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Record W2079290615 · doi:10.1111/medu.12208

Sexual prejudice among medical students

2013· article· en· W2079290615 on OpenAlexaboutno aff
Ludwing Flórez‐Salamanca, José Elías Robles Rubio

Bibliographic record

VenueMedical Education · 2013
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPrejudice (legal term)Health careLesbianSexual minorityPsychologyPopulationFeelingHealth equityTransgenderPublic healthMedicineSexual orientationSocial psychologyNursingPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

Despite recent social and legislative efforts to establish equal rights for the lesbian, gay, bisexual and transsexual (LGBT) community, attitudes that derive from sexual prejudice in health care providers are still of concern around the world.1 Sexual prejudice in health care providers has several implications,2-4 which include the stigmatisation and exclusion of LGBT individuals, the imposition of feelings of discomfort, poor communication, the disruption of the development of positive alliances with LGBT patients and the disregard of specific health and health care needs.5-7 In addition, sexual prejudice results in less access to and underutilisation of health care services among the LGBT community, and leads to inequality of treatment and poorer quality of care.5 Attitudes that derive from sexual prejudice in health care providers are of concern around the world The LGBT community represents a minority group with higher levels of risk for psychiatric disorders, sexually transmitted diseases, poor health outcomes, social marginalisation and particular health care needs.6, 8 For these reasons, sexual prejudice in health care providers is likely to have a particularly negative impact on this minority with public health implications.1 Identifying and addressing sexual prejudice in individuals during medical training may represent an initial strategy for improving the provision of health care to the LGBT population.9 High rates of sexual prejudice have been reported in students in training for different health care careers, including medical, nursing and psychology students.2-4 Rates of sexual prejudice among doctors in training range between 15% and 25%,2-4 and are higher in males, individuals without LGBT friends or patients, individuals who have not previously had a sexual partner, people with strong religious beliefs and people on low incomes.2-4 Sexual prejudice in health care providers is likely to have a negative impact with public health implications Sexual prejudice in medical students should be monitored in order that the curriculum can be adapted correspondingly.3 Unless action is taken, sexual prejudice in future doctors may eventually exact a toll on the quality of patient care.3 During graduate education, it is important to create awareness among students of the impact this prejudice may have on the care they provide to patients.2 Identifying predictors of sexual prejudice in medical students is very important because it will allow individuals who carry prejudice to be identified and thereby facilitate the initiation of preventive programmes to decrease such bias. Education directed towards increasing understanding of diversity, and discussions of beliefs associated with this subject may be implemented in order to improve the health care of future LGBT patients. Sexual prejudice in future doctors may exact a toll on the quality of patient care During the 2009–2010 academic year, medical schools in the USA and Canada dedicated an average of 5 hours in the entire curriculum to LGBT-related topics.7 Respondents to a survey reported dissatisfaction with medical school coverage of LGBT content, evidencing the deficiency of education provided in this area.7 Previous attempts to improve medical education concerning sexual prejudice were promising.9 The structure of a formal lecture provides little opportunity for dialogue, but, as lack of contact with LGBT people is highly correlated with sexual prejudice, educational initiatives that facilitate direct contact between students and the LGBT community are predicted to be effective and may improve education.9 However, there are non-formal opportunities to introduce issues of homo- and transsexuality into medical education. Panel discussions with members of the LGBT community and workshops in which opinions and reflections on these issues can be discussed may promote further open-mindedness and decrease sexual prejudice.3, 9 In addition, specialist workshops and daily interaction with openly LGBT students may raise awareness about the rights and visibility of this community.10 Furthermore, discussing homosexuality openly with patients who are willing to do so may benefit not only the patient, but also the doctor in training if it decreases his or her sexual prejudice.9 In addition, essential non-formal educational opportunities in this context depend on the transmission of positive values by mentors and the examples they set. To make use of these, faculty staff and attending physicians should demonstrate clinical empathy for LGBT patients.3, 9, 10 Limited knowledge of LGBT issues in faculty staff should be addressed using methods similar to those used in students. Educational initiatives that facilitate direct contact between students and the LGBT community are predicted to be effective In conclusion, sexual prejudice is a frequent finding in medical students, which, if it is not eradicated, may come to represent an unfortunate barrier in multiple ways to the provision of health care to the LGBT community. Specific groups may require greater levels of sensitisation and education in this area. Medical training includes many opportunities to approach the problem and to implement strategies to decrease sexual prejudice in future doctors. Strategies that involve direct interaction with the LGBT community and reinforcement by faculty members and staff are essential to decrease sexual prejudice in medical students.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0650.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.438
Teacher spread0.421 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2013
Admission routes1
Has abstractyes

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