Assessing Readiness for Advancing Women Scientists
Using the Transtheoretical Model
Janice M. Prochaska &Leanne M. Mauriello &
Karen J. Sherman &Lisa Harlow &Barbara Silver &
Published online: 2 November 2006
#Springer Science + Business Media, Inc. 2006
Abstract The under-representation of women in science,
technology, engineering, and math disciplines is of wide
interest. In this article we report on the development of new
Transtheoretical Model-based measures to assess readiness
to take action to advance women scientists. Reliable
measures of Stage of Change, Decisional balance, and
Self-efficacy were developed with a sample of science
faculty from a northeastern university. Theoretical relation-
ships among the constructs were validated and offer support
for extending the Transtheoretical Model to this area. These
measures are being used as part of a campus-wide initiative
to examine the advancement of women scientists before
and after a series of interventions.
Keywords Women scientists .Advancement of women .
Transtheoretical model .Science .Technology.
Engineering .Math departments .Organizational change
There is broad national concern about the under-represen-
tation of women in science, technology, engineering, and
math (STEM) academic disciplines. Although nearly one-
half of science undergraduates are women, college educated
women are less than one-half as likely as men to be
employed in science and engineering fields. Further, women
who do work in those fields tend to earn about 20% less than
their male peers (Graham & Smith, 2005). Within academia,
tenure and promotion rates are slower and attrition rates are
higher for women scientists than they are for men. Even
after controlling for time-since-doctorate, men are still more
likely to be tenured (60% of men vs. 35% of women) and to
be full professors (51% of men vs. 24% of women)
(National Science Foundation, 2000). Indeed, fewer than
15% of women scientists have been awarded full profes-
sor positions in the top science and engineering institu-
tions and in some disciplines it has been as low as 3%
(Commission on the Advancement of Women and Minor-
ities in Science, Engineering, and Technology, 2000;
Etzkowitz, Kemelyor, & Ussi, 2000; Massachusetts Insti-
tutes of Technology, 1999; National Science Foundation,
2001). Those trends lead to a significant difference in
median salaries between women and men faculty in many
STEM departments at universities and 4-year colleges
(National Science Foundation, 2001). Workplace inequity
is an obvious concern; however, the under-representation
of women in academic sciences is disquieting for several
Women faculty provide critically needed role models for
women students. In many STEM disciplines, women are
less likely than men to choose a STEM discipline as their
major in college, and women who do are more likely than
men to change their major before graduation (Margolis &
Fisher, 2002; Seymour & Hewitt, 1994). Reports regularly
cite mentoring and advising as crucial factors in the attrition
patterns and completion rates for women in both graduate
and undergraduate programs (Brainard & Carlin, 1988). It
is not the case that women forsake science majors because
of underperformance. In fact, women who leave engineer-
ing to pursue other college majors often have a higher grade
point average than the men who continue their engineer
track. STEM fields lose some of their most able candidates
before the end of college (Nauta, Epperson, & Waggoner,
Sex Roles (2006) 54: 869–880
J. M. Prochaska (*):L. M. Mauriello :K. J. Sherman
Pro-Change Behavior Systems, Inc.,
P.O. Box 755, West Kingston, RI 02892, USA
L. Harlow :B. Silver :J. Trubatch
University of Rhode Island,
Kingston, RI, USA
1999). Women science majors may be dissuaded from
completing the major not only because the majority of their
peers are men, but also because women mentors in their
fields are scarce. More women science faculty could attract
and retain women students in those fields and might
encourage recent women graduates to seek employment in
academia (Tilghman, 2004).
Women’s scientific perspectives, talents, and interests
can offer important advancements that can enlarge and
enrich scientific inquiry and practice. The diversification of
STEM departments would simultaneously expand faculty
areas of expertise and research foci. In this time of global
political tension, the diversification of leadership in the
STEM disciplines would bring different perspectives, skills,
and values to the fore and will more responsibly integrate
scientific practice with societal challenges we face today.
Finally, greater representation of women faculty in
STEM departments could help improve the working
climate for women (Ginorio, 1995). When women consti-
tute a minority in an applicant pool, their gender becomes
salient in evaluations of their capabilities, and unfavorable
evaluations of women are significantly more likely to occur
when they represent 25% or less of overall group
membership (Heilman, 1980). With national averages of
between 8 and 22% for women faculty in many scientific
disciplines, their status as marginalized members of their
department and their likelihood of negative experiences is
increased. And, indeed nationally women in the sciences
report more isolation, fewer interactions with other faculty,
fewer resources, less mentoring, and feelings of being
overburdened (American Association of Colleges and
Universities, 2000; Peterson, 1997). A study that has been
replicated at a number of different institutions has consis-
tently shown that women faculty in the STEM disciplines
are more likely to report feeling marginalized and isolated,
and to have less job satisfaction, unequal lab space, unequal
salary, unequal recognition through awards, unequal access
to resources, and unequal opportunities to take on admin-
istrative responsibilities that concern the future of the
department or the research unit. (Tilghman, 2004). These
factors do not produce working conditions that lend to the
productivity and retention of women faculty, nor to the
recruitment of new women scientists.
The process by which scientists are produced and
supported, particularly in academia, warrants evaluation.
Changes are needed to enable departmental diversity
growth, expand offerings and perspectives, and invoke the
view that STEM is an attractive choice for female students
and prospective faculty. To help in this effort, the National
Science Foundation (NSF) awarded Advance Institutional
Transformation grants to a number of institutions across the
United States. The main goals of the NSF grants are to
interest, retain, and advance women in the scientific and
engineering academic disciplines and to improve the
institutional climate for women.
In this article we present the results of a preliminary
study of measurement development to evaluate the readi-
ness of a northeastern state university to advance women
scientists. This university is taking a multi-level approach
to achieve the NSF goals, including increasing the number
of women faculty in STEM departments, providing existing
women STEM faculty with career development and training
opportunities, and improving social support services for
women faculty, all of which are aimed at changing the
climate of the institution, particularly in STEM depart-
ments. The theoretical underpinning of the organizational
or climate change approach is the Transtheoretical Model of
change (TTM) (Prochaska & DiClemente, 1983). Its
fundamental premise is that organizational and individual
behavior change occurs in stages over time. In this initiative
the TTM is being used to assess readiness of faculty to
adopt four specific behaviors that will help advance women
scientists. These behaviors include: (1) creating opportuni-
ties for collaboration, (2) enhancing competency through
mentoring, (3) providing resources for doing research, and
(4) generating support through community. The TTM can
be applied to organizational change to assess faculty on
their stage of readiness to do these behaviors and to provide
processes or strategies to help them move from one stage to
the next (e.g., Prochaska, 2000).
The Transtheoretical Model of Change
The Transtheoretical Model (also known as the “stage
model”), one of the leading models of behavior change
(Prochaska, DiClemente, & Norcross, 1992; Prochaska,
Norcross, & DiClemente, 1994), offers a systematic and
empirically based approach to conceptualizing and assess-
ing readiness to undertake an activity. The TTM under-
stands change as progress, over time, through a series of
stages: Precontemplation, Contemplation, Preparation, Ac-
tion, and Maintenance. The TTM systematically integrates
four theoretical constructs central to change: (1) Stage of
Change—Intention to take action; (2) Decisional balance—
Pros and Cons associated with a behavior’s consequences;
(3) Self-efficacy—Confidence to make and sustain changes
in difficult situations; and (4) Processes of Change—ten
cognitive, affective, and behavioral activities that facilitate
Stage of change The TTM was chosen for this initiative in
part because it utilizes Stages of Change or readiness as the
central organizing construct. Studies of change have found
that people move through a series of five stages when
modifying behavior on their own or with the help of formal
870 Sex Roles (2006) 54: 869–880
intervention (Prochaska & DiClemente, 1983; Prochaska et
al., 1992; Prochaska, Velicer, Fava, Rossi, & Tsoh, 2001).
In the Precontemplation stage individuals either deny that
they need to do things differently and, thus, are resistant to
making changes, are unaware of the negative consequences
of their behavior, believe the consequences of their
behavior are insignificant, or have given up the thought of
changing because they are demoralized. Individuals in
Precontemplation are often uninformed or underinformed
about the importance of specific actions, such as the
importance of advancing women scientists. They often
become defensive if they feel pressured to take action when
they are not ready. Precontemplators are assessed as not
intending to take action in the next 6 months. Individuals in
the Contemplation stage are more likely to recognize the
benefits of changing. However, Contemplators continue to
overestimate the costs of changing and, therefore, are
ambivalent and not ready to take action. Contemplators
are seriously considering taking action in the next 6
months. Individuals in the Preparation stage have decided
to make a change in the next 30 days and have already
begun to take steps toward that goal. Individuals in the
Action stage are overtly engaged in modifying their
behaviors or acquiring new behaviors. After about 6
months, individuals do not have to work as hard as they
progress into the Maintenance stage and become more
confident that they can continue to do the Action criteria, in
the present case: mentoring, collaborating, sharing resources,
and generating support. For most people, the change process
is not linear. Movement across the stages is fluid, and
individuals can regress to an earlier stage if their ambivalence
increases or their Self-efficacy decreases (Prochaska et al.,
Decisional balance Change requires consideration of the
potential gains (Pros) and losses (Cons) associated with a
behavior’s consequences. The Decisional balance Inventory
(Velicer, DiClemente, Prochaska, & Brandenburg, 1985)
consists of two scales: the Pros of Change and the Cons.
Longitudinal studies have shown these measures to be
among the best available predictors of future change (e.g.,
Velicer et al., 1985). In an integrative report of 12 studies,
Prochaska, J. O. Velicer, et al. (1994) found that the balance
of Pros and Cons was systematically related to Stage of
Change in all 12 behaviors examined (e.g., smoking
cessation, HIV risk reduction, diet, and exercise). The Cons
of changing to the new behavior outweigh the Pros in the
Precontemplation stage, the Pros surpass the Cons in the
middle stages, and the Pros outweigh the Cons in the Action
stage. From those 12 studies, Prochaska (1994) discovered
the degree of change in Pros and Cons needed to progress
across the Stages of Change: progression from Precontem-
plation to Action involved approximately a one standard
deviation increase in the Pros of making the behavior
change, and progression from Contemplation to Action
involved a one-half standard deviation decrease in the
Cons. A meta-analysis across 55 studies that used the TTM
offers impressive replication for Prochaska’s(1994) find-
ings (Hall, 2004), and these findings have relevance for
change in STEM disciplines. Among individuals not ready
to advance women scientists, increasing the salience and
enhancing the decisional weight of the Pros, and decreasing
the Cons, can help increase intentions to take the steps of
mentoring, collaborating, sharing resources, and generating
support. For example, individuals could be asked to list the
current benefits of advancing women scientists and then
could be encouraged to double that list of benefits.
Self-efficacy Self-efficacy, or the degree to which an
individual believes that he or she has the capacity to make
and sustain changes in difficult situations, can influence
motivation and persistence (Bandura, 1977). Self-efficacy
in the TTM has two components that are distinct but
related: confidence to make and sustain changes, and
temptation to relapse to an earlier stage. Like Decisional
balance, levels of Self-efficacy differ systematically across
the Stages of Change, as individuals further along in the
Stages of Change generally experience greater confidence
and less temptation. Hall and Rossi (2004) found that,
across 24 behaviors, Self-efficacy increased about 1.5
standard deviations from Precontemplation to Maintenance.
In the present study, Self-efficacy for advancing women
scientists means having the confidence to take the steps of
mentoring, collaborating, sharing, and supporting in a
variety of difficult situations (e.g., when people don’t think
they have the time or when they receive negative reactions
from their colleagues). To increase Self-efficacy individuals
could be encouraged to set realistic goals of moving one
stage at a time. Small steps to increase confidence are
Processes of change In a comparative analysis of 24 major
systems of psychotherapy, Prochaska (1978) distilled a set
of ten fundamental processes by which people change. The
set was refined following further theoretical analyses
(Prochaska & DiClemente, 1984) and empirical studies
(Prochaska & DiClemente, 1983). These ten processes;
Consciousness Raising, Dramatic Relief, Self Reevaluation,
Environmental Reevaluation, Self Liberation, Helping
Relationships, Reinforcement Management, Stimulus Con-
trol, Counter Conditioning, and Social Liberation, describe
the basic patterns of activity counselors have used to help
others change their behaviors, affects, cognitions, or
interpersonal relationships. The ten processes as applied to
advancing women scientists are defined in Table 1. Data
from previous research on a variety of behaviors, such as
Sex Roles (2006) 54: 869–880 871
smoking (Prochaska, Velicer, DiClemente, & Fava, 1988),
condom use (Prochaska, Redding, Harlow, Rossi, &
Velicer, 1994), and psychological distress (Prochaska &
DiClemente, 1983) show that self-changers in different
stages rely on different Processes of Change. Individuals in
the early stages rely more on using cognitive, affective, and
evaluative Processes of Change; individuals in the later
stages rely more on using social support, commitments, and
behavior management techniques. Table 2summarizes self-
changers’patterns of emphasizing the use of particular
processes as they progress through the stages.
Multiple clinical trials have documented the ability of TTM
interventions to recruit, retain, and effect change in large
populations of individuals for a number of behaviors,
including smoking cessation (Prochaska, DiClemente,
Velicer, & Rossi, 1993; Prochaska et al., 2001; Velicer,
Prochaska, Fava, Laforge, & Rossi, 1999), stress manage-
ment (Evers et al. 2006), exercise adoption (Marcus et al.,
1998), dietary change (Greene et al., 1999), limiting sun
exposure (Weinstock, Rossi, Redding, & Maddock, 2002),
and multiple behaviors (Prochaska et al., 2004; Riebe et al.,
2003; Prochaska et al., 2005). The TTM also has received
empirical support across studies of behavior change in a
range of organizational change areas, including collaborative
service delivery (Levesque, Prochaska, J. M. & Prochaska, J.
O., 1999), time limited therapy (Prochaska, 2000), and
continuous quality improvement (Levesque et al., 2001).
Stage-matched interventions can have a greater impact than
one-size-fits-all programs that are most often action-oriented.
Programs that are suitable for individuals in all Stages of
Change—those ready to change and those not ready—lead
to higher participation rates. Research conducted to compare
stage distributions across behaviors and at-risk populations
shows that the majority of individuals are not prepared to
take action (Laforge, Velicer, Richmond, & Owen, 1999;
Table 1 Ten transtheoretical processes of change applied to advancing women scientists.
Process of change Application to advancing women in science
Consciousness Raising Increasing awareness and information about the importance of taking the steps to advance women scientists
Dramatic relief Experiencing strong positive emotions that go along with advancing women scientists
Realizing the impact that taking the steps to advance women scientists has on other people
Self-reevaluation Emotional and cognitive reappraisal of values and self-image related to advancing women scientists
Self-liberation Making and demonstrating a firm commitment to take the steps to advance women scientists
Increasing intrinsic and extrinsic rewards for taking the steps for mentoring, collaborating, sharing, and supporting
Helping relationships Seeking and using social support to encourage or help with taking the steps
Counter-conditioning Identifying alternatives to support staying on track
Stimulus control Adding cues or reminders to take the steps to advance women scientists
Social liberation Realizing that universities are changing to support taking the steps to advance women scientists
Table 2 Integration of the stages, processes, and principles of change showing the stage(s) at which each process and principle of change is
applied the most.
Precontemplation Contemplation Preparation Action Maintenance
Pros of changing increasing
Cons of changing decreasing
Social Liberation has been found not to have differentiated emphasis across all five stages by TTM researchers.
872 Sex Roles (2006) 54: 869–880
Vel i ce r e t a l . , 1995). If impact equals participation rate
multiplied by behavior change rates, stage-tailored programs
delivered to an entire population can make a sizeable impact
on the targeted behavior or problem such as the advancement
of women scientists. Stage-matched interventions increase
the likelihood that individuals will take action. For example,
stage-matched interventions for smokers more than doubled
the smoking cessation rates of the American Lung Associ-
ation’s self-help manual, one of the best traditional home-
based interventions available (Prochaska et al., 1993).
TTM-based measures can provide sensitive assessments of
readiness to advance women scientists and guide the
development of tailored interventions that can reduce
resistance among senior faculty and increase the likelihood
of successful advancement of women scientists.
Application of the TTM to the advancement of women
scientists Development of measures of the core constructs
is the first step in the application of TTM to a new area.
One of the initial challenges is identifying criteria that
define action for the target behavior. For the advancement
of women scientists, the process of defining criteria
included reviewing literature on the topic, conducting focus
groups with women and men faculty, and individual
interviews with professors who are highly experienced in
advancing women and researchers who are highly experi-
enced in developing TTM measures for new applications.
Information and data collected from this process helped us
to extract the four key behaviors (collaborating, mentoring,
sharing resources, and generating support). This process
was also used to generate items that would best express the
Pros and Cons of changing and Self-efficacy to advance
women scientists. Measures of the Processes of Change
were not included in the present study. We focused on the
development and initial validation of TTM measures to
assess Stage, Pros and Cons, and Self-efficacy for taking
the steps to advance women scientists. Our research
question was whether these TTM variables would be
systematically related for this important area of advancing
Materials and Methods
All faculty members (n=670) from a northeastern univer-
sity campus were invited to complete a campus climate
survey. The overall response rate was 39%. An assessment
on readiness to advance women scientists was included in
the survey for faculty from STEM departments to complete.
Only data from the TTM section, completed by STEM
department faculty, are presented in this article. The
response rate for STEM faculty (53%) was higher than
the overall response rate and the response rate for NON-
STEM faculty (29%). One hundred and thirty-eight STEM
faculty from the following colleges completed the baseline
climate survey, 33.3% College of the Environment and Life
Sciences, 30.4% Arts and Sciences, 18.8% Engineering,
14.5% Graduate School of Oceanography, and 2.9%
Pharmacy. Departments within those colleges were consid-
ered STEM if they are supported by funding from the
National Science Foundation. Most participants were
tenured associate or full professors (53.3%), 15.6% were
tenure track assistant professors, and 23.7% were research
associates without a tenure-track position. Some partic-
ipants noted being in administrative (4.4%) and other
(3.0%) positions. The majority of participants were male
(73.7%, 26.3% female) and White (76.6%, 1.5% African
American, 8% Asian American, 2.9% Latino, 2.2% Native
American/American Indian, 5.1% Multiethnic, 3.6% Oth-
er). The age of participants ranged from 28 to 70 years; the
mean age was 51.3 years.
Descriptions of the measures developed in this study are
provided in this section. The outcomes of measurement
development, including reliability and validity data, are
presented in the “Results”section.
Stage of change algorithm Participants read a four-part
definition of the action criteria that included examples of
what it means to advance women in science. Examples of
each of the four behaviors were: (1) Creating opportunities
for collaboration, e.g., inviting women faculty to collabo-
rate on projects; (2) Enhancing competency through
mentoring, e.g., teaching about funding mechanisms; (3)
Providing resources for doing research, e.g., sharing
equipment facilities; (4) Generating support through com-
munity, e.g., encouraging social activities for the depart-
ment. They then rated how much they had participated in
each of the four behaviors on a 5-point scale that ranged
from “1=not at all”to “5= completely”.
Next, participants were asked to keep the entire
definition of what it means to advance women scientists
in mind and to report on their readiness to take the four
steps to advance women scientists. Participants were
directed to select one of five alternatives that best
represented their intentions to do all four steps: the
Precontemplation stage (PC)—not intending to take the
four steps to advance women scientists in the next 6
months; the Contemplation stage (C)—intending to take the
four steps in the next 6 months; the Preparation stage
(PR)—intending to take the four steps in the next 30 days;
Sex Roles (2006) 54: 869–880 873
the Action stage (A)—have taken the four steps but less
than 6 months ago; the Maintenance stage (M)—have taken
the four steps for more than 6 months.
Decisional balance This measure was designed to assess
the relative importance of eight Pros and eight Cons of
taking the steps to advance women scientists. Participants
reported on a 5-point scale that ranged from “1 = not at all
important”to “5=extremely important,”how important
each item was in their decision about whether or not to
take the four steps. A sample Pro item is “It could help keep
competent women colleagues at URI.”A sample Con item
is “It could take too much effort.”
Self-efficacy This measure was designed to assess an
individual’s degree of confidence to take the four steps to
advance women scientists. Participants reported on a 5-
point scale that ranged from “1=not at all confident”to “5=
extremely confident,”how confident they were in each of
the 14 specific difficult situations that they could carry out
the four steps. A sample situation is “You were feeling
stressed about your workload.”
Faculty members were sent the climate survey and a letter
inviting their participation in campus mail. They were
asked to complete the survey and return it in a postage paid
envelope. Participants were ensured that all information
included in the survey would be strictly confidential. An
incentive was used mainly as a means to gain the support of
college deans and department chairs to encourage faculty to
complete the climate survey. Departments with the highest
response rates received one or more $100 gift certificates to
sponsor a department lunch or other social event. The
public recognition of high participation was hoped to
inspire deans and chairs to encourage participation among
their departments. The university Institutional Review
Board approved all of the study procedures.
Behavior and Stage of Change
The most strongly endorsed behavior (M= 3.51, SD = 1.06)
for advancing women scientists was creating opportunities
for collaboration. On average participants rated that they
engaged in the other behaviors ‘sometimes,’as the means
all were close to 3.0 on the 5-point scale: enhanced
competency through mentoring (M=3.06, SD = 1.24), pro-
vided resources for doing research (M= 3.22, SD = 1.29),
and generated support through community (M= 3.07, SD =
1.20). Those four behaviors were summed to get a total
score with a range of 4 to 20. The sample mean was 12.85
Based on their response to the Stage of Change question
participants were classified into one of the five Stages of
Change. Due to extremely low numbers in Preparation and
in Action, the stages were collapsed into three categories:
Precontemplation (8.5%), Contemplation/Preparation
(10.8%), and Action/Maintenance (80.8%). Most partici-
pants categorized in the Action/Maintenance stage reported
being in Maintenance; only 3.8% of the sample were
classified as in Action. We recognize that these perceptions
may be optimistic on the part of the faculty. Future analyses
and interventions will help verify their accuracy.
As a validation of the Stage of Change algorithm, the
four behaviors and their sum were investigated by stage
classification. The sum of the behaviors increased across
the stages, F(2, 125)=30.97, p<0.01, η
Tukey tests revealed that individuals in Precontemplation
scored (M=8.0, SD= 2.86) much lower than those in
Action/Maintenance (M=14.05, SD = 3.20). Those in Con-
templation/Preparation scored closer to those in Precontem-
plation (M=9, SD=2.86), but there were no significant
differences with those in Action/Maintenance. The individ-
ual behaviors were examined by Stage with a multivariate
analysis of variance (MANOVA), Wilks’Lambda=0.64,
approximate, F(8, 244)=7.70, p<0.001, η
up ANOVA’s for each of the four behaviors were
significant. Results can be found in Table 3.
Overview of Measurement Development: Decisional
Balance and Self-efficacy
The sample size would not allow a split-half cross-validation
procedure. Exploratory analyses were conducted using
principal components analyses (PCA) for both Decisional
balance and Self-efficacy. After initial examination of the
inter-item correlations, item means, item standard devia-
tions, and component interpretability, a PCA was conducted
for the Decisional balance and Self-efficacy measure. This
analysis was conducted on the matrix of inter-item correla-
Table 3 Means and standard deviations of key behaviors by stage of
PC C/PR A/M
Collaboration* 2.36 (0.809) 2.64 (1.01) 3.80 (0.881)
Mentoring* 1.91 (0.944) 2.07 (1.14) 3.09 (1.23)
Resources* 2.09 (1.22) 1.86 (0.864) 3.25 (1.28)
Support* 1.64 (0.924) 2.43 (0.852) 3.10 (1.19)
874 Sex Roles (2006) 54: 869–880
tions with orthogonal (VARIMAX) rotation. Decisions
regarding how many factors to retain were based on the
scree plot (Cattell, 1966), the minimum average partial
(MAP) procedure (Velicer, 1976; Zwick & Velicer, 1982),
parallel analysis (PA) (Horn, 1965), factor loadings, and the
theoretical interpretability of the factors. Elimination of
items was based on factor loadings, inter-item correlations,
item means, item standard deviations, complexity of items,
Cronbach’s coefficient alpha with and without individual
items, and component interpretability.
Decisional balance PCA reduced the number of Decisional
balance items from 16 to 10; five represented the Pros of
advancing women scientists, and five represented the Cons
of advancing women scientists. After one poorly loading
item was deleted, there was agreement from MAP and PA
on a two-factor solution. The final factor loadings ranged
from 0.67 to 0.89, and both the Pros and Cons had good
coefficient alphas, 0.84 and 0.80, respectively. The final
two-component ten-item solution accounted for 60.3% of
the total variance. Scale scores were derived from the sum
of the item scores for each construct.
Self-efficacy The 14 Self-efficacy items were reduced to a
single eight-item factor that represented confidence to
engage in the four key behaviors to advance women
scientists. Factor loadings ranged from 0.64 to 0.89, and
the coefficient alpha was high (alpha=0.90). The one-factor
solution accounted for 60% of the total variance. A scale
score was derived from the sum of the item scores.
External Validity for Decisional Balance and Self-Efficacy
Once the final measures and subscales were obtained (see
Appendix), the relationships among the constructs of the
TTM were examined to provide an index of external
validity. Specifically, the relationship of Stage to the other
constructs (i.e., Decisional balance and Self-efficacy) was
examined. Several cross-sectional analyses of the data (i.e.
MANOVA, follow-up ANOVA, and post-hoc tests) were
conducted to determine if the patterns predicted by the
TTM emerged in this sample. To aid with ease of
comparison of the constructs across the stages, scores for
each scale were converted to T-scores (M=50, SD=10) for
Decisional balance An overall MANOVA on Decisional
balance by stage revealed significant differences, Wilks’
Lambda=0.83, approximate F(4, 240) = 5.85, p< 0.001, η
0.09. As expected, a follow-up ANVOA on the Pros was
significant, F(2, 121)=8.73, p<0.01, η
=0.13. Those in
Precontemplation reported significantly lower Pros of
advancing women scientists than did those in Contempla-
tion/Preparation and those in Action/Maintenance. The
follow-up ANVOA for the Cons did not show significant
differences. However, the Cons of advancing women
scientists were lower in Action/Maintenance than in either
of the two earlier Stages of Change. Overall, the pattern of
the Pros and Cons across the stages is consistent with past
research based on the TTM. Figure 1indicates that the
Cons of changing are greater than the Pros in Precontem-
plation, whereas the opposite is the case in Action/
Maintenance. Figure 1also indicates that the Pros of
PC (n=11) C/PR (n=14) A/M (n=99)
Stage of Change
Fig. 1 Decisional balance by
stage of change.
Sex Roles (2006) 54: 869–880 875
changing increased about 1.5 standard deviations from
Precontemplation to Action/Maintenance, whereas the Cons
decreased about 0.5 standard deviations from Contempla-
tion/Preparation to Action/Maintenance.
Self-efficacy An overall ANVOA on Self-efficacy by Stage
revealed significant differences, F(2, 117)=8.26, p<0.01,
=0.12. Individuals in Precontemplation reported signifi-
cantly less confidence about advancing women scientists
than did those in Contemplation/Preparation and those in
Action/Maintenance. As expected, confidence increased
more than 1.5 standard deviations across the Stages of
Change (see Fig. 2).
Differences were examined between men’s and women’s
responses on the measure. A Chi-Square analysis revealed
no gender differences across the stages; similar percentages
of men and women participants were classified as being in
each of the three stages. Means for the continuous variables
by gender are presented in Table 4. Although there were no
gender differences by the sum of the four key behaviors, an
examination of the four behaviors individually revealed
significant differences between men and women for
generating support through community, F(1, 130)= 6.97,
=0.05. Women reported more such behavior
than men did. There were no gender differences in the Pros
of advancing women scientists or in confidence to advance
women scientists. However, women rated the Cons of ad-
vancing women scientists higher than men did, F(1, 128)=
6.07, p<0.05, η
The results of this study offer preliminary support for the
application of the TTM to the advancement of women
scientists. One of the first challenges of applying the TTM
to a new area is to develop criteria for what it means to take
effective action. Through formative research, four behav-
ioral markers were used to define action for advancing
women scientists: (1) collaborating; (2) mentoring; (3)
sharing resources; and (4) generating support. Based on
those behaviors as a framework, reliable and valid measures
for assessing Stage of Change, Decisional balance, and
Self-efficacy were developed. Increased practice in the four
key behaviors by individuals in later Stages of Change
(Action/Maintenance) offers validation for the Stage of
Change assessment. The factor structure of the Decisional
balance and Self-efficacy measures are consistent with
measures developed across several other behaviors (Hall,
2004). In addition, external validation was also provided by
the predictable patterns of relationships that were found
between the Stages of Change and Decisional balance and
PC (n=11) C/PR (n=13) A/M (n=96)
Stage of Change
Fig. 2 Confidence by stage of
Table 4 Means and standard deviations of continuous variables by
Sum 13.38 (4.47) 12.64 (3.72)
Collaboration 3.61 (1.13) 3.46 (1.04)
Mentoring 3.20 (1.39) 2.99 (1.17)
Resources 2.94 (1.41) 3.30 (1.24)
Support** 3.50 (1.23) 2.94 (1.14)
Pros 19.69 (4.78) 19.19 (4.19)
Cons* 12.17 (4.27) 10.15 (3.97)
Confidence 25.63 (5.60) 25.83 (7.13)
876 Sex Roles (2006) 54: 869–880
Self-efficacy. These assessments can be used to understand
faculty members and academic departments practice to-
wards the advancement of women scientists. These mea-
surement tools also can aid in developing and structuring
interventions aimed at advancing women scientists.
For those who do not use the TTM perspective this study
provides measures that can be an important part of research
in advancing women in the sciences. First it identifies
behavioral criteria that can be used to assess faculty activity
designed to advance their female colleagues. Second, it
validates key constructs, like Decisional balance and Self-
efficacy, which are related to participation in such activities.
These behavior change constructs are used in a fairly broad
range of theories, such as social cognitive theory (Bandura,
1991) and the theory of reasoned action (Fishbein, 1979).
Some results of the present study were unexpected. It is
surprising that almost 81% of participants were classified in
the Action or Maintenance stages and that there were no
differences in Stage classification between men and women
faculty. Further, men did not rate the Pros or confidence to
advance women scientists lower than women did, nor did
they rate the Cons of advancing women scientists higher than
women did. The university at which this study was
conducted has experienced unfavorable conditions for
women faulty in certain science departments. The NSF grant
was sought to assist with changing the climate of those
departments, and the university as a whole, in order to
promote the advancement of women scientists. Qualitative
data from formative focus groups conducted prior to the
study exemplify the continued unpleasant and unfavorable
climate for many women faculty in STEM departments
(Bowleg, Harlow, Silver, & Webster, 2005). Yet, when
reporting their readiness to do the four key behaviors, the
great majority of the science faculty who participated in this
research reported actively working toward the advancement
of women colleagues. The response rate for STEM faculty
was approximately 54%. Faculty who are not committed to
or actively engaged in advancing women scientists were
probably less likely to complete the survey. People who are
in Precontemplation and Contemplation are often the most
difficult to reach and, at the same time, the most in need of
assessment and intervention efforts (Prochaska et al., 1993).
The relatively small percentages of participants in Precon-
templation and Contemplation in this sample likely under-
estimates the actual percentage of faculty who currently are
not ready to advance women scientists. The faculty who
declined to participate may represent a large portion of
faculty who have yet to commit to advancing women
scientists. Further research may need to use techniques like
individual incentives to get a higher percentage of faculty to
Despite the high percentages of participants in Action/
Maintenance, there is much room for improvement in the
frequency with which they reported practicing the key
behaviors and in their levels of Pros, Cons, and Self-
efficacy. On average, participants reported that they
“sometimes”engage in the four key behaviors. Intervention
efforts should focus on increasing the level of engagement
in the behaviors and faculty members’commitment always
to practice the behaviors necessary to help promote the
advancement of women scientists. The results indicated that
creating opportunities to collaborate was the most frequent-
ly practiced behavior and that men are less likely to
generate support through community than are women.
Researchers providing interventions should emphasize the
importance of all four of these behaviors while being aware
of the current practices and shortcomings of faculty and
administration in regard to the key behaviors. Further, on
average, participants rated moderate levels of Pros, Cons,
and confidence about advancing women scientists. A TTM-
based intervention could help faculty members recognize
more benefits and place less importance on the Cons of
advancing women. Interventions could be designed to provide
Consciousness Raising to continue to raise the Pros of
advancing women scientists and also increase attention to
reducing barriers. In addition, Self-efficacy could be increased
by offering strategies to increase confidence in difficult
situations. In this sample, with such a high percentage in
Action or Maintenance, there is little room to monitor
progress across the Stages of Change. However, there is
considerable room to assess improvement with the key
behaviors and other TTM constructs at follow-up time points.
There are limitations to the present study that must be
acknowledged. The sample size limited our study in two
important ways. Due to the sample size, measurement
development analyses were limited to exploratory data
analysis. Future research will need to confirm the factor
structure, reliability, and validity of the newly developed
measures. In addition, a larger sample would likely have
enabled a full stage distribution. In two cases adjacent
stages (Contemplation/Preparation and Action/Mainte-
nance) were collapsed because of limited sample sizes in
the groups. Therefore, analyses were limited to the
investigation of differences and patterns across three
groupings of Stages of Change. Stages have been collapsed
in other research, particularly with exploratory or pilot
studies (Mauriello, 2003; Hall, 2004). Given the similarity
of the results of the current study with previous TTM-based
research, collapsed stages do not appear to have compro-
mised the data analysis or the assessment of the application
of the TTM to this new area. Future work with a larger and
more representative sample will allow for further validation
of TTM-based theoretical relationships and will clarify
distributions and patterns across all five Stages of Change.
The length of the campus climate survey, in which these
TTM assessments were included, hindered the addition of a
Sex Roles (2006) 54: 869–880 877
measure of the Processes of Change. The development of
Processes of Change measures and an examination of the
pattern of the processes across the stages of advancing
women scientists should be conducted to further the
application of the TTM to this area. An understanding of
the Processes of Change for this application of the TTM
also will help to inform intervention efforts and materials.
Knowledge of the most important processes for each stage
transition and the norms associated with each process
subscale offers valuable information for tailoring appropri-
ate TTM-based interventions. In addition, longitudinal data
would help elucidate the effectiveness of TTM-based
interventions for the advancement of women scientists.
This new application of the TTM offers insights into
how the model can be used to help with the advancement of
women scientists. The TTM interventions that have
produced the greatest impact have been tailored communi-
cations that customize feedback to the needs of each
individual. The measures developed in the present study
can be valuable assets to aid in the development of
empirically based TTM interventions for departments and
universities across the country. With the current measures,
communications could be tailored to each individual’s
Stage of Change, Pros and Cons of changing, and Self-
efficacy. In the current ADVANCE initiative, workshops
with STEM departments are being conducted to help
faculty members understand the processes that hinder
versus promote the advancement of women colleagues. In
addition, department chairs and administrators will receive
TTM-based strategies to help facilitate faculty progress
toward promoting in the advancement of women scientists.
Follow-up assessments in the fifth year of the study will
evaluate the effectiveness of using TTM-based interven-
tions to prepare faculty to participate more actively and
fully in the advancement of women scientists.
Acknowledgement Partial support was received from a National
Science Foundation Grant (no. 0245039) on Advancing Women in the
Sciences (PI: Janet Trubatch/Lynn Pasquerella).
Stage of Change
Keeping the entire definition in mind, (collaborating,
mentoring, providing resources, and supporting), are you
taking these four steps to advance women scientists at URI?
NO, and I do not intend to in the next 6 months
NO, but I intend to in the next 6 months
NO, but I intend to in the next 30 days
YES, I have been, but for less than 6 months
YES, I have been for more than 6 months
It would help recruit competitive women faculty and
It could help keep competent women colleagues at
I would be helping to develop scientists.
It could increase morale in my department.
I would set a good example for others.
It might slow my career and advancement.
It could reduce my funding opportunities.
It could lead to conflicts over who receives primary
credit for the work done in collaboration.
It could strain my relationship with colleagues.
It could take too much effort.
You might end up competing for the same resources.
You are having trouble getting funding.
It takes a lot of time.
There could be conflict over authorship.
You were feeling stressed about your workload.
Other faculty members are not supportive of advancing
You prefer to work independently.
You had doubts about your own expertise.
You heard that a potential collaborator could be
difficult to work with.
You have concerns that a potential mentee may not be
strong enough for tenure.
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