Thesis Nurs. 1995 C814S
c.2
Cornell, Margaret
Norgang.
Stress and academic
performance /
1995.

STRESS AND ACADEMIC PERFORMANCE

by
Margaret Norgang Cornell BSN, RN

Submitted in Partial Fulfillment of the Requirements
for the Master of Science in Nursing Degree

Approved by:

PM/t
pPtidM,
Chairperson/ thesis

tPn Ms.

Committee
Edinboro University of Pennsylvania
Committee Member
Committee Member

Date

Date

ABSTRACT

This study examines the correlation between stress
and academic performance using the life events model to

measure stress.

Full-time nursing students enrolled in

an associate degree program at a rural community
college were participants in this study.

This study

concludes that there is a weak negative correlation
between stress and grade point average; r=.2553 with a
significance of .024.

Further study is recommended to

examine the effect of coping strategies, age,
socioeconomic status on stress and its relationship to

academic performance among community college students.

iii

ACKNOWLEDGEMENTS

The writer wishes to express sincere thanks and
appreciation to Charlotte Paul PhD, RN, Mary Lou
Keller, PhD, RN and James Palmer, MA for their time,

guidance and especially their patience in completing

this study.
In addition the writer wishes to express gratitude
to the many people at Jamestown Community College who

made this study possible.

A special thanks to my husband William for his
support and encouragement and to my son Stephen for his
inspiration.
MNC

May 1995

iv

Table of Contents
Abstract

Acknowledgments
Table of Contents

ii

iii
iv

List of Figures

v

Chapter
1. INTRODUCTION
Background of the problem
Statement of the purpose
Statement of the Problem
Assumptions
Definition of Terms
Limitations of the Study

1
4
5
5
5
6

2. REVIEW OF LITERATURE

7

3. METHODOLOGY
Setting
Sample
Instrumentation
Collection of Data

19
19
19
20
20

4. DATA ANALYSIS

24

5. CONCLUSIONS & SUMMARY
Recommendations

33
35

APPENDICES
A PERMISSION FOR RESEARCH APPROVAL
B PERMISSION FOR RESEARCH APPROVAL
C PERMISSION FOR QUESTIONNAIRE
D COVER LETTER FOR QUESTIONNAIRE
E STUDENT CONSENT
F HOLMES AND RAHE QUESTIONNAIRE
G ORIGINAL COLLECTED DATA

36
37
38
39
40
41

REFERENCES

42

V

LIST OF FIGURES

FIGURE

PAGE

1.

Frequency distribution of age

25

2.

Frequency distribution of marital status

26

3.

Frequency distribution of number of children
living in family

27

4.

Frequency distribution of annual household
incomes

28

5.

Frequency distribution of SRE scores

29

6.

Frequency distribution of GPA scores

30

7.

Scatter plot of correlation between SRE
and GPA

31

1

CHAPTER 1

INTRODUCTION

BACKGROUND OF THE PROBLEM

Academic problems facing our nation's colleges and
universities have been well documented.

Many authors

generally agreed that a decline in academic performance

has been occurring for several years.

Although many

examples have been cited, the following are most

noteworthy:
First of all, national statistics indicate that

students either failed or withdrew from forty percent
of their classes each semester (Roueche et al., 1989).

Secondly, student performance on global tests in
mathematics and science was reported to be poorer
according to a recent State University of New York
publication (University Faculty Senate, 1992) .

Lastly, it was noted by The Association of

American Colleges that decline is everywhere and that
approximately one half of all freshman classes

demonstrated deficiencies in mathematics and English
(Douglas, 1993).

2

Although there is consensus about the decline in

academic performance there are several opinions

regarding the cause.

Several factors contributing to

this decline have been well publicized.

Students doing

less work (Douglas,1993) and poor leadership (Roueche

et al, 1989) have been cited as examples.

Eroding

academic standards, inadequate secondary education,
grade inflation, cheating, social income, family
support and poor teaching have also been cited as
factors affecting academic performance.

(Sowell, 1993)

Stress has also been considered to affect

performance (Veninga, Spradey, 1981) and more
specifically teacher performance (Farber, 1991).

Authors of The Work Stress Connection pointed out that

job stress results in poor performance ie; making more
mistakes, avoiding decision making, being less creative
and having more on-the-job accidents (1981).

A similar

finding was also noted by Farber (1991) with regard to
teacher performance.

He found that stress resulted in

poorer performance and suggested that this had
potentially devastating effects on pupil education.
Grades are presumed to reflect performance.
Research on stress and its direct effect on academic

performance indicates that there is a relationship

3

between stress and academic performance (Wildman,
1978). Wildman's study (1978) concluded that stress had

an adverse affect on grades after a certain level of
stress was reached.

Because research in this area is

limited, Wildman recommended that further studies be

conducted.
Stress research was pioneered by Canadian

physician Hans Selye.

His research primarily focused

on the physiological responses of stress.

In his book,

The Stress of Life, he clearly presents convincing
evidence of the mind-body connection and its
relationship to illness by application of his general
adaptation syndrome model (Selye, 1956).

Holmes and Rahe pioneered research on the

relationship of life events to physical and mental

illnesses.

Their research demonstrated that certain

life events were stress producing and consequently
affected health.

Holmes and Rahe were responsible for

creating the Social Readjustment Rating Scale (SRRS)
which assigned a numeric value to each life experience

(1967) .

This tool has been used in a number of

experiments and is considered valid and reliable.
In conclusion, our educational institutions are
having serious problems with a decline in academic

4

performance.

Several sources have recommended that we

examine more closely the reasons for this decline.

In

particular, The State University of New York and The
Middle States Association

of Colleges on Schools

recommend an ongoing evaluation of academic performance

and student retention (Commission on Higher Education,
1983) .

Several contributing factors have been associated
with this decline.

Stress in particular has been found

to affect job performance, teacher performance,

academic performance and health.

Additional research

was recommended by one author (Wildman) to examine the
relationship between stress and academic performance.
Based on the above conclusions and

recommendations, research on the relationship between
stress and academic performance seems pertinent.

PURPOSE OF THIS STUDY

The purpose of this study is to examine the degree

to which stress and academic performance are related.
In doing so, the results will provide insight into a
possible contributing factor affecting the decline in
academic performance at the community college level.

If the level of stress is a predictor of academic

5

performance, perhaps early stress assessments can be
considered and possible stress management interventions

entertained.

STATEMENT OF THE PROBLEM

To what degree does stress impact on academic

performance among full-time community college nursing
students?

This study is designed to demonstrate that

there is a strong negative correlation between stress

and grade point average.

ASSUMPTIONS
An assumption congruent with research is that

stress can be measured.

Several measurement tools have

been validated through research.

Life events have been

thought to be indicators of stress and therefore have

been used as a measurement tool.

Another assumption is

that academic performance can be measured.

DEFINITION OF TERMS

1.

Stress is defined as the sum of self-reported life

change units on the SRRS occurring within a six month

period.

6

2.

Academic performance is defined as the fall

semester Grade Point Average as reported by the college
registrar.

3.

Student is defined as full-time sophomore nursing

student.
4.

Full time is defined as the total number of credit

hours taken in a semester to be between ten and not to

exceed seventeen.

LIMITATIONS OF STUDY

1.

The findings reflect responses from sophomore

student nurses enrolled in one associate degree

program.

2.

The findings cannot be generalized to nursing

students at other community colleges.

3.

Use of the self reported instrument may not

reflect accurate information.

7

CHAPTER II

REVIEW OF LITERATURE

The purpose of this study is to examine the
relationship between stress and academic performance.

This study will attempt to answer the question of

whether or not high levels of stress affect academic
performance among community college nursing students.
The theoretical background for this study was

based on Seyle's concept of stress (Selye,1956).

Selye

believed that stress was a non-specific response of the

body to any demand.

His research concluded that

several physiological adaptations occurred as a result

of repeated exposures to stress and that this caused
many pathological conditions.

Selye found that stress

produced a decrease in eosinophils and an increase in
serum cholesterol, glucagon, insulin, prolactin, and a
constant release of corticosteroids.

Selye also noted

that the adrenal cortex became enlarged, but the thymus

gland, spleen, and lymph nodes atrophied.

Ulcers were

noted in the stomachs and colon of experimental

animals.

Selye referred to these changes, the body

trying to adapt, for example, as the General Adaptation

8

Syndrome and identified three stages of this syndrome.
Stage one or stage of alarm is the initial stage in

which forces are mobilized to maintain life and cope
with the stressor. In stage two or stage of resistance,

the body is attempting to restore homeostasis even
though the stress still exists. In stage three or stage

of exhaustion, the body can no longer respond and
begins to fail ultimately resulting in death.

Selye outlined several signs and symptoms
occurring as a result of these stress induced

physiological changes.

Examples include: increased

blood pressure and accelerated heart rate, diaphoresis,

irritability, dry mouth, weakness, dizziness, insomnia,

diarrhea, and indigestion.

A case can be made that

these symptoms interfere with cognition, however, there
are two other reported symptoms that are more pertinent
to this study.

They are fatigue and the inability to

concentrate due to a flight of thoughts and general

disorientation (Selye, 1956).
Major life events have also been considered
stressors causing disease.

The relationship between

major life events and negative health outcomes is well

documented.

In 1964, Rahe, et al published results of

research in this area.

After surveying thousands of

9

individuals, forty three common life events were
identified as those responsible for activating stress.

After identifying these specific life events as
stressors, several physicians were asked to compare

health changes with the occurrence of life events.

There proved to be a significant correlation between

high life event scores and negative health outcomes
(Rahe, 1964)

In 1967, Holmes and Rahe further

developed this tool by adding a weighted numerical

value to each event.

This was called the Social

Readjustment Rating Scale (SRRS).
The SRRS has been used in several studies and has

been validated.

In 1975, a longitudinal study examined

the effects recent life changes have on cardiac events.

A correlation was found between life changes and
cardiac events such as arrhythmias and ventricular
contraction.

These findings were thought to validate

previous studies that indicated that life change events
were measures of stress and predictive of physiological

changes.(Theorell, Rahe, 1975)
Another study examined the influence of recent
life experiences on subsequent illnesses of the college
freshman.

The College Schedule of Recent Experiences

was used.

An association was found between high levels

10

of life change and increased illnesses.

(Marx, et al,

1975)
In 1979, a retrospective study looked at the

association between life change and the onset of

ulcers.

This study indicated that ulcer operations

occurred at a time following increased life changes.

Also reported was a correlation between life change and
post-operative gastrointestinal symptoms.

(Stevenson,

et al)
In summary, many studies have utilized life events

to measure stress and have found it predictive of

performance and physiological changes.

Therefore it is

generally considered to be a reliable, valid tool.

In 1978, another life events model was developed
called the Life Experience Survey (LES).

This model

listed forty seven life events, but did not assign a

value to their importance.

Instead each participant is

asked to rate the degree of distress experienced.

Results achieved with this model were very similar to
those achieved using the SRRS (Sarason, et al).
Research regarding the possible relationship

between stress and academic performance is difficult to
find.

Most of the research in this area is dedicated

to test anxiety.

11

The research conducted by Knapp (1975) looked at
utilization of life events as an indicator of the

amount of stress by summing the total number of events
experienced in a given time period and rating the life

event as either desirable or undesirable.

In this

study, college students rated the life events that had
occurred within the past year.

Desirable life events

did not correlate with grade point average.
Undesirable life events strongly correlated with lower
grade point averages when academic ability and past

academic performance were factored out.

This study

concludes that undesirable life events are a better
predictor of grade point average.

In 1989, Chapin questioned whether or not anxiety
is always a debilitating factor, even though it is most

commonly considered one in college students with regard
to academic performance.

He compared high-anxious high

performance students (HAHP) with high-anxious low
performance college students (HALP).

This study

suggested that HAHP and HALP students do experience

anxiety differently.
anxiety

The HAHP student found that

facilitated their performance while HALP found

that anxiety debilitates performance. The study found

that these differences held true regardless of the type

12

of anxiety, but failed to take coping
and performance
into account. Furthermore, it failed to control for

scholastic aptitude.

In Chapin's second study, however, scholastic

aptitude was taken into consideration.

This study

found that scholastic aptitude was a significant

covariant with both manifest anxiety and academic

performance.

It concluded that anxiety can facilitate

as well as debilitate students' performance.

In conclusion, it

suggests that anxiety may not

always be considered a debilitation factor.

Both of

the studies also suggested that stress can be a
facilitating factor if properly channeled.

Chartrand (1990) examined nontraditional student
adjustment with regard to student role evaluation,

commitment to student role and self-good student role
congruence.

The purpose of this research was to

determine if these were predictors of personal distress
and academic performance.

Two variables, anxiety and

depression were operationalized as personal distress.

The State scale of the State-trait Anxiety Inventory
was used to measure anxiety and the Beck Depression
Inventory was used to measure depression.

Academic

performance was defined as the grade point average.

13

Nontraditional students face difficulties of commitment
to the role of a student because they are
simultaneously being committed to other life roles such

as mother, parent, employee etc..

Maintaining a high

degree of commitment among all of the different life

roles is often difficult and stressful.
The results of this study suggest that self

evaluation and commitment to student role had an affect
on student role congruence.

Student role congruence

was found in turn, to be a predictor of personal
distress and

grade point average.

The multistage causal learning model of academic

achievement developed and validated in 1989 looks at
the effects of the following on academic achievement:
reading, language, math ability, life stress,

motivation, self-monitoring/use of study strategies,
and concentration and preparation for class.

(Chacko,1991)

In this study, the ASSET test was used

to measure cognitive ability; the Life Experience

Survey (LES) developed in 1978 by Sarason, Johnson and

Seigel measured the individual 's life stress, and a
modified learning and study strategies inventory

(Weinstein, 1987, Chacko, 1989) measured affective
learning strategy variables.

The instrument used to

14

measure stress consisted of forty-seven life events.

A

Likert scale ranging from extremely positive (+3) to

extremely negative (-3) was incorporated into this
survey.

Chacko's study found that life stress was directly
related to the students' level of preparedness for

class and concentration in class (1991).

It supported

the view that life stress may have a negative
relationship with academic achievement.

However, the

relationship between stress and academic performance

was found to be weak.

A limitation of this study was

in the use of self-reported instruments to measure all

independent variables with the exception of reading,
language and math ability.

This may lead to the

subjects' perceptions rather than actual behaviors.

Four other studies examined the relationship
between stress and grade point average by using life

events as the instrument to measure stress.

(Wildman,

1978; Lloyd, et al 1980; deMeuse, 1993; Huerta, 1990)

Wildman 1s research examined various tools for
measuring stress based on life events.
were devised to measure life events.

Four methods

One method simply

counted the number of events occurring within a given
time frame, another weighted each event according to

15

severity and the weighted values were counted, the

third method, counted how many times each event

occurred (up to four for each event) but weighted
values were not assigned,

and the last method

multiplied the number of times each event occurred with

the weighted value and added the numbers together.
Results suggested that the individual events had the
most impact on academic performance and not the

multiple occurrences of an event.

Results also

indicated that there was a threshold affect.

It

appeared that stress had an adverse affect on grades

after a certain point.

Further study on the affect of

stress on grades was one of the recommendations of this

study.
Lloyd et al (1980) used the Barron Ego-Strength
Scale, a revision of the Schedule of Recent Life

Events, and a form for rating the degree of
readjustment required by the life events to calculate
life changes.

Results demonstrated a significant

negative relationship between life change and academic
performance.

This study also suggested a threshold

effect, since the detrimental impact of life change

appeared evident only after the occurrence of about
twelve events in the one year time period.

DeMuse

16

(1985) , on the other hand,
used the Social Readjustment
Rating Scale to measure stressful life
events.
Correlation of the students responses with later
measures of academic performance upon completion of the
course indicated that life stress was a predictor of
exam scores, extra-credit points, and total course

points.

In conclusion, life stress was found to be a

predictor of final grades.

Huerta (1990) conducted a study involving nursing
students because of stress-related high attrition

rates.

The purpose of this study was to investigate

the relationship between stress and academic

achievement.

The Life Experiences Survey was used to

measure stress.

The results found that negative change

stress had a significant relationship with academic

achievement.

few.

Identification of positive stressors were

The academic environment was identified as a

contributor to the students1 stress by infringing on

personal time, causing illness and producing clinical,
academic and financial pressures.
Hensley's (1991) research focused on developing an
instrument to measure stress specifically for

undergraduate college students.

His sample consisted

of students in a highly competitive university setting.

17

The questionnaire consisted of events that
were
categorized under four classifications:
death/injury
to a valued other, academic achievement, general

college pressures and college nuisances,

Participants

were asked to identify the degree of stress for each of
the fifty-two events.

The results indicated that

females reported more stress than males in all areas.
A final questionnaire listing twenty events proved to

be a fairly reliable instrument for measuring stress
among college students.

The relative magnitude of

certain stressors was enlightening.

In summary, stress and its affect on physiological
function has been well researched and documented.

It

has also been demonstrated that stress and academic
performance are related.

The life events model has

proven to be an effective tool to measure stress and

has been used most frequently in research to measure
the affect of stress on academic performance.

Several

authors have concluded that certain life events
occurring within one year are predictors of academic
performance (Chacko, 1991; Wildman, 1978; Lloyd, et al

1980; deMeuse, 1993; Huerta, 1990).

While some

investigators used the Social Readjustment Rating Scale

to measure stress, others used a similar model that

18

rated the degree of distress caused by the event.

Both

found a relationship between stress and academic

performance.

Results achieved by one author using The

Life Experience Survey were rated to be very similar to

the Social Readjustment Rating Scale Schedule (Sarason
et al, 1978).

Other authors have developed and tested

other models, however, their use is not widespread

(Sarason, Lloyd, Knapp, Hensley).

19

CHAPTER III

METHODOLOGY

The purpose of this study is to examine the degree
to which stress and academic performance are related

among community college sophomore nursing students.

This study took place in a small rural community
college setting.

RESPONDENTS

Participants in this study consisted of first

semester full-time sophomore nursing students enrolled
in an associate degree program at two separate campuses
in a small rural community college in Western New York.

The campuses are approximately sixty miles apart.

This

convenience sample represents all full-time sophomore

nursing students attending this college who were
present during data collection.

Eighty-two full-time

nursing students are currently enrolled in the
sophomore nursing program at the college.
Sophomore nursing students were selected for this

study because of certain homogenous characteristics,
namely,

familiarity with the college, the environment,

20

and academic expectations, similar
course content and
prior GPA of 2.7 or better, This narrowed the number
of possible variables affecting this study.

INSTRUMENTATION
The Social Readjustment Rating Scale (SRRS)

developed by Holmes and Rahe was used as the stress

survey in this study (see appendix F) . Permission to
use this tool was granted by the Journal of
Psychosomatic Research as indicated by their signature

on a letter of request (see appendix C). Forty-three
life events are listed from the most stressful to the
least stressful event.

Events include both positive

and negative life events.

Each event has been weighted

according to its stress potential and a numeric value,
called "life change units," has been assigned to each

accordingly.

The life change units are added together

and a total score is obtained.

Subjects whose total

score is above 150 points are considered at risk of
developing a negative health outcome within two years.

COLLECTION OF DATA

Permission to conduct this research was solicited
from the following:

21
-Dean of Institutional
Research

-Director of Nursing Education

-Student nurses
All of the above have granted their permission as

indicated by their signature on a letter (see
appendixes A and B) , or consent form (see appendix E).
Students were informed of the nature of the study (see

appendix D) , methods of data collection, and assured

that confidentiality would be maintained.
Students were gathered in separate groups on each

campus.

Each student was given a copy of The Schedule

of Recent Experiences and instructions for completion

were read to each group as follows:
1.

Write your name, social security
number, gender, marital status, annual

household income, number of children

living with you and number of credits
you are taking this semester on the

back of the questionnaire.
2.

Under the column labeled RANK, circle
the number associated with each event

that has occurred in your life from
1994.
June 1/ 1994 through November 30,

22

3.

I will remain present to answer any
questions.

Upon completion, all surveys were collected.
survey was analyzed for completion.

Each

Life change units

were compiled in relationship to event and added
together to obtain a total score. Mid semester grade
point averages and age of participants were obtained

from the registrars office using name and social

security number.

Each grade point average was entered

on the individual survey correlating with that name and

social security number.

Data collection information

was kept strictly confidential and the original data
destroyed after computation.

DATA ANALYSIS

Descriptive methods were utilized to analyze this
data.

A scatter plot diagram was constructed to

demonstrate the correlation between the two variables.
Person's r correlation coefficient

was computed by

utilizing Excel software to measure the correlation

between stress and grade point average and the level of
significance.

Also bar graphs were used to show

frequency of age, marital status, number of children in

the household, annual household income, SRE scores, and

23

GPA scores.

It was determined that a significant

finding would be one of .05 or less.

24
CHAPTER IV

DATA ANALYSIS

CHARACTERISTICS OF THE SAMPLE

Seventy-eight out of a possible eighty-two
eligible participants were present and responded to the
survey on the day the data was collected.

Sixty-five

of the respondents were female and thirteen were male.

Forty-one of the students reported that they were

working at least on a part-time basis, twelve reported

that they were working on a full-time basis, and
twenty-five reported that they were not working.

Forty-one students were taking ten credit hours, seven
taking 12 hours, twenty-three taking 13 hours, six
taking 14 hours and only one student taking seventeen
credit hours during the Fall semester.
The following pages depict frequency distributions

of age, marital status, number of children in the
family, annual household income, SRE scores and GPA

scores.

(

25
The majority of students (55) were twenty-six

years of age or older.

the oldest fifty.

The youngest was nineteen and

The mean age of this sample is

thirty-one which is higher than the overall college

mean age of twenty-nine.

This sample clearly

represents the non-traditional aged student and also

represents a very broad age span.

This could

contribute significantly to the interpretation of the
findings.

Figure 1
Ages of Students

35

-- J

30-

25-r
u
c
a>
3

20 f;

SI 15-K

u.

$

io-i

I

5-

0 +L__

19-25

25-35

36-45

Age Range

45-50

26

The majority of the students in this sample were

married (thirty-nine) and those without partners ie;

single, separated, divorced or widowed also equaled
thirty-nine.

The number reporting to be separated was

three, divorced ten, single twenty-four and widowed
two.

Figure 2
MARITAL STATUS

' yjl

40-fii

35

o

H 30-1
LU
□ 25
□
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(a

u. 20

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02
111

tn

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04

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27

Although the majority of respondents reported
being married, the majority reported having no children

in their family ie; twenty-three.

Nineteen reported

one child, sixteen reported two children, eleven
reported three children, seven reported four and only
two reported that five children were living with them.

Figure 3
NUMBER OF CHILDREN
25i

tn
H
Z

20

111

§ 15
CO
U_

O
OS
111

tn

s

10

I1-,
4 5

number of children in family

28
The majority of students reported an annual

household income ranging from twenty-one to thirty
thousand dollars.

Of the six reporting zero to four

thousand dollars per year, two reported zero income,

one a questionable income, one a "poor” income and one
failed to report any income.

Figure 4
INCOME RANGES

1

25-r

20-'’
(J)
H
Z
id

a 15-*
□
to

Hi

IL

o

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Id

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11-20
21-30
31-40
INCOME IN THOUSANDS OF DOLLARS

29

Forty six respondents scored between two hundred

(200) and five hundred thirty-six (536) on the SRRS

questionnaire.

Thirty-two scored below two hundred. An

equal number of students (twenty-three) scored between

two hundred (200) and two hundred ninety-nine (299) and

three hundred (300) and five hundred thirty-six (536) .
The lowest score was twenty-six (26) and the highest
five hundred thirty-six (536) .

Figure 5
SRE SCORES

25-]

■

20-K

zId
□□ 15w
u.
o
a 10in
to
S

□z

■
26-149

150-199
200-299
SRE SCORE RANGES

300-536

30

The distribution for grade point average resembles

a normal distribution pattern.

The majority of

students fell within the 2.6 to 3.0 GPA range.

mean grade point average equaled 2.77.

Figure 6
GRADE POINT AVERAGE
30-i

25 Yl

w
S 20W
Q
□
H
CO
IL

i

154

O
Z
id

co
S 1(H

■

D
Z

0

1.0-2.0

' IK*
■IIE
2.1-2.5

2.6-3.0
GPA RANGE

3.1-3.5

3.5-4.0

The

31

Figure 7 depicts the scatter plot derived from
plotting the SRE scores and GPA scores with a predicted

regression solution (predicted Y) .

The correlation

between GPA and SRE is negative r=. 2553 (p=. 024) and
significance F = 0.024.

Figure 7

Correlation of SRE Score to GPA
4

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*

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■ Predicted Y

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£ 2•o

10

01.5 -

1 +
0

100

200

300

400

500

A
600

SRE Score

The

research question in this study asked to what

does stress impact on academic performance among
degree
full-time community college nursing students. This
study was

designed to examine the degree of correlation

32

between stress and GPA.

The results of this study

conclude that there is a weak negative correlation
between stress and grade point average and that this
finding is significant.

33

CHAPTER V

CONCLUSIONS AND SUMMARY

The correlation between stress and academic
performance has been researched and the findings

demonstrate that there is a relationship between these

two variables.

Several authors have concluded that

certain life events occurring within one year are
considered stressful and predictors of academic
performance (Chacko, 1991, Wildman, 1978, Lloyd et al,
1980, deMeuse 1993, Huerta, 1990).

This study, like Chacko's (1991) found that there
was a weak negative correlation between stress and

grade point average.

However, like Chapin's study

(1989) it failed to take coping into account but did

take scholastic aptitude into consideration as all of
the respondents achieved a GPA of 2.7 or above prior to

admission to the nursing program.
Unlike Wildman's (1978) and Lloyd's (1980)

studies

this study did not consistently find a

threshold effect.

In fact, several of the students who

reported stress scores above three hundrM
averages above three. There could be
grade point

34
several explanations fox* this finding.

Perhaps not all

students perceived each stress event as undesirable and
past research has demonstrated that undesirable life
events were better predictors of performance (1975).
Also, some students perform better under stress.

For

example, Chapin's study reported that anxiety may not
always be debilitating but can be a facilitating

factor.
This study did not examine the effect of socio

economic status, number of children in the family,
other role commitments such as mother, worker etc.,
coping strategies, perception of stress and age on the

relationship between stress and academic performance.
The mean age of the participants in this study was

thirty-one and the majority's annual household income

was between twenty-one and thirty thousand dollars per
year.
This study also failed to compare previous

performance levels without high stress levels to
performance under high stress levels. This comparison
demonstrate that an "A" student
may have been able to
when subjected to high levels of
became a "B" student
stressful life events.

35

RECOMMENDATIONS

This study found that there was a weak but

significant negative correlation between stress and
academic performance.

Further studies should be

conducted that also examine the impact of coping

strategies, age, socio-economic status and perception

of stress on academic performance.

Comparison studies

are also recommended to examine prior academic

performance without stress with academic performance
while under stress.

36

APPENDIX A

MEMORANDUM

TO:

Margaret Cornell

FROM:

Dean of Institutional Research

DATE:

April 21, 1994

RE:

Research Approval

(Name) Community College gives its approval to Ms.

Margaret Cornell to conduct her research on stress.
This approval allows Ms. Cornell to collect information
from students using a standard survey instrument and to

collect certain academic information such as student
QPAs.
Ms. Cornell will ensure the confidentiality of
this student information.

37

APPENDIX B

November 16, 1994

Dear Margaret:
It is my understanding that you would like to

survey the sophomore nursing students on the (name)
Community College campuses this Fall semester for the

purpose of conducting research for your thesis.
I have reviewed the survey tool by Holmes and Rahe

and grant permission for you to use it with the

students.

Please share the results of your findings with us

at the conclusion of your study.
Sincerely,

Director, Nursing Education

38

APPENDIX C

October 24, 1994

Journal of Psychosomatic Research

To Whom It May Concern:
I am in the process of completing my thesis for a

Masters of Science degree in Nursing.

The purpose of

this letter is to seek your permission to use the
Holmes and Rahe Social Readjustment Rating Scale to

collect data.

Thank you for your assistance.
Sincerely,

Margaret Cornell

39

appendix d

April 18, 1994

Dear Student:

I am in the process of completing my thesis as a

requirement for obtaining a master of science degree in

nursing at Edinboro University of Pennsylvania.

I am

studying the affect of stress on academic performance.

Perhaps the results of this study will provide enough
data to determine if stress assessment and
interventions are indicated for nursing students at
this college.

A questionnaire is attached.
answer all of the questions.

Please take time to

I will be available for

your inquiries while you are completing this survey.

The results of this questionnaire will be compared
with your grade point average for this semester.
your permission, I will request the registrar to
data. All data will
provide me with the necessary
remain strictly confidential.

Thank you for your assistance.
Sincerely,

Margaret Cornell

With

40

APPENDIX E

CONSENT

I hereby authorize Margaret Cornell to request

information about my grade point average from the
registrars office at (name) Community College for the

Fall semester of 1994.

I understand that this

information is being used for the sole purpose of
completing research for a thesis.

I also understand

that all data used for this purpose will remain
strictly confidential.

Student Signature

Date

41

APPENDIX F

RANK
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43

EVENT
LIFE CHANGE UNITS
Death of spouse
100
Divorce
73
Marital separation
65
Jail term
63
Death of close family member
63
Personal injury or illness
53
Marriage
50
Fired from Job
47
Marital reconciliation
45
Retirement
45
Change in Health of Family Member
44
Pregnancy
40
Sex Difficulties
39
Gain of New Family Member
39
Business Adjustment
39
Change in financial state
38
Death of a Close Friend
37
Change to different line of Work
36
Change in # of arguments with spouse
35
Mortgage over $10,000
31
Foreclosure of mortgage or loan
30
Change in responsibilities at Work
29
Son or Daughter leaving home
29
Trouble With In-laws
29
Outstanding Personal Achievement
28
26
Wife Begin or Stop Work
26
Begin or End School
25
Change in Living Conditions
24
Revision of Personal Habits
23
Trouble With Boss
20
Change in Work Hours or Conditions
20
Change in Residence
20
Change in Schools
19
Change in Recreation
19
Change in Church Activities
18
Change in Social Activities
17
Loan
Less
Than
$10,000
Mortgage or
16
Changein Sleeping Habits
15
Change
Change in Number of family Get-Togethers
15
Change in Eating Habits
13
Vacation
12
Christmas
11
Minor Violations of The Law

42

REFERENCES

Arsenault, A. , and Dolan, S.
(1983) The role of
personality, occupation and organization in
understanding the relationship between job stress,
performance and absenteeism: Journal of
Occupational Psychology, 56, 227-240

Chacko, S.B., Huba, M.E., (June 1991) Academic
Achievement Among Undergraduate Nursing Students:
The Development and test of a Causal Model.
Journal of Nursing Education, Vol. 30 No. 6
Chapin, Theodore J., (May 1989) The relationship of
trait anxiety and academic performance to
achievement anxiety: students at risk. Journal
of College Student Development, 229-36

Chartrand, Judy M.
(1990) A causal analysis to predict
the personal and academic adjustment of nontraditional students. Journal of Counseling
Psychology 37, 65-73
DeMuse, K.P.
(1985) The relationship between life
events and indices of classroom performance.
Teaching of Psychology, 12, 146-219
(January, 1993 pg 82) Resolving the
Douglas, Jack D.
crisis in Higher Education, USA Today (Magazine)

Farber, Barry (1991) Crisis in Education, Jossey-Bass
Publishers San Francisco/Oxford, pg 86-96
The measurement or
of
Hensley, Wayne E., (Oct 31, 1991) Tne
stress among college students. 1Paper presented at
the Speech Communication Associated Convention

R.H., (1967) The social
Holmes, T.H., Rahe, h..--,
readjustment rating scale. Journal of
Psychosomatic Research/ H• 213-218

Texas A & M

University Ed.u

43

napp

Samuel, (1975) The relationship of life events
co academic performance in college students
Research Report

Lloyd, C., Alexander, A.A. , D. G.,
C Greenfield, N.S.
G., j(1980) Life events as predictors of academic
performance. Journal of Human Stress. 6 (3), 1525
Marx, B. , Garrity, T. and Bowers, F.
(1975) The
influence of recent life experiences on the health
of college students. Journal of Psychosomatic
Research, 19, 87-103
Rahe, R. H. , Meyer, M. , Smith, M. , Kajoer, G., and
Holmes, T. , (1964) Social Stress and illness
onset, Journal of Psychosomatic Research, 8: 3544
—

Roueche, John E., Baker, George A., Rose, Robert R,
(1989) Shared Vision, The Community College Press.
American Association of Community and Junior
Colleges

Sarason, I.G., Johnson, J. H., and Siegel, J. M.,
(1978) Assessing the impact of life changes:
Development of the Life experiences survey.
Journal of Consulting and Clinical Psychology, 46,
932-946
Selye, Hans (1956) The Stress of Life, New York:
McGraw Hill
- -1 (1993) Inside American Education, New
Sowell/ —
Thomas,
York The Free Press, A division of Macmillan, Inc.
Stevenson, D. K., Nabseth, D. C., Masuda, M., and
Holmes T. H.
H. , (1979) Duodenal ulcers, Journal of
Human Stress, 5, 19-28

Theorell/ T. and Rahe, R. H., (1975) Life change
events,/ballistocardiography and coronary death.
journal of Human Stress, 1, 18-24
a Robert L./ and Spradey, James P., (1981) The
Venmga,
connection. Little, Brown and Co.,

44

Wildman, Richard C., (March, 1978) Life change with
college grades as a role-performance variable.
Social Psychology, 41; 1; 34-46