Content uploaded by Jae A. Puckett
Author content
All content in this area was uploaded by Jae A. Puckett on Nov 30, 2020
Content may be subject to copyright.
Journal of Family Psychology
Mental Health and Resilience in Transgender
Individuals: What Type of Support Makes a Difference?
Jae A. Puckett, Emmie Matsuno, Christina Dyar, Brian Mustanski, and Michael E. Newcomb
Online First Publication, July 18, 2019. http://dx.doi.org/10.1037/fam0000561
CITATION
Puckett, J. A., Matsuno, E., Dyar, C., Mustanski, B., & Newcomb, M. E. (2019, July 18). Mental Health
and Resilience in Transgender Individuals: What Type of Support Makes a Difference?. Journal of
Family Psychology. Advance online publication. http://dx.doi.org/10.1037/fam0000561
Mental Health and Resilience in Transgender Individuals: What Type of
Support Makes a Difference?
Jae A. Puckett
Michigan State University
Emmie Matsuno
University of California, Santa Barbara
Christina Dyar, Brian Mustanski, and Michael E. Newcomb
Northwestern University Feinberg School of Medicine
Research has generally shown the benefits of social support, such as the buffering effects on life stressors,
yet there has been little empirical investigation of different types of support resources for transgender
individuals. We examined family support, support from friends, and connectedness to a transgender
community and how these forms of support come together to influence mental health and resilience. The
sample included 695 transgender participants (mean age ⫽25.52 years, SD ⫽9.68, range ⫽16 –73;
75.7% White) who completed an online survey. Greater than half of participants reported moderate to
severe levels of anxious and depressive symptoms. Family social support had the strongest correlations
with symptoms of anxiety and depression (r⫽⫺.31 and ⫺.37, respectively, p⬍.01) and was the only
form of support associated with resilience when controlling for other forms of support. Latent profile
analyses revealed 4 groups based on levels of social support from family and friends and community
connectedness. Notably, Class 1 (n⫽323; 47.1%) had high levels of support from family and friends
and high levels of community connectedness. This class had lower levels of depression and anxiety
symptoms and higher levels of resilience compared to other classes (Class 2, n⫽276, 40.3%, high
friend/community, low family; Class 3, n⫽47, 6.9%, low support; Class 4, n⫽39, 5.7%, high family,
low friend/community). This study highlights the importance of examining support from a more holistic
approach and provides insight into unique associations between familial social support and resilience.
Keywords: transgender, social support, resilience, community connectedness, mental health
Supplemental materials: http://dx.doi.org/10.1037/fam0000561.supp
Transgender (or trans, also known as gender minorities) is an
umbrella term that refers to individuals who do not identify with
the gender that is typically associated with their sex assigned at
birth. This includes a diverse group (American Psychological
Association, 2015) of trans men, trans women, and other people
who do not identify with a gender (e.g., agender) or identify
outside binary notions of gender (e.g., genderqueer or nonbinary
individuals). We use the terms trans and gender diverse (TGD) and
gender minorities to capture the myriad of identities within the
broader transgender community.
TGD individuals experience striking elevations in mental health
concerns, such as depression (Bockting, Miner, Swinburne Ro-
mine, Hamilton, & Coleman, 2013; Rotondi et al., 2011), anxiety
(Bockting et al., 2013; Budge, Adelson, & Howard, 2013), and
suicidality (Goldblum et al., 2012; James et al., 2016). These
mental health concerns are partially driven by experiences of
stigmatization and marginalization, or minority stress (Hendricks
& Testa, 2012; Meyer, 2003). Although prior research has helped
elucidate processes that negatively impact mental health in TGD
individuals, very little research has focused on understanding what
Jae A. Puckett, Department of Psychology, Michigan State University;
Emmie Matsuno, Counseling Psychology, University of California, Santa
Barbara; Christina Dyar, Brian Mustanski, and Michael E. Newcomb,
Department of Medical Social Sciences, Institute for Sexual and Gender
Minority Health and Wellbeing, Northwestern University Feinberg School
of Medicine.
Jae A. Puckett presented on earlier versions of the findings reported
in this article to the Chicago Parents of Trans Individuals support group,
the Trans Health Community Advisory Board affiliated with this proj-
ect, and at the Association for Behavioral and Cognitive Therapies
Conference.
The project described herein was supported by a grant from the National
Institute on Drug Abuse (1F32DA038557).
We thank the members of the Trans Health Community Advisory Board,
who assisted with this project for their time, feedback, and dedicated involve-
ment. The authors also greatly appreciate the feedback that the Chicago
Parents of Trans Individuals support group provided related to early findings
from this study and their suggestions for ways that parents and families can
better support their trans loved ones. The authors would also like to thank the
participants who completed this study for their contributions.
Correspondence concerning this article should be addressed to Jae A.
Puckett, Department of Psychology, Michigan State University, 316 Phys-
ics Road, Room 262, East Lansing, MI 48824. E-mail: pucket26@msu.edu
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Journal of Family Psychology
© 2019 American Psychological Association 2019, Vol. 1, No. 999, 000
0893-3200/19/$12.00 http://dx.doi.org/10.1037/fam0000561
1
types of social supports benefit the mental health of gender mi-
norities. This study sought to understand how various types of
support (family, friends, and TGD community connectedness)
collectively relate to mental health and resilience for TGD people.
Social Supports and Mental Health
Social support, which refers to interpersonal supports that help
decrease stress (Gerrig & Zimbardo, 2002), has emerged as a key
factor that is associated with resilience and may buffer the negative
outcomes of minority stress among TGD individuals (Bockting et
al., 2013; Budge et al., 2013). For TGD people coping with
stigmatization, there are three prominent domains from which they
may seek support: family, friends, and a TGD community (Mizock
& Mueser, 2014). For each of these specific types of support, the
research is limited but provides an important base from which to
ask more nuanced questions about what types of supports might be
related to better mental health and resilience.
Most of the research about social support for TGD individuals
tends to average all forms of social support into a single construct.
This research indicates that social support, in general, is associated
with less depression and less anxiety in genderqueer individuals
(Budge, Rossman, & Howard, 2014), trans men, trans women
(Budge et al., 2013; Pflum, Testa, Balsam, Goldblum, & Bongar,
2015), and TGD youth (Grossman, D’augelli, & Frank, 2011). In
addition, greater social support has been associated with less
nonsuicidal self-injury for trans men and trans women (Claes et al.,
2015). And beyond demographic variables and other known cor-
relates of depression, such as gender-related victimization, social
support may be an especially strong predictor of mental health
(Boza & Nicholson Perry, 2014).
Family social support, specifically, is associated with higher life
satisfaction, lower feelings of being a burden, and less depression
in TGD individuals (Simons, Schrager, Clark, Belzer, & Olson,
2013) as well as less psychological distress (Bockting et al., 2013;
Lefevor, Sprague, Boyd-Rogers, & Smack, 2019). Support from
family members may be particularly important in protecting TGD
individuals from mental health risks (Mustanski, Newcomb, &
Garofalo, 2011; Olson, Durwood, DeMeules, & McLaughlin,
2016; Ryan, Russell, Huebner, Diaz, & Sanchez, 2010; Weinhardt
et al., 2019). For example, one study found that 57% of TGD youth
who said their parents were not supportive had attempted suicide
compared with only 4% of TGD youth who reported their parents
were supportive (Travers, Bauer, Pyne, & Bradley, 2012). Re-
search with lesbian, gay, bisexual, and transgender (LGBT) par-
ticipants demonstrates that family social support may contribute to
better mental health above and beyond other forms of support,
such as from peers or an LGBT community (Snapp, Watson,
Russell, Diaz, & Ryan, 2015), and may be essential to better
mental health (Mcconnell, Birkett, & Mustanski, 2015).
Although families have the capability to buffer the harmful
effects of stigma (Koken, Bimbi, & Parsons, 2009; Singh &
McKleroy, 2011), many TGD people experience rejection from
their own families (Bradford, Reisner, Honnold, & Xavier, 2013;
Koken et al., 2009; Mullen & Moane, 2013) and may instead be
more likely to turn to their friends for support (Moody & Smith,
2013; Nemoto, Bödeker, & Iwamoto, 2011). Unfortunately, very
limited research exists that separately examines the impact of
support from friends or peers on mental health among TGD
populations. Thus far, research has shown that support from
friends is associated with less psychological distress (Bockting et
al., 2013; Lefevor et al., 2019) and lower rates of suicidal ideation
(Bauer, Scheim, Pyne, Travers, & Hammond, 2015) for gender
minorities. Additionally, peer social support was found to have a
significant buffering effect on the association between stigma and
mental health for TGD individuals (Bockting et al., 2013).
TGD people also may seek a connection to a transgender com-
munity (Budge et al., 2012). This form of support can be important
for several reasons, including the ways connection with other TGD
individuals may facilitate the process of self-actualization and
self-acceptance, as well as decrease feelings of isolation when
faced with rejection from other groups (Graham et al., 2014).
Connectedness to a TGD community has been associated with
better well-being and fewer symptoms of depression and anxiety
(Barr, Budge, & Adelson, 2016; Pflum et al., 2015). Furthermore,
community involvement can significantly buffer the effects of
gender-based abuse on depression (Nuttbrock et al., 2015).
Although there are benefits to community connection, this re-
source may be limited to those willing to disclose their gender
minority identity (Hendricks et al., 2012) and to those in geo-
graphic locations that offer TGD community resources. Research
also indicates that involvement in TGD communities may be
associated with greater depression (Rotondi et al., 2011) and
greater exposure to discrimination (Bradford et al., 2013), perhaps
because this type of community connection may increase the
visibility of one’s identity. It also could be that this form of support
is more beneficial to the mental health of certain subgroups than
others. In one study, researchers found that TGD community
connectedness was significantly associated with fewer symptoms
of depression and anxiety among trans female spectrum partici-
pants but not trans male spectrum participants (Pflum et al., 2015).
Because of these mixed findings, research is still needed to assess
the associations between TGD community connection and mental
health.
Resilience and Social Support
Along with being associated with better mental health outcomes,
social support can help build resilience among TGD individuals
(Bockting et al., 2013; Matsuno & Israel, 2018; Singh, Hays, &
Watson, 2011). In this study, we conceptualized resilience as one’s
ability to overcome or bounce back from adversities (Matsuno et
al., 2018; Meyer, 2015; Smith et al., 2008). Although others have
labeled processes that may help one to be resilient, such as effec-
tive coping strategies or even social support, as resilience itself
(e.g., Bockting et al., 2013), we examined resilience as an indi-
vidual difference in how people respond and adapt to stressors
(Matsuno et al., 2018; Smith et al., 2008). According to the
minority stress model, resilience is hypothesized to moderate the
association between minority stressors and mental health outcomes
(Meyer, 2003). Therefore, higher levels of resilience among TGD
individuals may buffer the negative outcomes of minority stress,
making this an important area to study.
Although research has demonstrated the association between
social support and mental health outcomes (Budge et al., 2013;
Budge et al., 2014; Pflum et al., 2015), few quantitative studies
have examined how social support may relate to resilience for
TGD individuals. Partially, this is likely the case because social
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
2PUCKETT, MATSUNO, DYAR, MUSTANSKI, AND NEWCOMB
support and resilience have been equated in some prior studies
(e.g., Bockting et al., 2013; Grossman et al., 2011), whereas social
support may more accurately be characterized as a factor that
promotes resilience (Matsuno et al., 2018). Even so, quantitative
research shows that resilience is associated with better mental
health for TGD individuals (Gonzalez, Bockting, Beckman, &
Dura, 2012; Scandurra, Amodeo, Valerio, Bochicchio, & Frost,
2017) and higher levels of resilience are associated with turning to
family for support and more contact with LGBT peers (Bariola et
al., 2015). Qualitative studies have consistently identified social
support from friends, family, and the TGD community as support-
ing resilience for gender minority adults (Moody, Fuks, Peláez, &
Smith, 2015; Singh et al., 2011), TGD youth (Singh, Meng, &
Hansen, 2014), and TGD youth of color (Singh, 2013).
Current Study
Social support is important to the well-being of TGD individu-
als, yet there has been extremely limited research examining the
role of different interpersonal supports in relation to mental health
and resilience in gender minorities. This is particularly relevant,
given that few studies have simultaneously examined the three
major forms of support that TGD individuals use to cope (social
support from family, friends, and community). Research also has
typically included trans men and trans women, whereas research
with a gender diverse sample more accurately reflects the variety
of identities in the TGD community. In this gender diverse sample,
we examined: (a) severity of mental health symptoms in a TGD
sample; (b) associations between social supports, mental health,
and resilience; (c) groupings based on social support from family,
friends, and TGD community connectedness; and (d) differences
in mental health and resilience based on the types of supports.
Method
Participants
For this online study, there were 861 people who opened the
survey. Of these individuals, there were 166 participants who
either opened the survey and did not finish or who were disqual-
ified from the study after opening the link for a variety of reasons
(e.g., not completing any of the items, incorrectly answering
consent comprehension questions). After removing these individ-
uals, there were 695 participants in the final sample. The mean age
of the final sample was 25.52 years (SD ⫽9.68; range ⫽16 –73
years). The majority of the sample identified as White (75.7%) and
most had an income below $10,000 a year (51.4%). About half of
the participants identified as either transgender men (30.4%) or
transgender women (16.6%), and a variety of other gender iden-
tities (e.g., genderqueer, nonbinary) were reported by the other
participants. In regard to sex assigned at birth, 76.8% (n⫽534)
were assigned female at birth and 22.4% (n⫽156) were
assigned male at birth. Of note in regard to sexual orientation,
the largest percentage of participants identified as queer (25%),
with the second most common sexual orientation being pan-
sexual (18.7%). A breakdown of all demographic information is
available in Table 1.
Procedures
The data presented here were part of a broader study, which
entailed two components— one was a daily diary study and the
other a brief, one-time survey for participants who did not qualify
for the daily diaries. Participants completed a brief screener to
determine which portion of the study they would be presented. To
qualify for the daily diary portion, participants had to meet all of
the following criteria: be between 16 and 40 years old; identify as
trans men, trans women, genderqueer, or nonbinary; live in the
United States; had sex in the past 30 days; and either binge drank
or used substances in the past 30 days. Participants who did not
qualify for the daily diary portion could participate in the one-time
survey if they were aged 16 years and older, identified as TGD,
Table 1
Sample Demographics
Characteristic n(%)
Age Range ⫽16–73
Gender identity
Transgender man 211 (30.4%)
Transgender woman 115 (16.6%)
Genderqueer 87 (12.5%)
Nonbinary 132 (19%)
Agender 66 (9.5%)
Androgyne 7 (1%)
Bigender 22 (3.2%)
Sexual orientation
Queer 174 (25%)
Pansexual 130 (18.7%)
Bisexual 106 (15.3%)
Gay 62 (8.9%)
Asexual 100 (14.4%)
Heterosexual 38 (5.5%)
Lesbian 35 (5%)
Race/ethnicity
White 526 (75.7%)
Black/African American 13 (1.9%)
American Indian or Alaska native 1 (.1%)
Asian 21 (3%)
Latino/a 25 (3.6%)
Multiracial/multiethnic 98 (14.1%)
Education
Less than high school diploma 91 (13.1%)
High school graduate or equivalent 88 (12.7%)
Some college education but have not
graduated 228 (32.8%)
Associate’s degree/technical school degree 52 (7.5%)
Bachelor’s degree 160 (23%)
Master’s degree 63 (9.1%)
Doctorate or professional degree 13 (1.9%)
Income
Less than $10,000 357 (51.4%)
$10,000–19,999 112 (16.1%)
$20,000–29,999 59 (8.5%)
$30,000–39,999 49 (7.1%)
$40,000–49,999 39 (5.6%)
$50,000–69,999 36 (5.2%)
More than $70,000 40 (5.8%)
Note. There were five participants with missing data on the question
asking about sex assigned at birth and three participants with missing data
about their race/ethnicity and income. A response of not listed was chosen
for: 55 participants regarding gender identity, 50 for sexual orientation, and
eight for race/ethnicity. These participants had the option to provide written
responses.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
3
SOCIAL SUPPORT FOR TRANS INDIVIDUALS
and lived in the United States. The data presented here are from
only participants in the one-time survey.
This study was informed by a transgender community advisory
board (CAB), which included local TGD individuals who met
weekly for a month prior to the beginning of the study and
periodically after the initiation of data collection for the duration of
the project. The role of the CAB was to provide feedback about the
overall focus of the project and the relevance and cultural sensi-
tivity to their own lived experiences as well as to provide com-
ments on the questions included in the study, study design, recruit-
ment materials, and retention methods. The primary researcher on
the project also shared preliminary findings with the CAB and
sought feedback about the results, including findings focused on
social support.
Participants in the study were recruited from Facebook, Twitter,
Tumblr, and other social media sites as well as through community
organizations that serve the TGD community and via flyers at
community events. The study was approved by the institutional
review board of the primary investigator’s institutions with a
waiver of parental permission for 16- to 17-year-olds under 45
CFR 46.408(c). Participants provided their consent/assent to par-
ticipate in the study, which was completed via the online survey.
Participants who completed the one-time survey received a $5
Amazon gift card, with the exception of the first 200 participants
because they completed the survey prior to funding being avail-
able.
Because this was an online survey, there were several steps
taken to ensure the quality of the data. Participants did not gain
immediate access to the surveys, and they had to complete the
screener questionnaire to be considered for the study, allowing us
to screen for duplicate contact information in the screener ques-
tionnaire. The surveys were e-mailed to participants who qualified
for the study, and all e-mail addresses were reviewed for suspi-
cious e-mail accounts or duplicated e-mail addresses. Each e-mail
included a unique link to the survey that could only be used once.
We also examined IP addresses to screen for duplicate responses.
In addition, the survey platform included survey protection options
that prevented the survey from being taken multiple times by the
same user, including the screener questionnaire. The survey soft-
ware included a CAPTCHA (completely automated public turing
test to tell computers and humans apart) to inhibit programmed
responses. Finally, once participants gained access to the survey,
they also answered a series of three questions to assess their
understanding of the consent information (consent comprehension
questions). This also served as a way to ensure that participants
were attending to the information and not being careless or ran-
domly responding.
Measures
Demographics. Participants reported their age, sex assigned
at birth, gender identity, sexual orientation, racial/ethnic identifi-
cation, income, employment status, and education level. See Table
1 for response options to these questions.
Social support from family and friends. The subscales mea-
suring family support and support from friends from the Multidi-
mensional Scale of Perceived Social Support (Zimet, Dahlem,
Zimet, & Farley, 1988) were utilized to assess support from these
groups. These subscales each included four items, with response
options on a 7-point scale from very strongly disagree (1) to very
strongly agree (7). Averages were calculated for each subscale.
This measure has been supported with factor analyses and has been
found to be reliable (Cronbach’s alphas of .90 and .94 for family
and friends subscales, respectively; Zimet et al., 1988). In the
current sample, Cronbach’s alpha was .93 for both subscales.
Community connection. The community connectedness sub-
scale of the Gender Minority Stress and Resilience Scale (Testa,
Habarth, Peta, Balsam, & Bockting, 2015) was completed to assess
participants’ feelings of being connected to a community of other
individuals with similar gender identities. This subscale consisted
of five items measured on a 5-point scale from strongly disagree
(1) to strongly agree (5). Two items were reverse scored and a total
score was calculated, with higher scores indicating a greater sense
of TGD community connectedness. In the development study, this
subscale was found to be reliable, and there was support for
criterion, convergent, and discriminant validity (Testa et al., 2015).
In the current sample, Cronbach’s alpha was .82.
Mental health. Mental health was assessed via a measure of
depression symptoms and a measure of anxiety symptoms. To
assess depression, participants completed a short form of the
Patient-Reported Outcomes Measurement Information System
(PROMIS)–Depression scale (Cella et al., 2011). This was an
eight-item scale in which participants reported how often in the
past 7 days they experienced symptoms of depression, such as
feeling worthless, hopeless, or sad. To assess anxiety symptoms,
participants completed a short form of the PROMIS–Anxiety
scale, which included seven items in which participants reported
how often in the past 7 days they experienced symptoms such as
feeling fearful, tense, or worried. Response options ranged from
never (1) to always (5) on both scales. To calculate scores on these
measures, a raw score was computed, which was a total score that
was then converted to Tscores, which standardized the scores
against national norm data. The Cronbach’s alpha in the current
sample was .95 for the depression scale and .94 for the anxiety
scale. These measures were originally developed and tested with a
large sample of more than 20,000 individuals who were represen-
tative of the general population in the United States. Previous
validation research has shown that these scales have high levels of
reliability, and the short forms correlate highly with the full scales
as well as with other measures of depression and anxiety symp-
toms (Cella et al., 2011). For descriptive purposes, scores on these
two measures were categorized into none to slight (scores less than
55), mild (55–59.9), moderate (60 –69.9), and severe (70 and
over), in line with recommended cutoffs (American Psychiatric
Association, 2013).
Resilience. The Brief Resilience Scale (Smith et al., 2008)
assessed participants’ abilities to recover easily from stressful
experiences. This scale includes six items and responses were
measured on a 5-point scale from strongly disagree (1) to strongly
agree (5), and appropriate items were reverse scored before
calculating a mean score. Higher scores on this measure repre-
sented higher levels of resilience. Research has shown this scale
to be reliable, with good test-retest reliability and internal
consistency as well as support for convergent and discriminant
validity (Smith et al., 2008). Cronbach’s alpha in the current
study was .92.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
4PUCKETT, MATSUNO, DYAR, MUSTANSKI, AND NEWCOMB
Statistical Analysis
All data were analyzed using SPSS (Armonk, NY), with the
exception of the latent profile analyses, which were conducted in
Mplus version 8.1 (Los Angeles, CA). From the analytic sample,
1.2% of data was missing, and given this small percentage, this
was handled using pairwise deletion. Descriptive statistics were
conducted to describe the sample. Next, we examined associations
between demographics and support variables (support from family,
friends, and TGD community connectedness) and outcomes of
interest (depression symptoms, anxiety symptoms, resilience)
using correlations and ANOVAs. Bivariate correlations between
support variables and outcomes were examined next, and the sizes
of these correlations were compared using dependent correlation
comparisons. To examine the unique effects of each support vari-
able, we conducted multiple linear regressions in which demo-
graphic covariates and all three support variables were entered as
simultaneous predictors of depression symptoms, anxiety symp-
toms, and resilience. To determine whether the effect of a support
variable differed based on the amount of support present from
other sources, three-way interactions among the support variables
were tested as predictors of the outcomes.
Latent profile analyses (LPA) were then conducted to identify
groups based on support from family, friends, and TGD commu-
nity connectedness. We used a model-building approach in which
we started by estimating a model with one class and added one
class at a time. Bayesian Information Criterion (BIC) values,
sample size–adjusted BIC (adjusted BIC) values, Lo-Mendell-
Rubin (LMR) likelihood ratio tests, parametric bootstrapped like-
lihood ratio tests (BLRTs), the number of individuals in the small-
est class, and class interpretability were used to select the
appropriate number of classes (Dziak, Lanza, & Tan, 2014; Lo,
Mendell, & Rubin, 2001; Nylund, Asparouhov, & Muthén, 2007;
Tofighi & Enders, 2008; Yang, 2006). Higher entropy values
indicate greater distinguishability of latent classes and precision
with which individuals are categorized into classes (Ramaswamy,
DeSarbo, Reibstein, & Robinson, 1993). The model with the
lowest BIC and adjusted BIC indicated the number of classes
preferred by these indicators, and a significant LMR or BLRT
indicated a preference for the current model over the model with
one less class. ANOVAs and Tukey’s post hoc tests were then
conducted to examine which classes differed significantly on the
three support variables to help inform class interpretation.
2
analyses and ANOVAs were then conducted to evaluate whether
the classes differed based on demographics, mental health, and
resilience.
Results
A substantial portion of the sample reported elevated symptoms
of anxiety and depression. In regard to anxiety symptoms, 14.8%
of participants reported none to slight anxiety, 13.2% reported
mild anxiety, 45.3% reported moderate anxiety, and 24.2% re-
ported severe anxiety. For depression symptoms, 23.7% reported
none to slight depression, 22.9% mild depression, 36.4% moderate
depression, and 14.2% severe depression. Notably, more than half
of the sample reported moderate to severe levels of anxiety and
depression symptoms.
Correlations and descriptive statistics are available in Table 2.
Bivariate correlations indicated that age, sex assigned at birth, and
income were each significantly associated with at least one support
variable and one outcome and were therefore included as covari-
ates in subsequent multivariable regressions. Given the low in-
come of the sample, we also conducted a
2
analysis to assess
whether this was associated with the inclusion of 16- to 17-year-
olds in our sample and found a significant association between
being 16 or 17 years old and earning less than $10,000 a year
(
2
[1, N⫽692] ⫽21.11, p⬍.001).
Given the relatively small number of participants in certain
groups, we combined the following subgroups in our analyses:
agender, androgyne, and bigender participants were combined
with those who reported that their gender identity was not listed;
men were combined with trans men; women were combined with
trans women; bisexual and pansexual participants were combined;
lesbian and gay individuals were combined; and heterosexual
participants were combined with those who identified with an
unlisted label. ANCOVAs examining associations between educa-
tion, sexual identity, gender identity, and the outcomes indicated
that all demographic variables were associated with at least one
social support variable and one outcome (see Supplemental
Table 1) and thus were included as covariates in multivariable
regressions.
We utilized dependent variable correlations to determine
whether support from family or friends, or community connected-
Table 2
Correlations and Descriptive Statistics
Variable M(SD)12345678910
1. Age 25.52 (9.68) —
2. Sex assigned at birth — ⫺.33
ⴱⴱ
—
3. Race/ethnicity — ⫺.09
ⴱ
.02 —
4. Income — ⫺.31
ⴱⴱ
.07 .02 —
5. Social support–family 3.56 (1.75) .10
ⴱ
.02 ⫺.08
ⴱ
⫺.10
ⴱ
—
6. Social support–friends 5.54 (1.30) ⫺.02 ⫺.03 ⫺.08
ⴱ
.03 .12
ⴱⴱ
—
7. Community connectedness 17.57 (4.48) .08
ⴱ
⫺.10
ⴱ
⫺.04 .01 .07 .28
ⴱⴱ
—
8. Depression symptoms 60.52 (9.69) ⫺.26
ⴱⴱ
.02 .05 .13
ⴱⴱ
⫺.37
ⴱⴱ
⫺.22
ⴱⴱ
⫺.08
ⴱ
—
9. Anxiety symptoms 63.39 (10.24) ⫺.27
ⴱⴱ
.03 ⫺.002 .14
ⴱⴱ
⫺.31
ⴱⴱ
⫺.12
ⴱⴱ
⫺.04 .64
ⴱⴱ
—
10. Resilience 2.75 (.91) .25
ⴱⴱ
⫺.09
ⴱ
.05 ⫺.14
ⴱⴱ
.25
ⴱⴱ
.07 .01 ⫺.41
ⴱⴱ
⫺.49
ⴱⴱ
—
Note. Sex assigned at birth (0 ⫽male;1⫽female), race/ethnicity (0 ⫽White;1⫽People of Color), and income (0 ⫽less than $20,000 per year;1⫽
more than $20,000 per year) were dummy coded.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
5
SOCIAL SUPPORT FOR TRANS INDIVIDUALS
ness emerged as stronger bivariate predictors of anxiety symptoms,
depression symptoms, or resilience. Family social support was a
significantly stronger predictor of anxiety and depression symp-
toms as well as resilience compared with social support from
friends or community connectedness (ps⬍.01). Family support
had a moderate, negative correlation with anxiety, r⫽⫺.31, p⬍
.01, and depression symptoms, r⫽⫺.37, p⬍.01, and a small to
moderate positive association with resilience, r⫽.25, p⬍.01.
Social support from friends was also weakly negatively correlated
with anxiety, r⫽⫺.12, p⬍.01, and depression symptoms,
r⫽⫺.22, p⬍.01. Community connectedness was only weakly
negatively associated with depression symptoms, r⫽⫺.08, p⬍
.05, and this association was significantly weaker than that be-
tween social support from friends and depression symptoms (p⫽
.002). Social support from friends was not significantly associated
with resilience and community connectedness was not signifi-
cantly associated with anxiety symptoms or resilience.
To examine the unique effects of each support variable when
other support variables were controlled for, three multivariable
regressions were conducted in which all three social support vari-
ables were entered as simultaneous predictors of anxiety and
depression symptoms and resilience (Supplemental Table 2). In
these analyses age, sex assigned at birth, income, education, gen-
der identity, and sexual identity were included as covariates.
Results indicated that having more family support continued to
predict less depression and anxiety symptoms and more resilience,
even when support from friends and community connectedness
were controlled. Similarly, support from friends continued to pre-
dict less depression and anxiety symptoms when support from
family and community connectedness were controlled. However,
community connectedness did not predict anxiety and depression
symptoms or resilience in the multivariable models. None of the
three-way interactions of the support variables were significant,
indicating that the effects of the social support variables were
consistent across levels of the other social support variables (re-
sults not presented for brevity).
In the LPA, because of different scaling on the family/friend
support measure and the community connectedness variable,
scores were standardized prior to the analyses. Whereas BIC,
adjusted BIC, LMR, and BLRT indicated preference for a six-class
model (see Supplemental Table 3), this produced a very small class
consisting of 11 participants. Because classes smaller than 25
individuals can indicate the extraction of too many latent classes,
we examined four- and five-class solutions for interpretability.
Although the five-class model was preferred by model fit indices
over the four-class model, the four-class model was the most
interpretable (e.g., in the five-class solution, two groups were very
similar) and had adequate sample sizes for each group. See Sup-
plemental Figure 1 for a visual description of the classes that
emerged.
The (unstandardized) means for all social support variables by
class are presented in Table 3. Class 1 (n⫽323; 47.1%; high
support) was the largest of the classes and included participants
with relatively high levels of support from all areas. Class 2 (n⫽
276; 40.3%; high friend/community, low family) was character-
ized by high levels of support from friends and community con-
nectedness and low levels of support from family. Class 3 (n⫽47;
6.9%; low support) included participants who had low levels of
support from family and friends as well as low community con-
nectedness. Class 4 (n⫽39; 5.7%; high family, low friend/
community) was the smallest class that emerged and included
participants who reported low levels of support from friends, low
levels of community connectedness, and high levels of support
from family.
ANOVAs and Tukey’s post hoc tests were conducted to exam-
ine which classes differed significantly on support from friends
and family as well as community connectedness (see Table 3).
Omnibus ANOVAs were significant for all three sources of sup-
port (p⬍.001), and post hoc tests indicated good differentiation
across classes in levels of support from each source. These results
indicated that Classes 1 (high support) and 2 (low family, high
friend/community) were characterized by higher levels of support
from friends and community connectedness than Classes 3 (low
support) and 4 (high family, low friend/community). Classes 1 and
2 differed significantly on support from family, with Class 1 (high
support) reporting more support from family than Class 2 (low
family, high friend/community). Classes 3 and 4 also differed on
family support with Class 3 (low support) reporting lower family
support than Class 4 (high family, low friend/community).
A series of
2
analyses and ANOVAs were conducted to assess
whether the classes differed on demographic characteristics. Be-
cause some expected cell sizes were below or near 5 in analyses of
associations between class membership and gender and sexual
identity, we utilized Fisher’s exact tests for these analyses. There
were no significant differences across classes in terms of gender
identity,
2
(12, N⫽685) ⫽12.64, p⫽.40, sex assigned at birth,
Table 3
Analyses of Variance Examining Class Differences
Outcome ANOVA
Class means
Class 1 Class 2 Class 3 Class 4
Age F(3, 681) ⫽1.50, p⫽.21 26.33 24.73 24.74 26.05
Family support F(3, 673) ⫽698.20, p⬍.001 5.06
a
2.00
b
1.80
b
4.58
c
Friend support F(3, 673) ⫽363.10, p⬍.001 5.98
a
5.86
a
2.76
b
3.02
b
Community connectedness F(3, 680) ⫽18.91, p⬍.001 18.16
a
17.83
a
13.49
b
15.67
b
Depression symptoms F(3, 672) ⫽26.53, p⬍.001 57.45
a
62.60
b
67.75
c
62.00
b
Anxiety symptoms F(3, 674) ⫽17.85, p⬍.001 60.57
a
65.42
b
68.98
b
65.03
b
Resilience F(3, 673) ⫽9.59, p⬍.001 2.94
a
2.57
b
2.57
b
2.60
a,b
Note. Superscript letters (a, b, c) represent the results of Tukey’s post hoc comparisons of group means. Means with the same superscript letter are not
significantly different from one another, whereas means with different superscript letters differ significantly.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
6PUCKETT, MATSUNO, DYAR, MUSTANSKI, AND NEWCOMB
2
(3, N⫽680) ⫽1.42, p⫽.70, race/ethnicity (white participants
compared with people of color;
2
[3, N⫽682] ⫽6.34, p⫽.10),
sexual orientation,
2
(12, N⫽685) ⫽6.95, p⫽.86, education,
2
(6, N⫽685) ⫽7.77, p⫽.25, or age, F(3, 681) ⫽1.50, p⫽.21.
Classes did differ significantly on income,
2
(3, N⫽682) ⫽3.19,
p⫽.04, but the proportions of individuals who reported more than
$20,000 per year and less than $20,000 per year was similar within
each class. Given the lack of differences in class membership
based on demographics, no covariates were controlled for in sub-
sequent analyses of class membership.
ANOVAs were conducted to compare the classes on levels of
anxiety and depression symptoms and resilience. Means for the
classes on these variables are provided in Table 3. There were
significant differences between the classes on anxiety and depres-
sion symptoms and resilience, and Tukey post hoc tests revealed
several significant between-group differences. Participants in the
high support class (Class 1) reported significantly lower levels of
anxiety and depression symptoms compared with all other groups.
Those in the low support class (Class 3) reported significantly
higher levels of depression symptoms compared with all other
groups. Additionally, the high support class reported significantly
higher levels of resilience compared with the high friend support/
community connectedness, low family support class (Class 2) and
the low support class (Class 3) but did not differ significantly from
the high family support, low friend support/community connect-
edness class (Class 4). For further insight into differences in
anxious and depressive symptoms, pairwise comparisons of pro-
portions were conducted utilizing categorical anxiety and depres-
sion variables based on the prevalence of symptomology (none to
slight, mild, moderate, or severe; Table 4). Individuals with high
support were more likely to have no/slight or mild anxious or
depressive symptomology and less likely to have severe anxious or
depressive symptomology compared with other groups.
Discussion
Our findings align with prior research demonstrating the notable
elevations in anxiety and depression symptoms experienced by
TGD individuals (Bockting et al., 2013; Budge et al., 2013; Ro-
tondi et al., 2011). In this study, more than half of the participants
indicated that they experienced moderate to severe levels of anx-
iety and depression symptoms. Although not examined in these
analyses, it is important to understand that there are a variety of
stressors that are likely influencing these elevated levels of psy-
chological distress, such as rejection, discrimination, and violence
(Goldblum et al., 2012; Lombardi, 2009; Rotondi et al., 2011;
Testa et al., 2012). Additionally, the low income of our sample
may contribute to the elevated symptoms of anxiety and depres-
sion (Murali & Oyebode, 2004) because of many participants
likely experiencing financial stressors. Other studies have indi-
cated that transgender populations are at higher risk for poverty
because of workplace discrimination and harassment (James et al.,
2016). More than half of participants reported an income of less
than $10,000 per year, which is high in comparison with a large
national study with transgender adults that found 28% of trans-
gender individuals reported an income of less than $10,000 per
year (James et al., 2016). This discrepancy may result from a
portion of this sample being youth or young adults who may have
lower income, given their age or student status or from being
employed in entry-level positions.
In the LPA, it was noteworthy and encouraging that almost half
of the sample (47.1%) reported high levels of support from all
areas and that only 6.7% of the sample reported low support in all
three areas. The make-up of the classes indicated that it was more
common for TGD people to have low family support and high
friend support/community connectedness (40.3%) than to have
high family support and low friend support/community connect-
edness (5.7%). Additionally, levels of support from friends and
community connectedness stayed consistent in the class groupings
(i.e., no class that had high friend support, low community con-
nectedness or vice versa emerged). Together these results may
indicate that it is more common for TGD individuals to have some
form of support than none at all and that, when there is low familial
support, they may turn to their friends and community instead.
The LPA confirmed the importance of social support in relation
to mental health and demonstrated that it is the most beneficial to
have all three types of support. Notably, among participants in the
high support class only 5.1% reported severe depression symp-
toms. This rate was greater than 8 times higher when participants
Table 4
Categories of Depressive and Anxious Symptoms by Cluster
Outcome Severity
Class 1 Class 2 Class 3 Class 4
n%n%n%n%
Anxiety symptoms
None to slight 72
a
22.8 26
b
9.4 3
b
6.4 2
b
5.1
Mild 53
a
16.8 31
a,b
11.2 2
b
4.3 6
a,b
15.4
Moderate 143
a
45.3 128
a
46.4 21
a
44.7 23
a
59.0
Severe 48
a
15.2 91
b,c
33.0 21
c
44.7 8
a,b
20.5
Depression symptoms
None to slight 114
a
36.2 46
b
16.7 0
c
.0 5
b
12.8
Mild 84
a
26.7 54
b
19.6 10
a,b
21.3 11
a,b
28.2
Moderate 101
a
32.1 118
b
42.9 17
a,b
36.2 17
a,b
43.6
Severe 16
a
5.1 57
b
20.7 20
c
42.6 6
b
15.4
Note. Superscript letters (a, b, c) represent the results of pairwise z tests of group proportions. Groups with the
same superscript letter are not significantly different from one another, whereas groups with different superscript
letters differ significantly.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
7
SOCIAL SUPPORT FOR TRANS INDIVIDUALS
had low support from all areas, with close to half of the individuals
in this low support class (42.6%) reporting severe symptoms of
depression. Additionally, most TGD individuals (89.4%) who
lacked support in all areas reported moderate to severe anxiety
symptoms and were 3 times more likely to report severe anxiety
symptoms compared with the high support class. However, in all
four classes, a large portion of TGD participants endorsed mod-
erate anxiety symptoms (44.7% - 59%) including 45.3% of par-
ticipants in the high-support class.
Although all types of social supports were important to the
mental health of TGD people in our sample, there are nuances to
this that must be considered. Overall, familial support had the
strongest association with fewer symptoms of depression and
anxiety and greater resilience. Additionally, family support signif-
icantly predicted depression and anxiety symptoms and resilience
above and beyond the variance accounted for by the other forms of
support. Family support seems to be particularly important in
relation to resilience because it was the only form of support that
significantly predicted resilience when controlling for the other
support variables. Additionally, Class 1 (high support) and Class 4
(high family/low friend-community) did not differ in levels of
resilience, whereas Class 2 (low family/high friend-community)
and Class 3 (low support) had lower levels of resilience. Other
work has indicated an association between family support and
resilience (Matsuno et al., 2018), and therefore, it could be that
family support helps TGD people bounce back from adversities by
providing a safe and supportive home base. However, our analyses
were cross-sectional, and longitudinal research is needed to deter-
mine whether family support increases resilience or whether there
is an alternative explanation.
Similar to social support from family, social support from
friends was associated with fewer symptoms of depression and
anxiety. However, unlike family support, support from friends was
not significantly associated with resilience when controlling for
other forms of support. In the latent class analysis, Class 2 (low
family/high friend-community) and Class 4 (high family/low
friend-community) showed similar symptoms of depression and
anxiety, indicating that having support from either family or
friends and community connectedness can potentially counteract
some of the negative impact of lack of support in the other area.
Both classes 2 and 4 showed lower rates of depression symptoms
compared with class 3 (low support) but did not differ in anxiety
symptoms or resilience. This finding demonstrates the importance
of having support in all three areas and indicates that having some
social support may impact symptoms of depression more than
symptoms of anxiety. Again, our results cannot conclude causality,
and there could be alternative explanations for these associations,
such as those with fewer depressive symptoms being better
equipped to seek and develop social support networks. Ultimately,
longitudinal research is needed to answer such a question.
In contrast to previous literature, community connectedness was
not significantly correlated with anxiety symptoms or resilience,
and the negative correlation with depression symptoms was weak.
Community connectedness did not significantly predict depression
or anxiety symptoms or resilience when controlling for other forms
of support. There are a few possible explanations for these find-
ings. One is that there may be overlap or conflation between
support from friends and community connectedness as it is possi-
ble that friends in a person’s network are also part of the TGD
community. Our results indicated that social support from friends
was significantly correlated with community connectedness, and
therefore, TGD community spaces may be areas in which individ-
uals cultivate new friendships with supportive others or it could be
that friends help establish connection to TGD communities.
It also is possible that the findings would be different if we had
assessed feeling supported by a TGD community as opposed to
community connectedness. It is likely that differences exist be-
tween those who feel simply connected versus those who feel
supported by other TGD individuals. Additionally, other research
has shown that community connection can both benefit and place
individuals at risk for harm. Community connection often in-
creases one’s visibility as a gender minority and may place TGD
individuals at greater risk for encountering minority stressors
(Bradford et al., 2013). Additionally, it is possible that connection
to a TGD community could create more awareness of negative
events experienced by other TGD individuals, which may increase
anxiety, anticipated rejection, or depressive symptoms like feel-
ings of hopelessness. Future research is needed to establish the
routes through which this form of support may exert positive
influences on the lives of TGD individuals. And finally, it is
possible that there are other factors that may impact TGD individ-
uals’ connectedness to a community, including location, lack of
desire to be connected to a TGD community, not yet being out
about one’s identity, or lack of visibility of a TGD community.
This study had several strengths. First, we were able to recruit a
diverse sample in regard to gender, in which more than half of the
sample identified as a nonbinary identity (e.g., genderqueer, big-
ender). Also, this study is the first to our knowledge to utilize the
widely used PROMIS measures for anxiety and depression symp-
toms with a sample of TGD individuals. These measures have been
recommended for use by the American Psychiatric Association
and this study shows initial support for their use with TGD
samples, given the high levels of reliability. In addition, this is one
of few studies to examine simultaneously the three areas of support
that people who are TGD have reported relying on in previous
research (Mizock & Mueser, 2014). Our study did not conflate
different forms of support and instead conducted analyses that
described combinations of the types of support. Lastly, this study
contributes to the extremely limited empirical investigation of
resilience for TGD individuals.
In terms of limitations, our study had limited racial and ethnic
diversity. Other studies with online recruitment of TGD samples
have also had limited racial and ethnic diversity (Bockting et al.,
2013; Kuper, Nussbaum, & Mustanski, 2012). It may be necessary
to conduct more in-person recruitment to reach TGD people of
color. Furthermore, intentionally creating partnerships with orga-
nizations and communities that serve TGD people of color and
having researchers who identify as TGD people of color may build
greater trust among this population and increase research partici-
pation. Additionally, this was a cross-sectional study that pre-
cludes any causal interpretations of the data and longitudinal work
would help to further establish how changes in social support
relates to mental health and resilience. It is possible that our
sample will differ from other TGD samples, given that these were
participants who did not qualify for the daily diary study. Even so,
the subsample of participants who completed this one-time study
were largely sexually active (only 29.3% reported never having
had sex), and their rates of alcohol use and drug/substance use
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
8PUCKETT, MATSUNO, DYAR, MUSTANSKI, AND NEWCOMB
were similar to that found in the U.S. Trans Survey (James et al.,
2016), providing some evidence that our sample may not differ
substantially from others. Finally, although our inclusion of a
resilience measure is novel and a strength, given the state of
quantitative investigations of this construct with TGD samples, it
is worth noting that there may be aspects of resilience for TGD
individuals that are not captured in such a measure. For TGD
people, resilience may include a general ability to bounce back
from stressors, but it also might include the act and perseverance
of affirming one’s gender in a society in which TGD people face
many oppressive individuals and social systems.
Interpersonal relationships are one way of managing stressors,
and, as we found, social support from family and friends is related
to better mental health for TGD individuals. TGD people with high
levels of support from family and friends as well as TGD com-
munity connection showed the best mental health outcomes and
reported strikingly lower levels of depression and anxiety com-
pared with TGD who reported low levels of support in these areas.
Familial social support emerged as an important form of support in
relation to resilience. Through bolstering these core relationships
across these various sources of support, there may be improved
outcomes for TGD individuals who are likely facing great
amounts of oppression at the systemic, institutional, and inter-
personal levels.
References
American Psychiatric Association. (2013). Online assessment measures.
Retrieved from https://www.psychiatry.org/psychiatrists/practice/dsm/
educational-resources/assessment-measures
American Psychological Association. (2015). Guidelines for psychological
practice with transgender and gender nonconforming people. American
Psychologist, 70, 832– 864. http://dx.doi.org/10.1037/a0039906
Bariola, E., Lyons, A., Leonard, W., Pitts, M., Badcock, P., & Couch, M.
(2015). Demographic and psychosocial factors associated with psycho-
logical distress and resilience among transgender individuals. American
Journal of Public Health, 105, 2108 –2116. http://dx.doi.org/10.2105/
AJPH.2015.302763
Barr, S. M., Budge, S. L., & Adelson, J. L. (2016). Transgender community
belongingness as a mediator between strength of transgender identity
and well-being. Journal of Counseling Psychology, 63, 87–97. http://dx
.doi.org/10.1037/cou0000127
Bauer, G. R., Scheim, A. I., Pyne, J., Travers, R., & Hammond, R. (2015).
Intervenable factors associated with suicide risk in transgender persons:
A respondent driven sampling study in Ontario, Canada. BMC Public
Health, 15, 525. http://dx.doi.org/10.1186/s12889-015-1867-2
Bockting, W. O., Miner, M. H., Swinburne Romine, R. E., Hamilton, A.,
& Coleman, E. (2013). Stigma, mental health, and resilience in an online
sample of the U.S. transgender population. American Journal of Public
Health, 103, 943–951. http://dx.doi.org/10.2105/AJPH.2013.301241
Boza, C., & Nicholson Perry, K. (2014). Gender-related victimization,
perceived social support, and predictors of depression among transgen-
der Australians. International Journal of Transgenderism, 15, 35–52.
http://dx.doi.org/10.1080/15532739.2014.890558
Bradford, J., Reisner, S. L., Honnold, J. A., & Xavier, J. (2013). Experi-
ences of transgender-related discrimination and implications for health:
Results from the Virginia Transgender Health Initiative Study. American
Journal of Public Health, 103, 1820 –1829. http://dx.doi.org/10.2105/
AJPH.2012.300796
Budge, S. L., Adelson, J. L., & Howard, K. A. S. (2013). Anxiety and
depression in transgender individuals: The roles of transition status, loss,
social support, and coping. Journal of Consulting and Clinical Psychol-
ogy, 81, 545–557. http://dx.doi.org/10.1037/a0031774
Budge, S. L., Katz-Wise, S. L., Tebbe, E. N., Howard, K. A. S., Schneider,
C. L., & Rodriguez, A. (2012). Transgender emotional and coping
processes: Facilitative and avoidant coping throughout gender transition-
ing. Counseling Psychologist, 41, 601– 647. http://dx.doi.org/10.1177/
0011000011432753
Budge, S. L., Rossman, H. K., & Howard, K. A. S. (2014). Coping and
psychological distress among genderqueer individuals: The moderating
effect of social support. Journal of LGBT Issues in Counseling, 8,
95–117. http://dx.doi.org/10.1080/15538605.2014.853641
Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S.,...
Hays, R. (2011). Initial adult health item banks and first wave testing of
the Patient-Reported Outcomes Measurement Information System
(PROMIS) Network: 2005–2008. Journal of Clinical Epidemiology, 63,
1179 –1194. http://dx.doi.org/10.1016/j.jclinepi.2010.04.011
Claes, L., Bouman, W. P., Witcomb, G., Thurston, M., Fernandez-Aranda,
F., & Arcelus, J. (2015). Non-suicidal self-injury in trans people: Asso-
ciations with psychological symptoms, victimization, interpersonal func-
tioning, and perceived social support. Journal of Sexual Medicine, 12,
168 –179. http://dx.doi.org/10.1111/jsm.12711
Dziak, J. J., Lanza, S. T., & Tan, X. (2014). Effect size, statistical power
and sample size requirements for the bootstrap likelihood ratio test in
latent class analysis. Structural Equation Modeling, 21, 534 –552. http://
dx.doi.org/10.1080/10705511.2014.919819
Gerrig, R. J., & Zimbardo, P. G. (2002). Psychology and life (16th ed.).
Needham Heights, MA: Allyn & Bacon.
Goldblum, P., Testa, R. J., Pflum, S., Hendricks, M. L., Bradford, J., &
Bongar, B. (2012). The relationship between gender-based victimization
and suicide attempts in transgender people. Professional Psychology,
Research and Practice, 43, 468 – 475. http://dx.doi.org/10.1037/
a0029605
Gonzalez, C. A., Bockting, W. O., Beckman, L. J., & Dura, R. E. (2012).
Agentic and communal personality traits: Their associations with de-
pression and resilience among transgender women. Sex Roles, 67, 528 –
543. http://dx.doi.org/10.1007/s11199-012-0202-y
Graham, L. F., Crissman, H. P., Tocco, J., Hughes, L. A., Snow, R. C., &
Padilla, M. B. (2014). Interpersonal relationships and social support in
transitioning narratives of Black transgender women in Detroit. Inter-
national Journal of Transgenderism, 15, 100 –113. http://dx.doi.org/10
.1080/15532739.2014.937042
Grossman, A. H., D’augelli, A. R., & Frank, J. A. (2011). Aspects of
psychological resilience among transgender youth. Journal of LGBT
Youth, 8, 103–115. http://dx.doi.org/10.1080/19361653.2011.541347
Hendricks, M. L., & Testa, R. J. (2012). A conceptual framework for
clinical work with transgender and gender nonconforming clients: An
adaptation of the Minority Stress Model. Professional Psychology, Re-
search and Practice, 43, 460 – 467. http://dx.doi.org/10.1037/a0029597
James, S. E., Herman, J. L., Rankin, S., Keisling, M., Mottet, L., & Anafi,
M. (2016). The Report of the 2015 U.S. Transgender Survey. Washing-
ton, DC: National Center for Transgender Equality.
Koken, J. A., Bimbi, D. S., & Parsons, J. T. (2009). Experiences of familial
acceptance-rejection among transwomen of color. Journal of Family
Psychology, 23, 853– 860. http://dx.doi.org/10.1037/a0017198
Kuper, L. E., Nussbaum, R., & Mustanski, B. (2012). Exploring the
diversity of gender and sexual orientation identities in an online sample
of transgender individuals. Journal of Sex Research, 49, 244 –254.
http://dx.doi.org/10.1080/00224499.2011.596954
Lefevor, G. T., Sprague, B. M., Boyd-Rogers, C. C., & Smack, A. C.
(2019). How well do various types of support buffer psychological
distress among transgender and gender nonconforming students? Inter-
national Journal of Transgenderism, 20, 39 – 48.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
9
SOCIAL SUPPORT FOR TRANS INDIVIDUALS
Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of
components in a normal mixture. Biometrika, 88, 767–778. http://dx.doi
.org/10.1093/biomet/88.3.767
Lombardi, E. (2009). Varieties of transgender/transsexual lives and their
relationship with transphobia. Journal of Homosexuality, 56, 977–992.
http://dx.doi.org/10.1080/00918360903275393
Matsuno, E., & Israel, T. (2018). Psychological interventions promoting
resilience among transgender individuals: Transgender Resilience Inter-
vention Model. Counseling Psychologist, 46, 632– 655. http://dx.doi.org/
10.1177/0011000018787261
McConnell, E. A., Birkett, M. A., & Mustanski, B. (2015). Typologies of
social support and associations with mental health outcomes among
LGBT youth. LGBT Health, 2, 55– 61. http://dx.doi.org/10.1089/lgbt
.2014.0051
Meyer, I. H. (2003). Prejudice, social stress, and mental health in lesbian,
gay, and bisexual populations: Conceptual issues and research evidence.
Psychological Bulletin, 129, 674 – 697. http://dx.doi.org/10.1037/0033-
2909.129.5.674
Meyer, I. H. (2015). Resilience in the study of minority stress and health
of sexual and gender minorities. Psychology of Sexual Orientation and
Gender Diversity, 2, 209 –213. http://dx.doi.org/10.1037/sgd0000132
Mizock, L., & Mueser, K. T. (2014). Employment, mental health, inter-
nalized stigma, and coping with transphobia among transgender individ-
uals. Psychology of Sexual Orientation and Gender Diversity, 1, 146 –
158. http://dx.doi.org/10.1037/sgd0000029
Moody, C., Fuks, N., Peláez, S., & Smith, N. G. (2015). “Without this, I
would for sure already be dead”: A qualitative inquiry regarding suicide
protective factors among trans adults. Psychology of Sexual Orientation
and Gender Diversity, 2, 266 –280. http://dx.doi.org/10.1037/
sgd0000130
Moody, C., & Smith, N. G. (2013). Suicide protective factors among trans
adults. Archives of Sexual Behavior, 42, 739 –752. http://dx.doi.org/10
.1007/s10508-013-0099-8
Mullen, G., & Moane, G. (2013). A qualitative exploration of transgender
identity affirmation at the personal, interpersonal, and sociocultural
levels. International Journal of Transgenderism, 14, 140 –154. http://dx
.doi.org/10.1080/15532739.2013.824847
Murali, V., & Oyebode, F. (2004). Poverty, social inequality and mental
health. Advances in Psychiatric Treatment, 10, 216 –224. http://dx.doi
.org/10.1192/apt.10.3.216
Mustanski, B., Newcomb, M., & Garofalo, R. (2011). Mental health of
lesbian, gay, and bisexual youth: A developmental resiliency perspec-
tive. Journal of Gay & Lesbian Social Services, 23, 204 –225. http://dx
.doi.org/10.1080/10538720.2011.561474
Nemoto, T., Bödeker, B., & Iwamoto, M. (2011). Social support, exposure
to violence and transphobia, and correlates of depression among male-
to-female transgender women with a history of sex work. American
Journal of Public Health, 101, 1980 –1988. http://dx.doi.org/10.2105/
AJPH.2010.197285
Nuttbrock, L., Bockting, W., Rosenblum, A., Hwahng, S., Mason, M.,
Macri, M., & Becker, J. (2015). Transgender community involvement
and the psychological impact of abuse among transgender women.
Psychology of Sexual Orientation and Gender Diversity, 2, 386 –390.
http://dx.doi.org/10.1037/sgd0000126
Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the
number of classes in latent class analysis and growth mixture modeling:
A Monte Carlo simulation study. Structural Equation Modeling, 14,
535–569. http://dx.doi.org/10.1080/10705510701575396
Olson, K. R., Durwood, L., DeMeules, M., & McLaughlin, K. A. (2016).
Mental health of transgender children who are supported in their iden-
tities. Pediatrics, 137, e20153223. http://dx.doi.org/10.1542/peds.2015-
3223
Pflum, S., Testa, R., Balsam, K., Goldblum, P., & Bongar, B. (2015).
Social support, trans community connectedness, and mental health
symptoms among transgender and gender nonconforming adults. Psy-
chology of Sexual Orientation and Gender Diversity, 2, 281–286. http://
dx.doi.org/10.1037/sgd0000122
Ramaswamy, V., DeSarbo, W. S., Reibstein, D. J., & Robinson, W. T.
(1993). An empirical pooling approach for estimating marketing mix
elasticities with PIMS data. Marketing Science, 12, 103–124. http://dx
.doi.org/10.1287/mksc.12.1.103
Rotondi, N. K., Bauer, G. R., Travers, R., Travers, A., Scanlon, K., &
Kaay, M. (2011). Depression in male-to-female transgender Ontarians:
Results from the Trans PULSE Project. Canadian Journal of Commu-
nity, 30, 113–133. http://dx.doi.org/10.7870/cjcmh-2011-0020
Ryan, C., Russell, S. T., Huebner, D., Diaz, R., & Sanchez, J. (2010).
Family acceptance in adolescence and the health of LGBT young adults.
Journal of Child and Adolescent Psychiatric Nursing, 23, 205–213.
http://dx.doi.org/10.1111/j.1744-6171.2010.00246.x
Scandurra, C., Amodeo, A. L., Valerio, P., Bochicchio, V., & Frost, D. M.
(2017). Minority stress, resilience, and mental health: A study of Italian
transgender people. Journal of Social Issues, 73, 563–585. http://dx.doi
.org/10.1111/josi.12232
Simons, L., Schrager, S. M., Clark, L. F., Belzer, M., & Olson, J. (2013).
Parental support and mental health among transgender adolescents.
Journal of Adolescent Health, 53, 791–793. http://dx.doi.org/10.1016/j
.jadohealth.2013.07.019
Singh, A. A. (2013). Transgender youth of color and resilience: Negotiat-
ing oppression and finding support. Sex Roles, 68, 690 –702. http://dx
.doi.org/10.1007/s11199-012-0149-z
Singh, A. A., Hays, D. G., & Watson, L. S. (2011). Strength in the face of
adversity: Resilience strategies of transgender individuals. Journal of
Counseling and Development, 89, 20 –27. http://dx.doi.org/10.1002/j
.1556-6678.2011.tb00057.x
Singh, A. A., & McKleroy, V. S. (2011). ‘Just getting out of bed is a
revolutionary act’: The resilience of transgender people of color who
have survived traumatic life events. Traumatology, 17, 34 – 44. http://dx
.doi.org/10.1177/1534765610369261
Singh, A. A., Meng, S. E., & Hansen, A. W. (2014). “I am my own
gender”: Resilience strategies of trans youth. Journal of Counseling and
Development, 92, 208 –218. http://dx.doi.org/10.1002/j.1556-6676.2014
.00150.x
Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., &
Bernard, J. (2008). The brief resilience scale: Assessing the ability to
bounce back. International Journal of Behavioral Medicine, 15, 194 –
200. http://dx.doi.org/10.1080/10705500802222972
Snapp, S. D., Watson, R. J., Russell, S. T., Diaz, R. M., & Ryan, C. (2015).
Social support networks for LGBT young adults: Low cost strategies for
positive adjustment. Family Relations, 64, 420 – 430. http://dx.doi.org/
10.1111/fare.12124
Testa, R. J., Habarth, J., Peta, J., Balsam, K., & Bockting, W. (2015).
Development of the gender minority stress and resilience measure.
Psychology of Sexual Orientation and Gender Diversity, 2, 65–77.
http://dx.doi.org/10.1037/sgd0000081
Testa, R. J., Sciacca, L. M., Wang, F., Hendricks, M. L., Goldblum, P.,
Bradford, J., & Bongar, B. (2012). Effects of violence on transgender
people. Professional Psychology, Research and Practice, 43, 452– 459.
http://dx.doi.org/10.1037/a0029604
Tofighi, D., & Enders, C. K. (2008). Identifying the correct number of
classes in growth mixture models. In G. R. Hancock & K. M. Samuelsen
(Eds.), Advances in latent variable mixture models (pp. 317–341). Char-
lotte, NC: Information Age Publishing, Inc.
Travers, R., Bauer, G., Pyne, J., & Bradley, K. (2012). Impacts of strong
parental support for trans youth: A report prepared for Children’s Aid
Society of Toronto and Delisle Youth Services. Retrieved from http://
transpulseproject.ca/wp-content/uploads/2012/10/Impacts-of-Strong-
Parental-Support-for-Trans-Youth.pdf
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
10 PUCKETT, MATSUNO, DYAR, MUSTANSKI, AND NEWCOMB
Weinhardt, L., Xie, H., Wesp, L. M., Murray, J., Apchemengich, I., Kioko,
D.,...Cook-Daniels, L. (2019). The role of family, friend, and
significant other support in well-being among transgender and non-
binary youth. Journal of GLBT Family Studies. Advance online publi-
cation. http://dx.doi.org/10.1080/1550428X.2018.1522606
Yang, C.-C. (2006). Evaluating latent class analysis models in qualitative
phenotype identification. Computational Statistics & Data Analysis, 50,
1090 –1104. http://dx.doi.org/10.1016/j.csda.2004.11.004
Zimet, G., Dahlem, N., Zimet, S. G., & Farley, G. (1988). The Multidi-
mensional Scale of Perceived Social Support. Journal of Personality
Assessment, 52, 30 – 41. http://dx.doi.org/10.1207/s15327752jpa5201_2
Received October 9, 2018
Revision received March 26, 2019
Accepted May 16, 2019 䡲
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
11
SOCIAL SUPPORT FOR TRANS INDIVIDUALS
