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The Disclosure of an LGBTQ Identity in Thailand: Patterns, Correlates, and Responses
Alicia K Matthews1, Safa Elkefi1, Priyoth Kittiteerasack2
1School of Nursing, Columbia University, New York, New York, USA.
Abstract:
Limited lesbian, gay, bisexual, transgender, and queer (LGBTQ) health research exists in many countries, including Thailand. Understanding LGBTQ outness is a key determinant in developing targeted and impactful mental health strategies. Outness among LGBTQ individuals, once safe from potential discrimination, brings significant benefits of acceptance, affirmation, and adequate healthcare access. This study examined outness patterns among 388 Thai LGBTQ adults, using a secondary analysis of a larger cross-sectional descriptive survey on minority stressors and mental health. The Outness Inventory measured identity disclosure and responses to those disclosures in three categories: the World, Family, and Religious Community. Descriptive and bivariate analyses were conducted. Participants reported higher levels of outness to the world (M = 5.55, SD = 1.88) and to their family (M = 5.39, SD = 2.03) compared to their religious communities (M = 3.92, SD = 2.58). Acceptance rates following LGBTQ disclosure were highest in the 'World' category, followed by 'Family' and then 'Religious Communities.' Percentage acceptance ranged from 30.15% for members of religious communities to 64.69% for their heterosexual friends. Overall, less acceptance among family members and religious communities was associated with participants being gay, feminine, and at an older age when first disclosing their LGBTQ identity. Outness has important implications for LGBTQ mental health nursing research. Interventions to support the coming-out process and promote positive attitudes toward LGBTQ individuals are most needed for their families and religious institutions.
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There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...