EXPLORING LAURIER HEALTH SCIENCES STUDENTS’ KNOWLEDGE OF LGBTQ+ HEALTH
Bibliographic record
Abstract
In all health-related fields, the need for well-informed, holistic healthcare providers is paramount. For the heathcare field to be impactful in positive ways, providers should emerge from multifaceted academic backgrounds, equipped with an array of knowledge and skills to address the complex needs of different patients. Central to this is the idea that all aspects of an individual's identity and the intersectionality of these identities should be considered when providing care. Intersectionality recognizes that various social and personal identities, such as race, gender, sexuality, and socioeconomic status, intersect to shape individual experiences and health outcomes (Kelly et al., 2022). Lesbian, gay, bisexual, transgender, and queer (LGBTQ+) individuals face unique challenges, including when accessing and receiving healthcare (Goldsmith & Bell, 2022). They often experience prejudice and discrimination, which can lead to significant health disparities and outcomes (Goldsmith & Bell, 2022; Tran et al., 2023). Despite this, minimal hours are allocated to LGBTQ+-specific education and training in Canadian health programs (Obedin‐Maliver et al., 2011). This gap in LGBTQ+ health education is concerning, as it may leave recent healthcare providers ill-prepared to meet the needs of LGBTQ+ patients (Minturn et al., 2021; Obedin‐Maliver et al., 2011). Most of the research regarding LGBTQ+ health education has focused on medical or physiotherapy students’ preparedness to treat and care for LGBTQ+ patients. This research has highlighted a lack of preparation, identifying a shortfall in current medical and physiotherapy school curricula, failing to equip future healthcare providers with the necessary knowledge to not only offer adequate care, but to also demonstrate empathy and compassion when caring for LGBTQ+ individuals (Greene et al., 2018; Minturn et al., 2021). With much of the literature on LGBTQ+ health education centering on medical school and other professional programs, it is warranted to explore content earlier, in undergraduate programs that feed into these professional programs, and also other graduate programs, as it might provide an earlier opportunity to shape inclusive, informed health professionals. There is very minimal research examining the knowledge and attitudes of health sciences students regarding LGBTQ+ health topics and healthcare, especially in Ontario, and many of these students move on to work in healthcare settings where they will inevitably encounter LGBTQ+ patients. This thesis further explores these gaps in depth by examining the provision of LGBTQ+ health education in Laurier’s Health Sciences program by developing an understanding of the knowledge and attitudes of upper-year health sciences students. This research outlines areas where improvements or alterations in the curricula are suggested. The intention is to contribute to the development of more inclusive and effective LGBTQ+ health education in health sciences, recognizing the importance of understanding and the diverse needs of all patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".