Rainbow Community of Practice: Supporting Nurse Practitioners caring for 2SLGBTQ clients
Bibliographic record
Abstract
Aim: This study examines the learning needs of nurse practitioners (NPs) related to Two-Spirit, lesbian, gay, bisexual, transgender, and queer (2SLGBTQ) healthcare and evaluates the efficacy of a one-day conference on transgender health care to address the identified knowledge gaps for NPs. Background: 2SLGBTQ individuals continue to experience barriers when accessing healthcare. A lack of education about 2SLGBTQ healthcare needs has been identified as a barrier to NPs providing inclusive care to this population. The Rainbow NP community of practice was developed as a forum for sharing expertise about 2SLGBTQ healthcare, while providing safe space to ask questions, share resources and network. To understand the learning needs of NPs about 2SLGBTQ health, a survey was developed by the community of practice and sent to all members of the Nurse Practitioner Association of Ontario. Results from that survey informed the development of a one-day professional development conference on transgender health. Methods: This study utilized secondary analysis of two quantitative questionnaires. The first questionnaire examined NPs learning needs related to providing care to 2SLGBTQ clients, and the second questionnaire evaluated the effectiveness of the one-day conference on transgender health. Study participants included members of the Nurse Practitioner Association of Ontario and attendees of the one-day conference. Findings: Sixty-six member surveys (response rate 4.5%) were returned. Results showed that 74% of NPs surveyed felt their clinical practice setting was 2SLGBTQ friendly. The majority of participants reported they were comfortable or somewhat comfortable providing care to a transgender individual, however almost a third of NPs surveyed were not comfortable providing care to transgender clients. Forty-three conference participants completed the second survey (response rate 54%). The majority of participants rated the conference as excellent (84%). Four themes emerged from the feedback: clinical pearls; the patient voice; focus on transgender care; and the NP lens. Conclusion: Supporting NPs to provide care to transgender individuals is an important way to improve care to this population. Professional development opportunities for NPs to enhance their knowledge and capacity in caring for the 2SLGBTQ population were well received and much needed. Developing a community of practice is a way to support NPs, allow for professional development opportunities and to share knowledge with the broader NP community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 teacher head, 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".