MétaCan
Menu
Back to cohort
Record W2116904019 · doi:10.1177/0008417413484450

Working with transgender clients: Learning from physicians and nurses to improve occupational therapy practice

2013· article· en· W2116904019 on OpenAlexafffundvenue
Brenda L. Beagan, Alana Chiasson, Cheryl A. Fiske, Stephanie D. Forseth, Alisha C. Hosein, Marianne R. Myers, Janine E. Stang

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2013
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsRoyal Alexandra HospitalWilliam Osler Health SystemCumulative Environmental Management AssociationBrampton Civic HospitalDalhousie University
FundersCanadian Institutes of Health Research
KeywordsTransgenderNursingOccupational therapyHealth careLesbianMedicinePopulationMental healthPsychologyFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Gender identity disorder and the process of transitioning involve both mental and physical health, yet there is virtually no discussion of transgender health care in occupational therapy. PURPOSE: This study draws on interviews with primary-care nurses and physicians about their experience with transgender health care, extending the insights gleaned there to make suggestions for occupational therapy practice with this population. METHOD: Semi-structured interviews were conducted with 12 primary care nurses and 9 physicians who had clinical experience with lesbian, gay, and bisexual patients. FINDINGS: Participants felt uncertain about transgender care, wanting more specialized knowledge. Collaborating with patients, acknowledging stigma, ensuring inclusive systems and procedures, navigating health care, and providing holistic care emerged as key elements for best practice. Advocacy was a crucial part of care provision. IMPLICATIONS: Suggestions are provided for therapists to ensure that space and interactions are welcoming to transgender clients as well as suggestions for occupational therapy intervention in the transitioning process.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.142
GPT teacher head0.412
Teacher spread0.270 · 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; a candidate call from one teacher head, not a consensus.

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

Citations52
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Occupational TherapySame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207