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. 2022 Oct 25;17(10):e0275771. doi: 10.1371/journal.pone.0275771

Work-related stressors and mental health among LGBTQ workers: Results from a cross-sectional survey

Benjamin Owens 1, Suzanne Mills 1,*, Nathaniel Lewis 2, Adrian Guta 3
Editor: Remya Lathabhavan4
PMCID: PMC9595555  PMID: 36282835

Abstract

Purpose

Lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals experience high rates of adverse mental health outcomes due to the stressors they experience in families, communities, and society more broadly. Work and workplaces have the potential to influence these outcomes given their ability to amplify minority stress, and their ability to influence social and economic wellbeing in this already marginalized population. This study aims to identify how sociodemographic characteristics and characteristics of work, including degree of precarity, industry and perceived workplace support for LGBTQ people, influence self-reported mental health among LGBTQ people in two Canadian cities.

Methods

Self-identified LGBTQ workers ≥16 years of age (n = 531) in Sudbury and Windsor, Ontario, Canada were given an online survey between July 6 and December 2, 2018. Multivariate ordinal logistic regression was used to calculate odds ratios (OR) to evaluate differences in gender identity, age, income, industry, social precarity, work environment, and substance use among workers who self-reported very poor, poor, or neutral mental health, compared with a referent group that self-reported good or very good mental health on a five-point Likert scale about general mental health.

Results

LGBTQ workers with poor or neutral mental health had greater odds of: being cisgender women or trans compared with being cisgender men; being aged <35 years compared with ≥35 years; working in low-wage service sectors compared with blue collar jobs; earning <$20,000/year compared with ≥$20,000/year; working in a non-standard work situation or being unemployed compared with working in full-time permanent employment; feeling often or always unable to schedule time with friends due to work; feeling unsure or negative about their work environment; and using substances to cope with work.

Conclusions

Both precarious work and unsupportive work environments contribute to poor mental health among LGBTQ people. These factors are compounded for trans workers who face poorer mental health than cis-LGBQ workers in similar environments.

Introduction

Population-level studies have shown consistently that lesbian, gay, bisexual, transgender and other queer (LGBTQ) people have poorer mental health outcomes compared with cisgender heterosexual people [1,2]. Research has increasingly attributed these disparities to minority stress, comprising both proximal stress in the form of anticipated stigma and discrimination and distal stress in the form of actual experiences of discrimination [3,4]. Minority stress can increase depression, anxiety, deliberate self-harm, and substance abuse [1,3,4]. Although minority stress is often measured at the individual level through scales of outness, internalized homophobia and perceived discrimination [5,6], researchers have also acknowledged that experiences of minority stress may differ based on the gender and sexuality norms encountered in different spaces. These norms also have a socio-legal dimension, and thus experiences of minority stress are also dependent on structural stigma, or the level of protection and/or criminalization that individuals experience from various levels of government [3,7]. Due to the substantial amount of time spent at work, work has the potential to amplify or mitigate minority stress through both adverse experiences that LGBTQ people have in the workplace as well as work’s ability to provide a safe and supportive working environment [6,8].

Previous research has shown that measures of workplace environment or climate affect the mental health outcomes of LGBTQ workers. Heterosexism in the workplace has been associated with psychological distress [9], and depression specifically [10], among gay and lesbian workers. Gay, lesbian, and bisexual workers also face sexuality-specific stressors at work, such as fear of coming out [11] or experiences of heterosexist discrimination [12,13], that can contribute to psychological distress, anxiety, and depression. Workplace harassment has also been linked with increased alcohol consumption for lesbian and bisexual women [14]. While not specifically examining workplace experiences, recent research on minority stress has also linked psychosocial stressors to poorer cardiovascular health for LGBTQ people, demonstrating the ways cumulative stress can lead to adverse physical health outcomes in addition to affecting individuals’ mental health [15,16].

Alternatively, workplaces that are supportive of LGBTQ people decrease depression and anxiety [17] and job anxiety specifically [18]. Positive workplace environments, as experienced in terms of employer and co-worker support, can increase job and life satisfaction [19], as can choosing to come out at work [18]. Qualitative studies have suggested that these trends differ by sector; whereas normative gender performances in blue collar sectors (e.g., manufacturing) might negatively affect the wellbeing of sexual and gender minorities, public-sector work can be a refuge for sexual and gender minorities [8,20], though research has shown that even ostensibly progressive sectors can be sites of discrimination and stress for LGBTQ workers [21]. Furthermore, individual-level factors may also be protective; the availability of a same-sex partner and employment dyadic coping strategies appears to attenuate the relationship between workplace stress and anxiety [22].

In addition to the above factors, mental health outcomes among LGBTQ people might also be affected by unemployment and precarious work in ways similar to that of cis-heterosexual workers workers [23]. While previous studies have acknowledged that economic insecurity affects the mental health of bisexual people similarly to that of heterosexual and cisgender individuals [24], they do not necessarily acknowledge that adverse outcomes at the population level could be exacerbated by the overrepresentation of LGBTQ people in low-wage service work [25] or unemployment resulting from discrimination in hiring and firing practices [26].

A large volume of research has explored the effects of precarious employment, work that is insecure and/or unstable, on worker wellbeing [27]. Population level studies have associated precarious employment with poor mental health [28–30]. Rodgers [31] identified four key dimensions of precarious employment including short, limited working arrangments (instability), low control over wages or work conditions (job insecurity), lack of institutional protection, and low income/poverty. Some scholars have added additional dimensions including, degree control over work, status or prestige, risk of exposure to physical hazards, training and career advancement opportunities, and socio-cultural environment at work [27]. Though employment contingency or deviations from the standard employment relationship are commonly used to measure precarity in quantitative studies, studies are increasingly using composite measures and subjective measures [32–34]. In the case of LGBTQ workers, socio-cultural environments that are supportive could feasibly constitute a dimension of precarity. For conceptual clarity in this paper, however, precarity is understood as job instability resulting from contingent work arrangments and job insecurity resulting from the absence of control over wages or work hours.

Studies adopting a variety of objective, subjective and composite measures have shown that workers in precarious employment relationships have greater likelihood of suicidal ideation, depression, poor sleep and psychological distress [23,32,33]. Precarious employment and social stress leads to adverse psychological and physiological health through several direct and indirect pathways. Precarious employment negatively affects health both directly by increasing the release of stress hormones and indirectly by decreasing life and job satisfaction, causing material deprivation, fostering substance abuse, or increasing exposure to work hazards [27]. The relationship between mental health and precarity, moreover, exists on a continuum, with more precarious jobs leading to poorer mental health compared with less precarious jobs [35].

Intersectionality can also affect how one experiences precarity. Social location such as racialization, immigration status, gender identity and sexual orientation has the potential to mediate the effects of precarity on health. In a population level study in South Korea gender mediated the relationship between non-standard and chronic disease conditions; non-standard employment was associated with mental disorders in women and musculoskeletal disorders and liver disease in men [36]. Second, marginalized groups, such as women, recent immigrants and LGBTQ people, are often over-represented in precarious work and as a result more likely to suffer negative health effects. To date, however, most studies examining gender and precarity have adopted binary conceptions of gender and overlooking transgender, genderqueer, and non-binary population [36]. Precarious employment may amplify minority stress experienced by trans workers, in particular, since it is associated with fewer job protections, less access to extended health benefits, and greater economic insecurity. Sexual minority workers who are unemployed, for example, are more likely to report mental illness [37]. Although the link between unemployment and poor mental health has also been reported in research where sexual orientation is not reported [38], the reasons for which LGBTQ workers become unemployed (e.g., discrimination, work-related stress) may be different from heterosexual workers. Factors such as low income may also reinforce disadvantage. In Canada, bisexual people situated below the low-income cut-off in Canada were more likely to experience depression and to perceive discrimination due to both early-in-life experiences (e.g., discrimination) that affected financial stability, and difficulties accessing supports and mental health care due to their financial position [24].

Among studies exploring the relationship between work and LGBTQ mental health, few have been designed specifically to assess mental health outcomes across diverse sociodemographic segments of the LGBTQ community, diverse types of work, or to measure the relative impacts of precarious work, unemployment, and workplace culture on LGBTQ mental health outcomes.

Hypothesis: LGBTQ people in precarious work and in work environments that are not supportive of LGBTQ identities are more likely to have poor mental health outcomes.

By locating itself in two cities with transitional economies, Sudbury and Windsor [39,40] this study also seeks to better understand the specific challenges faced by LGBTQ workers in post-industrial societies marked by increasing precarity and still-persistent discrimination.

Methods

Ethics

This study was approved by the McMaster University Research Ethics Board (MREB#1866). For participants who completed the survey online, the informed consent process preceded the survey and participants provided their consent through answering an online question that asked them whether they consent to participate in the research. Participants who completed paper surveys provided written consent prior to beginning the survey. Consent from parents or guardians of participants ages 16 and 17 was not required given the potential social risks of involving family members in research about LGBTQ identity, and this was cleared by the McMaster University Research Ethics Board.

Recruitment and sample

We collected survey responses for 662 individuals in Sudbury and Windsor from July 6 to December 2, 2018. Surveys were available in both English and French in web-based and paper formats. We used rigorous multi-faceted recruitment strategies, including respondent-driven sampling techniques to reduce sampling bias, since LGBTQ people constitute a ‘hidden population’ [41]. Paper surveys were distributed by community organizations in each city. Links to the web-based survey were distributed using a variety of strategies including e-mailing membership lists of several large unions and employment lists in each city, distributing postcards to LGBTQ support groups promoting the survey on local radio stations, and placing ads on Facebook, Instagram, and the geosocial meet-up platforms Grindr and Scruff. Community advisory committees were formed in each city and members distributed surveys through their personal networks.

These strategies were supplemented by in-person recruitment at Pride and other community events in both cities, where researchers were available with tablets as well as paper surveys to encourage participation and minimize selection bias. Principles of respondent driven sampling were used to reach networks outside the reach of the above methods: participants were encouraged to distribute the survey to members of their social network by unique codes and a prize incentive [42]. Eligible survey participants had worked in one of the two cities in the past year, were ≥16 years of age, and identified as LGBTQ. Eligibility criteria was determined to be met based on a brief pre-survey, which asked participants for their age, whether they self-identified as LGBTQ, and whether they had worked in Windsor or Subdury over the past year. Given the exploratory nature of the study, which focused on the work and community experiences of LGBTQ workers, non-LGBTQ persons were excluded from participating.

Variables

Based on the literature on LGBTQ mental health and workplace mental health, we used ordered logistic regression to model self-reported mental health using sociodemographic characteristics (gender identity, age and income), industry, indicators of precarity (employment relationship, difficulty scheduling time with friends, fear of job loss), perceived workplace support for LGBTQ workers (workplace environment), and substance use, alcohol use and tobacco use as additional risk factors.

Outcome variable

Mental health: A self-assessed, single-item mental health outcome variable was determined based on responses to a question asking participants to rate their mental health on a five-point Likert scale. This scale is based on other single-item measures of self-rated mental health commonly used in health surveys as it reduces respondent burden and has been shown to be a reliable measure of mental health [43]. Poor and very poor were recoded to a single ‘poor’ category; average was maintained as ‘neutral’; and good and very good were recoded into a single referent ‘good’ category.

Predictor variables: Sociodemographic characteristics

Gender identity: Participants identified their gender identity from a list, with the option to write-in their own response. This variable was recoded into three categories: cisgender men, cisgender women, and trans. Trans women, trans men and non-binary/genderqueer identities were collapsed into one category ‘trans’ to increase cell sample size because of the small number of responses in each individual category.

Age range: Participants wrote in their year of birth, which was then recoded into two age groups: <35 years and ≥35 years.

Income: Participants were asked to indicate how much money they made in the previous year by choosing from a range of categories in $10,000 increments, before taxes and deductions; responses were recoded into two categories: < $20,000/year and ≥$20,000/year.

Race/ethnicity: Participants were asked to self-identify the race and/or ethnicity that best described them from a list, with the option to write-in their own response. This variable was then coded into four categories: White, Black, Indigenous, and other racialized. Respondents who did not identify as White, Black, or Indigenous were combined into one category ‘other racialized’ due to the small number of responses in each individual category.

Predictor variables: Work characteristics

Two variables were used to measure precarious work: a subjective measure (social life affected by uncertain work schedule), and an objective measure (employment relationship). Industry and work environment were used to capture the industries participants worked in and the degree to which their workplaces were positive for LGBTQ workers.

Social life affected by uncertain work schedule: Participants selected how often uncertainty about their work schedules limited time with friends, family, or community activities from a five-point scale; rarely, never, and sometimes were recoded into a single referent category; often and always were recoded into a single category.

Employment relationship: Participants selected what best matched their employment relationship in their primary job from a list of options. This was recoded into three categories: full-time permanent, non-standard (comprising contract, temporary, self-employed, and part-time work), and unemployed.

Industry: Participants selected the industry they worked in for their primary job based on the North American Industry Classification System (NAICS). Mining, manufacturing, transportation, agriculture, and construction were recoded into a single category of blue collar; finance, administration, information, management, real estate, education, health, and public administration were recoded as white collar; food service, retail, arts/entertainment, and other service were recoded as low-wage service.

Work environment: Participants were asked to rate their work environment for LGBTQ workers from a five-point scale; very negative, negative, and unsure were recoded to negative/unsure, and positive and very positive were recoded to positive.

Predictor variables: Other risk factors

Substance use: Participants were asked if they have ever used substances to cope with their work. This was coded as a binary variable.

Alcohol use: Participants were asked if they have ever used alcohol to cope with their work. This was coded as a binary variable.

Statistical analyses

A multivariable ordered logistic regression model was used to estimate the association between mental health and individual characteristics. We compared workers who reported poor mental health, neutral mental health and good mental health, which served as the referent category. Participants with complete outcome and descriptive data were included in regression models, and respondents with missing values were excluded from analysis. We created a multivariable regression model using a purposeful selection strategy [44], first conducting exploratory univariate analyses to assess whether there was a relationship between each variable and mental health outcomes. Variables meeting p<0.05 in univariate analyses were retained in the multivariable model. Results of a partial likelihood ratio test comparing the full model (including alcohol use) with the more parsimonious one suggests that adding the alcohol use variable did not result in significantly improved model fit (LR chi2(4) = 0.35 Prob >chi2 = 0.5542). We conducted a variance inflation factor (VIF) test for multicollinearity and no variables exceeded a VIF of 3, indicating that collinearity is minor and that no variables merited further investigation. Results are presented as adjusted odds ratios (aOR) and associated 95% confidence intervals (CIs). STATA™ (College Station, TX: StataCorp, LLC) was used to perform the analysis.

Results

Of the 632 people who completed the survey (405 from Sudbury and 266 from Windsor), data from 531 individuals had no missing values and was available for analysis. Overall, 48.2% reported good mental health, 32.8% reported neutral mental health, and 19.0% reported poor mental health.

Univariate analysis

Demographic, socioeconomic and employment characteristics among those who reported poor, neutral and good mental health, the referent group, are reported in Table 1. Compared with the referent group, those who reported poorer mental health were more likely to be cisgender women (OR: 2.15; 95% CI: 1.47–3.14) or trans (OR: 4.29; 95% CI: 2.68–6.85), and less likely to be cisgender men. Those reporting poor or neutral mental health were also more likely to be aged <35 years (OR: 3.58; 95% CI: 2.44–5.27) compared with people aged ≥35 years, and to have higher odds of having an individual income of ≤$20,000/year (OR: 5.05; 95% CI: 3.52–7.27), compared with >$20,000/year. Respondents reporting poorer mental health did not differ significantly from the referent group based on race/ethnicity.

Table 1. Sociodemographic, economic, and employment characteristics of LGBTQ workers by reported mental health: Good (ref., n = 256), neutral (n = 174), and poor (n = 101), and univariate ordered logistic regression models for each variable (‘neutral’ and ‘poor’ mental health compared to ‘good’ referent category).

Self-reported mental health
Good Neutral Poor
Characteristics N(%) N(%) N(%) OR 95% CI
Gender identity
 Cis man (ref) 112 (43.8) 51 (29.3) 15 (14.9) ref
 Cis woman 111 (43.4) 86 (49.4) 49 (48.5) 2.15* 1.47–3.14
 Trans 33 (12.9) 37 (21.3) 37 (36.6) 4.29* 2.68–6.85
Age range
 ≥35 years (ref) 109 (42.6) 39 (22.4) 10 (9.9) ref
 <35 years 147 (57.4) 135 (77.6%) 91 (90.1) 3.58* 2.44–5.27
Race/ethnicity
 White 193 (75.4) 135 (77.6) 76 (76.8) ref
 Black 20 (7.8) 8 (4.6) 7 (7.1) 0.76 0.39–1.51
 Indigenous 28 (10.9) 26 (14.9) 13 (13.1) 1.19 0.74–1.92
 Other racialized 15 (5.9) 5 (2.9) 3 (3) 0.51 0.21–1.21
Industry
 Blue collar (ref) 40 (15.6) 15 (8.6) 9 (8.9) ref
 White collar 153 (59.8) 101 (58.1) 37 (36.6) 1.36 0.79–2.35
 Low-wage service 63 (24.6) 58 (33.3) 55 (54.6) 3.14* 1.77–5.57
Income
 Over $20,000/year (ref) 217 (84.8) 105 (60.3) 38 (37.6) ref
 Under $20,000/year 39 (15.2) 69 (39.7) 63 (62.4) 5.05* 3.52–7.27
Employment relationship
 Permanent full-time (ref) 151 (59) 75 (43.1) 35 (34.7) ref
 Non-standard 105 (41) 97 (55.8) 59 (58.4) 2.00* 1.44–2.78
 Unemployed 0 (0) 2 (1.2) 7 (6.9) 25.22* 5.20–122.29
Workplace environment
 Positive (ref) 212 (82.8) 121 (69.5) 50 (49.5) ref
 Unsure/negative 44 (17.2) 53 (30.5) 51 (50.5) 3.16* 2.19–4.54
Social life affected by work
 Never/rarely/sometimes (ref) 213 (83.2) 131 (75.3) 55 (54.5) ref
 Often/always 43 (16.8) 43 (24.7) 46 (45.5) 2.74* 1.88–3.99
Substance use to cope with work
 Does not use (ref) 131 (51.2) 79 (45.4) 35 (34.7) ref
 Uses substances 125 (48.8) 95 (54.6) 66 (65.4) 1.56* 1.13–2.16
Alcohol use to cope with work
 Does not use (ref) 196 (49.4) 134 (33.8) 67 (16.9) ref
 Uses alcohol 60 (44.9) 40 (29.9) 34 (25.4) 1.34 0.93–1.94
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Compared with the referent group, those reporting poorer mental health also had higher odds of working in the low-wage service sector (OR: 3.14; 95% CI: 1.77–5.57), compared with working in a blue collar sector; odds of working in a white collar sector (OR: 1.36; 95% CI: .79–2.35) were not significantly different. Those reporting poorer mental health also had higher odds of being unemployed (OR: 25.22; 95% CI: 5.2–122.29) or being in a non-standard work situation (OR: 2; 95% CI: 1.44–2.78), compared with permanent, full-time employment.

Compared with the referent group, those reporting poorer mental health had higher odds of rating their work environment for LGBTQ employees negatively or being unsure what to rate it (OR: 3.16; 95% CI: 2.19–4.54), compared with rating it positively. Compared with the referent group, they also had higher odds of often or always feeling unable to schedule time with friends because of work (OR: 2.74; 95% CI: 1.88–3.99) compared with sometimes, rarely, or never. Finally, compared with the referent group, those reporting poorer mental health had higher odds of using substances to cope with work (OR: 1.56; 95% CI: 1.13–2.16). Respondents reporting poorer mental health did not differ significantly from the referent group in using alcohol to cope with work.

Multivariable analysis

All variables for which significant differences in odds were observed in multivariate analysis were retained in the multivariable model (Table 2). An additional industry category (white collar) for which differences from the referent (blue collar) were not observed was also retained as it was likely to underpin differences in variables such as employment status, income, and work environment. In the multivariable analysis, those reporting poorer mental health had greater adjusted odds of being trans (aOR: 3.01; 95% CI: 1.82–4.97) or cisgender women (OR: 1.91; 95% CI: 1.27–2.89), compared with cisgender men. Compared with the referent group, those reporting poorer mental health were more likely to be aged <35 years (OR: 2.08; 95% CI: 1.32–3.26) compared with people aged ≥35 years, and to have higher odds of having an individual income of ≤$20,000/year (OR: 2.85; 95% CI: 1.86–4.37), compared with >$20,000/year.

Table 2. Ordered logistic regression estimates of impact of sociodemographic and employment characteristics on LGBTQ workers’ mental health (‘neutral’ and ‘poor’ mental health compared to ‘good’ referent category).

Characteristics aOR 95% CI
Gender identity
 Cis man (ref) ref
 Cis woman 1.91* 1.27–2.89
 Trans 3.01* 1.82–4.97
Age range
 ≥35 years (ref) ref
 <35 years 2.08* 1.32–3.26
Industry
 Blue collar (ref) ref
 White collar 1.67 0.92–3.02
 Low-wage service 1.98* 1.05–3.72
Income
 Over $20,000/year (ref) ref
 Under $20,000/year 2.85* 1.86–4.37
Employment relationship
 Permanent full-time (ref) ref
 Non-standard 1.07 0.73–1.56
 Unemployed 9.45* 1.64–54.64
Workplace Environment
 Positive (ref) ref
 Unsure/negative 2.25* 1.51–3.33
Social life affected by work
 Never/rarely/sometimes (ref) ref
 Often/always 2.00* 1.33–3.00
Substance use to cope with work
 Does not use (ref) ref
 Uses substances 1.48* 1.04–2.11
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Compared with the referent group, those reporting poorer mental health continued to have higher odds of working in a low-wage service job (aOR: 1.98; 95% CI: 1.05–3.72), compared with working in a blue collar position; odds of working in a white collar job (aOR: 1.67; 95% CI: .92–3.02) were higher than observed in the univariate analysis but still not significant. Those reporting poorer mental health also had higher odds of being unemployed (aOR: 9.45; 95% CI: 1.64–54.62) compared with permanent, full-time employment; odds of being in a non-standard work situation were not significant.

Compared with the referent group, those reporting poorer mental health had higher odds of rating their work environment negatively or being unsure what to rate it (aOR: 2.25; 95% CI: 1.51–3.33). In addition, those reporting poor mental health had higher odds of often or always feeling unable to schedule time with friends because of work (OR: 2.00; 95% CI: 1.33–3.00) compared with sometimes, rarely, or never. Finally, compared with the referent group, those reporting poorer mental health had higher odds of using substances to cope with work (aOR: 1.48; 95% CI: 1.04–2.11).

Discussion

Our analysis shows that LGBTQ workers reporting poorer mental health are more likely to be cisgender women or trans people, to be <35 years old, to work in low-wage service sector jobs, and to have incomes under $20,000/year. They are also more likely to rate their work environment as negative for LGBTQ employees or to be unsure about it, and to work in precarious work environments, as evidenced by higher odds of working in non-standard employment relationships and often or always being unable to schedule time with friends due to work scheduling. LGBTQ workers reporting poor mental health are also more likely to lack sufficient coping strategies, as they are more likely to use substances to cope with work.

The narrative in LGBTQ organizational studies has long been that blue collar industries will be the most negative for workers’ mental health; our study shows that it is in fact low-wage, customer-facing workers who have poorer mental health. This suggests that the challenges experienced by LGBTQ in work environments that are gendered as masculine may be partially offset by the greater stability, income security and benefits that are often associated with these jobs. It also suggests that low-wage service work, while having less rigid gender norms and an overrepresentation of LGBTQ workers, also involves elements of precarity, low income, and customer interaction that can ultimately be detrimental to the mental health of LGBTQ people. This finding is important because LGBTQ people, due to histories of discrimination in the relatively secure industrial sectors, are overrepresented in the low-wage service jobs that now characterize post-industrial, economically transitioning areas.

Relatedly, our results extend organizational research about LGBTQ inclusion that has often focused on the importance of supportive work cultures to the exclusion of other aspects of work quality. Our results show that supportive work cultures are protective measures for LGBTQ mental health, however, other work characteristics, are also important. Precarity, which is endemic to the locales in this study, emerged as a clear driver of poor mental health among LGBTQ people, as it is for the population as a whole. Those employed on a temporary, part-time or casual basis, or whose uncertain work schedules limit their times with friends, may have greater income fluctuation, less job security, and fewer employment related benefits causing poor mental health.

While precarious work affects LGBTQ people in ways that are similar to cisgender heterosexual population, it may be experienced differently or more severely by different segments of the LGBTQ community, particularly trans workers and to a lesser degree lesbian and bisexual women, who both had higher odds of poor mental health compared with cisgender gay and bisexual men. In the case of trans workers, the greater economic security, stability and extended health benefits typically associated with full-time permanent employment might help mediate distal or proximal stressors experienced at work or outside of work by providing workers with the ability to access mental health supports or take leaves. Additionally, if workers feel insecure at work and fear negative repercussions such as being assigned fewer shifts, they may be less likely to be open about their sexual or gender identity or to report discrimination with negative consequences for their mental health. In addition, people with lower incomes in precarious employment are likely to experience greater economic insecurity and be at greater risk of poor mental health than those with higher incomes. This finding corroborates and extends previous research showing that health effects of employment precarity are amplified for low-income populations [45] and women [33].

Our findings also challenge the idea of younger LGBTQ generations being more empowered; rather, mental health problems are on the rise among young people generally and for the LGBTQ workers in this study specifically. The higher frequency of poor mental health for this group may be brought on by economic insecurity and by working in low-wage service work environments where there is less investment in worker wellbeing compared with other sectors. This finding reaffirms previous research on LGBTQ youth and mental health, which has consistently shown relatively poor mental health outcomes compared to heterosexual and cisgender youth, and potentially greater risk of poor mental health among younger LGBTQ people compared with LGBTQ adults [46–48].

Although we did not include sexual orientation as a variable (i.e., separating lesbian, gay, bisexual, and pansexual identities), preliminary analysis confirmed previous research showing that bisexual people had more negative mental health outcomes than gay and lesbian respondents. Despite these findings, sexual orientation was omitted because it was conceptually confounded with gender identity and, therefore, was excluded to maintain a parsimonious model. Indeed, the terminology for sexual orientation used in the survey was not able to capture differences in sexual orientation among non-binary transgender respondents, since the labels ‘lesbian’ and ‘gay’ presume that one fits the gender binary, and were reported as pansexual. Additionally, data on race and ethnicity was omitted from the multivariate analysis since univariate analysis was insignificant.

Conclusions and limitations

Previous attention to LGBTQ mental health and work from a policy perspective has often focused on ensuring that workplaces are LGBTQ friendly. The results of this study reaffirm the importance of LGBTQ supportive workplaces for mental health while also calling attention to the importance of income and job security. Both inclusion and quality of work more generally are captured in the International Labour Organization’s concept of decent work, defined as “productive work for women and men in conditions of freedom, equity, security and human dignity” [49]. Remedies to poor mental health among LGBTQ populations, particularly trans people and low-income LGBTQ people, therefore, need to extend beyond employer and union driven inclusion strategies to address both the concentration of LGBTQ people in precarious work and the degradation of work more broadly. While targeted programs and strategies can address the former, the latter requires more widespread institutional change. Regulatory environments that require the provision of paid sick days, discourage employers from irregular scheduling and subcontracting, and facilitate collective organizing would have positively affect LGBTQ workers’ mental health. Additionally, state funded security measures such as easily accessible unemployment insurance, state pensions and universal mental health care (including mental health) would also benefit low-wage LGBTQ workers most at risk of poor mental health.

In the current Canadian context, results suggest that LGBTQ mental health supports should target unemployed and precariously employed LGBTQ people, alongside trans and low-income individuals. This includes community-level mental health supports that are free or low-cost for LGBTQ people who do not have access to mental health care through employment, and that accommodate irregular scheduling to ensure low-wage service workers have access. Employment training also needs to be integrated with mental health supports to provide pathways for LGBTQ youth to move into more stable, well-paid employment.

This study has some limitations. LGBTQ people with poor mental health might be more or less likely to be unemployed or employed in non-standard employment, as such there is the potential of a reverse relationship between mental health and labour market outcomes. While we sought to reduce recruitment bias by using in person, as well as digital recruitment techniques, the use of an internet survey and social media plateforms as a form of recruitment may have introduced selection bias in favour of younger, digitally literate respondents. We used a single-item scale for mental health which, though considered a reliable measure that decreases the burden for survey participants, lacks the complexity of multi-item measures [43]. Our study also did not fully capture the effect of education on mental health outcomes because of suspected collinearity with income and industry, nor were we able to measure the effects of sexual orientation, which was omitted due to aforementioned conceptual limitations in the survey. Additionally, in our analysis of the data we used complete case analysis and excluded respondents with missing values, which may have introduced bias into the model. Last, results may not be generalizable to the United States or to larger cities with greater levels of acceptance of LGBTQ people. We suspect that results are, however, generalizable since growth in services and specifically the low-wage service sector has been widespread across the Global North.

Supporting information

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Click here for additional data file. (24.4KB, docx)

Acknowledgments

Adriane Paavo, United Steelworkers; United Steelworkers local 6500; Sarah McCue, Unifor; Mélodie Bérubé and Scott Florence, Sudbury Workers Education and Advocacy Centre; and Paul Chislet, Windsor Workers Education Centre provided in-kind support and assistance with data collection; Randy Jackson provided guidance with survey design and community engagement. Laur O’Gorman; John Antoniw; Bobby Jay Aubin; Derrick Carl Biso; Dani Bobb; Vincent Bolt; Lynne Descary; Debra Dumouchelle; Mel Jobin; Paul Pasanen; Jennifer Johnson; Leah McGrath-Reynolds; Angela Di Nello; and Natalie Oswin assisted with instrument design and data collection. Niko Yiannakoulias provided guidance with statistical analysis and revisions.

Data Availability

Data cannot be shared publicly as participants did not consent to the release of survey data in a public domain, nor was the public sharing of data cleared by the McMaster University Research Ethics Board. In addition, survey data holds sensitive information from LGBTQ workers in Windsor and Sudbury on their personal health and experiences of discrimination, including qualitative data from open-ended questions. Importantly, the LGBTQ populations in Windsor and Sudbury are relatively small, and thus publicly sharing data would compromise the level of risk of participating in the research—particularly given the marginalization that LGBTQ individuals already experience. Researchers who wish to access survey data are encouraged to contact the McMaster University Research Ethics Board to request access at ethicsoffice@mcmaster.ca, +1 (905) 525-9140 ext. 23142.

Funding Statement

SM received a Partnership Development Grant from the Social Sciences and Humanities Council of Canada, Award no. 890-216-0073 (www.sshrc-crsh.gc.ca). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Remya Lathabhavan

19 Jul 2022

PONE-D-22-12783Work-related stressors and mental health among LGBTQ workers: Results from a cross-sectional surveyPLOS ONE

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Reviewers' comments:

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Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #2: No

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Reviewer #2: Yes

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Reviewer #1: This is a well written manuscript, that I have enjoyed reading. The researchers are Weill organized and well informed. I specifically enjoyed the methodology and analysis parts. The discussion part is well written and reflective of the study expected outcomes.

Reviewer #2: Thank you for the opportunity to review “Work-related stressors and mental health among LGBTQ workers: Results from a cross-sectional survey.”

In general, it’s more appropriate in the context of discussing stressors and their effects to describe populations as “marginalized” rather than “vulnerable.” Marginalized is what happens to a group, vulnerable more often describes an innate quality.

Why wasn’t sexual orientation appropriately measured and included? The literature often shows that persons with non-monosexual identities (e.g., bisexual, pansexual, etc) fair worse than persons with monosexual identities (e.g., straight, gay, lesbian).

Why was race excluded from the analysis? The assumption that including it would introduce bias is an incomplete assumption that requires further support if its to pass muster.

Abstract:

Purpose: consider replacing “vulnerable” with “marginalized” when describing LGBTQ populations.

Methods: Include how and when respondents were surveyed. Describe referent group in methods. What constitutes “good mental health” in the context of this study?

Results: Delete “compared with a referent group with good mental health” as this doesn’t not clarify the results subsequently presented.

Conclusion: Clear and concise.

Introduction:

Page 3, Line 60: Please use a more recent reference to describe LGBTQ well-being; 2008 is already outdated by more than a decade.

Page 3, Line 61: you’ve reversed the definition of distal (external) and proximal (internal) stressors. Please verify your definitions at the outset.

Page 3, Line 65: turn to Meyer and Hatzenbuehler to describe additional distal stressors that occur on a more global scale (e.g., policies affecting LGBTQ life): https://pubmed.ncbi.nlm.nih.gov/?term=hatzenbuehler+stigma

Page 3, Line 70: I would note that there are disparities in access to employment for LGBTQ persons. UPDATE: I see this is well discussed later in the introduction at Line 93.

Page 4, Line 84: there are also differential experiences across sectors, even among health professions: https://pubmed.ncbi.nlm.nih.gov/28537796/

Page 5, Line 95: great introduction to factors associated with wellbeing related to work environment.

Page 5, Line 116: I suggest taking Minority Stress Theory further to include physical health outcomes as they relate to stress. This has been explored more recently in cardiovascular health as it relates to minority stress and disparities in risk factors as a result of stress:

https://www.ahajournals.org/doi/10.1161/CIR.0000000000000914

https://www.ahajournals.org/doi/full/10.1161/CIR.0000000000001003

Page 6, Line 112: desase = disease

Methods:

Great recruitment methods to reach LGBTQ persons.

How was LGBTQ identity ascertained?

Why were non-LGBTQ persons excluded?

Page 8, Line 173: Modeled how?

Page 8, Line 179: their mental what?

Page 9, Line 191: why was 35 the dividing point?

Page 9, Line 195: Why is income divided at $20,000? Why not a poverty level to account for variation between cities?

Page 10, Line 217: work environment is way too subjective here. Why not include measures of existing workplace protections? Explicit support of LGBTQ persons, etc?

Page 10, Line 218: why wasn’t tobacco considered as a substance for coping with stress?

Page 10, Line 227: style suggestion, “participants with complete outcome and descriptive data were included in regression models.” Excluding missing data may in fact introduce bias; Line 228-230 is not an appropriate assumption.

Results:

Page 11, Line 249: style suggestion, “those with poorer mental health” is actually “those who reported poorer mental health.” There are differences by gender in how people report mental health. As no objective measure of mental health were utilized, I caution saying who had poor mental health and instead frame it as those who reported it. People can have poor mental health without reporting it.

Otherwise, a clear presentation of results.

Discussion:

Page 16, Line 316: this study doesn’t have a variable for “male-dominated industries” so cannot speak to whether or not this is a factor in the mental health of the respondents.

Page 18, Line 360: why was the measure for sexual orientation not able to accurately capture respondent’s sexual identity? What preliminary analyses were conducted? Please ensure this is included in supplementary materials.

Page 18, Line 367: the exclusion of race data is highly problematic and flattens the experience of persons with multiply marginalized identities.

Conclusions and Limitations.

These suggestions to improve the work environment are lackluster. Be more specific and discuss institutional as well as policy-level interventions.

**********

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Reviewer #1: No

Reviewer #2: No

**********

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PLoS One. 2022 Oct 25;17(10):e0275771. doi: 10.1371/journal.pone.0275771.r002

Author response to Decision Letter 0

5 Sep 2022

We are very grateful to the editor and reviewers for your thoughtful comments on our manuscript. We address each of the comments in greater detail below. If there are any other comments or points that arise during the review process, please let us know.

Editor’s comments:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

a. The manuscript has been reviewed to ensure that it meets the PLOS ONE style requirements, including naming conventions for files.

2. You indicated that you had ethical approval for your study. In your Methods section, please ensure you have also stated whether you obtained consent from parents or guardians of the minors included in the study or whether the research ethics committee or IRB specifically waived the need for their consent.

a. Thank you for this comment. Parental consent was not required for participants ages 16 and 17 given the potential social risks of involving family members in research about LGBTQ+ identity. This was cleared by the McMaster Research Ethics Board. The manuscript’s methods section has been updated to include this information.

3. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

a. The Data Availability statement has been updated to describe, in detail, the ethical restrictions that limit our ability to share the data publicly. Researchers who are looking to access the underlying data are instructed to contact the McMaster Research Ethics Board and are provided with the relevant contact information. The revised statement reads as follows:

“Data cannot be shared publicly as participants did not consent to the release of survey data in a public domain, nor was the public sharing of data cleared by the McMaster University Research Ethics Board. In addition, survey data holds sensitive information from LGBTQ workers in Windsor and Sudbury on their personal health and experiences of discrimination, including qualitative data from open-ended questions. Importantly, the LGBTQ populations in Windsor and Sudbury are relatively small, and thus publicly sharing data would compromise the level of risk of participating in the research—particularly given the marginalization that LGBTQ individuals already experience. Researchers who wish to access survey data are encouraged to contact the McMaster University Research Ethics Board to request access at ethicsoffice@mcmaster.ca, +1 (905) 525-9140 ext. 23142.”

4. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well.

a. The manuscript’s methods section has been updated to include an ethics subsection, which stipulates that the project was cleared by the McMaster Research Ethics Board (MREB#1866), and the ways consent was obtained for the online and paper surveys.

Reviewer #2’s comments:

1. In general, it’s more appropriate in the context of discussing stressors and their effects to describe populations as “marginalized” rather than “vulnerable.” Marginalized is what happens to a group, vulnerable more often describes an innate quality.

a. Thank you for this comment. We have replaced the word ‘vulnerable’ with ‘marginalized’ in the manuscript.

2. Why wasn’t sexual orientation appropriately measured and included? The literature often shows that persons with non-monosexual identities (e.g., bisexual, pansexual, etc) fair worse than persons with monosexual identities (e.g., straight, gay, lesbian).

a. Thank you for drawing attention to this important topic. There are two reasons why sexual orientation was excluded from our analysis. First, given our small sample size, we needed to make strategic decisions on what to include in order to balance building a comprehensive model while also ensuring the model was appropriately parsimonious. This was further complicated by our need to include workplace factors, which were our primary variables of interest. Secondly, while we are aware that bisexual people typically experience poorer mental health outcomes when compared to heterosexual, gay, and lesbian individuals, we also experienced a conceptual challenge that bolstered our decision to not include the sexual orientation variable; since the labels ‘lesbian’ and ‘gay’ presume that one fits the gender binary, people with a non-binary gender identity become classified as pansexual, regardless of differences in their attraction. Therefore, the variables of sexual orientation and gender identity are not conceptually distinct. Based on these two reasons, we excluded sexual orientation from our modelling, which is consistent with some other research on self-reported mental health and LGBTQ+ individuals (Streed Jr. et al., 2018). The manuscript has been updated to add greater detail to this reasoning. We have also expanded the limitations section of the manuscript to include this as a limitation of the study.

3. Why was race excluded from the analysis? The assumption that including it would introduce bias is an incomplete assumption that requires further support if it’s to pass muster.

a. Thank you for this very important comment. To address this, we have included the race and ethnicity variable in the univariate analysis. Due to a lack of statistical significance, the variable was omitted from the final model. We have removed from the manuscript any references to reporting bias in race/ethnicity data.

4. Abstract: Purpose: consider replacing “vulnerable” with “marginalized” when describing LGBTQ populations.

a. As stated above, all uses of the word ‘vulnerable’ to describe a group have been replaced with ‘marginalized’.

5. Abstract: Methods: Include how and when respondents were surveyed. Describe referent group in methods. What constitutes “good mental health” in the context of this study?

a. The methods section of the abstract has been updated to state that the survey was administered online between July 6 and December 2, 2018, and that ‘good mental health’ was a self-rated measure on a five-point Likert scale that asked about participants’ mental health in general.

6. Abstract: Results: Delete “compared with a referent group with good mental health” as this doesn’t not clarify the results subsequently presented

a. This sentence has been removed from the results section of the abstract.

7. Page 3, Line 60: Please use a more recent reference to describe LGBTQ well-being; 2008 is already outdated by more than a decade.

a. The citation from 2008 has been replaced with a more recent article on LGBTQ+ well-being.

8. Page 3, Line 61: you’ve reversed the definition of distal (external) and proximal (internal) stressors. Please verify your definitions at the outset.

a. Thank you for catching this. This line has been revised to reflect the proper definitions of distal and proximal stressors.

9. Page 3, Line 65: turn to Meyer and Hatzenbuehler to describe additional distal stressors that occur on a more global scale (e.g., policies affecting LGBTQ life): https://pubmed.ncbi.nlm.nih.gov/?term=hatzenbuehler+stigma

a. We appreciate this suggestion and have added a sentence on structural stigma and the socio-legal dimensions of minority stress.

10. Page 4, Line 84: there are also differential experiences across sectors, even among health professions: https://pubmed.ncbi.nlm.nih.gov/28537796/

a. This is important nuance. We have added a sentence on how, even in sectors that are ostensibly progressive, LGBTQ workers can experiences stressors.

11. Page 5, Line 116: I suggest taking Minority Stress Theory further to include physical health outcomes as they relate to stress. This has been explored more recently in cardiovascular health as it relates to minority stress and disparities in risk factors as a result of stress:

https://www.ahajournals.org/doi/10.1161/CIR.0000000000000914 https://www.ahajournals.org/doi/full/10.1161/CIR.0000000000001003

a. Thank you for this suggestion. The physiological effects of minority stress are now included in the literature review.

12. Page 6, Line 112: desase = disease

a. This spelling mistake has been corrected.

13. Great recruitment methods to reach LGBTQ persons. How was LGBTQ identity ascertained?

a. The manuscript has been updated to explain that, prior to completing the survey, participants were required to complete a pre-survey to determine eligibility. This survey included a question on whether they self-identified as LGBTQ.

14. Why were non-LGBTQ persons excluded?

a. The methods section has been updated to explain that, given the exploratory nature of the study which focused on the work and community experiences of LGBTQ workers, non-LGBTQ persons were excluded from participating. Indeed, the experiences of non-LGBTQ people were outside of the scope of this study.

15. Page 8, Line 173: Modeled how?

a. This line has been updated to explain that the data was modelled using ordered logistic regression.

16. Page 8, Line 179: their mental what?

a. Thank you for catching this. This line has been updated to specify mental ‘health’.

17. Page 9, Line 191: why was 35 the dividing point?

a. We chose 35 as the dividing point for the age variable since previous research on career trajectories has identified 35 as the beginning of ‘midlife’ (Ferraro et al., 2018). In addition, many unions’ young workers’ committees define ‘young workers’ as those under the age of 35.

18. Page 9, Line 195: Why is income divided at $20,000? Why not a poverty level to account for variation between cities?

a. The survey question for income was ordinal, and asked participants to select the income range that best reflected their income. The options for this question were in $10,000 increments—following Statistics Canada—and, given the lack of granularity in the measure, the $20,000 cut-off best represented participants living below the poverty line in both cities.

19. Page 10, Line 217: work environment is way too subjective here. Why not include measures of existing workplace protections? Explicit support of LGBTQ persons, etc.?

a. Thank you for this comment. While we understand your concern, we believe that the subjective measure of work environment (which encompasses participants’ perceptions of policy, attitudes of co-workers and management, and symbolic supports) is appropriate here for two reasons. First, polices and supports vary across workplaces and industries, and given the project’s varied industrial makeup, a self-reported measure allows for a single variable that accounts for participants’ perceptions of their work environment across sectors. In addition, there is evidence that workplace protections can be superficial and do not always make workers feel safe, particularly given the primacy of LGBTQ workers’ interpersonal relationships with co-workers, customers, and management in determining comfort at work (Tayar, 2017; Giuffre et al., 2008). Thus, a subjective measure of workplace environment allowed participants to take a holistic approach when considering their levels of safety and comfort at work.

20. Page 10, Line 218: why wasn’t tobacco considered as a substance for coping with stress?

a. The variable used to measure substance use included whether or not participants had used tobacco to cope with work, alongside other substances. Separate variables measuring the use of individual substances were excluded to maintain a parsimonious model.

21. Page 10, Line 227: style suggestion, “participants with complete outcome and descriptive data were included in regression models.”

a. Thank you for this style suggestion. We have incorporated this proposed change into the manuscript.

22. Excluding missing data may in fact introduce bias; Line 228-230 is not an appropriate assumption.

a. Thank you for this very important point. We have removed the claim that complete case analysis removes bias, and have added this as a limitation to the study at the end of the manuscript.

23. Page 11, Line 249: style suggestion, “those with poorer mental health” is actually “those who reported poorer mental health.” There are differences by gender in how people report mental health. As no objective measure of mental health were utilized, I caution saying who had poor mental health and instead frame it as those who reported it. People can have poor mental health without reporting it.

a. Thank you for this important comment. The manuscript has been updated to keep results consistent with the self-reported nature of the mental health variable.

24. Page 16, Line 316: this study doesn’t have a variable for “male-dominated industries” so cannot speak to whether or not this is a factor in the mental health of the respondents.

a. The phrase ‘male-dominated industries’ has been replaced with the language used in the industry variable, i.e., ‘blue collar industries’.

25. Page 18, Line 360: why was the measure for sexual orientation not able to accurately capture respondent’s sexual identity? What preliminary analyses were conducted? Please ensure this is included in supplementary materials.

a. See response #2 above.

26. Page 18, Line 367: the exclusion of race data is highly problematic and flattens the experience of persons with multiply marginalized identities.

a. See response #3 above. We have included race data in the univariate results, though this variable did not meet the conditions for inclusion in the final model.

27. Conclusions and limitations: These suggestions to improve the work environment are lackluster. Be more specific and discuss institutional as well as policy-level interventions.

a. Thank you for this comment. We have expanded the conclusion to include more specific interventions.

References:

Ferraro, H. S., Prussia, G., & Mehrotra, S. (2018). The impact of age norms on career transition intentions. Career Development International, 23(2), 212-229.

Giuffre, P., Dellinger, K., & Williams, C. L. (2008). “No retribution for being gay?”: Inequality in gay-friendly workplaces. Sociological Spectrum, 28(3), 254-277.

Streed Jr, C. G., McCarthy, E. P., & Haas, J. S. (2018). Self-reported physical and mental health of gender nonconforming transgender adults in the United States. LGBT health, 5(7), 443-448.

Tayar, M. (2017). Ranking LGBT inclusion: Diversity ranking systems as institutional archetypes. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l'Administration, 34(2), 198-210.

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Decision Letter 1

Remya Lathabhavan

26 Sep 2022

Work-related stressors and mental health among LGBTQ workers: Results from a cross-sectional survey

PONE-D-22-12783R1

Dear Dr. Mills,

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Acceptance letter

Remya Lathabhavan

17 Oct 2022

PONE-D-22-12783R1

Work-related stressors and mental health among LGBTQ workers: Results from a cross-sectional survey

Dear Dr. Mills:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

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    Data Availability Statement

    Data cannot be shared publicly as participants did not consent to the release of survey data in a public domain, nor was the public sharing of data cleared by the McMaster University Research Ethics Board. In addition, survey data holds sensitive information from LGBTQ workers in Windsor and Sudbury on their personal health and experiences of discrimination, including qualitative data from open-ended questions. Importantly, the LGBTQ populations in Windsor and Sudbury are relatively small, and thus publicly sharing data would compromise the level of risk of participating in the research—particularly given the marginalization that LGBTQ individuals already experience. Researchers who wish to access survey data are encouraged to contact the McMaster University Research Ethics Board to request access at ethicsoffice@mcmaster.ca, +1 (905) 525-9140 ext. 23142.

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