298 Sleep Stability and Academic Performance in College Students

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A119-A119
Author(s):  
Alexandria Reynolds ◽  
Madelynn Shell
Keyword(s):  
College Students ◽  
Academic Performance ◽  
Longitudinal Study ◽  
Sleep Quality ◽  
Transition To College ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Patterns ◽  
Sleep Habits ◽  
Time Points

Abstract Introduction There is considerable research demonstrating poor sleep patterns in college students; however, few studies actually examine sleep stability over a typical undergraduate career. Considering that the transition to college involves significant shifts in independence and potentially creating a foundation of lifelong behavioral patterns, it is important to identify whether these poor sleep patterns change throughout college. Additionally, studies show that shorter sleep duration predicts poorer academic performance. In the current study, it was expected that students would report poor sleep on average, and that poorer sleep would predict worse academic performance. Methods Participants included 27 full-time first-year undergraduate students who completed an online survey every spring for four years to examine sleep habits as part of a larger longitudinal study on the transition to college at a small liberal arts school. The Pittsburgh Sleep Quality Index was used to assess total sleep time (TST), sleep efficiency, and quality; the Epworth Sleepiness Scale (ESS) was used to determine sleepiness. Semester GPA was obtained via college registrar records. Results Repeated measures ANOVAs revealed no differences in participants’ sleep variables (TST, sleep quality, sleep efficiency, and sleepiness) across all four time points. Average TST was 6.85 hours per night, and overall sleep quality (PSQI) was poor (M = 6.12). Mean sleep efficiency was 86.70%; mean ESS score was 5.35. Preliminary analyses revealed no significant differences between GPA values over the course of the four years; sleep factors did not predict GPA. Conclusion Overall, students reported short sleep, poor sleep quality, decent sleep efficiency, and borderline higher than normal daytime sleepiness. However, sleep factors and GPA were stable over all time points. These results suggest that poor sleep habits start early and continue throughout students’ college career, as opposed to developing throughout college, or starting out poor and improving. Surprisingly, preliminary results indicated that sleep factors did not predict academic performance. Limitations include subjective sleep assessments, limited testing, and small sample size; however, this longitudinal study sheds interesting light on the general sleep patterns of college students over the course of their entire academic career. Support (if any) None.

scholarly journals The Epidemiology of Sleep Quality, Sleep Patterns, Consumption of Caffeinated Beverages, and Khat Use among Ethiopian College Students

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Seblewengel Lemma ◽  
Sheila V. Patel ◽  
Yared A. Tarekegn ◽  
Mahlet G. Tadesse ◽  
Yemane Berhane ◽  
...  
Keyword(s):  
College Students ◽  
Cigarette Smoking ◽  
Sleep Quality ◽  
Poor Sleep ◽  
Sleep Patterns ◽  
Sleep Habits ◽  
Poor Sleep Quality ◽  
Caffeine Consumption ◽  
Sleep Complaints ◽  
Khat Use

Objective. To evaluate sleep habits, sleep patterns, and sleep quality among Ethiopian college students; and to examine associations of poor sleep quality with consumption of caffeinated beverages and other stimulants.Methods. A total of 2,230 undergraduate students completed a self-administered comprehensive questionnaire which gathered information about sleep complaints, sociodemographic and lifestyle characteristics,and theuse of caffeinated beverages and khat. We used multivariable logistic regression procedures to estimate odds ratios for the associations of poor sleep quality with sociodemographic and behavioral factors.Results. Overall 52.7% of students were classified as having poor sleep quality (51.8% among males and 56.9% among females). In adjusted multivariate analyses, caffeine consumption (OR=1.55; 95% CI: 1.25–1.92), cigarette smoking (OR=1.68; 95% CI: 1.06–2.63), and khat use (OR=1.72, 95% CI: 1.09–2.71) were all associated with increased odds of long-sleep latency (>30 minutes). Cigarette smoking (OR=1.74; 95% CI: 1.11–2.73) and khat consumption (OR=1.91; 95% CI: 1.22–3.00) were also significantly associated with poor sleep efficiency (<85%), as well as with increased use of sleep medicine.Conclusion. Findings from the present study demonstrate the high prevalence of poor sleep quality and its association with stimulant use among college students. Preventive and educational programs for students should include modules that emphasize the importance of sleep and associated risk factors.

scholarly journals 0407 Sleep, Stress, Cardiovascular, and Psychological Health in College Students

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A156-A156
Author(s):  
A M Reynolds ◽  
K M Mullins
Keyword(s):  
College Students ◽  
Blood Pressure ◽  
Heart Rate ◽  
Psychological Health ◽  
Psychological Factors ◽  
Cardiovascular Health ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Habits ◽  
Stress Symptoms

Abstract Introduction Epidemiological studies have long established that sleep factors, stress, and cardiovascular health are related. College students often struggle with the demands of college life, which leads to increased stress, symptoms of depression and anxiety, and poor sleep. The focus of the current study was to examine habitual sleep habits in college students, in association with psychological factors and physiological factors. Methods Participants included 51 undergraduate students (18 men, average age M=20.25 years, SD=1.78) who wore wrist actigraphs to measure their typical sleep habits. After one week, participants completed questionnaires about psychological symptoms (i.e., depression, anxiety, and stress; Depression Anxiety Stress Scale, DASS-21) and subjective physiological symptoms (i.e., fatigue; Multidimensional Assessment of Fatigue Scale, MAF). Blood pressure and heart rate were measured using a wrist cuff. Results Overall total sleep time was 6.59 hours and sleep efficiency was 82.55%. Pearson correlational analyses revealed a negative moderate association between sleep efficiency and diastolic blood pressure (r(49) = -.318, p = .024). Global PSQI scores were moderately associated with stress (r(49) = .419, p = .002). MAF Global Fatigue Index scores revealed positive associations with depression (r(49) = .344, p =.014), anxiety (r(49) = .474, p&lt;.001), and stress (r(49) = .620 p&lt;.001). Heart rate was positively associated with depressive symptoms r(49) = .296, p= .035), stress symptoms r(49) = .447, p= .001), and fatigue r(49) = .456, p= .001). Conclusion As expected, college students’ sleep was short in duration and poor in efficiency. Sleep factors, cardiovascular factors, psychological factors, and stress were all related, demonstrating the importance of sleep on physiological and psychological health. More research should be conducted to further examine the relationships and directionality between sleep, psychological factors, and stress as there may be underlying mechanisms important for cardiovascular health. Support None.

scholarly journals 1025 Sleep Patterns In Head Neck Cancer Patients During Radiotherapy

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A389-A390
Author(s):  
F Gu ◽  
C Jungquist ◽  
A Sonia ◽  
L Liu ◽  
E Repasky ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Neck Cancer ◽  
Sleep Disturbances ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Sleep Patterns ◽  
Sleep Habits ◽  
End Of Treatment

Abstract Introduction Sleep disturbances are reported to be highly prevalent in head and neck cancer (HNC) patients, but no carefully assessed sleep data exists in patients with HNC undergoing concurrent chemoradiotherapy (CRT). Methods To objectively assess sleep patterns in this study population, we conducted a pilot study in 15 patients and 13 non-cancer healthy volunteers. Patients wore the wrist Actiwatch Spectrum (Philips Respironics) at week 1, 3, and 6/7 during the 7-week treatment period. Volunteers wore the Actiwatch for one week. We used the Actiware software to calculate sleep parameters. A sleep log was used as a complement to define participants’ bedtime and rise-up time. Any sleep episode scored by the software during daytime was considered as a nap. Results Compared to healthy volunteers, patients had lower overnight sleep efficiency, longer sleep onset latency and more waking time after sleep onset (WASO), indicating more difficulty falling asleep and maintaining sleep. During CRT, patients’ sleep efficiency decreased whereas latency and WASO increased, indicating possible the decrease of sleep quality. Sleep efficiency of &lt;85% has been used previously as a cut-off for poor sleep; based on this criteria, 45% of HNC patients had poor sleep at treatment baseline, compared to 31% in non-cancer volunteers, and this proportion increased to 51% by the end of treatment. Patients had longer napping time: compared to healthy volunteers, the napping time was on average 2 hours longer at baseline, and 3 hours longer at the end of treatment, indicating unhealthy sleep habits of these patients. Conclusion Our data suggested HNC patients had severe sleep disturbances and unhealthy sleep habits, which were aggravated during CRT treatment. Support This study was supported by UL1TR001412-04, a Clinical and Translational Research Award under SUNY-Buffalo.

scholarly journals Fostering the sleep instructional guidelines for nursing students regarding their sleep quality, academic performance and psychosocial behavior

2019 ◽  
Vol 10 (1) ◽  
pp. 43
Author(s):  
Nahed Saied Mohamed El-Nagger ◽  
Orban Ragab Bayoumi
Keyword(s):  
Saudi Arabia ◽  
Academic Performance ◽  
Nursing Students ◽  
Sleep Quality ◽  
Well Being ◽  
Poor Sleep ◽  
Sleep Patterns ◽  
Kingdom Of Saudi Arabia ◽  
Positive Effects ◽  
Psychosocial Behavior

Background and Objective: Sleep is a basic human need and has a necessary role in individual’s life, functioning, overall health and well-being. Sleep is necessary for college students’ intellectual, emotional and physical health, also for their cognitive performance that significantly affected by sleep quality. Aim: To investigate the effect of fostering the sleep instructional guidelines for nursing students regarding their sleep quality, academic performance and psychosocial behavior.Methods: Design: A quasi-experimental study design was utilized. Setting: Faculty of Nursing at Umm Al-Qura University in Makkah Al-Mukramh affiliated to the Ministry of Education in the Kingdom of Saudi Arabia (KSA). Sample: A purposive sample composed of 85 males and females nursing students from all academic years. Tools: Three tools were used Pre & Post including: (1) A self-administered Questionnaire Sheet, (2) Epworth Sleepiness Scale (ESS), and (3) Pittsburgh Sleep Quality Index (PSQI).Results: Slightly more than three quarters (78.82%) of nursing students their ages were ranged from 20-22 years and 69.41% of them were females. More than one fourth (27.06%) of students were having good sleep and 72.94% of them had poor sleep pre the sleep instructional guidelines compared with 81.18% and 18.82% of them post providing the instructional guidelines respectively.Conclusions: Fostering the instructional guidelines regarding sleep had positive effects on nursing students' sleep patterns in the form of sleep quality, bedtime at night, sleeping latency, sleeping efficiency and disturbances. In addition to enhancing students' academic performance and modifying their psychosocial behavior regarding daytime dysfunction, coffee consuming in the evening, bedroom environment, social isolation, and use of social media. Recommendations: Future research should carry out for university students' sleep patterns on a broad category as a regional research project all over the Kingdom of Saudi Arabia (KSA) involving multidisciplinary team as doctors, nurses, psychologists, sociologists and nutritionists.

scholarly journals Sleep and circadian indices for planning post-pandemic university timetables

2022 ◽  
Author(s):  
Sara Montagnese ◽  
Lisa Zarantonello ◽  
Chiara Formentin ◽  
Gianluca Giusti ◽  
Chiara Mangini ◽  
...  
Keyword(s):  
Academic Performance ◽  
Sleep Quality ◽  
Sleep Deprivation ◽  
Ad Hoc ◽  
Poor Sleep ◽  
Sleep Habits ◽  
Timing Information ◽  
Sleep Timing ◽  
Hygiene Education ◽  
The University

The aims of the present study were to obtain sleep quality and sleep timing information in a group of university students, and to evaluate the effects of a circadian hygiene education initiative. All students of the University of Padova (approximately 64,000) were contacted by e-mail (major campaigns in October 2019 and October 2020) and directed to an ad hoc website for collection of demographics and sleep quality/timing information. Participants (n=5740) received one of two sets of circadian hygiene advice ('A regular life' or 'Bright days and dark nights'). Every month, they were then asked how easy it had been to comply, and provided with the advice again. At any even month from joining, they completed the sleep quality/timing questionnaires again. Information on academic performance was obtained post hoc, together with representative samples of lecture (n=5972) and exam (n=1800) timings, plus lecture attendances (n=25,302). 52% of students had poor sleep quality and 82% showed signs of sleep deprivation. Those who joined in October 2020, after several months of lockdown and distance learning, had better sleep quality, less sleep deprivation and later sleep habits. The 'Bright days and dark nights' advice resulted in earlier get-up time/midsleep compared to the 'A regular life' advice. Significant changes in most sleep quality and sleep timing variables were observed in both advice groups over time, also in relation to pandemic-related events characterising 2020. Early-chronotype students had better academic performances compared to their later chronotype counterparts. In a multivariate model, sleep quality, chronotype and study subject were independent predictors of academic performance. Taken together, these results underlie the importance of designing circadian-friendly university timetables.

The Relationship of University Students' Sleep Habits and Academic Motivation

NASPA Journal ◽  
2006 ◽  
Vol 43 (3) ◽  
Author(s):  
Kellah M. Edens
Keyword(s):  
College Students ◽  
Academic Performance ◽  
Goal Orientation ◽  
Self Efficacy ◽  
Academic Motivation ◽  
College Health ◽  
Sleep Habits ◽  
Lack Of Sleep ◽  
Relationship Of ◽  
The Relationship

College students are sleeping less during the week than reported a few years ago. Lack of sleep among college students has been identified as one of the top three healthrelated impediments to academic performance by the American College Health Association’s National College Health Assessment survey; and it is associated with lower grades, incompletion of courses, as well as negative moods. This research examines the underlying dynamics of lack of sleep on academic motivation, a key predictor of academic performance. Specifically, the relationship of sleep habits with self-efficacy, performance versus mastery goal orientation, persistence, and tendency to procrastinate were investigated. Findings indicate that 42% of the participants (159 students out of a total of 377) experience excessive daytime sleepiness (EDS); and those identified with EDS tend: (1) to be motivated by performance goals rather than mastery goals; (2) to engage in procrastination (a self-handicapping strategy) to a greater extent than students who are rested; and (3) to have decreased self-efficacy, as compared to students not reporting EDS. Several recommendations for campus health professionals to consider for a Healthy Campus Initiative are made based on the findings.

scholarly journals 1142 Comprehensive Phenotyping Of Ambulatory Sleep Patterns In Multiple Sclerosis

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A435-A435
Author(s):  
T J Braley ◽  
A L Kratz ◽  
D Whibley ◽  
C Goldstein
Keyword(s):  
Multiple Sclerosis ◽  
Sleep Quality ◽  
Extreme Values ◽  
Sleep Onset ◽  
External Support ◽  
Poor Sleep ◽  
Sleep Patterns ◽  
Poor Sleep Quality ◽  
Historical Cohort ◽  
The Impact

Abstract Introduction The majority of sleep research in persons with multiple sclerosis (PwMS) has been siloed, restricted to evaluation of one or a few sleep measures in isolation. To fully characterize the impact of sleep disturbances in MS, multifaceted phenotyping of sleep is required. The objective of this study was to more comprehensively quantify sleep in PwMS, using a recently developed multi-domain framework of duration, continuity, regularity, sleepiness/alertness, and quality. Methods Data were derived from a parent study that examined associations between actigraphy and polysomnography-based measures of sleep and cognitive function in MS. Actigraphy was recorded in n=55 PwMS for 7-12 days (Actiwatch2®, Philips Respironics). Sleep metrics included: duration=mean total sleep time (TST, minutes); continuity=mean wake time after sleep onset (minutes), and regularity=stddev wake-up time (hours). ‘Extreme’ values for continuity/regularity were defined as the most extreme third of the distributions. ‘Extreme’ TST values were defined as the lowest or highest sixth of the distributions. Sleepiness (Epworth Sleepiness Scale score) and sleep quality [Pittsburgh Sleep Quality Index (PSQI) sleep quality item] were dichotomized by accepted cutoffs (&gt;10 and &gt;1, respectively). Results Sleep was recorded for a mean of 8.2 days (stddev=0.95). Median (1st, 3rd quartile) values were as follows: duration 459.79 (430.75, 490.60), continuity 37.00 (23.44, 52.57), regularity 1.02 (0.75, 1.32), sleepiness/alertness 8 (4, 12), and sleep quality 1.00 (1.00, 2.00). Extreme values based on data distributions were: short sleep &lt;=426.25 minutes (18%), long sleep &gt;515.5 minutes (16%), poor sleep continuity ≥45 minutes (33%), and poor sleep regularity ≥1.17 hours (33%). Sleepiness and poor sleep quality were present in 36% and 40% respectively. For comparison, in a historical cohort of non-MS patients, the extreme third of sleep regularity was a stddev of 0.75 hours, 13% had ESS of &gt;10, and 16% had poor sleep quality. Conclusion In this study of ambulatory sleep patterns in PwMS, we found greater irregularity of sleep-wake timing, and higher prevalence of sleepiness and poor sleep quality than published normative data. Efforts should be made to include these measures in the assessment of sleep-related contributions to MS outcomes. Support The authors received no external support for this work.

scholarly journals 192 Self-reported sleep features in the Italian population across the first and second wave of the COVID-19 pandemic

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A77-A78
Author(s):  
Oreste De Rosa ◽  
Nicola Cellini ◽  
Francesca Conte ◽  
Serena Malloggi ◽  
Fiorenza Giganti ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Linear Mixed Model ◽  
Negative Impact ◽  
Italian Population ◽  
Sleep Habits ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
Time Points ◽  
Time In Bed ◽  
Second Wave

Abstract Introduction Several studies have shown the negative impact of COVID-19-related confinement measures (spring 2020) on sleep features and quality. Here we aim to follow-up on these data by assessing self-reported sleep characteristics during the second wave of the pandemic (autumn 2020) in Italy, where the government responded with a second, partial, lockdown. Methods Using a longitudinal approach, 214 participants (Mage=36.78±14.2y; 159F) who had participated in a previous survey (April 2020 – Total Lockdown, TL) completed the same online survey from November 10th to December 1st (Partial Lockdown, PL). In each survey, participants had to respond to a set of questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), referring to their current situation and, retrospectively, to their situation before the lockdown, resulting in four time-points (pre-TL, TL, pre-PL, PL). Results Linear mixed-model analysis showed that bedtime was delayed from pre-TL (23:46) to TL (24:42) and then linearly advanced in pre-PL (24:02) and PL (23:56). The same pattern emerged for rise time (pre-TL: 07:48, TL: 9:05, pre-PL: 8:28, PL: 7:58) and time in bed, which increased from pre-TL (8h4min) to TL (8h24min) and then linearly decreased (pre-PL: 8h15m, PL: 8h2m). Subjective sleep quality decreased in the two lockdowns compared to the period with no restrictions. The proportion of poor sleepers (PSQI&gt;5) increased from 39.7% (pre-TL) to 48.6% in TL and again from 36.9% (pre-PL) to 47.7% in PL. Conclusion Sleep habits and quality showed different profiles across four time-points of the COVID-19 pandemic and related restrictive measures. Sleep timing alterations appeared during the first lockdown, recovered after the confinement period, and almost returned to baseline during the second lockdown (likely due to a normalization of working schedules). Instead, subjective sleep quality markedly worsened during both lockdowns relative to the preceding respective months. These data suggest that subjective sleep quality is particularly sensitive to changes in life habits and psychological factors, independently of sleep habits. Considering that the pandemic situation may continue for several months, there is a need for interventions targeting sleep quality. Support (if any) N/A

Getting Enough Sleep: On the Importance of Collecting Longitudinal Data from Wearables to Assess Sleep Quality and Seasonal Effects on Variability in Daily Activity (Preprint)

2021 ◽  
Author(s):  
María Óskarsdóttir ◽  
Anna Sigridur Islind ◽  
Elias August ◽  
Erna Sif Arnardóttir ◽  
Francois Patou ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Data Collection ◽  
Sleep Quality ◽  
Daily Activity ◽  
Hospital Environment ◽  
Sensor Data ◽  
Seasonal Patterns ◽  
Sleep Patterns ◽  
Sleep Habits

BACKGROUND The method considered the gold standard for recording sleep is a polysomnography, where the measurement is performed in a hospital environment for 1-3 nights. This requires subjects to sleep with a device and several sensors attached to their face, scalp, and body, which is both cumbersome and expensive. For longer studies with actigraphy, 3-14 days of data collection is typically used for both clinical and research studies. OBJECTIVE The primary goal of this paper is to investigate if the aforementioned timespan is sufficient for data collection, when performing sleep measurements at home using wearable and non-wearable sensors. Specifically, whether 3-14 days of data collection sufficient to capture an individual’s sleep habits and fluctuations in sleep patterns in a reliable way for research purposes. Our secondary goals are to investigate whether there is a relationship between sleep quality, physical activity, and heart rate, and whether individuals who exhibit similar activity and sleep patterns in general and in relation to seasonality can be clustered together. METHODS Data on sleep, physical activity, and heart rate was collected over a period of 6 months from 54 individuals in Denmark aged 52-86 years. The Withings Aura sleep tracker (non-wearable) and Withings Steel HR smartwatch (wearable) were used. At the individual level, we investigated the consistency of various physical activities and sleep metrics over different time spans to illustrate how sensor data from self-trackers can be used to illuminate trends. RESULTS Significant variability in standard metrics of sleep quality was found between different periods throughout the study. We show specifically that in order to get more robust individual assessment of sleep and physical activity patterns through wearable and non-wearable devices, a longer evaluation period than 3-14 days is necessary. Additionally, we found seasonal patterns in sleep data related to changing of the clock for Daylight Saving Time (DST). CONCLUSIONS We demonstrate that over two months worth of self-tracking data is needed to provide a representative summary of daily activity and sleep patterns. By doing so, we challenge the current standard of 3-14 days for sleep quality assessment and call for rethinking standards when collecting data for research purposes. Seasonal patterns and DST clock change are also important aspects that need to be taken into consideration, and designed for, when choosing a period for collecting data. Furthermore, we suggest using consumer-grade self-trackers (wearable and non-wearable ones) to support longer term evaluations of sleep and physical activity for research purposes and, possibly, clinical ones in the future.

Differential Diagnosis of Sluggish Cognitive Tempo Symptoms in College Students

2020 ◽  
pp. 108705471989685
Author(s):  
Benjamin J. Lovett ◽  
Whitney L. M. Wood ◽  
Lawrence J. Lewandowski
Keyword(s):  
College Students ◽  
Sleep Quality ◽  
Substance Misuse ◽  
Sleep Problems ◽  
Sluggish Cognitive Tempo ◽  
Poor Sleep ◽  
Depression And Anxiety ◽  
Poor Sleep Quality ◽  
Clinically Significant ◽  
Cognitive Tempo

Objective: Sluggish cognitive tempo (SCT) refers to a set of symptoms that prior research has found to be related to several different psychological disorders, especially the predominantly inattentive presentation of ADHD. This study collected evidence relevant to the question of whether SCT is a distinct disorder. Method: College students ( N = 910) completed measures of SCT, ADHD, depression, anxiety, sleep quality, and substance misuse. Results: Students reporting clinically high SCT (reporting at least five symptoms often or very often) had significantly higher levels and rates of other types of psychopathology. Moreover, when students reporting clinically significant levels of ADHD, depression, and anxiety symptoms, poor sleep quality, or hazardous levels of alcohol or cannabis use were removed, very few students reporting high SCT remained (only 4.8% of the original high-SCT group). Conclusion: SCT may be best thought of as a symptom set common to many types of psychopathology, and it may be caused by sleep problems or substance misuse as well.

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