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Record W2324264186 · doi:10.3928/01484834-20120515-01

Nursing Student Perceptions of Disability and Preparation to Care for People With Intellectual Disabilities

2012· article· en· W2324264186 on OpenAlexaff
Beverley Temple, Elaine Mordoch

Bibliographic record

VenueJournal of Nursing Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIntellectual disabilityPerceptionNursingWheelchairPsychologyMedicineMedical educationPsychiatry

Abstract

fetched live from OpenAlex

As people with intellectual disabilities live longer and develop more chronic illnesses, nurses will have increasing contact with them. Therefore, nurses must have both an accurate understanding of and a positive attitude toward this population to ensure optimal nursing care is received. A cross-sectional survey of second-year and fourth-year nursing students measured their perceptions of disability, their contact with people with intellectual disabilities, and their perceptions of education to prepare them to care for people with intellectual disabilities. Students most often identified disability as physical, using a wheelchair to represent that perception. Students were confident in their ability to transfer many of the skills they learned to care for people with intellectual disabilities but identified a need for more education about providing that care. Curricular changes to enhance nursing students' awareness and understanding of people with intellectual disabilities are recommended.

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 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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.450
Teacher spread0.416 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations23
Published2012
Admission routes1
Has abstractyes

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