Review of the Literature Assignment
tamika894
FEMALECOLLEGE.pdf
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Am J Health Behav.™ 2013;37(6):851-858 851
S leep disturbances are common among college students.1-3 These sleep disturbances could be associated with stress derived from their
academic challenges and daily life.1-3 Stress and its effects on health are areas of concern for many health care providers. The concept of stress has been used in many different ways over the past century: stress as stimulus, stress as response, and stress as interaction and transaction.4 Laza- rus and Folkman5 defined stress as the complex interaction between an individual and his/her en- vironment that can impact one’s well-being. Col- lege students experience predictable, stressful life events during the school year that can lead to sleep deprivation and further endanger their well- being. Most students may sense the stress derived from school work; however, they may not realize that sleep deprivation is also a stressor in addi- tion to their daily life stress, and altogether could have negative impacts on their physical and men- tal health.
Stress was first conceived as a basis of poor
health more than 2 centuries ago. The biological reactions accompanying adaptation to stress re- sult in both short- and long-term adverse impacts to physical and mental conditions.5,6 When an indi- vidual faces a stressful situation, the sympathetic portions of the autonomic nervous system are ac- tivated and a fight-or-flight reaction6 is manifested as accelerated heartbeat, increased respiration, and redistribution of blood from peripheral areas of the body into the head and trunk. Each stress- or activates the sequence just described, thereby enabling the body to fight or take flight. The au- tonomic response occurs quickly and lasts only a short time; the endocrine response initiates more slowly and lasts longer. Setting off this response many times over a long period has a wear-and-tear effect on the body; eventually, it lowers resistance to disease. Ample evidence indicates that physical and psychological distress can affect an individu- al’s susceptibility to disease, such as depression, insomnia, cardiovascular disease, diabetes, and rheumatoid arthritis.7 College is a well-known time for stress. Stress is detrimental to good health and sleep habits, both of which are crucial for academ- ic success. Increased stress levels and psychologi- cal problems are associated with poor quality sleep in college students.8
Stress and sleep problems are inextricably linked and affect health and well-being. Sleep disturbance is defined as sleep deprivation resulting from inad- equate total sleep time or sleep disruption result-
Shih-Yu Lee, Associate Professor, Caroline Wuertz, Student Research Assistant, and Rebecca Rogers, Student Research Assistant, School of Nurs- ing, Georgia State University, GA. Yu-Ping Chen, As- sistant Professor, Department of Physical Therapy, Georgia State University, GA.
Correspondence Dr Lee; [email protected]
Stress and Sleep Disturbances in Female College Students
Shih-Yu Lee, PhD, RNC; Caroline Wuertz; Rebecca Rogers, BS; Yu-Ping Chen, ScD, PT
Objective: To describe the sleep char- acteristics and examine the associa- tions among perceived stress, sleep dis- turbances, depressive symptoms, and physical symptoms among female col- lege students. Methods: A total of 103 students completed a battery of ques- tionnaires. Results: The students expe- rienced high stress during the school year. The majority of them slept less than 6 hours during weekdays and ex- perienced moderate fatigue. High stress levels are associated with sleep distur- bances, less nocturnal total sleep time, higher fatigue severity, and more de-
pressive symptoms. Perceived stress and sleep disturbances are significant predictors for depressive symptoms and physical symptoms. Compared to the good sleepers, the poor sleepers report- ed more daytime sleepiness, depressive symptoms, and physical symptoms. Con- clusions: Interventions to reduce stress and improve sleep are critically needed in college education.
Key words: female, college students, sleep, stress, depressive symptoms, day- time sleepiness, physical symptoms
Am J Health Behav. 2013;37(6):851-858 DOI: http://dx.doi.org/10.5993/AJHB.37.6.14
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ing from fragmented sleep during the night, which leads to adverse health outcomes.9 Sleep distur- bances can also cause daytime sleepiness, which can lead to poor performance.9 The National In- stitutes of Health (NIH) estimate that sleep prob- lems add $15 billion to annual health care costs and cost industry about $50 billion yearly in lost productivity.7 The 2007 Sleep in America Poll sur- vey, which focused on adult women in different de- velopmental stages, found that about half of the women experienced sleep problems nightly.10 Epi- demiologic studies reveal that sleep loss increases the risks of cardiovascular disorders, diabetes mel- litus, and mortality.11-13 Other common symptoms associated with sleep disturbances include fatigue and depressive symptoms.7
The prevalence of sleep disturbances is differ- ent in various ethnic groups.9 Sleep disturbances are more prevalent among American females com- pared to males, and these sleep problems nega- tively affect their daytime functioning and physical and psychological well-being.10,14 Women are more vulnerable to the effects of sleep disturbances than men because of several physio-psycho-social fac- tors, such as cycling hormones15 and engagement in multiple social roles.10 Explaining the effects of cycling hormones is beyond the scope of this pa- per; however, researchers have hypothesized that follicle-stimulating hormone (FSH) may modulate melatonin circadian rhythms among postmeno- pausal women,16 and the changes in FSH may be responsible for substantive changes in the nature of sleep for females. To date, several studies have explored sleep patterns among college students and show that sleep problems are common1,2,17 and can impact academic performance and mood changes.17,18 A limited number of studies have fo- cused on the sleep issues in female students; how- ever, the studies that included females neglected the impact from hormones that can threaten the validity of findings. In addition, few studies have examined the relationships among sleep distur- bances and physical and mental health among fe- male students.
The data reported in this paper are baseline data from a larger scale, 2-phase prospective study in which we used multiple survey questionnaires to assess the impact of stress and sleep disturbances to health-related well-being (ie, fatigue, depressive symptoms, and physical symptoms) among female college students. The following research questions were addressed:
1. What are the sleep characteristics of female college students during the school year?
2. What are the relationships among perceived stress, sleep, and health-related well-being (ie, fa- tigue, depressive symptoms, and physical symp- toms)?
3. To what degree are depressive symptoms ex- plained by an individual’s personal characteristics (ie, ethnicity, age, body mass index), perceived stress, and sleep disturbances?
4. To what degree are physical symptoms explained by an individual’s personal characteris- tics (ie, ethnicity, age, body mass index), perceived stress, and sleep disturbances?
The following hypothesis (H) was tested: H1. Women with poor sleep have adverse health
outcomes such as increased fatigue severity, day- time sleepiness, depressive symptoms, and more physical symptoms than women with good sleep.
METHODS Participants
A convenience sample of 103 female college students aged 18 years and above was recruited from a university in the southern United States. Women were excluded for: (1) history of endocrine, immune, or metabolic disorders; (2) current use of medications that may alter sleep; (3) history of a diagnosed sleep disorder; (4) employment as a shift worker; and (5) pregnancy (because sleep pat- terns of pregnant women are different from those of non-pregnant women). At the end of the study, each participant received a sleep hygiene booklet and a report on her sleep patterns. The partici- pants (Table 1) were predominantly undergraduate students (88.3%), white (48.5%), single (62.1%), without children (87.4%), and with financial dif- ficulty (64.1%). These female students ranged in age from 18 to 53 (26.3 + 7.9) with a normal body mass index (63.7% with a BMI between 20 and 25). Among the ethnic groups, Blacks had the highest BMI (26.40 + 6.70) and Asians had the lowest BMI (21.54 + 1.92). A sample of 103 allows the detec- tion of a medium effect size with power of 80% with up to 7 predictors to test the hypothesis in a mul- tiple regression study.
Procedure and Instruments To recruit students for participation, the classes
in the college of health professions were randomly selected. The first author who had no personal or professional relationship with any of the selected classes went to the classrooms and spent about 5-10 minutes to address the purpose of the study, eligibility criteria, contact information, and to in- form students that participation would require an average commitment of 8-10 minutes per day for one week to complete the questionnaires. The potential study participants were informed that participation in this study was voluntary and that their decision about participation in this study would not affect their grades. Then, a sign-up sheet was passed around in the classroom so those who were interested could leave their contact informa- tion for further appointment and screening. Once the potential study participants’ eligibility was de- termined, they received detailed information about this study, and an opportunity was given for them to consider participation privately. Informed con- sent was obtained from each study participant.
Data were collected in the beginning of the se- mester in fall 2011 and spring 2012 while the
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Am J Health Behav.™ 2013;37(6):851-858 853 DOI: http://dx.doi.org/10.5993/AJHB.37.6.14
students were not having major examinations. All of the questionnaires listed below, along with a consecutive 7-day sleep diary and demographic information, were collected. Study participants were asked to complete the 7-day sleep diary to record their sleep-wake patterns first, and then to complete the questionnaires. Data from the sleep diary were used to calculate their total nocturnal sleep time. The data were collected within 7 days after the menstrual period (before luteal phase) to avoid extraneous factors, such as premenstrual syndrome and special sleep patterns during the luteal phase which may cause an underestimation
of sleep.16
All of the questionnaires adopted in this study have sound psychometric qualities. The Perceived Stress Scale (PSS),19 a 10-item, 5-point Likert scale (0= never, 4= often), was used to describe global stress the female college students experi- enced in the past week. Higher scores indicate a greater level of stress perception. A cut-off point of 13.7 is suggested for females.19 In addition to global stress, we also asked the participants to rate the level of their financial difficulty on a 10-point scale (1= a little difficulty, 10= extreme difficulty). The General Sleep Disturbance Scale (GSDS), a
Table 1 Demographics of the Female College Students (N=103)
Variables (cut-off) Mean (SD) Frequency (%) Above Cut-off (%) Age 26.3 (7.9) --- --- Ethnic group: White 50 (48.5) Black 26 (25.2) Hispanic 10 ( 9.7) Asian 17 (16.5) Program of study Undergraduate 91 (88.3) Graduate 12 (11.7) Employed Yes 51 (49.5) No 52 (50.5) Financial difficulty Yes 66 (64.1) No 36 (35.0) Self-reported health status Good 95 (92.2) Fair 8 ( 7.8) Marital status Single 64 (62.1) Married 25 (24.3) Living with a partner 14 (13.6) Have Children Yes 13 (12.6) No 90 (87.4) TST needed (hours) 7.80 (1.18) --- --- TST mean (< 7 hours) 7.15 (1.04) 43.7 Weekdays 6.89 (1.13) 54.4 Weekend 7.81 (1.46) 32.0 GSDS (> 3) 2.58 (1.05) 35.0 PSQI (> 5) 6.29 (2.98) 68.0 ESS (>9 ) 7.96 (4.06) 46.1 PSS (> 13.7) 16.27 (6.4) 56.3 CES-D (>16) 11.85 (8.91) 25.2 Morning fatigue (> 3.2) 3.81 (1.5) 61.2 Physical symptoms (median 5) 5.50 (3.2)
Note. GSDS= General Sleep Disturbance Scale; PSQI= Pittsburg Sleep Quality Index; ESS= Epworth Sleepiness Scale; PSS=Perceived Stress Scale; CES-D= Center of Epidemiology Scale-Depression; TST= Total Sleep Time
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21-item, 0-7 rating scale, was used to assess the study participants’ degree of sleep disturbance in the past week.20 A cut-off score of 3 for the total scale distinguishes good from poor sleepers.20 The Pittsburgh Sleep Quality Index (PSQI),21 a 19-item, 0-3 rating scale, was used to measure an individu- al’s subjective sleep quality and disturbances over a 1-month time interval. A total score above 5 sug- gests insomnia.21 The Epworth Sleepiness Scale (ESS), an 8-item, 0-3 rating questionnaire, was used to measure the degree of sleepiness during daytime.22 Higher scores indicate a higher degree of sleepiness; an individual who scores 9 or above indicates “very sleepy” and should seek medical advice.22
In this study, health-related well-being is defined in terms of depressive symptoms, fatigue sever- ity, and physical symptoms. The Center for Epi- demiologic Studies Depression Scale (CES-D),23 a 20-item scale with a possible score range of 0-60, was used to measure the study participants’ psy- chological health. Study participants with CES-D scores ≥ 16 were immediately referred to the on- site student counseling center. Fatigue was mea- sured with the Numerical Rating Scale for Fatigue (NRS-F),24 a self-rated 18-item scale, scored from 0 (not fatigued) to 10 (extremely fatigued). To de- crease the study participants’ burden, only a 7-item short version of the fatigue scale was in- cluded in this study. Cronbach’s alpha coefficients for the 7-item version of the NRS-F ranged from .89 to .97 in prior studies.25 The Physical Symp- tom Inventory (PSI),26 an 18-item scale, was used to measure the participants’ physical health. For each item, participants indicate “yes” or “no” on a rating scale of 18 physical symptoms (eg, upset stomach, headache, and infection) over the past 30 days. Participants also were asked to differentiate whether or not they saw a doctor if they experi- enced any physical symptoms.
Data Analysis Data were analyzed using the Statistical Package
for the Social Sciences 18 (SPSS, Inc., Chicago, IL). All of the data were verified for accuracy by review- ing questionable data in the questionnaires. De- scriptive and frequency statistics were computed for nominal and ordinal level data, and measures of central tendency were obtained for interval and ratio level data. Internal consistency reliability measures for all instruments were calculated us- ing Cronbach’s alpha coefficients with an excep- tion of using Kuder-Richardson-20 for the Physi- cal Symptoms Inventory, and all with an accept- able alpha of 0.8 and above. Analyses of variance (ANOVAs) were used to determine if there were any significant differences in sleep characteristics by ethnic group. Based on normal distribution of the variables, the associations among the variables were assessing by Pearson product-moment cor- relation coefficient to answer research question 2. Hierarchical regression analyses were performed
to answer research question 3 and 4 to determine whether any independent variables predicted de- pressive symptoms and physical symptoms. Inde- pendent t-tests were used to test the hypothesis and to determine if there were any mean differ- ences in health-related outcome variables between poor sleepers and good sleepers.
RESULTS We approached approximately 550 students,
and 153 of them signed up for further screening; however, only 103 met the criteria, consented to participate, and completed this study. We did not ask why the rest of the students were not interest- ed; however, anecdotally, the students expressed they were too busy to take part in this study. These students experienced high global stress (16.3 + 6.4) as measured by the PSS. About 46% of the study participants experienced a clinically signifi- cant daytime sleepiness as measured by the ESS (7.96 + 4.06). These female students also reported moderate morning fatigue severity, and about 61% experienced a clinically significant fatigue severity. The study participants reported a moderate level of depressive symptoms as measured by the CES-D, and about 25% of them scored above the cut-off point of 16. The PSI was used to assess the to- tal physical symptoms in the past month. Only 3 participants were symptom-free; on average, they experienced a total of 5.5 symptoms (SD=3.2), with a median of 5 symptoms. The most common symptoms were fatigue (76.7%), followed by head- ache (74.8%), trouble sleeping (52.5%), backache (52.4%), and upset stomach (50.4%). However, only a few of them had visited a doctor because of the above physical symptoms.
Sleep Characteristics These students reported in the GSDS that, on av-
erage, they experienced sleep disturbances about 3 nights during the past week (Table 1) and none of them had good sleep nightly. It was surprising to note that about 68% of them were identified as insomniacs by using the total scores of PSQI (> 5), with an average of 6.29 (SD=2.98) and median of 6 (ranging from 1 to 18). On average, they went to bed around 11:34 p.m. (SD=112 minutes) and got up around 7:25 a.m. (SD=87 minutes); however, there was a wide variance in both bedtime (range 9:30 p.m. to 3:45 a.m.) and arise time (range 5:00 a.m. to noon). The nocturnal total sleep time (TST) was calculated from the 7-day diary. On average, they slept about 7 hours (ranging from 4 to 9.5 hours). Their TST was significantly less than what they needed to feel rejuvenated (t[102]= 4.15, p < .001), and they slept less during weekdays com- pared to weekend days (t[102]=6.50, p < .001). Altogether, data indicate they were sleep deprived and their activity (sleep-wake) circadian rhythms were not well-synchronized, which may increase their vulnerability to adverse health outcomes.27 About half of the study participants scored ESS
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Am J Health Behav.™ 2013;37(6):851-858 855 DOI: http://dx.doi.org/10.5993/AJHB.37.6.14
above the cut-off point of 9, indicating they were very sleepy during daytime and should seek medi- cal attention for their daytime sleepiness problem.
Given that ethnicity may play a role in sleep characteristics,28 we also explored if there were any significant differences by ethnic group. It turned out that only TST needed to feel refreshed (F[3, 99]= 2.94, p = .04) and the nocturnal TST
during the weekend (F[3, 99]= 3.34, p = .02) were different among ethnic groups. Whites needed the greatest amount of sleep time (8.01 + 1.22 hours), but Blacks needed the least (7.05 + 1.09 hours) to feel refreshed. Whites also slept longest (8.24 + 1.29 hours) during the weekend compared to the other ethnic groups. Although there was no statis- tical significance, on average, Asian slept the least
Table 2 Correlations among Stress, Sleep, and Health-related Well-being
Variables 1 2 3 4 5 6 7
1. PSS --- 2. GSDS .53** --- 3. PSQI .56** .61** --- 4. ESS .43** .57** .47** --- 5. CES-D .74** .49** .65** .41** --- 6. AM Fatigue .33** .48** .33** .18 .36** --- 7. TST -.20* -.33** -.28** -.33** -.26** -.29* --- 8. Physical Symptoms .43** .44** .56** .29** .51** .29** -.19*
*p < .05 ** p < .01
Note. PSS= Perceived Stress Scale; GSDS= General Sleep Disturbance Scale; PSQI= Pittsburg Sleep Quality Index; ESS= Ep- worth Sleepiness Scale; CES-D= Center of Epidemiology Scale-Depression; TST= Total Sleep Time. -.19*
Table 3 Variables Associated with Depressive Symptoms and Physical Symptoms
Predictor
Depressive Symptoms Physical Symptoms
B β ∆R2 B β ∆R2
Step 1 (covariate) Age -.08 -.07 -.01 -.03 Ethnic groups .02 .00 -.13 -.05 BMI -.09 -.05 .008 .005 .007 .003
Step 2 PSS .79 .57** .48 .41** PSQI 1.06 .33** .625** .10 .20* .298** Total R2 .633** .301**
*p < .05 ** p < .01
Note. PSS= Perceived Stress Scale; GSDS= General Sleep Disturbance Scale; PSQI= Pittsburg Sleep Quality Index; ESS= Epworth Sleepiness Scale; CES-D= Center of Epidemiology Scale-Depression; TST= Total Sleep Time.
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amount of time during the weekdays (6.5 + .92 hours) compared to the other ethnic groups. Find- ings from this study are consistent with those from the 2010 National Sleep Foundation.28
Correlations among Stress, Sleep, and Well-being
Bivariate correlations were used to examine the associations (Table 2) among perceived stress, sleep disturbances (GSDS, PSQI), daytime sleepi- ness (ESS), depressive symptoms, fatigue severity (NRS-F), nocturnal total sleep time, and physical symptoms (PSI). The women’s perceptions of their overall stress was significantly and positively as- sociated with sleep disturbances, daytime sleepi- ness, depressive symptoms, morning fatigue se- verity, less nocturnal total sleep time, and more physical symptoms (p < .05). Although 64% of the study participants experienced financial difficulty, the financial burden only accounted for about 6% of their global stress and was not significantly as- sociated with any well-being outcome variables that we measured in this study (p > .05). The indi- viduals who reported poor sleep also experienced more fatigue, depressive symptoms, and physical symptoms. Those who had less total nocturnal sleep time also experienced higher fatigue severity and reported more depressive and physical symp- toms.
Predictors for Depressive Symptoms and Physical Symptoms
The last 2 research questions were answered by hierarchical regression analyses to determine the extent to which variables account for the variance in of severity of depressive symptoms and physical symptoms. The personal characteristics (ie, age, ethnicity, and BMI) were entered into the models first, as these variables are known to be associ- ated with the outcome variables, depressive symp- toms, and physical symptoms, followed by the per- ceived stress measured by the PSS and sleep qual- ity measured by the PSQI (Table 3). No significant association between personal characteristics and outcome variables was found for either model. The final model contained only 2 significant predictors for the depressive symptoms: perceived stress (t= 10.81, p < .001) and poor sleep quality (t= 8.00, p < .001), which accounted for 63.3% of the variance in depressive symptoms (F[5, 98]= 32.01, p < .001). Perceived stress (t=4.52, p < .001) and poor sleep quality (t= 5.92, p < .001) accounted for 30.1% of the variance in physical symptoms (F[5, 98]= 8.00, p < .001).
Comparison of Normal and Poor Sleepers on Health-related Well-being
Based on the PSQI score, the study participants were categorized into normal sleepers (PSQI < 5) and poor sleepers (PSQI > 5) to test the hypoth- eses (Table 4). Compared to good sleepers, poor sleepers perceived significantly higher stress levels (above the cut-off point) and experienced higher daytime sleepiness (p < .01). Poor sleepers also re-
Table 4 Comparison Between Good Sleepers and Poor Sleepers Based on PSQI
Variables Good sleepers Poor sleepers t-values* (N = 33) (N = 70) (df = 101)
Mean (SD) Mean (SD)
Age 24.58 (5.99) 27.16 (8.58) 1.56 TST 7-days Weekdays Weekend
7.43 (.78) 7.17 (.96)
8.06 (1.17)
7.02 (1.11) 6.75 (1.18) 7.70 (1.57)
1.91 1.77 1.15
ESS 6.36 (3.67) 8.72 (4.04) 2.84**
PSS 12.97 (4.47) 17.83 (6.61) 3.82** CES-D 7.09 (5.77) 14.10 (9.27) 3.99** AM Fatigue 3.47 (1.65) 3.97 (1.42) 1.56 Physical Symptoms 3.91 (2.29) 6.26 (3.29) 3.69**
*p < .05 ** p < .01
Note. Good sleepers= PSQI < 5 Poor sleepers= PSQI >5 PSQI= Pittsburg Sleep Quality Index; TST= Total Sleep Time; GSDS= General Sleep Disturbance Scale; ESS= Empower Sleepiness Scale; PSS= Perceived Stress Scale; CES-D= Center of Epidemiology Scale-Depression.
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Am J Health Behav.™ 2013;37(6):851-858 857 DOI: http://dx.doi.org/10.5993/AJHB.37.6.14
ported significantly more physical and depressive symptoms (p < .01). Both groups reported an above cut-off score for morning fatigue severity. Although the rest of the health-related outcome variables were all below the cut-off points, for the depressive symptoms, 30% of the poor sleepers and 6% of the good sleepers scored above the cut-off point.
DISCUSSION This study described the female college students’
sleep characteristics and their effects, along with the impact of stress on physical and mental health outcomes; further, it examined whether poor sleepers experienced more adverse health out- comes than good sleepers. Results showed serious existing and potential health problems for these women. Although all of the study participants were without a history of physical and depression prob- lems or sleep disorders, they were stressed out, sleep deprived, fatigued, sleepy during the day- time, and had significantly high depressive symp- toms and physical symptoms. These findings also suggest that stress derived from daily life was as- sociated with poorer health-related well-being and that poor sleepers were more vulnerable to adverse health outcomes. As we hypothesized, women who were classified as poor sleepers (PSQI >5) expe- rienced more depressive symptoms and physical symptoms compared to good sleepers. Perceived stress and poor sleep are significant predictors of depressive symptoms and physical symptoms.
College students experience predictable, stress- ful life events typically associated with reduced sleep, a change in circadian phases in an “ex- periment of nature” that occurs during the school year. A major advantage of studying these phe- nomena with this naturalistic approach is that sleep and well-being can be examined in a natural context over extended periods, rather than in a contrived laboratory context over short intervals. In this study, participants kept a sleep diary to record their bedtime and arise time for 7 consecu- tive days and nights. Findings from the sleep di- ary revealed that more than half of the students slept less than 7 hours during weekdays and they tended to catch up on their sleep debt during the weekend. The total nocturnal sleep time for these students was significantly less than what they needed to feel refreshed; on average, the total sleep time during weekdays was about one hour less than what they desired to have. In addition, their activity circadian rhythms were not synchro- nized, demonstrated by the large variance in their bedtime and awaking time records from the 7-day sleep diary. These findings are consistent with pri- or studies showing that college students are sleep deprived2,17 and that adult Blacks require the least amount of nocturnal sleep time to function well.28 Other studies also found that insomnia could con- tribute to emotional distress and suicidal ideation for college students.1,18 Altogether, these findings highlight a critical need for preventive care for col-
lege women. Limitations
This study is unique in 2 ways. First, it included an ethnically diverse group of women and explored their sleep characteristics and the relationships of these characteristics with stress and health out- comes. Second, it used both a standardized ques- tionnaire and a 7-day sleep diary to comprehend participants’ sleep patterns better and to differ- entiate between weekday and weekend sleep pat- terns. Although the study findings contribute to knowledge about female college students’ stress and sleep patterns and their impact on well-being, findings should be considered in light of the use of a convenience sample rather than a random sam- ple. Moreover, the geographic location was limited to an urban area in the southern US. In addition, this study only relied on self-report data which could result in bias. Future studies should include objective measurements, such as the wrist acti- graph, to assess sleep-wake patterns, and blood or saliva samples to examine biomarkers that are associated with stress, sleep disturbances, and health outcomes.
Conclusions Female college students in this study were dis-
tressed and experienced multiple adverse physical and emotional symptoms. Only about 19% of the students we approached to participate ultimately took part in this study. Those who did not sign up for this study possibly were experiencing higher levels of stress or had some conditions which dis- suaded them from participating. Although stress likely will continue to be a characteristic of college life, administrators and college health profession- als can work with students to find ways to allevi- ate stress and improve academic performance. Re- searchers at a large private university found that first-year students demonstrated reductions in depressive symptoms, along with improvements in sleep quality, after undergoing a self-administered cognitive behavior program.17 Additional research and attention to the problems of stress and poor sleep among college students will continue to ben- efit this population.
A better understanding of the associations among stress, sleep disturbances, and adverse health out- comes could advance clinicians’ knowledge in the prevention and treatment of certain diseases re- lated to stress and sleep problems. Interventions, such as mind-body exercise to reduce stress, im- prove sleep, and decrease depressive symptoms, are needed to promote students’ well-being. Edu- cational materials in the areas of stress-coping and sleep hygiene and their impact on health outcomes should be mandatorily included in the college cur- riculum. This study also shows that ethnicity plays a role in individual sleep characteristics; studies should attempt further exploration of the causes of differences across ethnic groups from both a genetic and an environmental perspective. Fail-
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ure to understand the mechanisms linking sleep disturbances with different developmental stages among diverse ethnic groups of women is a pos- sible reason that an effective intervention has not yet been developed and tested. Tailored interven- tions may be the key to promote better health and well-being, and thus, improve the quality of life for college women.
Human Subject Statement The Institutional Review Board at Georgia State
University approved the study.
Conflict of Interest Statement The research was supported by the Scholarly
Support Program at Georgia State University. The authors acknowledge no conflict of interest with the funding or the research study
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