Demonstrations of implicit anti-fat bias: the impact of providing causal information and evoking empathy.

Three studies investigated implicit biases, and their modifiability, against overweight persons. In Study 1 (N = 144), the authors demonstrated strong implicit anti-fat attitudes and stereotypes using the Implicit Association Test, despite no explicit anti-fat bias. When participants were informed that obesity is caused predominantly by overeating and lack of exercise, higher implicit bias relative to controls was produced; informing participants that obesity is mainly due to genetic factors did not result in lower bias. In Studies 2A (N = 90) and 2B (N = 63), participants read stories of discrimination against obese persons to evoke empathy. This did not lead to lower bias compared with controls but did produce diminished implicit bias among overweight participants, suggesting an in-group bias.     

Mental health and quality of life in non-binary transgender adults: a case control study

Abstract

Background: The social challenges that non-binary people experience, due in part to social intolerance and the lack of validation of non-binary gender identities, may affect the mental health and quality of life of this population. However, studies that have distinguished between non-binary and binary transgender identities are lacking.

Aim: To compare the mental health and quality of life of a community sample of non-binary transgender adults with controls (binary transgender people and cisgender people) matched on sex assigned at birth.

Method: A total of 526 participants were included. Ninety-seven were classified as non-binary and were compared with two control groups: 91 people classified as binary and 338 cisgender people. Only transgender people not on gender affirming hormone treatment or who had not undergone gender affirming surgery were included. Participants were invited to complete an online survey that included mental health and quality of life measures.

Results: Non-binary people reported significantly better mental health than binary transgender people, but worse than cisgender people. Overall, there were no significant differences in quality of life between non-binary and binary transgender participants assigned male at birth and transgender females, but non-binary assigned males at birth had better scores on the psychological and social domains of quality of life than transgender males. Quality of life was better across all domains in cisgender people than transgender groups.

Conclusion: There is an inequality with regard to mental health and quality of life between non-binary (and binary) transgender people and the cisgender population that needs to be addressed. The better mental health scores in non-binary people may reflect lower levels of body dissatisfaction among the non-binary population. Mental health problems and poor quality of life are likely to have social causes and hence legislative measures and broader government-led inclusive directives should be put in place to recognize and to validate non-binary identifying people.