Racial and Ethnic Disparities in Barriers to Mental Health Treatment in United States College Students

Abstract

Objectives:

In a national sample of college students, this study aimed to evaluate whether barriers to mental health treatment varied by race and ethnicity.

Methods:

Data were drawn from a large multicampus study conducted across 26 US colleges and universities. The sample (n = 5841) included students who screened positive for at least one mental health disorder and who were not currently receiving psychotherapy.

Results:

The most prevalent barriers across the entire sample were preferring to deal with issues on one’s own, lack of time, and financial difficulties. Black and Hispanic/Latine individuals reported a greater willingness to seek treatment than White individuals. However, Black and Hispanic/Latine individuals faced more financial barriers to treatment, whereas Hispanic/Latine individuals also showed a lower perceived importance of mental health. Asian American individuals preferred to handle their issues on their own or with support from family/friends and had lower readiness, willingness, and intentionality to seek help than White individuals, with greater financial barriers as well.

Conclusions:

Disparities in unmet treatment need may arise from both distinct and common barriers and point to the potential benefits of tailored intervention approaches to address the unique needs of students of color from varying racial and ethnic backgrounds. Findings further underscore the pressing need for the low-cost brief treatment models that can be employed or accessed independently to address the most prevalent barriers across all students.

Mental health problems are highly prevalent in college students, with approximately 1 in 3 screening positive for at least one mental health disorder.¹ Estimates of mental health disorder prevalence have increased to as much as 60–70% over the course of the COVID-19 pandemic. ^2,3 At the same time, the landscape of higher education has become increasingly diverse, with over 45% of U.S. undergraduates identifying as people of color.⁴ Despite similar or greater disorder prevalence rates, students of color report lower rates of treatment utilization compared to their White peers. ^5,6 This suggests there may be additional barriers to treatment in this vulnerable population. Understanding what antecedents and barriers may impact disparities in the mental health care of college students may help inform efforts of colleges to close this treatment gap.

According to Andersen’s behavioral model of healthcare use, ⁷ treatment seeking is impacted by three major determinants: 1) need for services (e.g., clinical severity; perceived need); 2) predisposing characteristics (e.g., demographics; beliefs and attitudes); and 3) enabling characteristics (e.g., available funds to pay for services). Predisposing characteristics have also been referred to as attitudinal barriers, whereas enabling characteristics have been conceptualized in relation to structural barriers.⁸ These factors work together to determine treatment seeking. For example, whereas individuals may perceive a strong need for treatment, they may face attitudinal or structural barriers such as the inability to afford the cost of treatment, lack of dissemination of information about where and how to access care, or lack time to attend treatment.⁹ Understanding the specific blockage points or barriers in each of these domains and how they may vary across unique racial and ethnic groups is critical to ensure approaches to culturally competent intervention that effectively target areas of concern. Although several studies have examined each of these factors separately, they often did so in predominantly White samples, or in single-campus designs with small sample sizes focusing on one racial and ethnic group. ^9–12 There is a pressing need for large-scale, nationwide studies of students of color that assess how each of these factors may differentially impact individuals from diverse racial and ethnic groups to develop a comprehensive understanding of barriers to obtaining mental health services.

The purpose of the present study was to examine unmet mental health treatment needs in college students of color and identify the nature, prevalence, and patterns of barriers to receiving mental health treatment. Data were drawn from a multicampus study of college student mental health across the US and included students who screened positive for at least one mental health disorder but who were not currently receiving psychotherapy.

Methods

Participants and Procedure

Data were collected from 31,285 undergraduate students from 26 U.S. colleges and universities during October 2019 to November 2021. Students enrolled at participating universities received an email invitation to complete an eligibility screen for a randomized-controlled trial (RCT) on a digital mental health intervention (see ¹³ for full information). Eligible students (n = 6874) answered questions about their motivation for and barriers to mental health treatment. Students ≥ 18 years old who screened at clinical levels for at least one mental health disorder and had no current mental health service use were included in the present sample. Of the initial sample, n = 921 individuals who did not meet criteria for any mental health disorder were excluded, as were n = 85 that had missing values for race and ethnicity or belonged to groups that were too small to draw meaningful comparisons (e.g., n = 13; n = 14; see online supplement for descriptive statistics). The resulting final analytic sample was n = 5841.

Measures

Demographics.

Participants were asked to report their sex, race, ethnicity, first-generation college student status (as assessed by parental education; 1 = first generation/no parents with a bachelor’s degree; 0 = not first generation), and financial hardship (“In the past month during college, how hard has it been for you to pay for expenses like tuition, textbooks, course materials, food, housing, and medical care?”; 1 = past month hardship; 0 = no hardship).

Mental Health Diagnoses.

Diagnoses were assessed with standardized screening tools. All diagnostic measures and their references are available in the online supplement.¹³

Barriers to Mental Health Treatment.

To obtain a comprehensive barriers assessment, items assessed attitudinal barriers, structural barriers, and personal preferences. All items were drawn from the Healthy Minds Study¹⁴, using an adapted version of the validated Healthcare for Communities Survey¹⁵ Attitudinal barriers were assessed with items that addressed help-seeking attitudes, intentions, and perceived importance of improving mental health. Perceived importance of mental health was rated from 0 = Not important to 10 = Extremely important. Help-seeking attitudes and intentions comprised willingness (“I am willing to seek help for emotional/mental health problems”; 1 = strongly disagree; 6 = strongly agree), intentions (“I have seriously considered seeking help for emotional/mental health problems”; 1 = strongly disagree; 6 = strongly agree), and readiness (“How ready are you at the present time to seek help for your emotional/mental health?”; 0 = Definitely not ready to 10 = Definitely ready). Personal preferences were assessed as follows: prefer to deal with issues on my own, prefer to deal with issues with support from family/friends (1 = endorsed, 0 = not endorsed)..

Structural barriers were assessed with the question “In the past 12 months, which of the following factors have caused you to receive fewer services (counseling, therapy, or medications) for your mental or emotional health than you would have otherwise received?” Response options were as follows: financial reasons (too expensive, not covered by insurance), not enough time, not sure where to go, difficulty finding an available appointment, no barriers. Participants could select multiple response options, though “no barriers” was mutually exclusive. Items were coded as binary (1 = endorsed, 0 = not endorsed).

Need for Services.

Subjective current and past 12-month perceived need for treatment was assessed using 6-point Likert scales (1 = strongly disagree to 6 = strongly agree); higher numbers indicate greater perceived need.

Statistical Analysis

Analyses were performed in R version 4.0.2. Missing data were handled using the multiple imputation (K = 10) using maximum likelihood estimation. To compare prevalence of disorders, financial hardship, first-generation status, and barriers to treatment across race and ethnicity, we used χ² tests of independence for all categorical items and ANOVAs for all continuous items. Pairwise comparisons with Bonferroni-corrected post-hoc tests were used to probe significance differences across groups.

Results

Descriptive Statistics

Demographic and Clinical Information.

Table 1 shows demographic and clinical information of participants in the current study. Table 2 shows the proportion of participants meeting screening criteria for each psychological disorder and differences across racial and ethnic groups, χ² tests of independence for differences in disorder prevalence across groups. Overall, disorder prevalence was similar across groups with small but significant differences in rates of major depressive disorder, generalized anxiety disorder, alcohol use disorder, panic disorder, PTSD, and insomnia. In addition, there were significant differences across groups in financial hardship and first-generation status, with Black and Latine students reporting the highest prevalence of financial hardship as well as of first-generation status (see online supplement).

Table 1.

Demographics and Disorder Prevalence of Students with at Least One Clinical Disorder (N = 5841)

Variable	N or M	SD or %
Age	20.2	3.94
Sex
Male	1452	0.25
Female	4388	0.75
Intersex	1	--
Race/Ethnicity
Non-Hispanic/Latine White	3298	0.56
Non-Hispanic/Latine Asian	777	0.13
Non-Hispanic/Latine Black	375	0.06
Non-Hispanic/Latine Multiracial	340	0.06
Hispanic/Latine	1051	0.18
First Generation College Student Status
First Generation	2102	0.36
Not First Generation	3739	0.64
Self-Report Financial Hardship
No Hardship	3904	0.67
Hardship	1937	0.33
Clinical Disorder Prevalence
Major Depressive Disorder	3985	0.68
Generalized Anxiety Disorder	2819	0.48
Social Anxiety Disorder	1534	0.26
Panic Disorder	942	0.16
Posttraumatic Stress Disorder	2785	0.48
Eating Disorder	1273	0.22
Insomnia	1844	0.32
Alcohol Use Disorder	2600	0.45

Note. Sex was assessed with the question “What was your sex at birth?” and included four response options: male, female, intersex, don’t know.”

Table 2.

Disorder Prevalence by Race and Ethnicity.

			NHL White		NHL Black		NHL Asian		NHL Multiracial		Hispanic/Latine
Disorder	Diagnostic Measure	α	N	%	N	%	N	%	N	%	N	%	χ2 (4)	V	Significant Pairwise Comparisons
Major depressive disorder	Patient Health Questionnaire-9	0.84	2156	65	282	75	561	72	225	66	760	72	8.73*	0.10	w<h, a, b
Generalized anxiety Disorder	Generalized Anxiety Disorder Questionnaire-IV	0.91	1569	48	197	53	335	43	157	46	560	53	5.61*	0.10	w, a<h; a< b
Social anxiety disorder	Social Phobia Diagnostic Questionnaire	0.96	873	27	104	28	198	26	91	27	268	26	0.25	0.00	N/A
Panic disorder	Panic Disorder Self-Report	0.84	583	18	56	14	71	9	51	15	181	17	8.80*	0.10	a<b, h, w
PTSD	Primary Care PTSD Screen	0.86	1537	47	186	49	361	47	158	46	544	52	2.39*	0.00	w<h
Insomnia	Insomnia Severity Index	0.98	930	28	155	41	242	31	115	34	401	38	14.00*	0.10	w, a<h, b
Alcohol use disorder	Alcohol Use Disorders Identification Test	0.77	1753	53	107	29	225	29	143	42	371	35	62.59*	0.20	b, a, h, m<w; b, a<m
Eating disorder	Stanford-Washington Eating Disorder Screen	0.78	703	21	73	20	169	22	76	22	252	24	1.07	0.30	N/A

Note. NHL = Non-Hispanic/Latine. α = Cronbach’s alpha. V = Cramer’s V measure of effect size. Eating disorder categeory encompassed bulimia nervosa and binge eating disorder. All participants were selected for having at least one disorder. Disorder categories were not mutually exclusive. Omnibus χ2 statistics were pooled statistics based on 10 imputed datasets. Significant pairwise comparisons are listed for racial groups that differed significantly from another racial group after Bonferroni correction. w =non-Hispanic/Latine White group. a = non-Hispanic/Latine Asian group. b = non-Hispanic/Latine Black group. h = Hispanic/Latine group. m = non-Hispanic/Latine multiracial group.

^*p < 0.05

Barriers to Mental Health Treatment

Table 3 shows the means and standard deviations (for continuous items) as well as numbers and proportions (for binary items) of barriers to mental health treatment in the overall sample and across racial and ethnic groups. Table 4 shows the results of ANOVA and Chi-squared tests, respectively. There were significant differences in attitudinal barriers of importance of mental health (F = 10.80, df = 4 and 467, p = .008, η = .01, help-seeking intentions (F = 16.16, df = 4 and 376, p = .01, η = .01, willingness (F = 16.40, df = 4 and 513, p = .01, η = .01), and readiness to seek help (F = 13.12, df = 4 and 325, p = .01, η = .01). Black students reported fewer attitudinal barriers relative to Asian, White, and Multiracial students as indicated by greater readiness for treatment, help-seeking intentions, and help-seeking willingness. In addition, Black students placed significantly higher importance on improving their mental health relative to Asian, White, and Multiracial students. Conversely, Asian students reported the greatest attitudinal barriers relative to all the other racial and ethnic groups, as indicated by significantly lower importance of mental health, readiness, intentions, and willingness to seek help. Effect sizes were largest between Black-Asian students (Cohen’s d = .30–.45) and Asian-Hispanic/Latine (Cohen’s d = .21–.35), whereas differences across Asian-White (Cohen’s d = .04–.25) and Asian-Multiracial (Cohen’s d = .04–.26) were relatively smaller (online supplement).

Table 3.

Barriers to Mental Health Treatment and Disorder Counts by Race and Ethnicity--Descriptive Statistics

Item	Overall		NHL White		NHL Black		NHL Asian		NHL Multiracial		Hispanic/Latine
	M or N	SD or %	M or N	SD or %	M or N	SD or %	M or N	SD or %	M or N	SD or %	M or N	SD or %
Perceived Need (12 Months) c	4.36	1.51	4.38	1.52	4.58	1.51	4.07	1.51	4.44	1.46	4.44	1.48
Perceived Need (Current) c	4.16	1.48	4.17	1.48	4.45	1.47	3.8	1.48	4.27	1.45	4.21	1.43
Importance of Mental Health c	7.45	2.39	7.36	2.36	8	2.39	7.23	2.45	7.75	2.38	7.32	2.38
HS – Readiness c	5.42	2.93	5.43	2.89	6.02	3.06	4.81	2.93	5.7	2.92	5.25	2.95
HS – Intention c	4.06	1.63	4.12	1.63	4.32	1.64	3.61	1.62	4.09	1.62	4.06	1.61
HS – Willingness c	4.27	1.28	4.27	1.27	4.6	1.22	3.97	1.34	4.28	1.2	4.36	1.25
PIssues on own b	2889	56	1790	0.54	195	52	477	62	206	62	562	54
PSocial support b	1254	24	846	26	50	13	217	28	78	23	214	20
Financial b	2073	40	1235	37	167	45	310	40	137	40	476	46
Not enough time b	2678	51	1723	52	163	44	368	48	189	56	548	53
Not sure where to go b	2331	45	1435	44	173	47	330	43	165	49	497	48
Difficulty finding appt b	800	15	538	16	60	16	94	12	50	15	151	14
No need b	997	19	618	19	63	16	230	29	62	17	160	15
Disorder Count c	3.05	1.66	3.07	1.68	3.09	1.62	2.78	1.56	2.99	1.67	3.18	1.25

Note. NHL = non-Hispanic/Latine. HS = Help-seeking.

^C= continuous item.

^B= binary item.

Means and standard deviations are reported for all continuous variables, whereas frequency and percentages are reported for all categorical variables. Effect sizes are given by η2 for all continuous variables and Cramer’s V for all categorical variables. All participants in the sample were selected for having at least one disorder. Disorder categories were not mutually exclusive. Range for each continuous item is as follows: perceived need—12 months (1–6); perceived need—current (1–6); Importance of mental health (0–10); HS - readiness (0–10); HS – intention (1–6); HS – willingness (1–6); disorder count (1–8).

Table 4.

Barriers to Mental Health Treatment and Disorder Counts by Race and Ethnicity--ANOVA and Chi-Squared Test Results

Item	Test	Degrees Freedom	Omnibus Test Statistic	Effect Size	Significant Pairwise Comparisons
Perceived Need (Past 12 Months)	F	4, 454	15.62*	0.01	a < w, m, h, b
Perceived Need (Current)	F	4, 1011	15.62*	0.01	a < w, h, m, b; w < b
Importance of Mental Health	F	4, 467	10.80*	0.01	h < w; a, m, w < b; a < h
HS - Readiness	F	4, 325	13.12*	0.01	w, a, m < b; a < h, w
HS - Intention	F	4, 376	16.16*	0.01	a < h, m, w, b
HS - Willingness	F	4, 513	16.40*	0.01	a, w, m, h < b; a < w, m, h
PIssues on own	χ2	4	4.04*	0.06	a < w
PSocial support	χ2	4	9.09*	0.09	b, h < w; b < a, m, w; h < a
Financial	χ2	4	5.15*	0.06	w < h
Not enough time	χ2	4	4.12*	0.06	b < w, m
Not sure where to go	χ2	4	1.7	0.04	N/A
Difficulty finding appt	χ2	4	2.37	0.04	N/A
No need	χ2	4	14.00*	0.11	a < h, b, m, w
Disorder Count	F	4, 454	9.13*	0.01	a < w, b, h

Note. Omnibus ANOVA test, η2 Omnibus χ2 and Omnibus Cramer’s V were pooled statistics based on 10 imputed datasets. Significant pairwise comparisons are listed for racial/ethnic groups that differed significantly from another racial/ethnic group after Bonferroni correction. w =non-Hispanic/Latine White group. a = non-Hispanic/Latine Asian group. b = non-Hispanic/Latine Black group. h = Hispanic/Latine group. m = non-Hispanic/Latine multiracial group.

^*p < 0.05

In addition, there were significant differences in personal preferences. Specifically, Asian students had a significantly higher preference to deal with issues on their own compared to Black, Hispanic/Latine, and White groups. Asian students also had the highest preference to deal with issues with support from family or friends, whereas Black and Hispanic/Latine students were lowest on this preference. Moreover, amongst Asian students, not endorsing a need for services was the most prevalent barrier (relative to all other groups). Effect sizes for pairwise comparisons were largest for Asian-Hispanic/Latine (Cramer’s V = .09–.19) and Black-Asian (Cramer’s V = .06–.18), whereas the others were relatively smaller.

There were significant racial and ethnic differences in structural barriers of financial barriers (χ2 = 5.15, df = 4, p = .0005, Cramer’s V = .06) and not enough time (χ2 = 4.12, df = 4, p = .003, Cramer’s V = .06). Black and Hispanic/Latine students showed the highest financial barriers to receiving mental health treatment. Multiracial students showed highest proportion of not having enough time for mental health treatment. Effect sizes were small (Cramer’s V = .05–.14). There were no differences in not sure where to go or difficulties finding an available appointment.

Need for Services

There were significant differences across groups in current (F = 15.62, df = 4 and 454, p = 0.000, η = .01) and past 12-month need (F = 9.13, df = 4 and 454, p = 0.000, η = .01), such that Black students reported highest current and 12-month perceived need for mental health treatment, whereas Asian students were lowest in current and 12-month perceived need (relative to all other groups). Effect sizes were largest for all Asian pairwise comparisons (Cohen’s d current = .20–.41; 12 month = .16–.32), whereas the other pairwise comparisons were relatively smaller (Cohen’s d = .02–.17).

Discussion

The present study examined disparities in attitudinal and structural barriers to mental health treatment in US college students. Findings suggested that barriers differentially impacted students from different racial and ethnic backgrounds, such that financial barriers were highest for Black and Hispanic/Latine students, whereas the most prevalent barriers for Asian students were attitudinal factors (e.g., help-seeking attitudes/intentions; preferring to deal with issues on own). For multiracial students, not having enough time was most prevalent. In addition, Black students reported high intentions, willingness, and readiness to seek help, and perceived a high need for treatment. By contrast, Asian students endorsed the lowest values of any racial and ethnic group on these variables, despite similar rates of disorder prevalence. Together, these findings illustrate the unique and common factors that impact mental health treatment disparities in US college students.

The present paper offers the first large-scale, multicampus study of barriers to treatment in students of color. By identifying distinct patterns of barriers across different racial and ethnic groups, the current study offers several novel insights that add further nuance to prior literature and can inform future research and intervention efforts. First, Black students were highly motivated for treatment, as indicated by a high perceived need, willingness to seek help, intentions to seek help, and readiness to seek treatment. However, they endorsed significant financial barriers. These findings add to prior literature that has identified stigma as an attitudinal barrier¹⁶ by suggesting that Black students also face significant structural barriers to treatment. Moreover, by assessing help-seeking attitudes and intentions, the present findings add further nuance to previous findings by demonstrating that Black students see mental health as important, are ready and willing to seek help, and perceive a need for treatment, suggesting they would be likely to engage in treatment-seeking if barriers such as financing and time constraints were addressed. In addition, Black students had the lowest preference for dealing with issues on their own or with help from family/friends, consistent with recent work on help-seeking in Black students.¹⁸

Second, Hispanic/Latine students endorsed moderate to high perceived need for treatment, but significantly lower importance of mental health compared to Black and White students. In addition, they endorsed significantly more financial barriers compared to their White peers. Together, these findings may suggest that, in addition to structural barriers, Hispanic/Latine students encounter attitudinal barriers with respect to mental health help-seeking. For example, although one may perceive a strong need for treatment, perceived unimportance of mental health to one’s overall well-being may interfere with seeking treatment. Prior work suggests that Hispanic/Latine families of adolescents were less likely to seek treatment despite perceiving a need for treatment;^19,20 the present study may offer one possible explanation as to why. Alternatively, need for treatment may be superseded by financial barriers.

Third, Asian students had the lowest help-seeking intentions, willingness to seek help, importance of mental health, and perceived need, which was significantly lower than all other groups. Though they had slightly lower overall disorder counts compared to other groups, it is notable that they were significantly higher on depression and insomnia, and had comparable rates of PTSD, social anxiety, and eating disorders compared to other groups. This suggests that differences in prevalence rates alone cannot account for these findings. These findings are aligned with prior literature that suggests that Asian Americans underutilize mental health services relative to White peers and relative to disorder rates. ^10,11 The present findings diverge from the literature in that some studies showed that Asian Americans had similar perceived need compared to White individuals. ¹¹ One prior study of Asian and Hispanic/Latine college students found that regardless of ethnicity, students who endorsed more cultural values of interdependence and obligation were less likely to perceive a need for mental health treatment. ¹² Perhaps the discrepancy in findings could be accounted for by differences in our sample with respect to cultural values—an important future direction to be followed up on in future work.

Finally, our study is one of the few that examined barriers in multiracial students. Besides common challenges faced by students of color, our findings highlight time constraints as the predominant obstacle in this group. National Center for Education and Statistics data²¹ reveals that full-time multiracial college students are more likely to work during college compared to Black and Asian (but not White) students. This correlates with lower reported financial hardships. Future research should delve into work-related factors by including survey questions about hours worked, aiding in understanding time-related barriers to treatment seeking in this population.

Implications for Research, Intervention, and Policy

Findings of the present study may suggest several avenues for future research, intervention, and policy. Specifically, it underscores the pressing need for the low-cost brief treatment models that can be employed or accessed independently. The provision of self-guided digital health interventions could be a helpful solution to address cost, time, and a preference to deal with issues on one’s own. Self-guided digital mental health interventions, such as mobile applications and chatbots, have been shown to be effective for college students with a variety of mental health conditions and could be a promising way to close the treatment gap.²² In addition to self-guided interventions, leveraging brief treatment models may be an efficient way to address these concerns. For example, single-session interventions have been shown to be effective for depression and anxiety in youth.²³ Thus, developing and evaluating single-session interventions and their efficacy for college students could be valuable to maximize college counselors limited time and help with staffing concerns. Finally, given uncertainty on where to seek treatment, providing students with resources on accessing care, such as through increased outreach efforts, could make treatment more accessible.

To address disparities in treatment barriers, a multipronged and personalized approach may be optimal. Given the role of both attitudinal and structural barriers, interventions that target both individual-level and system-level factors are warranted. Moreover, findings of the present study suggest that a personalized approach may be fruitful to provide pathways to mental health treatment access. For example, for Asian Americans, interventions targeted toward addressing attitudinal barriers toward treatment-seeking (e.g., help-seeking attitudes and intentions) could be helpful. However, further research is needed to assess why Asian Americans endorse these barriers more. Lacking access to culturally informed care that is sensitive to specific needs of Asian American individuals could drive willingness to seek help. Further research investigating perceived cultural appropriateness of available mental health services is needed.

From a policy standpoint, study findings suggest that the principle of equity rather than equality could be fitting to address some of the structural barriers to mental health treatment in college students of color. For instance, counseling centers often provide a fixed number of free sessions, irrespective of financial need. The findings suggest that Black and Hispanic/Latine students, more likely to face financial difficulties, could benefit from increased free sessions or fee reductions. Additionally, addressing awareness gaps about available free resources on campus through further research is crucial. Innovative solutions, such as utilizing brief therapy models via digital mental health and psychoeducation on treatment duration, may overcome time constraints, along with scheduling dedicated mental health time blocks for college students.

Limitations and Future Directions

Several limitations warrant mention. First, other barriers, such as stigma and perceived cultural appropriateness of services, were not assessed in the current study, and would be important to include in future work.²⁴ Moreover, since racial and ethnic groups are heterogenous, additional work that further differentiates across various Hispanic/Latine ethnic groups and Asian groups (e.g., East Asians vs. South Asians), for example, would be helpful to provide further specificity. Furthermore, since data collection took place from 2019–2021, it is possible that COVID-19 impacted our findings. However, results of supplemental analyses suggested no interactions between time and race/ethnicity on treatment barriers.

Conclusion

The present study provided a comprehensive examination of the prevalence and nature of barriers to treatment in college students. Findings offer novel insights into the crisis of unmet mental health treatment need in college students of color and provide several implications for policy and intervention. The present study has the potential to catalyze ongoing efforts to address public health programs geared toward ameliorating mental health treatment disparities and provide ample material for future investigations of social determinants of health.

Highlights:

• This study examined racial and ethnic disparities in mental health treatment barriers among in N = 5841 US college students.

• Black and Hispanic/Latine students demonstrated a higher willingness to seek treatment but faced financial barriers; Hispanic/Latine students exhibited a lower perceived importance of mental health; Asian American students preferred handling issues independently and had lower willingness to seek help, along with financial barriers.

• Study findings reveal disparities in mental health treatment barriers, emphasizing the urgent need for tailored interventions and low-cost brief treatment models accessible independently.