Psychometric Properties of the Multidimensional Scale of Perceived Social Support (MSPSS) Across Sexual Orientation and Gender

Abstract

Lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ+) people experience marginalization, negatively impacting their social, physical, and other mental health outcomes. Studies on LGBTQ+ people utilize scales developed largely for cisgender and heterosexual (cis-hetero) people. This study explored the factor structure, construct validity, reliability, and measurement invariance of the Multidimensional Scale of Perceived Social Support (MSPSS) using a sample of 1,436 adults in the United States. Roughly one-fifth of the sample identified as gender-diverse (19.08%; n = 274), as lesbian, gay, bisexual, queer or a sexual orientation other than straight (20.61%; n = 296), and from a race or ethnicity other than White (20.06%; n = 288). Confirmatory factor analyses (CFA) supported a three-factor measurement model of the MSPSS with gender-diverse people and people who have a marginalized sexual orientation. Invariance tests revealed thresholds were similar across the cis-hetero, marginalized sexual orientations, and gender-diverse groups, supporting measurement invariance. Further, the MSPSS had good internal reliability and convergent construct validity, suggesting sufficient psychometric evidence for use of the MSPSS with people marginalized based on gender and sexual orientation.

Keywords

psychometrics measurement invariance LGBTQ+ people social support MSPSS

Lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ+) individuals often face marginalization, discrimination, and violence due to stigma from society toward their gender identity and sexual orientation. The minority stress model (Meyer, 2003) provides a framework to understand how these experiences of societal harm function as chronic stressors negatively affecting both physical and mental health outcomes in the LGBTQ+ community (Forrest et al., 2023; Grossman et al., 2016; Russell & Fish, 2016). Research has consistently shown that LGBTQ+ individuals are at a higher risk for mental health issues, including suicidal behaviors, depression, anxiety, eating disorders, and substance-use disorders (Bostwick et al., 2014; Forrest et al., 2023; Marchia et al., 2022; Mongelli et al., 2019; Parker & Harriger, 2020); in particular, transgender or gender nonconforming members of the community have been reported to experience heightened distress as demonstrated through greater prevalence of suicidal ideation and depression (Martinez-Ales et al., 2022; Testa et al., 2017), which has led to the expansion of minority stress theory in consideration of the specific ways that transgender or gender nonconforming (GNC) individuals might experience societal harm (Breslow et al., 2015).

Experiences of distal stressors such as stigma or discrimination can become internalized on an individual level as proximal stressors such as hypervigilance, self-hatred, and self-doubt (Mays & Cochran, 2001; Meyer, 2003; Newcomb & Mustanski, 2010). For GNC individuals, heightened distal stressors may emerge from the specific kind of vitriol and violence directed toward individuals that visibly transgress norms harshly reinforced for the essentialized social construct of gender (Jauk, 2013); from those experiences of gender violence, additional distal stressors such as heightened rejection sensitivity and attempts at identity concealment may also be experienced (Hendricks & Testa, 2012). Consistent exposure and internalization of these stressors for LGBTQ+ individuals results in difficulties with emotional regulation, interpersonal relationships, and cognitive processes that accumulate over time, impeding development and increasing risk for psychopathology (Wittgens et al., 2022). Although symptoms of psychopathology may be similar, minority stress theory and natural observation demonstrates how LGBTQ+ individuals might experience their mental health difficulties differently, especially given elevated risk of suicide and prevalence of disorders like depression in the community (Marchia et al., 2022). However, commonly used scales or measures for clinical assessment of symptoms as well as protective or risk factors are developed and validated using predominantly cisgender and heterosexual (cis-hetero) samples, potentially missing important nuances in LGBTQ+ experiences of mental health and compromising their applicability to this population (Moseson et al., 2020).

One protective factor for mental health and suicide risk is social support (Lew et al., 2020). For the LGBTQ+ community, several studies have highlighted the importance of social support for reducing suicide risk and mitigating the impact of minority stressors (Levitt et al., 2015; Rimmer et al., 2023; Rogowska & Cisek, 2024). Pflum et al. (2015) demonstrated how both general social support and trans community connectedness significantly reduced symptoms of depression for transgender individuals. For sexual minority people, Bariola et al. (2017) found the presence of flourishing or positive mental health measured by the Keyes’s (1998) Social Well-Being scale, was more adaptive and contributed to overall improved health than the mere absence of mental disorder. Notably, the absence of social support or rejection or “thwarted belongingness” has been associated with worse mental health outcomes, such as higher rates of suicidal ideation and attempts among transgender youth (Grossman et al., 2016; Williams et al., 2017). Experiences of social support for LGBTQ+ individuals are nuanced; their experiences within a cisgender and heteronormative society increase their exposure to rejection, invalidation, and interpersonal violence with potential sources of social support, but their capacity to cultivate “chosen family” and alternative intimate connections to resist isolation and societal harm cannot be understated, redefining what social support might look like for them. Therefore, accurately assessing a protective factor such as social support is crucial for researching and addressing the mental health needs of LGBTQ+ individuals in the United States.

Developed by Zimet et al. (1988/2010), the Multidimensional Scale of Perceived Social Support (MSPSS) is a brief 12-item scale that assesses perceived social support with three subscales measuring sources of social support from (a) family, (b) friends, and (c) a significant other. Since its inception, the MSPSS has undergone numerous studies examining its dimensions and psychometric characteristics across languages and diverse populations, establishing its use across different age groups, settings, and communities as one of the most extensively translated and validated social support measures (Aloba et al., 2019; Dambi et al., 2018; Osman et al., 2014). Just to give a sense of the breadth of its application, the MSPSS has been validated for use among university students in China (Brugnoli et al., 2022), people living with HIV/AIDS in Vietnam (Kieu et al., 2023), family caregivers of people with dementia in the United States (Cartwright et al., 2022), cancer patients and teachers in Malaysia (Song et al., 2023), and among others, pregnant individuals in rural Pakistan (Sharif et al., 2021). Exploratory factor analyses have supported the three-factor structure, corresponding with the subscales with adolescents, college students, and elderly samples (Canty-Mitchell & Zimet, 2000; Stanley et al., 1998; Zimet et al., 1988/2010). Yet, limited research has explored the validation of the MSPSS for use with the LGBTQ+ community.

Most studies using the MSPSS have been with cisgender, heterosexual samples and have often conflated gender with assigned sex at birth (Aloba et al., 2019; Osman et al., 2014). However, emerging research has examined its factor structure and measurement invariance for use with LGBTQ+ people. Barry et al. (2025) found recently that the MSPSS’ factor structure differed for gender-diverse people from cisgender samples, suggesting a potential need for a new measure of social support for gender-diverse people. In another study, Westcott and Rocconi (2024) found a three-factor structure was supported for older sexual minority women with disabilities and Kler et al. (2023) found that the three-factor structure of the MSPSS had an appropriate model fit with a sample of LGBTQ+ people of color. However, given the inconsistency in findings in these studies, the psychometric properties should be examined further with a sample of LGBTQ+ adults. Psychometric properties assess how well a measurement tool performs in terms of consistency and accuracy. Measurement invariance assesses whether the measurement tool operates equivalently across different groups (e.g., by sexual orientation or gender identity), which is crucial for ensuring that a construct is understood the same across groups. If people interpret the wording or content of a measure differently based on their lived experiences, an instrument may not be equivalent across groups. Psychometric properties and measurement invariance are particularly important in psychological research involving group comparisons, mean comparisons across measurement occasions, and differential relations between constructs by group. Additional research on the psychometric properties and measurement invariance of the MSPSS is essential for accurately measuring experiences of social support for gender-diverse adults and those who are marginalized because of sexual orientation.

Current Study

Because experiences of social support can look different for people who have marginalized sexual orientations and genders (Barry et al., 2025; Kler et al., 2023; Westcott & Rocconi, 2024), the present study examined the psychometric properties, factor structure, and measurement invariance of the MSPSS across samples of sexual orientations and genders, assessing whether it measured social support within the LGBTQ+ community as it does with cis-hetero adults. Given the emerging studies that have demonstrated differing findings for gender-diverse people (Barry et al., 2025), older sexual minority women with disabilities (Westcott & Rocconi, 2024), and LGBTQ+ people of color (Kler et al., 2023) further examination of the MSPSS and its measurement invariance, factor structure, and psychometric properties is needed. This study aimed to provide additional empirical information and continue to explore the use of the MSPSS as a measurement tool for assessing social support of LGBTQ+ adults.

Method

Procedure

The Institutional Review Board (IRB) at Binghamton University approved this study as exempt because it used publicly available secondary data from the Transgender Population Health (TransPop) study (Meyer, 2016–2018). The TransPop study is the first national probability sample of transgender individuals in the United States and includes a comparative sample of cisgender individuals, to provide researchers with a representative sample of transgender people to explore various health-relevant domains and health outcomes and behaviors. The TransPop data set was chosen because it included a large number of gender diverse participants (>200), and it was designed and distributed by researchers from the Williams Institute at UCLA School of Law, Columbia University, Harvard University, and the Fenway Institute at Fenway Health (Meyer, 2016–2018). The comprehensive methodological procedures, including recruitment strategies, informed consent, demographic data, and the survey questionnaire, have been published in the report “TransPop—U.S. Transgender Population Health Survey (Methodology and Technical Notes),” available at http://www.transpop.org/methods (Krueger et al., 2020). Data from all recruitment periods were included in the present study to ensure adequate subject group sizes to estimate factor structure across gender and sexuality, with an overall average response rate of 30.9% across all data collection phases. Gallup, Inc. (http://www.gallup.com/) was responsible for recruiting and screening participants. Detailed recruitment and screening procedures have been documented in a separate publication (Feldman et al., 2021). Eligibility for the TransPop study required participants to be at least 18 years old, who have at least a sixth-grade education, and possess English language comprehension. The initial study received approval from the Institutional Review Boards (IRBs) of Gallup, Inc., UCLA, and the collaborating institutions prior to data collection.

Participants

The TransPop sample consisted of N = 1436 adults and was designed to represent an accurate proportion of cisgender (n = 1162; 80.92%) and gender-diverse people (n = 274; 19.08%) in the U.S. population. A total 22.98% of participants (n = 296) identified their sexual orientation as lesbian, gay, bisexual, queer or something other than straight or heterosexual. Participants ranged in age from 18 to 72+ years (M = 53.14; SD = 16.87) and median household income was US$60,000 to US$74,999. Most participants or 77.02% (n = 1106) were heterosexual and 80.92% (n = 1162) were cisgender. The majority of the sample (82.24%; n = 1181) identified as White, 6.62% (n = 95) identified as Black, and 6.13% (n = 88) identified as Latine. A total of 80.78% (n = 1160) respondents reported education as “some college” or higher. Nearly half of the participants (n = 654, 45.54%) reported their relationship status as married.

Three subsamples in addition to the full sample were examined for psychometric properties and factor structure: (1) the full sample from the TransPop data set (N = 1436) which included both cis-hetero and sexual and gender minority (SGM) adults, (2) a subsample of exclusively cis-hetero adults (n = 1048), (3) a subsample of exclusively sexual minority adults (n = 296), and (4) a subsample of exclusively gender-diverse adults (n = 274). Note that the subsample for sexual minority adults had both cisgender and gender-diverse adults, while the gender-diverse subsample had both heterosexual and sexual minority adults. The cis-hetero subsample had only cisgender and heterosexual individuals. Descriptive statistics by subject group are provided in Table 1. (Cross-tabulation of gender identity and sexual orientation for the full sample is provided in Supplemental Table A1).

Table 1.

Sociodemographic Information by Subject Group.

Variable	Full sample (N = 1436)		Cis-hetero (n = 1048)		SM (n = 296)		GD (n = 274)
Age M(SD) Income (Median)	53.14 (16.87) US$60,000- US$74,999		57.16 (14.70) US$60,000- US$74,999		41.35 (17.50) US$40,000- US$49,999		39.36 (16.89) US$40,000- US$49,999
Race and ethnicity	n	%	n	%	n	%	n	%
White	1148	79.94	871	83.11	237	71.82	187	68.25
Black	79	5.50	50	4.77	27	8.18	21	7.66
Latine	89	6.20	55	5.25	30	9.09	26	9.49
Multiracial	73	5.08	44	4.20	22	7.43	24	8.76
Other^a	47	3.27	28	2.67	10	3.38	16	5.84
Gender identity
Cisman	556	38.72	507	45.84	40	13.51	–	–
Ciswoman	606	19.08	541	48.92	43	14.53	–	–
Transman	78	5.43	–	–	51	17.23	78	28.47
Transwoman	120	8.36	–	–	88	29.73	120	43.80
Gender-nonbinary	76	5.29	–	–	74	25.00	76	27.74
Sexual orientation
Straight/heterosexual	1106	77.02	1048	100	—	—	58	21.17
Lesbian	39	2.72	—	—	39	13.18	24	8.76
Gay	40	2.79	—	—	40	13.51	23	8.39
Bisexual	78	5.43	—	—	78	26.35	50	18.25
Queer	53	3.69	—	—	53	17.91	49	17.88
Same-gender loving	21	1.46	—	—	21	7.09	12	4.38
Other	24	4.04	—	—	24	8.11	24	8.76
Asexual	16	1.11	—	—	16	5.41	12	4.38
Pansexual	25	1.74	—	—	25	8.45	22	8.03
ASAB
Female	736	51.25	541	51.62	145	48.99	130	47.45
Male	700	48.75	507	48.38	151	51.01	144	52.55
Education
Less than HS Diploma	32	2.23	22	2.10	7	2.36	6	2.19
HS diploma	195	13.58	132	12.60	48	16.22	52	18.98
Technical/vocational	49	3.41	30	2.86	14	4.73	16	5.84
Some college or more	1156	80.50	864	82.44	224	75.68	196	71.53

Note. Cis-hetero = cisgender-heterosexual subsample; SM = sexual minority subsample; GD = gender-diverse subsample; ASAB = assigned sex at birth; and HS = high school.

The “other” classification was composed of people who self-identified as Asian, a Native Hawaiian/Pacific Islander, or other.

Measures

Measures for sexual orientation and gender identity were dichotomized to illustrate shared experiences of marginalization in contrast to the dominant cisgender and heterosexual identities. Systems of cisgender-heteronormativity construct binary differences in identity between the privileged and oppressed, and although individual differences exist within marginalized communities (e.g., across and within sexual orientations and gender identities), marginalized communities navigate systemic structures that reinforce and promote cisgender and heterosexual identities.

Gender Identity

Participants were asked to self-report their gender. Options were cisman, ciswoman, transman, transwoman, or transgender-nonbinary (GNB). All individuals who identified as cisman or ciswomen were coded as cisgender, and all individuals who identified as transgender or gender-diverse were coded as a gender-diverse and included in that subsample.

Sexual Orientation

Participants were asked to self-report their sexual orientation. Options were straight/heterosexual, lesbian, gay, bisexual, queer, same-gender loving, other, asexual spectrum, or pansexual. To compare people who have marginalized sexual orientations with heterosexual people, all individuals who reported a sexual orientation other than straight/heterosexual were coded as sexual minorities and were included in that subsample.

Demographic Variables

This study provided descriptive statistics on demographic information including age, race, education, assigned sex at birth (ASAB), and household income. Race categories were: White, Black, Latine, Asian, Native Hawaiian/Pacific Islander, multiracial, and other. Education level categories were from less than high school education to post-graduate work or degree. Categories for ASAB were either male or female. Respondents self-reported yearly household income by choosing from categories that ranged from none to US$150,000 or more.

Measure Tested

Social Support

The Multidimensional Scale of Perceived Social Support (MSPSS) is a 12-item widely used and well validated scale (Zimet et al., 1988/2010, 1990) for use with many populations across settings. It measures perceptions of social support from three sources: from Family (FAM), a Significant Other (SO), and Friends (FR; Zimet et al., 1988/2010). Respondents rate their agreement to statements (using a 7-item Likert-type scale: “Very strongly disagree” to “Very strongly agree”).

Measures Used to Assess Construct Validity

Psychological Distress

An underlying assumption of the MSPSS is that it inversely correlates with symptoms of psychological distress such as depression and anxiety (Zimet et al., 1988/2010). Research has since demonstrated significant negative associations between social support and psychological distress (Clara et al., 2003). Although not specifically validated for use with LGBTQ adults, the K6 is a widely used and validated measure (Bessaha, 2015; Kawakami et al., 2020; Kessler et al., 2002; Umucu et al., 2021). Respondents rated statements using a 5-item Likert-type scale (from “All of the time” to “None of the time”). Higher scores represented higher levels of distress (Kessler et al., 2002). Cronbach’s alpha for all measures are provided in Table 2; Cronbach’s alpha for psychological distress were a = .90 or higher across subject groups.

Table 2.

Pearson Correlations of Study Measures by Subject Group.

Observed scores by group	ω	a	1	2	3	4	5	6	7
Full Sample (N = 1,436)
1. MSPSS (full scale)	.95	.95	1
2. SS Family	.94	.93	.86***	1
3. SS Friend	.94	.94	.85***	.58***	1
4. SS Significant Other	.95	.95	.89***	.64***	.67***	1
5. Social well-being	.80	.80	.33***	.30***	.34***	.24***	1
6. Psychological distress	.91	.91	−.28***	−.34***	−.18***	−.21***	−.47***	1
7. AUDIT-C	.81	.75	.04	.02	.04	.04	.06*	.02	1
Cis-Hetero subsample (n = 1,048)
1. MSPSS (full scale)	.96	.96	1
2. SS Family	.93	.93	.90***	1
3. SS Friend	.95	.95	.89***	.70***	1
4. SS Significant Other	.95	.95	.91***	.74***	.71***	1
5. Social well-being	.81	.80	.32***	.29***	.35***	.24***	1
6. Psychological distress	.88	.88	−.28***	−.27***	−.23***	−.24***	−.46***	1
7. AUDIT-C	.82	.74	.08*	.05	.07*	.08*	.09**	−.03	1
SM subsample (n = 296)
1. MSPSS (full scale)	.90	.91	1
2. SS Family	.92	.91	.73***	1
3. SS Friend	.94	.94	.78***	.33***	1
4. SS Significant Other	.95	.95	.83***	.39***	.55***	1
5. Social well-being	.80	.79	.24***	.21***	.24***	.14*	1
6. Psychological distress	.90	.90	−.17**	−.26***	−.11	−.06	−.46***	1
7. AUDIT-C	.79	.75	−.03	−.03	−.03	−.02	.01	.07	1
GD subsample (n = 274)
1. MSPSS (full scale)	.91	.92	1
2. SS Family	.92	.92	.75***	1
3. SS Friend	.94	.94	.79***	.34***	1
4. SS Significant Other	.95	.95	.84***	.41***	.59***	1
5. Social well-being	.82	.82	.34***	.26***	.34***	.26***	1
6. Psychological distress	.91	.91	−.22***	−.27***	−.17**	−.13*	−.44***	1
7. AUDIT-C	.80	.77	−.10	−.07	−.05	−.10	−.03	.19**	1

Note. MSPSS = Multidimensional Scale of Perceived Social Support; SS = social support subscale; AUDIT-C = Alcohol Use Disorders Identification Test Consumption; ω = McDonald’s omega; a = Cronbach’s alpha; SM = sexual minority; and GD = gender-diverse.

p < .05. **p < .01. ***p < .001.

Social Well-Being

Keyes’ (2007) developed the Mental Health Continuum Long-Form (MHC-LF) as a measure of overall mental health or psychological well-being (Keyes, 2005). One study used this measure with lesbians, gay men, and bisexuals, but it did not specifically test measurement invariance or validity (Bariola et al., 2017). Social well-being in the present study was measured using the 15-items from the MHC-LF that measures social support across five dimensions (Keyes, 1998). Example items are provided in parentheses for each of the five domains: social integration (“I feel close to other people in my community”), social-acceptance (“I believe that people are kind”), social actualization (“The world is becoming a better place for everyone”), social contribution (“I have something valuable to give to the world”), and social coherence (“I find it easy to predict what will happen next in society”). Cronbach’s alpha for the social well-being measure was a = .79 or higher across subject groups. (See Table 2).

Alcohol Use

The Alcohol Use Disorders Identification Test Consumption (AUDIT-C) is a 3-item measure used to screen for unhealthy alcohol use using a scale of 0–12 (scores of zero reflect no alcohol use; Bush et al., 1998). Generally, the higher the AUDIT-C score, the more likely it is that a person’s alcohol consumption is affecting their health and safety; it has been validated for use with gender diverse adults (Dermody et al., 2023) and sexual minority people (Horvath et al., 2023). Cronbach’s alpha for AUDIT-C for the full, cis-hetero, sexual minority, and gender minority subsamples were a = .75, a = .74, a = .75, and a = .77 respectively.

Data Analysis

Stata MP 18.5 was used to conduct all analyses. The internal consistency for observed scores on the MSPSS subscales were assessed using the traditional Cronbach’s alpha coefficient and McDonald’s omega (ω) values, which yield a better estimate of the reliability of the aggregate score of the items within a construct (Brunner et al., 2012; Dunn et al., 2014; McDonald, 1981). Like Cronbach’s alpha, McDonald’s omega ranges between zero and one. The higher its value the more reliable the scale. Convergent and divergent validity were assessed by calculating Pearson correlations for the full MSPSS, subscales, social well-being measure, K6, and AUDIT-C. For convergent validity, the Keyes’ social well-being measure was anticipated to have significant positive correlations with the full scale and subscales, and the K6 was anticipated to have significant negative correlations with the full scale and subscales. For divergent or discriminant validity, the AUDIT-C was anticipated to be unrelated to the MSPSS and subscales across subject groups.

Using the full sample, one-way analysis of variance (ANOVA) tests were conducted on the MSPSS full scale and its three subscales to compare mean differences for each across sexual orientations and gender identities. Bartlett’s test was used to assess if variances were unequal for each ANOVA. If homogeneity of variance held, omega-squared effect sizes and Tukey’s Honestly Significant Difference (HSD) post hoc test were calculated to learn which group means were significantly different. If Bartlett’s test was significant, Welch’s ANOVA was conducted and epsilon squared (ε²) effect size calculated, followed by Games-Howell post hoc test to compare group means. Further, the Welch unequal variance t-tests and ANOVAs were conducted to compare means of the full MSPSS and its subscales by sexual orientation (heterosexual compared with sexual minority) and by gender identity (cisgender compared with gender-diverse) and to examine between group mean differences. The Welch tests use Satterthwaite’s degrees of freedom, which is a more accurate and more conservative method than assuming equal variances, particularly when sample sizes of comparison groups are different (Ruxton, 2006).

The three-dimensional structure of the MSPSS across samples were tested. Confirmatory factor analyses (CFA) were conducted with the full TransPop sample (N = 1,436), the cis-hetero subsample (n = 1,048), sexual minority subsample (n = 296), and then finally with the gender-diverse subsample (n = 274). CFA is an analytic technique that can help evaluate the scores and allows for testing of an a priori factor structure of a specific measurement tool before estimating the latent constructs while correcting for measurement errors. CFA was used instead of exploratory factor analyses (EFAs) because the MSPSS scale has clearly defined three subscales. Promax rotation was used for each CFA, because it is an oblique rotation method that allows factors to be correlated in a CFA and can be used to reduce the number of measures of interest into a smaller number of factors (Tabachnick & Fidell, 2007). Items with a factor loading greater than .3 were considered significant (Kline, 2002). One-, two-, and three-factor solutions and model fit indices were examined for each subject group to determine if the three-factor solution corresponding with the subscales of the MSPSS had a good model fit across subject groups (Fabrigar et al., 1999; Finch, 2020; Hu & Bentler, 1999; Marsh et al., 2004). After establishing the best model, structural equation modeling was used and factor loadings for the observed items of the MSPSS were calculated by constraining the first loading to one for each subject group and to determine overall model data fit.

Structural equation modeling with maximum likelihood (ML) estimation was then conducted to assess measurement invariance across sexual orientation and gender by using nested models with an increasing degree of restriction to compare model-fit. ML estimation was chosen because it is considered a best estimator with Likert-type scales of five or more points (Finney & DiStefano, 2006). After estimating the global model with the full sample (N = 1,436), two base models were allowed free estimation of all parameters to examine configural invariance across sexual orientation and gender. The second nested model tested “weak” measurement invariance across groups and included restriction of factor loadings and intercepts. This model tested that each observed item contributed to the latent constructs to a similar degree, and that item intercepts were equal across groups, which is crucial for meaningful comparisons between groups. Next, nested in this second model the “strong” measurement invariance model was tested, and the residual variances were constrained. And finally, nested in the third model the “strict” measurement invariance model was tested, and factor means were constrained in the comparison groups. Establishment of measurement invariance of the MSPSS across sexual orientation and gender were based on changes (Δ) in the CFI (ΔCFI), RMSEA (ΔRMSEA), and SRMR (ΔSRMR) between the increasingly constrained models. Metric invariance is supported by ΔCFI ≤ −.01, ΔRMSEA ≤ .015, and ΔSRMR ≤ .03 in comparison to the configural model, while scalar invariance is supported by ΔCFI ≤ −.01, ΔRMSEA ≤ .015 and ΔSRMR ≤ .01 compared with the metric model (Chen, 2007). For example, a ΔCFI between models greater than .01 would suggest the absence of measurement invariance (Cheung & Rensvold, 2002). The confirmation of measurement invariance would support the equivalency of the MSPSS for use with gender-diverse and sexual minority adults.

To establish goodness-of-fit for each model, the comparative fit index (CFI) and root mean square error of approximation (RMSEA) indices with 90% confidence interval were used. RMSEA values < 0.06 were considered an excellent model fit and < 0.09 acceptable. Comparative fit index (CFI) and Tucker–Lewis’s index (TLI) values were assessed (>0.95 considered excellent and >0.90 good model fit). Standardized root mean square residual (SRMSR) values between 0 and 0.08 were considered a good model fit and coefficients of determination were reported (Hu & Bentler, 1999). Normality was assessed using the skewness and kurtosis for observed scores on the MSPSS full scale, subscales, social well-being measure, K6, and AUDIT-C for each subject group (Curran et al., 1996). Prior to data analysis, variables were cleaned and patterns of missingness were explored (Austin & Steyerberg, 2015). No variables included in the analyses had greater than 5% of responses missing (missingness ranged from .28% to 4.87%). Patterns of missing data were explored by creating dummy variables for missing data and using logistic regressions to examine if any missing data patterns were present for the model variables. No significant predictors of missingness were identified (McArdle, 2013; Schafer & Graham, 2002); complete case analyses were used.

Results

Consistency, Reliability, and Validity

The full MSPSS and its subscales (FAM, SO, and FR) demonstrated good internal consistency and reliability for cis-hetero, sexual minority, and gender-diverse subject groups. Good internal consistency and reliability were demonstrated by Cronbach’s alpha and McDonald’s omega as reported in Table 2. Omega coefficients for the full MSPSS scale and three-factor corresponding subscales were computed (alpha ranged a = .91 to .96 and omega ranged ω = .90 to .96).

Upon calculation of Pearson’s correlation coefficients for each subject group, the full MSPSS and its subscales demonstrated acceptable convergent validity, with small to medium effect sizes. For the cis-hetero and gender-diverse subsamples, the full MSPSS and its subscales were significantly correlated with the social well-being measure as expected, with medium effect sizes (ranging r = .24 to .35), but it had small to medium effect sizes for the sexual minority subsample (ranging r = .14 to .24). The full MSPSS and the FAM subscale were significantly negatively correlated with the K6 across subject groups as expected: the cis-hetero subsample had medium effect sizes for these relationships (ranging r = −.23 to −.28), the gender-diverse subsample had small to medium effect sizes (ranging r = −.13 to −.22), and the sexual minority subsample had small to medium effect sizes (r = −.17 to r = −.26). However, the FR and SO subscales were unrelated to the K6 for the sexual minority subsample. For divergent validity, despite predictions that the AUDIT-C would be unrelated to the MSPSS and its subscales, the full scale and the SO and FR subscales were significantly correlated to the AUDIT-C, but only for the cis-hetero subsample and with very small effect sizes (ranging r = .07 to r = .08). As predicted, no significant relationships between the AUDIT-C and the MSPSS and subscales were found for the sexual minority and gender-diverse subsamples. Although results provided evidence for convergent and divergent validity, findings were inconsistent across subject groups.

The Welch t-tests demonstrated the mean scores were significantly different between sexual minority and heterosexual scores on the MSPSS and the FAM and SO subscales. Scores were also significantly different between gender-diverse and cisgender people on the MSPSS and its FAM and SO subscales (see Table 3). Several one-way ANOVAs revealed significant differences when comparing by sexual orientation, with small effect size for the full MSPSS, F(8, 1,315) = 5.81, p < .001, ω² = .028, a medium effect size for the FAM subscale, F(8, 1,342) = 16.03, p < .001, ω² = .082, and a small effect size for the SO subscale, F(8, 1,342) = 3.63, p < .001, ω² = .015, but no significant differences for the FR subscale. Tukey’s post hoc comparisons revealed that lesbian, bisexual, and asexual people had significantly lower full MSPSS means compared with straight/heterosexual people. Similarly, lesbian, gay, bisexual, queer, and pansexual people had significantly lower FAM subscale means compared with straight/heterosexual people. And finally, lesbians had significantly lower SO subscale means compared with straight/heterosexual people. No other pairwise comparisons across sexual orientations were statistically significant. (See Supplemental Table A2.)

Table 3.

Welch Tests Examining Mean Differences for MSPSS Full Scale and Subscales by Gender and Sexual Orientation.

Variable	Heterosexual		Sexual minority		t (df)	p	Cohen’s d
Variable	M	SD	M	SD	t (df)	p	Cohen’s d
MSPSS (Full Scale)	5.48	1.36	4.92	1.27	6.50 (476.20)	.00	.42
SS Family	5.40	1.54	4.27	1.68	10.29 (431.49)	.00	.72
SS Friend	5.36	1.45	5.27	1.50	.82 (446.02)	.41	.06
SS Significant Other	5.70	1.56	5.28	1.71	3.80 (426.91)	.00	.27
	Cisgender		Gender-diverse		t (df)	p	Cohen’s d
	M	SD	M	SD	t (df)	p	Cohen’s d
MSPSS (Full Scale)	5.46	1.35	4.98	1.33	5.30 (409.46)	.00	.36
SS Family	5.38	1.52	4.25	1.78	9.51 (367.52)	.00	.71
SS Friend	5.34	1.45	5.33	1.52	.06 (398.06)	.95	.00
SS Significant Other	5.68	1.56	5.36	1.74	2.74 (382.41)	.01	.20

Note. df = Welch degrees of freedom.

Several Welch’s ANOVAs were used to compare the means for the full MSPSS, the FAM subscale, and the SO subscale by gender because the Bartlett test was significant for each, full MSPSS: χ²(4) = 13.38, p = .01, FAM: χ²(4) = 13.87, p = .01, and SO: χ²(4) = 23.09, p < .001. Welch’s ANOVAs revealed significant differences when comparing by gender, with medium effect for the full MSPSS, F(4, 248.04) = 8.90, p < .001, ε² = .11, a large effect for the FAM subscale, F(4, 237.87) = 23.60, p < .001, ε² = .27, and a medium effect for the SO subscale, F(4, 247.72) = 5.57, p < .001, ε² = .07. Games–Howell post hoc tests showed that transwomen had significantly lower full MSPSS means compared with cismen, ciswomen, and transmen. GNB people had lower full MSPSS means compared with ciswomen. Similarly, transmen, transwomen, and GNB people had significantly lower FAM subscale means compared with cismen and ciswomen. Transwomen had significantly lower SO subscale means compared with cismen, ciswomen, and transmen. And finally, a one-way ANOVA revealed significant differences when comparing by gender, with a small effect for the FR subscale, F(4, 1,368) = 4.06, p < .01, ω² = .009. Tukey’s post hoc comparison revealed that ciswomen had significantly higher FR subscale means compared with cismen. No other pairwise comparisons across genders were statistically significant. (See Supplemental Table A3.)

Factor Structure

The fit indices for the one-, two-, and three-factor models by subject group are provided in Table 4. Findings supported the three-factor solution across subject groups, and it had the most parsimonious structure regardless of sexual orientation or gender identity. Notably though, the RMSEA for the three-factor solution for the full sample and each subject group indicated only a marginal fit (ranging RMSEA = .10 to .11). The three-factor solution corresponded with the MSPSS subscales—support from FAM, FR, and SO. Factor loadings for each item of the MSPSS were well above .3 (ranging from .68 to .95) when conducting the CFA with subject groups (Kline, 2002). Constrained factor loadings were significant for each item when SEM was used to estimate the model; these constrained factor loadings are provided in Table 5.

Table 4.

Goodness-of-Fit Indices Comparing Factor Models of the MSPSS by Subject Group.

Subject group	Factors	ꭓ²(df)	RMSEA	AIC/BIC	CFI/TLI	SRMR	CD
Full Sample (N = 1436)	One-factor	5,932.98 (54)***	.29***	51,282.15/51,469.34	.66/58	.12	.95
	Two-factor	3,472.92 (52)***	.22***	48,826.10/49,023.69	.80/.75	.08	.93
	Three-factor	708.60 (51) ***	.10 ***	46,063.78/46,266.56	.96/.95	.02	.87
Cis-Hetero Subsample (n = 1048)	One-factor	3,487.05 (54)***	.25***	35,327.27/35,503.40	.74/.69	.08	.96
	Two-factor^a	1,959.09 (52)***	.19***	33,803.31/33,989.25	.86/.82	.06	.97
	Three-factor	639.07 (51) ***	.11 ***	32,485.29/32,676.10	.96/.94	.03	.91
SM Subsample (n = 296)	One-factor	1,627.69 (54)***	.32***	11,874.17/12,005.54	.52/.42	.20	.95
	Two-factor	970.99 (52)***	.25***	11,221.47/11,360.13	.72/.65	.13	.64
	Three-factor	192.23 (51) ***	.10 ***	10,444.71/10,587.02	.96/.95	.03	.80
GD Subsample (n = 274)	One-factor	1,472.85 (54)***	.32***	11,125.65/11,254.38	.54/.44	.19	.95
	Two-factor	811.22 (52)***	.24***	10,468.02/10,603.90	.76/.69	.12	.63
	Three-factor	172.81 (51) ***	.10 ***	9,831.61/9,971.07	.96/.95	.03	.82

Note. Bold indicates the best fitting model to the data; cis-hetero = cisgender and heterosexual; SM = sexual minority; GD = gender-diverse; ꭓ²(df) = chi-square likelihood ratio (degrees of freedom); RMSEA = root mean squared error of approximation; AIC = Akaike information criterion; BIC = Bayesian information criterion; CFI = comparative fit index; TLI = Tucker–Lewis index; and SRMR = standardized root mean squared residual; CD = coefficient of determination.

Indicates different item loadings for two-factor structure.

**p < .001.

Table 5.

Constrained Factor Loadings for MSPSS Items by Subscale (Three-Factor Solution) across Subject Groups.

MSPSS items by subscale	Subject groups
MSPSS items by subscale	Full sample (N = 1,436)	Cis-hetero (n = 1,048)	SM (n = 296)	GD (n = 274)
Family Subscale
My family tries to help me.	1.00***	1.00***	1.00***	1.00***
I get emotional help and support from my family.	1.14***	1.10***	1.17***	1.14***
I can talk about my problems with my family.	1.05***	1.01***	1.03***	1.05***
My family is willing to help me make decisions.	1.01***	1.00***	1.01***	1.00***
Friend Subscale
My friends really try to help me.	1.00***	1.00***	1.00***	1.00***
I can count on my friends when things go wrong.	1.02***	1.02***	1.03***	1.02***
I have friends with whom I share joys and sorrows.	1.05***	1.05***	1.02***	1.06***
I can talk about my problems with my friends.	.98***	.98***	1.02***	.98***
Significant Other Subscale
There is a special person around when I am in need.	1.00***	1.00***	1.00***	1.00***
There is a special person I share joys and sorrows with.	1.00***	1.01***	1.01***	.99***
I have a special person who is a source of comfort.	.99***	1.00***	1.02***	.99***
There is a special person who cares about feelings.	.98***	.99***	1.02***	.97***

Note. MSPSS = Multidimensional Scale of Perceived Social Support; cis-hetero = cisgender-heterosexual subsample; SM = sexual minority subsample, GD = gender-diverse subsample.

***

p < .001.

Measurement Invariance

Table 6 shows the results of the three-factor model by subject group, and the nested invariance models in ascending order of level of restriction across groups by sexual orientation (heterosexual and sexual minority) and gender (cisgender and gender-diverse). Configural, weak, and strong invariance were achieved, given the ΔCFI, ΔRMSEA, and ΔSRMR were within acceptable parameters as outlined. Metric invariance was supported because the ΔCFI ≤ −.01, ΔRMSEA ≤ .015 and ΔSRMR ≤ .03 relative to the configural model. Scalar invariance was supported because the ΔCFI ≤ −.01, ΔRMSEA ≤ .015 and ΔSRMR ≤ .01 relative to the metric model (Chen, 2007). A ΔCFI between models greater than .01 would suggest the absence of measurement invariance. Findings confirmed that each observed item contributed to the latent constructs to a similar degree across groups, and the item intercepts were comparable across groups. These findings are crucial for meaningful comparisons between heterosexual and sexual minority people, as well as between cisgender and gender-diverse people. Said differently, the MSPSS three-factor model had good invariance across sexual orientation and gender, and the probability of a response for each item of the MSPSS was similar for all groups. These results allow the comparison of latent means for the subscales of the MSPSS between heterosexual and sexual minority adults and cisgender and gender-diverse adults.

Table 6.

Goodness-of-Fit Indices for MSPSS Three-Factor Model and Measurement Invariance across Sexual Orientation and Gender.

Models		ꭓ²(df)	RMSEA [90% CI]	CFI	TLI	SRMR	ΔRMSEA	ΔCFI	ΔSRMR
Three-Factor Model		708.60 (51)***	.098 [.092, .105]	.962	.951	.024	—	—	—
Invariance model across sexual orientation	Configural	798.75 (102)***	.102 [.095, .108]	.959	.947	.030	—	—	—
	Weak	852.91 (120)***	.096 [.090, .102]	.957	.953	.032	−.006	−.002	.002
	Strong	961.70 (132)***	.097 [.092, .103]	.951	.951	.035	.001	−.006	.003
	Strict	1,068.55 (135)***	.102 [.097, .108]	.945	.946	.086	−.005	.006	−.051
Invariance model across gender identity	Configural	828.10 (102)***	.103 [.097, .110]	.958	.946	.029	—	—	—
	Weak	866.96 (120)***	.096 [.090, .103]	.957	.953	.030	−.007	−.001	.001
	Strong	983.66 (132)***	.098 [.093, .104]	.951	.951	.033	.002	−.006	.003
	Strict	1,080.18 (135)***	.102 [.097, .108]	.945	.947	.079	−.004	.006	.004

Note. ꭓ²(df) = chi-square likelihood ratio (degrees of freedom); RMSEA = root mean squared error of approximation; CFI = comparative fit index; TLI = Tucker–Lewis index; SRMR = standardized root mean squared residual; Δ = difference or change.

**p < .001.

Discussion

This study investigated the measurement invariance, factor structure, and psychometric properties of the MSPSS for gender-diverse adults and people who have marginalized sexual orientations in the United States, contributing to the emerging literature exploring the use of the MSPSS with LGBTQ+ adults. Analyses were conducted with the TransPop (Meyer, 2016–2018) data set and findings suggested that the MSPSS three-factor model was acceptable for LGBTQ+ people, coinciding with the three subscales of social support from FAM, FR, and SO. The MSPSS had good internal consistency, acceptable construct validity, and reliability across the subject groups and measurement invariance was achieved. Furthermore, notable comparisons between groups revealed some important areas for further exploration. Mean comparisons revealed significantly different averages of the MSPSS and its subscales across sexual orientations and genders.

Although most of the model fit statistics were acceptable, the RMSEA was marginal for the full sample and all subject groups, including the full sample and cis-hetero subsample. As a potential explanation, Kenny et al. (2015) studied the performance of the RMSEA for models with small degrees of freedom and small sample sizes, finding that as degrees of freedom decreased, model rejection rates increased for the RMSEA, even with sample sizes as large as 1,000. This is important given that the size and characteristics of the subject groups examined in the present study were all under 1,500 and well under 1,000 for the sexual minority and gender-diverse subsamples. Furthermore, the full MSPSS demonstrated good internal consistency and convergent validity.

Measurement invariance assesses whether a measurement tool operates equivalently across different groups (e.g., by sexual orientation or gender identity), determining if the content of the measure is understood the same across groups; when measurement invariance is overlooked, conclusions may be overgeneralized without accurately reflecting the experiences of different groups with negative implications for future research, policy, and intervention (Slof-Op’t Landt et al., 2009). Results demonstrated the mean scores were significantly different between sexual minority and heterosexual and cisgender and gender-diverse scores on the MSPSS and most of its subscales except for the FR subscale. Examining mean differences more closely between groups, more differences were revealed and highlighted a gap in our understanding about social support for LGBTQ+ people. Future research could explore whether these mean differences may reflect differing support, or something else. Findings suggest either different interpretations of the questions, or potentially varying rates of social support for gender-diverse people and people who have marginalized sexual orientations. Clearly it is crucial to evaluate measurement invariance of the MSPSS for LGBTQ+ adults because of potential differences in the ways social support may be experienced. LGBTQ+ people may have relational experiences outside cis-heteronormative ideals, redefining and blurring distinctions of social support from FAM, FR, and SO (Bertone & Pallotta-Chiarollo, 2015; Sarna et al., 2021). Our findings demonstrated the MSPSS three-factor model had good invariance across sexual orientation and gender, however findings should be explored with other samples of gender-diverse and sexual minority people to confirm this and explore divergent validity further with other measures.

In early assessment of the psychometric properties for the MSPSS, Zimet et al. (1990) emphasized the importance of evaluating potential nuances in understanding of each subscale, exploring what participants might consider as “family” in the FAM subscale or a “special person” in the SO subscale. For example, the term “special person” in the MSPSS could refer to different individuals (e.g., partner, close friend, therapist, etc.) with whom a participant has an intimate relationship with and, if someone is polyamorous, further clarification may be needed. Polyamory is typically defined as the practice or desire for intimate relationships with more than one partner, where all partners are aware of and consent to the arrangement (Barker & Langdridge, 2010). Questions from the MSPSS only ask about one “special person” and do not account for polyamory or other diverse relationship structures in which there may be more than one “special person” that a participant can refer to. Furthermore, Zimet et al. (1990) highlighted the meaning of family may change due to factors such age, marital status, and number of children; for the LGBTQ+ community, the meaning of family is also shaped by the ways in which their biological families engage with or reinforce stigma for their marginalized identities as well as the ways they might resist ideals of the traditional nuclear family that can blur the distinction between family and friends (Bertone & Pallotta-Chiarollo, 2015; Sarna et al., 2021). While these findings indicate measurement of social support for LGBTQ+ adults using the MSPSS is sufficiently similar to their cisgender, heterosexual counterparts, it is important to consider broadening the scale to avoid construct under-representation (Messick, 1995) and to align with theoretical recognition of other domains of social support that exist for the LGBTQ+ community.

These findings are particularly important because social support has been associated as a protective factor against negative health outcomes and suicide for the LGBTQ+ community, especially as a potential moderator for minority stress (Casey et al., 2022; Meyer, 2003). Validating the MSPSS for use with LGBTQ+ adults can help guide further research or intervention to address the high prevalence of mental health concerns within the community, specifically identifying important sources and the influence of social support for unique minority stressors (Bostwick et al., 2014; Forrest et al., 2023; Parker & Harriger, 2020).

As with all studies, limitations exist, and findings should be interpreted in the context of these limitations. First, the full sample was demographically representative of the U.S. population because it was a probability sample, but probability sampling may not ensure unbiased inference; future studies should consider replicating findings to ensure the MSPSS has high factor loadings, internal consistency, and construct validity with other samples of LGBTQ+ adults. Second, this study used a cross-sectional survey, which limited the extent to which conclusions and longitudinal studies would allow researchers to limit common method bias. The third limitation was that the participants’ ages ranged widely, and data was collected between 2016 and 2018. Given the ever-changing sociopolitical climate in the United States and across the participants’ lifespans, examining measurement invariance across ages and with a more recent sample may provide further information about the MSPSS and its use with LGBTQ+ individuals today. Fourth, identities in this study were grouped together in binary categories of gender-diverse people and those who have marginalized sexual orientations; additional analyses to understand the psychometric properties and measurement invariance of the MSPSS across distinct and intersectional identities within the LGBTQ+ community is warranted. And finally, a fifth limitation was that although the AUDIT-C has been validated for use with LGBTQ+ people, the K6 and social well-being measures have not, which may limit the ability to reliably establish construct validity. Future studies should continue to explore validity of these measures and others for use with LGBTQ+ people. To provide additional evidence of reliability for the MSPSS, its psychometric properties should be examined with other samples of LGBTQ+ adults. Future studies could also investigate whether the psychometric properties and measurement invariance are consistent for other samples of LGBTQ+ globally, and particularly whether it can be used with LGBTQ+ youth.

Conclusion

This study yields important and relevant findings about the MSPSS and its ability to measure social support for LGBTQ+ adults in the United States. Findings suggested acceptable use of this research instrument with gender-diverse people and those who have marginalized sexual orientations. It is critical that social science researchers ensure the measurement of scales being utilized are culturally relevant and have sound psychometric properties for populations of interest. This study provides evidence that MSPSS is an acceptable tool to measure perceived social support from FAM, FR, and SO for LGBTQ+ adults, however additional research that continues to examine its psychometric properties using other LGBTQ+ samples is warranted.

Supplemental Material

sj-docx-1-asm-10.1177_10731911251381536 – Supplemental material for Psychometric Properties of the Multidimensional Scale of Perceived Social Support (MSPSS) Across Sexual Orientation and Gender

Supplemental material, sj-docx-1-asm-10.1177_10731911251381536 for Psychometric Properties of the Multidimensional Scale of Perceived Social Support (MSPSS) Across Sexual Orientation and Gender by Kelley Cook in Assessment

Footnotes

Acknowledgements

The author acknowledges contributions from Adam Zhao a doctoral student in the Community Research and Action program at Binghamton University for reviewing and editing an initial version of the manuscript.

Data Availability

The author had full access to the publicly available data in the study and took responsibility for the integrity and the accuracy of the data analysis. The TransPop data set is a publicly available data set. Data can be found at the Inter-university Consortium for Political and Social Research (doi:10.3886/ICPSR37938.v1).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Ethical Considerations

The Institutional Review Board (IRB) at Binghamton University, SUNY approved this study as exempt.

Consent to Participate

Not applicable; the comprehensive methodological procedures, including informed consent are published in the report “TransPop—US Transgender Population Health Survey (Methodology and Technical Notes),” available at http://www.transpop.org/methods (Krueger et al., 2020).

ORCID iD

Kelley Cook

Supplemental Material

Supplemental material for this article is available online.

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