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Record W2008616045 · doi:10.1016/s1013-7025(09)70018-1

Intensive Care Physiotherapy — Medical Staff Perceptions

2001· article· en· W2008616045 on OpenAlexaboutno aff
Alice Jones

Bibliographic record

VenueHong Kong Physiotherapy Journal · 2001
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineService (business)Work (physics)PerceptionNursingIntensive carePhysical therapyMarketingIntensive care medicine

Abstract

fetched live from OpenAlex

A questionnaire was sent to directors of intensive care units (ICUs) in the United Kingdom, Australia, Canada, South Africa and Hong Kong, to gather regional perceptions of each ICU's physiotherapy service. A second questionnaire was sent to the ICU physiotherapist-in-charge to profile their experience and any demarcation disputes. Fifty-four of 101 ICU directors and 100% of the physiotherapists returned a completed questionnaire. While 79% of the directors rated the service provided by their physiotherapists as either ‘outstanding’ or ‘very good’, nearly 60% of them also considered that the physiotherapist's work could be performed by other disciplines. It is suggested that ICU physiotherapists broaden their research base to promote evidence-based practice, and develop a precise marketing strategy to preserve customer (ICU director) reliance on their product and to maintain ‘market share’, especially where ‘doctor-referrals’ impacts on their practice.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.049
GPT teacher head0.469
Teacher spread0.420 · 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 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

Citations35
Published2001
Admission routes1
Has abstractyes

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