Development of gender identity implicit association tests to assess attitudes toward transmen and transwomen.

Abstract

The purpose of this study was to develop and validate 2 gender identity implicit association tests (GI-IATs) designed to assess attitudes toward transsexual men (Transmen-IAT) and transsexual women (Transwomen-IAT). A sample of 344 Mechanical Turk participants from the United States (173 women, 129 men, 43 transgender) completed the following: GI-IATs, Genderism and Transphobia Scale, Allophilia Toward Transsexual Individuals Scale, Social Desirability Scale-17, feelings thermometers, and ratings of intention to support transgender workplace policies. Results indicate that people who are cisgender (non-transgender), heterosexual, politically conservative, or who reported no personal contact with transgender individuals showed cisgender preferences on both GI-IATs. Additionally, both measures correlated as predicted with the explicit measures (feeling thermometers) of attitude toward transgender individuals. As expected, the explicit attitude measures, but not the GI-IATs, correlated with social desirability. Further, confirmatory factor analyses supported the model comprising 4 distinct latent variables: implicit attitudes toward transmen, explicit attitudes toward transmen, implicit attitudes toward transwomen, and explicit attitudes toward transwomen. Finally, hierarchical multiple regressions showed that both explicit and implicit measures predicted support for transgender workplace policies. Additional analyses showed that both the Transmen-IAT and the Transwomen-IAT accounted for incremental variance above and beyond the relative feelings thermometers in predicting policy support intentions. These findings provide significant psychometric support for both GI-IATs. They also highlight the importance of incorporating implicit measures in studying attitudes toward transgender individuals, and of distinguishing attitudes toward transmen versus transwomen.

Implicit Transgender Attitudes Independently Predict Beliefs About Gender and Transgender People

“…More notably, these results differ from previous work assessing implicit transgender attitudes. In Wang-Jones et al (2017), participants classified as transgender ( N = 42) showed no ingroup favoritism on IATs measuring associations toward “transsexual men” (vs. “biological men”) or “transsexual women” (vs. “biological women”). One potential explanation may come from differing methods for classifying transgender participants.…”

“…In fact, the only existing measure of implicit transgender attitudes (Wang-Jones et al, 2017, 2018) used an Implicit Association Test (IAT; Greenwald et al, 1998), and found that implicit attitudes toward “transsexual men” and “transsexual women” correlate reliably but weakly with parallel explicit attitudes. However, this implicit measure had features that limit its generalizability.…”

“…Such evidence would suggest that implicit attitudes play an independent role in individuals’ beliefs about transgender people, with potentially unique causes driving their development. Most prior investigations into this issue of incremental predictive validity for implicit attitudes (including Wang-Jones et al, 2017) relied on least squares linear regression, an analysis strategy known to inflate false positives (Westfall & Yarkoni, 2016) due to inability to account for measurement reliability. Establishing the incremental predictive validity of transgender attitudes via more appropriate analysis strategies would provide evidence for the predictive validity of both implicit transgender attitudes and implicit association measures in general.…”

“I’m Not a Science Nerd!”

“…In addition, the measure of explicit STEM gender associations used in this study was a 1-item 0-100 feelings thermometer. Although feeling thermometers have been used in the past to successfully measure stereotypes (Wang-Jones et al, 2017), having a scale with multiple items may increase reliability. Finally, the scale order was not randomized, and order effects could not be tested.…”

Reward Omissions Variably Augment Racial Bias along Political Ideology

“…-cf., Johnson, Lakhan, Lecci, Dovidio, & Schellhaas, 2020), or across different gender categories (e.g., do Conservatives become more anti-Trans when frustrated? -cf., Wang-Jones, Alhassoon, Hattrup, Ferdman & Lowman, 2017). The present work constitutes a template for exploring other social biases that may be augmented by arbitrary reward omissions (Amsel, 1992).…”