Existing quantitative research, which largely relies on health and social surveys and censuses, has several limitations, including: small samples, how and if key constructs such as sexual orientation and gender idenity are measured, response biases, trust. as well as diffculity capturing intersectional identities.

Sample Size for 2SLGBTQ+ Research

For social work researchers and practitioners, a persistent challenge in generating evidence on 2SLGBTQ+ populations is the question of adequate sample size. Historically, studies such as Kinsey’s mid-century reports estimated that up to 10% of adults were gay or lesbian (Kinsey, Pomeroy, & Martin, 1948). Since then, more rigorous survey data shows that these early figures were inflated.

Recent Canadian data highlights generational change. Statistics Canada reports that approximately 4.4% of Canadians agedd 15 and older (about 1.3 million people) identified as part of the 2SLGBTQ+ community between 2019 and 2021. Among younger Canadians, the proportions are much higher: 10.5% of those aged 15-24 reported a sexual or gender minority identity, compared with 4.1% of adults aged 25–64 and only 1.3% of those 65 and older (Statistics Canada, 2023). The 2021 Census also revealed that roughly 0.19% of adults identified as transgender and 0.14% as non-binary, amounting to nearly one in every 300 Canadians (Statistics Canada, 2022).

For social work education, these figures carry significant implications. Even large national surveys often include relatively few 2SLGBTQ+ respondents overall, and when those respondents are further disaggregated by race, Indigeneity, migration status, or disability, subgroup sizes become very small for statistical analysis. This limits statistical power, reduces the reliability of findings, and constrains the development of intersectional analyses that are central to social work’s concern with equity and social justice. Moreover, nonresponse, survey attrition, and the understandable reluctance of some individuals to disclose a stigmatized identity can further erode sample sizes.

Methodological strategies can partially address these challenges. For example, pooling multiple years of cross-sectional surveys, such as the Canadian Community Health Survey, increases the number of 2SLGBTQ+ respondents for analysis. Targeted oversampling, the use of linked administrative data, and advanced statistical techniques (e.g., small-area estimation or Bayesian modeling) are additional tools. Yet from a social work perspective, these strategies should be evaluated not only for technical and statistical adequacy but also for their ability to capture the lived realities of marginalized communities.

Small sample sizes should not deter research. Instead, it is important to recognize the value of mixed-methods, where qualitative enquiry can illuminate the nuances behind limited quantitative findings. For social work educators, this provides an opportunity to teach students how to critically evaluate data, recognize the limitations imposed by small numbers, and integrate statistical analysis with narratives and community-based knowledge. In practice and advocacy, this translates into a more cautious but also more inclusive use of data to inform services, challenge inequalities, and promote anti-homophobic and anti-transphobic policies.

In sum, the relatively modest size of 2SLGBTQ+ populations in national datasets poses statistical and conceptual challenges, but it also offers social work educators a valuable teaching moment and show how methodological creativity and critical interpretation can help overcome barriers to evidence-informed practice with 2SLGBTQ+ communities.

Measuring Sexual Orientation

Sexual orientation is complex and cannot be reduced to a single dimension. It is usually described in terms of identity (how people label themselves), attraction (who they are drawn to emotionally or physically), and behavior (with whom they engage in sexual activity). These dimensions do not always overlap neatly. For example, someone may identify as heterosexual while reporting same-sex attraction or same-sex sexual experiences. Conversely, individuals who identify as lesbian, gay, or bisexual may not currently report same-sex attraction or behavior. This lack of alignment complicates how sexuality is measured and, in turn, how evidence is used to inform social work practice, policy, and education.

In Canada, most large-scale surveys have historically relied on identity-based questions, often with wording that implies sexual behavior. The Canadian Community Health Survey (CCHS), General Social Survey (GSS), Canadian Health Measures Survey (CHMS), and Canadian Longitudinal Study on Aging (CLSA) ask about sexual orientation in ways that focus on identity but often define the categories in terms of behavior (e.g., heterosexual = “sexual relations with people of the opposite sex”). Research suggests that this wording may underidentify individuals who have same-sex attraction or partners but still identify as heterosexual (Dharma & Bauer, 2017).

Other surveys have experimented with different approaches. The Canadian Alcohol and Drug Use Monitoring Survey (CADUMS) asked a straightforward self-identity question without the behavioral qualifier, which may reduce bias. The Public Service Employee Survey (PSES, 2018) also used a self-reported orientation question with options for heterosexual, gay/lesbian, bisexual, or “please specify.” The Survey of Sexual Misconduct in the Canadian Armed Forces (SSMCAF) initially relied on a yes/no format (“Do you identify as gay, lesbian, or bisexual?”), but later revised the question to allow respondents to select heterosexual, homosexual, bisexual, or specify another orientation. While this was an improvement, it still collapsed diverse identities into limited categories and did not capture attraction or behavior.

Despite these efforts, no Canadian national survey consistently includes all three dimensions—identity, attraction, and behavior. This limits the ability of researchers and social workers to fully understand the scope of 2SLGBTQ+ experiences, particularly among those who do not use 2SLGBTQ+ identity labels but may face health or social concerns linked to same-sex attraction or behavior. Recent improvements, such as the 2019–2021 CCHS updates and the 2021 Census on gender identity and sex at birth, represent important progress toward more inclusive data, but gaps remain. The 2026 Census will finally include a measure for sexual orientation. Specifically, the long-form questionnaire will include a question on sexual orientation for people aged 15 years and over, asking them to

For social work educators, these limitations are not just methodological details. They have real consequences for how students learn to interpret evidence about LGBTQ+ populations. For instance:

• Surveys that collapse bisexual respondents into “gay/lesbian” categories risk erasing the distinct experiences of bisexual people, including elevated risks of poor mental health and violence.

• Surveys that only ask about identity may overlook individuals who engage in same-sex sexual behavior but identify as heterosexual (i.e., groups that may still benefit from affirming services, HIV/STI prevention, or supportive community programming).

• Non-response categories (“don’t know” or “prefer not to answer”) may reflect discomfort, lack of inclusive options (e.g., queer, pansexual, asexual), or even capture transgender respondents who were not given other opportunities to self-identify.

Teaching students to critically evaluate these measurement issues helps prepare them for evidence-informed practice. It highlights that survey design choices influence who is counted, who is left invisible, and how social work professionals can advocate for better data collection to advance anti-homophobic and anti-transphobic policy and practice.

Watch MapleSoup video about 2026 Census changes, including the inclusion of sexual orientation, here.

Measuring Gender Identity

How surveys frame gender questions has direct implications for who is counted and how results can be interpreted. For social work educators, this is important because it shapes the evidence students and practitioners draw on when discussing equity, health, and social policy.

Best practice is a two-step approach that first asks about sex at birth and then about current gender identity. This method is widely seen as the most accurate way to identify transgender and gender diverse populations.

Canadian surveys have moved unevenly in this direction. The 2021 Census was the first national census to ask directly about both sex at birth and current gender, allowing Statistics Canada to produce population counts for transgender and non-binary people. The Canadian Community Health Survey (CCHS) has also introduced a two-step measure, giving researchers the ability to examine health outcomes by gender identity with more precision.

Other surveys remain more limited. The Public Service Employee Survey, for example, allows respondents to select male, female, or write in another identity. While this offers an option beyond the binary, it does not ask about sex at birth. This makes it difficult to separate transgender men and women from non-binary or other gender diverse groups, resulting in a category that mixes very different experiences.

For social work education, these examples illustrate both progress and gaps. They provide an opportunity to teach students how survey design influences visibility and representation, and why inclusive measurement is necessary if we want reliable data to inform practice with marginalized communities.

Response Bias

Questions about sexuality and gender identity are sensitive and some respondents may choose to not answer truthfully. This risk can be higher in face-to-face or telephone surveys, where privacy feels limited. Inclusive wording, self-administered questionnaires, and assurances of confidentiality can reduce this problem.

Patterns of response bias are not the same across all groups. For example, Kim and Fredriksen-Goldsen (2013) found that nonresponse to sexual orientation questions in U.S. surveys was more common among Asian American, Hispanic, and African American participants than among non-Hispanic white respondents. In Canada, Statistics Canada has reported relatively strong response rates. In the 2021 Census, nonresponse was about 4% for the gender question and 3.8% for sex at birth. In the Canadian Community Health Survey (CCHS), nonresponse to the sexual orientation item has averaged around 3.7%. While these nonresponse rates are low, analysts note that certain groups such as racialized populations, Indigenous peoples, and newcomers, may still be more hesitant to disclose, which could lead to underrepresentation.

For social work educators, this highlights two teaching points: survey design can either encourage or discourage disclosure, and data on 2SLGBTQ+ populations may underrepresent those already facing structural barriers. Recognizing these gaps helps students think critically about how statistics inform, and sometimes obscure, the realities of marginalized communities.

Distrust and Barriers to Participation

Another challenge is the distrust some 2SLGBTQ+ people feel toward research participation, especially those who have experienced institutional discrimination, such as older generations. Concerns about how their data will be used, whether their identities will be respected, or the risk of unwanted disclosure can result to hesitation, partial disclosure, or refusing to participate. This reduces representation in survey results and therefore limits the accuracy of data findings. For social work educators, this highlights the need to teach students how research should build trust. This can be accomplished through clear communication, strong adherence to ethical obligations for ensuring participant confidentiality, as well as building research collaborativly with community organizations so that research better represents lived experiences.

Intersectionality in 2SLGBTQ+ Data

A major gap in current LGBTQ+ data collection is the difficulty of capturing intersectionality. 2SLGBTQ+ experiences are shaped not only by sexual orientation or gender identity, but also by race, Indigeneity, ethnicity, race, disability, class, geography, and migration status. When surveys collect data on these variables separately, the small number of respondents who belong to multiple marginalized groups often become invisible as public data needs to suppress for example cross tabulations where redisclosure risk can happen. For example, while a national survey might report outcomes for “LGBTQ+ respondents” as a whole, it may not be able to disaggregate results for Two-Spirit Indigenous youth, disabled transgender adults, or queer newcomers to protect priavacy.

Without intersectional analysis, disparities perpetuate, and services may be designed in a way that does not reflect the needs of its most marginalized members. For instance, housing insecurity may be more acute for racialized 2SLGBTQ+ youth, or health access gaps may be wider for transgender people living in rural or northern regions. These realities are often missed when sample sizes are too small to support detailed breakdowns.

It therefore becomes critical for social work educators to flag this limitation and encourages students to think critically about who is represented in the data, who is excluded, and how these exclusions reinforce structural inequities. It also underscores the need for complementary qualitative research or community-based participatory action research, which can amplify the voices of those at the intersections of multiple oppressions.