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Harmful Workplace Experiences and
Women’s Occupational Well-being:
A Meta-Analysis
Victor E. Sojo
1
, Robert E. Wood
2
, and Anna E. Genat
2
Abstract
We report a meta-analytic review of studies examining the relations among harmful workplace experiences and women’s
occupational well-being. Based on previous research, a classification of harmful workplace experiences affecting women is
proposed and then used in the analysis of 88 studies with 93 independent samples, containing 73,877 working women. We
compare the associations of different harmful workplace experiences and job stressors with women’s work attitudes and
health. Random-effects meta-analysis and path analysis showed that more intense yet less frequent harmful experiences (e.g.,
sexual coercion and unwanted sexual attention) and less intense but more frequent harmful experiences (e.g., sexist orga-
nizational climate and gender harassment) had similar negative effects on women’s well-being. Harmful workplace experiences
were independent from and as negative as job stressors in their impact on women’s occupational well-being. The power
imbalance between the target and the perpetrator appeared as a potential factor to explain the type and impact of harmful
workplace experiences affecting women’s occupational well-being. In the discussion, we identify several gaps in the literature,
suggest directions for future research, and suggest organizational policy changes and interventions that could be effective at
reducing the incidence of harmful workplace experiences. Additional online materials for this article are available to PWQ
subscribers on PWQ’s website at http://pwq.sagepub.com/supplemental.
Keywords
workplace violence, sexual harassment, discrimination, sexism, meta-analysis, path analysis
Of the many occupational factors that can have a negative
impact on women’s well-being, being the target of harmful
actions by colleagues is among the most pernicious. The evi-
dence indicates that women are much more likely than men
to become targets of workplace harassment (Cortina, Magley,
Williams, & Langhout, 2001), sexual harassment (Berdahl,
2007a; Rospenda, Richman, & Shannon, 2009), gender-
based discrimination (Schmitt, Branscombe, Kobrynowica,
& Owen, 2002), negative attitudes towards their gender (Eagly
& Karau, 2002), and sexual assault (Elliot, Mok, & Briere,
2004). Very few studies have reported finding no gender dif-
ferences in harmful experiences at work (e.g., Leymann,
1996). Harmful experiences represent obstacles for women’s
career satisfaction and progression as well as their organiza-
tional and individual well-being (Eagly&Karau, 2002;Willness,
Steel, & Lee, 2007). Previous meta-analyses have examined
the associations of general harassment and sexual harassment
with personal and occupational well-being (Chan, Lam, Chow,
& Cheung, 2008; Hershcovis & Barling, 2010; Willness et al.,
2007) but have not considered the full range of harmful work-
place experiences that women may be exposed to.
In the present study, we build on previous meta-analyses
to organize and integrate the empirical research considering
the effect of different harmful workplace experiences on the
most commonly studied, and arguably the most relevant, indi-
cators of women’s occupational well-being. We first develop a
classification of harmful workplace experiences. We then pres-
ent a model of the impact of harmful workplace experiences, as
stressful events, on proximal work attitudes and distal health
outcomes. Finally, we use meta-analytic techniques and path
analysis to test the hypothesized relations in the model.
The present study makes several contributions to our
understanding of the effect of harmful workplace experiences
on women’s well-being. Specifically, this study will test and
clarify: (a) the magnitude and direction of the association of
sexist discrimination and a sexist organizational climate with
1
Melbourne Business School and Melbourne School of Psychological
Sciences, University of Melbourne, Carlton, Victoria, Australia
2
Melbourne Business School, University of Melbourne, Carlton, Victoria,
Australia
Corresponding Author:
Victor E. Sojo, Melbourne Business School, University of Melbourne, 200
Leicester Street, Carlton, Victoria 3053, Australia.
Email: vesojo@unimelb.edu.au
Psychology of Women Quarterly
1-31
ª The Author(s) 2015
Reprints and permission:
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DOI: 10.1177/0361684315599346
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women’s occupational well-being; these relations have not
previously been meta-analyzed; (b) whether or not the dis-
tinction between seemingly more severe forms of harmful
experiences (e.g., sexual coercion, unwanted sexual atten-
tion) and less severe forms of harmful experiences (e.g., gen-
der harassment, sexist discrimination) is reflected in the
impacts of each on women’s well-being at work; (c) whether
or not the harmful workplace experiences are as detrimental
to women’s occupational well-being as other job stressors;
(d) how the relative representation of women in the work-
place could moderate the association of harmful workplace
experiences with women’s occupational well-being; (e)
whether or not harmful workplace experiences have an asso-
ciation with women’s occupational well-being independent
from job stressors; and (f) how work attitudes (i.e., proximal
well-being indicators) could operate as mediators in the rela-
tion of harmful workplace experiences and job stressors with
women’s health (i.e., distal indicators).
Classification of Harmful Workplace
Experiences
Harmful workplace experiences are broadly defined as inter-
personal abuse against employees in the workplace that might
harm or injure them and contribute to a hostile work context
(Bowling & Beehr, 2006; Rospenda et al., 2009). Our review
of the literature reveals a variety of interpersonal actions that
can be considered harmful workplace experiences; it also
shows an overlap in the definitions and measures of some
of the most widely studied constructs in this area (e.g., gender
harassment and sexist organizational climate). Hence, we
thought it was necessary to present and discuss a categoriza-
tion framework for these experiences that we then will use to
organize the literature and frame the present meta-analysis.
Our categorizations of harmful workplace experiences are
based on three nested distinctions. We first distinguish
between non-gender-based and gender-based harmful work-
place experiences. Second, within harmful gender-based
workplace experiences, we differentiate between non-sexual
and sexual experiences (American Psychological Associa-
tion, Task Force on the Sexualization of Girls, 2010; Fitzger-
ald, Gelfand, & Drasgow, 1995). Finally, for both sexual and
non-sexual experiences, we separate individual experiences
from hostile organizational climates. Figure 1 illustrates this
categorization framework. These experiences are discussed
in more detail below.
Non-Gender-Based Versus Gender-Based Harmful
Workplace Experiences
Non-gender-based harmful workplace experiences. This cate-
gory encompasses interpersonal workplace experiences that
are unwanted and harmful, which are not necessarily based
on any specific demographic attribute. Workplace harass-
ment, incivility, victimization, and bullying are some of the
labels used to describe the variety of interactions studied
under the umbrella of non-gender-based harmful workplace
experiences. These actions may be intentional (Bowling &
Beehr, 2006) or may have ambiguous intent (Andersson &
Pearson, 1999) and do not include behaviors intended to
cause harm to the organization. Some studies have differen-
tiated between physical and psychological harassment (e.g.,
Barling, Rogers, & Kelloway, 2001; Dionisi, Barling, &
Dupre, 2012), and psychological harassment has been
described as a product of covert or overt actions (e.g., Kau-
kiainen et al., 2001). Covert actions include condescending
remarks, ignoring people, insinuating negative gestures, or
talking behind somebody’s back (Kaukiainen et al., 2001).
Overt actions include verbal behavior, such as addressing
someone using inappropriate language or yelling, and physi-
cal behaviors, such as pushing or grabbing (Barling et al.,
2001).
Non-gendered harmful workplace experiences are typi-
cally measured as the frequency with which the target has
been exposed to covert and overt actions (e.g., Cortina
et al., 2001). Few studies include different indices for physi-
cal versus psychological aggression (e.g., Barling et al.,
2001). Most employ a single composite indicator of harmful
workplace experiences (e.g., Rospenda, Richman, & Shan-
non, 2006). The low number of studies reporting the effect
of the different facets or dimensions of non-gendered harmful
workplace experiences (e.g., studies with women in which
the effects of low-frequency/high-intensity events such as
physical aggression are compared with the effects of high-
frequency/low-intensity events such as incivility) drew us
to study non-gendered harmful workplace experiences in
general, and not by facets, in the present meta-analysis.
Following social categorization theory (Turner, Hogg,
Oakes, Reicher, & Wetherell, 1987), it has been argued that
victims of non-gendered harmful workplace experiences are
more likely to blame themselves for such events than victims
of gender-based harmful workplace experiences (Hershcovis
& Barling, 2010). For example, instances of sexualized har-
assment could be attributed to gender, whereas instances of
non-gendered work harassment might trigger labeling of
internal and personal attributions. These expected differences
in attributions might lead to different occupational well-being
outcomes. To explore that possibility, in the present meta-
analysis, we compare non-gender-based work harassment
versus gender-based harmful workplace experiences in their
association with several occupational well-being indicators.
Gender-based harmful workplace experiences. This category
includes interpersonal workplace incidents that are unwanted
and harmful, which are primarily targeted towards women.
These experiences might express hostility, devaluing, objec-
tification, or discrimination towards the targets because of
being women. Similarly, these experiences could be sexua-
lized or non-sexual in their nature and operate in individual
interactions or be characteristic of the organizational climate
2 Psychology of Women Quarterly
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(Bergman, 2003; Gelfand, Fitzgerald, & Drasgow, 1995; Set-
tles, Cortina, Malley, & Stewart, 2006). A detailed descrip-
tion of these experiences follows.
Harmful Gender-Based Workplace Experiences:
Non-Sexual Versus Sexual
Gender-based harmful non-sexual workplace experiences.
These experiences encompass hostility towards or devaluing
of women because of their gender. Harmful gender-based
non-sexual workplace experiences are studied at the level
of personal experiences and at the level of the organizational
climate. Gender-based non-sexual harmful workplace indi-
vidual experiences have been studied in at least two forms:
(a) sexist discrimination comprises gender-based non-sexual
workplace personal experiences of devaluing, bias, or obsta-
cles to success or satisfaction because of gender (Bergman,
2003; Shrier et al., 2007) and (b) gender harassment, which
includes personal experiences of verbal, physical, or sym-
bolic, behaviors that express hostile and offensive attitudes
about members of one gender, typically women (Leskinen
& Cortina, 2014). As illustrated in Figure 1, gender harass-
ment is considered a facet of sexual harassment (Gelfand
et al., 1995) and is discussed later in this article. However,
the experiences studied under the term of gender harassment
are essentially hostile behaviors based on gender and not
necessarily sexualized harassment. Therefore, in the present
meta-analysis, we consider gender harassment a gender-
based non-sexual harmful workplace experience.
At the organizational level, sexist organizational climate
is understood as a gender-based non-sexual harmful work-
place experience embedded in formal and informal organi-
zational policies, practices, and procedures (Reichers &
Schneider, 1990). A sexist climate is characterized by neg-
ative attitudes, and discriminatory actions of colleagues and
the organization towards women (Parker & Griffin, 2002;
Settles et al., 2006).
Several aspects distinguish sexist discrimination from
gender harassment. While hostile expressions are the central
aspect of gender harassment (Leskinen & Cortina, 2014), no
expression of hostility is required for sexist discrimination to
take place (e.g., a manager might overlook a woman for a
promotion in favor of an equally or less qualified male coun-
terpart without the need to experience or express hostility
towards the woman). A woman can only experience bias or
discrimination in the allocation of resources and opportuni-
ties from somebody who has more organizational power than
she does (e.g., supervisors). Conversely, women can be tar-
gets of gender harassment from co-workers or subordinates
who have no control over women’s resources and opportuni-
ties (O’Connell & Korabik, 2000). Sexist discrimination has
also been measured in a way that incorporates instances of
Harmful
workplace
experiences
Non-gender-
based work
harassment
Gender-based
Sexual
Organizaonal
climate
Org. tolerance
for sexual
harassment
Individual
experiences
Sexual coercion
Unwanted
sexual
aenon
Non-Sexual
Individual
experiences
Gender
harassment
Sexist
discriminaon
Organizaonal
climate
Sexist
organizaonal
climate
Sexualharassment
Figure 1. Classification of harmful workplace experiences reported in previous research.
Sojo et al. 3
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devaluing of women (e.g., Bergman, 2003), which can be a
form of gender harassment (Gelfand et al., 1995). Similarly,
gender harassment can be understood as a form of sexist
discrimination, in the sense that it restricts women’s social
participation at work and threatens women’s human rights,
in particular the right to just and favorable conditions at
work (United Nations General Assembly, 1948) and the
right to a life free from violence (United Nations General
Assembly, 1993).
Sexist organizational climate and sexist discrimination
also appear intimately related. These two categories are often
referred to as instances of sexism at work (Reid & Clayton,
1992; Wessel & Ryan, 2012). However, a central difference
between these two forms of sexism is that the former is the
experience of generalized negative attitudes towards women
within the organization (e.g., frequent and unchallenged sexist
jokes, judgments of women as less competent, pressure on
women to change their behavior to match the work context);
the latter is the experience of bias toward a specific individual
because of her gender (e.g., lower pay, being left out of promo-
tions, being ignored in meetings because of being a woman).
There is conceptual and measurement overlap between
sexist organizational climate and gender harassment. They
are distinguished from one another by their target. Sexist
jokes, displays of sexist or suggestive materials, and devalu-
ing of women are treated as instances of sexism in measures
of sexist organizational climate when directed towards
women in general (Parker & Griffin, 2002) and as gender har-
assment when directed toward a specific woman (Gelfand
et al., 1995). In measures of sexist organizational climate,
participants are often asked to report whether sexist events
are characteristic of the work context (Bergman & Hallberg,
2002). In measures of gender harassment, participants are
asked how often they have been exposed to sexist events
(Gelfand et al., 1995). We coded and analyzed the association
of sexist organizational climate, sexist discrimination, and
gender harassment with women’s occupational well-being
in this meta-analysis.
Harmful sexual gender-based workplace experiences. In the
workplace context, an experience is considered sexualized
if it inappropriately imposes sexuality on individuals. For
example, sexualized experiences are actions that draw atten-
tion to aspects of an individual’s sexual life, value individuals
exclusively for their sexual appeal, or, in general, treat
individuals as objects available for sexual use (American
Psychological Association, Task Force on the Sexualization
of Girls, 2010; Fitzgerald et al., 1995; Lim & Cortina,
2005). Harmful sexual gender-based workplace experiences
also are studied at the level of personal/individual events and
at the level of the organizational climate. Sexual harassment
is an individual-level gender-based sexualized harmful work-
place experience. Sexual harassment is defined as unwanted
sex-related workplace behaviors that the targets find offen-
sive, exceeding their resources to cope, and threatening to
their well-being (Fitzgerald, Swan, & Magley, 1997). Fitz-
gerald, Gelfand, and Drasgow (1995) have described three
related facets of sexual harassment: (a) gender harassment,
described above, which is not necessarily sexualized; (b) sex-
ual coercion, in which rewards are made contingent on sexual
cooperation (e.g., implicitly threatening or bribing someone
for sexual favors); and (c) unwanted sexual attention, com-
prising sexual behaviors that are not wanted, welcomed, or
reciprocated by the target (e.g., repeated attempts to get a date
after being rejected, attempted, or actual sexual assault).
The combination of indicators of sexual assault and sexual
harassment (Fitzgerald et al., 1995; Fitzgerald, Magley, Dras-
gow, & Waldo, 1999) has been questioned on several grounds
(Harned, Ormerod, Palmieri, Collinsworth, & Reed, 2002).
First, there is evidence that sexual assault is only weakly
related to unwanted sexual attention (Stockdale & Hope,
1997) and that experiences of sexual assault and bribery are
more distressing than unwanted sexual attention or gender har-
assment (Gruber, Smith, & Kauppinen-Toropainen, 1996).
Second, sexual assault and sexual harassment can have very
different legal statuses. While sexual harassment is usually
addressed as a civil law matter, sexual assault can also be pro-
secuted under criminal law (Harned et al., 2002). Future
research should consider exploring further these differences
in nature and impact.
Different approaches have been used in the measurement
of sexual harassment, which may account for differences
observed in relations between sexual harassment and well-
being. That is, the measurement method might moderate the
relations observed between sexual harassment and women’s
occupational well-being. Sexual harassment has been mea-
sured in terms of how frequently the target experienced the
harassing behaviors; measures use different versions of the
Sexual Experiences Questionnaire (SEQ; Dionisi et al.,
2012; Fitzgerald et al., 1995; Leskinen, Cortina, & Kabat,
2011). Researchers reported results either for the overall
questionnaire (e.g., Cortina, Fitzgerald, & Drasgow, 2002)
or for each of the scales of the questionnaire, namely, gender
harassment, unwanted sexual attention, and sexual coercion
(e.g., Shaffer, Joplin, Bell, Lau, & Oguz, 2000).
In addition to the frequency approach, two other measure-
ment strategies have been used: (a) self-reports of experience
of harassment, in which participants are provided with a
behavioral list, and instead of reporting frequency of occur-
rence they report whether the event took place or not (e.g.,
Settles et al., 2006), or they indicate the frequency of harass-
ment and the researchers later dichotomize their responses
into yes/no categories (e.g., Newell, Rosenfeld, & Culbert-
son, 1995) and (b) a direct question approach or acknowl-
edgement of sexual harassment, in which participants are
asked to indicate whether they have experienced sexual har-
assment or whether sexual harassment has been a problem at
work, relying on the participants’ own understanding and
capacity to label their experience as sexual harassment
(e.g., Murrell, Olson, & Hanson, 1995).
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Reporting whether a harmful event took place or not,
when the situation might have occurred several times, intro-
duces a restriction in the range of responses that might influ-
ence their association with well-being outcomes (Hunter &
Schmidt, 2004). Measures of psychological constructs that
use multiple indicators are expected to more accurately
cover the relevant domain, to be more reliable, and to
explain more variance of specific criteria (Diamantopoulos,
Sarstedt, Fuchs, Wilczynski, & Kaiser, 2012; Haynes,
Richard, & Kubany, 1995). Without the definition of beha-
viors under investigation, participants might underreport or
overreport sexual harassment due to a lack of understanding,
misunderstanding, or the normalization of harassment beha-
vior in the work environment (Magley, Hulin, Fitzgerald, &
DeNardo, 1999).
In the present meta-analysis, we compare results for the
three different forms of measuring sexual harassment (i.e.,
behavior list with frequency, behavior list with experience,
and direct question or acknowledgment). For the frequency-
based measures, we present results for overall sexual harass-
ment and each of the facets (i.e., gender harassment,
unwanted sexual attention, and sexual coercion), in order to
identify which form of sexual harassment might have the
most harmful effect on women’s occupational well-being.
Organizational tolerance for sexual harassment (OTSH) is
a gender-based harmful workplace experience that might be
sexual in nature and operates at the level of the organizational
climate. Employees’ beliefs that complaints about sexual har-
assment will not be taken seriously by the organization, that
complaints will put them at further risk, and that offenders
will not be punished lead workers to develop the view that
an organization is tolerant of sexual harassment (Cortina
et al., 2002). Permissiveness or tolerance of sexual harass-
ment in an organization has been identified as a key predictor
of increased incidences of sexual harassment (Willness et al.,
2007). OTSH also indicates the presence of organizational
behavioral norms that are hostile towards individuals who are
targets of harassment. These behavioral norms can also
impact directly on women’s well-being. Similar to sexual
harassment and other sexist behaviors, OTSH is a form of
discrimination against women, one that violates women’s
human right to have a life free from violence (United
Nations General Assembly, 1993). OTSH can undermine
the satisfaction and commitment of women who feel
unfairly treated and unsupported by colleagues, supervisors,
and the organization (Estrada, Olson, Harbke, & Berggren,
2011; Fitzgerald et al., 1999). OTSH might also trigger
anxiety in the potential and actual targets of harassment,
who may perceive their work environment as one that does
not protect them from violence and might even foster
aggression (Glomb et al., 1997).
Measures of OTSH help understand how the organization
might deal with instances of sexual harassment (e.g., Hulin,
Fitzgerald, & Drasgow, 1996). These measures are indica-
tors of the kind of organizational climate that operates, and
may have a direct impact on women’s well-being, or could
increase the incidence of other forms of maltreatment
towards women. The construct OTSH is typically assessed
with the Organizational Tolerance for Sexual Harassment
Inventory (Dekker & Barling, 1998; Hulin et al., 1996).
This and other similar scales (e.g., Union Tolerance for
Sexual Harassment Inventory, Bulger, 2001; Tolerance of
Sexual Harassment in the Army Scale, Rosen & Martin,
1998) assess the tolerance for sexual harassment as a
whole, without reporting or making distinctions for specific
facets of harassment. Workplace tolerance for different
kinds of sexual and sexist hostility is an area that requires
further study before it can be properly addressed in a meta-
analysis.
Harmful Workplace Experiences Within
a Stress Framework
In this meta-analysis, harmful workplace experiences are
studied within a general stress framework (Hobfoll, 1989;
Lazarus & Folkman, 1986). Stress is understood as a specific
relationship between people and their environment, when
the environment is perceived as threatening and exceeding
personal resources, and their well-being is believed to be in
danger (Lazarus & Folkman, 1986). Harmful workplace
experiences are psychosocial stressors (Lazarus & Folkman,
1991); they take place within interpersonal relations, can
cause harm, and require adaptive responses (Bowling &
Beehr, 2006; Rospenda et al., 2009).
Why would women appraise negative attitudes towards
their gender, discrimination, and harassment as stressful
events? A situation is evaluated as stressful when it involves
any of three conditions (Hobfoll, 1989): (a) when people
experience a loss of resources, (b) when people’s resources
are threatened, or (c) when people have invested their
resources without gaining anything in return. Hobfoll
(1989) and colleagues (Hobfoll, Dunahoo, Ben-Porath, &
Monnier, 1994; Hobfoll & Leiberman, 1987) outlined four
categories of resources: (a) object resources (e.g., houses,
cars, and clothes), (b) condition resources (e.g., employment
and job level), (c) personal resources (e.g., self-esteem, skill,
and physical health), and (d) energy resources (e.g., means to
attain other resources, such as actual money or credit).
Harmful workplace experiences have the potential to have
an impact on all types of resources that Hobfoll identified.
For instance, sexist discrimination directly affects women’s
condition resources (e.g., getting a promotion) and energy
resources (e.g., salary and bonuses) and indirectly affects
their object resources (e.g., possibility of buying a car or a
house) and personal resources (e.g., feelings of self-worth).
Experiences of harassment and a sexist organizational cli-
mate directly affect women’s personal resources and in the
long-term their condition and energy resources, leading to the
same outcomes as those related to other life stressors.
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Intensity and Frequency of Harmful Workplace
Experiences
Harmful workplace experiences have been described as
‘‘more severe’’ (e.g., sexual coercion and unwanted sexual
attention) or ‘‘less severe’’ (e.g., gender harassment, sexist
discrimination, a sexist organizational climate, and OTSH;
Ford, Boxer, Armstrong, & Edel, 2008; Powell, 2012; Var-
hama et al., 2010) based on the levels of threat and potential
harm in a single event. For instance, Varhama et al. (2010)
and Gruber, Smith, and Kauppinen-Toropainen (1996) have
argued that experiences of sexual assault and sexual coercion
are more distressing than unwanted sexual attention and
gender harassment. Similarly, the importance of gender har-
assment is often downplayed, under the assumption that it
does not have a negative influence on relevant outcomes
(Munson, Hulin, & Drasgow, 2000). Hershcovis and Barling
(2010) have also indicated that gender harassment is arguably
less intense than unwanted sexual attention or coercion.
A large proportion of the population think that sexual
coercion and unwanted sexual attention at work are not
acceptable. At the same time, individuals see sexist jokes and
sexist language at work as less problematic (Australian
Human Rights Commission [AHRC], 2008; Ford et al.,
2008; Powell, 2012). This is of concern because sexist jokes
and comments are some of the most explicit and effective
ways to create and perpetuate a sexist organizational climate
(Boxer & Ford, 2010; Ford et al., 2008). There is extensive
research showing that people typically fail to identify these
and other abusive behaviors as forms of hostile sexual harass-
ment (AHRC, 2008; Ilies, Hauserman, Schwochau, & Stibal,
2003; Rosen & Martin, 1998; Rospenda et al., 2009) or as
potentially damaging sexist work experiences (Powell,
2012). Similarly, discrimination against women at work is
often downplayed and justified as the consequence of alleged
merit-based systems and processes (United Nations Women
National Committee Australia, 2015). Perceptions that abuses
are less intense may normalize these workplace experiences,
lead to toleration of them, and make it less likely that they
will trigger actions to stop them (Powell, 2012; Riger,
1991; Summers, 1996).
When individuals separate sexual coercion and unwanted
sexual attention as more damaging than gender harassment,
sexist organizational climate, OTSH, and sexist discrimina-
tion, they are considering the intensity of the events (i.e., the
potential for the events to cause physical and psychological
trauma in a single encounter); but they disregard the perva-
siveness of occurrence of the experiences (Langhout et al.,
2005). It might be useful to differentiate between the frequen-
cies of harmful workplace experiences at the population level
and at the individual level. Gender harassment, sexist organi-
zational climates, gender-based discrimination, and OTSH
appear to be more prevalent across the population than sexual
coercion or unwanted sexual attention (AHRC, 2008; Gett-
man & Gelfand, 2007; Murrell et al., 1995; Powell, 2012;
Sandroff, 1992; Summers, 1996). However, it is possible that
individual female targets of sexual coercion or unwanted sex-
ual attention actually have experienced these forms of harass-
ment frequently. Studies of frequency of different forms of
sexual harassment at the individual level have shown that
women experience gender harassment more often (i.e., sev-
eral more times during a given period) than sexual coercion
and unwanted sexual attention (Rosen & Martin, 1998; Shaf-
fer et al., 2000).
Gender-based discrimination in employment, performance
evaluations, salary, and career advancement (Dunlea, Sojo,
Thiel, & Westbrook, 2015; European Commission, 2012;
Genat, Wood, & Sojo, 2012; McCann, 2013; Schmitt et al.,
2002; Weichselbaumer & Winter-Ebmer, 2005), sexist
comments and jokes at work (Ford et al., 2008; Powell,
2012; Rosen & Martin, 1998), and feeling that the organi-
zation is fertile ground for harassment or expecting that the
organization will not act to protect you if you are a target
of sexual harassment (AHRC, 2008; Sandroff, 1992; Sum-
mers, 1996) might not be perceived as experiences that can
cause immediate physical or psychological trauma, but
they are still very prevalent in the population and operate
as everyday hassles.
Less intense but more common harmful workplace experi-
ences can have subtle effects with an accumulative impact
over time. The frequencies may create a context that fosters
more extreme forms of abuse (Fitzgerald, 1993; Nielsen,
Bjørkelo, Notelaers, & Einarsen, 2010). Furthermore, less
extreme forms of harassment often come from several differ-
ent sources, making them more difficult to escape, more nor-
mative, and harder to demonstrate as wrong (Berdahl, 2007a;
Ford et al., 2008). For example, women commonly experi-
ence questions about their competencies to perform their jobs
(Genat et al., 2012), lower pay for doing the same jobs
(Weichselbaumer & Winter-Ebmer, 2005), and fewer oppor-
tunities to progress their careers and access managerial roles
(Dunlea et al., 2015) relative to their equally qualified male
counterparts. The pervasiveness of these experiences makes
them very harmful over time and with repeated exposure
across situations. While an incident of sexual coercion might
be highly traumatic for the woman directly affected and oth-
ers in her immediate workplace (Gruber et al., 1996), it is
possible that sexist events of low intensity at work, which are
much more widespread, occur more frequently and, are rarely
challenged, may have much greater negative impacts on the
well-being of women (Charlesworth, McDonald, & Cerise,
2011; Fitzgerald, 1993; Nielsen et al., 2010).
Hypothesis 1: High-frequency/low-intensity harmful
workplace experiences (e.g., gender harassment, sexist
discrimination, sexist organizational climate, and OTSH)
will have an effect on women’s occupational well-being,
which will be as detrimental as low-frequency/high-inten-
sity experiences (e.g., sexual coercion and unwanted sex-
ual attention).
6 Psychology of Women Quarterly
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Proximal and Distal Indicators of Women’s
Occupational Well-being
Experiences of threats to women’s resources could have
several important consequences. Harmful workplace experi-
ences are typically followed by initial negative emotional
reactions towards the sources of the threat and the environ-
ment where threats take place. Those negative, affective reac-
tions, sustained over time, could impair women’s health
(Schneider, Swan, & Fitzgerald, 1997). An additive model
of well-being posits that proximal reactions to specific aspects
of one’s life have an accumulative impact on more distal
health outcomes that are not domain specific (Frone, Russell,
& Cooper, 1992). Models of work stress and organizational
climate argue that the effects of employees’ perceptions of the
organizational climate on individual and organizational out-
comes are mediated through work attitudes (Carr, Schmidt,
Ford, & DeShon, 2003; Kelloway & Barling, 1991).
In the present meta-analysis, we focus on work attitudes
as proximal outcomes and health as distal outcomes. Work
attitudes and health are the most widely studied indicators
of occupational well-being that can be affected by harmful
workplace experiences. Focusing on them allows for a more
robust evaluation of the impact of harmful workplace
experiences. Work attitudes (e.g., organizational commit-
ment, job satisfaction and its facets) are markers of the
quality of the relationship between the employees and their
work environment; they have been shown to be associated
with workers’ health and performance (Faragher, Cass, &
Cooper, 2005; Fried, Shirom, Gilboa, & Cooper, 2008;
Mathieu & Zajac, 1990; Meyer & Maltin, 2010). Organiza-
tional stressors typically lead to negative affective reactions,
including job dissatisfaction and reduced organizational
commitment (Munson et al., 2000).
Interpersonal stressors in occupational contexts, such as
the harmful workplace experiences studied in this meta-
analysis, are expected to have a larger effect on emotional
reactions towards the psychosocial aspects of the work
context that are the source of the stress, such as dissatisfaction
with co-workers and supervisors. Two previous meta-
analyses with mixed samples of men and women support this
idea. Topa Cantisano, Morales Domı´nguez, and Depolo
(2008) found that overall sexual harassment (a psychosocial
organizational stressor) was more strongly associated with
supervisor satisfaction and co-worker satisfaction than with
overall job satisfaction. Similarly, Willness, Steel, and Lee
(2007) found that sexual harassment was more strongly nega-
tively associated with supervisor satisfaction and co-worker
satisfaction than with work satisfaction (satisfaction with the
nature of the tasks performed at work). Topa Cantisano et al.
(2008) argued that sexual harassment should have a stronger
impact on the psychosocial facets of job satisfaction (e.g.,
supervisor satisfaction and co-worker satisfaction) than on
the evaluations of more concrete work aspects (e.g., work
satisfaction). However, no previous meta-analysis has
considered the association of sexist organizational climate
and sexist discrimination with these outcomes.
Hypothesis 2: Harmful workplace experiences will have a
stronger negative impact on co-worker and supervision
satisfaction than on work satisfaction.
Several studies in the area of stress and trauma have
shown the negative effect of stressful events, both life
events and everyday hassles, on physical health (Baum &
Posluszny, 1999; Everson-Rose & Lewis, 2005) and mental
health (Goldmann & Galea, 2014). In many studies linking
stress with health, negative affect such as anger, hostility,
resentment, and job dissatisfaction have been shown to be
mediating mechanisms (Everson-Rose & Lewis, 2005; Kelly,
Hertzman, & Daniels, 1997; Kiecolt-Glaser, McGuire, Robles,
& Glaser, 2002). The negative affect associated with stressful
events can trigger physiological responses (e.g., heightened
blood pressure, heart rate, and cortisol secretion) as well as
psychological responses (e.g., cognitive dissonance and desire
to escape), both of which, if sustained over time, could impair
the targets’ well-being (Barling et al., 2001; Bergman, 2003;
Pascoe & Smart Richman, 2009). Both the acute experience
of an intense stressful event and the chronic exposure to
stressors have been associated with stress reactions that,
over time, lead to disorders such as increased blood glucose,
infections, cardiovascular diseases, depression, anxiety dis-
orders, and post-traumatic stress disorder (PTSD; Kiecolt-
Glaser et al., 2002; Krantz & McCeney, 2002; Miller, Chen,
& Cole, 2009; Pascoe & Smart Richman, 2009; Steptoe &
Kivimaki, 2013).
The negative emotional reactions women display towards
elements of their jobs (e.g., job dissatisfaction and lower
organizational commitment) following harmful workplace
experiences might mediate the relation between those experi-
ences and distal health indicators. However, some authors
have established a distinction between low-frequency/high-
intensity versus high-frequency/low-intensity harmful work-
place experiences and how they affect health outcomes
(Hershcovis & Barling, 2010; Varhama et al., 2010). High
intensity events (e.g., sexual coercion and unwanted sexual
attention) present a higher level of threat and the potential for
immediate harm; they are expected to have a direct negative
effect on women’s health. Harmful workplace experiences of
high frequency but low intensity that signal a hostile work
environment (e.g., gender harassment, sexist organizational
climate, and OTSH) may impact health via the accumulative,
recurrent, and negative affective reactions towards the work
context (e.g., high dissatisfaction with co-workers and super-
visor and lower organizational commitment). These relations
are shown in Figure 2.
Hypothesis 3: The relation between high-frequency/low-
intensity harmful workplace experiences and health will
be mediated by work attitudes; the relation of low-
Sojo et al. 7
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frequency/high-intensity experiences with health will be
partially mediated by work attitudes, having also a direct
association with health.
Controlling for Other Job Stressors
Stressors that can affect women’s well-being include but are
not restricted to harmful experiences at work. Job stressors
such as poorly planned, excessive, and tedious tasks, job
uncertainty, and physical risks are typically evaluated as
threatening and exceeding personal resources (Goldenhar,
Swanson, Hurrell, Ruder, & Deddens, 1998). The relative
effects of harmful work experiences on female well-being
compared to other job stressors are important to the current
study. Failure to consider harmful workplace experiences in
the studies of job stress, and vice versa, will give inaccurate
estimates of the full impact that potential stressors can have
on occupational well-being (Rospenda et al., 2009).
In the present study, we compare the association between
women’s occupational well-being and harmful workplace
experiences, with other common job stressors (Cooper &
Cartwright, 2001) that are not based on interpersonal
conflicts (e.g., job overload, role conflict, job tedium, role
ambiguity, responsibility for others, and poor physical job
conditions). We use classic meta-analytic procedures and
path-analysis in this process. Some studies of job stressors
include measures of overall occupational stress (e.g., Cortina
et al., 2002; Vinokur, Pierce, & Buck, 1999), whereas others
measure specific stressful events such as job overload (e.g.,
Lyness & Thompson, 1997) or job monotony (e.g., Grandey,
Cordeiro, & Crouter, 2005) in their relation with occupational
well-being outcomes and harmful workplace experiences.
In a previous meta-analysis (Bowling & Beehr, 2006), with
mixed samples of men and women, workplace harassment was
related to several occupational well-being outcomes (e.g.,
burnout, physical health, organizational commitment, and job
satisfaction) even after role ambiguity and role conflict were
controlled. These results were interpreted as indicating that
work harassment had a fairly independent effect on the well-
being outcomes, distinct from the effect of other job stressors.
However, no previous meta-analysis has evaluated the impact
of different gender-based harmful workplace experiences on
occupational well-being after controlling for the effect of other
job stressors included in this meta-analysis.
Hypothesis 4: The impact of harmful workplace experi-
ences on women’s occupational well-being will be signif-
icant after controlling for other job stressors.
Harmful Workplace Experiences and Male-dominated
Contexts
Previous research has identified several variables as possible
moderators of the association between harmful workplace
experiences and occupational well-being (Bowling & Beehr,
2006). We focus on the power and status differentials of men
and women, as indexed by the representation of women in
the organizations studied. In organizations, as in society,
gender is used to differentiate between individuals, to allo-
cate roles, and to define individuals’ status (Fiske, Haslam,
& Fiske, 1991). Men are typically accorded higher status
than their female counterparts in cultures, societies (Hopcroft,
2009; Ridgeway, 1991), and organizations (Andes, 1992;
Ragins & Sundstrom, 1989). This higher status is associated
with greater access to, and control over, key resources
(Deere & Doss, 2006; Weichselbaumer & Winter-Ebmer,
2005). Harmful behaviors by men towards women help
them to preserve their higher status in the gender hierarchy
and the associated benefits.
The effects of the lower status and lower power of women
in the hierarchy of gender identities is exacerbated in male-
dominated contexts (Berdahl, 2007a). Women have less
power and lower status when the gender ratio of their occupa-
tion is heavily biased towards men (Miner-Rubino, Settles, &
Stewart, 2009); this increases the risk of women being seen as
‘‘easy targets’’ for harmful experiences. At the same time,
men have more to lose from perceived challenges to their
higher status as the dominant group. Women who work in
Harmful Workplace Experiences
Low-frequency/high-intensity
• Sexual coercion
•
Unwanted sexual aenon
High-frequency/low-intensity
•
Gender harassment
•
OTSH
•
Sexist discriminaon
•
Sexist organizaonal climate
Proximal Outcomes
•
Organisaonal commitment
• Job sasfacon
• Supervision sasfacon
•
Co-worker sasfacon
•
Work sasfacon
Distal Outcomes
•
General health
• Physical health
• Mental health
•
Life sasfacon
Figure 2. Relation between harmful workplace experiences, proximal and distal occupational well-being indicators.
8 Psychology of Women Quarterly
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male-dominated occupations are often perceived as counter-
stereotypical. Women who behave counter-stereotypically
(e.g., express feminist views and display masculine traits) are
more likely to be harassed (Berdahl, 2007b; Maass, Cadinu,
Guarnieri, & Grasselli, 2003).
Hypothesis 5: The association between harmful work-
place experiences and women’s occupational well-being
will be significantly more negative in male-dominated
work environments compared to more gender-balanced
work contexts.
The Meta-Analysis
In the present meta-analysis, we focus on understanding the
impact of harmful workplace experiences on women.
Women are the targets for the majority of harmful work-
place experiences. Also, the psychosocial experience of
harmful encounters at work is fundamentally different for
men and women (Gutek, 1985; Welsh, 1999). Women and
men identify different actions as cases of sexual harassment
(Berdahl, Magley, & Waldo, 1996); they experience differ-
ent levels of hostility and degradation (Parker & Griffin,
2002), and they have different perceptions of the perpetra-
tors of sexual harassment (Dougherty, 2006). In addition,
themostwidelyusedmeasuresofgenderedandsexualized
harmful workplace experiences were designed for female
respondents (e.g., Bergman, 2003; Fitzgerald et al., 1995;
Gruber, 1998). Measures of general, gendered, and sexualized,
harmful workplace experiences that cover the full spectrum of
experiences that both men and women might encounter is an
area that requires further research (Hershcovis & Barling,
2010; Willness et al., 2007).
Previous meta-analyses have successfully conceptualized
discrimination, work harassment, and sexual harassment
within a stress framework and have established their negative
association with diverse well-being indicators (Bowling &
Beehr, 2006; Chan et al., 2008; Pascoe & Smart Richman,
2009; Willness et al., 2007). Willness et al. (2007) hinted at
disparities in the impact of different forms of sexual harass-
ment on well-being. However, studies have taken an undiffer-
entiated view of harmful experiences, analyzing the overall
sexual harassment, without analyzing different types of harm-
ful experiences, or comparing gender-based stress with other
sources of work stress (Chan et al., 2008; Willness et al.,
2007). Other meta-analyses also have considered only gen-
eral job satisfaction (Lapierre, Spector, & Leck, 2005) or
other well-being outcomes, such as job and work with-
drawal (Hershcovis & Barling, 2010); they have excluded
life satisfaction or physical health, which are considered
in the present meta-analysis. Finally, to our knowledge, no
other meta-analysis has described and compared the effect
of a sexist organizational climate and sexist discrimination
with each other, and with work harassment, sexual harass-
ment, and other work stressors.
The present meta-analysis aims to provide answers to the
following questions: (1) Are there differences between high-
frequency/low-intensity and low-frequency/high-intensity
harmful workplace experiences in their impacts on women’s
occupational well-being? (2) Are these harmful workplace
experiences as detrimental for women’s occupational well-
being as other job stressors? (3) How does women’s relative
representation in the organization affect the relation between
harmful workplace experiences and women’s well-being? (4)
What is the effect of harmful workplace experiences on
women’s occupational well-being after controlling for job
stressors? (5) Do work attitudes mediate the relation between
harmful workplace experiences and women’s health?
Method
Data Collection
We searched electronic databases to identify relevant pub-
lished research including EBSCO (Academic, Business and
Education, Psychology and Behavioral Sciences), ERIC,
Health Business Elite, Health Source: Nursing/Academic
Edition, MEDLINE, MasterFILE Premier, PsycINFO, SocIN-
DEX, and Emerald. The keywords that we used were combina-
tions of women, gender, aggression, violence, sexism, sexual
harassment, work harassment, incivility, bullying, mobbing,
discrimination, stress, job stress with health, well-being,
cardio*, blood pressure, smok*, alcohol* depress*, anxiety,
distress, mental, occupational health, work attitudes, job satis-
faction,andorganizational commitment. We also searched
through the reference lists of previous meta-analyses (Bowling
& Beehr, 2006; Chan et al., 2008; Hershcovis & Barling, 2010;
Lapierre et al., 2005; Pascoe & Smart Richman, 2009; Willness
et al., 2007). No limit by year of publication was established
for these searches. Approximately 3,000 articles were identi-
fied and screened by at least two of the authors.
Articles were excluded when they were not empirical
(e.g., literature reviews), if they were not published in a
peer-review journal (e.g., dissertations and book chapters),
if they did not include independent results for women, if the
samples were not employed at the time of data collection or
did not report on their situation as workers, if the study did
not examine at least one indicator of health or work attitudes,
and if the study did not include zero-order correlations
between the relevant variables or have statistics that could
be transformed to correlations (e.g., F, t, X
2
). A number of
studies contained data collected from the same samples but
reported results for different combinations of variables
(e.g., Langhout et al., 2005; Murry, Sivasubramaniam, & Jac-
ques, 2001). The relevant data were extracted from those
studies without violating the independence of observations.
We decided to work only with published articles to avoid
studies that had not been peer-reviewed. Authors were con-
tacted when data were not complete, when we identified mis-
takes in the labeling of some variables, and when we needed
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to clarify if authors had more than one publication from the
same data set. Given that we worked exclusively with pub-
lished research, we conducted publication bias analyses and
the results indicated it was very unlikely any of our findings
were affected by publication bias (see Publication bias in the
Results section below). The screening process resulted in the
inclusion of 88 studies with 93 independent samples and
73,877 participants published from 1985 to 2012.
1
Coding Categories
The first step in the coding process was to review previous
research to examine the definitions of variables and to iden-
tify the items used to measure them. We then created concep-
tually based categories for grouping the different variables
(see McKee-Ryan, Song, Wanberg, & Kinicki, 2005, for a
similar approach). The three authors discussed the categories
until reaching 100% agreement about their content. Variables
were subdivided into indicators of occupational well-being
(i.e., work attitudes and individual health), harmful work-
place experiences (i.e., forms of harassment and sexism), and
job stressors.
Indicators of occupational well-being were grouped into
two categories of proximal and distal indices. Five proximal
indicators were analyzed with measures of organizational
commitment (i.e., general organizational commitment or
affective commitment), job satisfaction (i.e., overall evalua-
tions of the job with items either targeting different dimen-
sions of the job or different emotional reactions towards the
job), work satisfaction (i.e., evaluations towards the work
tasks performed), co-worker satisfaction and supervision
satisfaction (i.e., affective or evaluative reactions towards the
co-workers and towards the supervisor, respectively). Four
measures of women’s health were used as distal indicators
of occupational well-being: general health (i.e., mixed indica-
tors of physical and psychological health outcomes), physical
health (e.g., self-reported physical problems and diagnosed
physical symptoms), mental health (e.g., anxiety, depression,
PTSD, burnout, and psychological distress), and satisfaction
with life (i.e., affective reactions towards the personal life and
towards roles such as parent and spouse).
Harmful workplace experience categories included non-
gender-based work harassment, sexual harassment, OTSH,
and sexism at work. This last category was further divided
into sexist discrimination and sexist organizational climate.
Non-gender-based work harassment was measured with
behavioral lists, frequency-based scales that included both
physical and psychological forms of harassment. In most
studies, the responses to the different items were reported
as a single composite indicator.
The different measures of sexual harassment were cate-
gorized as those that asked the respondents to acknowledge
harassment (i.e., direct question whether the participant
had experienced sexual harassment), report experiences of har-
assment (i.e., behavioral lists to report presence or absence of
harassment events or behavioral list to report frequency of
experience; the authors dichotomized the latter), or report the
frequency of experiencing harassment (i.e., behavioral lists
to report how often the harassing event took place). In studies
evaluating how frequently individual women experienced each
kind of sexual harassment, associations were reported for
either the general sexual harassment or for the facets of sexual
harassment (i.e., gender harassment, sexual coercion, and
unwanted sexual attention); these categories also were ana-
lyzed. The SEQ (Fitzgerald et al., 1995), in its several versions,
is the most widely used measure of sexual harassment. We
analyzed the associations of sexual harassment measured with
the SEQ versus the other measures of sexual harassment.
We also compared the summary effect sizes of high-
frequency/low-intensity harmful workplace experiences
(i.e., frequency of gender harassment, sexist discrimination,
sexist organizational climate, and OTSH) with the summary
effect of low-frequency/high-intensity experiences (i.e., fre-
quency of sexual coercion and unwanted sexual attention) for
each outcome variable. One general category of job stressors
was analyzed, which comprised measures of events such as
role ambiguity, job monotony, and work overload. Defini-
tions of variables and examples of measures for each of them
are presented in Table 1.
2
For the moderation analysis, we classified the studies into
those conducted in male-dominated work environments (e.g.,
armed forces, mining, and basic science) versus studies done
in general work environments (e.g., social sciences, day care,
schools, and samples from mixed contexts). To guide the
categorization of the samples, we used previous research with
classifications of actual and perceived gender representation
in occupational sectors (i.e., studies where participants were
asked to rate how stereotypically masculine or feminine an
occupation was or to estimate the representation of women
and men in an occupation; e.g., Bouazzaoui & Mullet,
2012; Johnson, Podratz, Dipboye, & Gibbons, 2010) and gov-
ernment reports (e.g., European Commission’s Expert Group
on Gender and Employment, 2009; International Labour
Office, 2012). The classification for each study can be found
in the Supplemental materials in Table S1.
One of the authors and two research assistants indepen-
dently coded for the reference of the publication, country,
age, work context of the sample, variables’ name, measure-
ment, internal consistency (i.e., Cronbach’s a), and the effect
size and sample size of the association between the variables.
The results of the three independent coding processes were
compared and discrepancies in coding were resolved with
discussions until 100% agreement was reached (see Table
S1 in the Supplemental materials for full data set coded).
Meta-Analytic Procedures
The meta-analysis methods were based on recommendations
by Borenstein, Hedges, Higgins, and Rothstein (2009) and
Hunter and Schmidt (2004). First, we converted different
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Table 1. Categories, Variables, Descriptions, and Examples of Measures Used in Studies Meta-Analyzed.
Predictors
Variable Description Examples of Measures Used
Harmful workplace experiences
Work
harassment
Instances of aggression and violence
experienced in the workplace that are
not obviously sexual or related to
gender
Overt-Covert Aggression Scale. Twenty-one items with a 4-point scale
(0 ¼ never and 3 ¼ very often) assessing direct overt, indirect
manipulative, covert insinuative, and rational-appearing aggression
(Kaukiainen, Salmivalli, Lagerspetz, Lahtinen, & Kostamo, 1997)
Generalized Workplace Harassment Questionnaire. Twenty-nine items
with a 5-point scale (0 ¼ never and 4 ¼ many times) assessing five
dimensions of general workplace harassment: verbal aggression,
disrespectful behavior, isolation/exclusion, threats/bribes, and physical
aggression (Rospenda & Richman, 2004)
Acknowledged
general sexual
harassment
Experience of events in the workplace that
are regarded as ‘‘sexual harassment’’
Single item. ‘‘Have you been subject to unwelcome behavior that you
regard as sexual harassment (a) by a partner, (b) by a supervisor, (c) by
a co-worker, (d) by a client?’’ with a 3-point scale (1 ¼ yes, more than
once;2¼ yes, once; and 3 ¼ no; Burke, 1995)
Single item. Participants were asked if they had been sexually harassed by
a co-worker or supervisor in their units in the past 12 months.
Response choices were ‘‘yes’’ and ‘‘no’’ (Rosen & Martin, 1998)
Experience of
general sexual
harassment
Being a target of instances of gender
harassment, sexual coercion, or
unwanted sexual attention in the
workplace
Northwestern National Life Insurance Company (1993) Survey on
Workplace Violence. Three items with a 2-point, yes–no scale.
Example item: ‘‘On the job site, have you ever had unwanted
suggestions about, or references to, sexual activity directed at you by
(a) co-workers or (b) supervisors?’’
1 item with a 4-point scale (0 ¼ not applicable,1¼ not at all a factor,2¼
somewhat of a factor, and 3 ¼ definitely a factor). Participants indicated
whether sexual harassment was a reason for leaving their job (Rosin &
Korabik, 1991)
Frequency of
general sexual
harassment
Regularity with which instances of gender
harassment, sexual coercion, or
unwanted sexual attention jokes are
experienced in the workplace
Sexual Experiences Questionnaire. Eighteen items with a 5-point scale
(1 ¼ never,2¼ a few times,3¼ several times,4¼ regularly, and 5 ¼
many times). Three dimensions: gender harassment, unwanted sexual
attention, and sexual coercion (Fitzgerald et al., 1988)
Thirty-six items with a 6-point scale (0 ¼ never,1¼ once,2¼ twice,3¼ three
times,4¼ four times,and5¼ five or more times). Example item: ‘‘been
sexually propositioned by someone.’’ Two dimensions: sexualized
aggression and sexual harassment (Barling, Rogers, & Kelloway, 2001)
Frequency of
gender
harassment
Regularity with which offensive verbal and
non-verbal sexual behaviors, such as
making sexual gestures, comments, or
jokes are experienced in the workplace
(Buchanan, Settles, & Woods, 2008)
Sexual Experiences Questionnaire—Gender harassment. Four items with
a 5-point scale (0 ¼ never and 4 ¼ many times). Example item: have
personally been ‘‘habitually told suggestive stories or offensive jokes’’
(Fitzgerald et al., 1988)
One item with a 4-point scale (x ¼ never and x ¼ very often). Example item:
‘‘At work, have you experienced or heard offensive slurs or jokes or
remarks about women?’’ (Piotrkowski, 1998)
Frequency of
sexual
coercion
Regularity with which instances of implicit
or explicit efforts to gain sexual
cooperation in exchange for job-related
outcomes are experienced in the
workplace (Bulger, 2001)
Sexual Experiences Questionnaire—Sexual coercion. Seven item with a
5-point subscale (0 ¼ never and 4 ¼ many times). Example item: ‘‘made
you afraid that you would be treated poorly if you did not cooperate
sexually?’’ (Fitzgerald et al., 1988)
Sexual Experiences Questionnaire—Department of Defense—Sexual
coercion. Four items with a 5-point scale (0 ¼ never and 4 ¼ very often).
Example item: ‘‘implied faster promotions or better treatment if you
were sexually cooperative’’ (Fitzgerald et al., 1999)
Frequency of
unwanted
sexual
attention
Regularity with which instances of overt
direct victim-focused behaviors including
pressure for dates, touching or ogling,
and unwanted attempts to fondle are
experienced in the workplace (Murry,
Sivasubramaniam, & Jacques, 2001)
Sexual Experiences Questionnaire—Unwanted sexual attention. Six item
with a 5-point subscale (0 ¼ never;4¼ many times). Example item:
‘‘made unwanted attempts to establish a romantic relationship with you
despite your efforts to discourage it’’ (Fitzgerald et al., 1988)
Sexual Harassment Survey. One item with a 5-point scale (0 ¼ never
and
4 ¼ four or more times) asking about experiences during Persian Gulf
military deployment. Example item: ‘‘Physical sexual harassment (e.g.,
unwanted sexual touching, fondling, cornering, or brushing against
you)’’ (Wolfe et al., 1998)
(continued)
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Table 1. (continued)
Predictors
Variable Description Examples of Measures Used
Organizational
tolerance for
sexual
harassment
How the organization might react when
individuals complain for sexual
harassment, in terms of taking the
complaints seriously, how risky it is to
complain, and lack of meaningful
sanctions for perpetrators (Cortina
et al., 2002)
Organizational Tolerance for Sexual Harassment Inventory. Three
scenarios of sexual harassment followed by 3 items with a 5-point
Likert-type scale to assess perception of risk for complaining about the
event, likelihood that complains would be taken seriously, and chances
that the harasser would face sanctions (Hulin et al., 1996)
Organizational Sanctions against Sexual Harassment Scale. Eight items
with a 5-point Likert-type scale. Example item: ‘‘In this company, if you
know who to talk to, you can get ‘off the hook’ when a sexual
harassment complaint is filed against you’’ (Dekker & Barling, 1998)
Sexist
discrimination
Personal experiences of unequal allocation
of resources, opportunities, or benefits
at work because of being a woman
Gender Evaluation Scale. Six items with a 5-point Likert-type scale.
Example item: ‘‘Gender played a role in the last performance evaluation
I received’’ (Shaffer, Joplin, Bell, Lau, & Oguz, 2000)
Women Workplace Culture Questionnaire—Personally experienced
burdens. Nine items with different scale formats mainly frequency-
based. Example item: ‘‘Fewer developmental opportunities than I wish
for’’ (Bergman & Hallberg, 2002)
Sexist
organizational
climate
Extent to which the organization values
men more than women and is associated
with stereotypically male traits as well as
experiences of gender-based
discrimination
University of Virginia School of Medicine Gender Fairness Environment
Scale. Six items with a 5-point Likert-type scale. Example item: ‘‘Some
faculty have a condescending attitude towards women’’ (Hostler &
Gressard, 1993)
Women Workplace Culture Questionnaire—Perceived burdens on
women. Eleven items with different scale formats mainly frequency-
based. Example item: ‘‘Unfair judgment of women’s work’’ (Bergman &
Hallberg, 2002)
Job stress
Job stress Presence and frequency of events taking
place at work that are considered as
taxing or exceeding the own resources
Job Stress Scale. Twenty items with a 4-point scale (1 ¼ almost never or
never and 4 ¼ almost always) evaluating work overload, lack of
autonomy, role ambiguity, and lack of responsibility (Frone, Russell, &
Cooper, 1992)
Role Overload Scale. Thirteen items with a 5-point Likert-type scale.
Example item: ‘‘There are too many demands on my time’’ (Reilly,
1982)
Proximal: work attitudes
Organizational
commitment
Identification and psychological attachment
to the organization (Gettman & Gelfand,
2007)
Organizational Commitment Scale. Six items with a 7-point Likert-type
scale. Example item: ‘‘This organization has a great deal of personal
meaning to me’’ (Meyer, Allen, & Smith, 1993)
Organizational Commitment Questionnaire, short version. Nine items
with a 7-point Likert-type scale. Example item: ‘‘Willingness to expend
extra effort on a job’’ (Mowday, Steers, & Porter, 1979)
Job satisfaction General affective reaction to the job with
and without references to specific job
facet
Five items with a 5-point scale (1 ¼ very dissatisfied and 5 ¼ very satisfied).
Participants indicated their level of satisfaction on items such as job
challenge, level of responsibility, and opportunity to use skills and
abilities (Lyness & Thompson, 1997)
Seven items with a 7-point scale (1 ¼ very dissatisfied and 7 ¼ very satisfied).
Three items tapped intrinsic job satisfaction, 3 items tapped extrinsic
job satisfaction, and 1 item assessed global job satisfaction. Example
intrinsic item: ‘‘feel good about yourself as a person’’ (Cook,
Hepworth, Wall, & Warr, 1981)
Work satisfaction General affective reaction to the quality of
the specific tasks performed in a job
Armed Forces Sexual Harassment Survey. Six items with a 5-point Likert-
type scale. Example item: ‘‘you like the kind of work you do’’ (Edwards,
Elig, Edwards, & Riemer, 1997)
Fifteen items with a 5-point Likert-type scale. Example item: ‘‘Does your
work provide you with a sense of pride?’’ (Harned, Ormerod, Palmieri,
Collinsworth, & Reed, 2002)
(continued)
12 Psychology of Women Quarterly
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effect sizes to a common statistic r. The sample correlations
were transformed to Fisher’s z for all calculations and trans-
formed back to correlation units for interpretations (see
Borenstein, Hedges, Higgins, & Rothstein, 2009, pp. 42 and
48, for transformation formulas). Second, variables were
coded so that a higher number would reflect more of the
variable as defined by a category; correlation signs were
reversed when necessary. Third, correlations obtained from
the same sample evaluating the same variables were averaged
to prevent violation of observations’ independence. The final
set for this section of the meta-analysis included 403 correla-
tions. Fourth, sample-size weighted mean effect sizes and Q
statistics were computed using random-effects models. Fifth,
we calculated corrected mean effect sizes (i.e., r
c
) by adjust-
ing for measurement error. Mean reliability for each variable
was used to correct for measurement error (Hunter &
Schmidt, 2004). Table 2 presents the reliability distributions
of the measures. Finally, we computed the confidence
Table 1. (continued)
Outcomes
Variable Description Examples of Measures Used
Co-worker
satisfaction
General affective reaction to the quality of
the relationship with co-workers
Six items with a 5-point Likert-type scale. Example item: ‘‘you are satisfied
with the relationship you have with your co-workers’’ (Leskinen,
Cortina, & Kabat, 2011)
Three items with a 5-point scale. One item ranged from not at all to very
large extent, 1 item ranged from very dissatisfied to very satisfied,and1item
ranged from strongly disagree to strongly agree. Example item: ‘‘Is there
conflict among your co-workers?’’ (Harned et al., 2002)
Supervision
satisfaction
General affective reaction to the quality of
the relationship with supervisor
Job Descriptive Index. Eighteen items with a 3-point supervision subscale
(yes, no, and uncertain). Participants were asked whether the item
describes the supervision they get on the job. Example item:
‘‘supportive’’ (Smith, Kendall, & Hulin, 1969)
Six items with a 5-point scale (1 ¼ not at all, very dissatisfied, strongly
disagree;5¼ very large extent, very satisfied, strongly agree). Example item:
‘‘Do you trust your supervisor?’’ (Harned et al., 2002)
Distal: health
General health Overall well-being and absence of specific
perceived or diagnosed mental and
physical health symptoms, conditions,
and social dysfunctions
Short-Form 36. Four items with a 4-point scale (1 ¼ definitely false and 4 ¼
definitely true). Example item: ‘‘my health is excellent’’ (Ware &
Sherbourne, 1992)
Three items with a 4-point subscale. Participants indicated current health
(1 ¼ poor and 4 ¼ excellent), extent to which daily activities are limited
by health (1 ¼ great deal and 4 ¼ not at all), and satisfaction with health
(1 ¼ not at all satisfied and 4 ¼ completely satisfied; House, 1986)
Physical health Physical well-being and absence of specific
perceived or diagnosed physical health
symptoms or conditions
Hopkins Symptom Checklist—Somatization. Twelve items with a 7-point
scale (1 ¼ never and 7 ¼ very often) used to report how often a symptom
has been experienced during the past week. Example item: ‘‘Pains in the
heart or chest’’ (Derogatis, Lipman, Rickels, Uhlenhuth, & Covi, 1974)
Health Condition Index (Adapted). Thirteen items with a yes–no scale
used to indicate the presence or absence of symptoms. Example item:
‘‘Severe headaches’’ (Fitzgerald et al., 1997)
Mental health Mental well-being and absence of specific
perceived or diagnosed mental health
symptoms or conditions
Short-Form 36. Three item with a 4-point scale (1 ¼ little or none of the
time and 4 ¼ all or most of the time). Example item: ‘‘didn’t do work or
other activities as carefully as usual’’ ... ‘‘as a result of emotional
problems (such as feeling depressed or anxious)’’ (Leskinen et al., 2011)
Hopkins Symptom Checklist—Depression. Eleven items with a 7-point
scale (1 ¼ never and 7 ¼ very often) used to report how often a
symptom has been experienced during the past week. Example item:
‘‘Crying easily’’ (Derogatis et al., 1974)
Satisfaction with
life
Overall evaluation of own life Satisfaction with Life Scale. Five items with a 7-point Likert-type scale.
Example item: ‘‘In most ways my life is close to my ideal’’ (Diener,
Emmons, Larsen, & Griffin, 1985)
Two items with a 3-point scale. Example item: ‘‘In general, how satisfying
do you find the way you’re spending your life these days? Would you
call it completely satisfying, pretty satisfying, or not very satisfying?’’
(Cooke & Rousseau, 1984)
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intervals (CIs) around the corrected mean effect sizes (see
Table S2 in Online Supplements for the extended results) fol-
lowing Hunter and Schmidt’s (2004) approach.
Results
The presentation of results follows the hypotheses. First, we
report the meta-analytic results for the relations of harmful
workplace experiences and job stressors with indicators of
women’s occupational well-being. In this section, we address
Hypothesis 1 by comparing the magnitude of the effect sizes
of the more intense/less frequent harmful experiences (i.e., sex-
ual coercion and unwanted sexual attention) with those of more
frequent/less intense experiences (i.e., gender harassment,
OTSH, sexist discrimination, and sexist organizational cli-
mate). We also compare the association of the different harmful
workplace experiences with co-worker and supervisor satisfac-
tion versus work satisfaction to evaluate Hypothesis 2. We then
report the path analyses to evaluate the mediating effect of work
attitudes in the relation of the different harmful workplace
experiences and job stress with mental health to evaluate
Hypotheses 3 and 4. Finally, we address Hypothesis 5 and pres-
ent the publication bias results. Only statistically significant
associations are described. Summary effect sizes were consid-
ered significant when their 95% CI did not include zero. Differ-
ences between effect sizes were considered significant, when
the 95% CI of the effect sizes analyzed did not overlap. The
magnitude of significant effects was interpreted using Cohen’s
(1988) categorization: small effects are r
c
<.29,mediumeffects
are .30 < r
c
< .49, and large effects are r
c
>.50.
Hypothesis 1
High-frequency/low-intensity harmful workplace experi-
ences (e.g., gender harassment, sexist discrimination, sexist
organizational climate, and OTSH) were expected to have
an impact on women’s occupational well-being as detrimen-
tal as low-frequency/high-intensity experiences (e.g., sexual
coercion and unwanted sexual attention).
Correlates of general work attitudes. The results for women’s
organizational commitment and job satisfaction (see Table 3)
indicate that high-frequency/low-intensity harmful work-
place experiences (r
c
¼.24; 95% CI [.30, .17]) had a
significantly stronger association with organizational com-
mitment than low-frequency/high-intensity experiences (r
c
¼.13; 95% CI [.17, .10]). Similarly, high-frequency/
low-intensity harmful workplace experiences (r
c
¼.36;
95% CI [.41, .31]) had a significantly stronger association
with job satisfaction than low-frequency/high-intensity
experiences (r
c
¼.18; 95% CI [.20, .15]).
To be more specific, both OTSH (r
c
¼.29; 95% CI
[.40, .18]) and sexist organizational climate (r
c
¼.28;
95% CI [.39, .16]) had significantly larger associations
with organizational commitment than sexual coercion (r
c
¼
.12; 95% CI [.13, .10]). Sexist discrimination (r
c
¼
.43; 95% CI [.56, .29]) and sexist organizational climate
(r
c
¼.47; 95% CI [.56, .37]) had significantly larger
associations with job satisfaction than sexual coercion (r
c
¼
.15; 95% CI [.18, .13]) and unwanted sexual attention
(r
c
¼.20; 95% CI [ .22, .17]). Also, OTSH (r
c
¼
.27; 95% CI [.32, .21]) had a significantly larger asso-
ciation with job satisfaction than sexual coercion.
In general, harmful experiences had a stronger negative
relation with women’s job satisfaction than with their organi-
zational commitment, although most correlations were small.
Frequency-based measures of sexual harassment were more
strongly related to work attitudes than the other methods.
However, only one of these differences was significant: The
reported frequency of sexual harassment (r
c
¼.30; 95% CI
[.37, .23]) had a significantly larger association with job
satisfaction than acknowledged sexual harassment (r
c
¼
.11; 95% CI [.19, .04]).
Correlates of specific work attitudes. The results of analyses of
women’s satisfaction with work, co-workers, and supervision
(see Table 4) showed no significant difference in the associ-
ation of high-frequency/low-intensity harmful workplace
experiences with any of the specific work attitudes, compared
to the associations of these outcome variables with low-
frequency/high-intensity experiences. However, in all cases,
high-frequency/low-intensity experiences presented stronger
associations. Comparing the specific harmful workplace
experiences, sexist discrimination (r
c
¼.49; 95% CI
[.63, .34]) had a significantly larger association with co-
worker satisfaction than sexual coercion (r
c
¼.16; 95%
CI [.27, .06]) and unwanted sexual attention (r
c
¼
.21; 95% CI [.32, .10]). Sexist discrimination (r
c
¼
.29; 95% CI [.39, .19]) had significantly larger associa-
tions with work satisfaction than sexual coercion (r
c
¼.12;
95% CI [.15, .10]). The harmful work experiences and job
stressors were negatively correlated with all three specific
work attitudes.
Correlates of general and physical well-being. The associations of
the harmful workplace experiences and job stressors with
general and physical health are presented in Table 5. All
effects were negative and mostly small. High-frequency/
low-intensity harmful workplace experiences (r
c
¼.18;
95% CI [.22, .15]) had a significantly stronger association
with general health than low-frequency/high-intensity experi-
ences (r
c
¼.12; 95% CI [.14, .10]). No significant dif-
ference was observed in the association of high-frequency/
low-intensity harmful workplace experiences with physical
health, compared to the associations of this outcome with
low-frequency/high-intensity experiences. However, when
the specific experiences were compared in their impact, sex-
ist discrimination had a significantly higher correlation with
physical health (r
c
¼.38; 95% CI [.48, .28]) than sexual
coercion (r
c
¼.17; 95% CI [.19, .14]) and unwanted
sexual attention (r
c
¼.18; 95% CI [.21, .16]).
14 Psychology of Women Quarterly
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Correlates of psychological well-being. Results for mental health
and life satisfaction are in Table 6. All the correlates had stron-
ger negative associations with women’s mental health than with
their life satisfaction. However, all the correlations were small
or medium. No significant difference was observed in the asso-
ciation of high-frequency/low-intensity harmful workplace
experiences with mental health, compared to the associations
of this variable with low-frequency/high-intensity experiences.
There were no studies evaluating the association of life satisfac-
tion with sexual coercion and unwanted sexual attention.
In summary, supporting Hypothesis 1, high-frequency/
low-intensity harmful workplace experiences were as detri-
mental for women’s occupational well-being as the low-
frequency/high-intensity experiences. It is important to note
that high-frequency/low-intensity harmful workplace experi-
ences were significantly more detrimental to women’s orga-
nizational commitment, job satisfaction, and general health
than low-frequency/high-intensity ones.
Hypothesis 2
Harmful workplace experiences were expected to have a
larger negative impact on the satisfaction with co-workers
and supervisors than on the satisfaction with work tasks. The
relevant results are presented in Table 4. Supporting our
hypothesis, all the harmful workplace experiences had stron-
ger negative associations with co-worker satisfaction and
supervision satisfaction than with work satisfaction.
However, only some of these differences were significant.
Overall, sexual harassment had significantly stronger rela-
tions with both co-worker satisfaction (r
c
¼.24; 95% CI
[.29, .20]) and supervisor satisfaction (r
c
¼.27; 95%
CI [.32, .22]) than with work satisfaction (r
c
¼.14;
95% CI [.20, .07]). The same was observed with fre-
quency of sexual harassment, which had stronger relations
with both co-worker satisfaction (r
c
¼.27; 95% CI
[.31, .22]) and supervisor satisfaction (r
c
¼.27; 95%
CI [.32, .22]) than with work satisfaction (r
c
¼.14;
95% CI [.21, .07]). Low-frequency/high-intensity harm-
ful workplace experiences had a stronger association with
supervision satisfaction (r
c
¼.33; 95% CI [.45, .20])
than with work satisfaction (r
c
¼.15; 95% CI [.17,
.13]); these results mirrored specifically the effect of
unwanted sexual attention. Sexism at work had a stronger
association with co-worker satisfaction (r
c
¼.43; 95% CI
[.52, .34]) than with work satisfaction (r
c
¼.23; 95%
CI [.31, .15]); these results reflected specifically the
results for sexist organizational climate.
Hypothesis 3
It was expected that the relation between high-frequency/low-
intensity harmful workplace experiences and health would be
mediated by work attitudes, whereas the relation of low-fre-
quency/high-intensity experiences with health would be par-
tially mediated by work attitudes and have a direct
association with health. To evaluate this hypothesis, we con-
ducted a path-analysis. The meta-analysis described so far pro-
vided estimates of the associations between two variables
(e.g., summary correlation of OTSH and mental health) but did
not provide a test of a model that includes harmful workplace
experiences, job stress, and occupational well-being. Classic
meta-analytic procedures do not analyze the unique variance
explained by variables in a model. Path analysis was used to
explore how harmful workplace experiences relate to proxi-
mal and distal occupational well-being outcomes after control-
ling for job stress, and to study the relations of the harmful
workplace experiences with the health outcomes, which were
expected to be at least partially mediated by the work attitudes.
Ideally, we would have tested the impact of all the harmful
workplace experiences and job stressors on all the proximal and
distal indicators of well-being. However, the lack of studies
including all these variables meant that we could not test a single
model with all variables in the meta-analysis. A relation was only
included in the model when there were at least two independent
studies evaluating the association between two variables.
Enough data were available to evaluate a model with orga-
nizational commitment, co-worker satisfaction, supervision
Table 2. Descriptive Statistics for the Reliability (as) Distributions.
Variables kMSD
Work harassment 10 .88 .06
Sexual harassment (SH) 43 .86 .08
SH by measurement method
Acknowledged SH 8 1.0 .00
Experience of SH 6 .76 .05
Frequency of SH 33 .85 .07
Frequency by facets
SH 26 .87 .07
Gender harassment 11 .82 .09
Sexual coercion 8 .88 .08
Unwanted sexual attention 10 .84 .08
SH by questionnaire
SEQ 24 .86 .06
No-SEQ 19 .85 .11
Organizational tolerance for SH 13 .89 .07
Sexism at work 11 .85 .08
Sexist discrimination 4 .84 .08
Sexist organizational climate 9 .85 .09
Low-frequency/high-intensity 10 .85 .07
High-frequency/low-intensity 29 .86 .08
Job stress 40 .82 .08
Organizational commitment 20 .84 .06
Job satisfaction 34 .84 .06
Work satisfaction 15 .87 .04
Co-worker satisfaction 18 .86 .05
Supervision satisfaction 17 .89 .04
General health 22 .82 .07
Physical health 14 .79 .11
Mental health 54 .87 .05
Life satisfaction 19 .85 .06
Note. SEQ ¼ Sexual Experiences Questionnaire; k ¼ number of samples.
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satisfaction, and work satisfaction as mediators in the relation
between high-frequency/low-intensity harmful workplace
experiences (i.e., OTSH and gender harassment), low-
frequency/high-intensity harmful workplace experiences
(i.e., sexual coercion and unwanted sexual attention), and job
stressors as predictors with mental health as the outcome (see
Figure 3). The meta-analyzed pairwise correlations matrix
used to test the structural model is in Table 7.
In previous empirical studies using structural equation
modeling, OTSH has been treated as a predictor of sexual
harassment, and not as a direct predictor of work attitudes
or health outcomes (e.g., Fitzgerald,Drasgow,Hulin,Gel-
fand, & Magley, 1997; Glomb et al., 1997). In the introduc-
tion, we argued that the exposure to an organizational
climate that tolerates sexual harassment is in itself a form
of discrimination that violates women’s right to just and
favorable conditions at work (United Nations General
Assembly, 1948) and the right to a life free from violence
(United Nations General Assembly, 1993), which could
have a direct impact on women’s occupational well-being
(Pascoe & Smart Richman, 2009). Following this notion,
we evaluated the association of OTSH, not as a predictor
of sexual harassment, but as a high-frequency/low-intensity
harmful workplace experience that could have a direct det-
rimental effect on women’s work attitudes.
We tested a model in which the association between the
harmful workplace experiences and mental health were
fully mediated by the work attitudes. We then compared the
original model with another model in which the low-fre-
quency/high-intensity experiences (i.e., sexual coercion and
unwanted sexual attention) and job stress were allowed to
directly predict mental health.
The path analysis of the correlation matrix was conducted
using a generalized least square estimator on AMOS 20.0
(Arbuckle, 2011). w
2
p values are only asymptotically correct
with infinitely large samples from perfectly multivariate nor-
mal distributions; this condition might not apply for data
comprised of many samples. The Dw
2
tests for nested models
relies on the same assumptions. Therefore, p values of the w
2
tests should be interpreted with caution. Considering this, we
used a variety of indices to evaluate the fit of the models (Hu
& Bentler, 1998; Jo¨reskog & So¨rbom, 1993): the comparative
fix index (CFI), the adjusted goodness-of-fit index (AGFI),
and the root mean square error of approximation (RMSEA),
along with the standard w
2
statistic. Values of .95 for the CFI
and AGFI, and .05 for the RMSEA, were used as cutoffs
representing a good fit of the data to the model. Structural
equation modeling assumes a constant sample size for all
observed correlations; however, the matrix we used con-
tained different sample sizes for many of the meta-
Table 3. Meta-Analytic Results for the Correlates of Women’s General Work Attitudes.
Organizational Commitment Job Satisfaction
95% CI 95% CI
Variables Kr
c
LUKr
c
LU
Harmful workplace experiences
Work harassment 2 .11 .19 .03 4 .18 .23 .13
Sexual harassment (SH) 13 .13 .18 .08 23 .24 .29 .20
SH by measure method
Acknowledged SH 3 .06 .16 .05 4 .11 .19 .04
Experience of SH 1 .23 .34 .10 6 .23 .29 .17
Frequency of SH 11 .14 .19 .10 13 .30 .37 .23
Frequency by facets
General SH 7 .18 .29 .06 9 .34 .41 .26
Gender harassment 5 .17 .24 .11 4 .26 .38 .14
Sexual coercion 4 .12 .13 .10 2
.15 .18 .13
Unwanted sex attention 5 .15 .20 .10 3 .20 .22 .17
By questionnaire
SEQ 9 .15 .20 .10 7 .23 .28 .18
Non-SEQ 4 .06 .16 .04 16 .25 .33 .17
OTSH 5 .29 .40 .18 6 .27 .32 .21
Sexism at work 5 .24 .33 .15 13 .43 .51 .35
Sexist discrimination 2 .18 .35 .02 8 .43 .56 .29
Sexist org climate 3 .28 .39 .16 8 .47 .56 .37
low-frequency/high-intense 5 .13 .17
.10 3 .18 .20 .15
High-frequency/low-intense 11 .24 .30 .17 21 .36 .41 .31
Job stress 6 .16 .29 .02 15 .29 .40 .17
Note. SEQ ¼ Sexual Experiences Questionnaire; k ¼ number of samples; r
c
¼ corrected mean weighted correlation; Bold ¼ The 95% confidence interval of r
c
does not include zero; OTSH ¼ organizational tolerance for sexual harassment; CI ¼ confidence interval.
a
Q statistic has p < .05.
16 Psychology of Women Quarterly
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analytic correlations. Alternative approaches for handling
this issue are to use the harmonic mean of the sample sizes
(e.g., Colquitt, Scott, & LePine, 2007) or the lowest sample
size (e.g., Carr et al., 2003). We opted for the conservative
approach of using the smallest sample size of 681 partici-
pants. Results using the harmonic mean were not different
in model fit or conclusions drawn.
We first tested the full model shown in Figure 3. Because
of the correlation between work attitudes, the residuals of
these constructs were allowed to freely covary (for similar
approaches, see Carr et al., 2003). This model had a signifi-
cant w
2
test, w
2
(5, N ¼ 681) ¼ 97.6, p < .01, and poor fit
(AGFI ¼ .68, CFI ¼ .88, RMSEA ¼ .17). To evaluate
Hypothesis 3, we tested a revised model adding direct paths
from job stress, sexual coercion, and unwanted sexual atten-
tion to mental health. The changes significantly increased the
model fit, shown by a significantly reduced w
2
, Dw
2
(3, N ¼
681) ¼ 94.14, p < .01. The revised model had a non-
significant w
2
, w
2
(2, N ¼ 681) ¼ 3.47, p ¼ .18, and good fit
indices (AGFI ¼ .97, CFI ¼ .99, RMSEA ¼ .03). Finally,
we tested a revised model removing paths with non-
significant standardized regression coefficients. This final
model, presented in Figure 4, also had a non-significant w
2
,
w
2
(12, N ¼ 681) ¼ 12.5, p ¼ .41, and the fit indices showed
a good model fit (AGFI ¼ .98, CFI ¼ .99, RMSEA ¼ .01).
Even though no significant difference was observed between
the two revised models, Dw
2
(10, N ¼ 681) ¼ 9.03, p ¼ .53,
there was an increase in AGFI and reduction in RMSEA in
this more parsimonious model.
In this final model, gender harassment had a significant
negative association with co-worker satisfaction, and
unwanted sexual attention was negatively related to satisfac-
tion with supervision and work. Job stressors, sexual coer-
cion, and unwanted sexual attention had direct negative
relations with mental health. After allowing for these direct
effects, supervision satisfaction was no longer a significant
predictor of mental health.
3
The effect of gender harassment on mental health was
mediated by co-worker satisfaction, whereas the effect of
OTSH on mental health was mediated by organizational com-
mitment, co-worker satisfaction, and work-satisfaction. Also,
sexual coercion and unwanted sexual attention were directly
linked to mental health. This pattern of results is consistent
with Hypothesis 3. Job stressors and OTSH remained
significant predictors of all the work attitudes, indicating
their independent contribution to occupational well-being
outcomes. The reduced partially mediated model in Figure
4 is a reasonable representation of the population path
model relating women’s experiences of high-frequency/
low-intensity harmful workplace experiences (i.e., OTSH and
Table 4. Meta-Analytic Results for the Correlates of Women’s Specific Work Attitudes.
Variables
Work Satisfaction Co-Worker Satisfaction Supervision Satisfaction
95% CI 95% CI 95% CI
Kr
c
LUKr
c
LUKr
c
LU
Harmful workplace experiences
Work harassment 1 .29 .36 .21 3 .34 .48 .19 3 .45 .62 .24
Sexual harassment (SH) 15 .14 .20 .07 20 .24 .29 .20 18 .27 .32 .22
SH by measure method
Acknowledged SH 2 .07 .16 .01 4 .14 .22 .06 3 .30 .53 .03
Experience of SH 4 .17 .24 .10 3 .21 .31 .10 4 .21 .29 .13
Frequency of SH 12 .14 .21 .07 15 .27 .31 .22 13 .27 .32 .22
Frequency by facets
General SH 9 .13
.25 .02 11 .28 .33 .23 11 .25 .31 .18
Gender harassment 4 .19 .28 .10 5 .28 .40 .15 3 .36 .45 .26
Sexual coercion 2 .12 .15 .10 4 .16 .27 .06 2 .29 .47 .09
Unwanted sex attention 2 .18 .22 .14 4 .21 .32 .10 2 .36 .44 .28
By questionnaire
SEQ 11 .15 .22 .07 13 .26 .31 .21 11 .26 .32 .21
Non-SEQ 4 .13 .20 .07 7 .22
.27 .16 7 .28 .41 .15
OTSH 5 .25 .40 .09 6 .29 .32 .25 6 .35 .45 .26
Sexism at work 3 .23 .31 .15 2 .43 .52 .34 4 .36 .46 .26
Sexist discrimination 2 .29 .39 .19 2 .49 .63 .34 3 .32 .53 .09
Sexist org climate 3 .18 .26 .10 2 .35 .44 .26 4 .35 .49 .21
low-frequency/high-intense 2 .15 .17 .13 4 .19 .29 .08 2 .33
.45 .20
High-frequency/low-intense 10 .23 .32 .13 12 .29 .34 .24 12 .37 .42 .31
Job stress 6 .14 .26 .02 9 .27 .35 .19 9 .34 .39 .28
Note. SEQ ¼ Sexual Experiences Questionnaire; k ¼ number of samples; r ¼ mean weighted correlation; r
c
¼ corrected mean weighted correlation; OTSH ¼
organizational tolerance for sexual harassment; CI ¼ confidence interval.
*The 95% confidence interval does not include zero.
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gender harassment), low-frequency/high-intensity harmful
workplace experiences (i.e., sexual coercion and unwanted
sexual attention), and job stressors with work attitudes and
mental health.
Hypothesis 4
We hypothesized that the impact of harmful workplace
experiences on women’s occupational well-being would be
significant after controlling for other job stressors. The results
of the path-analysis (see Figure 4) indicate that all of the
harmful workplace experiences analyzed were still signifi-
cantly associated with one or more occupational well-being
indicator in a model controlling for job stress. These results
suggest the independent negative contribution that being
exposed to these specific harmful workplace experiences
could have on women’s occupational well-being, apart from
the effect of other common work stressors such as work over-
load, job monotony, or role ambiguity.
Hypothesis 5
It was expected that the association between harmful work-
place experiences and women’s occupational well-being
would be significantly more negative in male-dominated
work environments compared to more gender-balanced work
contexts. To evaluate this hypothesis, we compared samples
of women working in male-dominated environments with
women working in mixed contexts. The subgroup moderation
analyses were conducted only when the Q heterogeneity sta-
tistic was significant (Borenstein et al., 2009) and when the
smallest group had at least four independent samples. The
subgroup method proposed by Hunter and Schmidt (2004)
was used. Separate meta-analyses were conducted for each
subgroup, and moderation was assumed when the 95% CI
of the r
c
of the subgroups did not overlap.
Male-dominated (vs. mixed) work environments did not
significantly moderate the association of sexual harassment
with mental health; in all cases, the CIs across the two con-
texts overlapped (see Table 8). However, all the facets of sex-
ual harassment and both low-frequency/high-intensity and
high-frequency/low-intensity harmful workplace experiences
had stronger negative associations with women’s mental
health when they were working in male-dominated contexts
than for women working in mixed settings.
4
Publication Bias
Because we only used published studies in this meta-analysis,
we explored the potential impact of publication bias on
Table 5. Meta-Analytic Results for the Correlates of Women’s General and Physical Health.
Variables
General Health Physical Health
95% CI 95% CI
Kr
c
LUKr
c
LU
Harmful workplace experiences
Work harassment 3 .15 .22 .08 2 .23 .53 .10
Sexual harassment (SH) 18 .23
a
.29 .16 13 .17 .21 .14
SH by measure method
Acknowledged SH 1 .19 .33 .04 1 .10 .21 .01
Experience of SH 2 .04 .38 .31 4 .15 .21 .09
Frequency of SH 16 .24 .31 .18 9 .18 .22 .14
Frequency by facets
General SH 13 .26 .34 .17 8 .18 .24 .12
Gender harassment 4 .15 .23 .07 1 .20 .22 .17
Sexual coercion 2 .09 .16 .03 1 .17 .19 .14
Unwanted sex attention 2 .13 .16 .11 1 .18 .21 .16
By questionnaire
SEQ 11
.18 .24 .12 8 .16 .19 .13
Non-SEQ 7 .29 .45 .11 5 .23 .33 .13
OTSH 7 .20 .25 .15 3 .12 .25 .01
Sexism at work 3 .20 .37 .03 3 .20 .41 .03
Sexist discrimination 3 .23 .45 .02 2 .38 .48 .28
Sexist org climate 2 .21 .31 .11 3 .14 .30 .02
low-frequency/high-intense 2 .12 .14 .10 1 .18 .20 .15
High-frequency/low-intense 13 .18 .22 .15 6 .19 .26 .10
Job stress 11 .30 .39
.22 8 .26 .36 .15
Note. SEQ ¼ Sexual Experiences Questionnaire;k¼ number of samples; r
c
¼ corrected mean weighted correlation; Bold ¼ The 95% confidence interval of r
c
does not include zero; OTSH ¼ organizational tolerance for sexual harassment; CI ¼ confidence interval.
a
Q statistic has p < .05.
18 Psychology of Women Quarterly
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Table 6. Meta-Analytic Results for the Correlates of Women’s Psychological Well-being.
Variables
Mental Health Life Satisfaction
95% CI 95% CI
Kr
c
LUKr
c
LU
Harmful workplace experiences
Work harassment 10 .37 .48 .25 3 .14 .32 .05
Sexual harassment (SH) 36 .27
a
.31 .23 8 .14 .19 .10
SH by measure method
Acknowledged SH 3 .20 .27 .13 — — — —
Experience of SH 6 .18 .28 .07 — — — —
Frequency of SH 30 .29
a
.33 .24 8 .14 .19 .10
Frequency by facets
General SH 23 .31
a
.37 .25 8 .14 .19 .09
Gender harassment 9 .34
a
.44 .24 1 .10 .18 .01
Sexual coercion 6 .36
a
.51 .19 — — — —
Unwanted sex attention 9 .39
a
.50 .27 — — — —
By questionnaire
SEQ 21 .24 .28 .19 8 .14 .19 .10
Non-SEQ 15 .36 .46 .25 — — — —
OTSH 8 .24 .29 .18 4 .20 .27 .13
Sexism at work 6 .29 .37 .21 — — — —
Sexist discrimination 4 .35 .55 .13 — — — —
Sexist org climate 4 .28 .34 .23 — — — —
low-frequency/high-intense 9 .35
a
.46 .23 — — — —
High-frequency/low-intense 18 .31
a
.35 .26 5 .16 .23 .09
Job stress 30 .34 .41 .27 19 .15 .22 .08
Note. Dashes indicate that data were not available. SEQ ¼ Sexual Experiences Questionnaire. k ¼ number of samples; r
c
¼ corrected mean weighted
correlation; Bold ¼ The 95% confidence interval of r
c
does not include zero; OTSH ¼ organizational tolerance for sexual harassment; CI ¼ confidence interval.
a
Q statistic has p < .05.
Gender
harassment
OTSH
Sexual coercion
Unwanted sex.
attention
Work
satisfaction
Co-worker
satisfaction
Organisational
commitment
Mental health
.61*
.84*
.17*
.15*
.21*
.11*
.12*
.32*
.35*
.25*
.32*
.26*
.54*
Job stress
.00
.44*
.83*
-.04
.28*
.14*
.18*
-.06
-.20*
.08
-12
-.02
.05
-.46*
-.13
-.03
-.25*
.00
.08
-.12*
-.33*
-.24*
-.13*
-.24*
-.18*
-.26*
-.16*
Supervision
satisfaction
Figure 3. Fully mediated model with standardized regression weights. OTSH ¼ organizational tolerance for sexual harassment. w
2
(5, N ¼
681) ¼ 97.6, p < .01; AGFI ¼ .68, CFI ¼ .88, RMSEA ¼ .17; *standardized regression coefficients are significant at p < .05.
Sojo et al. 19
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Table 7. Meta-Analytic Matrix Used in the Path Analysis.
Job Stress OTSH
Gender
Harassment Sexual Coercion
Unwanted Sexual
Attention
Organisational
Commitment
Co-Worker
Satisfaction
Supervision
Satisfaction
Work
Satisfaction
OTSH .21 (.10, .30)
(.18, 5)
Gender harassment .22 (.16, .27) .46 (.34, .57)
(.18, 3) (.39, 3)
Sexual coercion .07 (.02, .13) .20 (.02, .36) .65 (.50, .78)
(.06, 2) (.17, 3) (.55, 9)
Unwanted sexual attention .11 (.04, .26) .30 (.13, .47) .85 (.75, .92) .86 (.73, .94)
(.09, 2) (.26, 3) (.70, 10) (.74, 9)
Organizational commitment .16 (.29, .02) .29 (.40, .18) .17 (.24, .11) .12 (.13, .10) .15 (.20, .10)
(.13, 6) (.25, 5) (.14, 5) (.10, 4) (.13, 5)
Co-worker satisfaction .27 (.35, .19)
.29 (.32, .25) .28 (.40, .15) .16 (.27, .06) .21 (.32, .10) .40 (.30, .40)
(.23, 9) (.25, 6) (.23, 5) (.14, 4) (.18, 4) (.34, 6)
Supervision satisfaction .34 (.39, .28) .35 (.45, .26) .36 (.45, .26) .29 (.47, .09) .36 (.44, .28) .36 (.15, .55) .48 (.40, .56)
(.29, 9) (.32, 6) (.30, 3) (.25, 2) (.31, 2) (.31, 6) (.42, 16)
Work satisfaction .14 (.26, .02) .25
(.40, .09) .19 (.28, .10) .12 (.15, .10) .18 (.22, .14) .58 (.35, .77) .39 (.35, .43) .37 (.22, .50)
(.12, 6) (.22, 5) (.16, 4) (.11, 2) (.15, 2) (.50, 5) (.34, 14) (.32, 13)
Mental health .34 (.41, .27) .24 (.29, .18) .34 (.44, .24) .36 (.51, .19) .39 (.50, .27) .27 (.17, .37) .30 (.25, .34) .32 (.25, .39) .28 (.20, .35)
(.28, 30) (.21, 8) (.29, 9) (.31, 6) (.33, 9) (.23, 10) (.25, 14) (.28, 13) (.24, 11)
Note. Mean corrected correlations (r
c
) are italicized. Values in parenthesis following r
c
indicate the lower and upper bound of the 95% CI of the r
c
. Values in parenthesis below indicate r (uncorrected mean correlation)
and k (number of studies). OTSH ¼ organizational tolerance for sexual harassment.
20
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summary correlations that were based on three or more stud-
ies. To analyze bias, we computed Egger’s regression inter-
cept. The inverse of the standard error (i.e., an indicator of
study precision) was used to predict the standardized effect
(i.e., effect size divided by the standard error). Publication
bias is inferred when the intercept of this equation is signifi-
cant (Borenstein et al., 2009). The trim and fill approach was
used to analyze symmetry in the funnel plot (i.e., graphic rep-
resentation of the standard errors and effect sizes in each
summary effect). When asymmetry was observed, the
method estimated the missing effect sizes necessary to make
the plot symmetric, and added the imputed effects to recalcu-
late the summary effects (Duval & Tweedie, 2000). Finally,
we used the classic fail-safe N (i.e., file-drawer analysis) to
compute the number of studies necessary to nullify the
observed significant summary effects (Borenstein et al.,
2009).
Table S2 in Online Supplements presents the extended
results. Only three significant summary effects might be
inflated by the exclusion of null studies: The correlation of
work harassment and general health (r ¼.13, p < .01) had
a fail-safe N of 10, the summary effect of non-SEQ measures
with work satisfaction (r ¼.12, p < .01) had a fail-safe N
of 9, and the correlation of sexism at work with general health
(r ¼.17, p < .01) had a fail-safe N of 10. However, the
Egger’s regression intercepts and the trim and fill results for
these three effects did not indicate publication bias. Changes
to mitigate potential publication bias do not affect the inter-
pretation of the results of the meta-analysis. These analyses
indicate that it is unlikely unpublished data would change the
results or should be of concern.
Summary of Findings
The results of this meta-analysis led to several conclusions.
High-frequency/low-intensity harmful workplace experiences
(i.e., sexist discrimination, sexist organizational climate,
OTSH, and gender harassment) appeared as detrimental for
women’s occupational well-being as low-frequency/high-
intensity harmful workplace experiences (i.e., sexual coercion
and unwanted sexual attention). Similarly, the harmful work-
place experiences were as detrimental for women’s occupa-
tional well-being as the job stressors. The harmful workplace
experiences were still significant predictors of women’s occu-
pational well-being after controlling for job stress.
Sexist discrimination and sexist organizational climate had
negative and small to medium associations with both proximal
and distal indicators of women’s occupational well-being.
Frequency-based measures of sexual harassment had stronger
correlations with well-being than acknowledgment- or
experience-based measures. However, those differences were
only significant for job satisfaction. No significant difference
or clear pattern was observed in the association of SEQ and non-
SEQ measures with the health indicators. Harmful workplace
experiences were consistently more strongly related to
assessments of interpersonal relationships at work (i.e., satisfac-
tion with co-workers and supervisors) than with the tasks (i.e.,
work satisfaction). These differences were significant for low-
frequency/high-intensity harmful workplace experiences, and
in particular for overall sexual harassment, frequency of sexual
harassment, unwanted sexual attention, sexism at work, and
sexist organizational climate.
A key result was that the association between high-
frequency/low-intensity harmful workplace experiences
(i.e., OTSH and gender harassment) and mental health was
mediated by work attitudes. On the other hand, the relation
of low-frequency/high-intensity experiences (i.e., unwanted
sexual attention and sexual coercion) with mental health was
partially mediated by the work attitudes and had a direct asso-
ciation with mental health.
The moderation analysis indicated that male dominance in
the work context did not significantly moderate the associa-
tion of the harmful workplace experiences and women’s
health. However, the results show a trend of larger negative
effects of the harmful experiences in male-dominated con-
texts. Finally, the publication bias analysis supports the
robustness of the results of this study.
Discussion
Harmful workplace experiences come from a range of sources
and take many different forms. For women, harmful work-
place experiences can add to the pressures from general stres-
sors and demands. Women are more likely than men to be
targets of sexual harassment and discrimination (Schmitt
et al., 2002), and the adverse impact of these behaviors appear
greater in male-dominated work contexts (O’Connell & Kor-
abik, 2000) and when sexism is widely accepted as the norm
(Settles et al., 2006).
Two of the questions we sought to address through the
meta-analysis were ‘‘across the different harmful experiences
and job stressors, which have the most pronounced negative
effects on women’s work attitudes and health?’’ and ‘‘how
did the different harmful workplace experiences impact on
women?’’ All of the harmful workplace experiences and job
stressors had negative relations with the full range of attitudi-
nal and health measures for women. Harmful experiences that
are specifically targeted at an individual, including general
harassment, sexual harassment, and sexist discrimination,
were negatively related to all measures of women’s work atti-
tudes and health. The two assessments of potentially harmful
contexts, OTSH and a sexist organizational climate, also had
negative effects across the full range of attitudinal measures
and all health indicators except physical health.
High-frequency/low-intensity Harmful Workplace
Experiences Affect Well-being
Consistent with Hypothesis 1, there were few significant dif-
ferences in the effect sizes for the relations of different
Sojo et al. 21
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harmful workplace experiences with work attitude and
health outcomes. Where we observed differences, the less
intense/more frequent harmful workplace experiences had
larger negative associations with women’s work attitudes,
compared with harmful workplace experiences, such as sex-
ual coercion or unwanted sexual attention; these harmful
experiences were previously considered to be more severe
(Hershcovis & Barling, 2010). This finding points to an
important distinction for researchers and managers who
wish to understand and reduce the negative impacts of harm-
ful events on women’s experiences of work and on their
mental health. Sexual coercion and unwanted sexual atten-
tion are traumatic for the people involved, and more likely
to result in court cases and public reporting. However, in
many work settings, these intense experiences are low-fre-
quency events. Norms, leadership, or policies that reduce
intense harmful experiences may lead managers to believe
that they have solved the problem of maltreatment of
women in the workplace. However,themorefrequent,less
intense, and often unchallenged gender harassment, sexist
discrimination, sexist organizational climate, and OTSH
appeared at least as detrimental for women’s well-being.
They should not be considered lesser forms of sexism.
Frequency-based measures of sexual harassment were
more strongly related to indicators of occupational well-being
than any other method of measurement, though these differ-
ences were only significant for job satisfaction and co-worker
satisfaction. It is the frequency of exposure to gendered and
sexualized maltreatment, and not the acknowledgment of
interpersonal encounters as sexual harassment, that more
strongly undermines women’s occupational well-being.
While the type of measure might make a difference to the
outcomes observed, the specific measurement tools used did
not. As found in Willness et al.’s (2007) meta-analysis of sex-
ual harassment with mixed gender samples, no difference was
observed in the comparisons of the association of SEQ versus
non-SEQ measures of sexual harassment with the well-being
outcomes.
Harmful Workplace Experiences Affect Specific Work
Attitudes
As outlined in Hypothesis 2, work harassment, sexual harass-
ment, and sexism at work were more strongly related to dis-
satisfaction with supervisors and co-workers than with work.
Even though victims of harassment were more dissatisfied
with their supervisor than with their co-workers (which may
be due to supervisors being more common sources of mal-
treatment or because they are more likely to be considered
responsible), this difference was not significant. This result
contrasts with Willness et al.’s (2007) meta-analysis that
included samples of men and women and found that sexual
harassment was more strongly related to dissatisfaction with
co-workers than with supervisors.
We were unable to assess how the source of harassment
(e.g., supervisor vs. co-workers) affected well-being, as we
found only two studies that differentiated between harass-
ment by workers above or at the same level of the targets
Gender
harassment
OTSH
Sexual coercion
Unwanted sex.
attention
Work
satisfaction
Supervision
satisfaction
Organisational
commitment
Mental health
.65*
.86*
.20*
.10*
.09*
.33*
.38*
.26*
.33*
.27*
.54*
Job stress
.11*
.46*
.85*
.07*
.31*
.22*
.21*
-.21*
-.26*
-.08*
-.09*
-.27*
-.20*
-.10*
-.22*
-.18*
-.27*
-.15*
Co-worker
satisfaction
-.26*
-.15*
-.19*
.09*
Figure 4. Partially mediated model with standardized regression weights. OTSH ¼ organizational tolerance for sexual harassment. w
2
(12,
N ¼ 681) ¼ 12.5, p ¼ .41; AGFI ¼ .98, CFI ¼ .99, RMSEA ¼ .01; *standardized regression coefficients are significant at p < .05.
22 Psychology of Women Quarterly
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(i.e., Morrow, McElroy, & Phillips, 1994; O’Connell & Kor-
abik, 2000). The gender and status of the perpetrator and the
target of abuse, and the status differential between them
might interact to affect the prevalence, interpretation, attribu-
tions, and impact of different forms of harmful workplace
experiences. For example, an issue that is rarely studied is
sexual harassment from clients or customers (see Gettman
& Gelfand, 2007), which might happen in many occupational
sectors, such as legal and medical services. More research in
these areas could help to clarify the disparity in the results of
the current study and Willness et al.’s (2007) meta-analysis.
Work Attitudes Mediate Mental Health and Harmful
Workplace Experiences
Hypothesis 3 tested the potential mediating role of work atti-
tudes in the relation between different kinds of harmful work-
place experiences and health. While physical health and
satisfaction with life are important well-being outcomes,
there have not been enough studies completed to allow us
to include these health indicators in our mediation analysis.
Available data for the path analysis only allowed us to test the
effects for one well-being distal indicator, mental health,
which is arguably one of the most severe and costly outcomes
for individuals, their social groups, organizations, and society
(Doran, 2013; Insel, 2011; Knapp, 2003). The less frequent
and more intense forms of harassment (i.e., sexual coercion
and unwanted sexual attention) had a direct independent rela-
tion with mental health. However, more frequent and less
intense harassment, OTSH and gender harassment, both of
which are markers of a work environment that is hostile
towards women, were only related to mental health through
the mediating pathway of the work attitudes. In the final
model, gender harassment was related to dissatisfaction with
co-workers, while unwanted sexual attention was associated
with supervisor dissatisfaction. Consistent with these results,
O’Connell and Korabik (2000) explained that women might
be exposed to more hostile gender harassment from co-
workers of the same organizational status who perceive them
as a threat, whereas women of lower status might be exposed
to more unwanted sexual attention from workers with higher
status (e.g., supervisors). The current results might reflect
women’s negative reactions to the specific perpetrators of
each form of harassment. The complex relation between
forms of harassment and status of the target and perpetrator
requires further study.
OTSH was a significant predictor of all the work attitudes
after controlling for sexual harassment and job stressors.
These results again highlight that an organizational climate
that is permissive of sexual harassment could have a negative
effect on women’s work attitudes, independent of the effect
of actual sexual harassment and job stressors. As previously
noted, when low-intensity, yet widespread and normalized,
sexism is part of the organizational climate, the organization-
wide impacts are potentially much larger, but less obvious,
than the impacts of isolated incidences of more intense forms
of harmful workplace experiences.
Job Stressors Don’t Explain Effects of Harmful
Workplace Experiences
Compared to job stressors, the harmful workplace experi-
ences analyzed in the current study are at least as detrimental
for women’s health and work attitudes. The path analysis also
provided useful insights about the independent effects of dif-
ferent harmful experiences and job stressors on work attitudes
and mental health. Following Hypothesis 4, the harmful
workplace experiences were still significantly associated
with the work attitudes and mental health after controlling for
job stressors. For women, the understanding of job stressors
will be incomplete without consideration of the impacts of
harmful workplace experiences, which draw on the same set
of individual resources for coping. Given that gender discrim-
ination, sexist organizational climates, and other harmful
experiences may influence the allocation of work and control
over work, focusing on job stressors without consideration of
Table 8. Moderation Analysis for Occupational Contexts.
Variables Context kr r
c
95% CI
LH
General Health
Sexual harassment (SH)
General 11 .22 .27
a
.40 .13
Male-dominated 7 .14 .17
a
.25 .09
Mental health
Sexual harassment (SH)
General 17 .20 .24
a
.30 .17
Male-dominated 19 .27 .31
a
.36 .26
Frequency of SH
General 15 .21 .25
a
.32 .18
Male-dominated 15 .28 .32
a
.38 .27
Frequency of General SH
General 11 .21 .25
a
.34 .15
Male-dominated 12 .30 .35
a
.43 .26
Gender harassment
General 5 .21 .25
a
.37 .12
Male-dominated 4 .42 .50
a
.71 .24
Unwanted sexual attention
General 5 .23 .26
a
.37 .15
Male-dominated 4 .48 .57
a
.82 .21
Low-frequency/high-intensity
General 5 .20 .23
a
.34 .12
Male-dominated 4 .45 .53
a
.78 .19
High-frequency/low-intensity
General 9 .22 .25
a
.33 .18
Male-dominated 9 .32 .37
a
.43 .30
Note. k ¼ number of samples; r ¼ mean weighted correlation; r
c
¼ corrected
mean weighted correlation; L ¼ Lower limit; H ¼ Higher limit.
a
The 95% confidence interval does not include zero.
Sojo et al. 23
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harmful workplace experiences studied here may be to ignore
the root causes of well-being outcomes.
Male-dominated Work Environments May Not Be
More Harmful to Women
In terms of Hypothesis 5, sexual harassment appeared to have
a more negative effect on women in male-dominated work
environments than in more gender-balanced contexts. How-
ever, these differences were non-significant. Given the post
hoc nature of the classification conducted in this meta-
analysis between male-dominated and gender-balanced work
environments, future research should investigate these issues
further to directly compare the frequency of occurrence and
impact of different harmful experiences and the actions to
manage them in relation to the numerical and normative male
dominance of the work contexts and the status of the targets.
Future Research
In the discussion, we indicated several areas for future
research that were relevant to the specific results presented.
In this section, we will add to those suggestions. With few
exceptions (e.g., Rospenda et al., 2006), most of the research
conducted about harmful workplace experiences is cross-
sectional and based on self-report measures, making it diffi-
cult to draw conclusions about causal pathways. For instance,
it is possible that women who have voiced their discontent
with their supervisor or co-workers might become targets
of harassment. Feelings of helplessness might impair
women’s capacity to speak up or seek help and may lead them
to remain in a risky situation. The lack of longitudinal
research limits the possibility to test such alternative expl-
anations to the associations observed in this meta-analysis.
The few longitudinal studies conducted have found discrim-
ination to predict mental health problems but not the other
way around (Brown et al., 2000; Pavalko, Mossakowski, &
Hamilton, 2003). Longitudinal studies need to include other
reactions to harmful workplace experiences, such as work
and job withdrawal and the targets’ self-evaluations. Women
leave male-dominated work environments at a higher rate
than more balanced work environments (Miner-Rubino &
Cortina, 2007). Withdrawal is most likely a common response
to harassment and sexist work climates, but one that is not
properly captured in cross-sectional studies.
The study of sexual harassment and gender-based dis-
crimination would also benefit from more precision in the
conceptualization and measurement of the constructs. Three
additional distinctions seem necessary. First, unwanted sex-
ual attention should be measured as a separate construct from
sexual assault, as they could have different impacts on both
mental and physical health (Gruber et al., 1996). Second,
measures of gender harassment should distinguish between
both sexist (e.g., co-worker being condescending because
of your gender) and sexual hostility (e.g., co-worker trying
to draw you into a discussion about your sexual life), as done
by Fitzgerald, Magley, Drasgow, and Waldo (1999). Sexist
gender harassment might have a different effect on women’s
work attitudes, health, and other outcomes compared to
sexualized gender harassment; they may also be used by the
perpetrators with different intentions. Gender harassment can
be expressed in many ways (Leskinen & Cortina, 2014), such
as questioning women’s capacity to do their job, questioning
the level of femininity/masculinity of women’s behavior,
using sexual language and images with sexual content, or
judging women’s management of work–home roles. These
forms of harassment are worth exploring to identify their
impacts and for the crafting of effective interventions.
Third, measures of gender harassment should distinguish
how sexism at work is labeled and operationalized. Some
studies used the same label, such as sexist climate or climate
perceptions (Miner-Rubino et al., 2009) to talk about two
different dimensions of sexism: personal experiences of dis-
crimination because of one’s gender versus experiences of
a work environment that devalues women in general (Settles
et al., 2006). That distinction in conceptualization and mea-
surement should be made clear in future studies.
Our study was also limited by the number and nature of
existing studies. We were not able to analyze in a single
model a broad range of harmful workplace experiences
versus other work and personal stressors, due to the lack of
studies addressing the relation between these variables. Ros-
penda, Richman, and Shannon (2009) have indicated the need
for more studies in which the effect of harmful workplace
experiences on well-being is compared to the effect of per-
sonal factors (e.g., family violence and family demands), or
personal/work life interactions (e.g., work–family conflict)
using the same outcomes. Similarly, the associations between
personal stressors and harmful workplace experiences require
further study.
It is particularly important to conduct more studies about
thespecificgender-based harmful workplace experiences
affecting men and members of groups who are often targets
of gender-based discrimination and harassment, such as les-
bian, gay, bisexual, transgender and intersex (LGBTI) indi-
viduals (Ryan & Rivers, 2003). The vast majority of the
measures of gender-based and sexualized harmful work-
place experiences were developed thinking of women as the
targets (e.g., Bergman, 2003; Fitzgerald et al., 1995; Gruber,
1998). These measures might not encompass the diverse
range of harmful experiences that men or members of the
LGBTI communities are exposed to. The development of
relevant measures of these experiences and the study of their
impact on the occupational well-being of the mentioned
groups requires further research (Hershcovis & Barling,
2010; Willness et al., 2007).
Our moderator analysis was restricted by the small number
of studies reporting relevant information. For instance, the
race of the target is an important moderator to consider
(Buchanan, Settles, & Woods, 2008), but few studies of race
24 Psychology of Women Quarterly
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of target exist. Finally, the inclusion of moderators in future
studies should be guided by theory to avoid capitalizing on
chance (Hunter & Schmidt, 2004).
Practice Implications
The current study has potential to correct a number of mis-
conceptions about the experience of women in the workplace.
First, individuals commonly fail to recognize several abusive
behaviors as sexual harassment (AHRC, 2008; Rospenda
et al., 2009). Also, people do not always recognize the poten-
tial harm and think it is sometimes acceptable to engage in
different forms of sexism at work (Powell, 2012). If
individuals do not acknowledge these interactions as abusive,
and do not think they are harmful, it is unlikely they will
complain and unlikely that corrective actions will be taken
(Riger, 1991; Summers, 1996). The information from this
meta-analysis could be presented in educational programs
(e.g., in schools, universities, sport clubs, and businesses) to
reduce the variety of harmful workplace experiences women
are exposed to and to mitigate the consequences of these
harmful experiences on their well-being.
Large organizations typically have policies to manage
overt forms of gender-based hostility at work. However,
women still fear retaliation if they complain (Murrell et al.,
1995). Educating workers about the consequences of these
events will be fruitless if there are no formal policies and
practices to manage complaints. Individuals tasked with
responding to complaints should have the technical skills and
independence necessary to act without having their positions,
and that of the targets of abuse, compromised. Making this
possible will require allocation of funds for training and
changes in relevant organizational reporting structures.
For policy makers and practitioners, covert sexism (e.g.,
sexist jokes, ignoring women during meetings, and talking
behind women’s backs) is one of the most challenging issues
to tackle. Our results suggest that organizations should have
zero tolerance for low-intensity sexism, the same way they
do for overt harassment. This will require teaching workers
about the harmful nature of low-intensity sexist events, not
only for women but also for the overall organizational cli-
mate. The promotion of civilized interactions among col-
leagues is essential.
A more active approach is to train workers in bystander
intervention (Powell, 2012). The results of this study can be
used to develop training programs about how to identify sex-
ist events, highlight why they are problematic, emphasize
their potential consequences, and propose alternative beha-
viors. This kind of training program should be directed to
middle and upper managers.
The results of this meta-analysis indicate that women who
are targets of harmful workplace experiences are more dissa-
tisfied with their supervisors than with co-workers. Supervi-
sors have the main responsibility to set the standards of
expected and acceptable behaviors in organizations and to
advocate for and protect the personnel under their leadership.
Supervisors need to be among the first to learn about and act
on our results; middle managers, who are in direct contact
with most personnel and are expected to be upper managers
in the future, play a critical role in changing harmful work-
place behaviors.
Finally, the harmful impact of gender-based discrimina-
tion does not stop at hindering women’s career progression.
This meta-analysis shows that discrimination also has a neg-
ative effect on women’s work attitudes and health. It is nec-
essary to identify, analyze, and change organizational gender
bias ‘‘hot spots.’’ These are decision-making events where
resources and opportunities are allocated in a way that discri-
minates against women. For instance, women might get pena-
lized in performance evaluations, promotion decisions, and
allocation of important projects, among others, sometimes
due to unconscious biases and lack of formalized processes
(Dunlea et al., 2015; Genat et al., 2012). This kind of analysis,
coupled with training and compensatory strategies for better
decision making, may reduce the bias against women.
Conclusions
Hostile work environments and individual experiences of
hostility at work have negative effects on women’s occupa-
tional well-being. More frequent though less intense harmful
workplace experiences can impair women’s occupational
well-being as much as less frequent yet more intense experi-
ences. Distinctions among harmful workplace experiences
based on severity should be avoided. Such distinctions may
perpetuate the view that some harmful workplace experiences
(e.g., sexist jokes and remarks, ignoring women during meet-
ings) have a lesser impact; they are in fact as detrimental as
other well-recognized forms of mistreatment at work.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, author-
ship, and/or publication of this article.
Notes
1. The references of the meta-analyzed studies are in Table S1 in the
Supplemental materials.
2. Definitions of coding fields and all data coded are in Table S1 in
the Supplemental materials.
3. To evaluate the robustness of these results, we also conducted the
same set of analyses, this time excluding job stress from the
model. The same pattern of results and the level of significance
of associations were observed in these models. The only excep-
tion was that in the final model excluding job stress, supervision
satisfaction was still a significant predictor of mental health,
however, with a b ¼ .09, p ¼ .04.
Sojo et al. 25
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4. The percentage of managers in the sample was also evaluated for
a potential moderating role. However, this variable did not mod-
erate the relation between sexual harassment and mental health or
general health.
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