Background
Same-sex attracted women (SSAW) are more likely than heterosexual women to experience depression, anxiety, and substance use disorders [
1,
2]. In the Australian National Survey of Mental Health and Wellbeing [
3], the most commonly reported past 12 month mental disorders experienced by homosexual/bisexual respondents were anxiety disorders (31.5 %), affective disorders (19.2 %), and substance use disorders (8.6 %), compared with the heterosexual sample (14.1 %, 6.0 %, and 5.0 % respectively). Specifically among women, bisexual women in the Australian Longitudinal Study on Women’s Health (ALSWH) reported the highest levels of perceived stress, depression symptoms, anxiety symptoms, and the lowest scores on the mental health index and the social support scale [
4]. Transgender people also experience very high levels of mental health problems. In an Australian study of 482 trans women and 232 trans men, 43.7 % currently had clinically relevant depressive symptoms; 28.8 % had major depressive disorder; 18.3 % had a panic syndrome; and 16.9 % another anxiety disorder [
5]. Moreover, 57.2 % had ever been diagnosed with depression, and 39.9 % ever diagnosed with an anxiety disorder.
Experiences of discrimination, abuse and victimisation have been consistently identified as risk factors for mental health disorders amongst these population subgroups. For example, in an Australian convenience sample of gay, lesbian, bisexual, transgender and intersex (LGBTI) people, 49.2 % of trans women and 30.9 % bisexual women had experienced at least one incident of heterosexist abuse in the previous year [
6]. There was a direct relationship between having experienced abuse and higher levels of psychological distress. High levels of substance abuse are also reported amongst SSAW compared with heterosexual women [
4], which is associated with mental health problems, both as a risk and causative factor. Bisexual women are even more likely than lesbians to have re-victimisation experiences and more harmful alcohol use [
7]. Conversely, social support and community connectedness are protective factors for the mental health of SSAW [
8,
9].
Given the higher prevalence of mental health disorders, we should expect higher utilisation of mental health services by SSAW than heterosexual women, and this is found to be the case [
10,
11]. Peer support is also a common form of help seeking amongst women in general, and there is some evidence that SSAW are more likely to access self-help then heterosexual women [
10]. Complementary and alternative medicine (CAM) use is also more likely amongst SSAW [
12‐
14]. Data from the ALSWH revealed that lesbian and bisexual women were significantly more likely than heterosexual women to have used health services, however their satisfaction with these services and continuity of care were significantly lower [
15]. Several barriers to effective mental health service provision for this group have been identified and categorised as external and internal barriers. External barriers are perceived inadequacies with the service such as a provider’s lack of cultural competence [
16], and internal barriers include fear of mistreatment or lack of readiness to seek help [
17,
18]. For example, up to 60 % of SSAW have reported negative or mixed reactions from mental health service providers towards their sexual orientation [
19]. Online therapeutic services are increasingly available, but again are perceived to be inadequate. The majority of lesbian and gay people in an Australian focus group study felt that e-therapies should be more inclusive; that they should include stigma-related challenges faced by lesbians and gay men, and cater to vulnerable subpopulations [
20]. Most participants believed that they were rendered invisible due to the lack of overt acknowledgement of non-heterosexuals in current online services.
There are several gaps in the literature that the current study aimed to address. Firstly, previous studies have not adequately examined help seeking behaviour and service use across the various categories of support, namely formal (professional) services including CAM, and informal services including social support and self-help. Few studies have examined patterns of help seeking among sexual minority subgroups. The majority of previous research has broadly compared heterosexuals with LGB people, and lesbian and bisexual women are often grouped together. This is problematic because sexual minority subgroups are very diverse and the issues faced by each group are not necessarily comparable [
21]. Recent literature recommends the development of health promotion campaigns and messages to reduce harmful effects of substance abuse and other mental health risk factors that are tailored to specific population subgroups [
22], however this is not possible until the different subgroups and their mental health service needs are identified. Therefore, the aims of the study were first to describe the mental health of the study sample and demographic associations with mental health. Second, to improve knowledge on help-seeking behaviours including types of services used by a diverse range of same-sex attracted women, based on their sexual orientation and gender identity. Third, to identify other demographic associations, barriers and enablers to help seeking. Finally, to identify priorities for targeted mental health promotion messaging for same sex attracted women.
The study hypotheses were first, that study participants would have differing levels of mental health depending on their sexual orientation and gender identity, with worse mental health amongst more marginal identity groups. This in part relates to our second hypothesis that community connectedness would be associated with better mental health, as we would expect that those with less marginal identities would be more community connected. Third, that levels of help seeking would be associated with levels of mental health need, but reduced by lack of community connectedness. Finally, we expected to identify distinct health promotion messaging that applied to same sex attracted women.
Results
Sample
The eight key stakeholders included five women, one man, one trans man, and one gender queer person. Key stakeholders were not questioned about their sexual orientation. One person identified as Aboriginal. Three key stakeholders lived in Sydney, New South Wales, two were from regional centres in Queensland, one was from Victoria, one from Tasmania, and one from Western Australia, with all three of these residing in capital cities. Three of the key stakeholders were AIDS Council CEOs; one was an LGBTI mental health organisation coordinator; one was an LGBTI ageing organisation president; two were staff at a national LGBTI health organisation; and one was a LGBTI youth service coordinator.
The survey sample included 1628 people who answered a majority of the questions. The target population was any woman who was same sex attracted and people who were trans or gender diverse. People with a wide diversity of gender identities responded, a majority identifying as female, and 84 identifying as trans female (Table
1). Almost 10 % identified as other gender identities including 38 as other (gender diverse, gender queer, non-binary gender) and 10 as agender. Nine trans male participants were excluded from the analyses. Unfortunately, there were only 24 intersex identified participants, so they were analysed within the ‘other gender’ group, although we acknowledge that intersex status is not regarded as a gender identity. Lesbian, bisexual, queer and pansexual (people who are attracted to people of non-binary gender) were the most common sexual identity groups. The ‘other’ sexual orientation groups included 27 unsure, 22 asexual, 23 heterosexual (all trans or gender diverse people) and 38 listing ‘other’.
The mean age of the sample was 34.09 years with a range from 18 to 81, and there were significant differences in age according to gender identity and sexual orientation (Table
1). Lesbian identified women and trans females were more likely to be older. The majority of the bisexual, pansexual and other sexual identities were under 30, as were people with diverse gender identities. These diverse identities are emerging particularly amongst young people. By emerging, we mean they are terms and identities that have only recently been used by people over the past 5 years or so, whereas before they may have identified under the broader banners of lesbian, bisexual, or transgender.
There were several other significant demographic differences amongst the various gender identity and sexual orientation subgroups (Table
2). Female identified participants more commonly reported homelessness than gender diverse people. Lesbian and female identified respondents most frequently achieved a university degree or higher and had a higher income. Despite relatively high education levels, only 18.2 % of the sample earned more than $75,000 per annum. Lesbian and female identified participants were more likely to be in a relationship with one person than bisexual, trans female, and other gender identified participants. Lesbians were significantly more likely to report being in a relationship with a woman.
Mental health of the survey sample
A high proportion (80 %) of the total sample perceived that they had mental health problems over the past 12 months. Perceived physical health problems were also high (73 %), and 39.5 % had a chronic illness or disability. The perception of mental health problems was correlated with high scores on the anxiety and depression scales (Table
10). As we hypothesised, there were significant differences according to gender identity and sexual orientation (Table
3). Trans females and gender diverse participants were twice as likely as female participants to be stressed (PSQYW) or distressed (K10), and more likely to be depressed (CES-D). Lesbian women were least likely of all sexual orientation groups to be stressed, distressed, depressed or anxious.
Table 3
Gender identity and sexual orientation differences in number of participants with clinically significant levels of self-reported symptoms of mental illness
Gender identity |
p < .001 |
p < .001 |
p < .001 |
p = .10* |
p = .01 |
Female | 1178 | 16.6 | 1162 | 27.7 | 1156 | 54.2 | 1152 | 97.4 | 1277 | 78.9 |
Trans female | 76 | 30.3 | 76 | 51.3 | 76 | 67.1 | 76 | 96.1 | 80 | 85.0 |
Other | 138 | 31.2 | 136 | 53.7 | 135 | 76.3 | 135 | 100.0 | 151 | 88.1 |
Sexual orientation |
p < .001 |
p < .001 |
p < .001 |
p = .03* |
p < .001 |
Lesbian | 739 | 14.2 | 728 | 23.9 | 728 | 49.0 | 726 | 96.4 | 798 | 74.8 |
Queer | 195 | 25.1 | 194 | 35.1 | 191 | 60.2 | 191 | 100.0 | 219 | 85.8 |
Bi-sexual | 242 | 21.9 | 240 | 37.9 | 238 | 65.1 | 236 | 98.7 | 262 | 82.8 |
Pan-sexual | 131 | 32.1 | 128 | 45.3 | 128 | 73.4 | 128 | 97.7 | 136 | 91.9 |
Other | 86 | 15.1 | 85 | 50.6 | 83 | 72.3 | 83 | 98.8 | 94 | 87.2 |
Mental health differences according to demographic variables
Univariate analyses showed several other demographic variables that influenced mental health including age, education, income, relationship status, parenting status and homelessness. Ever experiencing homelessness had the strongest relationship of any demographics to stress (odds ratio 2.61), distress (OR 2.01) and depression (OR 1.88), and also influenced increased help seeking. These variables were added to binary logistic regression analyses for each of the four mental health variables (Tables
4,
5,
6 and
7) and after adjustment there were still several significant differences according to diverse gender identities and sexual orientations. Note that homelessness did not significantly differ among sexual orientation subgroups and therefore was only included in analyses for gender identity. Stress was influenced particularly by homelessness, lower age and income, not being in a relationship, and diverse gender identity (Table
4). Distress was strongly influenced by all demographic variables, including diverse gender and sexual identities (Table
5). Depression was affected by all demographics except parenting status, with diverse gender identity moderately influential (Table
6). Conversely, low income was the only significant demographic to influence anxiety after adjustment (Table
7). Therefore, diverse gender identities had a strong relationship to distress (OR 1.41) and moderate relationship with stress and depression. Diverse sexual orientations had a small relationship (low ORs) with distress and depression. Anxiety levels were very high across the sample, and did not significantly differ with different gender identities or sexual orientations.
Table 4
Binary logistic regression models for predicting higha perceived stress
Gender identity | <.001 | 1.56 | 1.29 | 1.88 | .02 | 1.27 | 1.03 | 1.56 |
Age | <.001 | 0.55 | 0.44 | 0.68 | .001 | 0.60 | 0.45 | 0.80 |
Education | <.001 | 0.70 | 0.62 | 0.80 | .30 | 0.93 | 0.80 | 1.07 |
Income | <.001 | 0.68 | 0.61 | 0.76 | <.001 | 0.79 | 0.70 | 0.89 |
Relationship | .03 | 0.73 | 0.56 | 0.97 | .93 | 0.99 | 0.73 | 1.34 |
Homelessness | <.001 | 2.78 | 2.19 | 3.54 | <.001 | 2.61 | 2.01 | 3.38 |
Children | .14 | 0.79 | 0.58 | 1.08 | .11 | 1.37 | 0.94 | 2.01 |
Sexual orientation | <.001 | 1.20 | 1.08 | 1.32 | .41 | 1.05 | 0.94 | 1.17 |
Age | <.001 | 0.55 | 0.44 | 0.68 | .03 | 0.74 | 0.57 | 0.96 |
Education | <.001 | 0.70 | 0.62 | 0.80 | .06 | 0.87 | 0.76 | 1.01 |
Income | <.001 | 0.68 | 0.61 | 0.76 | <.001 | 0.74 | 0.66 | 0.84 |
Relationship | .03 | 0.73 | 0.56 | 0.97 | .69 | 0.94 | 0.70 | 1.26 |
Children | .14 | 0.79 | 0.58 | 1.08 | .08 | 1.39 | 0.96 | 2.01 |
Table 5
Binary logistic regression models for predicting higha distress
Gender identity | <.001 | 1.82 | 1.53 | 2.17 | .001 | 1.41 | 1.16 | 1.72 |
Age | <.001 | 0.39 | 0.32 | 0.47 | <.001 | 0.61 | 0.48 | 0.78 |
Education | <.001 | 0.55 | 0.49 | 0.61 | <.001 | 0.73 | 0.64 | 0.83 |
Income | <.001 | 0.60 | 0.54 | 0.66 | <.001 | 0.78 | 0.70 | 0.87 |
Relationship | <.001 | 0.49 | 0.39 | 0.62 | .03 | 0.75 | 0.58 | 0.98 |
Homelessness | <.001 | 2.12 | 1.72 | 2.63 | <.001 | 2.01 | 1.58 | 2.56 |
Children | <.001 | 0.39 | 0.29 | 0.52 | .04 | 0.69 | 0.49 | 0.98 |
Sexual orientation | <.001 | 1.36 | 1.25 | 1.49 | .03 | 1.11 | 1.01 | 1.23 |
Age | <.001 | 0.39 | 0.32 | 0.47 | .01 | 0.73 | 0.58 | 0.91 |
Education | <.001 | 0.55 | 0.49 | 0.61 | <.001 | 0.70 | 0.62 | 0.80 |
Income | <.001 | 0.60 | 0.54 | 0.66 | <.001 | 0.76 | 0.68 | 0.84 |
Relationship | <.001 | 0.49 | 0.39 | 0.62 | .02 | 0.73 | 0.57 | 0.95 |
Children | <.001 | 0.39 | 0.29 | 0.52 | .05 | 0.71 | 0.51 | 0.99 |
Table 6
Binary logistic regression models for predicting high symptoms of depression
Gender identity | <.001 | 1.66 | 1.37 | 2.02 | .02 | 1.30 | 1.05 | 1.61 |
Age | <.001 | 0.49 | 0.42 | 0.58 | .004 | 0.73 | 0.59 | 0.91 |
Education | <.001 | 0.55 | 0.49 | 0.61 | <.001 | 0.70 | 0.62 | 0.79 |
Income | <.001 | 0.66 | 0.62 | 0.71 | <.001 | 0.81 | 0.75 | 0.88 |
Relationship | <.001 | 0.46 | 0.37 | 0.59 | .01 | 0.66 | 0.51 | 0.85 |
Homelessness | <.001 | 2.07 | 1.66 | 2.58 | <.001 | 1.88 | 1.47 | 2.40 |
Children | <.001 | 0.53 | 0.42 | 0.67 | .31 | 0.86 | 0.64 | 1.15 |
Sexual orientation | <.001 | 1.36 | 1.24 | 1.49 | .01 | 1.14 | 1.03 | 1.26 |
Age | <.001 | 0.49 | 0.42 | 0.58 | .08 | 0.83 | 0.67 | 1.02 |
Education | <.001 | 0.55 | 0.49 | 0.61 | <.001 | 0.68 | 0.60 | 0.77 |
Income | <.001 | 0.66 | 0.62 | 0.71 | <.001 | 0.79 | 0.73 | 0.86 |
Relationship | <.001 | 0.46 | 0.37 | 0.59 | .001 | 0.66 | 0.51 | 0.85 |
Children | <.001 | 0.53 | 0.42 | 0.67 | .35 | 0.88 | 0.66 | 1.16 |
Table 7
Binary logistic regression models for predicting higha anxiety
Gender identity | .15 | 1.95 | 0.79 | 4.86 | .17 | 1.96 | 0.74 | 5.18 |
Age | .01 | 0.51 | 0.31 | 0.84 | .23 | 0.69 | 0.37 | 1.27 |
Education | .49 | 0.89 | 0.65 | 1.23 | .24 | 1.25 | 0.86 | 1.82 |
Income | <.001 | 0.74 | 0.63 | 0.86 | .001 | 0.73 | 0.61 | 0.88 |
Relationship | .79 | 1.10 | 0.54 | 2.26 | .25 | 1.57 | 0.73 | 3.38 |
Homelessness | 1.00 | 1.00 | 0.52 | 1.92 | .82 | 0.92 | 0.46 | 1.83 |
Children | .06 | 0.51 | 0.25 | 1.03 | .52 | 0.78 | 0.36 | 1.67 |
Sexual orientation | .05 | 1.41 | 1.00 | 2.00 | .23 | 1.24 | 0.87 | 1.75 |
Age | .01 | 0.51 | 0.31 | 0.84 | .29 | 0.72 | 0.39 | 1.33 |
Education | .49 | 0.89 | 0.65 | 1.23 | .25 | 1.24 | 0.86 | 1.80 |
Income | <.001 | 0.74 | 0.63 | 0.86 | .001 | 0.74 | 0.62 | 0.89 |
Relationship | .79 | 1.10 | 0.54 | 2.26 | .23 | 1.60 | 0.74 | 3.45 |
Children | .06 | 0.51 | 0.25 | 1.03 | .49 | 0.76 | 0.36 | 1.64 |
We hypothesised that community connectedness would positively correlate with mental health. We found that overall there were high levels of connection, particularly to LGBTI communities, but also to mainstream communities, relative to LGBT community sample means [
23]. The levels of LGBTI and mainstream connection varied little according to gender identity and sexual orientation. We report correlations with mental health using r statistics in Table
10. Higher LGBTI connectedness was weakly correlated with higher levels of stress, but not with any of the other mental health variables. Mainstream connectedness was weakly correlated with lower levels of stress, distress, depression and anxiety.
Help seeking for mental health issues
Overall, a high proportion of the sample had sought help over the previous 12 months, both using professional help and social support. The types of professional help seeking included 74.4 % of people seeing a GP at least once, 44.3 % seeing a psychologist/counsellor, 23.3 % seeing an allied health professional, 14 % seeing a psychiatrist, 22.2 % other specialist doctors, and 10.4 % using telephone counselling. Just 6.8 % had not accessed any professional support. Social help seeking with family and/or friends was used by 74.7 %, 55.2 % used internet support, 18 % social organisations and 10.7 % used self-help or support groups. Only 6.3 % of participants had not accessed any social support. By contrast, 44.4 % of the sample had not used any form of CAM, 33.3 % used massage therapists, 11.1 % saw a naturopath or herbalist, and 8.3 % used acupuncture. The level of help seeking varied appropriately according to mental health need (Table
8).
Table 8
Prevalence of help seeking by mental health indicators and perceived need for mental health support
Professional help | | | | | | | | | |
GP | 85.2 | (1.3-1.4) | 85.4 | (24.1-25.2) | 85.4 | (11.6-12.4) | 85.3 | (15.2-15.7) | 84.8 |
Psychologist/counsellor | 50.8 | (1.5-1.6) | 51.0 | (26.6-28.0) | 51.0 | (13.1-14.1) | 51.1 | (16.0-16.7) | 59.7 |
Allied health professional | 26.6 | (1.4-1.5) | 26.6 | (24.0-26.0) | 26.7 | (11.4-12.8) | 26.6 | (15.1-16.1) | 26.3 |
Other specialist doctor | 25.5 | (1.2-1.4) | 25.7 | (22.9-25.0) | 25.6 | (10.9-12.4) | 25.6 | (14.7-15.6) | 22.2 |
Psychiatrist | 15.9 | (1.6-1.8) | 15.9 | (29.7-32.2) | 15.8 | (15.7-17.4) | 15.8 | (17.0-18.3) | 18.8 |
Telephone counselling/helpline | 12.0 | (1.7-1.9) | 12.0 | (29.0-31.9) | 12.0 | (14.8-17.0) | 12.0 | (17.4-18.8) | 14.1 |
None | 7.4 | (0.9-1.2) | 7.3 | (20.8-24.3) | 7.3 | (9.2-11.5) | 7.3 | (14.0-15.8) | 6.0 |
Mental health nurse | 5.5 | (1.8-2.1) | 5.5 | (32.5-36.3) | 5.5 | (17.3-20.2) | 5.5 | (18.0-20.1) | 6.0 |
Other | 3.4 | (1.4-1.9) | 3.4 | (23.5-29.5) | 3.4 | (11.5-15.8) | 3.4 | (13.3-16.5) | 3.1 |
Informal help | | | | | | | | | |
Friends/family/partner | 85.1 | (1.3-1.4) | 85.0 | (24.0-25.1) | 85.0 | (11.3-12.1) | 85.0 | (15.2-15.7) | 86.2 |
The internet | 62.5 | (1.4-1.5) | 62.6 | (25.5-26.7) | 62.4 | (12.4-13.3) | 62.6 | (15.8-16.4) | 66.3 |
Social organisations | 21.0 | (1.5-1.7) | 21.2 | (25.1-27.2) | 21.1 | (12.0-13.5) | 21.1 | (15.5-16.6) | 22.2 |
Self-help/support group | 12.2 | (1.6-1.9) | 12.2 | (28.8-31.6) | 12.2 | (14.4-16.4) | 12.2 | (16.4-17.9) | 14.4 |
None | 7.0 | (0.9-1.2) | 7.1 | (18.7-22.8) | 7.2 | (8.1-11.1) | 7.1 | (12.6-14.5) | 4.4 |
Religious organisations | 3.4 | (1.4-1.7) | 3.3 | (25.1-31.3) | 3.4 | (12.1-16.6) | 3.4 | (15.4-18.5) | 3.5 |
Other | 2.3 | (1.3-1.7) | 2.3 | (20.4-25.4) | 2.3 | (7.8-12.8) | 2.3 | (12.8-15.5) | 2.6 |
Any complimentary help | 45.6 | (1.3-1.4) | 45.7 | (22.3-23.6) | 45.9 | (10.3-11.4) | 45.8 | (14.5-15.2) | 44.6 |
Help seeking prevalence did vary according to gender identity and sexual orientation (Table
9). Trans female participants appeared to be the highest users of services relative to other gender identities, and were also most likely to have participated in social organisations or support groups, but least likely to have sought help from friends or family. Other demographic variables were associated with higher levels of help seeking including having lower education and income levels, and living in urban areas; and younger participants were more likely to access social support. There were no differences according to relationship or parenting status.
Table 9
Prevalence of help seeking by gender identity and sexual orientation
Professional help | | | | | | | | |
GP | 76.7 | 86.9 | 75.9 | 79.1 | 82.5 | 74.9 | 74.5 | 68.9 |
Psychologist/counsellor | 43.9 | 57.1 | 57.4 | 41.7 | 54.7 | 46.0 | 58.4 | 47.2 |
Allied health professional | 24.6 | 17.9 | 23.5 | 24.8 | 27.8 | 20.6 | 22.1 | 26.4 |
Other specialist doctor | 22.2 | 40.5 | 19.8 | 23.9 | 27.4 | 20.2 | 18.1 | 21.7 |
Psychiatrist | 11.7 | 44.0 | 22.8 | 12.9 | 17.5 | 13.2 | 16.1 | 22.6 |
Telephone counselling/helpline | 9.9 | 13.1 | 17.3 | 8.4 | 13.7 | 12.5 | 16.8 | 12.3 |
None | 7.5 | 2.4 | 6.2 | 7.8 | 4.7 | 8.4 | 4.0 | 8.5 |
Mental health nurse | 3.7 | 8.3 | 11.7 | 4.5 | 6.8 | 3.5 | 5.4 | 5.7 |
Other | 2.7 | 2.4 | 5.6 | 2.5 | 3.4 | 2.8 | 2.7 | 6.6 |
Social help | | | | | | | | |
Friends/family/partner | 78.6 | 65.5 | 75.3 | 78.2 | 82.5 | 81.5 | 75.8 | 63.2 |
The internet | 55.8 | 56.0 | 70.4 | 51.8 | 66.2 | 58.9 | 71.1 | 65.1 |
Social organisations | 16.9 | 35.7 | 25.3 | 16.0 | 23.5 | 20.2 | 22.1 | 22.6 |
Self-help/support group | 9.9 | 22.6 | 15.4 | 8.3 | 14.1 | 12.5 | 14.1 | 20.8 |
None | 6.3 | 11.9 | 5.6 | 8.3 | 4.7 | 4.9 | 2.7 | 6.6 |
Religious organisations | 2.4 | 6.0 | 5.6 | 3.2 | 3.0 | 1.0 | 4.0 | 3.8 |
Other | 1.7 | 2.4 | 4.9 | 2.1 | 3.8 | 1.4 | 1.3 | 0.9 |
Any complimentary help | 44.7 | 17.9 | 29.0 | 46.2 | 50.9 | 39.7 | 27.5 | 16.0 |
Peer support groups were seen by key stakeholders as a crucial element of support for SSAW. They noted that many people turn to this type of help first before they seek professional help. However, there were several concerns about the reliance on peer support groups, including that they are often unfunded, can be difficult to find, can tend to exclude certain subgroups, and are often facilitated by people with no training in group management including conflict resolution and confidentiality. The key stakeholders identified several sub-groups that were unable to utilise peer-support within the LGBTI community due to a lack of connection (for example some older women and bisexual women) or fear of rejection including religious minority women, and women who don’t identify with any identity label. Also, preferences for family or community care over peer support were seen amongst indigenous and ethnic minority women.
General practice care was the most common source of professional help, particularly high amongst trans women (Table
9). Overall, 75.2 % of the sample had a regular GP, and 34.8 % had seen their GP at least four times over the past 12 months. Over half (56.8 %) believed that their GP knew about their sexual orientation, 18.8 % were not sure, and 24.4 % believed their GP did not know. GPs were most likely to know about sexual orientation for trans women (73.7 %) and lesbian women (71.5 %), and least likely for pansexual (30.3 %) and bisexual women (32.4 %). Having a regular GP was moderately correlated with seeking professional help (Table
10). Participants with a perceived mental health issue over the previous 12 months were less likely to have told their GP about their sexual orientation.
Table 10
Correlations between previous help seeking behaviour, mental and physical health indicators, perceived need for help, and community connectedness
1. Health professionals |
r
| 1 | | | | | | | | | | | | | |
|
n
| 1697 | | | | | | | | | | | | | |
2. Regular GPa
|
r
| .21***
| 1 | | | | | | | | | | | | |
|
n
| 1484 | 1484 | | | | | | | | | | | | |
3. Informal/self-help |
r
| .51***
| .01 | 1 | | | | | | | | | | | |
|
n
| 1697 | 1484 | 1697 | | | | | | | | | | | |
4. Comp./alt. medicine |
r
| .20***
| .06*
| .20***
| 1 | | | | | | | | | | |
|
n
| 1697 | 1484 | 1697 | 1697 | | | | | | | | | | |
5. Perceived stressb
|
r
| .32***
| -.02 | .26***
| -.04 | 1 | | | | | | | | | |
|
n
| 1393 | 1387 | 1393 | 1393 | 1393 | | | | | | | | | |
6. Distressc
|
r
| .28***
| -.06*
| .21***
| -.13***
| .62***
| 1 | | | | | | | | |
|
n
| 1375 | 1370 | 1375 | 1375 | 1375 | 1375 | | | | | | | | |
7. Depressiond
|
r
| .28***
| -.05 | .17***
| -.10 | .59***
| .88***
| 1 | | | | | | | |
|
n
| 1368 | 1363 | 1368 | 1368 | 1368 | 1366 | 1368 | | | | | | | |
8. Anxietye
|
r
| .22***
| -.06*
| .18***
| -.09 | .54***
| .73***
| .69***
| 1 | | | | | | |
|
n
| 1364 | 1359 | 1364 | 1364 | 1364 | 1363 | 1363 | 1364 | | | | | | |
9. Emotional/mental health problemsf
|
r
| .22***
| - | .23***
| .01 | .37***
| .42***
| .40***
| .33***
| 1 | | | | | |
|
n
| 1509 | - | 1509 | 1509 | 1391 | 1373 | 1366 | 1362 | 1509 | | | | | |
10. Physical health problemsg
|
r
| .25***
| - | .11***
| .14***
| .18***
| .11***
| .14***
| .10***
| - | 1 | | | | |
|
n
| 1502 | - | 1502 | 1502 | 1384 | 1366 | 1359 | 1355 | - | 1502 | | | | |
11. Resilienceh
|
r
| -.28***
| -.004 | -.20***
| .05 | -.43***
| -.55***
| -.56***
| -.43***
| -.36***
| -.11***
| 1 | | | |
|
n
| 1358 | 1353 | 1358 | 1358 | 1358 | 1357 | 1356 | 1355 | 1356 | 1349 | 1358 | | | |
12. Chronic illnessi
|
r
| .36***
| - | .15***
| -.01 | .24***
| .28***
| .29***
| .22***
| - | - | -.31***
| 1 | | |
|
n
| 1324 | - | 1324 | 1324 | 1324 | 1322 | 1321 | 1319 | - | - | 1322 | 1324 | | |
13. LGBTIj
|
r
| .09**
| .01 | .14***
| .06*
| .07**
| .01 | -.03 | .04 | -.02 | .001 | .04 | .02 | 1 | |
|
n
| 1560 | 1483 | 1560 | 1560 | 1393 | 1375 | 1368 | 1364 | 1508 | 1501 | 1358 | 1324 | 1560 | |
14. Mainstreamk
|
r
| -.05*
| .07**
| -.003 | .05*
| -.16***
| -.26***
| -.28***
| -.18***
| -.14***
| -.04 | .22***
| -.09**
| .21***
| 1 |
|
n
| 1557 | 1481 | 1557 | 1557 | 1392 | 1374 | 1367 | 1363 | 1506 | 1499 | 1357 | 1323 | 1557 | 1557 |
Very few participants (12.2 %, n = 179) had used LBGTI specific health services over the past 12 months. These services included LGBTI specific general practices, AIDS Councils, LGBTI friendly psychologists/ therapists, gender-specific services such as Gender centres and trans support groups, LGBTI support groups at University or online, and LGBTI specific youth or sexual health services. The majority of the services listed by participants were in inner urban locations, reflecting the lack of existing LGBTI specific services outside of these areas. The majority of help seeking therefore was through mainstream services.
Non-demographic associations with help seeking
We conducted correlation analyses using r-statistics to determine relationships between help seeking and mental health, physical health, resilience, community connectedness and perceived need for help (Table
10). All four mental health variables (stress, distress, depression and anxiety) were strongly correlated with each other, and they were strongly correlated with lower resilience.
Regarding help seeking behaviour, there was a correlation between professional help seeking and social help seeking, indicating that participants generally chose to seek help in both ways rather than one replacing the other. There were medium correlations between all mental health variables and seeking professional help, and weaker relationships with seeking social support, indicating that higher mental health care need was associated more with professional help seeking. This was also reflected in medium correlations with perceived mental health problems, and less so for perceived physical health problems. Resilience was also negatively correlated particularly with professional help seeking. Perceived physical health problems was correlated with all forms of professional help-seeking.
Barriers and enablers of help seeking in relation to sexual orientation and gender identity
We listed nine common barriers to help seeking (Table
11). Experiencing discrimination or judgement were consistently the most common barriers, followed by a lack of LGBTI sensitivity. Lack of readiness to seek help or self-reliance were common, and around one third were concerned about a lack of confidentiality. Discrimination was most problematic for gender diverse participants, and queer and pansexual people; and these same groups were also most affected by a lack of LGBTI sensitivity. Gender diverse and bisexual participants were most affected by a lack of readiness or self-reliance. Key stakeholders identified a pattern where negative experiences with mainstream care generated a lack of trust in many health professionals, and a reliance on untrained peer-support rather than professional support for some people.
Table 11
Barriers to help seeking for gender identities and sexual orientations
Gender Identity | | | | | | | | | | | | |
Female, n = 1390 | 896 | 64.5 | 710 | 51.1 | 550 | 39.6 | 604 | 43.5 | 321 | 23.1 | 123 | 8.8 |
Trans female, n = 84 | 60 | 71.4 | 32 | 38.1 | 38 | 45.2 | 27 | 32.1 | 32 | 38.1 | 8 | 9.5 |
Other, n = 162 | 128 | 79.0 | 95 | 58.6 | 81 | 50.0 | 78 | 48.1 | 59 | 36.4 | 5 | 3.1 |
Sexual Orientation | | | | | | | | | | | | |
Lesbian, n = 848 | 536 | 63.2 | 421 | 49.6 | 298 | 35.1 | 347 | 40.9 | 197 | 23.2 | 93 | 11.0 |
Queer, n = 234 | 179 | 76.5 | 144 | 61.5 | 111 | 47.4 | 106 | 45.3 | 65 | 27.8 | 10 | 4.3 |
Bisexual, n = 287 | 188 | 65.5 | 143 | 49.8 | 136 | 47.4 | 150 | 52.3 | 74 | 25.8 | 20 | 7.0 |
Pansexual, n = 149 | 113 | 75.8 | 92 | 61.7 | 71 | 47.7 | 66 | 44.3 | 43 | 28.9 | 5 | 3.4 |
Other, n = 106 | 69 | 65.1 | 38 | 35.8 | 53 | 50.0 | 40 | 37.7 | 33 | 31.1 | 8 | 7.5 |
Four groups of common enablers were listed in the survey (Table
12). The most commonly selected enabler was having a trustworthy GP by 62.4 % overall, followed by encouragement to get help by a friend or partner 44.6 %. Having a choice of provider was an enabler for up to one third of participants. Trans female compared with other genders and queer women compared with other sexual orientations were most likely to find LGBTI sensitivity enabling (Table
12). Encouragement to seek help by friends was most enabling for pansexual, bisexual and gender diverse participants.
Table 12
Enablers of help seeking for gender identities and sexual orientations
Gender Identity | | | | | | | | | | |
Female, n = 1390 | 934 | 67.2 | 604 | 43.5 | 389 | 28.0 | 545 | 39.2 | 164 | 11.8 |
Trans female, n = 84 | 67 | 79.8 | 43 | 51.2 | 19 | 22.6 | 34 | 40.5 | 7 | 8.3 |
Other, n = 162 | 112 | 69.1 | 72 | 44.4 | 53 | 32.7 | 73 | 45.1 | 13 | 8.0 |
Sexual Orientation | | | | | | | | | | |
Lesbian, n = 848 | 595 | 70.2 | 428 | 50.5 | 243 | 28.7 | 305 | 36.0 | 94 | 11.1 |
Queer, n = 234 | 179 | 76.5 | 119 | 50.9 | 79 | 33.8 | 98 | 41.9 | 20 | 8.5 |
Bisexual, n = 287 | 177 | 61.7 | 88 | 30.7 | 80 | 27.9 | 130 | 45.3 | 40 | 13.9 |
Pansexual, n = 149 | 99 | 66.4 | 58 | 38.9 | 41 | 27.5 | 74 | 49.7 | 14 | 9.4 |
Other, n = 106 | 64 | 60.4 | 27 | 25.5 | 19 | 17.9 | 45 | 42.5 | 16 | 15.1 |
Key stakeholders compared the use of mainstream health services with LGBTI-specific health services amongst SSAW. A consistent perspective was that it was particularly important for certain subgroups to have access to LGBTI inclusive mainstream mental health services. These groups included those that cannot or prefer not to access LGBTI specific services such as older women, remote or rural, cultural minorities, and indigenous women. They also identified specific services that need to be LGBTI inclusive such as those that provide primary care or deal with issues with a high degree of sensitivity. These included general practice, fertility/ gynaecology, emergency departments, women’s refuges, and domestic violence, homelessness, and mental health services.
There was also strong support for targeted mental health promotion for SSAW that highlights the specific issues affecting their mental health including discrimination, marginalisation both from mainstream and LGBTI communities, and the compounding effects of multiple identities. The key stakeholders encouraged the use of a strengths-based perspective in health promotion with three major themes: building self-esteem and normalising, encouraging help seeking including where to find LGBTI sensitive mainstream services or LGBTI specific services, and embracing diversity within LGBTI communities to overcome marginalisation.
Discussion
The diversity of the sample in terms of sexual orientation and gender identity was broad, which we suggest reflects a social trend of diversification within the LGBTI community. No longer does the acronym LGBTI accurately reflect the range of people that are connected with this community. Other Australian researchers have recently identified specific subgroups including queer women with higher rates of anti-LGBTI discrimination than lesbians [
31], and same-sex attracted men of diverse subcultural identities with more health disparities [
32]. In our study, there were significant differences in the mental health and help seeking behaviours among various subgroups. Those with more significant mental health disparities tended to be the people with identities including pansexual and queer identified women, and trans and gender diverse people. This extends the existing literature on the higher rates of depression and anxiety amongst bisexual women [
33,
34] and transgender women [
35] to include other subgroups. Some of the contributors to bisexual differences posited in the literature include marginalisation from both mainstream and LB communities, experiences of biphobia, internalised stigma, and a lack of established bisexual community [
34,
36,
37]. Distress amongst trans people is related to being victimised, lack of family support and lack of connection with LGBT peers [
35]. Marginalisation even within LGBTI communities is also likely to be influencing the mental health of the diverse subgroups that we have identified. We had expected that LGBTI community connection would correlate with better levels of mental health as seen in other work [
38,
39], however this was not the case, and indeed higher perceived stress was slightly correlated. It is possible that our results were influenced by issues of marginalisation amongst various subgroups, so that connection was being sought, but expectations of support were not being met due to identity policing, rejection or lack of organised and specific peer groups.
A further subgroup of note in our study were the people who had ever experienced homelessness (33.8 % of the sample). LGB people are over-represented in Australian national homelessness data, with 13.4 % heterosexuals ever having been homeless compared with 20.8 % bisexual people and 33.7 % lesbian/gay people [
40]. Higher rates and subsequent impacts of homelessness for LGBT people is an emerging issue [
41,
42] and should always be considered when examining the influences on mental health and help seeking disparities for LGBTI people.
Levels of depression, anxiety and stress in our study were much higher than those in an Australian population-based sample from the Australian Longitudinal Study of Women’s Health (ALSWH), despite similar demographic findings including income and education levels [
4]. For example, the mean perceived stress score in that study was 0.88 for heterosexual women, 1.04 for lesbians, and 1.34 for bisexual women (
p < .01); compared with scores in our study of 3.13 for lesbians and 3.36 for bisexuals. Similarly, proportions of women scoring in the depressed range on CES-D in the ALSWH varied with heterosexuals at 24.5 %, lesbians 28.6 % and bisexuals 44.4 %; compared with lesbians at 49.0 % and bisexuals at 65.1 % in our study. Therefore, we suggest that our study attracted people with much higher levels of mental health problems than expected for Australian same-sex attracted women generally, probably as our study was overtly focused on help seeking for mental health.
The levels of health service use for mental health problems over the previous 12 months were higher in our sample than those in the 2007 National Survey of Mental Health and Wellbeing. In our study, professional service use amongst people with depression included 85.4 % seeing a GP, 51 % seeing psychologist and 15.8 % seeing a psychiatrist; compared with 58.6 % seeing any service in the national survey [
43]. The use of services for those with anxiety in our study were 85.3 % seeing a GP, 51.1 % seeing a psychologist and 15.8 % seeing a psychiatrist, compared with 37.8 % seeing any service in the national survey. Even for those with severe mental health problems in the national survey, the rates of use in the past 12 months are much lower than in our survey for GP use 49.7 % (CI 39.6-59.8), psychologist 23.1 % (CI 16.1-30.1), but higher than our survey for psychiatrist use 19.4 % (CI 12.0-26.8) [
44]. So, it seems that professional health service use for equivalent levels of depression and anxiety in our study was higher than in the national study, indicating a willingness amongst people of diverse sexual and gender identities to seek help. This was also found in a UK population-based study, with higher usage of general practice and community support amongst the non-heterosexual group compared with heterosexuals [
1]. By contrast, the level of complimentary help seeking did not vary with the type or severity of mental health need. We consider that this suggests participants may have used this support for health maintenance rather than mental illness management.
Social support help seeking rates were very high across the range of participants in our study, and were correlated with all four mental health indicators, and perceived mental health problems. We consider that peer support is a crucial element of mental health care for these population groups, particularly as it is likely to contribute to high levels of encouragement by peers to seek help. In our sample, this encouragement was perceived to be an enabler of help seeking, particularly for the more potentially marginalised populations, such as gender diverse, trans, pansexual and bisexual identified people. They were also most likely to identify both discrimination/fear of judgement and a lack of readiness as barriers to professional help seeking. Fear of discrimination related to diverse sexual orientations and gender identities is found to be a major barrier to seeking professional care, particularly amongst young and gender diverse people [
18,
45]. It is also a pattern for older LGB people, with evidence that they are more likely to rely on partners than professional services [
46]. There is evidence that formalised peer support groups improves mental health for lesbian and bisexual women [
47]. It also provides people with information about LGBTI sensitive services to attend, and encourages professional support [
48]. The internet was used by the majority of our participants across the age spectrum for social support and this should be recognised as an increasingly legitimate source of help [
18]. Further, broader social interventions to reduce discrimination and improve mental health should be encouraged including mainstream community and family support.
There are implications for mainstream health services arising from our study, in particular that they need to be LGBTI sensitive. First, few participants accessed LGBTI specific services, relying instead on mainstream services; second key stakeholders identified the need for mainstream services to be more LGBTI inclusive, and finally over two thirds of the participants identified access to such services as an enabler of help seeking. Yet there is evidence that very few health services actually offer such care. An Irish study found that 64 % participants experienced a lack of LGBT knowledge amongst mental health professionals [
49]. Further, LGBTI sensitivity means understanding the diversity within this population group, rather than treating all LGBTI people in the same way. For example, “concordance” of sexual identity and behaviour is found to be associated with higher levels of health screening than for women with discordant identities [
50]. People with ‘discordant’, perhaps better phrased as diverse or fluid, expressions of sexual identity, sexual attraction and gender identity tend to have more difficulty being understood and their identities can be de-legitimised. This might explain why so many of the trans (86 %) and lesbian (79 %) women had disclosed to their regular GP in our study, compared with so few bisexual (32 %) and pansexual (30 %) women. Further, the gender diverse participants, queer and pansexual people were most likely to identify discrimination in services as a key barrier. These are all identities that are more marginal, and providers are likely to have low levels of knowledge about their specific health needs. Reluctance to disclose may also relate to personal or friends’ experiences of lack of sensitivity in the face of fluid and emerging identities. Yet, given that these very experiences in their wider lives are contributing to their mental health needs, LGBTI sensitive care becomes a critical need. A Sydney-based study of LBQ women found that the queer-identified women had experienced the highest levels of sexuality-based discrimination, had the highest levels of illicit drug use, and were most likely to seek professional support [
31]. The authors concluded that “meaningful engagement with contemporary sexual identities and their local social and cultural significance is essential for the development of appropriate and effective targeted public health interventions.” Recent development of online mental health services that are tailored to LGBTI people may be an additional source of LGBTI sensitive care [
51].
The study limitations included, first, that this was a convenience sample, so cannot be generalised to all SSAW. Particular groups that are not well represented include those that are less connected with LGBTI communities, and people with intersex status. Second, the cross-sectional study design was useful to provide descriptive analyses, however does not allow delineation of causation or directions of association. For example, the question of whether LGBT community connectedness increases mental health vulnerability due to feelings of marginalisation within the community cannot be answered. Third, the correlations are also limited to linear associations and cannot assist with more complex associations such as the relative influence of both stress, marginality and homelessness on depression. Finally, the study attracted a disproportionate number of people with mental health problems, so does not well represent help seeking behaviours for mental health maintenance by SSAW with good mental health. However, the convenience sampling also leant strength to the study, through providing large numbers of people and allowing disaggregation and comparison of several large sub-groups.
Acknowledgements
Thank you to Shaun Staunton at beyondblue for supporting all aspects of the project. Thank you to the participants in the online survey and key informant interviews.