The Gender Congruence and Life Satisfaction Scale (GCLS): Development and validation of a scale to measure outcomes from transgender health services

Background: It is vital that the treatment offered at transgender health services can be evaluated to ensure a high quality of care. However, the tools currently used to evaluate treatment at transgender health services are limited by mainly focusing on mental health or because they have been developed for binary transgender people only. This study therefore aimed to develop and validate a tool that addresses these limitations. The Gender Congruence and Life Satisfaction Scale (GCLS) was developed through reviewing the literature, conducting interviews with transgender people, and holding discussions with experts working in transgender healthcare. An initial pool of items was developed and feedback on these was obtained. The tool was then validated.

Method: For the validation of the tool, a total of 789 participants (451 transgender [171 transgender females, 147 transgender males, 133 people identifying as non-binary], and 338 cisgender [254 females, 84 males]) were recruited from the United Kingdom to test the factor structure and validity of the GCLS.

Results: Exploratory factor analysis retained 38 items which formed seven subscales (psychological functioning; genitalia; social gender role recognition; physical and emotional intimacy; chest; other secondary sex characteristics; and life satisfaction). These seven subscales were found to have good internal consistency and convergent validity. The GCLS was also found to be capable of discriminating between groups (e.g., people who have and have not undergone gender affirming medical interventions). Transgender and cisgender subscale norms are provided for the GCLS.

Conclusion: The GCLS is a suitable tool to use with the transgender population to measure health-related outcomes for both clinical and research purposes.     

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.     

Suggestions for the maintenance of accuracy of calculations implemented on digital computers

An approach that selectively uses double precision in calculating statistical quantities is described. Emphasis is placed upon the multiplication and accumulation rather than on the data themselves. In this way, core storage requirements are minimized and good relative error is also achieved.