Abstract
Sexual and gender minority (SGM) individuals experience a greater burden of poor mental health compared to heterosexual individuals. One factor that helps to explain this disparity is trauma experienced during childhood. SGM are more likely to report traumatic experiences during childhood contributing to this disparity. Previous research has shown that resilience moderates the relationship between childhood trauma and adults mental health outcomes. As part of the Strengthening Colors of Pride project, data on 463 SGM adults living in San Antonio were collected using surveys. A diverse recruitment strategy was used in conjunction with a community advisory board. The brief resilience scale (BRS) was used to assess intrapersonal level resilience to determine if there was an effect on the relationship between ACEs and quality of mental and physical health. Differences were noted for some items across low, normal, and high levels of resilience. Both ACEs and BRS significantly predicted quality of mental and physical health. We also noted a significant interaction between ACEs and BRS with regard to quality of mental health. Findings suggest there is a relationship between intrapersonal level resilience, ACEs, and quality of mental health.
Keywords: Adverse Childhood Experiences (ACEs), sexual and gender minority, LGBTQ+, mental health, resilience
Introduction
Past research indicates that compared to heterosexual individuals, sexual and gender minorities (SGMs) experience a greater burden of poor mental health, including higher rates of depression,1–8 anxiety,8 post-traumatic stress disorder,9 suicidal ideation, as well as suicide attempts.10–12 More recent studies have shown that SGM report poor quality of mental health significantly more often compared to heterosexuals,4 and transgender and other gender nonconforming (TGN) individuals have greater odds of poor quality of mental health compared to cisgender sexual minorities.13 Factors associated with differences in mental health outcomes among SGM are partly attributed to childhood trauma,4,13 experiences of minority stress,14 and differences related to internal psychological processes.15,16
Trauma experienced prior to adulthood has been shown to affect one’s quality of mental health.17 This is particularly true for SGM individuals18,19 and has been linked to childhood abuse,20,21 childhood neglect,13 and other childhood trauma.22,23 Past research has shown that SGM adults report experiences of childhood trauma more often than heterosexual adults.4,24 Work by Austin and Herrick,4 indicated that SGM adults are more likely to report childhood abuse and household dysfunction compared to heterosexual adults. More recent research by Schnarrs, Stone, Salcido, Baldwin, Georgiou, and Nemeroff13 found that experiences of childhood physical and emotional neglect are common among SGM, and that transgender adults are more likely to report neglect compared to cisgender sexual minorities. In their work, Schnarrs and colleagues13 also found a relationship between higher ACEs scores and poor quality of mental health after controlling for transgender identity, sexual orientation, and other sociodemographic variables, with transgender identity also significantly predicting greater odds of poor mental health.
While there is no agreed upon definition of resilience, it has been characterized as one’s ability to bounce back from, or overcome, difficult or stressful situations.25 However, until recently, resilience has largely been defined in terms of an individual’s capacity to cope with stressful events. Current theoretical frameworks of resilience conceptualize the construct through a social-ecological lens that encompasses intrapersonal (e.g., acceptance of change), relational (e.g., family cohesion, social support), and contextual factors (e.g., cultural identity).25 Conceptualizing resilience as having multiple levels also points to the various types of resources one has, or does not have, access to which increases the chances of successfully managing traumatic experiences or chronic stress. This broadening of the conceptual definition of resilience encourages the identifying of resilient factors and resources across the social ecological model that improve health outcomes, specifically among marginalized groups.26 However, as Colpitts and Gahagan argue, little is known about how well current frameworks of resilience fit with the experiences of SGM individuals and call for assessing different models and measures, as well as creating new frameworks based on the lived experiences of SGM individuals.26
Research has demonstrated that resilience affects the relationship between childhood trauma and mental health. Resilience has been shown to moderate the relationship between traumatic experiences in adolescence and depression,27–30 anxiety,31 major depressive disorder,32 and post-traumatic stress diosrder32 in adulthood. Across these studies individuals with low intrapersonal resilience reported poorer mental health outcomes across different measures of trauma experienced prior to adulthood. To date, the literature has not yet examined the effect intrapersonal resilience has on the relationship between ACEs and quality of mental health in SGM adults.
Aside from conceptual and methodological limitations that have been noted in the literature, resilience has been reported to have a positive effect on individuals’ mental health. There is limited research on the role of resilience as a potential moderating effect on the relationship between ACEs and poor quality of mental health among SGM adults. In this study we hypothesize that resilience moderates the relationship between ACEs score and quality of mental health among SGM adults, so that individuals with low resilience scores on BRS will have greater odds of reporting poor quality of mental health across ACEs scores.
Methods
Study design
This study used a community-based participatory research (CBPR) framework to guide the overall project from which these data are drawn called “Strengthening Colors of Pride San Antonio” (Colors of Pride). CBPR is a paradigm of research that includes community members as collaborators in research from conceptualization to dissemination of findings.33 The community advisory board (CAB) for Colors of Pride was comprised of SGM-focused, and associated, community-based organizations, local government offices and organizations, community-members from the San Antonio area, research partners, as well as other key stakeholders such as the Pride Center San Antonio. Data presented here were part of a screener survey to recruit participants for an in-depth interview about resilience among SGM living in San Antonio. The study was approved by the Institutional Review Board at Trinity University.
Recruitment and data collection
We employed a diverse recruitment strategy that included online recruitment through study social media sites, our community advisory board (CAB) networks on- and offline, community outreach events, table tents at local gay-owned businesses, and during the annual LGBTQ+PRIDE event in San Antonio, TX. The first phase of the study, conducted between May and August of 2018, consisted of a survey of sociodemographic characteristics, ACEs, and quality of mental and physical health. Data were collected using both online and paper-based surveys. Paper based surveys were distributed and completed as community events and for those who did not have internet access.
Measures
We used a two-part item to assess sex and gender developed by the Williams Institute.34 Participants were first asked about the sex assigned on their original birth certificate (1 = male; 2 = female; 3 = prefer not to respond). Next, participants were asked their current gender-identity (1 = man; 2 = woman, 3 = transgender, 4 = agender/gender non-conforming). A binary variable was created such that assigned male at birth who identified as women, and assigned female at birth who identified as men were combined with those who self-identified as transgender or agender/gender non-conforming. All transgender and gender non-conforming individuals were then coded as TGN= 1, and all other participants were coded as cisgender = 0.
Adverse Childhood Experiences (ACEs) is an index score measuring exposure to childhood abuse, childhood neglect, and household dysfunction before the age of 18. ACEs is comprised of 10 items across these three domains. Scores are derived from across these 3 domains: Household challenges (e.g., substance abuse in the family, family member incarceration, divorce, witnessing domestic violence); Abuse (e.g., physical, emotional, and sexual harm); and neglect – both emotional (e.g., not feeling loved) and physical (e.g., not having enough to eat, having to wear dirty clothes). Participants indicated that they either had or had not experienced each event. From these data a summative score is generated ranging from 0 to 10.35,36
Resilience was measured using the brief resilience scale (BRS) which is a 6-item measure assessing self-reported intrapersonal resilience. The possible score range of the BRS is from 1 (low resilience) to 5 (high resilience). BRS has been psychometrically validated and used in a variety of populations and settings (Figure 1). All items are loaded onto one factor with good internal consistency (α = .80–.91) and test re-test reliability (interclass correlation coefficient (ICC) = 0.61–0.69).37,38
Figure 1.
Quality of mental health and ACE moderated by BRS.
Quality of physical and mental health was measured with a 5-point Likert scale that asked participants, “In the past 30 days, how would you say your physical health has been?” and “In the past 30 days, how has the quality of your mental health been?” The response options ranged from excellent to poor. This was transformed into a binary variable so that excellent, very good, and good = 1 and fair and poor = 0. Participants who selected don’t know or no response were removed from the analysis. These items were pulled from the Behavioral Risk Factor Surveillance System (BRFSS) and standard procedure for analysis were used.39
We also measured sexual orientation, age, race/ethnicity, educational attainment, and income Sexual orientation was dichotomized so that bisexual and pansexual were = 1 and gay, lesbian, and other were = 0, given the documented mental health disparities that exists between bisexual individuals and other sexual minorities7,8 (Table 1).
Table 1.
Sample demographics for the total sample, and stratified by low, normal, and high resilience.
| Total sample (n = 463) |
Low resilience (n = 108) |
Normal resilience (n = 283) |
High resilience (n = 72) |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | χ 2 | P | |
| Age | 8.49 | 0.21 | ||||||||
| 18–44 | 327 | 70.6 | 84 | 77.8 | 199 | 70.3 | 44 | 61.1 | ||
| 45–54 | 65 | 14.0 | 15 | 13.9 | 37 | 13.1 | 13 | 18.1 | ||
| 55–64 | 47 | 10.2 | 6 | 5.6 | 30 | 10.6 | 11 | 15.3 | ||
| 65+ | 24 | 5.2 | 3 | 2.8 | 17 | 6.0 | 4 | 5.6 | 2.79 | 0.85 |
| Race/ethnicity | ||||||||||
| White (non-Hispanic) | 173 | 37.4 | 44 | 40.7 | 104 | 36.7 | 25 | 34.7 | ||
| Latinx, Hispanic, Chicano/a | 211 | 45.6 | 45 | 41.7 | 130 | 45.9 | 36 | 50.0 | ||
| African-American | 32 | 6.9 | 6 | 5.6 | 20 | 7.1 | 6 | 8.3 | ||
| Other | 47 | 10.2 | 13 | 12.0 | 29 | 10.2 | 5 | 6.9 | ||
| Annual income | 30.30 | <0.01 | ||||||||
| Less than $20,000 | 146 | 31.5 | 51 | 47.2 | 83 | 29.3 | 12 | 16.7 | ||
| $20,000–49,000 | 192 | 41.5 | 43 | 39.8 | 121 | 42.8 | 28 | 38.9 | ||
| $50,000 or more | 125 | 27.0 | 14 | 13.0 | 79 | 27.9 | 32 | 44.4 | ||
| Educational attainment | 3.98 | 0.40 | ||||||||
| Less than or equal to high school | 47 | 10.2 | 10 | 9.3 | 31 | 11.0 | 6 | 8.3 | ||
| Some college | 183 | 39.5 | 51 | 47.2 | 104 | 36.7 | 28 | 38.9 | ||
| At least a 4-year degree | 233 | 50.3 | 47 | 43.5 | 148 | 52.3 | 38 | 52.8 | ||
| Sexual orientation | 4.91 | 0.09 | ||||||||
| Non-bisexual/pansexual | 346 | 74.7 | 79 | 73.1 | 220 | 77.7 | 47 | 65.3 | ||
| Bisexual/pansexual | 117 | 25.3 | 29 | 26.9 | 63 | 22.3 | 25 | 34.7 | ||
| Gender identity | 7.51 | 0.02 | ||||||||
| Cisgender | 368 | 79.5 | 76 | 70.4 | 231 | 81.6 | 61 | 84.7 | ||
| Trans or similar gender minority | 95 | 20.5 | 32 | 29.6 | 52 | 18.4 | 11 | 15.3 | ||
| ACEs | 8.68 | 0.01 | ||||||||
| Less than 4 ACEs | 230 | 49.7 | 41 | 38.0 | 147 | 51.9 | 42 | 58.3 | ||
| 4 or more ACEs | 233 | 50.3 | 67 | 62.0 | 136 | 48.1 | 30 | 41.7 | ||
| Mental health | 65.62 | <0.01 | ||||||||
| Good or better | 285 | 61.6 | 35 | 32.4 | 185 | 65.4 | 65 | 90.3 | ||
| Poor or fair | 178 | 38.4 | 73 | 67.6 | 98 | 34.6 | 7 | 9.7 | ||
| Physical health | 21.63 | <0.01 | ||||||||
| Good or better | 352 | 76.0 | 68 | 63.0 | 217 | 76.7 | 67 | 93.1 | ||
| Poor or fair | 111 | 24.0 | 40 | 37.0 | 66 | 23.3 | 5 | 6.9 | ||
Data analysis
Descriptive statistics, such as frequency counts and chi-squares for demographics, ACEs and resilience were run first. Demographics and ACEs were stratified by resilience score based on Smith et al. with cuts for resilience as follows 1.00–2.99 (low resilience), 3.00–4.30 (normal resilience), and 4.31–5.00 (high resilience).37 Chi-square analysis was used to assess relationships between sample characteristics and resilience scores, as well as individual ACEs items and resilience scores.
Logistic regression was used to assess whether BRS score moderates the relationship between ACEs and self-reported quality of mental health. ACEs and BRS scores were centered on their means prior to calculating the interaction term.36 Four logistic regression models were run. First, a model to assess the relationship between ACEs and quality of mental health. BRS score was then added to the model. Next, we added in the ACEs and BRS score interaction term to the model. Finally, we added in relevant demographic characteristics of annual income, educational attainment, sexual orientation, age, and transgender identity.
Results
Demographic characteristics
A total of 463 self-identified SGM adults completed the survey. The mean age was 37.8 years (SD = 13.8). Nearly half (45.6%, n = 211), identified as Latinx, Hispanic, or Chicano/a. Over a third (37.4%, n = 173) identified as White (non-Hispanic), 6.9% as African-American, and 10.2% as another (i.e., “other”) race. Roughly three-quarters (73%) had an annual income of less than $50,000 per year and half of participants (50.3%) had at least a 4-year college degree. As for health, a sizeable portion of the sample reported poor or fair mental (38.4%) and physical health (24%). Overall, 61% of respondents had a normal BRS score, followed by 23.3% with low, and 15.5% with high BRS scores. Using a chi-square (χ2) test, differences were noted in terms of demographics and low, normal and high resilience with a statistically significant relationship between annual income [χ2(3, 463) = 30.298, P < 0.001), transgender identity [χ2(3, 463) = 7.508, P = 0.023), mental [χ2(3, 463) = 65.615, P < 0.001] and physical health [χ2(3, 463) = 21.633 P < 0.001).
Adverse Childhood Experiences
In terms of ACEs, 50.3% of participants reported experiencing 4 or more ACEs with 26.1% reporting 6 or more ACEs. Frequencies for each ACE item are shown in Table 2. The three most common ACEs were emotional abuse (53.3%), having a household member with mental disorders and suicidal attempts (49.2%), and separation or divorce of parents (48.4%). Among those with a low BRS score, physical neglect (34.7%) was the most common ACEs items, followed by witness to domestic violence (30.9%), and emotional abuse (30.4%). Those participants with a normal BRS score, the most common ACEs were having a household member ever in prison (64%), separation or divorce of parents (62.9%), and emotional neglect (61.4%). Among those with high BRS scores, the most common ACEs were having a household member ever in prison (18.6%), living with someone with substance abuse problems (17.3%), and sexual assault (14.9%). Finally, using a χ2 test differences in ACEs were noted across levels of BRS score and included emotional abuse [χ2(3, 463) = 16.334, P < 0.001], emotional neglect [χ2(3,463) = 6.339, P = 0.042], physical neglect [χ2(3,463) = 6.918, P = 0.032), and having a family member with mental disorders or suicide attempt ([χ2(3,463) = 12.439, P = 0.002).
Table 2.
Prevalence of ACEs items for the total sample, and stratified by low, normal, and high reslience.
| Total sample (n = 463) |
Low resilience (n = 108) |
Normal resilience (n = 283) |
High resilience (n = 72) |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|
| ACEs item | n | % | n | % | n | % | n | % | χ 2 | P |
| Emotional abuse | 247 | 53.3 | 75 | 69.4 | 142 | 50.2 | 30 | 41.7 | 16.33 | <0.01 |
| Physical abuse | 166 | 35.9 | 48 | 44.4 | 97 | 34.3 | 21 | 29.2 | 5.17 | 0.08 |
| Sexual abuse | 201 | 43.4 | 52 | 48.1 | 119 | 42 | 30 | 41.7 | 1.29 | 0.52 |
| Emotional neglect | 202 | 43.6 | 55 | 50.9 | 124 | 43.8 | 23 | 31.9 | 6.34 | 0.04 |
| Physical neglect | 75 | 16.2 | 26 | 24.1 | 41 | 14.5 | 8 | 11.1 | 6.92 | 0.03 |
| Separation or divorce of parents | 224 | 48.4 | 53 | 49.1 | 141 | 49.8 | 30 | 41.7 | 1.56 | 0.46 |
| Witness to domestic violence | 123 | 26.6 | 38 | 35.2 | 69 | 24.4 | 16 | 22.2 | 5.50 | 0.06 |
| Living with someone with substance abuse problems | 214 | 46.2 | 55 | 50.9 | 122 | 43.1 | 37 | 51.4 | 2.84 | 0.24 |
| Having a household member with mental disorders or suicidal attempts | 228 | 49.2 | 69 | 63.9 | 129 | 45.6 | 30 | 41.7 | 12.44 | <0.01 |
| Having a household member ever in prison | 59 | 12.7 | 10 | 9.3 | 38 | 13.4 | 11 | 15.3 | 1.71 | 0.42 |
Notes. Cutoff points for BRS score are taken from Smith et al.38
ACEs, resilience and health
Four logistic models were run using mental health and physical health as outcome variables. At the bivariate level, a significant relationship was found between ACEs score and quality of mental health, with those participants reporting higher ACEs scores having greater odds of poor mental health [odds ratio (OR) = 1.16, 95% confidence interval (CI) = 1.08–1.25). ACEs Score (AOR = 1.16, CI = 1.08–1.25) and BRS (AOR = 0.31, CI = 0.23–0.40) score were statistically significant in the second logit model. Moderating effects of resilience were found significant (AOR = 1.14, CI = 1.03–1.27), and also effects of ACEs (AOR = 1.14, CI = 1.06–1.24) and resilience score (AOR = 0.30, CI = 0.22–0.40). Lastly, we adjusted for age, annual income, educational attainment, sexual orientation and transgender identity for our next model and found that higher ACEs were still associated with higher likelihoods of mental health problems (AOR = 1.16, CI =1.06–1.27), while resilience could be considered as a protective factor (AOR = 0.31, CI = 0.22–0.42), however the moderating effects of resilience disappeared after adjustment (AOR = 1.11, CI = 1.00–1.25). We also examined effects of ACEs and resilience on quality of physical health. Logistic models for physical health are presented in Tables 3 and 4. The negative association between ACEs and physical health was found, while resilience contributed to good physical health. Moderating effects of resilience could not be found in the model with or without adjustment for confounders.
Table 3.
Odds ratio and adjusted odds ratio for quality of mental health.
| Model 1 | Model 2 | Model 3 | Model 4 | |
|---|---|---|---|---|
|
| ||||
| Age | ||||
| 18–44 | 1.00 (Ref.) | |||
| 45–54 | 0.53 (0.27–1.00) | |||
| 55–64 | 0.26 (0.10–0.60)** | |||
| 65+ | 0.24 (0.05–0.77)* | |||
| Annual income | ||||
| Less than $20,000 | 1.00 (Ref.) | |||
| $20,000–49,000 | 1.18 (0.70–2.01) | |||
| $50,000 or more | 0.84 (0.44–1.61) | |||
| Educational attainment | ||||
| Less than or equal to high school | 1.00 (Ref.) | |||
| Some college | 1.09 (0.51–2.36) | |||
| At least a 4-year degree | 1.13 (0.52–2.47) | |||
| Sexual orientation | ||||
| Non-bisexual/pansexual | 1.00 (Ref.) | |||
| Bisexual/Pansexual | 1.52 (0.89–2.60) | |||
| Gender identity Cisgender |
1.00 (Ref.) | |||
| Trans or similar gender minority | 1.60 (0.91–2.80) | |||
| ACEs score | 1.16 (1.08–1.25)*** | 1.13 (1.05–1.22)** | 1.14 (1.06–1.24)*** | 1.14 (1.05–1.25)** |
| BRS score | 0.32 (0.24–0.42)*** | 0.30 (0.22–0.40)*** | 0.31 (0.23–0.42)*** | |
| ACEs score X BRS score | 1.14 (1.03–1.27)* | 1.11 (1.00–1.25) | ||
Notes. Model 1 reports odds ratio (OR) and models 2–4 are adjusted odds ratios (AOR). Outcome (Y) variable: quality of mental health (0 = excellent, very good, good mental health; 1 = poor or fair mental health). Predictor (X) variale: ACEs score. Moderator (M) variable: BRS score.
P < 0.05
P < 0.01
***P < 0.001.
Table 4.
Odds ratio and adjusted odds ratio for quality of mental health
| Model 1 | Model 2 | Model 3 | Model 4 | ||
|---|---|---|---|---|---|
|
| |||||
| Age | |||||
| 18–44 | 1.00 (Ref.) | ||||
| 45–54 | 0.60 (0.28–1.21) | ||||
| 55–64 | 1.08 (0.47–2.30) | ||||
| 65+ | 1.48 (0.50–3.94) | ||||
| Annual income | |||||
| Less than $20,000 | 1.00 (Ref.) | ||||
| $20,000–49,000 | 0.83 (0.49–1.42) | ||||
| $50,000 or more | 0.65 (0.33–1.28) | ||||
| Educational attainment | |||||
| Less than or equal to high school | 1.00 (Ref.) | ||||
| Some college | 0.51 (0.25–1.08) | ||||
| At least a 4-year degree | 0.49 (0.23–1.05) | ||||
| Sexual orientation | |||||
| Non-bisexual/pansexual | 1.00 (Ref.) | ||||
| Bisexual/pansexual | 1.45 (0.84–2.48) | ||||
| Gender identity Cisgender |
1.00 (Ref.) | ||||
| Trans or similar gender minority | 0.85 (0.47–1.50) | ||||
| ACEs score | 1.13 (1.04–1.22)** | 1.11 (1.02–1.20)* | 1.11 (1.02–1.21)* | 1.10 (1.01–1.20)* | |
| BRS score | 0.54 (0.41–0.71)*** | 0.54 (0.41–0.70)*** | 0.54 (0.40–0.72)*** | ||
| ACEs score X BRS score | 1.02 (0.92–1.13) | 1.03 (0.93–1.14) | |||
Notes. Model 1 reports odds ratio (OR) and models 2–4 are adjusted odds ratios (AORs). Outcome (Y) variable: quality of mental health (0 = excellent, very good, good mental health; 1 = poor or fair mental health). Predictor (X) variale: ACEs score. Moderator (M) variable: BRS score.
P < 0.05
P < 0.01
P < 0.001.
Discussion
Our study contributes to the growing body of literature assessing the roles of ACEs and resilience on SGM adult health and is one of the first to assess the effect of resilience on the quality of mental health among SGM individuals. Previous research has documented higher rates of poor mental health among SGM adults compared to heterosexuals, but we are only now beginning to understand the effect of ACEs on the mental health of this population. Our findings extend previous research by assessing the effect of resilience on the relationship between ACEs and quality of mental health in adulthood.
Confirming other studies, we found that income and education were related to BRS score. We add to this literature by demonstrating that gender identity is significantly related to BRS score with gender minorities more likely to have low or normal scores. Lower BRS scores are likely related to the lack of social support and acceptance for gender minorities.16,18 However, this may also be indicative of gender minorities not perceiving themselves as resilient even though they may be, as well as a poor conceptual definition of resilience among the scientific community and in popular cultural. The measure we used focused on one’s ability to bounce back or overcome and this may be limiting for some individuals. For example, what we label as survival or poor coping may actually be resilient acts, such as cutting ties with one’s family or engaging in sex work. While measures assessing the general concept of resilience, such as BRS, have been shown to be associated with health outcomes, they are limited in capturing the nuances of resilience that are specific to SGM adults and often related to survival rather than “bouncing back.” A broader definition, beyond one’s ability to bounce back, of resilience is needed that is inclusive of how SGM individuals define resilience, and measurement about how individuals are resilient, rather than if they believe themselves to be resilient, will likely provide additional information.
A significant relationship was identified between some ACEs items and levels of resilience. Most notably, both items related to neglect were associated with low level of resilience, as was emotional abuse, and mental illness or suicide attempt in the home. While our findings demonstrate a relationship between resilience and ACEs, it is unclear from our data the direction of this relationship. This finding points to the current debate about the relationship between trauma and resilience. Most research conceptualizes resilience as an intrapersonal level personality trait that one has or does not have and those who do not have it are somehow deficient. More specifically, as a field the debate over resilience is centered on whether we are born with resilient traits that allow us to successfully overcome trauma or if we must experience trauma and successfully overcome it in order to be resilient in the future. If resilience is a learned behavior and an outcome of traumatic experience, how do we help young people successfully navigate these experiences to build a foundation for the future? Resilience continues to be difficult to measure because of the broad, and somewhat inaccurate definition that does not fully capture the nature of resilience, which encompasses intrapersonal, relational, and contextual aspects, the relationship between these three levels, and how they influence the relationship between early trauma and adult health. Longitudinal research is needed to better understand how trauma before the age of 18 effects the development of resilience to establish temporal mechanisms. Additionally, a social-ecological resilience framework is needed when researching trauma, resilience, and adult health outcomes that includes various levels for both trauma and resilience to better understand the availability of resilience resources that may be unique to diverse groups, and how these resources are accessed.
Our findings show a significant interaction between ACEs and resilience in terms of quality of mental health with resilience reducing the effect of ACEs on quality mental health. However, after adding potential confounders to the final model this relationship was no longer significant. After probing potential reasons for this by removing potential confounders from the model, we uncovered that sexual orientation plays an important role in terms of this interaction. After removing sexual orientation from the model, the interaction terms remained significant. The reason for this is beyond our data, but should be investigated in future research. Understanding the role of sexual orientation as it relates to both resilience and ACEs is important to understanding adult SGM health.
While this study extends our understanding of ACEs, resilience, and adult SGM health by showing that there is a relationship between some ACE items and levels of resilience, and that resilience does moderate the relationship between ACEs and quality of mental health, it is not without limitations. First, while we did employ a diverse recruitment strategy, this is a convenience sample limiting our ability to generalize beyond the sample and make casual associations, and our findings should be viewed as such. Second, while ACEs have been shown to affect adult health, our findings about the relationship between childhood trauma and level of resilience need further investigation given ACEs is focused on past experience and BRS is a current assessment. The amount of time between childhood trauma and resilience in adulthood needs to be considered. There is evidence to suggest that early childhood trauma increases the likelihood for trauma in adulthood. Also, and related to the previous limitation, our data, and past research, is unable to demonstrate if adversity leads to resilience or if resilience is a personality trait that leads to less experiences of adversity. Finally, both ACEs and BRS do not take into account the unique ways that SGM experience trauma during childhood or how SGM adults are resilient, potentially affecting scores on both measures.
Conclusions
This study adds to the literature on resilience, ACEs, and adult SGM health. It extends recent work by showing that a relationship exists between specific ACEs items and level of resilience, and that this relationship affects adult SGM health to some extent. However, there is need for additional research on SGM health, ACEs, and resilience. Finally, findings provide further evidence of the difficulty in measuring resilience, especially as it relates to childhood trauma that can be partly attributed to conceptual and methodological challenges associated with how we define resilience. Additional research is needed to better understand ACEs and resilience in SGM people.
Acknowledgements
This research was completed with funding from the Robert Wood Johnson Foundation Interdisciplinary Research Leaders program. Support for undergraduate research assistants was provided through the Ronald E. McNair Post-Baccalaureate Achievement Program and Murchison Summer Undergraduate Research Award. The Strengthening Colors of Pride research team thanks our community advisory board for its support and wisdom in guiding this project.
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