Perceptions And Preparedness: A Study On Lgbt Patient Care Among Medical And Allied Healthcare Students And Practitioners In India Using LGBT-DOCSS
Bibliographic record
Abstract
Introduction: LGBTQ+ individuals often have unique healthcare needs, but they also face significant barriers that make it harder for them to access the care and support they deserve.. They continue to face challenges when accessing healthcare, particularly in countries like India, where social stigma and lack of adequate training among healthcare providers contribute to unequal care. [1] There is a lack of comprehensive education on LGBTQ+ healthcare, and students’ understanding of these issues is not well-documented. This study explored the knowledge and attitudes toward LGBTQ+ healthcare among medical, allied health students, and practitioners in India. Methods: This study used an online self-report survey to collect information on participants' personal and academic backgrounds, as well as their experiences with LGBT-related education during their medical and allied health studies and clinical practice. The total scores from the LGBT-DOCSS, along with the individual scores for the three subscales—clinical preparedness, knowledge, and attitudes—were analysed and compared against international standards. Results: The sample comprised of 200 respondents, all of the respondents reported a lack of LGBT community-related courses during their studies and clinical practice. The total score on the LGBT-DOCSS was 4.291 ± 0.717 out of 7, indicating a relatively low level of clinical competence. The highest mean score was in the attitude subscale (4.842 ± 1.059), which was significantly higher than the scores for the knowledge subscale (4.323 ± 1.419) and the clinical preparedness subscale (3.722 ± 1.349). Men reported higher levels of knowledge and clinical preparedness, but also showed more negative attitudes compared to women. On comparison with the scores of other countries like Israel, USA and Canada, India was lagging behind significantly in LGBT healthcare training due to Attitude of the people which was significantly lower when compared to other countries leading to such a significant difference in study. Conclusion: The participants reported low levels of clinical competency, especially in self-reported knowledge and clinical preparedness, but generally had positive attitudes toward the LGBT community. This highlights a crucial need for LGBT-inclusive education in medical and allied healthcare programs in India. The low levels of preparedness among students and clinicians stress the importance of incorporating LGBT-focused training to ensure healthcare providers are better equipped to offer inclusive and culturally competent care. Future studies should assess the long-term impact of such training on patient outcomes and healthcare delivery.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".