Consecutive Nights of Moderate Sleep Loss Does Not Affect Mood in Healthy Young Males

Sleep loss causes mood disturbance in non-clinical populations under severe conditions, i.e., two days/nights of sleep deprivation or a week of sleep restriction with 4–5 h in bed each night. However, the effects of more-common types of sleep loss on mood disturbance are not yet known. Therefore, the aim of this study was to examine mood disturbance in healthy adults over a week with nightly time in bed controlled at 5, 6, 7, 8 or 9 h. Participants (n = 115) spent nine nights in the laboratory and were given either 5, 6, 7, 8 or 9 h in bed over seven consecutive nights. Mood was assessed daily using the Profile of Mood States (POMS-2). Mixed-linear effects models examined the effect of time in bed on total mood disturbance and subscales of anger-hostility, confusion-bewilderment, depression-dejection, fatigue-inertia, tension-anxiety, vigour-activity and friendliness. There was no effect of time in bed on total mood disturbance (F(4, 110.42) = 1.31, p = 0.271) or any of the subscales except fatigue-inertia. Fatigue-inertia was higher in the 5 h compared with the 9 h time in bed condition (p = 0.012, d = 0.75). Consecutive nights of moderate sleep loss (i.e., 5–7 h) does not affect mood but does increase fatigue in healthy males.

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Profile of Mood States: Racial Differences in a Delinquent Population

Psychological Reports ◽

10.2466/pr0.1978.43.2.348 ◽

1978 ◽

Vol 43 (2) ◽

pp. 348-350 ◽

Cited By ~ 3

Author(s):

Thomas J. Fagan ◽

Frank T. Lira

Keyword(s):

Young Adult ◽

Racial Differences ◽

Affective Responses ◽

Mood States ◽

Mood Disturbance ◽

Profile Of Mood States ◽

Total Mood Disturbance ◽

Recreational Programs ◽

Racial Balance

When affective responses of 40 white and 40 black young adult delinquents were compared, white delinquents scored significantly higher on four of the six factors, Confusion, Tension, Depression, and Fatigue. Also, white subjects obtained significantly higher total mood disturbance scores. Results are discussed in terms of the racial balance of the institution, number of previous legal contacts, pre-confinement affiliations with other inmates, and failure or inability comfortably to pursue clinical and recreational programs aimed at reducing tension associated with incarceration.

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Effect of Various OR Noise on Fine Motor Skills, Cognition, and Mood

Surgery Research and Practice ◽

10.1155/2019/5372174 ◽

2019 ◽

Vol 2019 ◽

pp. 1-5 ◽

Cited By ~ 2

Author(s):

Cara Marie Rogers ◽

Hannah Palmerton ◽

Brian Saway ◽

Devin Tomlinson ◽

Gary Simonds

Keyword(s):

Operating Room ◽

Verbal Learning ◽

Mood States ◽

Mood Disturbance ◽

Fine Motor ◽

Profile Of Mood States ◽

Total Mood Disturbance ◽

Motor Dexterity ◽

The Impact ◽

Surgeon Performance

Background. The amalgam of noises inherent to the modern-day operating room has the potential of diluting surgeon concentration, which could affect surgeon performance and mood and have implications on quality of care and surgeon resilience. Objective. Evaluate the impact of operating room environmental noises on surgeon performance including fine motor dexterity, cognition, and mood. Methods. 37 subjects were tested under three different environmental noise conditions including silence, a prerecorded soundtrack of a loud bustling operating room, and with background music of their choosing. We used the Motor Performance Series to test motor dexterity, neuropsychological tests to evaluate cognitive thinking, and Profile of Mood States to test mental well-being. Results. Our results showed that typical operating room noise had no impact on motor dexterity but music improved the speed and precision of movements and information processing skills. Neurocognitive testing showed a significant decrement from operating room noise on verbal learning and delayed memory, whereas music improved complex attention and mental flexibility. The Profile of Mood States found that music resulted in a significant decrease in feelings of anger, confusion, fatigue, and tension along with decreased total mood disturbance, which is a measure of psychological distress. Loud operating room noise had a negative impact on feelings of vigor but no increase in total mood disturbance. Conclusion. Our results suggest that loud and unnecessary environmental noises can be distracting to a surgeon, so every effort should be taken to minimize these. Music of the surgeons’ choosing does not negatively affect fine motor dexterity or cognition and has an overall positive impact on mood and can therefore be safely practiced if desired.

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117 Comparison of Various Methods to Differentiate Resilience and Vulnerability to Sleep Loss Using Self-Rated Measures

SLEEP ◽

10.1093/sleep/zsab072.116 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A48-A48

Author(s):

Courtney Casale ◽

Erika Yamazaki ◽

Tess Brieva ◽

Caroline Antler ◽

Namni Goel

Keyword(s):

Sleep Loss ◽

Vulnerable Groups ◽

Sleep Restriction ◽

Average Score ◽

Profile Of Mood States ◽

Differential Impact ◽

Subjective Perceptions ◽

Time In Bed ◽

Average Change ◽

Open Question

Abstract Introduction There are robust, trait-like individual differences in subjective perceptions in response to sleep restriction (SR) and total sleep deprivation (TSD). How to best define neurobehavioral resilience and vulnerability to sleep loss remains an open question. We compared multiple approaches and cutoff thresholds for defining resilience and vulnerability using scores on the Karolinska Sleepiness Scale (KSS) and the Profile of Mood States Fatigue and Vigor (POMS-F and POMS-V) subscales. Methods Forty-one adults (33.9±8.9y;18 females) participated in a 13-night experiment (two baseline nights [10h-12h time in bed, TIB], 5 SR nights [4h TIB], 4 recovery nights [12h TIB], and 36h TSD). The KSS, POMS-F, and POMS-V were administered every 2h during wakefulness. Resilience and vulnerability were defined by the following: average score during SR1-5, average change from baseline to SR1-5, and variance during SR1-5. Resilient and vulnerable groups were defined by the following cutoffs: the top and bottom 12.5%, 20%, 25%, 33%, 50%, and +/-1 standard deviation. Bias-corrected and accelerated bootstrapped t-tests compared the scores of resilient and vulnerable groups during baseline and across SR1-5. Kendall’s tau correlations compared the ranking of individuals in each group (tau=0.4:moderate,0.7:strong). Results Resilient and vulnerable groups for POMS-F, as defined by all three approaches, significantly differed in their scores at all cutoffs during SR. However, only raw score and change from baseline approaches defined significantly different resilient and vulnerable groups during SR for KSS, and only raw score and variance approaches defined significantly different groups during SR for POMS-V. Notably, raw scores at baseline significantly differed between resilient and vulnerable groups for all measures. Correlations revealed moderate to strong associations between all three approaches at all cutoffs for POMS-F, between raw score and change from baseline approaches for KSS, and between raw score and variance approaches for POMS-V. Conclusion Defining resilience and vulnerability on self-rated measures by change from baseline was comparable to using raw score for KSS and POMS-F, whereas defining these groups by variance was comparable for POMS-F and POMS-V. Differences across methods may be due to the differential impact of SR on these various distinct subjective states. Support (if any) ONR Award No. N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488

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Raw scores on subjective sleepiness, fatigue, and vigor metrics consistently define resilience and vulnerability to sleep loss

SLEEP ◽

10.1093/sleep/zsab228 ◽

2021 ◽

Author(s):

Courtney E Casale ◽

Erika M Yamazaki ◽

Tess E Brieva ◽

Caroline A Antler ◽

Namni Goel

Keyword(s):

Sleep Loss ◽

Mood States ◽

Vulnerable Groups ◽

Sleep Restriction ◽

Profile Of Mood States ◽

Baseline Score ◽

Score Change ◽

Subjective Responses ◽

Subjective Sleepiness ◽

Karolinska Sleepiness Scale

Abstract Study Objectives Although trait-like individual differences in subjective responses to sleep restriction (SR) and total sleep deprivation (TSD) exist, reliable characterizations remain elusive. We comprehensively compared multiple methods for defining resilience and vulnerability by subjective metrics. Methods 41 adults participated in a 13-day experiment:2 baseline, 5 SR, 4 recovery, and one 36h TSD night. The Karolinska Sleepiness Scale (KSS) and the Profile of Mood States Fatigue (POMS-F) and Vigor (POMS-V) were administered every 2h. Three approaches (Raw Score [average SR score], Change from Baseline [average SR minus average baseline score], and Variance [intraindividual SR score variance]), and six thresholds (±1 standard deviation, and the highest/lowest scoring 12.5%, 20%, 25%, 33%, 50%) categorized Resilient/Vulnerable groups. Kendall’s tau-b correlations compared the group categorization’s concordance within and between KSS, POMS-F, and POMS-V scores. Bias-corrected and accelerated bootstrapped t-tests compared group scores. Results There were significant correlations between all approaches at all thresholds for POMS-F, between Raw Score and Change from Baseline approaches for KSS, and between Raw Score and Variance approaches for POMS-V. All Resilient groups defined by the Raw Score approach had significantly better scores throughout the study, notably including during baseline and recovery, whereas the two other approaches differed by measure, threshold, or day. Between-measure correlations varied in strength by measure, approach, or threshold. Conclusion Only the Raw Score approach consistently distinguished Resilient/Vulnerable groups at baseline, during sleep loss, and during recovery‒‒we recommend this approach as an effective method for subjective resilience/vulnerability categorization. All approaches created comparable categorizations for fatigue, some were comparable for sleepiness, and none were comparable for vigor. Fatigue and vigor captured resilience/vulnerability similarly to sleepiness but not each other.

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Mood State Changes Accompanying the Crossfit Open™ Competition in Healthy Adults

Sports ◽

10.3390/sports6030067 ◽

2018 ◽

Vol 6 (3) ◽

pp. 67 ◽

Cited By ~ 8

Author(s):

Allyson Box ◽

Yuri Feito ◽

Steven Petruzzello ◽

Gerald Mangine

Keyword(s):

Mood State ◽

Healthy Adults ◽

Mood States ◽

Mood Disturbance ◽

Profile Of Mood States ◽

Energy Index ◽

Total Mood Disturbance ◽

State Changes

Background: Specific mood states were examined during the CrossFit Open, a consecutive 5-week fitness competition involving five separate CrossFit® workouts, to determine whether the unique design or strenuous workouts of the competition resulted in acute and/or chronic mood state alterations. Methods: Participants (n = 8) completed the Profile of Mood States (POMS) questionnaire one-week prior to the competition (baseline), prior to (PRE), immediately post (IP), 30-min post- (30P) and 60-min post-workout (60P) each week. Tension, depression, anger, confusion, fatigue and vigor were derived from the POMS, as was Total Mood Disturbance (TMD) and an Energy Index (EI). Results: Workout intensity exceeded 93% HRmax each week. No differences were observed between baseline and PRE-workout mood states across weeks, indicating little effect of the unique competition design. Significant (week x time) interactions were observed for TMD (p = 0.037), EI (p = 0.038) and fatigue (p = 0.005). Acute mood state fluctuations were consistent across each week, where mood states improved to and beyond PRE values 60-min post-workout. Conclusions: In competitors, the differences in workout design between each week did not influence mood states. This may be related to adaptation to this style of training, while the acute mood state alterations are likely due to the workout intensity.

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Residual, differential neurobehavioral deficits linger after multiple recovery nights following chronic sleep restriction or acute total sleep deprivation

SLEEP ◽

10.1093/sleep/zsaa224 ◽

2020 ◽

Author(s):

Erika M Yamazaki ◽

Caroline A Antler ◽

Charlotte R Lasek ◽

Namni Goel

Keyword(s):

Sleep Deprivation ◽

Response Speed ◽

Sleep Loss ◽

Sleep Restriction ◽

Total Sleep Deprivation ◽

Psychomotor Vigilance Test ◽

Recovery Sleep ◽

Time In Bed ◽

Neurobehavioral Deficits ◽

Chronic Sleep

Abstract Study Objectives The amount of recovery sleep needed to fully restore well-established neurobehavioral deficits from sleep loss remains unknown, as does whether the recovery pattern differs across measures after total sleep deprivation (TSD) and chronic sleep restriction (SR). Methods In total, 83 adults received two baseline nights (10–12-hour time in bed [TIB]) followed by five 4-hour TIB SR nights or 36-hour TSD and four recovery nights (R1–R4; 12-hour TIB). Neurobehavioral tests were completed every 2 hours during wakefulness and a Maintenance of Wakefulness Test measured physiological sleepiness. Polysomnography was collected on B2, R1, and R4 nights. Results TSD and SR produced significant deficits in cognitive performance, increases in self-reported sleepiness and fatigue, decreases in vigor, and increases in physiological sleepiness. Neurobehavioral recovery from SR occurred after R1 and was maintained for all measures except Psychomotor Vigilance Test (PVT) lapses and response speed, which failed to completely recover. Neurobehavioral recovery from TSD occurred after R1 and was maintained for all cognitive and self-reported measures, except for vigor. After TSD and SR, R1 recovery sleep was longer and of higher efficiency and better quality than R4 recovery sleep. Conclusions PVT impairments from SR failed to reverse completely; by contrast, vigor did not recover after TSD; all other deficits were reversed after sleep loss. These results suggest that TSD and SR induce sustained, differential biological, physiological, and/or neural changes, which remarkably are not reversed with chronic, long-duration recovery sleep. Our findings have critical implications for the population at large and for military and health professionals.

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0304 Greater Slow-Wave Activity is Associated with Deteriorating Mood Across Sleep Restriction

SLEEP ◽

10.1093/sleep/zsaa056.301 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A115-A115

Author(s):

O R Larson ◽

C W Jones ◽

M Basner ◽

D F Dinges

Keyword(s):

Slow Wave ◽

Power Spectral Analysis ◽

Sleep Time ◽

Wave Activity ◽

Slow Wave Activity ◽

Mood Disturbance ◽

Sleep Restriction ◽

Linear Regression Models ◽

Time In Bed ◽

Rem Latency

Abstract Introduction Mood progressively deteriorates over consecutive days of sleep restriction. The neurobiological processes active during sleep that influence the risk of mood disturbance are unknown. This study investigated the relationships between physiological sleep parameters (i.e., slow-wave activity (SWA), slow-wave energy (SWE), rapid eye-movement (REM) sleep duration and latency), and self-reported measures of mood across sleep restriction. Methods N=181 healthy participants (48.1% female; 30±6.8 yrs) had valid polysomnography (PSG) and mood data. The study design included two baseline nights (8h time in bed [TIB]) followed by five nights of 4h TIB. PSG (EEG derivations C3-A2, Fz-A1, O2-A1) was collected on the second baseline night (B2), first night of 4h TIB (SR1), and the fifth night of 4h TIB (SR5). The Profile of Mood States was assayed on days following PSG. Power spectral analysis for SWE and SWA was conducted (delta power; band: 0.5-4.5 Hz). General linear regression models were used to independently assess the slope of SWE, SWA, percent REM of total sleep time (TST), and REM latency on mood disturbance across sleep restriction. Results At baseline, higher SWE (unadjusted; r=0.21; P=0.004) and SWA (unadjusted; r=0.19; P=0.007) were associated with greater mood disturbance; these relations were attenuated when adjusted for age and sex. No relation was found between mood and REM latency or REM percent of TST. The slope of mood disturbance from B2 to SR5 was associated with greater percentage increases in C3 SWA on SR5 relative to B2 (β=0.039; P=0.008); this association was not observed for SWE (β=-0.016; P=0.48). The slope of REM latency and REM percent of TST were not associated with the slope of mood disturbance. Conclusion Our results indicate that greater SWA due to sleep restriction was associated with greater mood disturbance, suggesting that less SWA may confer resilience to mood disturbances resulting from sleep restriction. Support This work was supported by National Institute of Health NIH R01NR004281 and National Space and Biomedical Research Institute NSRBI NCC 5-98.

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0291 Recovery Sleep Alleviates Mood Disturbance Following Chronic Sleep Restriction, Albeit Transiently and in a Dose-Dependent Manner

SLEEP ◽

10.1093/sleep/zsaa056.288 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A110-A110

Author(s):

A Mange ◽

C W Jones ◽

M Kaizi-Lutu ◽

M Basner ◽

D F Dinges

Keyword(s):

Linear Models ◽

Mood Disturbance ◽

Individual Growth ◽

Sleep Restriction ◽

Dependent Manner ◽

Growth Curve Models ◽

Recovery Sleep ◽

Time In Bed ◽

Sleep Physiology ◽

Dose Dependent

Abstract Introduction Fatigue is one contributor to mood disturbance observed following sleep restriction; however, the contribution of other factors remains unclear. This study examined contributions to mood disturbance resulting from sleep restriction beyond that of fatigue, evaluated the benefit of recovery sleep, and assessed whether recovery sleep buffered the re-emergence of mood disturbance upon re-exposure to sleep restriction. Methods N=223 healthy participants (48% female; n=108) approximately 30-years-old (SD=6.89, range=22–45 years) completed two baseline nights of 8h time in bed (TIB), followed by five nights of 4h TIB, and were then then randomized to one of 7 sleep recovery opportunities (i.e., 0, 2, 4, 6, 8, 10, or 12 hours TIB). Following the sleep period, a subset of participants (n=72) were re-exposed to five consecutive nights of 4h TIB. The profile of mood states (POMS) was completed every 2h during wakefulness and daily averages were calculated. The POMS total mood disturbance (TMD) score without the fatigue subscale (i.e., mood disturbance = TMD - fatigue) was the primary outcome to isolate changes in mood disturbance beyond fatigue. Individual growth curve models were applied to the trajectory of mood disturbance. General linear models were used to evaluate the dose-response function of mood disturbance after recovery sleep. Results Mood disturbance (absent the POMS fatigue scale) increased with each day of sleep restriction (β=1.550 per day; P<0.0001), and decreased with longer recovery sleep durations in a dose-dependent manner (β=-1.614 for every 2h increase; P<0.0001). The benefits of recovery sleep were abated by the second night of 4h sleep during re-exposure, where mood disturbance was slightly higher than that observed before recovery, but this difference was not statistically significant (β=0.046; P=0.85). Conclusion The study findings suggest that fatigue is not the only contributor to mood disturbance following sleep restriction. Recovery sleep attenuates mood disturbance in a dose-dependent manner, albeit transiently. Candidate pathways linking sleep restriction and mood include the immune system and the dynamics of sleep physiology. Support This work was funded by National Institute of Health NIH R01NR004281 and National Space and Biomedical Research Institute NSRBI NCC 5–98.

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0312 Performance on a Cognitive Interference Task in Children After One-Night of Sleep Restriction

SLEEP ◽

10.1093/sleep/zsaa056.309 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A117-A118

Author(s):

G de Queiroz Campos ◽

D P Dickstein ◽

M A Carskadon ◽

J M Saletin

Keyword(s):

Repeated Measures ◽

Sleep Loss ◽

Sleep Restriction ◽

Adhd Symptoms ◽

Cognitive Interference ◽

Interference Task ◽

Attentional Processes ◽

Short Sleep ◽

Time In Bed ◽

Fmri Session

Abstract Introduction Short sleep contributes to attention failure in conditions such as ADHD. Whether sleep loss affects attentional processes as a task varies in cognitive interference is unclear. We used a multi-source interference task (MSIT) in a sleep restriction paradigm in children with a range of ADHD symptoms to examine how short sleep disrupts attention in these youth. Methods Thirteen children (7F, 11.7±1.28 years) with a range of ADHD symptom severity completed a repeated-measures experiment on two consecutive nights in the laboratory: baseline (BSLN; 9.5h time-in-bed) and sleep restriction (SR; 4h time-in-bed). Each morning they took part in an fMRI session including the MSIT, in which participants respond to a series of 3-digit numbers by indicating which digit is different on no-interference (e.g., 003; correct=3) or interference (e.g., 311, correct=3) trials. Performance measures were inverse reaction time (1/RT) and accuracy. A two-way within-subject ANOVA assessed performance across interference and sleep conditions respectively. Results 1/RT showed main-effects of sleep loss (BSLN vs. SR; F(1,148)=4.01;p<0.05;η 2=0.026) and trial type (no-interference vs. interference; F(1,148)=24.7;p<0.001;η 2=0.143). Responses were slower for interference (BSLN RT: 799.3ms, SR RT: 895.8ms) than no-interference (BSLN RT: 653.2ms, SR RT: 697.4ms) trials. No interaction between interference and sleep loss was found (F(1,148)=0.11;p>0.05;η 2=0.001). Likewise, accuracy was lower (F(1,148) = 31.1, p<.001;η 2=0.174) in interference trials (73.5%) than in no-interference trials (92.2%), however with no effect of sleep loss, nor an interaction of interference and sleep loss (all p’s > .05). Conclusion These data provide evidence that partial sleep loss disrupts attention processes in children, yet these differences do not appear to depend on cognitive interference in our sample. Future analyses will examine whether ADHD symptoms distinguish individual differences, as well as analyze fMRI data to probe neural processes underlying attention control. Support K01MH09854 (to JMS); Brown University UTRA (to GDQC).

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Mood improvement in young adult males following supplementation with gold kiwifruit, a high-vitamin C food

Journal of Nutritional Science ◽

10.1017/jns.2013.12 ◽

2013 ◽

Vol 2 ◽

Cited By ~ 14

Author(s):

Anitra C. Carr ◽

Stephanie M. Bozonet ◽

Juliet M. Pullar ◽

Margreet C. M. Vissers

Keyword(s):

Young Adult ◽

Vitamin C ◽

Well Being ◽

Mood Disturbance ◽

Profile Of Mood States ◽

Dietary Intakes ◽

Adult Males ◽

Young Adult Males ◽

Lower Baseline ◽

Total Mood Disturbance

AbstractEnhanced intakes of fruit and vegetables have been associated with improved psychological well-being. We investigated the potential mood-enhancing effects of kiwifruit, a fruit rich in vitamin C and a number of other important micronutrients. Young adult males (n 35) were supplemented with either half or two kiwifruit/d for 6 weeks. Profile of Mood States questionnaires were completed at baseline and following the intervention. No effect on overall mood was observed in the half a kiwifruit/d group; however, a 35 % (P = 0·06) trend towards a decrease in total mood disturbance and a 32 % (P = 0·063) trend towards a decrease in depression were observed in the two kiwifruit/d group. Subgroup analysis indicated that participants with higher baseline mood disturbance exhibited a significant 38 % (P = 0·029) decrease in total mood disturbance, as well as a 38 % (P = 0·048) decrease in fatigue, 31 % (P = 0·024) increase in vigour and a 34 % (P = 0·075) trend towards a decrease in depression, following supplementation with two kiwifruit/d. There was no effect of two kiwifruit/d on the mood scores of participants with lower baseline mood disturbance. Dietary intakes and body status of specific micronutrients indicated a significant increase in the participants' vitamin C intakes and corresponding plasma levels of the vitamin. The results indicate that enhanced intake of kiwifruit by individuals with moderate mood disturbance can improve overall mood.

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