Karlyn E. Vatthauer
College of Arts & Science, Department of
Psychology, & Honors College
Mentor: Dr. Daniel Taylor, Ph.D., Department of
Psychology, UNT
Research Topic
 The predictive relationship of sleep and
academic performance (GPA).
Vocabulary
 Traditional - variables that have commonly been
shown to predict academic performance in
previous research
 High school GPA, standardized test scores,
ethnicity, gender, socioeconomic status
 Modifiable - variables that may be amenable to
treatment to increase academic performance
 Alcohol/drug use, alcohol/drug disorder,
anxiety, depression, sleep
Purpose
 The intention of this project was to compare
traditional and modifiable variables, specifically
sleep, as predictors of GPA (cumulative &
semester*).
* Data not shown in this presentation
Research Questions
 Is sleep significantly correlated with GPA?
 If yes, in what way?
 Is sleep a significant predictor of GPA when other
variables are accounted for?
Literature Review
 Several studies have shown a positive
correlation between undergraduate academic
performance (GPA) and postgraduate earnings
(Filer 1981, 1983; Jones & Jackson, 1990;
Pascarella & Terenzini, 2003; Wise, 1975).
 Colleges and universities rely very heavily on
standardized test scores and high school grades
to predict GPA.
Literature Review
 When combined, HS GPA and standardized test
scores only predict 25 % of GPA variance (ACT,
1997; Boldt, 1986; Mathiasen, 1984; Mouw &
Khanna).
 In previous studies, gender, ethnicity, and
socioeconomic status (SES) have predicted GPA
(Betts & Morell, 1999; Peters, Joireman, &
Ridgway, 2005).
Literature Review
 Research has shown mixed results (negative
relationship or no relationship) for alcohol use as
a predictor of GPA (Paschall & Freisthler, 2003;
Singleton, 2007).
 Chronic drug use leads to cognitive impairments
on achievement tests (Block, Erwin, & Ghoneim,
2002; Hoshi, Mullins, Boundy, Brignell, Piccini, &
Curran, 2007; Solowij et al., 2002).
Literature Review
 Previous and current research has shown a
positive relationship between anxiety disorders
and GPA (Stringer, Crown, Lucas, &
Supramanium, 1977).
 Research has yet to show whether a
relationship exists between depression and GPA
(Hysenbegasi, 2005; Svanum & Zody, 2001).
Literature Review
 Research of sleep patterns and academic
performance has been very limited.
 Most researchers use total sleep time to study
differences in sleep patterns (Gau et. al, 2007;
Peters et al., 2005; Thacher, 2008).
 There are many other sleep variables that can
be studied:
 Time in bed, sleep efficiency, sleep onset
latency, wake after sleep onset, time awake
in morning, nap time, and number of
awakenings
Literature Review
 Sleep problems are a frequent occurrence within
the college population (Forquer, Camden,
Gabriau, & Johnson, 2008).
These problems should
affect more than the
bedroom.
Hypotheses
 Sleep pattern will be significantly correlated with
GPA because it is a primary part of students’
lifestyles.
 Specifically, sleep onset latency, wake time
after sleep onset, and time awake in morning
will predict GPA.
 Sleep pattern will significantly predict GPA when
all variables are accounted for.
 Sleep pattern will significantly predict GPA when
traditional variables are removed.
Methods
 Participants (N = 951) were recruited from
undergraduate psychology classes at the
University of North Texas.
 Participants completed a self-report health
questionnaire packet and a week long sleep
diary, available on the SONA system, an online
research service.
 Students received four extra credit points
towards their psychology class.
Methods
 Demographics
 74% were females
 Ethnicity
63% Caucasian
 13% African-American
 10% Hispanic-American
 5% Asian/Pacific-Islander
 1% Native American
 4% other
 Academic rank
 40% freshmen
 27% sophomores
 19% juniors
 15% seniors
 Age (M = 20.3; SD = 3.9).
 Family income ( Mean = $100,000 - $149,000 (SD = 2.9)

Data Analysis
 Multiple correlation
 Sleep pattern variables and GPA
 All other variables and GPA*
 Stepwise multiple regression
 Significant correlates and GPA**
 Significant modifiable variables and GPA
*Data not shown in this presentation
**Only sleep pattern variables shown
Results
 Multiple correlation of sleep pattern and GPA
 Significant relationship between GPA and:



Sleep onset latency (r = -.06, p < .05)
Nap time (r = -.11, p < .01)
Number of awakenings (r = .08, p < .05)
Table 1
Summary of Stepwise Multiple Regression Analysis with Significant
Correlates as Criterion
Step
Predictor Variable
R²
R²
F
β
6
NWAK
.18
.01
5.93*
.10**
7
NAP
.19
.01
6.42*
-.08*
Note. NWAK = Number of Wakenings; NAP = Nap Time; PSS =
Perceived stress scale
*p < .05. **p < .01.
Table 2
Summary of Stepwise Multiple Regression Analysis with Significant InterventionPossible Correlates as Criterion
Step
Predictor Variable
R²
R²
F
β
1
AUDIT
.02
.02
20.26**
-.12**
2
NAP
.03
.01
11.44**
-.11**
3
PSS
.04
.01
9.20**
-.11**
4
NWAK
.06
.01
10.02**
.11**
5
MPS
.06
.01
5.07*
-.08 *
Note. AUDIT = Alcohol use disorders identification test; NAP = Nap Time; PSS =
Perceived stress scale; NWAK = Number of Wakenings; MPS = Marijuana
problem scale. *p < .05. **p < .01.
Discussion
 Sleep pattern was significantly correlated with
GPA.
 Specifically, sleep onset latency, nap time, and
number of awakenings.
 Nap time and number of awakenings continued
to be significant predictors of GPA after
accounting for all other variables
 Each accounted for an additional 1% of GPA
variance.
Discussion
 Overall, of modifiable variables:
 Sleep variables accounted for 2% of GPA
variance
 Alcohol use disorders 2%
 Trait stress 1%
 Marijuana use 1%
Acknowledgements
 Dr. Daniel Taylor, Psychology
 Dr. Susan Eve, Associate Dean of the Honors
College
 Dr. Gloria Cox, Dean of the Honors College
 Department of Psychology
 College of Arts and Science
References
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Betts, J.R. & Morell, D. (1999). The determinants of undergraduate grade point average. The
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Block, R. I., Erwin, W. J., & Ghoneim, M. M. (2002). Chronic drug use and cognitive impairments.
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Filer, R. K. (1981). The influence of effective human capital on the wage equation. In R. G.
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Forquer, L. M., Camden, A. E., Gabriau, K. M., & Johnson, C. M. Sleep patterns of college students
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Hoshi, R., Mullins, K., Boundy, C., Brignell, C., Piccini, P., & Curran, H. V. (2007). Neurocognitive
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Jones, E. B. & Jackson J. D. (1990). College grades and labor market rewards. The Journal of
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References
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