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Sampling

Sampling

The LGBTQ population has been underrepresented or absent from empirical research in the social, behavioral, and health sciences until relatively recently. While there are many explanations for why this has been the case, a primary culprit has been the stigmatization of LGBTQ people as well as research about them. LGBTQ people have been a “hidden” population, posing a challenge for recruiting samples for participation in research. More specifically, given the diversity among LGBTQ people, sampling methods that are effective for recruiting from one population may not be effective for recruiting from another.

Understanding sampling is important because researchers and consumers of research alike must critically examine the degree to which results from empirical studies are relevant for understanding the populations that may be of interest to them. For example, different sampling strategies are required, and results differ, if a study focuses on gay-identified men, men who have sex with men (MSM), or all men who could be understood as part of the broad LGBTQ population.

The following sections begin with an introductory discussion of sampling, including attention to issues of representation (the degree to which a sample represents the larger population that a given study is designed to understand). Sampling methods are then discussed within historical context, including early research on human sexuality and the slow emergence of research designed to include LGBTQ individuals. Finally, persistent challenges of obtaining samples that adequately represent the experiences of this diverse population are considered.

Sampling LGBTQ

Most studies that include individual human subjects rely on some form of sample because data from the entire population is unavailable and infeasible to obtain. In the case of LGBTQ research, it is unrealistic and impractical to include every individual who identifies as LGBTQ in a study; thus, research depends on collecting information from a smaller subgroup or “sample.” In social, behavioral, and health sciences (often using quantitative methods), typically the goal is to derive estimates from a sample that should reflect patterns in, or that can be generalized to, the broader population. In cultural studies or in fields of humanistic inquiry (often using qualitative methods), the goals for sample selection may not include generalizability but rather to understand the meaning of, and gain rich knowledge about, a social or cultural phenomenon. In both cases, the nature and character of a sample is important because the composition of a sample will shape either the degree to which results are generalizable to a broader population or the specificity or breadth of participant perspectives that inform the meanings or knowledge that emerge through analysis and interpretation.

Appropriate sampling methods therefore differ in relation to the type of study being employed. In quantitative studies, researchers often strive to collect large and random samples, also referred to as probability samples, as this provides some assurance that they accurately represent the population of interest. When researchers rely on opportunistic samples (samples consisting of participants who are the most easily accessible), individuals self-selecting into a study, or small samples, their findings may be biased and therefore not generalizable (e.g., the sample may only reflect a particular subset of the LGBTQ population). Although it is possible and desirable to recruit a large sample to participate in a survey, it is much more challenging to do so for a qualitative study, such as those based on interviews, focus groups, or ethnographic inquiries. Yet qualitative studies offer the possibility to provide profound insight into the lives of LGBTQ people; the depth of knowledge obtained obviates the need for generalizability. In sum, sampling methods must be carefully evaluated in conjunction with the proposed research questions and the most relevant type of data for addressing research questions.

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