Organizational climate of hostility and support toward LGTBI+ employees: meta-analysis and gender identity as a moderating variable

Abstract

Introduction:

Supportive and hostile workplace climates are relevant to understanding the work experiences of LGTBI+ employees.

Method:

A meta-analysis was carried out to examine the associations between supportive and hostile workplace climates and work-related psychosocial outcomes, psychological variables (individual-level mental health) and identity management variables.

Results:

Supportive climate has positive effect sizes with disclosure and job satisfaction. It also has negative effect sizes with discrimination, distress and covering. Hostile climate is linked to higher distress and covering, and with lower disclosure and job satisfaction.

Conclusion:

Hostility and support are associated with psychosocial, identity management and psychological variables among LGTBI+ employees.

1 Introduction

Lesbian, Gay, Bisexual, Trans, Intersex and Queer (LGTBI+) employees are exposed to multiple environmental conditioning factors that shape their life and work experience. Firstly, like all employees, they are confronted with experiential and life background conditions related to their socio-economic situation. Additionally, despite the huge progress in recent years toward the consolidation of the rights and freedoms of LGTBI+ people (International Lesbian Gay Bisexual Trans and Intersex Association, 2020; Muñoz, 2019), high levels of workplace hostility persist (Di Marco et al., 2018; European Union Agency for Fundamental Right, 2015). As a result, LGTBI+ employees often face additional stress arising from the discrimination to which they are exposed on the basis of their sexual orientation and gender identity. This additional stress is associated with higher levels of physical illness, mental health problems and suicide attempts (Flentje et al., 2020; Meyer, 2003; Miranda-Mendizábal et al., 2017; Poteat et al., 2021).

In this context, LGTBI+ employees who experience discriminatory behavior make use of their coping resources to buffer and/or diminish the negative outcomes of hostility. The most effective strategies are related to their own coping skills and to supportive networks and contexts (Meyer, 2003). Thus, perceived discrimination is attenuated by the social support received, which critically reduces the negative psychosocial and psychological outcomes for LGTBI+ employees.

In relation to the above, the analysis of the organizational climate of LGTBI+ employees in its double dimension is of special scientific and social relevance: on the one hand, the hostile workplace climate (as a stressor) and on the other, the supportive workplace climate (as a buffer against possible stressors).

Despite the large number of existing primary studies assessing discrimination or support toward LGTBI+ employees, there is no meta-analytical review that collects and compares the associations of hostile and supportive workplace climates on LGTBI+ employees and their relationship with psychological, psychosocial and LGTBI+ identity management variables.

To fill this gap, this meta-analysis aims to collect and analyze all available scientific evidence on the associations of hostility (operationalized as hostile workplace climate) and support (operationalized as supportive workplace climate) with psychosocial, identity management outcomes and psychological variables among LGBTI+ employees.

1.1 Supportive and hostility workplace climate

An organizational climate of support for LGTBI+ employees is a construct that captures LGTBI+ employees' perceptions of supportive behaviors of colleagues, organization and/or superiors in their workplace environment (Liddle et al., 2004). It has been frequently related to measures of decent work (Allan et al., 2019), high levels of job and life satisfaction (Allan et al., 2015), lower levels of anxiety in high-demand environments (Goldberg and Smith, 2013), better person-organization, person-job fit (Velez and Moradi, 2012) and a greater tendency to talk about one's LGTBI+ identity at work (Reed and Leuty, 2016; Tatum et al., 2017).

In the beginning, research related to the work experiences of LGTBI+ people focused on collecting and analyzing the hostile and discriminatory aspect (Webster et al., 2017). Later, research shifted its focus to the supportive workplace climate. A significant advance in this direction was the creation of the LGBTCI scale (Liddle et al., 2004). The LGBTCI is based on a conception of support and hostility as a continuum, such that the absence of one determines the presence of the other. In relation to this, significant discussion has emerged in recent years on the concept of a supportive workplace climate for LGTBI+ employees and its relationship with hostile workplace climates (Holman et al., 2019; Rivero-Díaz et al., 2021). In this sense, supportive workplace climates toward LGTBI+ employees are not considered equivalent to non-hostile workplace climates and vice versa. A low score on the discrimination perceptions scales does not imply a supportive and inclusive climate. Both constructs have been moderately correlated in the literature reviewed (Liddle et al., 2004) and need to be analyzed independently: although complementary, they are different constructs and are at different levels of analysis (Holman et al., 2019; Rivero-Díaz et al., 2021).

Therefore, this meta-analysis will analyze (1) the relationships established between the supportive workplace climate and psychosocial, psychological and LGTBI+ identity management variables; (2) the relationships established between the hostile workplace climate and psychosocial, psychological and LGTBI+ identity management variables.

1.2 Intersectionality

In addition to the distinction between support and discrimination, it is essential to bear in mind that these discriminatory situations and their outcomes are intensified or reduced by the different intersections of gender, sexual orientation and gender identity among LGTBI+ employees.

Sexual orientation is a determining factor. In their work environment, bisexual people face different challenges than gays and lesbians (Arena and Jones, 2017; Pichler and Ruggs, 2018). Bisexual employees who are open about their sexual orientation are still at risk of being wrongly categorized as heterosexual or homosexual by their colleagues. This leads to greater dissonance between disclosing or not disclosing their sexual orientation in future interactions (Arena and Jones, 2017). Not even bisexual men and women face the same problems: bisexual men are more discriminated against in their work environment, are less open and have higher rates of substance abuse and psychological distress compared to bisexual women (Corrington et al., 2019). Moreover, it is not only heterosexual colleagues who have discriminatory attitudes toward bisexual employees. Also, gays and lesbians (Arena and Jones, 2017). As a result, they suffer from more physical illnesses, greater psychological distress and are less open about their sexual orientation at work than lesbians and gays (Arena and Jones, 2017).

The analysis of the effect of gender identity is particularly important. Transgender employees face additional difficulties to their LGB colleagues: gender identity, unlike sexual orientation, is visible to others without needing to be voluntarily expressed (Sawyer et al., 2016). For example, in Spain 60% of transgender people were discriminated against when seeking a job (Muñoz, 2019) and 38% during the previous year [European Union Agency for Fundamental Rights (FRA), (2020)]. Thirty-four percentage of transgender people had felt discriminated against in the workplace, much higher than lesbians (18%), gays (17%), and bisexuals [19% women and 22% men; European Union Agency for Fundamental Rights (FRA), (2020)]. In addition, trans employees have difficulty in keeping their jobs during the reassignment process and have many more problems in renewing their contracts [Comisiones Obreras (CCOO) and Federación Estatal de Lesbianas Gais Trans y Bisexuales (FELGTB), 2016].

Looking at other regions, specifically the Global South, reveals a more complex picture. According to (International Lesbian Gay Bisexual Trans Intersex Association, 2026; International Lesbian, 2026), up to 63 UN member states still criminalize homosexual acts by law, including Saudi Arabia, Guyana, Mauritania, Mali, and Malaysia, among many others. A cross-continental analysis indicates that in the Americas, up to five UN member states criminalize homosexual acts, in Oceania 6, in Asia 21, and in Africa up to 33. Regarding protection against discrimination in employment, Europe has the highest percentage of UN member states with legislation against discrimination in employment (81%), followed by Oceania at 57%, the Americas at 51%, Africa at 19%, and Asia as the least protected with only 7%. Workplace discrimination against LGBTI+ employees is not sufficiently studied in non-Western contexts. A review of some studies also indicates that differences exist between regions. Punnakitikashem et al. (2019) in the context of Thailand, showed differences regarding the effect of supervisory support in non-Western contexts. In Africa, there are also sociocultural and political factors that require context-specific responses to reduce discrimination in the workplace (Ramelepe and Asamani, 2024). Significant gaps are also found between protective legislation, where it exists, and actual discriminatory practices (Luiz and Terziev, 2022), and workplace discrimination persists in sectors such as education and mining, among others (Ramelepe and Asamani, 2024). This discrepancy between regulations and discrimination also occurs in European Union countries such as Greece (Drydakis, 2009).

In short, the study of work experiences must reflect the diversity of LGTBI+ employees in order to be able to analyze in depth the discriminatory processes and the possible effective interventions that can be developed in the workplace.

1.3 This study

The general objective of this study was to analyze the relationships between supportive workplace climates and climates of hostility toward LGTBI+ employees and three broad groups of outcomes: work-related psychosocial variables, psychological health outcomes and LGTBI+ identity management variables.

The selection of these outcomes was based on theoretical and empirical criteria. They included variables that represent central dimensions of the workplace experiences of LGTBI+ employees.

On the one hand, the Psychology of Working Theory (Duffy et al., 2016) provides a useful framework for understanding how marginalization and stigmatization, along with structural limitations, affect the possibility of accessing and/or maintaining decent employment. Applied to this context, it indicates that employed LGTBI+ individuals, due to their stigmatized characteristics, may face greater barriers to securing decent employment. In this sense, variables such as job insecurity and intentions to leave employment are relevant because of their ability to describe the degree of job retention. On the other hand, Minority Stress Theory (Meyer, 2003) offers a theoretical framework to explain how stressors associated with stigma, including workplace discrimination against LGTBI+ people, are linked to variables that deteriorate mental health. From this perspective, hostile work environments act as stressors that contribute to psychological distress and other negative psychological situations. Conversely, supportive work environments can reduce exposure to these stressors, as well as mitigate their associations.

Furthermore, the management of LGTBI+ identity is fundamental to this analysis, since decisions regarding disclosure, concealment, and openness concerning sexual orientation or gender identity are influenced by the work climate and can influence the relationships between climate and other psychosocial or psychological variables.

Thus, the analysis is organized around large groups of variables with theoretical significance. These include psychosocial variables, psychological variables, variables related to the degree of openness and the process of concealing sexual orientation and/or gender identity, and variables related to job satisfaction. In this study, psychosocial variables refer to work-related and social-contextual indicators that arise from the interaction between LGTBI+ employees and the organizational context. On the positive side (positive psychosocial variables), these include the fit between the individual and their work environment, constituting variables related to job retention. On the other hand, negative psychosocial variables also refer to the interaction with the work environment but are related to the likelihood of the employee leaving the company (such as job insecurity or intentions to quit).

This grouping into broader constructs allows us to observe how supportive and hostile workplace climates are associated with key dimensions of LGTBI+ employees' workplace experiences, including their work-related adjustment, mental health, identity management strategies and likelihood of remaining in or leaving their current employment.

The general objective can be operationalized in several more specific objectives. To avoid repetition, Table 1 summarizes the specific objectives, the outcome analyzed and the expected direction of the associations.

These hypotheses were based on empirical evidence. In relation to specific objective 1, a supportive climate toward LGTBI+ employees has been related to high job satisfaction (Allan et al., 2015; Liddle et al., 2004; Wood, 2020) support from supervisors (Huffman et al., 2008) and better person-organization and person-employment fit (Rivero-Díaz et al., 2021; Velez and Moradi, 2012). On the other hand, more supportive climates have been associated with lower turnover intentions (Cancela et al., 2022; Rivero-Díaz et al., 2021; Velez and Moradi, 2012), lower job uncertainty (Rivero-Díaz et al., 2021) and lower job stress (Griffith and Hebl, 2002). With regard to the second specific objective, concerning the individual and psychological outcomes of support networks, a supportive workplace climate is positively related to life satisfaction and with measures of quality of life (Allan et al., 2015; Huffman et al., 2008; Tombari, 2020). It is also associated with lower levels of anxiety in environments of high demand and urgency (Goldberg and Smith, 2013). The third specific objective focuses on LGTBI+ identity management. Recent studies find that support is positively related to variables of disclosure about sexual orientation in the workplace (Brenner et al., 2010; Reed and Leuty, 2016; Tatum et al., 2017; Wood, 2020). On the other hand, a supportive workplace climate is also negatively related to covering variables (Chrobot-Mason et al., 2001; Reed and Leuty, 2016; Tombari, 2020). Following the above logic, we will carry out the same analyses with the hostile workplace climate variable. Thus, the fourth specific objective has to do with the relationship between hostility and psychosocial variables. As previous studies have shown, it is to be expected that climate is negatively related to positive psychosocial variables such as person-organization fit (Martinez et al., 2017), organizational commitment or job satisfaction (Martinez et al., 2017; Velez and Moradi, 2012). On the other hand, hostile workplace climates can also be expected to be positively related to negative psychosocial variables such as turnover intention (Rabelo and Cortina, 2014; Singh and O'Brien, 2019), burnout (Singh and O'Brien, 2019) or job stress (Waldo, 1999). In relation to the fifth specific objective, it is appropriate to highlight the close relationship between hostility and negative psychological variables. Hypervigilance, rumination, negative affect (Thoroughgood et al., 2017), distress (Corrington et al., 2019) and various emotional reactions (Miner and Costa, 2018) have very high positive correlations with hostility. Also, hostility is negatively related to positive psychological variables (Singh and O'Brien, 2019).

Regarding the relationship between hostility and LGTBI+ identity management (sub-objective 6), hostility is negatively related to disclosure about sexual orientation in the workplace (Capell et al., 2018; Reed and Leuty, 2016; Waldo, 1999). And, as might be expected, it is positively related to covering variables (Corrington et al., 2019).

Regarding specific objective 7, trans employees are more likely to experience hostility (because their status is involuntarily visible; Sawyer et al., 2016). This reason may expose them to high levels of discrimination for which they may be unprepared if they do not have sufficient coping tools or social support (Meyer, 2003). In addition, trans employees experience higher levels of hostile behavior in the workplace. Finally, it should be added that the psychological outcomes of discrimination in the school environment are projected in the long term. According to Minority Stress Theory (Meyer, 2003), being exposed to distal experiences of victimization or discrimination (e.g. discrimination in the educational environment) generates, in the victims, higher expectations of suffering discrimination in the future. This leads to greater negative psychosocial outcomes compared to LGBTI+ people who have not had such experiences. In fact, experiences of discrimination at school in young transgender people are related to the appearance of greater depression and lower life satisfaction in adulthood (Toomey et al., 2010). Therefore, it is to be expected that trans employees will have greater negative outcomes of hostile climates than LGB employees.

On the other hand, as trans employees are more affected by hostility at work, they will presumably have more intense and positive outcomes in relation to supportive workplace climates as this will act as a buffer (Meyer, 2003). Accordingly, we expected the magnitude of the associations between workplace climate and the analyzed outcomes to differ according to sample composition. We expected samples including trans people to show stronger associations between supportive workplace climate and positive outcomes than samples including only LGB employees.

2 Materials and methods

The meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA; Page et al., 2021). This study was approved ethically by the Ethics Committee of the Psychology Department of Oviedo University (Spain). It is also governed by the principles of the Helsinki Declaration for research involving people.

2.1 Criteria for inclusion or exclusion of articles

The selection criteria for the studies were the following: (a) articles with a measurement of supportive organizational climate or discriminatory organizational climate (operationalized as perceptions of support or perceptions of discrimination); (b) articles with at least one measurement of a psychosocial variable (job satisfaction, turnover intention, person-organization fit, organizational commitment, etc.) and/or psychological-individual variables (anxiety, depression, fear, strategies for managing gender identity and sexual orientation at work, etc.); (c) the sample with which the analyses have been carried out must be exclusively lesbian, gay, bisexual and/or transgender employees (or, at least, the correlations must be calculated with a subsample of gay, lesbian, bisexual and/or transgender employees); (d) national and international scope with no age restriction on participants. The year of publication of the studies is not limited.

2.2 Literature search strategy

During July 2022, several searches were conducted to locate the articles. First, a search was conducted on the Web of Science (WoS) with the following terms in the keywords, title or abstract: psychological variables: “psychological strain,” “wellbeing,” “anxiety,” “depression”; psychosocial variables: “job satisfaction,” “work satisfaction,” “life satisfaction,” “work attitudes”; LGBT: “queer,” “gay,” “bisexual,” “Lesbian,” “transgender,” “lgtbi,” “lgbt,” “lgtbiq,” “lgbtiq,” “lgtbq”; Organizational climate: “organizational climate,” “psychological climate,” “workplace climate,” “work climate,” “work environment perceptions,” “organizational support,” “workplace.”

Subsequently, and through the subsets of the WoS search, the results of the search for words related to organizational climate were joined to the results of the searches for words related to LGTBI+. The results of this combination (Organizational climate AND LGBT) were in turn combined with the articles resulting from the search for psychosocial variable keywords or the search for articles resulting from the psychological variable keywords.

Subsequently, a Google Scholar search was also conducted to retrieve doctoral theses and conference articles that were not indexed in WoS but had variables of interest, relevant samples and correlations between variables. The inclusion criteria for the studies were the same as in the WoS search. Finally, two meta-analyses of similar subject matter were also reviewed (Wax et al., 2018; Webster et al., 2017) in case any article had not been included in the previous searches.

The search process ended with 391 results in WoS and 34 in Google Scholar. After the refining process (explained in Figure 1), 23 articles from WoS, four from Google Scholar and two obtained from other meta-analyses were finally included (Smith, 1956; Tejeda, 2006 extracted from Wax et al., 2018). From these articles, k = 69 discrimination samples and k = 69 support samples were obtained.

Figure 1

2.3 Coding of moderator variables

To assess the possible effect of moderating variables, characteristics of the primary studies that were considered relevant were coded in an Excel file (version 2022). The coded variables were the following: (1) year, (2) authors, (3) climate variable, (4) outcome variable, (5) Pearson correlation, (6) sample size, (7) instruments used for the climate variable, (8) instruments used for the outcome variable, (9) sample composition (in relation to sexual orientation and gender identity).

2.4 Analysis variables

In the meta-analysis there are two large groups of variables. On the one hand, there are the climate variables (supportive climate and hostile climate) and on the other, there are the psychosocial, psychological and LGTBI+ identity management variables.

2.4.1 Psychosocial or psychological variables related to the workplace climate

These variables were grouped around seven major constructs (disclosure, covering, psychological distress, positive individual factors, negative psychosocial factors, positive psychosocial factors, and job satisfaction) according to the initial hypotheses, the coincidence of the instruments used in their measurement and the conceptual proximity between them.

The construct of psychological distress includes measurements of work stress, perceived stress, emotional overflow, rumination, hypervigilance, negative affect, fear, anger. In other words, all those variables referring to psychopathological or emotional variables of an “individual” nature.

On the other hand, measurements of psychological safety, wellbeing, life satisfaction, physical quality of life and psychological quality of life were included in the construct of positive individual factors.

In addition to the individualizing psychological factors, other psychosocial constructs were constructed. In this group we find the construct of negative psychosocial factors and positive psychosocial factors.

In the first of these, measurements of job insecurity and turnover intention were included. In other words, variables that provoke a subject's discomfort within their work environment and that compromise their performance, productivity and continuity in the organization.

In the case of positive psychosocial factors, variables related to the person-worker fit and the person-organization fit, safety climates and support from supervisors were included. That is, all those variables that occur in the interaction between the work environment and the individual and that are related to the employee's physical, psychological or social wellbeing or health.

Due to the large number of studies that had measurements of job satisfaction, covering and disclosure, they were not grouped at any higher level and formed their own construct. A meta-analysis was also performed between the hostile workplace climate and supportive workplace climate variables to assess their relationship. Table 2 reports the number of correlations available in each database, and to which constructs they were confined.

2.5 Data analysis

Meta-analyses were performed between each outcome variable and each of the two climate variables (supportive climate and hostile climate). Moderation analyses were performed on the basis of a categorical variable (gender identity). Pearson's correlation was used as a measurement of effect size. As Pearson correlations are not normally distributed, the correlations of the primary articles were transformed to the Fischer Z scale (Quintana, 2015). After analysis, these values were transformed back to Pearson correlations to facilitate interpretation of the data. A random effects statistical model was assumed throughout the process. The estimation method was DerSimonian and Laird (DerSimonian and Laird, 1986). The estimated effect size value and its confidence interval (95%) were used to indicate the results. Cochram's Q statistic for Heterogeneity was used to assess heterogeneity. The value of I²Higgins and Thomson, (2002) was also taken into account, which reports the percentage of real heterogeneity between studies and corrects for the low statistical power of Q with values of k < 30 (Sánchez-Meca and Marín-Martínez, 1997). Following the considerations of (Huedo-Medina et al. 2006) I² values of 25%, 50% and 75% were considered low, medium, and high heterogeneities.

Hypotheses 1A, 1B, 2A, 2B, 3A, 3B, and 8 were tested through meta-analyses of the supportive climate with each of the outcome variables. Hypotheses 4A, 4B, 5A, 5B, 6A, and 6B were tested through meta-analyses of hostile climate and each of the outcome variables. Hypothesis 7A was tested through a moderation analysis of gender identity in the relationship between support and the positive and negative variables. Hypothesis 7B was tested through a moderation analysis of gender identity in the relationship between hostility and the positive and negative variables.

Sample composition was coded as a categorical moderator based on whether the primary-study sample included trans employees. Depending on the primary study from which the correlation is drawn, the samples can be composed of lesbian and gay people (the first studies only asked about these two categories); lesbian, gay and bisexual people (in a perspective in which it is understood that the work experience is different according to sexual orientation but not the same as for people with different gender identity); trans people; and, finally, also of great heterogeneity (LGTBI+). The analysis of sample type as a possible moderator is very interesting to differentiate work experiences determined by sexual orientation or gender identity. Although the analysis of specific subgroup differences among lesbian, gay and bisexual employees are relevant, the available primary studies did not provide the sufficient number of correlations to analyze these groups separately. To avoid generating categories with low correlations, lesbian, gay and/or bisexual samples were grouped together and compared with trans or LGTBI+ samples. That is, studies whose samples consisted only of LGB employees were compared with studies whose samples contained trans people (exclusively or together with LGB people). Thus, this comparison captures whether the inclusion of gender identity diversity in the sample is associated with differences in the observed correlations.

Finally, the validity of the meta-analysis was assessed. Studies with non-significant effect sizes are much less likely to be published (Botella-Ausina and Sánchez-Meca, 2015). To assess possible publication bias, the Egger's regression test (Egger et al., 1997) was performed. Egger's test shows evidence of bias if p < 0.05. In addition, we also calculated Rosenthal's safety number which indicates, on our effect size, how many studies should be included in the meta-analysis with non-significant effect sizes for our meta-analysis to become non-significant. In other words, how many studies should be included with no effect to reach the critical point of non-significance. Rosenthal proposes as a rule of thumb to decide whether the safety number is sufficient or not, to calculate a limit based on the following formula: 5 ^*k + 10 (Botella-Ausina and Sánchez-Meca, 2015). All analyses were performed with R (R Core Team, 2021) and the metafor package (Viechtbauer, 2010).

3 Results

3.1 Characteristics of the studies

With regard to the studies obtained, first of all, a general analysis will be carried out and then their characteristics will be analyzed in terms of hostile workplace climate and supportive workplace climate.

3.1.1 Global characteristics

Since 2012, 58% of primary studies have included transgender people in their sample. Despite this, the number of studies with exclusive samples of transgender people remains residual (Brewster et al., 2012; Cancela et al., 2022). In addition, none of them report the correlations of the subsamples of cis and trans people. With regard to relevance and currency, the research is recent, with the first articles dating back to 1996. Moreover, an increase is observed in scientific interest in the topic: 63.33% of the articles are from the last 10 years.

3.1.2 Characteristics of supportive workplace climate studies

Based on the sample, 38.88% have trans people. Of these, 6 (85.71%) are from the last 10 years (2012–2022).

With regard to the instruments used, the LGBTCI, and its modified versions, remain the benchmark tool for assessing the organizational climate in LGTBI+ employees. 72.22% of the primary studies used the LGBTCI to measure the supportive climate. Other instruments used for this purpose were the Organizational Tolerance for Heterosexism Inventory (Waldo, 1999), Work Environmental Scale (Driscoll et al., 1996) and adapted versions of the Workplace Heterosexist Experiences Questionnaire (Waldo, 1999).

A job satisfaction variable was used in 66.67% of the primary studies. Fifty percentage of the studies have assessed disclosure regarding sexual orientation in the workplace. Only 22.22% of the studies have assessed covering.

3.1.3 Characteristics of hostile workplace climate studies

There are a variety of scales used to measure hostility: WHEQ (Waldo, 1999); Perceived Discrimination (Griffith and Hebl, 2002), the LGBTCI with hostile subscale (Rivero-Díaz et al., 2021) or reverse LGBTCI measurements (Liddle et al., 2004). Despite this, 53% of the hostile climate studies used the WHEQ as an instrument (Waldo, 1999).

The most frequently used variable in the 17 studies with a hostile climate is job satisfaction (it appears in 65% of them). The next most used variable is disclosure (53%). Distress appears in 35% of the studies and turnover intention in 35%. There is a higher frequency (50%) of studies with disclosure variables than studies with covering variables (18%).

3.2 Supportive workplace climate outcomes

3.2.1 Meta-analysis with supportive workplace climate

In the case of the supportive workplace climate, meta-analyses were conducted with eight different constructs (see Table 3). The supportive workplace climate, in LGBTI+ employees, is positively associated with disclosure (r =0.486 [0.422; 0.544]); positive individual factors (r =0.333 [0.265; 0.397]), positive psychosocial factors (r =0.547 [0.444; 0.636]) and job satisfaction (r =0.423 [0.340; 0.500]). Conversely, a supportive workplace climate is negatively related to discrimination (r = −0.556 [−0.652; −0.442]); psychological distress (r = −0.399 [−0.35; −0.508]); negative psychosocial factors (r = −0.42 [−0.489; −0.346]); and covering (r = −0.437 [−0.598; −0.241]). Hypotheses 1A, 1B, 2A, 2B, 3A, 3B, and 8 are therefore accepted.

With respect to heterogeneity, discrimination, positive psychosocial factors, negative psychosocial factors, concealment and job satisfaction all obtained very high values (above 75%). Only distress, disclosure and wellbeing obtain values below 75%.

It is possible that the variability that is occurring between some correlation coefficients and others is due to moderating variables. To assess this heterogeneity, a moderation analysis was carried out according to the type of sample.

3.2.2 Moderation analysis with supportive workplace climate and gender identity

To test hypothesis 7B, and in view of the heterogeneity of the results, a moderation analysis was conducted with the variables positive psychosocial factors, negative psychosocial factors and job satisfaction. It was not carried out with disclosure, discrimination and covering for two reasons: firstly, because they did not have enough samples to compare between groups; secondly, because disclosure and discrimination had very unbalanced subgroups (in disclosure, eight were of non-trans people and two of trans people; in discrimination, six had no trans people and three had trans people).

The gender identity variable moderates the relationship between positive psychosocial factors and a supportive workplace climate [Q_M (2) = 76.02, p < 0.001, I² = 94.12%]. Among LGB people, a supportive organizational climate has a lower positive relationship with positive psychosocial factors than among trans people (Table 4).

As for the negative psychosocial factors, the subgroup analysis found differences in effect size depending on the sample (Table 4). The subgroup of samples with transgender people had a significantly larger negative effect size than that obtained in samples without transgender people [Q_M (2) = 107.627, p < 0.001, I² = 85.73%].

Finally, the effect size of the organizational climate variable on job satisfaction was also different depending on the composition of the sample (Table 4). In the sample of employees including transgender people there is a significantly smaller effect size than in the sample of non-transgender people. The heterogeneity in this case was Q_M (2) = 75.971, p < 0.001; I² = 89.07%.

Therefore, hypothesis 7B is partially accepted as it could not be tested in all pairs of meta-analyses.

3.2.3 Supportive workplace climate publication bias

No meta-analyses have problems of publication bias.

3.3 Results with hostile workplace climate

3.3.1 Meta-analysis with hostile workplace climate

As shown in Table 5, all meta-analyses performed were significant. Regarding heterogeneity, the meta-analyses between hostility and disclosure, positive psychosocial factors, negative psychosocial factors and covering showed high heterogeneities (more than 75%). Distress and Job Satisfaction showed medium heterogeneities (more than 50% and less than 75%) and only positive individual factors showed low heterogeneities.

The constructs positively related to a hostile climate were psychological distress, negative psychosocial factors and LGTBI+ identity covering. More specifically, high hostile climate scores are related in LGTBI+ employees to high levels of psychological distress (r =0.434 [0.376; 0.489]), negative psychosocial factors (r =0.265 [0.192; 0.335]) and covering (r =0.408 [0.222; 0.565]). The constructs with the strongest positive relationship with hostile climate were psychological distress and covering.

Conversely, disclosure, positive individual factors, positive psychosocial factors, and job satisfaction were negatively related to hostile climate. In this case, the highest mean effect sizes were with the constructs most closely related to psychosocial factors: positive psychosocial factors (r = −0.371 [−0.477; −0.253]) and job satisfaction (r = −0.355 [−0.399; −0.309]). The remaining constructs maintained negative effect size means, although smaller than the previous ones: disclosure (r = −0.249 [−0.344; −0.148]); positive individual factors (r =0.219 [−0.253; −0.185]).

3.3.2 Analysis of moderation with hostility

Subsequently, to test hypothesis 7A, a moderation analysis was conducted with the following variables: disclosure, distress and job satisfaction. It was not conducted with positive individual factors, positive psychosocial factors, negative psychosocial factors and covering because of the low number of available studies (positive individual factors has k = 3 trans samples and k = 5 samples without trans people; positive psychosocial factors has only k = 6 correlations; covering has only k = 4 correlations) and their high heterogeneity, as well as unbalanced groups (in negative psychosocial factors we found k = 10 samples without trans people and k = 3 samples with trans people). These situations can lead to imprecise estimates with very low statistical power (Cuijpers et al., 2021; Griffin, 2021; Harrer et al., 2021).

The analysis of subgroups in disclosure (Table 6) shows differences in effect size in samples with trans people and samples without trans people. Samples with trans people had a lower negative effect size than samples without trans people [Q_M (2) = 21.499, p < 0.001; I² = 86.87%].

Regarding distress, the subgroup analysis (Table 6) found differences in effect size depending on the composition of the sample (without trans people, with trans people). The subgroup consisting of samples with trans people had a larger positive effect size than samples without trans people [Q_M (2) = 190.254, p < 0.001; I² = 52.74%].

Subgroup analysis in relation to job satisfaction and hostility (Table 6) also found differences in effect size depending on the sample (without trans people, with trans people). The subgroup of samples with trans people had a larger negative effect size than samples without trans people [Q_M (2) = 248.773, p < 0.001; I² = 60.45%; T² = 0.005 (se = 0.003)].

Hypothesis 7A is therefore partially accepted.

3.3.3 Hostile workplace climate publication bias

Publication bias was analyzed using Egger's test and Rosenthal's test. In the case of hostility, as with support, we found no problems of bias in any meta-analysis.

4 Discussion

The aim of this study was to investigate the relationships between supportive and hostile workplace climates and psychosocial, psychological and identity management variables among LGTBI+ employees.

The meta-analyses conducted corroborated the hypothesized connections between the variables. All meta-analytic relationships evaluated were significant and their mean effect sizes were intermediate-high. In addition, the hypotheses concerning the moderation of gender identity in the relationships between supportive and hostile climate were also partially corroborated. In a supportive climate, gender identity moderates the relationship with positive psychosocial factors, negative psychosocial factors and job satisfaction. In a hostile climate, it moderates the relationship with disclosure, distress and job satisfaction. The relationships between variables are stronger in the transgender samples, except for disclosure and hostility.

4.1 Hostile and supportive workplace climates

One of the specific aims of the study (SO 8) was to analyze the relationship between hostility and support and to assess the differences in how they operate. Although there is a high heterogeneity between study scores, hostility and support are negatively and moderately related to each other. The high heterogeneity may originate from the variety of instruments to measure hostility: WHEQ (Waldo, 1999), LGBTCI hostility subscale (Rivero-Díaz et al., 2021), LGBWDS (Croteau et al., 1998), WHEQ-TF, Incivility (Cortina et al., 2013), ad hoc (Ragins and Cornwell, 2001).

On the other hand, a supportive climate is positively related to disclosure, positive individual factors, positive psychosocial factors and job satisfaction and negatively related to discrimination, distress, negative psychosocial factors and covering. A hostile climate is positively related to distress, negative psychosocial factors and covering and negatively related to disclosure, positive individual factors, positive psychosocial factors and job satisfaction. As we can see, the relationships they establish are opposites, although not of the same magnitude. In fact, making pairwise comparisons of meta-analyses, support obtained stronger relationships than hostility with variables of a work and organizational nature (positive psychosocial factors, positive individual factors, negative psychosocial factors and job satisfaction) and hostility showed stronger relationships than support (in absolute value) with variables of a psychological-individual nature (distress). In a domain analysis, support showed the strongest relationships with organizational variables (positive psychosocial factors, negative psychosocial factors, and job satisfaction) and with disclosure. Hostility showed the strongest relationships with individual variables (distress and covering).

Also, the frequency of variable use in the primary studies supports these results: studies of hostility tend to use more instruments focusing on distress, turnover intention and disclosure. Whereas studies related to support tend not to use distress or covering variables.

It is worth noting that these results are also deduced from the Minority Stress Theory (Meyer, 2003), in which hostility is closely related to individual-psychological variables such as distress (Meyer, 2003). The relationship between hostility and covering, on the other hand, can be explained in terms of psychological, environmental and consequence anticipation factors (Chrobot-Mason et al., 2001; Meyer, 2003; Prati and Pietrantoni, 2014; Ragins, 2008. Thus, in hostile environments, anticipation of consequences (among other factors) will favor covering. The role of support, in this case, would be to mitigate the negative outcomes of hostility and favor the free expression of LGTBI+ identity (Meyer, 2003).

From the above, we can conclude that hostility and support are moderately-highly related and differ in the magnitude of their relationships with outcome variables. This result provides further empirical evidence for the conceptual distinction between the two phenomena (Holman et al., 2019; Meyer, 2003; Rivero-Díaz et al., 2021; Webster et al., 2017).

4.2 Comparison with other studies

The relationship between discrimination and support obtained smaller effect sizes in our meta-analysis than in previous meta-analyses (r_r = −0.556 vs. r_w = −0.69 from Webster et al., 2017). This difference may be due to the fact that in our study we did not introduce the outness instrument from the primary study by Huffman et al. (2008) as a discrimination, but as a disclosure variable. Furthermore, our meta-analysis includes additional studies (Brenner et al., 2010; Singh and O'Brien, 2019).

With respect to psychological distress and support, our meta-analysis found larger effect sizes than Webster et al. (2017; r_r = −0.399 vs. r_w = −0.29). Also, in the relationship between distress and hostility, our meta-analysis found higher effect sizes than (Webster et al., 2018; r_r = 0.434 vs. r_w = 0.28). These variations may be due to some differences in the conceptualization of psychological distress in both meta-analyses. In Webster et al. (2017), Job Stress measures are included as measurements of psychological distress. In our study, we consider that being measurements of feelings of being under constant time pressure at work (Muñoz, 2005), they are more related to psychosocial factors than to purely psychological ones because of their circumscription to the workplace and their close relationship with other organizational variables.

Regarding the meta-analysis on job satisfaction, both studies have similar mean effect sizes (support: r_r = 0.423 vs. r_w = 0.43; hostility: r_r = −0.355 vs. r_w = −0.21).

Finally, regarding the relationship with the disclosure construct, both support and discrimination obtain very similar values in both meta-analyses (Supportive: r_r = 0.482 vs. r_w = 0.56; hostile: r_r = −0.249 vs. r_w = −0.22).

4.3 Moderation analysis

Gender identity moderates the effect sizes that are established between some variables. In studies including trans employees, supportive workplace climate showed stronger associations with positive psychosocial factors and negative psychosocial factors than in studies including only LGB employees.

A possible alternative explanation for the hypotheses underlying the above results may be the year in which the studies were conducted. Most of the studies with transgender samples have been carried out during the last 10 years. We also know that the employment situation of LGTBI+ employees is improving (International Lesbian Gay Bisexual Trans and Intersex Association, 2020). So, it is possible that either intervention in the workplace has improved by creating more and better supportive workplace environments and is therefore more effective in creating positive outcomes and reducing negative associated outcomes, or that LGB employees are not currently experiencing as high levels of discrimination in the workplace as trans employees, as shown in the latest EU discrimination survey [European Union Agency for Fundamental Rights (FRA), (2020)]. In this situation, the mental health and psychosocial outcomes of trans employees will depend to a large extent on not experiencing hostility in the workplace and having a supportive climate in relation to their gender identity (Meyer, 2003). In conclusion, it is possible that, for trans employees, the perception of having a supportive climate is more relevant for their life and job satisfaction than for other employees who do not face such high levels of discrimination.

In the case of the hostile workplace climate, something similar happens. Trans employees, with the same levels of hostility, score higher in psychological distress and lower in job satisfaction than LGB employees. In this case, trans employees have worse psychological outcomes in hostile work environments than LGB employees.

On the other hand, with the same hostile workplace climate scores, LGB people score significantly lower in disclosure. The latter result can be explained by the fact that the measurements of disclosure used in the primary studies focus on disclosure about sexual orientation [WSIMM (Anderson et al., 2001) and Outness Inventory (Mohr and Fassinger, 2000)]. An exception is the study by (Brewster et al. 2012) in which the authors make a modification of the WSIMM (WSIMM-TF) to adapt it to gender identity management and trans people. As some trans people are heterosexual, one would expect that even if they experience a hostile environment toward LGBTI+ people, they would have no problems talking about their sexual orientation because it would be normative (heterosexual).

The results provide meta-analytic evidence that trans people have different work experiences than LGB employees. This indicates that, as hypothesized in the introduction, gender identity and sexual orientation, although related, do not generate (through support or discrimination) the same psychological and psychosocial outcomes. More research is needed in this area.

4.4 Breadth of constructs analyzed: new approaches

The final constructs were similar to those used in the Webster et al. (2017) meta-analysis, although with some modifications: the Webster et al. (2017) construct called work attitudes is similar to the measurements of job satisfaction. In our meta-analysis, as in Webster et al. (2017), measurements of disclosure, psychological strain and perceived discrimination are also collected. However, a significant contribution of this meta-analysis is that it introduces the constructs of covering (more related to hostility), and negative and positive psychosocial factors. Another contribution is that this meta-analysis is the only one that analyses the relationship of variables with measurements of hostility in the workplace, and not only of support with covering, disclosure, psychological and psychosocial variables.

4.5 Organizational, occupational and psychosocial implications

The results are consistent with other similar meta-analyses (Webster et al., 2017) and provide empirical evidence of the relevance of the organizational climate on psychosocial and psychological variables in the workplace.

The implications of these findings range from organizational to psychological, human resource management, occupational and psychosocial levels.

At the organizational level, the business and productivity outcomes of discrimination toward LGTBI+ employees have been extensively discussed in other articles (Badgett et al., 2019). In this regard, the effects of hostility can be direct or indirect. Directly, hostility generates a negative view of the company in the eyes of consumers, leading to lower financial profits (Lloren and Parini, 2017). Indirectly, hostility leads to a loss of talent (Ragins, 2008; Rivero-Díaz et al., 2021, 2020; Velez and Moradi, 2012). Not only does discrimination facilitate job turnover, but it also reduces employee productivity through psychosocial variables such as job dissatisfaction, psychological distress and covering (Badgett et al., 2019; Webster et al., 2017).

To avoid this, programmes are needed to evaluate and improve the climate of support for LGTBI+ employees. Protocols are also needed to detect and prevent hostile and discriminatory behavior. The perception by LGTBI+ employees that the organization and their work environment support them in relation to their sexual orientation or gender identity can reverse specific situations of discrimination and hostility. Therefore, intervention in the workplace and organizational environment must have a two-fold objective: to reduce and prevent hostility and to create a supportive workplace environment.

The effective development of these strategies may contribute to more favorable levels of job satisfaction, life satisfaction and the person-organization fit, and ultimately improve the mental health of LGTBI+ employees. This may be associated with improvements in productivity, increased business profits and an improved public image for organizations. Similarly, all these developments will lead to improvements in talent management and their commitment/loyalty to the company.

4.6 Limitations and future directions

Moderation analyses have been limited by the small number of primary studies and correlations available with samples of trans people (Cuijpers et al., 2021; Dijkman et al., 2009). In this regard, in addition, meta-analyses with k < 5 (hostility-covering and support-distress) need to be taken with caution (Borenstein et al., 2010; Jackson and Turner, 2017), meaning that this is a field that requires further research in the future.

Another limitation is that the moderation analysis was carried out on the basis of gender identity and the collected articles had few samples composed exclusively of trans people (4 primary studies and k = 25 samples with correlations). Therefore, studies need to be promoted that use samples of transgender people to assess differences according to gender identity and type of sexual orientation.

Another limitation concerns the scope of the databases used in the search strategy. Web of Science is a multidisciplinary database that provides broad coverage of organizational, psychosocial and workplace-related journals. Nevertheless, future studies should consider including additional databases with a stronger focus on psychology and health sciences, such as PsycINFO, or others like PubMed or Scopus.

Although lesbian, gay, and bisexual employees may have differentiated workplace experiences, the available primary studies did not provide a sufficient number of independent correlations. Therefore, lesbian, gay and/or bisexual samples were grouped into a single LGB category for analytic purposes. This grouping should not be interpreted as assuming homogeneity among LGB employees, but rather as a methodological decision to avoid very small moderator categories and unstable estimates. A methodological recommendation is that primary studies should report correlations obtained by subgroups created on the basis of sexual orientation, gender, or gender identity.

Finally, it would also be interesting to carry out an analysis of moderation according to organizational variables (type of job, salary or job category). In our analysis, this could not be done because most of the samples analyzed were made up of people from the upper-middle class, highly educated, with a high level of purchasing power and an academic-intellectual background. It is necessary to collect a higher quality and larger sample: a greater number of trans people and greater heterogeneity in terms of work, education and salary characteristics.

5 Conclusion

A supportive climate toward LGTBI+ employees show high effect sizes both positively (with positive psychosocial factors, disclosure, job satisfaction and positive individual factors) and negatively (with discrimination, covering, negative psychosocial factors and negative individual factors) confirming its relevance in explaining and understanding the experiences of LGTBI+ employees. On the other hand, hostile workplace climates are positively related to psychological distress, negative psychosocial factors and covering. And negatively with disclosure, positive individual factors, positive psychosocial factors and job satisfaction.

Finally, gender identity moderates these relationships. In samples including trans employees, supportive workplace climate showed stronger associations with positive and negative psychosocial factors than in samples including only LGB employees. On the other hand, hostility-distress and hostility-job satisfaction relationships are stronger among trans employees than among LGB employees. The experiences of LGTBI+ employees are not homogeneous and therefore need to be analyzed in terms of their intersectionality (gender identity, gender, sexual orientation, social class, income, organizational variables and other defining characteristics of their work experiences).

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