Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Feb 1.
Published in final edited form as: Appl Nurs Res. 2021 Dec 12;63:151552. doi: 10.1016/j.apnr.2021.151552

A Systematic Review of Sleep Deprivation and Neurobehavioral Function in Young Adults

Stephanie Griggs 1, Alison Harper 2, Ronald L Hickman Jr 3
PMCID: PMC8766996  NIHMSID: NIHMS1765872  PMID: 35034695

Abstract

Aim:

To examine the effect of sleep deprivation (total and partial) on neurobehavioral function compared to a healthy sleep opportunity (7–9 hours) in young adults 18–30 years.

Background:

More than one-third of young adults are sleep deprived, which negatively affects a range of neurobehavioral functions, including psychomotor vigilance performance (cognitive), affect, and daytime sleepiness.

Methods:

A systematic review of randomized controlled trials (RCTs) on sleep deprivation and neurobehavioral function. Multiple electronic databases (Cochrane Central Registry of Controlled Trials [CENTRAL], PubMed, PsycINFO, CINAHL, and Web of Science) were searched for relevant RCTs published in English from the establishment of each database to December 31, 2020.

Results:

Nineteen RCTs were selected (N = 766, mean age = 23.7 ± 3.1 years; 44.8% female). Seven were between-person (5 were parallel-group designs and 2 had multiple arms), and 12 were within-person designs (9 were cross over and 3 used a Latin square approach). Total sleep deprivation had the strongest detrimental effect on psychomotor vigilance performance, with the largest effects on vigilance tasks in young adults in the included studies.

Conclusion:

Acute sleep deprivation degrades multiple dimensions of neurobehavioral function including psychomotor vigilance performance, affect, and daytime sleepiness in young adults. The effect of chronic sleep deprivation on the developing brain and associated neurobehavioral functions in young adults remains unclear.

Keywords: sleep, sleep deprivation, vigilance, systematic review, young adults

1. Introduction

Sleep loss has a negative effect on multiple neurobehavioral functions, such as psychomotor vigilance performance (cognitive), daytime sleepiness, and affect (Franzen et al., 2011; Van Dongen et al., 2003). Degradation of vigilance following sleep deprivation is one of the most robust alterations in healthy young adults aged 18–30 years (Lim & Dinges, 2010). Multiple dimensions of neurobehavioral impairment are differentially affected by sleep deprivation (Van Dongen et al., 2004). Sleep deprivation affects regions of the prefrontal cortex (Chee & Choo, 2004), which continues to mature up to the late ‘20s (Johnson et al., 2009), leading to executive dysfunctions with the prefrontal cortex (Dinges et al., 1997; Nilsson et al., 2005). The prefrontal cortex is most vulnerable to the effects between states of sleep and wake due to the metabolic change associated with sleep deprivation (Muzur et al., 2002).

Biological, social, and environmental factors converge, resulting in sleep deprivation in more than one-third (32.3%) of young adults (Peltzer & Pengpid, 2016). Sleep deprivation contributes to a negative interaction between homeostatic and circadian processes. In young adulthood, there is reduced homeostatic sleep pressure (adenosine) accumulation during wakefulness, a delay in sleep timing, and a delay in releasing the onset of melatonin that peaks in the mid-’20s (Crowley & Carskadon, 2010; Fischer et al., 2017). Motor vehicular accident risk increases at the circadian cycle nadir following total sleep deprivation which, correlates with slowing of psychomotor vigilance performance (Patanaik, Zagorodnov, Kwoh, et al., 2014).

The broad effect of sleep manipulation (sleep deprivation, sleep restriction, and sleep improvement) on cognitive functioning in adolescents aged 10 – 19 years was addressed in one previous systematic review (de Bruin et al., 2017). In the systematic review, the effect of total sleep deprivation was examined in 4 studies, partial sleep deprivation in 10 studies, sleep extension in one study, and cognitive behavioral therapy for insomnia in one study and 45 unique cognitive tests were reported where a vast array of cognition was assessed (de Bruin et al., 2017). In the review, partial sleep deprivation had a small or no effect on cognitive functioning, total sleep deprivation negatively affected psychomotor vigilance performance, and sleep extension improved working memory in the adolescents studied (de Bruin et al., 2017). However, conclusions could not be made about the specific domains affected by sleep manipulation due to the differences and quantity of tests (de Bruin et al., 2017). The extent of the associations between total and partial sleep deprivation and neurobehavioral impairment (e.g., decrements in psychomotor vigilance performance – cognitive performance impairment, affect, and daytime sleepiness) remains unclear.

2. Methods

The primary aim of this research was to determine the effect of sleep deprivation compared to healthy sleep opportunity (sleep duration 7–9 hours) on psychomotor vigilance performance as measured by psychomotor vigilance testing (PVT) only. PVT-related outcomes may include mean and median response time, reciprocal response time slowest 10%, mean reaction time fastest 10%, number of lapses (No. of times RT is > 500 ms lapses). The secondary aim of this research was to determine the effect of sleep deprivation on affect or daytime sleepiness compared to a healthy sleep opportunity. Secondary outcomes were change in affect or daytime sleepiness outcomes measured by diagnostic criteria or self-reported questionnaires.

Our focus is on young adults aged 18 to 30 years who are at a key developmental stage at a great risk of sleep deprivation and sleep deprivation-related neurobehavioral impairment. This focus addresses a significant gap in the existing literature. Additionally, the focus on sleep deprivation with a primary outcome of psychomotor vigilance performance to assess cognitive performance via psychomotor vigilance testing, a proven assay for evaluating vigilance (Dinges et al., 2004), will allow a common outcome to be synthesized across studies.

2.1. Design

The Preferred Reporting Items for Systematic Reviews and Meta-analyses Statement guidelines were followed for this systematic review (Nagendrababu et al., 2019). We registered our protocol with the PROSPERO registry before implementing the search in the International Prospective Register of Systematic Reviews (Prospero; registration number CRD42021225200).

2.2. Search methods

Studies with participants between the ages of 18 to 30 years were included. Sampling adults across the lifespan has a great potential to underestimate the effects of sleep deprivation in young adults. The following studies were included in this systematic review: (1) randomized controlled trials (RCTs) of young adults published in English; (2) data collected for both the intervention and control group(s); (3) sample mean age from 18 to 30 years; and (4) one or more objectively measured neurobehavioral-related outcomes (e.g., mean reaction time, median reaction time, reciprocal response time slowest 10%, mean reaction time fastest 10%, number of lapses (No. of times RT is > 500 ms lapses) by psychomotor vigilance testing only. Additionally, affect or daytime sleepiness outcomes were also extracted if available. We excluded studies of people with: (1) known sleep disorders; (2) chronic medical; (3) severe psychiatric illness (e.g., bipolar disorder, schizophrenia); (4) Body Mass Index (BMI) > 35 kg/m2 in addition to (5) night shift workers.

The following databases were searched with controlled vocabulary and keywords: Cochrane Central Registry of Controlled Trials (CENTRAL), PubMed, PsycINFO, CINAHL, and Web of Science. Articles published in English from the establishment of each database to December 13, 2020 were searched. We provide the PubMed search terms in Table 1. We adjusted the syntax for the search strategies for each database as appropriate.

Table 1.

Database: PubMed ALL Search Strategy

1 exp sleep deprivation
2 “total sleep deprivation”.mp.
3 “partial sleep deprivation”.mp.
4 1 or 2 or 3
5 “vigilance”.nip.
6 “cognitive”.mp.
7 5 or 6
8 4 and 7
9 limit 8 to “young adult” (19 to 44 years)
10 10 and 11
Open in a new tab

The search was conducted under the guidance of a health science librarian with input from the primary and senior investigator. Also, an ancestry/bibliographic search was conducted to identify additional articles until the end of December 2020.

2.3. Search outcome

All 4,149 references were imported to Covidence™ (Veritas Health Information) and duplicates were removed. A total of 3,110 were screened through Covidence™. Two reviewers independently screened all titles and abstracts with 93% agreement. Next, the two reviewers independently assessed full texts. A third reviewer resolved any disagreements regarding eligibility when consensus was not reached among the first two reviewers. The largest study was included when more than one article included the same trial and/or participants.

2.4. Quality appraisal

The risk of bias in the included studies was assessed independently by two reviewers using the Cochrane risk of bias tool through Covidence™ (Jørgensen et al., 2016). Sequence generation, concealment of allocation, blinding of outcome assessment blinding, >80% incomplete outcome data (< 80%), selective reporting of outcomes, and ‘other issues’ were the components of the risk of bias tool. The blinding domain was omitted as the intervention was sleep deprivation, and thus it would not be possible to blind participants.

2.5. Data abstraction and synthesis

A customized spreadsheet was used to extract and record data from the papers. Study characteristics, total or partial sleep deprivation with hours and length of time, age, measures used, the sample size (intervention and control groups), along with means and standard deviations of data were extracted. We contacted corresponding authors when insufficient or unclear data were reported. Extracted data were compared between the two reviewers, and disagreements were resolved by consultation with data in original papers and discussion.

We followed guidance on the conduct of a narrative synthesis described by Popay et al. (2006). Three standardized data tables were used to organize the data which included (1) all studies, (2) between-persons designs, and (3) within-person designs. We started with a preliminary synthesis to organize findings from the studies to describe patterns along with direction and size of the effect when effects were reported. Next, we explored relationships considering factors that might explain any differences in significance or direction/size of the effect if applicable. Lastly, we assessed the robustness of the synthesis to draw conclusions and assess generalizability/reproducibility of the findings. Significant PVT outcomes and the effect size if applicable are presented in Table 2. The between-person and within-person designs were considered and described separately as within-person comparisons have the advantage of a smaller within-person variation and possibility of a carryover effect (Jones & Kenward, 2014).

Table 2.

Characteristics of studies

Authors, reference Country Sample Age in years mean (SD) % female Sleep Measure/Setting Sleep deprivation condition Design PVT Outcome, (Effect Size)
Drake et al. 2001 US N=12 27.5 (5.4) 41.7 PSG/Lab 24-h TSD Latin square Mean RT* (NR)
Esposito et al. 2015 Italy N = 50 22 (2.1) 62 ACT/Lab 24-h TSD 1:1 Mean RT, Slowest 10% RT, Lapses, *** (NR)
Franzen et al. 2008 US N = 29 24.4 (2.8) 51.7 PSG/Lab 24-h TSD 1:1 MeanRT*(n2 = 0.17), Lapses** (n2 = 0.22)
Haavisto et al. 2010 Finland N = 20 23.8 (2.3) 0 PSG Lab 120-hPSD (4h/night) 1:1 Lapses* (NR)
Honn et al. 2020 a US N = 56 27.2 (4.6) 50.8 PSG/Lab 38-hTSD Latin square Fastest 10%, Median RT, Slowest 10% Sig NR
Honn et al. 2020 b US N = 26 25.9 (4) 38.5 PSG/Lab 62-h TSD Latin square Fastest 10%, Median RT, Slowest 10% Sig NR
Jewett et al. 1999 US N = 61 18–30 NR NR/Lab 24-h TSD Multi-arm Median RT, Slowest 10%, Median RT*** (NR)
Kaida et al. 2014 Japan N = 16 21.4 (1.6) 0 ACT/Home1 36-h TSD Cross-over Median RT** (NR)
Lin et al 2020 South China N = 24 21.4 (2.1) 66.7 PSG/Lab 24-h TSD Cross-over 1/RT *** (d=−0.98) Lapses***(d=1.34)
Patanaik et al 2014 Singapor e N = 135 21.9 (1.7) 51.1 ACT/Lab 24-h TSD Cross-over Mean RT, Median RT, Lapses *** (NR)
Robillar d et al. 2011 Canada N = 13 25 (2.7) 46.2 PSG/Lab 25-h TSD Cross-over Mean RT*** (NR)
Rossa et al. 2014. Australia N = 19 20.2 (2.1) 63.2 ACTVHome1 PSD (4h/1night) Cross-over Mean RT* (n2 = .24)
Schwartz et al. 2016 Germany N = 47 26 (6.8) 72.3 ACTVHome1 PSD (4h/1night) Cross-over 1/RT, Lapses (d=0.77)**
Schwartz et al. 2013 Germany N = 33 21.6 (2.7) 84.8 ACT/Home1 PSD (4h/1night) Cross-over Mean RT** (n2 =0.21)
Tempest a et al. 2014 Italy N = 25 23.8 (2.4) 56 NR/Lab 24-h TSD Cross-over NS (NR)
Tucker et al. 2009 US N = 84 25 (3.7) 26.2 ACT/Lab2 54-h TSD 1:1 Interaction TSD and Mean RT** (NR)
Van Dongen et al. 2004 US N = 22 26 (3.6) 9 PSG/Lab 72-h TSD Multi-arm Mean RT, Lapses** (NR)
Whitney et al. 2015 US N = 26 26.6 (4.4) 38.5 PSG/Lab 62-h TSD 1:1 Lapses*** (np2=0.53)
Yeo et al. 2015 Singapore N = 68 22 (2.5) 47.1 ACT/Lab 24-h TSD Cross-over Mean RT*** (NR)
Open in a new tab

Note: ACT, actigraphy; PSG, polysomnography; TSD, total sleep deprivation; PSD, partial sleep deprivation; Lab, controlled setting; 1:1 parallel group design; multi-arm, more than two experimental conditions - only the TSD condition is listed on the table when the study has multiple arms; NR: not reported. All studies were randomized controlled trials. Data from two studies are presented in one article.

a, b

Participants slept at home in an uncontrolled setting, but testing was conducted in a laboratory setting.

1

Participants in the control group slept at home and participated in PVT, Psychomotor vigilance testing, outside of a lab setting.

2

PVT outcomes, RT reaction time; 1/RT, reciprocal of mean reaction time; lapses (reaction time > 500ms).

*

p < 0.05,

**

p < 0.01,

***

p < 0.001.

3. Results

3.1. Study selection

We identified 19 RCTs and present results below. We contacted seven corresponding authors; two responded, one shared additional data, and one provided additional clarification on their data. The study selection process is illustrated in Figure 1.

Figure 1.

Figure 1.

Open in a new tab

PRISMA Flow Diagram

3.2. Characteristics of the included studies

A summary of the details of the 19 RCTs included in this systematic review is presented in Table 2. A total of 766 young adults with mean ages ranging from 20.2 to 27.5 years (mean age, 23.7 ± 3.09 years; 55.2% male) were included in these RCTs. BMI was only reported in one trial, and the mean was 20.0 ± 1.9 kg/m2. Seven were between-person (5 were parallel-group designs and 2 had multiple arms), and 12 were within-person designs (9 were cross over and 3 used a Latin square approach).

Sleep was measured via polysomnography in 9 studies and with actigraphy in eight studies (Table 2). The setting for a majority of these studies was a controlled laboratory (e.g., temperature, sound, avoidance of alcohol and caffeine) except for four studies (Kaida & Niki, 2014; Rossa et al., 2014; Schwarz et al., 2016; Schwarz et al., 2013). The RCTs were conducted in the following countries: the United States (8), Italy (2), Finland (1), Australia (1), Japan (1), South China (1), Singapore (2), Canada (1), and Germany (2). All RCTs had a sleep deprivation experimental condition (15 were total sleep deprivation ranging from 24 hours to 72 hours and four were partial sleep deprivation of 4-hours per night ranging from one night to four nights) and a healthy sleep opportunity (duration of 7–9 hours) comparison condition.

The dose-response effect of total and partial sleep deprivation on psychomotor vigilance performance was examined in three different RCTs (Drake et al., 2001; Jewett et al., 1999; Van Dongen et al., 2004). Acute sleep deprivation was assessed in two trials (Drake et al., 2001; Jewett et al., 1999) and chronic sleep deprivation in the other trial (Van Dongen et al., 2004). All trials had one 8-hour condition and one total sleep deprivation condition, but total sleep deprivation varied in each of the trials and was for one night in one trial (Jewett et al., 1999), two nights in the second trial (Drake et al., 2001), and three nights in the third trial (Van Dongen et al., 2004). The comparison groups also varied in dose and length with 8-hours, 5-hours, or 2-hours for one night (Jewett et al., 1999); 8-hours for four nights, 6-hours for four nights, and 4-hours for two nights (Drake et al., 2001); and 8-hours, 6-hours, or 4-hours per night for 14 nights (Van Dongen et al., 2004).

The daytime sleepiness measures used in the trials included a 9-item self-report Karolinska Sleepiness Scale (Akerstedt & Gillberg, 1990), 7-item self-report Stanford Sleepiness Scale (Babkoff et al., 1991), a visual analogue scale (Monk, 1989), and objective pupillography as a physiological daytime sleepiness indicator (Lüdtke et al., 1998). The affect measures included the 10-item positive and negative affect schedule (PANAS) (Watson et al., 1988), 100mm visual analogue profile of mood states (POMS) (McNair et al., 1971), and visual analogue scale (Tempesta et al., 2014).

3.3. Risk of bias

A graph summarizing the risk of bias of the included studies is presented in Table 3 and Figure 2. We determined that a majority of the studies were of high quality, with an overall low risk of bias (n = 8). Sequence generation was judged six times to be both low and high risk, as allocation of the participants was low risk, but the time in between the sleep deprivation trial and the control condition for cross-over studies was only a week; therefore, there was a high likelihood of carryover effects from sleep deprivation. Incomplete outcome data was unclear in 6 trials, and selective outcome reporting was unclear in one. Selective outcome reporting was determined to be both low risk and high risk as it was low risk for objective measures but high risk for self-reported measures like affect and daytime sleepiness. Other source of bias was high risk in four studies due to the trials being held outside of a controlled laboratory setting.

Table 3.

Cochrane Risk of Bias Assessment

Authors, reference Sequence generatio n Allocation concealme nt Blinding of outcome assessment Incomplete outcome data (< 80%) Selective outcome reporting Other source of bias
Drake et al. 2001 1 + − + + + + +
Esposito et al. 2015 + + + + + +
Franzen et al. 2008 + + + + + +
Haavisto et al. 2010 + + + + + +
Honn et al. 2020 a + + + + + +
Honn et al. 2020 b + + + + + +
Jewett et al. 1999 + + + + + +
Kaida et al. 2014 1 + − + + + + −
Lin et al 2020 + + + ? + +
Patanaik et al 2014 1,2 + − + + ? + − +
Robillard et al. 2011 + + + ? + +
Rossa et al. 2014.1 + − + + + + −
Schwartz et al. 2016 + + + + + −
Schwartz et al. 2013 1 + − + + ? + −
Tempesta et al. 2014 1,2 + − + + + + − +
Tucker et al. 2009 + + + + + +
Van Dongen et al. 2004 + + + + + +
Whitney et al. 2015 + + + ? + +
Yeo et al. 2015 2 + + + ? + − +
+ = low risk of bias ? = unclear risk of bias − = high risk of bias
Open in a new tab
a, b

Data from two studies are presented in one article.

1=

low risk for allocation, high risk for bias as there was only 1 week in between sleep deprivation and the control trial for the cross-over studies

2 =

low risk for objective measures, high risk for self-report measures

Figure 2.

Figure 2.

Open in a new tab

Cochrane Risk of Bias Assessment Across Studies (Higgins et al., 2011)

3.4. Effect of sleep deprivation by outcome

3.4.1. Effect of sleep deprivation on cognitive performance

The effect of total sleep deprivation on cognitive performance was tested in 6 RCT’s using a between-person comparison (n = 272); four were parallel-group (Esposito et al., 2015; Franzen et al., 2008; Tucker et al., 2009; Whitney et al., 2015) and two had multiple-arms (Jewett et al., 1999; Van Dongen et al., 2004). In these RCTs, the total sleep deprivation condition ranged from 24 hours to 72 hours, and all trials had a healthy sleep opportunity condition for comparison. Significant declines in psychomotor vigilance performance were observed in all trials using a between-person comparison with a slower mean reaction time in three trials (Drake et al., 2001; Esposito et al., 2015; Tucker et al., 2009; Van Dongen et al., 2004), increased slowest 10% in one trial (Esposito et al., 2015), and a higher number of lapses in four trials (Esposito et al., 2015; Franzen et al., 2008; Haavisto et al., 2010; Whitney et al., 2015). The effect sizes ranged from small (Franzen et al., 2008) to medium (Whitney et al., 2015) and were not reported in four between-person comparison trials (Esposito et al., 2015; Haavisto et al., 2010; Jewett et al., 1999; Tucker et al., 2009). In Haavisto’s trial of 20 young adults comparing 4 hours of partial sleep deprivation (n = 13) to healthy sleep opportunity (n = 7), lapses increased significantly for the partial sleep deprivation group compared to the healthy sleep opportunity group (0.92 ± 0.73 to 3.54 ± 0.73 vs. 0.62 ± 1.00 to 0.90 ± 1.00, p = .0321, respectively) and there was a tendency that the slowest 10% of all responses were slower in the partial sleep deprivation group, but the group difference was not significant (p = .16) (Haavisto et al., 2010).

The effect of total sleep deprivation on psychomotor vigilance performance was tested in nine RCT’s using a within-person comparison (n = 375) (Kaida & Niki, 2014; Lin et al., 2020; Patanaik, Zagorodnov, Kwoh, et al., 2014; Robillard et al., 2011; Rossa et al., 2014; Schwarz et al., 2016; Schwarz et al., 2013; Tempesta et al., 2014; Yeo et al., 2015), three of which used a Latin square approach (Drake et al., 2001; Honn et al., 2020). Total sleep deprivation ranged from 32 to 62 hours, and the cross-over between the sleep deprivation and healthy sleep opportunity conditions ranged from one week to one month. One night of total sleep deprivation resulted in significant decrements in psychomotor vigilance performance in four of the cross-over trials (Drake et al., 2001; Kaida & Niki, 2014; Patanaik, Zagorodnov, Kwoh, et al., 2014; Robillard et al., 2011) with a slower mean reaction time in four trials (Adler et al., 2017; Drake et al., 2001; Kaida & Niki, 2014; Patanaik, Zagorodnov, Kwoh, et al., 2014; Robillard et al., 2011), slower median reaction time in two of the trials (Kaida & Niki, 2014; Patanaik, Zagorodnov, Kwoh, et al., 2014), and a higher number of lapses in two of the trials (Lin et al., 2020; Patanaik, Zagorodnov, Kwoh, et al., 2014).

The difference was not significant between the total sleep deprivation and healthy sleep opportunity condition in Tempesta et al. 2014’s cross-over trial of 25 young adults (mean age 23.8 ± 2.4 years). In this trial, a 5-minute PVT on a computer was used when a 10-minute PVT was used in most studies which may have affected these outcomes (Tempesta et al., 2014). The reaction time was slower in the sleep deprivation condition in one trial; however, whether the difference between the two conditions was significant was not reported as the focus of the analysis was not on change in PVT performance (Honn et al., 2020). In the cross-over trials where significant decrements in psychomotor vigilance performance from total sleep deprivation were reported, effect sizes ranged from medium (Rossa et al., 2014) to large (Lin et al., 2020). The effect size was not reported in four trials (Drake et al., 2001; Kaida & Niki, 2014; Patanaik, Zagorodnov, Kwoh, et al., 2014; Robillard et al., 2011). Differences in age and sex were not discussed in all but two studies reported in one paper (Honn et al., 2020), where no significant group differences in age or sex were found (p = 0.24 and 0.26 respectively).

3.4.2. Dose-response effects on cognitive performance from sleep deprivation

The dose-response effect of sleep deprivation on psychomotor vigilance performance was tested in 3 RCTs (n = 121) (Drake et al., 2001; Jewett et al., 1999; Van Dongen et al., 2004). Greater psychomotor vigilance performance impairment was observed in all three trials with larger doses of sleep deprivation (Drake et al., 2001; Jewett et al., 1999). In Jewett’s trial of 61 young adults (0-hours, 2-hours, 5-hours, or 8-hours for one night), all PVT metrics improved as sleep duration increased (p < .0002), particularly between the 0-hour and 2-hour sleep conditions; however, only a slight improvement was observed between the 5-hour and 8-hour sleep conditions with a 2.14-hour decay mean rate for all PVT metrics. Chronic sleep deprivation (8-hours, 6-hours, 4-hours – time in bed (TIB) per night for 14 nights) resulted in cumulative dose-dependent deficits in psychomotor vigilance performance, and daytime sleepiness showed an acute response but did not differentiate between the 6-hour and 4-hour conditions in Van Dongen’s trial of 48 young adults (mean age 26 ± 3.6 y). In this same trial, deficits in cognitive performance were equivalent between the chronic sleep deprivation of sleep to 6-hours or less per night over 10 nights and up to 2-nights of total sleep deprivation conditions (Van Dongen et al., 2004). In Drake’s trial of 12 young adults using a Latin square design (no sleep loss-8 hours TIB for 4-nights; slow: 6-hours TIB hours for 4 nights; intermediate: 4-hours TIB for two nights; and rapid: 0-hours TIB for one night), higher impairment of cognitive performance impairment with rapid loss of sleep loss as opposed to when loss of sleep occurred or accumulated over time (Drake et al., 2001). Also, alertness levels were lower in the 6-hour per night condition relative to the 8-hour condition in the same trial (Drake et al., 2001). We present a dose response graph comparing pooled baseline to partial sleep deprivation conditions (6- and 4-hour sleep duration) and total sleep deprivation (0-hour sleep duration) mean reaction time as measured by the PVT over the days of monitoring in Figure 3.

Figure 3.

Figure 3.

Open in a new tab

Dose Response graph Note: 1 day = 24 hours; 0-hour time in bed is total sleep deprivation; 4 and 6-hour time in bed is partial sleep deprivation; and 8-hour time in bed is a healthy sleep opportunity.

3.4.3. Effect of sleep deprivation on daytime sleepiness

The effect of sleep deprivation on self-reported daytime sleepiness was assessed in 5 trials (n = 135) using a between-person comparison (Esposito et al., 2015; Franzen et al., 2008; Haavisto et al., 2010; Jewett et al., 1999; Van Dongen et al., 2004) and objective daytime sleepiness was additionally assessed in one of the trials (Franzen et al., 2008). Trials of total sleep deprivation (Esposito et al., 2015; Franzen et al., 2008; Jewett et al., 1999; Van Dongen et al., 2004) and partial sleep deprivation (Haavisto et al., 2010) resulted in significantly higher daytime sleepiness ratings in the sleep deprivation as opposed to the healthy sleep opportunity conditions. In comparison to the PVT, the largest magnitude of effects were seen in all measures of daytime sleepiness (2 objective and 1 self-report) in Franzen et al. 2008’s trial of 29 young adults following one night of total sleep deprivation (n = 15) compared to a healthy sleep opportunity condition (n = 14) (mean sleep latency test F = 25.08, p < .001, n2 = 0.501, pupillary unrest test F = 11.58, p = .002, n2 = 0.317, visual analogue scale F = 42.80, p <.001, n2 = 0.631).

The effect of total sleep deprivation on self-reported daytime sleepiness was assessed in 4 cross-over trials (Lin et al., 2020; Patanaik, Zagorodnov, Kwoh, et al., 2014; Tempesta et al., 2014; Yeo et al., 2015). Results were not reported in 3 trials (Patanaik, Zagorodnov, & Kwoh, 2014; Tempesta et al., 2014; Yeo et al., 2015). The effect of one night of total sleep deprivation on self-reported daytime sleepiness was only significant in one of the cross-over trials (F1,28.95 = 103.09; p < 0.01) (Tempesta et al., 2014); whereas a marginal increase in daytime sleepiness was noted in the other cross-over trial, but the effect was not significant (t = −1.890, p = 0.071, Cohen’s d = −0.39) (Lin et al., 2020). On the other hand, the effect of partial sleep deprivation (4-hours for one night) on self-reported daytime sleepiness relative to healthy sleep opportunity was significant in 3 cross-over trials with a medium effect size (Rossa et al., 2014; Schwarz et al., 2016; Schwarz et al., 2013). Also, the partial sleep deprivation as opposed to the healthy sleep opportunity condition displayed higher objective daytime sleepiness via the pupillary unrest test (5.7 ± 2.1 vs. 4.5 ± 2.1 mm/min, p = .002) with a medium effect size (Cohen’s d = 0.55) (Schwarz et al., 2016).

3.4.4. Effect of sleep deprivation on affect

The effect of sleep deprivation on affect was only assessed in one trial using a between persons comparison (Franzen et al., 2008). Those in the total sleep deprivation condition (n = 14) as opposed to the healthy sleep opportunity condition (n = 15) had a higher negative mood (F = 4.76, p = .039), lower positive affect (F = 4.78, p = .038), but the change in negative affect was not significant (F = 1.74, p = .20) (Franzen et al., 2008).

The effect of sleep deprivation on affect was assessed in 5 RCTs using a within-person comparison (n = 178) (Drake et al., 2001; Kaida & Niki, 2014; Lin et al., 2020; Rossa et al., 2014; Tempesta et al., 2014). The effect of one night of total sleep deprivation resulted in a significant negative effect on affect in 3 trials relative to the healthy sleep opportunity condition (Drake et al., 2001; Kaida & Niki, 2014; Lin et al., 2020). Compared to a healthy sleep opportunity, both positive affect and negative affect were significantly reduced when participants were totally sleep deprived in one cross-over trial (Lin et al., 2020) and partially sleep-deprived (4-hours one night) in another cross over trial (Rossa et al., 2014). The effect size was small in the partial-sleep deprivation cross over trial (Rossa et al., 2014), medium in one of the total sleep deprivation cross-over trials (Cohen’s d = 0.51) (Lin et al., 2020), and not reported in the other two trials (Drake et al., 2001; Kaida & Niki, 2014). Lastly, there was a significant interaction between sleep loss and negative affect in working memory performance, but not with PVT performance in Tempesta et al. (2014) ‘s cross-over trial of 25 young adults.

4. Discussion

In this systematic review, the effect of sleep deprivation on neurobehavioral functioning (psychomotor vigilance performance, affect, and daytime sleepiness) in young adults was examined. The primary aim of this study was to examine the effect of sleep deprivation on psychomotor vigilance performance. The largest effects with significant decrements on the most PVT metrics were found in total sleep deprivation studies (Drake et al., 2001; Esposito et al., 2015; Franzen et al., 2008; Honn et al., 2020; Jewett et al., 1999; Kaida & Niki, 2014; Lin et al., 2020; Patanaik, Zagorodnov, Kwoh, et al., 2014; Robillard et al., 2011; Tempesta et al., 2014; Tucker et al., 2009; Van Dongen et al., 2004). There was a dose-response relationship between the rate of sleep loss and psychomotor vigilance performance measured via PVT. Also, adaptation occurred with a slower accumulation of sleep loss (Drake et al., 2001; Jewett et al., 1999; Van Dongen et al., 2004). The short time constant that was observed in one of the trials (0h to 2h conditions) (Jewett et al., 1999) indicates that the first few hours of sleep may serve to restore psychomotor vigilance decrements following sleep deprivation. This may partially explain why a nap affords recovery disproportionate to its duration (Jewett et al., 1999).

The second aim of this systematic review was to determine how sleep deprivation affected daytime sleepiness. Daytime sleepiness was measured via self-report in a majority of the trials with the Karolinska Sleepiness Test or Stanford Sleepiness Test and objectively with the Multiple Sleep Latency Test and Pupillary Unrest Index (Lüdtke et al., 1998) in two trials (Franzen et al., 2008; Schwarz et al., 2016). Most of the trials included acute sleep deprivation, however in the trial where partial sleep deprivation was examined over 14-days (Van Dongen et al., 2004), chronic partial sleep deprivation of 4 – 6 hours resulted in an initial elevation of self-report ratings on both the Stanford Sleepiness Scale and Karolinska Sleepiness Scale, but as the study progressed only minor further increases in self-report daytime sleepiness that did not mirror the decrements in PVT performance were observed. Even at the end of the 14 days, participants only reported feeling slightly sleepy (Van Dongen et al., 2004). This suggests that there is an adaptation to chronic partial sleep deprivation especially considering the chronic partial sleep deprivation condition was compared to a total sleep deprivation condition ruling out the potential for a ceiling effect as the total sleep deprivation condition showed considerably greater levels of daytime sleepiness after two nights (Van Dongen et al., 2004). Another consideration when assessing daytime sleepiness is that it might be intertwined with affect and related to the same latent construct making it difficult to differentiate perceptions of daytime sleepiness from mood; therefore, it is warranted to include physiologic measures more sensitive than self-report measures as suggested by Franzen et al, 2008.

Regarding our final aim to determine the effect of sleep deprivation on affect, it must be highlighted that affect was only assessed in one-third of the studies. Also, the designs and instruments to measure affect varied, making it difficult to draw conclusions. Nonetheless, both partial and total sleep deprivation conditions resulted in worsened affect in the young adults in the selected studies, which is consistent with other young adult and adolescent studies (Baum et al., 2014; Franzen et al., 2008; Haavisto et al., 2010). Studies where objective physiological and/or neural measures of affect were assessed provide additional verification of the emotional dysregulation following sleep deprivation. This was demonstrated in two of the trials in the current review with additional measures of pupillary affective response (Franzen et al., 2008; Schwarz et al., 2016). In previous research, a 60% amplification in reactivity of the amygdala assessed using functional MRI (fMRI) was observed following one night of total sleep deprivation (n = 14) in response to negative pictures triggering emotions, when compared to a healthy sleep opportunity condition (n = 12) (Yoo et al., 2007).

Limitations

There are some limitations of this systematic review that should be considered. First, regarding sample characteristics, we included individuals free of medical, psychiatric, and sleep disorders with previous healthy weight and sleep schedules, limiting the generalizability of these findings. Second, although psychomotor vigilance performance was a common outcome across studies, only 6 used a parallel-group design, and with a lack of baseline and outcome data reporting, we could not conduct a meta-analysis. Baseline and some post-intervention values were not available to calculate mean change in these studies, so our results are fully based on a narrative review. Third, although outcomes were common via the PVT, the heterogeneity across designs, analyses, and objectives made the synthesis and analysis difficult. We recommend more transparent data reporting in the future, particularly through the inclusion of baseline data. This would allow for meta-analyses to be performed in the future, allowing the effects to be pooled to advance the science. Also, because of the different designs and analyses, a determination about reproducibility could not be made.

Objective assessments and physiologic measures (e.g., the Multiple Sleep Latency test and Pupillary Unrest Index) were more precise and sensitive, which may have affected the self-reported daytime sleepiness and affective outcomes. A larger effect size was reported for the physiologic measures (daytime sleepiness and affect regulation) as opposed to the self-report mood and PVT outcomes in one of the trials (Franzen et al., 2008).

5. Conclusions

We determined that sleep deprivation degrades young adults’ neurobehavioral functioning. These results are congruent with adult and adolescent studies, where total sleep deprivation (as opposed to partial sleep deprivation) has a substantial detrimental effect on psychomotor vigilance performance, with the largest effects for vigilance tasks (de Bruin et al., 2017; Lim & Dinges, 2010). The studies were all based on acute sleep deprivation, so it was not possible to determine if psychomotor vigilance deficits accumulate over time during chronic sleep deprivation, which is most consistent with real-world settings (Goel et al., 2009). This is important as young adult brains are sensitive to sleep loss, as indicated by imaging studies examining the prefrontal cortex (Chee & Choo, 2004). There is considerable evidence that the prefrontal cortex continues to develop into early adulthood which may affect speed of performance on psychomotor vigilance tasks, although this association has not been examined longitudinally (Chee & Choo, 2004; Gied et al., 1999; Muzur et al., 2002). Thus, the effects of chronic sleep deprivation on the psychomotor vigilance performance of the developing brain remain unclear. Also, though our primary intention was to assess the effect of sleep deprivation on psychomotor vigilance performance via PVT, daytime sleepiness was only assessed in 10 and affect in 6 of the studies limiting the ability to comprehensively assess neurobehavioral function among young adults in the included studies.

The findings presented underscore the importance of measuring different neurobehavioral function metrics (e.g., psychomotor vigilance - cognitive performance via PVT, daytime sleepiness via self-report and objective measures, and affect) when studying their response to sleep and wakefulness. Larger RCTs that include an objective to examine the effect of sleep deprivation on neurobehavioral function under controlled conditions are needed to reveal predictors and negative effects of acute and chronic sleep deprivation in this high-risk group. Researchers should also consider including moderators (e.g., age, sex, dose) when these larger studies are available for meta-analysis. Nurses working across tertiary care and the community are well-positioned to take the lead on advocating for policies and practices promoting a healthy sleep opportunity and sleep education to optimize brain development in this age group.

Highlights.

  • Total and partial sleep deprivation lead to significant decrements in neurobehavioral function (cognitive performance, affect, and sleepiness) in young adults.

  • Adaptation to sleep loss can occur when it accumulates over time.

  • The focus of the current literature is on short term sleep loss limiting the ability to draw inference to real world settings where sleep loss occurs at a more stable state over time (e.g., chronic partial sleep deprivation).

  • The prefrontal cortex continues to develop until the late 20’s, thus the effects of sleep loss over time in the developing brain remain unclear.

Acknowledgements:

The authors would like to acknowledge the contributions of DG in screening for inclusion and assisting with quality assessment.

Funding Statement:

This work was supported by American Academy of Sleep Medicine Foundation (AASM), 220-BS-19 and the National Institute for Nursing Research (NINR), K99NR018886. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the AASM Foundation or NIH.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

CRediT authorship contribution statement: Stephanie Griggs: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing – original draft, Project administration, Funding acquisition. Alison Harper: Validation, Formal analysis, Investigation, Data Curation, Writing – original draft. Ronald L. Hickman: Supervision, Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writing – review and editing, Project administration.

Declaration of competing interests: No conflict of interest has been declared by the authors.

Contributor Information

Stephanie Griggs, Case Western Reserve University, Frances Payne Bolton School of Nursing, Cleveland, Ohio, USA 44106.

Alison Harper, Case Western Reserve University, Frances Payne Bolton School of Nursing, Department of Anthropology, Cleveland, Ohio, USA 44106.

Ronald L. Hickman, Jr, Ruth M. Anderson Endowed Professor of Nursing and Associate Dean for Research Case Western Reserve University, Frances Payne Bolton School of Nursing, Cleveland, OH, USA 44106.

References

  1. Adler A, Gavan MY, Tauman R, Phillip M, & Shalitin S (2017). Do children, adolescents, and young adults with type 1 diabetes have increased prevalence of sleep disorders? Pediatric Diabetes, 18(6), 450–458. 10.1111/pedi.12419 [DOI] [PubMed] [Google Scholar]
  2. Akerstedt T, & Gillberg M (1990). Subjective and objective sleepiness in the active individual. International Journal of Neuroscience, 52(1–2), 29–37. 10.3109/00207459008994241 [DOI] [PubMed] [Google Scholar]
  3. Babkoff H, Caspy T, & Mikulincer M (1991). Subjective sleepiness ratings: the effects of sleep deprivation, circadian rhythmicity and cognitive performance. Sleep, 14(6), 534–539. 10.1093/sleep/14.6.534 [DOI] [PubMed] [Google Scholar]
  4. Baum KT, Desai A, Field J, Miller LE, Rausch J, & Beebe DW (2014). Sleep restriction worsens mood and emotion regulation in adolescents. The Journal of Child Psychology and Psychiatry, 55(2), 180–190. 10.1111/jcpp.12125 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Chee MWL, & Choo WC (2004). Functional imaging of working memory after 24 hr of total sleep deprivation. Journal of Neuroscience, 24(19), 4560–4567. 10.1523/jneurosci.0007-04.2004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Crowley SJ, & Carskadon MA (2010). Modifications to weekend recovery sleep delay circadian phase in older adolescents. Chronobiology International, 27(7), 1469–1492. https://dx.doi.org/10.3109%2F07420528.2010.503293 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. de Bruin EJ, van Run C, Staaks J, & Meijer AM (2017). Effects of sleep manipulation on cognitive functioning of adolescents: A systematic review. Sleep Medicine Reviews, 32, 45–57. 10.1016/j.smrv.2016.02.006 [DOI] [PubMed] [Google Scholar]
  8. Dinges DF, Pack F, Williams K, Gillen KA, Powell JW, Ott GE, Aptowicz C, & Pack AI (1997). Cumulative sleepiness, mood disturbance and psychomotor vigilance performance decrements during a week of sleep restricted to 4–5 hours per night. Sleep: Journal of Sleep Research & Sleep Medicine, 20(4), 267–277. [PubMed] [Google Scholar]
  9. Dinges DF, Rogers NL, & Dorrian J (2004). Psychomotor vigilance performance: Neurocognitive assay sensitive to sleep loss. In Sleep deprivation (pp. 67–98). CRC Press. [Google Scholar]
  10. Drake CL, Roehrs TA, Burduvali E, Bonahoom A, Rosekind M, & Roth T (2001). Effects of rapid versus slow accumulation of eight hours of sleep loss. Psychophysiology, 38(6), 979–987. 10.1111/1469-8986.3860979 [DOI] [PubMed] [Google Scholar]
  11. Esposito MJ, Occhionero M, & Cicogna P (2015). Sleep deprivation and time-based prospective memory. Sleep, 38(11), 1823–1826. 10.5665/sleep.5172 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fischer D, Lombardi DA, Marucci-Wellman H, & Roenneberg T (2017). Chronotypes in the US–influence of age and sex. PLoS One, 12(6), e0178782. 10.1371/journal.pone.0178782 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Franzen PL, Gianaros PJ, Marsland AL, Hall MH, Siegle GJ, Dahl RE, & Buysse DJ (2011). Cardiovascular reactivity to acute psychological stress following sleep deprivation. Psychosomatic Medicine, 73(8), 679–682. 10.1097/PSY.0b013e31822ff440 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Franzen PL, Siegle GJ, & Buysse DJ (2008). Relationships between affect, vigilance, and sleepiness following sleep deprivation. Journal of Sleep Research, 17(1), 34–41. 10.1111/j.1365-2869.2008.00635.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Giedd JN, Snell J, Lange N, Rajapakse J Casey BJ, Kozuch P, et al. (1996). Quantitative magnetic imaging of human brain development: Ages 4–18. Cerebral Cortex, 6, 551–560. 10.1093/cercor/6.4.551 [DOI] [PubMed] [Google Scholar]
  16. Goel N, Rao H, Durmer JS, & Dinges DF (2009). Neurocognitive consequences of sleep deprivation. Seminars in Neurology, 29(4), 320–339. 10.1055/s-0029-1237117 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Haavisto ML, Porkka-Heiskanen T, Hublin C, Härmä M, Mutanen P, Müller K, Virkkala J, & Sallinen M (2010). Sleep restriction for the duration of a work week impairs multitasking performance. Journal of Sleep Research, 19(3), 444–454. 10.1111/j.1365-2869.2010.00823.x [DOI] [PubMed] [Google Scholar]
  18. Honn KA, Halverson T, Jackson ML, Krusmark M, Chavali VP, Gunzelmann G, & Van Dongen HPA (2020). New insights into the cognitive effects of sleep deprivation by decomposition of a cognitive throughput task. Sleep: Journal of Sleep and Sleep Disorders Research, 43(7), 1–14. 10.1093/sleep/zsz319 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Jewett ME, Dijk D-J, Kronauer RE, & Dinges DF (1999). Dose-response relationship between sleep duration and human psychomotor vigilance and subjective alertness. Sleep: Journal of Sleep Research & Sleep Medicine, 22(2), 171–179. 10.1093/sleep/22.2.171 [DOI] [PubMed] [Google Scholar]
  20. Johnson SB, Blum RW, & Giedd JN (2009). Adolescent maturity and the brain: the promise and pitfalls of neuroscience research in adolescent health policy. Journal of Adolescent Health, 45(3), 216–221. 10.1016/j.jadohealth.2009.05.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Jones B, & Kenward MG (2014). Design and analysis of cross-over trials (Third edition. ed.). CRC Press/Taylor & Francis. [Google Scholar]
  22. Jørgensen L, Paludan-Müller AS, Laursen DR, Savović J, Boutron I, Sterne JA, Higgins JP, & Hróbjartsson A (2016). Evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials: overview of published comments and analysis of user practice in Cochrane and non-Cochrane reviews. Systematic Reviews, 5, 80. 10.1186/s13643-016-0259-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kaida K, & Niki K (2014). Total sleep deprivation decreases flow experience and mood status. Neuropsychiatric Disease and Treatment, 10, 19–25. 10.2147/ndt.s53633 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Lim J, & Dinges DF (2010). A meta-analysis of the impact of short-term sleep deprivation on cognitive variables. Psychological Bulletin, 136(3), 375–389. 10.1037/a0018883 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lin Y, Hu P, Mai ZF, Jiang TX, Mo L, & Ma N (2020). Sleep deprivation impairs cooperative behavior selectively: Evidence from prisoner’s and chicken dilemmas. Nature and Science of Sleep, 12, 29–37. 10.2147/nss.s237402 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Lüdtke H, Wilhelm B, Adler M, Schaeffel F, & Wilhelm H (1998). Mathematical procedures in data recording and processing of pupillary fatigue waves. Vision Research, 38(19), 2889–2896. 10.1016/s0042-6989(98)00081-9 [DOI] [PubMed] [Google Scholar]
  27. McNair D, Lorr M, & Droppleman L (1971). Manual for the profile of mood states (POMS). San Diego: Educational and Industrial Testing Service. [Google Scholar]
  28. Monk TH (1989). A Visual Analogue Scale technique to measure global vigor and affect. Psychiatry Research, 27(1), 89–99. 10.1016/0165-1781(89)90013-9 [DOI] [PubMed] [Google Scholar]
  29. Muzur A, Pace-Schott EF, & Hobson JA (2002). The prefrontal cortex in sleep. Trends in Cognitive Sciences, 6(11), 475–481. 10.1016/s1364-6613(02)01992-7 [DOI] [PubMed] [Google Scholar]
  30. Nagendrababu V, Duncan H, Tsesis I, Sathorn C, Pulikkotil S, Dharmarajan L, & Dummer P (2019). Preferred reporting items for systematic reviews and meta- analyses for abstracts: best practice for reporting abstracts of systematic reviews in Endodontology. International Endodontic Journal, 52(8), 1096–1107. https://onlinelibrary.wiley.com/doi/pdf/10.1111/iej.13118 [DOI] [PubMed] [Google Scholar]
  31. Nilsson JP, Söderström M, Karlsson AU, Lekander M, Akerstedt T, Lindroth NE, & Axelsson J (2005). Less effective executive functioning after one night’s sleep deprivation. Journal of Sleep Research, 14(1), 1–6. 10.1111/j.1365-2869.2005.00442.x [DOI] [PubMed] [Google Scholar]
  32. Patanaik A, Zagorodnov V, & Kwoh C (2014). Parameter estimation and simulation for one-choice Ratcliff diffusion model. Proceedings of the 29th Annual ACM Symposium on Applied Computing. [Google Scholar]
  33. Patanaik A, Zagorodnov V, Kwoh CK, & Chee MWL (2014). Predicting vulnerability to sleep deprivation using diffusion model parameters. Journal of Sleep Research, 23(5), 576–584. 10.1111/jsr.12166 [DOI] [PubMed] [Google Scholar]
  34. Peltzer K, & Pengpid S (2016). Sleep duration and health correlates among university students in 26 countries. Psychology, Health, and Medicine, 21(2), 208–220. 10.1080/13548506.2014.998687 [DOI] [PubMed] [Google Scholar]
  35. Popay J, Roberts H, Sowden A, Petticrew M, Arai L, Rodgers M, … & Duffy S (2006). Guidance on the conduct of narrative synthesis in systematic reviews. A Product from the ESRC Methods Programme Version, 1, b92 [Google Scholar]
  36. Robillard R, Prince F, Boissonneault M, Filipini D, & Carrier J (2011). Effects of increased homeostatic sleep pressure on postural control and their modulation by attentional resources. Clinical Neurophysiology, 122(9), 1771–1778. 10.1016/j.clinph.2011.02.010 [DOI] [PubMed] [Google Scholar]
  37. Rossa KR, Smith SS, Allan AC, & Sullivan KA (2014). The effects of sleep restriction on executive inhibitory control and affect in young adults. Journal of Adolescent Health, 55(2), 287–292. 10.1016/j.jadohealth.2013.12.034 [DOI] [PubMed] [Google Scholar]
  38. Schwarz JFA, Geisler P, Hajak G, Zulley J, Rupprecht R, Wetter TC, & Popp RFJ (2016). The effect of partial sleep deprivation on computer-based measures of fitness to drive. Sleep and Breathing, 20(1), 285–292. 10.1007/s11325-015-1220-0 [DOI] [PubMed] [Google Scholar]
  39. Schwarz JFA, Popp R, Haas J, Zulley J, Geisler P, Alpers GW, Osterheider M, & Eisenbarth H (2013). Shortened night sleep impairs facial responsiveness to emotional stimuli. Biological Psychology, 93(1), 41–44. 10.1016/j.biopsycho.2013.01.008 [DOI] [PubMed] [Google Scholar]
  40. Tempesta D, De Gennaro L, Presaghi F, & Ferrara M (2014). Emotional working memory during sustained wakefulness. Journal of Sleep Research, 23(6), 646–656. 10.1111/jsr.12170 [DOI] [PubMed] [Google Scholar]
  41. Tucker AM, Basner RC, Stern Y, & Rakitin BC (2009). The variable response-stimulus interval effect and sleep deprivation: An unexplored aspect of psychomotor vigilance task performance. Sleep: Journal of Sleep and Sleep Disorders Research, 32(10), 1393–1395. 10.1093/sleep/32.10.1393 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Van Dongen HPA, Baynard MD, Maislin G, & Dinges DF (2004). Systematic interindividual differences in neurobehavioral impairment from sleep loss: Evidence of trait-like differential vulnerability. Sleep, 27(3), 423–433. [PubMed] [Google Scholar]
  43. Van Dongen HPA, Maislin G, Mullington JM, & Dinges DF (2003). The cumulative cost of additional wakefulness: Dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep, 26(2), 117–126. 10.1093/sleep/26.2.117 [DOI] [PubMed] [Google Scholar]
  44. Watson D, Clark LA, & Tellegen A (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. 10.1037//0022-3514.54.6.1063 [DOI] [PubMed] [Google Scholar]
  45. Whitney P, Hinson JM, Jackson ML, & Van Dongen HPA (2015). Feedback blunting: Total sleep deprivation impairs decision making that requires updating based on feedback. Sleep: Journal of Sleep and Sleep Disorders Research, 38(5), 745–754. 10.5665/sleep.4668 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Yeo BTT, Tandi J, & Chee MWL (2015). Functional connectivity during rested wakefulness predicts vulnerability to sleep deprivation. Neuroimage, 111, 147–158. 10.1016/j.neuroimage.2015.02.018 [DOI] [PubMed] [Google Scholar]
  47. Yoo SS, Gujar N, Hu P, Jolesz FA, & Walker MP (2007). The human emotional brain without sleep--a prefrontal amygdala disconnect. Current Biology, 17(20), R877–878. 10.1016/j.cub.2007.08.007 [DOI] [PubMed] [Google Scholar]

RESOURCES