Latent class analysis (LCA) is a statistical method used to identify unobserved subgroups in a population with a chosen set of indicators. Given the increasing popularity of LCA, our aim is to equip psychological researchers with the theoretical and statistical fundamentals that we believe will facilitate the application of LCA models in practice. In this article, we provide answers to 10 frequently asked questions about LCA. The questions included in this article were fielded from our experience consulting with applied researchers interested in using LCA. The major topics include a general introduction in the LCA; an overview of class enumeration (e.g., deciding on the number of classes), including commonly used statistical fit indices; substantive interpretation of LCA solutions; estimation of covariates and distal outcome relations to the latent class variable; data requirements for LCA; software choices and considerations; distinctions and similarities among LCA and related latent variable models; and extensions of the LCA model. To illustrate the modeling ideas described in this article, we present an applied example using LCA. Specifically, we use LCA to model individual differences in positive youth development among college students and analyze demographic characteristics as covariates and a distal outcome of overall life satisfaction. We also include key references that direct readers to more detailed and technical discussions of these topics for which we provide an applied and introductory overview. We conclude by mentioning future developments in research and practice, including advanced cross-sectional and longitudinal extensions of LCA. What is the significance of this article for the general public?In this article, we answer 10 frequently asked questions about the technical and applied underpinnings of latent class analysis (LCA), a statistical approach to understanding unobservable within-group differences in a population. Our goal is to provide readers with an introductory and conceptual understanding of LCA to inform appropriate application and interpretation of these models in research practice.

This article presents the development and psychometric evaluation of the Internalized Racism in Asian Americans Scale (IRAAS), which was designed to measure the degree to which Asian Americans internalized hostile attitudes and negative messages targeted toward their racial identity. Items were developed on basis of prior literature, vetted through expert feedback and cognitive interviews, and administered to 655 Asian American participants through Amazon Mechanical Turk. Exploratory factor analysis with a random subsample (n = 324) yielded a psychometrically robust preliminary measurement model consisting of 3 factors: Self-Negativity, Weakness Stereotypes, and Appearance Bias. Confirmatory factor analysis with a separate subsample (n = 331) indicated that the proposed correlated factors model was strongly consistent with the observed data. Factor determinacies were high and demonstrated that the specified items adequately measured their intended factors. Bifactor modeling further indicated that this multidimensionality could be univocally represented for the purpose of measurement, including the use of a mean total score representing a single continuum of internalized racism on which individuals vary. The IRAAS statistically predicted depressive symptoms, and demonstrated statistically significant correlations in theoretically expected directions with four dimensions of collective self-esteem. These results provide initial validity evidence supporting the use of the IRAAS to measure aspects of internalized racism in this population. Limitations and research implications are discussed. (PsycINFO Database Record

Internalized binegativity (IB), negative attitudes and beliefs about one's own bisexuality, can develop from chronic exposure to binegative discrimination and prejudice and is associated with several negative mental health consequences. We developed and tested an online intervention following the Releasing Internalized Stigma for Empowerment (RISE) model (Lin, Israel, & Ryan, 2018) to reduce IB and to offer a novel means to access and treat bisexual people. We analyzed data from 641 bisexual adults recruited from Amazon Mechanical Turk (MTurk) who were randomly assigned to the intervention or active control condition and asked to complete pretest and posttest measures. Four modules tailored for bisexual people, based on a review of relevant literature and expert feedback, comprised the intervention. The modules included: (a) a true/false quiz that challenged negative bisexual stereotypes with research evidence, (b) an activity where participants identified external sources of their binegative beliefs, (c) a biaffirming video and a writing exercise to express support for a bisexual person, and (d), presentation of positive aspects of being bisexual and biaffirming images. We used a posttest-only randomized controlled design with the intervention as the between-subjects factor. A series of one-way analyses of covariance (ANCOVAs), controlling for covariates of identity concealment and self-esteem, revealed that the intervention was efficacious in reducing IB at a small effect size in addition to influencing related constructs. These results offer a promising contribution to accessible and targeted intervention efforts for reducing bispecific minority stressors. Future directions include examining acceptability, feasibility, implementation, and replication issues. Public Significance StatementResults from our randomized controlled trial demonstrated that 4 online modules-comprised of activities using social psychology principles-conferred statistically significant and practically meaningful (e.g., effect sizes) changes in IB and related constructs compared with a control condition, supporting the efficacy of the intervention. Our findings demonstrate the viability of using online platforms to access and serve bisexual people, as well as the importance of considering bispecific aspects of minority stress when working with this highly vulnerable population.

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The purpose of this literature review article was to centralize a holistic view of sexual minority Asian and Pacific Islander American (SM APIA) experiences and offer recommendations to guide psychological practice. Theoretical and empirical works from various disciplines were synthesized and found to demonstrate the central role of API cultural values in the development and management of SM APIA sexual expressions. Connectedness to communities and cultures of origin, maintenance of prized social relationships, traditional expectations related to family and gender, as well as coping with minority stress emerged as key elements to understanding and working with this population. Findings suggest that conceptualizing SM APIAs through the lens of predominantly White LGBTQ community norms may lead psychologists to pathologize healthy approaches to navigating the sexual minority experience and intervene in culturally inappropriate ways. The authors discuss the broader API cultural context as a framework for understanding the following thematic sections that emerged from the literature: identity development, coming out, minority stress, and issues related to seeking healthy communities and relationships. They conclude with recommendations with which psychologists can support SM APIAs to draw on, and reconnect to, relevant cultural strengths to thrive despite exposure to multiple oppressions.