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Record W4235525940 · doi:10.2196/preprints.23568

Exploration of Gender-Sensitive Care in Vocational Rehabilitation Providers Working With Youth With Disabilities: Codevelopment of an Educational Simulation (Preprint)

2020· preprint· en· W4235525940 on OpenAlexaff
Sally Lindsay, Kendall Kolne, D Barker, Angela Colantonio, Jennifer Stinson, Sandra Moll, Nicole Thomson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsHospital for Sick ChildrenCentre for Addiction and Mental HealthHolland Bloorview Kids Rehabilitation HospitalMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)Vocational educationNonprobability samplingPsychologyMedical educationHealth careRelevance (law)RehabilitationQualitative researchFocus groupNursingMedicinePedagogySociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND Although research shows that there is a need for gender-specific vocational support to help youth with disabilities find employment, health care providers often report needing more training in this area. Currently, there are no existing educational simulations of gender-sensitive care within vocational rehabilitation for clinicians who provide care to youth with disabilities. Therefore, developing further educational tools that address gender-sensitive care could help them enhance the care they provide while optimizing patient outcomes. OBJECTIVE This study aims to codevelop an educational simulation and identify issues relevant to providing gender-sensitive care within the context of vocational rehabilitation for youth with disabilities. METHODS We used a qualitative co-design approach with a purposive sampling strategy that involved focus group discussions and journal reflections to understand and address issues relevant to gender-sensitive care within vocational rehabilitation for those working with youth with disabilities. A total of 10 rehabilitation providers participated in two sessions (5 participants per session) to design the web-based simulation tool. The sessions (2.5 hours each) were audio recorded, transcribed, and analyzed thematically. RESULTS Two main themes arose from our analysis of codeveloping a simulation focusing on gender-sensitive care. The first theme involved the relevance of gender within clinical practice; responses varied from hesitance to acknowledging but not talking about it to those who incorporated gender into their practice. The second theme focused on creating a comfortable and safe space to enable gender-sensitive care (ie, included patient-centered care, effective communication and rapport building, appropriate language and pronoun use, respecting gender identity, awareness of stereotypes, and responding to therapeutic ruptures). CONCLUSIONS Our web-based gender-sensitive care simulation that addressed vocational rehabilitation among youth with disabilities was cocreated with clinicians. The simulation highlights many issues relevant to clinical practice and has potential as an educational tool for those working with young people with disabilities. CLINICALTRIAL

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.044
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0050.003
Open science0.0020.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.128
GPT teacher head0.362
Teacher spread0.233 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2020
Admission routes1
Has abstractyes

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