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Record W1976605563 · doi:10.2182/cjot.2011.78.5.3

A Critical Review of Interventions Addressing Ageist Attitudes in Healthcare Professional Education

2011· review· en· W1976605563 on OpenAlexafffundvenue
Cary A. Brown, Diane J. Kother, Trish Wielandt

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2011
Typereview
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsRed Deer Regional HospitalUniversity of Alberta
FundersPublic Health Agency of CanadaMcMaster University
KeywordsPsychological interventionHealth careHealth professionalsNursingMedicinePsychologyMedical educationEngineering ethicsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: As the population ages, the demand for health care services will increase. Evidence suggests that the pervasive negative societal beliefs regarding aging and older persons are also found among occupational therapy students and practitioners. These attitudes can negatively affect healthcare service provision. PURPOSE: To determine the strength of the evidence regarding educational interventions used to modify ageist values and beliefs of health care professionals. METHODS: A critical review of the literature was undertaken to evaluate methodological quality of relevant outcome studies. FINDINGS: . Of the fifteen studies meeting the inclusion criteria one was rated as "strong" evidence, and the remainder lacked methodological rigour. Such results make it difficult to decide the usefulness of including educational interventions in health care curricula to negate ageism. IMPLICATIONS: Research specific to occupational therapy is required as our unique frames of reference and theoretical models to guide practice may preclude generalizability of research from other professional groups.

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)0.010
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.033
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.692
GPT teacher head0.648
Teacher spread0.044 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations21
Published2011
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Occupational TherapySame topicAging and Gerontology ResearchFrench-language works237,207