Neurodiversity,Minority Status,and Mental Health: A Quantitative Study on the Experiences of Culturally Diverse University Students in Canada

Abstract

Background:

There is community knowledge shared among autistic and other neurodivergent (ND) communities that ND individuals are more likely to share other non-normative identities, along with research demonstrating that ND individuals have worse mental health outcomes than neurotypicals (NTs). The purpose of this study is to assess how co-occurrence of neurodivergence with other minority statuses impacts distress and discrimination among students in a large university student sample (N = 2206) in Canada and to examine representation of ND students across different identities and minority groups.

Methods:

Participants were recruited to an online survey and coded based on reported gender, sexuality, racial and linguistic groups, citizenship status, relationship preferences, religiosity, socioeducational profile, and neurodivergencies. Psychological distress was assessed using the Depression, Anxiety, and Stress Scale (DASS-21), and experience of discrimination was assessed using the Everyday Discrimination Scale (EDS). Analyses of variance were conducted to examine the differences in DASS-21 and EDS scores between ND and non-ND groups across different groups.

Results:

ND participants were more likely to share Two-Spirit, lesbian, gay, bisexual, transgender, queer, questioning, and other nonheterosexual and gender-expansive identities and to engage in nonconventional relationship dynamics, academic trajectories, and spiritual paths. White participants were proportionally more represented among NDs than non-White participants, which might reflect cultural and systemic factors. ND participants had higher scores in all subscales of the DASS-21 but not the EDS. Main and interaction effects in DASS-21 scores were observed between neurodivergence and gender, racial group, and income, and main effects were observed in nonheterosexual participants. Main and interaction effects were found between neurodivergence and racial and linguistic minority statuses in discrimination scores.

Conclusion:

Results of this study reflect the community-based understanding that ND individuals are more likely to share other non-normative identities and enlighten the impact of race, gender, and linguistic status on the mental health of ND university students. Our findings endorse a culturally sensitive approach for supporting neurominoritized students.

Community Brief

Why is this an important issue?

Neurodivergent communities, such as the autistic community, have long observed that neurodivergent individuals are more likely to hold “unconventional” identities than neurotypicals. These identities include forms of sexual and gender expression outside of the norms, relationship styles different than monogamous relationships, and other life trajectories outside of the “mainstream.” Among many other topics that autistic and neurodivergent individuals have brought up for public discussion, several people also noted that there is a mental health crisis in their communities, due to increased barriers to academic and health care support, pressure to “mask” neurodivergent traits, and neuroableism. Unfortunately, most scientific publications about neurodivergent individuals have not tried to understand the impact of co-occurring marginalized identities on the psychological distress experienced by young neurodivergent people or how many of them identify with “nonconventional” identities.

What was the purpose of this study?

Our study examined how neurodivergent university students from different cultural backgrounds identify in terms of race, language, gender, spiritual path, relationship preferences, and other identities. We also examined whether neurodivergent students who share other marginalized identities were experiencing more distress and discrimination than neurotypicals.

What did the researchers do?

We analyzed the representation of neurodivergent university students across different demographic and cultural groups, with a focus on racial, linguistic, sexual, and gender minorities, and other groups. We also compared the levels of distress and discrimination experienced by neurominoritized students in different groups.

What were the results of the study?

In our sample, neurodivergent participants were proportionally more represented among White students, sexual and gender minorities, and those engaging in nonconventional relationship dynamics, academic trajectories, and spiritual paths. Neurodivergent students were more distressed in all groups, especially if they were People of Color or had lower income. Neurodivergent students who were also linguistic or racial minorities were also more discriminated.

What do these findings add to what was already known?

Our research helps scientists get one step closer to representing in the literature some of the many important insights that neurodivergent communities have been sharing for decades, especially the identification with “unconventional groups,” and the notion that the more marginalized identities a neurodivergent person has, the more likely they are to be experiencing emotional distress.

What are potential weaknesses in the study?

Some of our questions could be better tailored to the experiences of distress and discrimination that are unique to neurodivergent students. We were also not able to analyze data from groups that were underrepresented in our sample, for instance, Black neurodivergent immigrants or Autistic Indigenous people. We also did not examine the differences between people who have a formal diagnosis (e.g., of autism and ADHD) and those who self-identified.

How will these findings help autistic adults now or in the future?

Our study brings more representation to autistic and other neurodivergent individuals to scientific literature in a depathologized way and highlights some of the important long-held insights that neurodivergent people shared in the community and were indeed reported by our participants. Hopefully, our study will also inform institutional policies to support neurodivergent students in higher education and in clinical settings, including mental health support that uses neuroaffirming and culturally sensitive approaches to treatment.

Background

The neurodiversity movement originated from activist work by autistic self-advocates in the 1990s, evolving to embrace the experiences of people diagnosed with other “neurologically different” conditions, who adopt neurodivergent (ND) identities. Such diagnoses include attention-deficit/hyperactivity disorder (ADHD), learning disabilities, and Tourette's syndrome.^1–3 Other conditions are increasingly described by activists and self-advocates as forms of neurodivergence. Examples include epilepsy, schizophrenia,¹ obsessive-compulsive disorder (OCD),⁴ acquired neurological disabilities (e.g., traumatic brain injury) and conditions not scientifically recognized as “disorders,” such as synesthesia or misophonia.

The neurodiversity movement proposes that these conditions, “disorders,” and identities are natural variations within human diversity, which do not require cure, and should be understood using the social model of disability.⁵ Thus, disabilities in neurominoritized individuals lie in the socially constructed notion of “misfit” between a person’s neurological characteristics and a social environment that excludes and denigrates non-normative bodies and brains, rather than being determined by intrinsic defects or flaws of ND individuals.⁶

Neurodivergence, mental health, minority stress, and diagnostic biases

Both community knowledge and scientific research indicate that ND people are more likely to receive diagnoses of depression, anxiety, and phobias,^7–9 and to die of suicide.¹⁰ The severity of psychological distress in these populations has been linked to co-occurrence (and misdiagnoses) of conditions such as bipolar disorders^11,12 and personality disorders.¹³

Research suggests that suicidality rates among ND individuals are higher among racial minorities, sexual minorities, and those with female gender identity, lower levels of education, and lower socioeconomic status.^14–17 These correlations suggest that the combination of neurodivergence and other marginalized identities is likely to significantly increase minority stress (the chronic exposure to socially driven stressors such as harassment, discrimination, and prejudice).¹⁵ In other words, social environments that are stressful and hostile toward specific identities or characteristics can lead to accumulated discrimination, prejudice, expectations of rejections, and, consequently, poorer mental health outcomes for those perceived as “neurologically different” while holding other marginalized identities. Although these effects vary across neurotypes, identities, and most certainly across social contexts, the shared effect of being perceived as cognitively “different” is likely to produce some shared outcomes across ND groups that are worth exploring.

Meyer¹⁸ argues that community affiliation can buffer minority stress among sexual minorities, reducing the impact of minority stress in these populations. A similar effect might occur in ND communities. For instance, connection to autistic communities was shown to mitigate autistic burnout.¹⁹ However, in less supportive environments, public disclosure (“outness”) about ND status correlates positively with poorer mental health.²⁰ This finding might be explained by the increased likelihood of being stereotyped, perceived as “different” and, as a consequence, being harassed, othered,²⁰ bullied, and pressured to educate others about autism.²¹

Furthermore, hiding autistic traits, known as masking or camouflaging, also correlates with poorer mental health outcomes.²² In particular, autistic women are more likely to camouflage autistic traits, which, combined with diagnostic biases, contribute to higher rates of late diagnosis,²³ as well as increased diagnostic rates of borderline personality disorder and anorexia nervosa, both risk factors for suicide,^24,25 in the absence of a correct identification of autism.

Racial stereotypes on the emotional expression of racially minoritized children, as well as White-based biases embedded in “gold standard” diagnostic tools of autism and ADHD, also negatively impact the identification of neurodivergencies by health professionals. Black children in the United States are less likely to receive an accurate diagnosis of autism or ADHD on a first visit to a health provider than their White counterparts.²⁶ Black and Hispanic children are also more likely to be diagnosed with oppositional defiant disorder and conduct disorders, labels that are more stigmatized and less likely to be institutionally supported than ADHD and other neurodivergencies.²⁷ From a community standpoint, Black autistic adults also report being othered, silenced, and discriminated in White-dominated autistic communities,²⁸ which might produce even higher levels of distress due to increased isolation and experienced discrimination both in neurotypical and in neurodivergent spaces. Black autistic people, who are already at a higher risk of police violence due to systemic racism, are even more likely to be misinterpreted by police when behaving in a distressed or “autistic way,” further increasing the risk of violent outcomes driven by both racism and neuroableism.^29,30(p136)

Although observed independently from feminist scholarship, these accumulated stressors and overlapping experiences of oppression resonate with some key ideas in the intersectional framework, established by the activist and scholar Kimberlé Crenshaw. In her work, Crenshaw examines how different forms of subjugation and domination intersect and interact within those who belong to multiple marginalized groups,³¹(p386) highlighting the importance of considering multiple grounds of identity to understand how social realities are constructed.³² Regarding disability, Patricia Hill Collins³³ builds on Crenshaw’s theory and argues that experiences of disability are inherently shaped by race, class, and gender, and thus, ability can be understood as one of several intersecting socially constructed meanings attached to all bodies. She argues that cultural notions of “fit” and “unfit” are determined by an essentially eugenic Western medical discourse that pathologizes differences and dictates notions of normal and deviant³³(p259) and is based on Western-centered assumptions about whiteness, masculinity, and sexuality.³⁰(p50)

While our research questions are inspired by this framework, the present study will not conduct a formal intersectional analysis, but rather quantitatively examines the impact of some of the overlapping marginalized identities on ND university students’ mental health and well-being, as well as whether controlling for variables such as gender, income, sexuality, racial minority status, and citizenship status is influencing the rates of self-identification with neurodivergencies.

Community wisdom: Non-normative and unconventional profiles

Members of autistic and other ND communities have long argued that there is a high representation of ND individuals in several “unconventional” and non-normative groups. In the sexual, gender, and relational spheres, ND individuals are believed to be more likely to share 2SLGBTQ+ (Two-Spirit, lesbian, gay, bisexual, transgender, queer, questioning, and other nonheterosexual and gender-expansive) identities.^17,34–36 Autistic people seem to also be more likely to report satisfaction in singlehood,³⁵ more likely to identify (and less likely to be acknowledged) as asexual³⁷ or demisexual,³⁸ and more likely to adhere to non-normative relationship styles such as polyamory.³⁹

In the professional sphere, ND individuals, particularly women, are more likely to report struggling to find a conventional or stable career path.⁴⁰ In religious and spiritual domains, autistic individuals are reportedly more likely to identify as atheists or agnostic and, when religious, to follow their own unique belief systems.⁴¹ One of the goals of the present work was to take a “confirmatory” quantitative approach to the hypotheses on these “unconventional profiles” that were already identified and explored by autistic and other ND communities, to inform future policy and research tailored for them. Here, we refrain from speculating on the mechanisms behind the association between neurodivergence and unconventional profiles to avoid oversimplification, as we believe these connections deserve an in-depth, depathologizing, and neuroaffirming examination.

Methods

Participants

The dataset used in this study is a subset of the data collected between February and March 2022 for a large student survey conducted at Concordia University (Montreal) by members of the Culture, Health and Personality Laboratory. The study was approved by Concordia University’s Human Research Ethics Committee. The goal of the main study was to assess the well-being of the student body as a whole to improve student services at the university. With institutional incentive to recruit as many students as possible to examine ethnocultural minorities and 2SLGBTQ+ students, who are not always represented in this kind of research, approximately 5,000 students were invited to participate.

Students were recruited through their institutional email addresses in two waves. The email contained a call for participation in a 20-to-25minute online survey aiming to learn more about students’ mental health needs and a link to the survey. Students were offered to enter a draw to win gift cards for their participation.

Eligible participants (N = 2,206) were enrolled in undergraduate (80.8%), graduate (18.5%), and diploma (0.7%) programs and were aged between 18 and 75 years (M_age = 24.1, SD = 5.7). Among all participants, 67.0% were Canadian citizens, 5.4% were permanent residents (PR) of Canada, and 27.3% were international students (proportionally more than the 12% enrolled at the university⁴²). Two groups were particularly underrepresented: 0.1% of participants identified as Indigenous, members of a First Nation community, Métis, or Inuit (proportionally less than the 2% enrolled in the university⁴²) and 0.1% identified as refugees.

Survey structure

The survey was implemented on Checkbox⁴³ and comprised four thematic modules, one of which was analyzed in the present study. This module consisted of questions to which all participants responded and included demographics, questions related to disability status, relationships, sexual and gender identities, spirituality and academic path, and validated questionnaires on psychological distress and everyday discrimination. Students who identified with at least one of the other specific underrepresented groups that the research team was interested in examining were requested to complete one additional thematic module corresponding to their respective group. These specific thematic modules were not included in the present study. Only participants who completed our module of interest were included in our analysis. As an additional measure to prevent bots, at the end of the survey, participants were asked to type their year of birth. Responses with incorrect or missing entries were individually verified using a unique identifier created by participants based on personal information.

Measures

Demographics

Participants were invited to report their age, gender, degree type, citizenship status, whether they have immigrated to Canada, relationship status, sexual orientation, yearly household income, number of children, religion, first language, ethnocultural identity, whether they identified as first-generation students and/or as students with a nonconventional academic path, and disability status. In the sample, 25.7% of participants immigrated to Canada at some point, and 37.5% of participants belong to linguistic minorities (defined in the Quebec context as “allophones” or non-native speakers of either French or English). Participants were coded into different racial categories based on a combination of their reported ethnocultural identities and visible minority status, resulting in a representation of 51.2% White students and 48.8% non-White students (10% more than the student body’s representation⁴²). Finally, 3.8% of participants were parents, 29.7% identified as first-generation students, 22.1% reported nonconventional academic paths (e.g., mature entry, breaks or leaves, second degree, change of program), 35.8% reported a yearly household income lower than 25,000 CAD, and 28.6% reported a yearly income higher than 50,000 CAD.

Items related to gender, relationship status, religion, ethnocultural identity, nonconventional academic path, and disability status included follow-up open-ended questions (e.g., Other. Please specify), allowing participants to specify particular identities in their own words if none of the options available applied to them.

Sexual, gender, and racial identities

For the purposes of this study, all participants who reported any gender identity other than cisgender woman or cisgender man were considered gender minorities. Among participants, 54.3% identified as cisgender women, 36.7% as cisgender men, and 8.9% as gender minorities (trans men and women, Two-Spirit, non-binary, agender, and others), 2% more than the student body’s representation of members of gender minorities.⁴² Likewise, participants who reported any sexual orientation other than straight (heterosexual) were coded as sexual minorities. In our sample, 31.3% of participants identified as non-heterosexual (8% more than the student body’s representation⁴²).

For this study, students identified as Black, Indigenous, or People of Color were grouped into a BIPOC category, with a White counterpart. Participants who did not explicitly identify as White or as belonging to any of the BIPOC categories and who provided ambiguous responses (e.g., European, Canadian) were not assigned to either category. Due to the ambiguity of racial identity in the Canadian context, participants who identified as Portuguese, Italian, Semitic, Armenian, Greek, or Mediterranean without explicitly identifying as White were not assigned to either category. Participants who identified as White (strictly) or reported only Irish, German, or Eastern European identities were classified as White. The final sample sizes are n_BIPOC = 1,008; n_White = 1,077. In total, 121 participants were not assigned to either racial category. We opted to use this categorization to examine the contrasting impacts of White privilege versus being racially minoritized on well-being, mental health, and self-identification as ND, which are central to our research questions. Nonetheless, we recognize the limitations of categorizing participants into only two categories, which fails to capture the innumerable complex historical and sociocultural factors impacting racially minoritized students within and between different ethnoracial groups.

Depression, Anxiety, and Stress Scale

The survey included a short version (21 items) of the Depression, Anxiety, and Stress Scale (DASS-21).⁴⁴ Participants were offered four response options to rate the frequency at which they experience certain events, from “Did not apply to me at all” (0 point) to “Applied to me very much or most of the time” (3 points). The scale items are distributed across three dimensions as follows: depression (e.g., I couldn’t seem to experience any positive feeling at all); anxiety (e.g., I was worried about situations in which I might panic and make a fool of myself); and stress (e.g., I found myself getting agitated). The final scores for the DASS-21 and each of the subscales were calculated, as per standard procedure, by doubling the sum of the individual item scores. Cronbach’s alpha for DASS-21 in this study was 0.937, with a confidence interval of 95% CI: [0.933, 0.941].

Everyday Discrimination Scale

The Everyday Discrimination Scale (EDS)⁴⁵ was included in the survey. Given the main study’s focus on multicultural experiences, the original heading of the questionnaire was adapted to include the cultural component of discrimination (“In your day-to-day life, how often do any of the following things happen to you because of your race, ethnicity, or culture?”). Participants could rate the frequency of discrimination experiences ranging from “Never” (0 point) to “Almost everyday” (5 points). The questionnaire consists of nine items (e.g., You are treated with less courtesy than other people are; people act as if they’re better than you are). Scores were averaged for each participant. In this study, Cronbach’s alpha for the EDS was 0.912, 95% CI: [0.907, 0.918].

Coding of variables: Self-reports

Additional variables were coded manually, based on participants’ answers to three questions: (1) Disability: Do you identify as having one or more disabilities? Participants who answered “Yes” were asked, “If you are comfortable disclosing your specific disability or disabilities, please do so below”; (2) Religion: Do you follow a religious/spiritual practice? Participants were offered the options “Yes (please specify which):” and “No”; and (3) Relationship: Which relationship status best describes you now? Participants were offered several options, including “other (please specify).”

Neurodivergence

A binary variable was created to represent the presence of at least one form of neurodivergence. Participants who answered the disability question by listing neurodivergencies (regardless of diagnostic status) were included under the ND category. The remaining participants were included under the NT category. The following responses were included under the ND category: autism (including variations: autistic, ASD, autism spectrum disorder, Asperger’s, Asperger’s syndrome), ADHD, ADD, dyslexia, dysgraphia, dyscalculia, dysphasia, dysorthographia, learning disabilities, HSP (highly sensitive person), FND (functional neurological disorder), Tourette's syndrome, brain injury,¹ and OCD.² Six participants whose responses included feelings of having significantly different communication styles than others, having a “different brain,” or experiences notably congruent with “traditional” ND presentations, such as tics, were also coded as ND. The authors acknowledge that this section of the coding required a degree of subjective interpretation of symptoms and experiences of disability but chose to adopt the approach of focusing on the reported experience of being “neurologically different” regardless of diagnostic status. In the present dataset, there were no occurrences of some conditions that are disputed as ND, such as epilepsy, sensory processing disorder, misophonia, and synesthesia. The total number of participants coded as ND is N_ND = 208, which constitutes 9.4% of the total sample.

Nonconventional relationship styles

Another binary variable was created to identify participants in nonconventional forms of relationships. Participants who reported being in open or polyamorous relationships were coded under this category, as well as participants who qualitatively reported other nonconventional relationship dynamics (e.g., “queerplatonic relationships,” “romantic friends,” “long-distance relationships,” “in a relationship with a poly-partner”) or nonconformism with normative models of relationship (e.g., “not interested in relationships,” “relationship anarchist”). Participants who reported being single (strictly) were not coded. Those who reported being in a monogamous relationship, dating (and variations, e.g., “I see someone very sporadically,” “situationship”), in a domestic partnership, engaged, or married were coded as not in an unconventional relationship. Widowed, separated, and divorced participants were also not coded, due to the impossibility of inferring their respective relationship preferences. The total number of participants coded as engaged in nonconventional relationship styles is n_NCR = 70, representing 3.2% of the sample.

Nonreligiosity and nonconventional religious/spiritual path

Two binary variables were created to differentiate participants who did not identify with normative and/or traditional religious groups and coded based on answers to the religion question. Participants who did not report any religion, or who explicitly identified as either atheist or agnostic, or qualitatively reported secularism (e.g., secular Jewish) were coded as nonreligious (n_NR = 1,367, representing 62.0% of the sample). The second category (nonconventional religious or spiritual path) was attributed to all participants who were questioning, those who selected “personal sense of spirituality” or “Pagan/Neopagan/Wiccan,” and those who qualitatively reported Neopagan religiosity (e.g., “Ásatrúar,” “Hellenism”); personal interpretations of religious traditions (e.g., “I don’t follow a religion”; “I believe in past lives/spirituality,” “I respect all of them,” “Sufi” [White Canadian]; “Buddhism” [White Canadian]); meditation practices; and other non-normative groups (e.g., “Pantheism,” “Gnosticism,” “Unitarian Universalism,” “Satanism”). The final sample was n_NCRS = 133, representing 6.0% of the sample.

Other variables

Students who answered “yes” to a question about being an older student or following a nontraditional pathway were coded as having a nonconventional academic path. Household income was categorized into three bands for analysis of variance (ANOVA) (C = less than $24,999; B = $25,000 through $49,999; A = $50,000 or more) and into two for contingency tables (poorer = below $25,000; richer = $25,000 or higher), based on the official Canadian poverty line.

Migrants were identified as those who reported migrating to (as opposed to being born in) Canada, excluding international students who were automatically coded based on their immigration status.

Data analysis

Raw data were exported from Checkbox and then cleaned, merged, and coded (as described above) using Microsoft Excel. All data were analyzed using JASP.⁴⁶ The demographic profiles reported in the sections above were calculated using the Descriptive Statistics option.

The correlations between reported neurodivergence and each of the DASS-21 subscores and the total EDS score were calculated. Contingency tables were generated to visualize the frequency distribution of all the different binary variables between the NT and the ND groups. For each table, the chi-square and respective p-values were calculated.

Finally, 3 × 2 and 2 × 2 ANOVAs were conducted to examine the differences in DASS-21 scores across ND and non-ND groups for sexual, gender, racial, and linguistic minorities, as well as for program type, migration, first-generation status, religiosity, citizenship status, and yearly income. ANOVAs were also run to examine differences in EDS for racial minorities, linguistic minorities, migrants, and international students.

Results

Zero-order correlations

The correlations (Pearson’s r) between reported neurodivergence and DASS-21 scores are shown in Table 1. There was no statistically significant correlation between EDS scores and reported presence of neurodivergence [r(2202) ∼ 0, p = 0.99].

Table 1.

Pearson’s r for Reported Neurodivergencies and Scores of the Depression, Anxiety, and Stress Scale (DASS-21)

Reported neurodivergence	r (2167)
Depression	0.096***
Anxiety	0.129***
Stress	0.147***
DASS-21 total	0.139***

***

p < 0.001.

DASS-21: Depression, Anxiety, and Stress Scale.

Profile of ND participants

The representation of ND individuals in all analyzed subgroups is shown on Table 2, with respective effect sizes expressed as odds ratios. We were able to get a sufficient number of participants to yield adequate power for all the analyses we conducted. As per G*Power 3,⁴⁷ a sensitivity analysis for our chi-square yields more than adequate power (0.90) to detect an effect size of w = 0.10, which is considered a small effect size by Cohen.⁴⁸

Table 2.

Contingency Table—Student Profiles, Neurotypical Versus Neurodivergent Participants

Program χ² = 13.78*** OR = 0.41, 95% CI [0.25, 0.67] (N = 2190)		No reported neurodivergence(n = 1982)	Neurodivergent(n = 208)
Undergraduate (n = 1781)	Count	1592	189
Undergraduate (n = 1781)	(expected count)	(1612)	(169)
Graduate (n = 409)	Count	390	19
Graduate (n = 409)	(expected count)	(370)	(39)
First Generation χ² = 0.08, p = 0.811 OR = 0.96, 95% CI [0.70, 1.31] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
No (n = 1562)	Count	1413	149
	(expected count)	(1415)	(147)
Yes (n = 644)	Count	585	59
	(expected count)	(583)	(61)
Nonconventional Academic Path χ² = 35.84*** OR = 2.44, 95% CI [1.81, 3.30] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
No (n = 1719)	Count	1591	128
	(expected count)	(1557)	(162)
Yes (n = 487)	Count	407	80
	(expected count)	(441)	(46)
Yearly Household Income (Canadian dollars) χ² = 4.25^* OR = 0.71, 95% CI [0.51, 0.98] (N = 1631)		No reported neurodivergence(n = 1462)	Neurodivergent(n = 169)
Below $25,000 (n = 911)	Count	804	107
	(expected count)	(817)	(94)
$25,000 and higher (n = 720)	Count	658	62
	(expected count)	(645)	(75)
Gender Ratio (cis) χ² = 8.95** OR = 1.06, 95% CI [0.61, 1.85] (N = 2012)		No reported neurodivergence(n = 1857)	Neurodivergent(n = 155)
Men (n = 812)	Count	767	45
	(expected count)	(749)	(63)
Women (n = 1200)	Count	1090	110
	(expected count)	(1108)	(92)
Gender minorities χ² = 79.72*** OR = 1.06, 95% CI [0.61, 1.85] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
No (cis) (n = 2012)	Count	1857	155
	(expected count)	(1822)	(190)
Yes (non-cis) (n = 194)	Count	141	53
	(expected count)	(176)	(18)
Sexual orientation χ² = 127.81*** OR = 4.46, 95% CI [2.58, 7.71] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
Heterosexual (n = 1516)	Count	1445	71
Heterosexual (n = 1516)	(expected count)	(1373)	(143)
Nonheterosexual (n = 690)	Count	553	137
Nonheterosexual (n = 690)	(expected count)	(625)	(65)
Reported nonconventional relationship χ² = 33.51*** OR = 4.46, 95% CI [2.58, 7.71] (N = 1101)		No reported neurodivergence(n = 983)	Neurodivergent(n = 118)
No (n = 1031)	Count	935	96
	(expected count)	(920)	(110)
Yes (n = 70)	Count	48	22
	(expected count)	(62)	(8)
Racial group χ² = 49.85*** OR = 0.32, 95% CI [0.23, 0.45] (N = 2085)		No reported neurodivergence(n = 1892)	Neurodivergent(n = 193)
White (n = 1008)	Count	868	140
White (n = 1008)	(expected count)	(915)	(93)
BIPOC (n = 1077)	Count	1024	53
BIPOC (n = 1077)	(expected count)	(977)	(100)
Migration to Canada χ² = 6.79** OR = 0.55, 95% CI [0.35, 0.87] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
Born in Canada (n = 1830)	Count	1644	186
	(expected count)	(1657)	(173)
Migrated to Canada (n = 376)	Count	354	22
	(expected count)	(341)	(35)
Immigration status χ² = 20.54*** OR = 0.40, 95% CI [0.27, 0.60] (N = 2199)		No reported neurodivergence(n = 1992)	Neurodivergent(n = 207)
Canadian citizen/PR (n = 1597)	Count	1419	178
	(expected count)	(1447)	(150)
International student (n = 602)	Count	573	29
	(expected count)	(545)	(57)
Linguistic minorities χ² = 34.71*** OR = 0.35, 95% CI [0.25, 0.51] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
Anglo/Francophone (n = 1377)	Count	1208	169
	(expected count)	(1247)	(130)
Allophone (n = 829)	Count	790	39
	(expected count)	(751)	(78)
Religious χ² = 15.35*** OR = 1.90, 95% CI [1.37, 2.62] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
Yes (n = 839)	Count	786	53
Yes (n = 839)	(expected count)	(760)	(79)
No (no religion, atheist or agnostic) (n = 1367)	Count	1212	155
No (no religion, atheist or agnostic) (n = 1367)	(expected count)	(1238)	(129)
Nonconventional religious or spiritual path χ² = 6.71^* OR = 1.89, 95% CI [1.16, 3.09] (N = 2206)		No reported neurodivergence(n = 1998)	Neurodivergent(n = 208)
No (n = 2073)	Count	1886	187
	(expected count)	(1878)	(195)
Yes (n = 133)	Count	112	21
	(expected count)	(120)	(13)

*p < 0.05; **p < 0.01; ***p < 0.001.

BIPOC, Black, Indigenous, or People of Color; CI, confidence interval; OR, odds ratio.

Overall, ND participants were proportionally more represented among undergraduate students and students who followed unconventional academic paths and were more likely to report a yearly income lower than $25,000. As predicted by community accounts on ND sexuality, gender identity, and relationship styles, ND participants were overrepresented among gender minorities and sexual minorities and reported proportionally higher adherence to nonconventional models of relationship. BIPOC participants, migrants, international students, and linguistic minorities were less likely to report neurodivergence. Finally, ND participants were overrepresented among nonreligious participants and among participants with unconventional religious or spiritual paths.

Group differences in emotional state and discrimination

There were significant main and/or interaction effects observed between ND and NT groups in the DASS-21 scores for gender, sexual minority identity, yearly income, and racial minority status, as shown in Table 3. There were no interaction effects, or main effects other than neurodivergence, in DASS-21 scores for (a) program type, F(1, 2152) = 17.16, p < 0.001, d = 0.512 for neurodivergence, suggesting a medium effect size, F(1, 2152) = 1.80, p = 0.180 for program type, F(1, 2152) = 0.31, p = 0.579 for interaction; (b) nonconventional relationship status, F(1, 1083) = 18.13, p < 0.001, d = 0.60 for neurodivergence, suggesting a medium effect size, F(1, 1083) = 2.36, p = 0.125 for relationship style, F(1, 1083) = 0.78, p = 0.377 for interaction; (c) nonconventional academic path, [F(1, 2165) = 34.48, p < 0.001, d = 0.45 for neurodivergence, a small-to-medium effect size, F(1, 2165) = 1.36, p = 0.244 for academic path, F(1, 2165) = 0.11, p = 0.738 for interaction; (d) first-generation status, F(1, 2165) = 34.44, p < 0.001, d = 0.47 for neurodivergence, a small-to-medium effect size, F(1, 2165) = 1.01, p = 0.314 for first-generation status, F(1, 2165) = 0.07, p = 0.786 for interaction; (e) migration status, F(1, 2165) = 16.28, p < 0.001, d = 0.47 for neurodivergence, a small-to-medium effect size, F(1, 2165) = 0.35, p = 0.554 for migration status, F(1, 2165) = 0.02, p = 0.898 for interaction; (f) citizenship F(1, 2158) = 20.75, p < 0.001, d = 0.47 for neurodivergence, a small-to-medium effect size, F(1, 2158) = 0.88, p = 0.349 for citizenship status, F(1, 2158) = 0.06, p = 0.813 for interaction; (g) linguistic minority status, F(1, 2165) = 33.44, p < 0.001, d = 0.53 for neurodivergence, a medium effect size, F(1, 2165) = 0.47, p = 0.495 for linguistic minority status, F(1, 2165) = 1.19, p = 0.275 for interaction; and (h) religiosity, F(1, 2165) = 34.73, p < 0.001, d = 0.49 for neurodivergence, a small-to-medium effect size, F(1, 2165) = 0.01, p = 0.923 for religiosity, F(1, 2165) = 0.15, p = 0.696 for interaction. The respective mean scores for each of these categories are also shown in Table 3, below the respective ANOVA results that provided significant effects for categories other than neurodivergencies.,

Table 3.

Depression, Anxiety, and Stress Scale-21 Score Means for Reported Neurodivergence and Demographic Groups

Reported ND	Gender	M (SD)	n
No	Man (cisgender)	38.85 (25.67)	743
	Woman (cisgender)	48.41 (27.10)	1078
	Gender minority	58.33 (26.14)	140
Yes	Man (cisgender)	56.00 (21.47)	45
	Woman (cisgender)	57.80 (25.03)	110
	Gender minority	61.09 (22.80)	53
Reported ND	Sexual orientation	M (SD)	n
No	Heterosexual	42.20 (26.48)	1412
	Nonheterosexual	53.97 (26.87)	549
Yes	Heterosexual	54.85 (25.71)	71
	Nonheterosexual	60.02 (22.48)	137
Reported ND	Income band	M (SD)	n
No	Above $50,000	42.28 (27.44)	433
	$25,000 through $49,999	43.91 (24.23)	213
	Less than $25,000	48.26 (27.63)	789
Yes	Above $50,000	51.84 (21.51)	25
	$25,000 through $49,999	57.84 (19.43)	37
	Less than $25,000	60.88 (25.54)	107
Reported ND	Racial group	M (SD)	n
No	White	45.51 (26.60)	862
	BIPOC	45.50 (27.49)	998
Yes	White	56.69 (23.67)	140
	BIPOC	66.26 (23.77)	53
Reported ND	Program type	M (SD)	n
No	Undergraduate	46.64 (27.22)	1570
	Graduate	40.38 (26.04)	378
Yes	Undergraduate	58.49 (23.20)	189
	Graduate	55.90 (28.79)	19
Reported ND	Relationship style	M (SD)	n
No	Conventional	44.35 (27.01)	922
	Unconventional	46.77 (26.41)	47
Yes	Conventional	56.85 (21.99)	96
	Unconventional	65.82 (21.42)	22
Reported ND	Academic path	M (SD)	n
No	Conventional	44.87 (26.86)	1560
	Unconventional	47.95 (27.91)	401
Yes	Conventional	57.59 (25.14)	128
	Unconventional	59.30 (21.31)	80
Reported ND	First generation	M (SD)	n
No	No	44.69 (26.84)	1391
	Yes	47.46 (27.66)	570
Yes	No	57.80 (23.48)	149
	Yes	59.39 (24.40)	59
Reported ND	Migration status	M (SD)	n
No	Born in Canada	45.10 (26.67)	1613
	Migrated	47.35 (28.98)	348
Yes	Born in Canada	58.10 (24.35)	186
	Migrated	59.55 (17.59)	22
Reported ND	Citizenship status	M (SD)	n
No	Citizen or PR	46.49 (27.05)	1396
	International student	43.25 (27.06)	559
Yes	Citizen or PR	58.42 (22.55)	178
	International student	56.48 (30.30)	29
Reported ND	Linguistic status	M (SD)	n
No	Anglo/Francophone	45.89 (26.77)	1192
	Allophone	44.89 (27.61)	769
Yes	Anglo/Francophone	57.43 (23.53)	169
	Allophone	61.80 (24.40)	39
Reported ND	Religiosity	M (SD)	n
No	Religious	45.01 (27.92)	766
	No religion, atheist, or agnostic	45.75 (26.57)	1195
Yes	Religious	59.06 (23.37)	53
	No religion, atheist, or agnostic	57.97 (23.88)	155

M, mean; PR, permanent resident; SD, standard deviation.

We were once again able to recruit a sufficient number of participants to yield adequate power for all the conducted analyses. As per G*Power 3,⁴⁷ sensitivity analyses for our ANOVAs yield more than adequate power (0.90) to detect an effect size of f = 0.10, considered a small effect size by Cohen.⁴⁸

In the ANOVAs for gender, there was a statistically significant main effect for neurodivergence, F(1, 2163) = 20.92, p < 0.001, and gender, F(2, 2163) = 8.84, p < 0.001, as well as a significant interaction, F(2, 2163) = 3.01, p = 0.047, η²_p = 0.003, a very small effect size. As per the Tukey post hoc test, the gender effect is primarily attributable to the mean score difference between cisgender men and gender minorities (M_diff = 12.29, t = 4.21, p < 0.001, d = 0.47, suggesting a small effect size). There were also significant differences between cis men and cis women (M_diff = 5.68, t = 2.36, p = 0.048, d = 0.22, suggesting a small effect size) and between cisgender women and gender minorities (M_diff = 6.61, t = 2.65, p = 0.022, d = 0.25, suggesting a small effect size). There was a statistically significant neurodivergence effect (M_diff = 9.77, t = 4.57, p < 0.001, d = 0.37, suggesting a small-to-medium effect size).

For sexual minorities, there was a statistically significant main effect for neurodivergence, F(1, 2165) = 21.07, p < 0.001, d = 0.36, suggesting a small-to-medium effect size, and sexual orientation, F(1, 2165) = 17.33, p < 0.001, d = 0.32, suggesting a small-to-medium effect size, but no significant interaction, F(1, 2165) = 2.63, p = 0.105, η²_p = 0.001.

Regarding income, there was a statistically significant main effect for neurodivergence, F(1, 1598) = 21.49, p < 0.001, and income, F(2, 1598) = 3.31, p = 0.037, but no significant interaction, F(2, 1598) = 0.19, p = 0.829, η²_p ∼ 0. As per the Tukey post hoc test, the significance of the income effect is only attributable to the mean score difference between the richest and the poorest band (M_diff = 7.51, t = 2.44, p = 0.039, d = 0.27, a small effect size). The neurodivergence effect corresponds to a mean difference (M_diff = 12.04, t = 4.64, p < 0.001, d = 0.45, suggesting a small-to-medium effect size).

For racial minorities, there was a statistically significant main effect for neurodivergence, F(1, 2049) = 50.35, p < 0.001, d = 0.60, a medium effect size, and racial minority status, F(1, 2049) = 4.51, p = 0.034, d = 0.18, a small effect size, as well as a significant interaction, F(1, 2049) = 4.54, p = 0.033, η²_p = 0.002, suggesting a very small effect size.

Significant effects were also observed comparing the ND and NT groups for the EDS scores for racial minority status and linguistic minority status. The mean scores are shown in Table 4.

Table 4.

Everyday Discrimination Scale (EDS) Score Means for Reported Neurodivergence and Racial Minority Statuses

Reported ND	Racial group	M (SD)	n
No	White	0.534 (0.76)	868
	BIPOC	1.094 (0.91)	1022
Yes	White	0.565 (0.80)	140
	BIPOC	1.562 (1.03)	53
Reported ND	Linguistic group	M (SD)	n
No	Anglo/Francophone	0.716 (0.86)	1207
	Allophone	1.029 (0.91)	789
Yes	Anglo/Francophone	0.704 (0.88)	169
	Allophone	1.419 (1.09)	39
Reported ND	Citizenship status	M (SD)	n
No	Citizen or PR	0.793 (0.884)	1418
	International student	0.955 (0.892)	572
Yes	Citizen or PR	0.791 (0.917)	178
	International student	1.004 (1.018)	29
Reported ND	Migration status	M (SD)	n
No	Born in Canada	0.805 (0.873)	1642
	Migrated	1.000 (0.953)	354
Yes	Born in Canada	0.784 (0.940)	186
	Migrated	1.298 (1.058)	22

In the racial minority analysis, there was a statistically significant main effect for neurodivergence, F(1, 2079) = 12.38, p < 0.001, d = 0.28 (a small effect size), and racial minority status, F(1, 2079) = 120.56, p < 0.001, d = 0.92 (a large effect size), as well as a statistically significant interaction, F(1, 2079) = 9.46, p = 0.002, η²_p = 0.005. For linguistic minorities, there was a statistically significant main effect for neurodivergence, F(1, 2200) = 5.48, p = 0.019, d = 0.22 (a small effect size), and linguistic minority status, F(1, 2200) = 40.36, p < 0.001, d = 0.58 (a medium effect size), as well as a significant interaction, F(1, 2200) = 6.17, p = 0.013, η²_p = 0.003.

There were significant main effects of citizenship status, but not neurodivergence, in discrimination for international students, F(1, 2193) = 4.17; p = 0.041, d = 0.21 for citizenship status, a small effect size, F(1, 2193) = 0.068; p = 0.80 for neurodivergence, and F(1, 2193) = 0.08; p = 0.78 for interaction, and migration status, F(1, 2200) = 11.60; p < 0.001, d = 0.40, for migration status, a small-to-medium effect size, F(1, 2200) = 1.77, p = 0.183 for neurodivergence, and F(1, 2200) = 0.13, p = 0.125 for interaction. The mean EDS scores for these categories are also shown in Table 4, below the results with significant main effects for neurodivergence.

Discussion

This study aimed to examine the mental health status of ND students in a large university sample, regardless of formal diagnoses. While some may argue that students could be self-diagnosing inaccurately, it is known that many ND adults are only formally diagnosed after identifying as ND themselves³ and that ND people are often underdiagnosed or misdiagnosed by mental health professionals due to racial⁴⁹ and gender⁵⁰ stereotypes that bias the implementation and interpretation of diagnostic criteria, limiting the possibility of an accurate diagnosis for minority groups. Furthermore, it is reasonable to assume that students with self-reported neurodivergencies judged that their ND experience was disabling enough—and hence, more distressing—to hinder their well-being and academic performance enough to justify reporting them as a disability. Thus, some students with ND identities but not disabled identities may have refrained from reporting their neurodivergencies as disabilities.

Nonetheless, once the reported presence of neurodivergence has been established as a variable, the correlation with the characteristics that were predicted based on shared anecdotal knowledge in activist and educational ND communities was remarkably consistent. The correlation between the reported neurodivergence and subscores of the DASS-21 (Table 1) was statistically significant but not strong enough to indicate redundancy. This suggests that, as expected, ND participants experience higher levels of distress, but other factors beyond the presence of neurodivergence are playing a role in such experiences. Future studies addressing specific questions on neurodivergence with an intersectional approach might provide a clearer picture of specific sources of distress, discrimination, and oppression experienced by university students with specific positionalities.

Other variables in this study are open to improvements. Future studies on ND populations could benefit from explicitly phrased questions on religiosity (e.g., “Do you consider yourself as someone who has followed a nonconventional religious and/or spiritual path in your particular cultural context?”) and relationship styles (e.g., “Are you, or have you ever been, engaged in relationship dynamics or philosophies that would be considered atypical in your particular cultural context?”). The cultural component of these questions would be essential in studies in diverse populations and cross-cultural studies, since “deviation from the norm” is always a contextual and socioculturally determined phenomenon. Furthermore, cross-cultural research on non-normative romantic and sexual profiles (e.g., ace/aromantic, 2SLGBTQ+, polyamory) could also benefit from including questions addressing ND identities.

Finally, the yearly income variable, although conveying significant mean differences in levels of psychological distress, might present interpretative limitations, since some participants might have interpreted the question as addressing their personal income rather than their household income. Future studies on neurodivergence, particularly those concerned with socioeconomic status, could benefit from questions explicitly addressing this difference.

The profiles of ND participants

As shown in Table 2, there were statistically significant differences in the ratio of reportedly ND participants across several demographic groups. At the socioeducational level, graduate students and students with yearly household income higher than $25,000 were less likely to report neurodivergence, and participants with nonconventional academic paths were, as predicted, more likely to identify as ND. No statistically significant difference was observed among first-generation students. Unsurprisingly, ND students were proportionally more represented among sexual minorities, gender minorities, and those engaged in nonconventional relationship styles. Interestingly, ND students were proportionally more represented among cisgender women than among their cis-male counterparts. Given we merged all neurodivergencies into a single group for the purposes of this study, it is hard to speculate about whether this difference would also be observed if we were to consider autistic participants exclusively.

Racial minorities were found to be overall less likely to report neurodivergence: the representation of NDs was approximately half the expected value across participants who were BIPOC, international students, immigrants, and linguistic minorities. ND participants were, unsurprisingly, more likely to be atheist, agnostic, or to report no religion, and also more likely to have followed an unconventional religious or spiritual path.

Distress, discrimination, and minority status

The DASS-21 was used in this study to assess psychological distress. The mean scores among ND participants were higher across all analyzed subgroups, and neurodivergence had a statistically significant main effect across all ANOVAs, as shown in Table 3. All four minority statuses were also associated with higher DASS-21 scores.

Gender minorities had higher DASS-21 scores than cisgender participants, and cisgender women had higher scores than cisgender men. There was a moderately strong effect for the difference between cisgender men and gender minorities in the prediction of distress. NT cisgender women and gender minorities, as well as ND men and women, presented moderate levels of distress. There was a significant interaction between gender and neurodivergence, suggesting that the overlap of gender minority and neurominority statuses might be particularly distressing, a topicworth exploring in future studies.

Sexual minorities had on average higher DASS-21 scores than heterosexual participants, in both NT and ND groups. The sexual orientation component yielded a moderate Cohen’s d, but no interaction effect was observed, suggesting that, although both ND status and sexual minority identity produce higher levels of distress, the interaction between both might itself not increase the likelihood of negative affect more than each of these statuses would provide independently. Nonetheless, neurominoritized members of sexual minorities reported higher mean scores than all their respective counterparts. This phenomenon was also observed in several other minoritized categories with statistically insignificant main ANOVA effects, as shown in Table 3.

Although, as discussed in the previous section, the household income ranges might not reflect socioeconomic status accurately, it is remarkable that (1) the total DASS-21 score of ND participants with the lowest reported income is comparable with those of ND gender minorities and ND sexual minorities, suggesting that socioeconomic status plays an important role in the levels of distress experienced by participants, and (2) only 25 among all the 169 ND participants reported a household income larger than $50,000, representing 14.8% of the subsample. Conversely, among non-ND participants, 30.2% of participants reported a household income above $50,000. One hypothesis that should be examined in future research is that richer ND participants are less likely to be identified as neurominorities, possibly due to access to more opportunities and resources to develop personal interests and talents than poorer ND individuals, and therefore having more opportunities to minimize sources of distress. A similar argument could be used to help explain why graduate students were less likely to report ND, combined with the possibility that neurodivergence is an obstacle to access to graduate-level education due to its neuronormative structure, and in light of research showing that ND young adults are less likely to graduate from postsecondary programs than their NT peers.⁵¹

Finally, among all analyzed intersections, ND racial minorities reported the highest DASS-21 mean scores across all analyzed groups. Moreover, while in the non-ND group, BIPOC participants outnumbered White participants, among ND participants, BIPOCs represented only 27.5% of the sample. This difference might be caused by racial biases in diagnostic practices, or a shared cultural understanding of neurodivergence historically based on White stereotypes, which might lead both clinicians and BIPOC ND individuals to be less likely to consider neurodivergencies as part of their life experiences.

It is also possible that BIPOC participants who reported neurodivergence were more likely to have experienced more severe levels of distress, leading to a more thorough investigation of diagnoses and identities that would not be considered otherwise due to the racial biases among both mental health professionals and ND communities. Nonetheless, the remarkably high levels of distress in this group suggest that those who are racially minoritized and self-identified as nerrodivergent are at particularly increased risk to experience mental health crises.

BIPOC participants also reported higher levels of experienced discrimination (Table 4), both among NT and ND samples. Both main and interaction effects conveyed statistically significant results and a very strong effect. This is likely to be connected by the compounded effect of racist discrimination experienced by this group and their ND experience, behavior, and expression being subjected to more prejudice, stereotyping, and targeting.

Lastly, linguistic minorities (Table 4) were also found to experience higher levels of discrimination both among NT and ND participants. Both main and interaction effects were statistically significant, and post hoc analysis of the linguistic status contribution indicated a moderately strong effect. Similar to racial minorities, linguistic minorities are disproportionately represented among participants who did not report any form of neurodivergence: while allophones represent 39.5% of participants who did not report any form of neurodivergence, the percentage of allophones among reportedly ND participants is only 18.8%. The same argument on diagnostic stereotypes could be made here, with the caveat that allophones are more likely to be born outside of Canada, which urges for the consideration that culture plays an important role in the perception and conceptualization of neurodivergencies both by patients and by mental health professionals. In addition, ND students born in other countries who desire to study abroad face even more barriers to be able to accomplish this goal than NT students. Moreover, the different cultural conceptualizations on neurodivergence could explain, at least partially, why there were no ND main effects in discrimination scores for migrants to Canada and international students.

Although the present study provided a good opportunity to examine neurodivergence in combination with different minority statuses in a culturally diverse large sample, participants were all university students, which is likely to have biased the results toward higher socioeconomic and educational status, and to reflect ND experiences that do not intersect with intellectual disabilities or other characteristics that are not well received or accommodated in educational environments due to lack of neuro-inclusiveness. Furthermore, besides the limitations previously described, our analyses are looking strictly at intersections of two dichotomous variables at a time. Dubrow⁵² notes that although interaction effects are helpful to identify some unique intersectional experiences, omitting higher order interactions (i.e., interaction effects between more than two variables) does not tell a full intersectional story of the observed phenomena. Furthermore, using pre-established “master demographic categories” does not allow for the discovery of new social categories that might be impacting participants.⁵²

Finally, future quantitative studies focusing on specific underrepresented ND groups could benefit from directly recruiting different groups of ND students based on ND identities, diagnostic status, and other identities, and then examining scores on measures of different kinds of distress (e.g., acculturative distress, xenophobia, sexism, cisheteronormativity).

Conclusions

This study examined the experiences of ND students within a large, culturally diverse sample of university students in Canada, focusing on the impact of some minority statuses on distress and discrimination among neurominoritized students. Our findings highlight a necessity for creating a better environment for multiply-minoritized ND students, which could be accomplished through the incorporation of neuroinclusive strategies such as fairer academic accommodations,³ universal design principles,⁵³ and culturally responsive, neurodiversity-affirming mental health services.

Our results suggest that scientific inquiry on neurodivergence should account for cultural factors typically overlooked in psychological research, such as non-normative expressions of religiosity, sexuality, and relationship styles. In clinical research and practice, a culturally informed perspective on neurodivergence is crucial to understand how ND traits manifest differently across socioeconomic and cultural contexts, particularly among immigrants and other cultural minorities.

Finally, incorporating the neurodiversity framework in psychological research requires addressing the historically perpetuated epistemic injustices in the field of psychopathology (for a detailed discussion, see Catala et al.⁵⁴). Bottom-up approaches, qualitative methods, and neuroinclusive practices are essential for amplifying marginalized voices to ensure that diverse experiences are recognized as legitimate forms of knowledge that should guide scientific inquiry around neurodivergence.

Footnotes

Acknowledgments

The authors would like to thank all the original members of the Student Mental Health team, without whom this project would have not been possible: Dr. Momoka Sunohara, Lisa Stora, Joon Lee, Sofia Mira, and Kristina Céus. They would also like to thank all the students who generously shared their honest assessment on the mental health challenges they experience in higher education.

Authorship Confirmation Statement

R.B.: Conceptualization, investigation, formal analysis, data curation, and writing—original draft preparation. A.G.R.: Supervision, methodology, investigation, funding acquisition, and writing—reviewing and editing. The article has been submitted solely to Autism in Adulthood.

Author Disclosure Statement

The authors have no conflicts of interest to disclose. Data collection from the “student mental health survey” was supported by Bell Canada.

Funding Information

This work was supported by Bell Canada.

1

The total number of participants who listed at least one among Tourette's, traumatic brain injury, FND, and HSP combined is four, one of which explicitly identifying as ND.

2

OCD is one of the conditions often but not universally recognized as a form of neurodivergence in ND communities, and autism is often misdiagnosed as OCD. There were in total six occurrences of OCD in the dataset that were not explicitly listed in combination with other ND identities.

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