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Record W2126388465

Research orientation of South African occupational therapists

2013· article· en· W2126388465 on OpenAlexaboutno aff
Hanlie Pitout

Bibliographic record

VenueSouth African Journal of Occupational Therapy · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyOrientation (vector space)Research designValue (mathematics)Survey researchPsychologyMedicineMedical educationNursingApplied psychologyPhysical therapySociologySocial scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Abstract The value placed on and extent of involvement of occupational therapists in research is unknown. This article reports on the quantitative part of a mixed methods study conducted to establish the multi-dimensional factors that influence Research Orientation. A cross-sectional descriptive design was employed. Data was collected using a previously validated instrument, the Edmonton Research Orientation Survey (EROS). The survey was posted to all occupational therapists on the HPCSA register (2279 occupational therapists) in August 2007. A thirteen percent response rate (298 of 2279) was achieved. Most respondents (177/275, 67%) had high overall EROS scores (mean = 133.6 and median =136.) indicating a strong research orientation. With further analyses it became clear that occupational therapists value research ( 195 / 290, 67%) and see themselves at the leading edge of the profession (214 / 291, 73% ) yet evidence based practice (149 / 285, 52%) and involvement in research is limited (76 / 275, 28%). The results suggest that although occupational therapists value research they do not engage in applying research in practice or participate in execution of research. The positive research orientation provides an opportunity for the profession to use the available potential to increase research output.

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)0.006
metaresearch head score (Gemma)0.001
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 score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.352
GPT teacher head0.546
Teacher spread0.194 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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