gp2 = 0.04). Morning chronotypes reported the least total mood disturbance, tension and confusion compared to intermediate and evening chronotypes, as seen in Table 2. Another one-way ANOVA revealed a significant effect of MEQ on trait anxiety (as measured by the STAI) in which evening chronotypes reported the greatest trait anxiety, F(2,153) = 4.53, P < 0.05, gp2 = 0.06, as seen in Table 2. The affective symptom and chronotype scores broken down by good

Table 2 The effects of the MEQ on psychosocial functioning Morning

PSQI_TS CES-D POMS DEP POMS ANG POMS VIGR POMS FATG POMS TENS POMS CONF POMS TMD STA TA

Intermediate

Evening

Means

SD

Means

SD

Means

SD

5.38a 10.33a 3.81 3.14 12.81 6.76 5.29a 4.38a 10.57a 37.33 34.52a

3.44 8.05 6.31 4.04 7.85 6.77 4.88 3.52 26.74 12.71 10.40

6.48a 12.90 7.07 5.59 10.44 9.48 10.02b 7.59b 29.31b 43.40 39.35

2.44 7.76 8.82 6.87 6.05 6.57 7.03 4.56 31.38 13.30 9.01

7.84b 16.33c 5.84 3.95 9.57 9.75 8.41 8.10b 26.48 42.44 42.16c

3.01 10.11 8.01 4.35 6.63 6.88 6.04 4.64 27.98 11.51 10.36

Means between columns with differing superscripts are significantly different at P < 0.05. MEQ, Morningness–Eveningness Questionnaire; PSQI_TS, PSQI total score; DEP, depression; ANG, anger; VIGR, vigour; FATG, fatigue; TENS, tension; CONF, confusion; TMD, total mood disturbances; STA, state anxiety, TA, trait anxiety; CES-D, Center for Epidemiologic Studies Depression Scale; SD, standard deviation.

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versus poor subjective sleep quality groups are shown in Table 3. A 3 9 2 9 2 factorial ANOVA determining the effect of MEQ (morning, intermediate and evening chronotypes), stress (stress versus non-stress condition) and time tested (09:00 hours versus 21:00 hours) on target accuracy for the SART revealed no main effects or interactions, all Ps > 0.05. A series of 3 9 2 9 2 factorial ANOVAs conducted to determine the effect of MEQ (morning, intermediate and evening chronotypes), stress (stress versus non-stress condition) and time tested (09:00 hours versus 21:00 hours) on the percentage of correct recognition for the negative and neutral stimuli from the IAPS revealed no main effects or interactions, all Ps > 0.05. DISCUSSION An overall relationship between global PSQI score and emotion and attention measures was not supported. However, we found that the PSQI component of subjective sleep quality predicted increases in the correct recognition of emotional pictures. Compared to those who reported good sleep quality, participants who reported poor sleep quality showed a negative cognitive bias towards the stimuli with negative valence (with a greater percentage of hits for negative stimuli). The increase in the percentage of hits for negative stimuli does not appear to be due to a general over-responsiveness, as a similar effect was not observed for the false alarms to negative stimuli. Consistent with previous findings, we show that subjective sleep quality also predicts a decrease in performance on a sustained attention task (target accuracy). Also in agreement with previous work, we show that poor sleep quality has a negative effect on affective symptom measures – poor sleep quality relates to increased depressive symptoms, greater state and trait anxiety and higher total mood disturbance (increased tension, fatigue, confusion and less vigour). Although previous research suggest that stress sensitivity and chronotype would be important variables to consider in the impact of sleep perturbations on emotion processing, we did not find any stress, chronotype or time of testing effects on these measures.

Sleep quality and emotion Overall, our findings show a negative cognitive bias as well as an increase in affective symptomatology in those with poor subjective sleep quality relative to those with good subjective sleep quality. However, we did not find any relationship between affective symptomatology and our negative cognitive bias measure. This is perhaps surprising – especially for our measure of depressive symptomatology (CES-D), as depression has been implicated strongly in an increase in negative emotional memory recall (Bradley and Mathews, 1983; Denny and Hunt, 1992; Ridout et al., 2003; Watkins et al., 1992) and negative emotion biases are apparent in atrisk populations (Watters and Williams, 2011). It is possible that our results represent a boundary condition where the direct relationship between affective symptoms and emotional biases are not apparent in a subclinical not at-risk population. For example, in a memory recognition task using emotional pictures, no differences were found between a subclinical depressed population and a control group (Ramponi et al., 2010). The association of poor sleep quality with negative cognitive bias in the picture task agrees with previous work involving functional neuroimaging after sleep loss. In particular, as short-term sleep loss results in a hyperlimbic amygdala response (Yoo et al., 2007), enhanced amygdala activation is a potential pathway through which poor sleep quality can improve memory for emotional events. This is possible because enhanced amygdala activation can improve hippocampal-dependent memory to emotional information (Phelps, 2004). For example, enhanced activation of the amygdala during emotional stimuli presentation has been shown to enhance later memory recall for the emotional stimuli (Cahill et al., 1996; Hamann et al., 1999). Similar to our study, the sleep quality component of the PSQI has been shown to be a sensitive measure of maladaptive behaviour such as excessive video game-playing in adults (Exelmans and Van Den Bulck, 2014), increased mindwandering (Carciofo et al., 2014) and low positive affect (Bower et al., 2010). However, the strength of this component in predicating emotion processes is less clear. One study showed that the components of sleep disturbance, but not

Table 3 The effects of the MEQ on psychosocial functioning Morning

Intermediate

Evening

Dependent variable

Means

SD

n

Means

SD

n

Means

SD

n

CES-D POMS_TENS POMS_CONF POMS_TMD TAY

10.33 5.29 4.38 10.57 34.52

8.05 4.88 3.52 26.74 10.40

21 21 21 21 21

12.90 10.02 7.59 29.31 39.35

7.76 7.03 4.56 31.38 9.01

86 88 88 88 88

16.33 8.41 8.10 26.48 42.16

10.11 6.04 4.64 27.98 10.36

45 44 44 44 45

MEQ, Morningness–Eveningness Questionnaire; CES-D, Center for Epidemiologic Studies Depression Scale; POMS, Profile of Mood States; TENS, tension; CONF, confusion; TMD, total mood disturbances; TAY, trait anxiety inventory; SD, standard deviation.

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Sleep quality effects on attention and emotion sleep quality, was predictive of generalized anxiety (Almoznino et al., 2014). Although we did not find a relationship between sleep disturbance and anxiety, differences can be explained by the fact that we were measuring anxiety symptomology in a non-clinically anxious group. In agreement with our results, however, is a functional magnetic resonance imaging (fMRI) study which found a trend for the PSQI sleep quality component in predicting decreased subjective emotional responses (Minkel et al., 2012b). Sleep quality and attention In the current study, participants with poor subjective sleep quality also showed decreased target accuracy in the SART task, suggesting a decrement in their ability to sustain their attention and focus on the task at hand. Importantly, the mediation analysis demonstrated that despite the positive relationship between target accuracy and negative picture recognition, sleep quality still had a direct impact upon negative picture recognition when accounting for the indirect effect through sustained attention. These results build upon a previous report that sleep deprivation results in a failure to sustain attention and inhibit responses to negative stimuli (Anderson and Platten, 2011) by suggesting that individuals with poor sleep quality may also have a compromised ability to sustain their attention, in general, and correctly withhold responses for non-emotional stimuli. Chronotype and stress sensitivity factors The additional examination of the effects of stress, chronotype and time of day showed no effects on both the emotional memory and non-emotional sustained attention task. Consistent with previous research, however, evening types reported the worst sleep quality as well as greater depressive symptoms and trait anxiety. Morning types reported the least tension, confusion and total mood disturbances. In light of the finding that evening types reported higher self-perceived stress after the task than morning types (Roeser et al., 2012), it is uncertain why we did not see any effects of chronotype on task performance, especially after the stress manipulation. In addition, we did not see any relationship between subjective sleep quality, stress and task performance. This might have been due to the intensity of the cold-pressor test, as Minkel et al. (2012a) found that sleep deprivation increases the perception of stress in a low- but not a high-stress condition. Alternatively, short-term sleep deprivation might alter stress responses, but longer-term changes in sleep quality might not have a robust effect on stress perception.

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power. However, our main findings on the effects of subjective sleep quality on affective symptoms and performance on the emotional and non-emotional task are quite robust, with a large sample size and strong effect sizes. In addition, the effects seen here were tested in a limited sample of healthy college-aged students and may not be generalizable to older adults or clinical populations. Due to the limitations of the study design, it was not possible to determine if the negative cognitive bias was due to a difference in memory encoding or retrieval in the poor sleep quality group. However, previous work which showed a negative cognitive bias in depressed individuals suggests that the memory advantage is due to an enhanced encoding of the negative images (Bradley and Mathews, 1983). Finally, the current study did not examine the impact of sleep quality on recognition for pictures with positive valence. It is possible that poor sleep quality may decrease recognition for both positive emotionally positive images. CONCLUSION The present study showed the importance of good sleep quality on emotional memory, sustained attention and affective symptomatology. Specifically, poor sleep quality, as an independent component, was associated with better memory for negative stimuli (interpreted as such from the greater percentage of recognition hits) and a deficit in sustained attention to non-emotional stimuli. With regard to affective symptomology, individuals with poor subjective sleep quality were more likely to experience depressive symptoms, state and trait anxiety, total mood disturbances, tension, confusion, fatigue and less vigour. Of note, the effects of sleep quality do not appear to be mediated or affected by time of day, stress or chronotype. While our findings underscore the importance of sleep quality on emotion sensitivity and sustained attention for a normal college population, future research should incorporate neuroimaging technology to assess if these effects of sleep quality are attributed to decreased activation of the different areas in the brain implicated in emotion processing and sustained attention. ACKNOWLEDGEMENTS The authors wish to thank the anonymous reviewer and associate editor for their helpful comments and suggestions to improve the quality of the paper. This work was supported through a Nova Southeastern University President’s Faculty Research and Development Grant awarded to JT, AF and CG. AUTHOR CONTRIBUTIONS

Limitations We were unable to recruit a high number of morning types into the study. Thus, the comparisons on the interactions between chronotype, time of day and stress for the cognitive measures might have suffered from a lack of statistical ª 2015 European Sleep Research Society

CG, AF, JB and JT designed the study; CG performed the experiments; CG, AF, JB and JT analysed and interpreted the data. CG drafted the first version of the manuscript and AF, JB and JT edited the manuscript. All authors discussed the results and interpretations.

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REFERENCES Almoznino, G., Zini, A., Sharav, Y. et al. Sleep quality in patients with dental anxiety. J. Psychiatr. Res., 2014, 61: 214–222. Anderson, C. and Platten, C. R. Sleep deprivation lowers inhibition and enhances impulsivity to negative stimuli. Behav. Brain Res., 2011, 217: 463–466. Bower, B., Bylsma, L., Morris, B. and Rottenberg, J. Poor reported sleep quality predicts low positive affect in daily life among healthy and mood-disordered persons. J. Sleep Res., 2010, 19: 323–332. Bradley, B. and Mathews, A. Negative self-schemata in clinical depression. Br. J. Clin. Psychol., 1983, 22: 173–181. Breck, B. E. and Smith, S. H. Selective recall of self-descriptive traits by socially anxious and nonanxious females. Soc. Behav. Personal., 1983, 11: 71–76. Buysse, D. J., Reynolds, C. F. III, Monk, T. H., Berman, S. R. and Kupfer, D. J. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res., 1989, 28: 193–213. Cahill, L., Haier, R. J., Fallon, J. et al. Amygdala activity at encoding correlated with long-term, free recall of emotional information. Proc. Natl. Acad. Sci. USA, 1996, 93: 8016–8021. Carciofo, R., Du, F., Song, N. and Zhang, K. Mind wandering, sleep quality, affect and chronotype: an exploratory study. PLoS One, 2014, 9: e91285. Chuah, L. Y., Dolcos, F., Chen, A. K., Zheng, H., Parimal, S. and Chee, M. W. Sleep deprivation and interference by emotional distracters. Sleep, 2010, 33: 1305–1313. Claeys, W. Social anxiety, evaluative threat and incidental recall of trait words. Anxiety Res., 1989, 2: 27–43. Denny, E. B. and Hunt, R. R. Affective valence and memory in depression: dissociation of recall and fragment completion. J. Abnorm. Psychol., 1992, 101: 575–580. Durmer, J. S. and Dinges, D. F. Neurocognitive consequences of sleep deprivation. Semin. Neurol., 2005, 25: 117–129. Exelmans, L. and Van Den Bulck, J. Sleep quality is negatively related to video gaming volume in adults. J. Sleep Res., 2015, 24: 189–196. Hamann, S. B., Ely, T. D., Grafton, S. T. and Kilts, C. D. Amygdala activity related to enhanced memory for pleasant and aversive stimuli. Nat. Neurosci., 1999, 2: 289–293. Hayes, A. F. Introduction to mediation, moderation, and conditional process analysis: A regression based approach. The Guilford Press, New York, 2013. Hidalgo, M. P., Caumo, W., Posser, M., Coccaro, S. B., Camozzato, A. L. and Chaves, M. L. Relationship between depressive mood and chronotype in healthy subjects. Psychiatry Clin. Neurosci., 2009, 63: 283–290. Horne, J. A. and Ostberg, O. A self-assessment questionnaire to determine morningness–eveningness in human circadian rhythms. Int. J. Chronobiol, 1976, 4: 97–110. Killgore, W. D. Effects of sleep deprivation on cognition. Prog. Brain Res., 2010, 185: 105–129. Lang, P. J., Bradley, M. M. and Cuthbert, B. N. International Affective Picture System (IAPS): Affective Ratings of Pictures and Instruction Manual. Technical Report A-8. University of Florida, Gainesville, FL, 2008. Levandovski, R., Dantas, G., Fernandes, L. C. et al. Depression scores associate with chronotype and social jetlag in a rural population. Chronobiol. Int., 2011, 28: 771–778. Lim, J. and Dinges, D. F. Sleep deprivation and vigilant attention. Ann. N Y Acad. Sci., 2008, 1129: 305–322. Lovallo, W. The cold pressor test and autonomic function: a review and integration. Psychophysiology, 1975, 12: 268–282. McCoy, J. G. and Strecker, R. E. The cognitive cost of sleep lost. Neurobiol. Learn. Mem., 2011, 96: 564–582. McKenna, B. S., Dickinson, D. L., Orff, H. J. and Drummond, S. P. The effects of one night of sleep deprivation on known-risk and ambiguous-risk decisions. J. Sleep Res., 2007, 16: 245–252.

McNair, D. M., Lorr, M. and Droppleman, L. F. Manual for the Profile of Mood States. Educational and Industrial Testing Services, San Diego, CA, 1971. Meerlo, P., Sgoifo, A. and Suchecki, D. Restricted and disrupted sleep: effects on autonomic function, neuroendocrine stress systems and stress responsivity. Sleep Med. Rev., 2008, 12: 197–210. Minkel, J., Htaik, O., Banks, S. and Dinges, D. Emotional expressiveness in sleep-deprived healthy adults. Behav. Sleep Med., 2011, 9: 5–14. Minkel, J. D., Banks, S., Htaik, O. et al. Sleep deprivation and stressors: evidence for elevated negative affect in response to mild stressors when sleep deprived. Emotion, 2012a, 12: 1015–1020. Minkel, J. D., Mcnealy, K., Gianaros, P. J. et al. Sleep quality and neural circuit function supporting emotion regulation. Biol. Mood Anxiety Disord., 2012b, 2: 22. Mogg, K., Mathews, A. and Weinman, J. Selective processing of threat cues in anxiety states: a replication. Behav. Res. Ther., 1989, 27: 317–323. Phelps, E. A. Human emotion and memory: interactions of the amygdala and hippocampal complex. Curr. Opin. Neurobiol., 2004, 14: 198–202. Radloff, L. S. The CES-D scale a self-report depression scale for research in the general population. Appl. Psych. Meas., 1977, 1: 385–401. Ramponi, C., Murphy, F., Calder, A. and Barnard, P. Recognition memory for pictoral material in subclinical depression. Acta Psychol., 2010, 135: 293–301. Ridout, N., Astell, A., Reid, I., Glen, T. and O’Carroll, R. Memory bias for emotional facial expressions in major depression. Cogn. Emot., 2003, 17: 101–122. Robertson, I. H., Manly, T., Andrade, J., Baddeley, B. T. and Yiend, J. ‘Oops!’: performance correlates of everyday attentional failures in traumatic brain injured and normal subjects. Neuropsychologia, 1997, 35: 747–758. Roeser, K., Meule, A., Schwerdtle, B., Kubler, A. and Schlarb, A. A. Subjective sleep quality exclusively mediates the relationship between morningness–eveningness preference and self-perceived stress response. Chronobiol. Int., 2012, 29: 955–960. Selvi, Y., Aydin, A., Boysan, M., Atli, A., Agargun, M. Y. and Besiroglu, L. Associations between chronotype, sleep quality, suicidality, and depressive symptoms in patients with major depression and healthy controls. Chronobiol. Int., 2010, 27: 1813–1828. Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R. and Jacobs, G. A. Manual for the State-Trait Anxiety Inventory. Consulting Psychologists Press, Palo Alto, CA, 1983. Talbot, L. S., McGlinchey, E. L., Kaplan, K. A., Dahl, R. E. and Harvey, A. G. Sleep deprivation in adolescents and adults: changes in affect. Emotion, 2010, 10: 831–841. Taylor, N. D., Fireman, G. D. and Levin, R. Trait hostility, perceived stress, and sleep quality in a sample of normal sleepers. Sleep Disord., 2013, 2013: 735812. Tempesta, D., Couyoumdjian, A., Curcio, G. et al. Lack of sleep affects the evaluation of emotional stimuli. Brain Res. Bull., 2010, 82: 104–108. Tsuchiyama, K., Terao, T., Wang, Y., Hoaki, N. and Goto, S. Relationship between hostility and subjective sleep quality. Psychiatry Res., 2013, 209: 545–548. Van Der Helm, E., Gujar, N. and Walker, M. P. Sleep deprivation impairs the accurate recognition of human emotions. Sleep, 2010, 33: 335–342. Watkins, P. C., Mathews, A., Williamson, D. A. and Fuller, R. D. Mood-congruent memory in depression: emotional priming or elaboration? J. Abnorm. Psychol., 1992, 101: 581–586. Watters, A. J. and Williams, L. M. Negative biases and risk for depression; integrating self-report and emotion task markers. Depress. Anxiety, 2011, 28: 703–718. Yoo, S. S., Gujar, N., Hu, P., Jolesz, F. A. and Walker, M. P. The human emotional brain without sleep – a prefrontal amygdala disconnect. Curr. Biol., 2007, 17: R877–R878. ª 2015 European Sleep Research Society