Sociology Mind
2013. Vol.3, No.4, 317-324
Published Online October 2013 in SciRes (http://www.scirp.org/journal/sm) http://dx.doi.org/10.4236/sm.2013.34043
Does Work Environment Affect Faculty Health Scores?
Rhonda C. Magel
Department of Statistics, North Dakota State University, Fargo, USA
Received August 7th, 2013; revised September 11th, 2013; accepted September 28th, 2013
Copyright © 2013 Rhonda C. Magel. This is an open access article distributed under the Creative Commons At-
tribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited.
This study investigates the relationship between self-reported health scores with work environment and
various components of a women faculty score at a Research 1 University in the Midwest USA. The study
examines the differences between male and female faculty responses in the various components making
up the women faculty score and also gender differences in self-reported health scores and work environ-
ment scores. Differences between STEM and Non-STEM faculty are examined. A significant positive re-
lationship is found between self-reported health scores and work environment controlling for gender. The
study finds that the overall university work environment has a stronger relationship to faculty health than
adequate gender ratio, women climate, and women leadership, even for women faculty. No significant
differences in responses are found between STEM and Non-STEM faculty for women climate, women
leadership, health scores, and work environment scores. Significant differences are found only in ade-
quate gender ratio.
Keywords: Higher Education; Gender Differences; STEM Fields; Job Climate
Purpose
The purpose of this research is to investigate any relationship
of health with work climate and other environmental factors for
faculty in higher education. This study is interested in any gen-
der effects and whether or not any relationships among these
factors differ between Science, Technology, Engineering, and
Mathematics (STEM) faculty and Non-STEM faculty.
Previous Studies
Previous Gender Studies in Higher Education
During the past several years, studies have been conducted to
evaluate gender differences. Some of this research has focused
on salary inequities including studies by Thacker (1995); Balzer
and Bourdreau (1996); Bourdreau, Sullivan, Balzer, Ryan, Yonker,
Thorsteinson, and Hutchinson (1997); Bellas (1993); Sosin, Rives,
and West (1998); Burke, Duncan, Krall, and Spencer (2005);
Toumanoff (2005); Porter, Toutkoushian, and Moore (2008);
Barbezat and Hughes (2005); Travis, Gross, and Johnson (2009).
Others have presented methods to help correct for gender dif-
ferences in salary including work by Oaxaca and Ransom (2002),
Weistroffer, Spinelli, Canavos, and Fuhs (2010), and Haney
and Forkenbrock (2006).
Student evaluation of teaching and gender impact has been
studied by Laube, Massoni, Sprague, and Ferber (2007); Brady
and Eisler (1999); Worthington (2002); Burns-Glover and Veith
(1995); Sprinkle (2008). One study found that male teachers
were more often classified by their students as professors while
female teachers were more often classified as instructors (Miller
& Chamberlin, 2000).
The work climate and environment of women faculty mem-
bers has also been studied. Bronstein and Farnsworth (1998)
reported from the results of a campus climate survey that women
were more likely to feel left out, discriminated against by stu-
dents, and treated unfairly in promotions and tenure decisions.
Cress and Hart (2009) reported their findings at two different
universities saying that men and women faculty members within
the same university and department often experience different
environments.
Some studies have focused on women in science and engi-
neering fields (STEM disciplines). In particular, a survey was
done on women faculty in the College of Science at Massachu-
setts Institute of Technology (MIT) in 1999 and followed up in
2003. In 2004, a set of matched men faculty were also inter-
viewed at MIT. The researchers in the MIT study found that
women were more likely to be given larger service loads, more
likely to feel left out of interactions with colleagues, and more
likely to feel stressed from a work/family life balance due to
university policies. Women were also more likely to feel un-
fairly treated in promotional and tenure decisions (Hult, 2005).
A study by Blackwell, Synder, Mavriplis (2009) found that
women in STEM fields reported a more negative environment.
There has been research which relates the work climate and
environmental conditions of women faculty to job and career
satisfaction. August and Waltman (2004) found that overall ca-
reer satisfaction for faculty women was related to their envi-
ronmental conditions using Hagedorn’s (2000) model. August
and Waltman found that having a mentor, and salaries compa-
rable to their male counterparts, resulted in a more positive
work environment for women faculty. They also found that
having collegial peer relations was significant for non-tenured
women and being involved with departmental relations was
significant for tenured women for a more positive environment.

R. C. MAGEL
318
Hult (2005) found that women faculty were less likely to be
satisfied with their job or career because of the more negative
environmental conditions. Settles, Cortina, Malley, and Stewart
(2006, 2007) found that a negative environment led to lower
job satisfaction among women faculty.
Other research examining the relationship between campus
environment and job or career satisfaction have reported similar
findings (Glen, 2007), Greene, Stockard, Lewis, and Richmond
(2010), Blackwell, Synder, Mavriplis (2009), and Cress and
Hart (2009). Glen (2007) reports on a survey of 962 full-time
faculty members at one university that finds women felt they
were more likely to be ignored and they were more likely to be
stressed. Viefers, Christie, and Ferdos (2006) discuss their find-
ings as to why they feel there are very few women on physic
faculties in Sweden.
Xu (2008) found that the faculty turnover rate for women in
higher education institutions in the STEM disciplines was
higher than for men. Xu’s research links the higher turnover
rate with women receiving less support, having fewer opportu-
nities for advancement, and not as much of an opportunity to
have a voice.
Previous Studies Linking Job Climate with Health
Studies have been conducted examining the relationship be-
tween job climate/environment with physical and psychological
health of various types of workers. Some of these studies have
involved gender. Messing, Lippel, Demers, & Mergler (2000)
studied occupational illnesses with regard to gender in blue
collar workers in Canada. Their research found that women
reported more sicknesses and occupational illnesses than men.
Holmgren, Hensing, and Dellve (2010) studied the relationship
between organizational climate and number of days absent
because of sickness in the general population in Sweden. Find-
ings were similar to the studies of Messing et al. (2000). Abram-
son (2007) studied mid-life women (ages 40 - 54) in various
jobs in Canada and found that women working in negative en-
vironmental conditions were more likely to suffer from physical
and/or mental ailments.
Miner-Rubino, Settles, Stewart (2009) considered a sample
of 87 college educated white women and looked at their per-
ceptions of workplace climate, job satisfaction, and general
health. If a woman had a positive perception of her workplace
climate, and there were a larger percentage of women at the
level above, the woman’s general health seemed to be higher
than when compared to the general health of women who had a
smaller percentage of women at the level above and a positive
workplace climate. When the woman responding had a negative
perception of her workplace climate, and there were a larger
percentage of women at the level above, the woman’s general
health was generally worse than when there was a smaller per-
centage of women at the level above. It appears that workplace
climate is an important factor in the general health of women
and the number of women at the level above the subject has an
interaction effect with climate. Miner-Rubino et al. (2009) found
these findings with regard to the general health of a woman
were particularly strong for women sensitive to sexism.
Dollard and Bakker (2010) examined the association between
workplace climate and psychological health of education work-
ers in Australia. Their research suggested an association be-
tween workplace climate and health.
Previous Health/Climate Studies in Universities
There has been some recent research studying the relation-
ship between health and environment in higher education. Tyther-
leigh, Jacobs, Webb, Ricketts, & Cooper (2005, 2007) studied
occupational stress and work environment in English Higher
Education Institutions. They found that women reported a sig-
nificantly higher level of stress at the older universities which
were more male dominated. Jacobs, Tytherleigh, Webb, and
Cooper (2007) found that a poorer work environment for em-
ployees at English Higher Education Institutions was also asso-
ciated with lower levels of job performance and more work
days missed because of the increase in physical and mental
health problems.
Catano, Francis, Haines, Kirpalani, Shannon, Stringer, &
Lozanzki (2010) studied occupational stress and work envi-
ronment in Canadian universities. Their study found that women
reported significantly higher stress levels in the following areas:
work-life conflict; unfairness by the administration; unfairness
in rewards; and work load.
Winefield, Gillespic, Stough, Dua, Hapuarachchi, & Boyd
(2003) studied stress of workers in Australian universities. The
study found that faculty had higher reported stress levels than
non-faculty.
Previous Efforts to Improve Climate
Efforts have been made to improve the campus environment
for women. Henry and Nixon (1994) discuss some of these
efforts. Piercy, Giddings, Allen, Meszaros, and Joest (2005)
introduced pilot programs to help improve the environment of
all faculty members, particularly those of color. In 2005, the
President of Harvard announced that 50 million dollars would
be spent over the next 10 years in an effort to improve campus
climate for everyone (Fields, 2005). The University of Wiscon-
sin-Madison has been holding departmental workshops on im-
proving climate and has made documents available online to
help improve the department climate including “Recommended
Actions for Enhancing Department Climate” (2011) and “En-
hancing Department Climate: A Guide for Department Chairs”
(2011). Abadie, Christy, Jones, Wang, and Lima (2009) con-
ducted a longitudinal survey of women faculty in biological and
agricultural engineering in the hopes of finding ways to help
improve the climate of women in these areas. Unfortunately,
Valian (2004) writes that progress is slow in climate change for
women faculty.
Summary of Previous Studies
Summarizing the aforementioned studies, women faculty in
higher education often face a more negative climate/environ-
ment than men faculty, particularly in the STEM disciplines.
This more negative climate has led to a lower percentage of
women faculty in higher education satisfied with their jobs
and/or careers. Studies in the general population have found
that a more negative climate/environment for women more often
results in physical and mental health symptoms (Miner-Rubino
et al., 2009; Abramson, 2007; Messing et al., 2000). Some
studies at higher education institutions have suggested this
may also be true for women in higher education particularly
at male dominated universities (Tytherleigh et al., 2007;
Catano et al., 2009). There also have been studies that have
suggested that there is more stress in academic jobs than

R. C. MAGEL
other jobs (Tylerleigh, Webb, Cooper, & Rickets, 2005). Women
in jobs that reported more stress and a poorer environment have
more sickness. If academic jobs cause even more stress than the
norm and female faculty have higher levels of stress than male
faculty, female faculty could have more physical ailments. This
could be further magnified for mid-life female faculty if the
findings for the general population hold true for female faculty
in higher education (Abramson, 2007).
Purpose of Re se a rc h
The main questions that arose after examining the past lit-
erature are the following: “Is there a relationship between a
faculty member’s general health and the work climate or other
environmental factors after controlling for gender?” and “Is
there a difference in the work climate and other environmental
factors between STEM and Non-STEM faculty? If there is a
difference, does this difference affect the overall health of a
faculty member?”
Description of Variables
Research conducted at a Research 1 university in the Mid-
west was designed to help answer the previous questions and to
study the relationship of self-reported general health of both
male and female faculty members along with various factors
within the university. A work life survey was composed con-
sisting mainly of questions taken from the WESLLI survey
with a few questions adapted to fit the university being sur-
veyed (Faculty Work life Survey, 2006). Institutional Review
Board Approval was obtained for the study. The survey was
administered electronically through a faculty listserv. The sur-
vey went out to all tenured or tenure-track faculty members in
mid-December 2008. Faculty were given through early Febru-
ary 2009 to respond. There were 224 faculty members who
responded to at least some of the questions on the survey out of
a total of 488 faculty members. This was a 45.9% response rate.
Responses were anonymous and collected by a third party not
involved with this research. Data is given on the North Dakota
State University—Forward webpage (NDSU 2010).
Several questions on the survey were combined to form three
scores for all responding faculty members. These three scores
were the following: work environment score; composite health
score; and women faculty score. The work environment score
for a faculty member was a combined score based of the faculty
member’s responses, each on a four point scale, to statements
on the following 19 items: respected by colleagues; respected
by students; respected by staff; respected by chair; excluded
form informal network; encounter unwritten rules; colleagues
solicit my opinion; research is mainstream; colleagues value my
research; a lot of work not formally recognized; “fit in”; feel
isolated in department; feel isolated at the university; full and
equal participant; voice in resource allocation; meetings allow
shared views; committee assignments are fair; chair involves
me in decision-making; and overall satisfaction with job at the
university. The response that a faculty member gave to his/her
overall job satisfaction counted double in their work environ-
mental score. Responses were recoded for each of the 19 items
so that a higher response indicated the faculty member was
more positive on that item. A faculty member could receive a
work environment score between 20 and 80. A score of 50 in-
dicated a “neutral” work environment. A score below 50 would
indicate a “negative” work environment. A score above 50
would indicate a “positive” work environment.
The composite health score for a faculty member was based
on the faculty member’s responses to their overall health (this
counted double); and whether or not they were happy, fatigued,
stressed, nervous, depressed, short-tempered, well-rested, or
physically fit. All responses to individual components were
based on a four point scale. The points were assigned to the
individual items so that a higher score was better. The mini-
mum health score that a faculty member could receive was 10
and the maximum score was 40. A score of 30 indicated “good”
health while a score of 20 indicated “fair” health, with the mid-
dle score being 25.
A women faculty score was also calculated for each faculty
member responding to the survey. This score consisted of add-
ing the faculty member’s responses to three components of the
work life survey: adequate gender ratio score; women climate
score; and women leadership score. The adequate gender ratio
score was a composite of the weighted responses from whether
there were too few women in the department, whether or not
the department had identified ways to recruit women faculty,
and whether or not the department has actively recruited women
faculty. The active recruitment response was multiplied by
three and the identifying response was multiplied by two. The
adequate gender ratio score could range between 6 and 24 for a
responding faculty member. A higher gender ratio score indi-
cated more women faculty and/or efforts being made to recruit
more women faculty. The women climate score was a compos-
ite of responses to whether or not the climate for women in the
department is good (this was multiplied by three); whether or
not the department has taken steps to enhance the climate for
women (this was multiplied by two); and whether or not the
department has identified ways to enhance the climate. A fac-
ulty member’s response to the women climate score could
range between 6 and 24 with a higher score indicating a better
climate. The women leadership score was a composite of re-
sponses to the following: department has made an effort to
promote women (this was multiplied by three); department has
identified ways to move more women into leadership positions
(this was multiplied by two); and the department has too few
women in leadership positions. A faculty member’s response to
the women leadership score could also range between 6 and 24.
It is noted that responses to statements such as “ the department
has too few women in leadership positions” were recoded so
that a higher number response indicates that the faculty member
felt there were several women in leadership positions and/or a
lot of effort was being made to get women into leadership posi-
tions. Since the women’s faculty score is the sum of the re-
sponses from the adequate gender ratio score, the women cli-
mate score and the women leadership score, the women’s fac-
ulty score ranges between 18 and 72. A score of 45 would in-
dicate a neutral woman’s faculty score so that overall, the situa-
tion for women as that person perceives it would be neither
positive nor negative.
Preliminary Research Analysis
Some preliminary analysis was done to help determine where
gender differences existed before the main purpose of the re-
search was considered. The preliminary analysis also explored
whether any differences existed among the factors being con-
sidered between STEM and Non-STEM faculty.

R. C. MAGEL
320
A two-sample t-test was conducted to test for gender differ-
ences in the composite work environment score (WE). Men and
women faculty were found to have significantly different work
environment scores (p-value = .000). The sample mean work
environment score for men was found to be 62.9 while for
women it was 56.2. Recall that a score of 50 indicated a neutral
work environment, so on average both men and women faculty
reported positive work environments with men reporting on
average a more positive work environment than women. A
regression analysis was conducted to determine whether the
work environment scores differed between STEM and Non-
STEM faculty while controlling for gender. The gender indica-
tor variable was set equal to 1 if the faculty member was a man
and 2 if the faculty member was a woman. The STEM indicator
was equal to 1 if the faculty member was in a STEM discipline
and 0 otherwise. It was found that the STEM indicator variable
was not significant (p-value = .804) with the gender indicator
variable in the model. This study did not find a significant dif-
ference in work environment scores between those faculty in
STEM and Non-STEM disciplines. The average work envi-
ronment scores for women in STEM and Non-STEM based on
the sample were 56.81 and 56.4, respectively. These were based
on sample sizes of 32 and 38, respectively. The average work
environment scores for men in STEM and Non-STEM based on
the sample were 62.46 and 63.79, respectively. These were
based on sample sizes of 46 and 34, respectively.
A two sample t-test was conducted to determine if male and
female faculty members had significantly different self-reported
health scores. The self-reported composite health scores be-
tween men and women were found to be significantly different
(p-value = .000). The average male and female health scores for
the sample were 29.86 and 26.02, respectively. (Recall that a
health score of 30 indicated “good” health, while a health score
of 20 indicated “fair” health.) A regression analysis was con-
ducted to see if STEM and Non-STEM faculty members had
different health scores while controlling for gender. No signifi-
cant difference was found between the self-reported health scores
of STEM and Non-STEM faculty members while controlling
for gender (p-value = .170). The health scores for STEM and
Non-STEM women faculty in the sample were found to be
25.34 and 26.681, respectively, based on sample sizes of 35 and
47. The health scores for STEM and Non-STEM men faculty in
the sample were found to be 29.386 and 30.537, respectively,
based on sample sizes of 57 and 41.
Gender differences were tested for in the various components
of three segments making up the women faculty score. The first
component considered was the adequate gender ratio score
(AG). A regression analysis was conducted with the adequate
gender ratio score as the dependent variable. Gender was sig-
nificant (p-value = .001) with men having significantly higher
scores than women. Not surprisingly, it was found that men and
women do have significantly different views on whether the
present number of women faculty was adequate, on effort being
made to identify ways to recruit women faculty, and on the
effort being made to recruit women faculty. Responses were
considered between faculty in the STEM disciplines and faculty
in the Non-STEM disciplines. A regression analysis was con-
ducted on the adequate gender ratio score to determine whether
or not there was a significant difference between STEM and
Non-STEM faculty responses while controlling for gender. STEM
was significant with gender in the model (p-value = .006) with
faculty in the Non-STEM disciplines having higher adequate
gender ratio scores. The average adequate gender ratio scores
for STEM and Non-STEM women were 14.944 and 16.50, re-
spectively, based on sample sizes of 36 and 49. The average
adequate gender ratio scores for STEM and Non-STEM men
were 16.811, and 19.00, respectively, based on sample sizes of
61 and 43. The adequate gender ratio score could range be-
tween 6 and 24, with the middle value being 15.
The second component considered in the women faculty score
was the women climate score (WC). A two-sample t-test was
conducted between male and female responses to the women
climate score. Gender was found to be significant (p-value
= .004). Men perceive the climate for women to be significantly
better than women perceive the climate for women. A regres-
sion analysis was conducted with women climate score being
the dependent variable testing whether or not there was a sig-
nificant difference in responses between STEM and Non-
STEM faculty while controlling for gender. The indicator vari-
able for STEM was not significant when further added to the
model (p-value = .954) indicating that the climate perceptions
of women in both STEM and Non-STEM, are not significantly
different. The average women climate scores for women in the
sample for STEM and Non-STEM were found to be 18.19, and
17.353, respectively based on sample sizes of 36 and 48. The
average women climate scores for men in the sample for STEM
and Non-STEM were found to be 20.03, and 20.619, respec-
tively based on sample sizes of 60 and 42. The average women
climate score could range from 6 to 24, with 15 being the mid-
dle value.
The third component considered was the women leadership
score (WL). A two-sample t-test was conducted between male
and female faculty women leadership scores. It was found that
men significantly perceive that the number of women in lead-
ership positions is adequate and more effort is being made to
get women in leadership positions than women (p-value = .000).
A regression analysis was conducted with women leadership
scores as the dependent variable testing whether there was a
significant difference between STEM and Non-STEM responses
while controlling for gender. The indicator variable for STEM
was not significant with gender in the model (p-value = .695)
which implies that the responses for women in both the STEM
and Non-STEM areas were not significantly different. The
sample average responses for women in STEM and Non-STEM
were 15.40 and 16.06, respectively, based on sample sizes of 35
and 47. The sample average responses for men in STEM and
Non-STEM were 19.661 and 19.86, respectively, based on
sample sizes of 59 and 43. Women in both the STEM and Non-
STEM disciplines found the adequacy of the number of women
in leadership positions and the opportunity for women in lead-
ership positions to be about the same.
Health Score versus Women Faculty Score
This study investigated the relationship between health score
and the women faculty score. A regression analysis was con-
ducted with health score as the dependent variable and the
women faculty score as the independent variable while control-
ling for gender and whether or not the faculty member was in a
STEM discipline. The STEM indicator variable was not sig-
nificant and was taken out of the model (p-value = .323). The
women faculty score was significant in predicting the health
score with gender differences taken into account (p-value = .026).
The estimated coefficient for this was positive indicating that

R. C. MAGEL
there is a positive correlation between the women faculty score
and the health score controlling for gender. If the women fac-
ulty score increases, the health score tends to increase. It is
noted, however, that the R2 for this model is only .123 indicat-
ing that only 12.3% of the variation in health scores is ex-
plained by gender and the women faculty score. The results for
the regression analysis may be found in Table 1.
Health Score versus Work Environment Score
This study investigated the relationship between health score
and work environment score. A regression analysis was con-
ducted with health score as the dependent variable and work
environment score as the independent variable while control-
ling for gender and whether or not the faculty member was in a
STEM discipline. The STEM indicator variable was not sig-
nificant (p-value = .711) and was taken out of the model. Work
environment was significant in predicting the health scores with
gender differences taken into account (p-value = .000). The esti-
mated coefficient for the work environment variable was posi-
tive indicating that work environment and health scores are
positively correlated taking gender into account. Work environ-
ment scores and gender account for slightly over 30% of the
variation in health scores. Results are given in Table 2. For
every extra increase of one point in the work environment score,
it is estimated that the health score will increase by .252. Work
environment scores still accounted for about 30% of the varia-
tion in health scores even without gender in the model. The
women faculty score was added to the model with gender and
work environment scores in the model. It was found that the
women faculty score was not significant with the work envi-
ronment score and gender in the model (p-value = .284). The
work environment score was significant while controlling for
Table 1.
Regression analysis: Health score versus women faculty score and
gender.
The regression equation is
health score = 29.4 + .065*WF − 3.324*gender
WF = women faculty score
183 cases used, 17 cases contain missing values
Predictor Coef SE Coef T p
Constant 29.422 2.361 12.46 .000
WF .065 .029 2.24 .026
Gender −3.324 .902 −3.68 .000
(1 = M; 2 = F)
S = 5.840 R-Sq = 12.3% R-Sq(adj) = 11.3%
Table 2.
Regression analysis-health score versus work environment and gen-
der.
The regression equation is
health score = 15.7 + .252*WE − 2.179*gender
WE = work environment score
152 cases used, 48 cases contain missing values
Predictor Coef SE Coef T p
Constant 15.694 2.844 5.52 .000
WE .252 .036 6.92 .000
Gender −2.179 .877 −2.48 .014
(1 = M; 2 = F)
S = 5.19 R-Sq = 31.6% R-Sq(adj) = 30.7%
the women faculty score and gender (p-value = .000). The work
environment score is more significant in predicting the health
score than the women faculty score and both are not needed in
the model.
Health Score versus 3 Components of Women Faculty
Score
Because the women faculty score is made up of three com-
ponents, this study wanted to examine the relationship of the
three components of the women faculty score and the health
score. The three components that make up this score include the
adequate gender ratio score (AG), the women climate score
(WC), and the women leadership score (WL). A backwards
stepwise regression analysis at a .10 significance level was con-
ducted with health score as the dependent variable and adequate
gender ratio score, women climate score, and women leadership
scores as the independent variables, while controlling for gen-
der. STEM was placed in the initial model to determine whether
or not STEM made a difference. Since the p-value was for the
STEM indicator variable was .271 and this variable was taken
out of the model. The only variable remaining in the model
besides the gender indicator variable was the women climate
variable. The adequate gender ratio variable or the women lead-
ership variable was not significant in predicting health scores
with the women climate variable in the model.
A regression analysis was conducted with health score as the
dependent variable and women climate score as the independ-
ent variable while controlling for gender. The R2 value for this
model was .1278 indicating that about 12.78% of the variation
in health scores was explained by women climate score and
gender. Interaction between gender and women climate score
was tested for significance and found not to be significant.
There was about the same amount of variation in health scores
explained when the women faculty score (12.3%) was used as
the independent variable instead of the women climate score.
This result suggests that it is the climate that has more of a
relationship with health than either the adequate gender ratio or
the number of women in leadership positions. Results may be
found in Table 3.
Health Score versus Work Environment and 3
Components of Women Faculty Score
Both a stepwise and backwards regression procedure was
performed with health score as the dependent variable with women
climate (WC), women leadership (WL), adequate gender ratio
score (AG), and work environment (WE) as the independent
variables, while controlling for gender. STEM was left out
since it was not significant. Both the stepwise and backwards
regression procedures ended up with the same model and that
model contained only work environment with gender. The re-
sults for the backwards regression procedure may be found in
Table 4. An interaction term between environment and gender
was added to the model, tested for significance, and found not
to be significant (p = .896). The interaction term was taken out
of the model. Recall that in the study by Miner-Rubino et al.
(2009) whether or not a large percentage of women at the level
above was a positive factor in determining the health for women
was dependent upon whether the particular woman under con-
sideration viewed the climate as positive or negative. Climate
was the lead important factor in their study. This current study
is having similar findings with regard to climate. This current

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322
Table 3.
Stepwise regression: Health score versus gender, adequate gender ratio
score, women climate score, women leadership score.
Backward elimination. Alpha-to-Remove: .1
AG = adequate gender ratio score; WC = women climate score;
WL = women leadership score; Gender = 1 if male and 0 if female
Response is health score on 4 predictors, with N = 183
Step 1 2 3
Constant 29.28 29.42 29.81
Gender
Coefficient −3.43 −3.48 −3.470
T-Value −3.80 −3.94 −3.940
p-Value .00 .00 .000
AG
Coefficient .049 .052
T-Value .490 .530
p-Value .628 .594
WC
Coefficient .134 .145 .174
T-Value 1.330 1.620 2.470
p-Value .184 .107 .014
WL
Coefficient .022
T-Value .220
p-Value .823
S 5.85 5.83 5.82
R-Sq 12.94 12.91 12.78
R-Sq(adj) 10.98 11.45 11.81
Table 4.
Stepwise regression: Health score versus women climate, gender, work
environment score, women leadership score, and number of women
score.
Backward elimination. Alpha-to-Remove: .1
AG = adequate gender ratio score; WC = women climate score;
WE = work environment score; WL = women faculty score;
Gender = 1 if male and 0 if female
Response is health score on 5 predictors, with N = 148
Step 1 2 3 4
Constant 15.00 14.70 15.61 15.12
WC
Coefficient −.124 −.159 −.079
T-Value −1.120 −1.60 −.990
P-Value .263 .111 .322
Gender
Coefficient −2.220 −2.100 −2.050 −1.970
T-Value −2.440 −2.350 −2.290 −2.200
P-Value .016 .020 .024 .029
WE
Coefficient .278 .276 .275 .256
T-Value 6.650 6.630 6.580 6.880
P-Value .000 .000 .000 .000
WL
Coefficient −.071
T-Value −.720
P-Value .470
AG
Coefficient .144 .132
T-Value 1.45 1.35
P-Value .149 .180
S 5.17 5.16 5.18 5.18
R-Sq 33.24 32.99 32.14 31.67
R-Sq(adj) 30.89 31.12 30.72 30.73
study did not consider the number of women at the level above,
but examined how the responder felt about the adequacy of the
number of women and/or efforts to increase the number of
women as well the number of women in leadership positions
and the efforts made to increase the number of women in lead-
ership positions. The reason for this is that in several depart-
ments, there were not any women at the level above. The ade-
quate gender ratio score and the women leadership score were
not significant either by just themselves in the model or when
put in the model with women climate while controlling for
gender (p-values = .125 and .077, respectively). In the Miner-
Rubino et al. (2009) study, it was the perceived climate over the
percentage of women at the level above that mattered first when
considering overall health of women. This study is also finding
that climate has the greater impact.
The present study considered both a women’s climate score
and an environmental score. The women’s climate score asked
for responses about the climate for women and possible efforts
being made to improve the climate for women within a depart-
ment. The environmental score asked for responses from the
individual about how they thought the environment was for
them, whether or not they “fit in”, how they were treated by
students and staff, and in general about the overall University
environment, not just the environment for the Department.
Conclusion
This research found a relationship between self-reported health
scores and women’s climate scores while controlling for gender.
A relationship was found between self-reported health scores
and environment scores while controlling for gender. The sec-
ond relationship was the more significant of the two accounting
for over 30% of the variation in health scores. Some observa-
tions were made as a result of this analysis. It appears that
working with individual departments to help improve the cli-
mate for women in their departments is useful to improve
health scores. However, work needs to be done at addressing
the environment for the entire University for everyone if health
scores are to improve. The environment considers how the fac-
ulty member is treated by students and staff and other col-
leagues who may be outside the department. The environment
score also has the individual considering whether or not they
feel isolated in the university, in addition to the department, and
whether their research is valued.
This study did not find a relationship between adequate gen-
der ratio and the health scores. When the adequate gender ratio
was placed in the regression with gender, it was not significant
in predicting health scores (p-value = .125). It was also not
significant when placed in the model with the women’s climate
score of the environmental score. The adequate gender ratio
scores were higher among Non-STEM faculty than STEM fac-
ulty, but self-reported health scores for women in the Non-
STEM disciplines were not significantly different than self-
reported health scores for women in the STEM disciplines.
Work environment scores for faculty in the STEM disciplines
were not significantly different from work environment scores
in the Non-STEM disciplines. There was a difference based on
gender, but women in both STEM and Non-STEM reported
about the same average work environment score.
A relationship was found between self-reported health scores
and environment scores. It is recommended that if universities
want to improve the health of their faculty members, they work

R. C. MAGEL
on improving their overall environment. The adequate gender
ratio score did not make an overall difference in women’s health
scores. Disciplines that reported a higher ratio of women fac-
ulty and greater efforts being made to recruit women faculty,
did not report significantly higher health scores for women.
What did have an effect on health scores was how women thought
they were treated, whether they thought their work was valued,
and whether they thought their opinions were sought and mat-
tered. This also is what had an effect on health scores for men.
Acknowledgements
This work was sponsored by an NSF Advance Grant HRD-
0811239.
REFERENCES
Abadie, A., Christy, A., Jones, J., Wang, J. and Lima, M. (2009). Lon-
gitudinal survey of female faculty in biological and agricultural en-
gineering. Transactions of the ASABE, 52, 1397-1405.
Abramson, Z. (2007). Masked symptoms: Mid-life women, health, and
work. Canadian Journal on Aging, 26, 295-304.
http://dx.doi.org/10.3138/cja.26.4.295
August, L., & Waltman, J. (2004). Culture, climate, and contribution:
Career satisfaction among female faculty. Research in Higher Edu-
cation, 45, 177-192.
http://dx.doi.org/10.1023/B:RIHE.0000015694.14358.ed
Balzer, W., & Bourdreau, N. (1996). Critical modeling principles when
testing for gender equity in faculty salary. Research in Higher Edu-
cation, 37, 633-658. http://dx.doi.org/10.1007/BF01792950
Barbezat, D., & Hughes, J. (2005). Salary structure effects and the
gender pay gap in academia. Research in Higher Education, 46, 621-
640. http://dx.doi.org/10.1007/s11162-004-4137-1
Bellas, M. (1993). Faculty salaries: Still a cost of being female? Social
Science Quarterly (University o f T e xa s Press), 74, 62-75.
Bourdreau, N., Sullivan, J., Balzer, W., Ryan, A. M., Yonker, R., Thor-
steinson, T., & Hutchinson, P. (1997). Should faculty rank be in-
cluded as a predictor variable in studies of gender equity in univer-
sity faculty salaries? Resea r ch in Higher Education, 38, 297-312.
http://dx.doi.org/10.1023/A:1024946022857
Blackwell, L. V., Snyder, L. A., & Mavriplis, C. (2009). Diverse fac-
ulty in STEM fields: Attitudes, performance, and fair treatment. Jour-
nal of Diversity in Higher Education, 2, 195-205.
http://dx.doi.org/10.1037/a0016974
Brady, K. L., & Eisler, R. M. (1999). Sex and gender in the college
classroom: A quantitative analysis of faculty-student interactions.
Journal of Educational Psychology, 91, 127-145.
http://dx.doi.org/10.1037/0022-0663.91.1.127
Bronstein, P., & Farnsworth, L. (1998). Gender differences in faculty
experiences of interpersonal climate and processes for advancement.
Research in Higher Education, 39, 557-585.
http://dx.doi.org/10.1023/A:1018701722855
Burke, K., Duncan, K., Krall, L., & Spencer, D. (2005). Gender differ-
ences in faculty pay and faculty salary compression. Social Science
Journal, 42, 165-181. http://dx.doi.org/10.1016/j.soscij.2005.03.006
Burns-Glover, A., & Veith, D. (1995). Revisiting gender and teaching
evaluations: Sex still makes a difference. Journal of Social Behavior
and Personality, 10, 69-80.
Catano, V., Francis, L., Haines, T., Kirpalani, H., Shannon, H., Stringer,
B., & Lozanzki, L. (2010). Occupation stress in Canadian Universi-
ties: A national survey. International Journal of Stress Management,
17, 232-258. http://dx.doi.org/10.1037/a0018582
Cress, C. M., & Hart, J. (2009). Playing soccer on the foot-ball field:
The persistence of gender inequities for women faculty. Equity &
Excellence in Education, 42, 473-488.
http://dx.doi.org/10.1080/10665680903284523
Dollard, M. F., & Bakker, A. B. (2010). Psychosocial safety climate as
a precursor to conducive work environments, psychological health
problems, and employee engagement. Journal of Occupational &
Organizational Psychology, 83, 579-599.
http://dx.doi.org/10.1348/096317909X470690
Faculty Worklife Survey (2006). Study of faculty worklife at the Uni-
versity of Wisconsin-Madison.
http://wiseli.engr.wisc.edu/research/w2_facultyversion06.pdf
Fields, C. (2005). Summers to improve college climate. Change, 3, 7.
Glen, D. (2007). Alienation harms female professors, study finds. Chro-
nicle of Higher Education, 53.
Greene, J., Stockard, J., Lewis, P., & Richmond, G. (2010). Isthe aca-
demic climate chilly? The views of women academic chemists.
Journal of Chemical Education, 87, 381-385.
http://dx.doi.org/10.1021/ed800042z
Hagedorn, L. S. (2000). Conceptualizing faculty job satisfaction com-
ponents, theories, andoutcomes. New Directions for Institutional Re-
search, 27, 5-20. http://dx.doi.org/10.1002/ir.10501
Haney, P., & Forkenbrock, D. (2006). Making fair and predictable
salary adjustments for faculty of public research universities. Re-
search in Higher Education, 47, 111-127.
http://dx.doi.org/10.1007/s11162-005-8154-5
Henry, W. J., & Nixon, H. L. (1994). Changing a campus climate for
minorities and women. Equity & Diversity in Education, 27, 48-54.
http://dx.doi.org/10.1080/1066568940270308
Holmgren, K., Hensing, G., & Dellve, L. (2010). The association be-
tween poor organizational climate and high work commitments, and
sickness absence in a general population of men and women. Journal
of Occupational & Environmental Medicine, 52, 1179-1185.
http://dx.doi.org/10.1097/JOM.0b013e3181fc5c1a
Hult, C. (2005). How’s the climate on your campus? Academic Leader,
21, 5-6.
Jacobs, P., Tytherleigh, M., Webb, C., & Copper, C. (2007). Predictors
of work performance among higher education employees: An ex-
amination using the ASSET model of stress. International Journal of
Stress Management, 14, 199-210.
http://dx.doi.org/10.1037/1072-5245.14.2.199
Laube, H., Massoni, K., Sprague, J., & Ferber, A. L. (2007). The im-
pact of gender on the evaluation of teaching: What we know and
what we can do. NWSA Journal, 19, 87-104.
Messing, K., Lippel, K., Demers, D. L., & Mergler, D. (2000). Equality
and difference in the workplace: Physical job demands, occupational
illnesses, and sex differences. Feminist Formations, 12, 21-49.
Miller, J., & Chamberlin, M. (2000). Women are teachers, men are
professors: A study of student perceptions. Teaching Sociology, 28,
283-298. http://dx.doi.org/10.2307/1318580
Miner-Rubino, K., Settles, I. H., & Stewart, A. J. (2009). More than
numbers: Individual and contextual factors in how gender diversity
affects women’s well-being. Psychology of Women Quarterly, 33,
463-474. http://dx.doi.org/10.1111/j.1471-6402.2009.01524.x
NDSU Internal Evaluation Work Life Survey (2010).
http://www.ndsu.edu/forward/program_evaluation
Oaxaca, R., & Ransom, M. (2002). Regression methods for correcting
salary inequities between groups of academic employees. New Di-
rections for Institutional Research, 115, 91-103.
http://dx.doi.org/10.1002/ir.55
Piercy, F., Giddings, V., Allen, K., Dixon, B., Meszaros, P., & Joest, K.
(2005). Improving campus climate to support faculty diversity and
retention: A pilot program for new faculty. Innovative Higher Edu-
cation, 30, 53-66. http://dx.doi.org/10.1007/s10755-005-3297-z
Porter, S., Toutkoushian, R., & Moore III, J. (2008). Pay inequities for
recently hired faculty, 1988-2004. The Review of Higher Education,
31, 465-487. http://dx.doi.org/10.1353/rhe.0.0014
Recommended actions for enhancing department climate.
Settles, I. H., Cortina, L. M., Malley, J., & Stewart, A. J. (2006). The
climate for women in academic science: The good, the bad, and the
changeable. Psychology of Women Quarterly, 30, 47-58.
http://dx.doi.org/10.1111/j.1471-6402.2006.00261.x
Settles, I. H., Cortina, L. M., Stewart, A. J., & Malley, J. (2007). Voice
matters: Buffering the impact of a negative climate for women in
science. Psychology of Women Quarterly, 31, 270-281.
http://dx.doi.org/10.1111/j.1471-6402.2007.00370.x

R. C. MAGEL
324
Sprinkle, J. E. (2008). Student perceptions of effectiveness: An exami-
nation of the influence of student biases. College Student Journal, 42,
276-293.
Sosin, K., Rives, J., & West, J. (1998). Unions and gender pay equity in
academe: A study of US institutions, Feminist Economics, 4, 25-45.
http://dx.doi.org/10.1080/135457098338419
Thacker, R. (1995). Gender, influence tactics, and job characteristics
preferences: New insights into salary. Sex Roles, 32 , 617-638.
http://dx.doi.org/10.1007/BF01544215
Toumanoff, P. (2005). The effects of gender on salary-at-hire in the
academic labor market. Economics of Education Review, 24, 179-188.
http://dx.doi.org/10.1016/j.econedurev.2004.03.008
Travis, C. B., Gross, L. J., & Johnson, B. A. (2009). Tracking the gen-
der pay gap a case study. Psychology of Women Quarterly, 33, 410-
418. http://dx.doi.org/10.1111/j.1471-6402.2009.01518.x
Tytherleigh, M. Y., Webb, C., Cooper, C. L., & Ricketts, C. (2005).
Occupational stress in UK higher education institutions: A compara-
tive study of all staff categories. Higher Education Research & De-
velopment, 24, 41-61.
http://dx.doi.org/10.1080/0729436052000318569
Tytherleigh, M. Y., Jacobs, P. A., Webb, C., Ricketts, C., & Cooper, C.
(2007). Gender, health and stress in English university staff-exposure
or vulnerability? Applied Psychology: An International Review, 56,
267-287. http://dx.doi.org/10.1111/j.1464-0597.2006.00254.x
Valian, V. (2004). Beyond gender schemas: Improving the advance-
ment of women in academia. NWSA, 16, 207-220.
http://dx.doi.org/10.2979/NWS.2004.16.1.207
Viefers, S. F., Christie, M. F., & Ferdos, F. (2006). Gender equity in
higher education: Why and how? A case study of gender issues in a
science faculty. European Journal of Engineering Education, 31, 15-
22. http://dx.doi.org/10.1080/03043790500429948
Weistroffer, H. R., Spinelli, M. A., Canavos, G. C., & Fuhs, F. P.
(2010). A merit pay allocation model for college faculty based on
performance quality and quantity. Economics of Education Review,
20, 41-49. http://dx.doi.org/10.1016/S0272-7757(99)00037-0
Winefield, A. H., Gillespic, N., Stough, D., Dua, J., Hapuararchchi, J.,
& Boyd, C. (2003). Occupational stress in Australian university staff:
Results from a national survey. International Journal of Stress Man-
agement, 14, 199-210.
Worthington, A. (2002). The impact of student perceptions and charac-
teristics on teaching evaluations: A case study in finance education.
Assessment & Evaluation in Higher Education, 27, 49-64.
http://dx.doi.org/10.1080/02602930120105054
Xu, Y. J. (2008). Gender disparity in STEM Disciplines: A study of
faculty attrition and turnover intentions. Research in Higher Educa-
tion, 49, 607-624. http://dx.doi.org/10.1007/s11162-008-9097-4
(2011). Enhancing department climate: A guide for department chairs.