- Research Grants
|Support type:||Scholarships in Brazil - Scientific Initiation|
|Effective date (Start):||August 01, 2019|
|Effective date (End):||July 31, 2020|
|Field of knowledge:||Health Sciences - Collective Health|
|Principal Investigator:||Edson Zangiacomi Martinez|
|Home Institution:||Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil|
Although the restrictions on blood donation of men who have sex with men (MSM) have been reviewed worldwide, the temporary deferral is commonly interpreted by the LGBT community as discriminatory and conducive to homophobic attitudes, being based solely on sexual orientation alone. No Brazilian studies as far we know has evaluated the perceptions, attitudes and practices of the LGBT population regarding blood donation and investigated the opinions about the current norms in the regulation of hemotherapy services in Brazil. It motivates us to investigate this issue in our country and to enhance the knowledge for the area wich can be useful both to support current discussions on the topic and to generate hypotheses for future studies. Objectives: To evaluate the perceptions, attitudes and practices regarding blood donation and regulations currently in force in the regulation of blood services among members of the LGBTQ community. Methods: This is a cross-sectional study characterized as Open Web Survey. Data collection will be conducted in three large LGBT communities on Facebook through an electronic self-completion questionnaire available via online link using the REDCap data capture tool. The data will be analyzed through logistic regression models to study the association between (dependent) variables (a) donation practice (donor / non donor), (b) search for blood bank for serological tests (yes / no), and the independent variables: age, marital status, pattern of alcohol and drug use, social class, among others. The variables related to perceptions and attitudes will be associated by logistic regression models or politomic regression models.