Brandy M. Roane

Epidemiology of insomnia in college students: relationship with mental health, quality of life, and substance use difficulties.

The purpose of this study was to evaluate the prevalence and correlates of insomnia using rigorous diagnostic criteria and a comprehensive assessment battery. In a large sample (N=1,074) of college students (mean age 20.39years), participants were asked to complete a week-long sleep diary and comprehensive questionnaire packet assessing recommended daytime functioning domains (i.e., fatigue, quality of life, depression, anxiety, stress, academic performance, substance use) during the academic year. A significant portion of this sample of college students met proposed DSM-5 criteria for chronic insomnia (9.5%). The chronic insomnia group reported significantly worse sleep, fatigue, depression, anxiety, stress, and quality of life, and greater hypnotic and stimulant use for sleep problems. There were no differences between groups on excessive daytime sleepiness, academic performance, or substance use. This was a rigorous and comprehensive assessment of the prevalence and psychosocial correlates of insomnia. Insomnia is a significant problem in college students and should be regularly assessed. More research is also needed to guide treatment in this population.

Circadian Phase Preference in College Students: Relationships With Psychological Functioning and Academics

The current study offers a comprehensive assessment of psychosocial functioning and academic performance in relation to circadian phase preference in a US sample of undergraduate college students (N = 838), aged 17–26 (M = 19.78, SD = 1.89). Women had greater morning preference than men, and seniors had greater morning preference than freshmen. Circadian phase preference, fatigue, perceived stress, depression, anxiety, and substance use were assessed cross-sectionally and grade point average (GPA) was assessed prospectively. Evening phase preference was related to higher levels of fatigue, alcohol and caffeine use, and worse academic performance than morning or intermediate phase preferences. (Author correspondence: djtaylor@unt.edu)

Treatment of insomnia in adults and children: a practice-friendly review of research.

Chronic insomnia affects nearly 16% of adults and up to 25% of children. Many clinicians are unfamiliar with the research and practice of psychological treatments of insomnia and thus do not use them with their patients. The primary goals of this article were to (a) review the research support for psychological treatments of adult and child insomnia, and (b) describe those treatments with the highest level of research support in enough detail to allow practitioners to begin to utilize them with their own patients. The adult psychological treatments with the best research support are stimulus control, progressive muscle relaxation, and multimodal cognitive-behavioral therapy, followed by multimodal behavioral therapy, sleep restriction, biofeedback, and paradoxical intention. The child psychological treatments with the highest level of research support are preventive parent education, unmodified extinction, and extinction with parental presence, followed by graduated extinction, bedtime fading/positive routines, and scheduled awakenings.

Insomnia and mental health in college students.

Insomnia is strongly associated with certain mental health problems in the general population. However, there is little research examining this relation in young adults—an age group where many mental health problems first present. This study examined relations between insomnia and mental health symptoms in a college population (N = 373; 60.9% women; mean age of 21 years). Insomnia was assessed via self-report and sleep diaries, and mental health was assessed via the Symptom Check List–90. Analyses revealed insomnia was prevalent (9.4%), and these young adults had significantly more mental health problems than those without insomnia, although some significant results were lost after controlling for comorbid health problems.

Sex of College Students Moderates Associations among Bedtime, Time in Bed, and Circadian Phase Angle

Sex differences in circadian rhythms have been reported with some conflicting results. The timing of sleep and length of time in bed have not been considered, however, in previous such studies. The current study has 3 major aims: (1) replicate previous studies in a large sample of young adults for sex differences in sleep patterns and dim light melatonin onset (DLMO) phase; (2) in a subsample constrained by matching across sex for bedtime and time in bed, confirm sex differences in DLMO and phase angle of DLMO to bedtime; (3) explore sex differences in the influence of sleep timing and length of time in bed on phase angle. A total of 356 first-year Brown University students (207 women) aged 17.7 to 21.4 years (mean = 18.8 years, SD = 0.4 years) were included in these analyses. Wake time was the only sleep variable that showed a sex difference. DLMO phase was earlier in women than men and phase angle wider in women than men. Shorter time in bed was associated with wider phase angle in women and men. In men, however, a 3-way interaction indicated that phase angles were influenced by both bedtime and time in bed; a complex interaction was not found for women. These analyses in a large sample of young adults on self-selected schedules confirm a sex difference in wake time, circadian phase, and the association between circadian phase and reported bedtime. A complex interaction with length of time in bed occurred for men but not women. We propose that these sex differences likely indicate fundamental differences in the biology of the sleep and circadian timing systems as well as in behavioral choices.

The Role of Sleep in Predicting College Academic Performance: Is it a Unique Predictor?

Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. This project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Participants (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset latency, later bedtimes, later wake times, and TST inconsistency would predict decreased academic performance. The most significant predictors of academic performance were high school GPA, standardized test scores (i.e., SAT/ACT), TST, time awake before arising (TWAK), TST inconsistency, and the quadratic terms of perceived stress (PSS) and TST.

Digital media use in the 2h before bedtime is associated with sleep variables in university students

Digital media use is widespread in University students, and use of digital media near bedtime has a broadly negative effect on sleep outcomes. Adequate and good quality sleep is important for physical and mental health, but few studies have rigorously measured both sleep and digital media use. In this study, we investigated whether self-reported sleep patterns were associated with digital media use in a first-year University student (N = 254, 48% male) population. Students tracked their sleep through daily online diaries and provided digital media use data in 15-min blocks for 2 h prior to bedtime on nine occasions. A longer duration of digital media use was associated with reduced total sleep time and later bedtime, while greater diversity of digital media use was associated with increased total sleep time and earlier bedtime. Analysis of activities in the last hour before bedtime indicated that activity type plays a role in digital medias effect on sleep, with computer work, surfing the Internet, and listening to music showing the strongest relationship to multiple sleep variables. These findings have implications for physical and mental health of University students and can inform design of devices to minimize negative effects of digital media on sleep.

Estimating sleep from multisensory armband measurements: validity and reliability in teens.

Given the recognition that sleep may influence obesity risk, there is increasing interest in measuring sleep parameters within obesity studies. The goal of the current analyses was to determine whether the SenseWear® Pro3 Armband (armband), typically used to assess physical activity, is reliable at assessing sleep parameters. The armband was compared with the AMI Motionlogger® (actigraph), a validated activity monitor for sleep assessment, and with polysomnography, the gold standard for assessing sleep. Participants were 20 adolescents (mean age = 15.5 years) with a mean body mass index percentile of 63.7. All participants wore the armband and actigraph on their non‐dominant arm while in‐lab during a nocturnal polysomnographic recording (600 min). Epoch‐by‐epoch sleep/wake data and concordance of sleep parameters were examined. No significant sleep parameter differences were found between the armband and polysomnography; the actigraph tended to overestimate sleep and underestimate wake compared with polysomnography. Both devices showed high sleep sensitivity, but lower wake detection rates. Bland–Altman plots showed large individual differences in armband sleep parameter concordance rates. The armband did well estimating sleep overall, with group results more similar to polysomnography than the actigraph; however, the armband was less accurate at an individual level than the actigraph.

Psychometric Evaluation of the PSQI in U.S. College Students.

STUDY OBJECTIVES Examine the psychometric properties of the PSQI in two U.S. college samples. METHODS Study I assessed convergent and divergent validity in 866 undergraduates who completed a sleep diary, PSQI, and other sleep and psychosocial measures. Study II assessed PSQI insomnia diagnostic accuracy in a separate sample of 147 healthy undergraduates with and without insomnia. RESULTS The PSQI global score had only moderate convergent validity with sleep diary sleep efficiency (prospective global measure of sleep continuity; r = 0.53), the Insomnia Severity Index (r = 0.63), and fatigue (r = 0.44). The PSQI global score demonstrated good divergent validity with measures of excessive daytime sleepiness (r = 0.18), circadian preference (r = -0.08), alcohol (r = 0.08) and marijuana (r = 0.05) abuse scales, and poor divergent validity with depression (r = 0.48), anxiety (r = 0.40), and perceived stress (r = 0.33). Examination of other analogous PSQI and sleep diary components showed low to moderate convergent validity: sleep latency (r = 0.70), wake after sleep onset (r = 0.37), sleep duration (r = 0.51), and sleep efficiency (r = -0.32). Diagnostic accuracy of the PSQI to detect insomnia was very high (area under the curve = 0.999). Sensitivity and specificity were maximized at a cutoff of 6. CONCLUSIONS The PSQI demonstrated moderate convergent validity compared to measures of insomnia and fatigue and good divergent validity with measures of daytime sleepiness, circadian phase preference, and alcohol and marijuana use. The PSQI demonstrated considerable overlap with depression, anxiety, and perceived stress. Therefore, caution should be used with interpretation.

Current alcohol use is associated with sleep patterns in first-year college students

STUDY OBJECTIVES To examine whether differences exist in self-reported sleep patterns and self-reported alcohol use for first-semester college students who do or do not report drinking during the last 6 months (mo) of high school. METHODS Participants were 878 first-year college students. Students completed a survey in late May/early June about alcohol use and consequences, during the last 6 mo of high school; they later completed a daily record of sleep behavior and alcohol use across the first 9 weeks of the first semester of college. High school drinking status (past 6 mo) was classified as positive (HS-6 mo+) or negative (HS-6mo-) based on any indication of drinking on the May/June survey. Collegiate drinking was determined from first-semester daily diary alcohol reports as non-drinkers (0 reported drinks), drinkers (one or fewer heavy episodic drinking episodes (HED)), and drinkers reporting more than one HED episode. Sleep patterns were compared for non-drinkers, drinkers, and HED with no high school drinking history (HS-6mo-/HED). In addition, a separate analysis compared sleep patterns for college HED with (HS-6mo+/HED) and without (HS-6mo-/HED) high school self-reported alcohol use. RESULTS Increased alcohol consumption in the first semester of college was associated with later bedtimes and rise times. We found no association of high school alcohol use and sleep in those with collegiate HED. CONCLUSIONS Later sleep timing in those with greater alcohol use, supports a connection between sleep patterns and alcohol use. Such an early appearance of this connection may herald the development of alcohol use disorder in some individuals.