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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. 相似文献
Research Highlights
- Reinforcement learning shows age-related improvement during adolescence, but more in stable learning environments compared with volatile learning environments.
- People tend to stay with an option after a win more than they shift from an option after a loss, and this asymmetry increases with age during adolescence.
- Computationally, these changes are captured by a developing confirmatory learning style, in which people learn more from outcomes that confirm rather than disconfirm their choices.
- Age-related differences in confirmatory learning are explained by decreases in stochasticity, rather than changes in the magnitude of the confirmation bias.