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Record W3195676069 · doi:10.1201/b20752-40

Evidence- based education in physiotherapy

2005· book-chapter· en· W3195676069 on OpenAlexaboutno aff
Sarah Wojkowski and Julie Richardson Vanina Dal Bello- Haas

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical therapyPhysical medicine and rehabilitationPsychologyMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION Physiotherapy entry-level education has undergone extreme changes over the past century. Entry-level physiotherapy education has evolved from a 6-month to 1-year training course coinciding with World War I to a diploma programme. Although diversity in physiotherapy education still exists, since the 1980s physiotherapy education programmes have progressed from a diploma programme (still in existence in some African, Asian and eastern European countries) to a 3-or 4-year baccalaureate degree (e.g. European Union countries, the United Kingdom, Australia, New Zealand), a master’s degree (e.g. Canada, the United Kingdom, Australia) and a clinical doctorate degree (e.g. the United States, Australia).1 Numerous factors drive changes in entry-level education, physiotherapy curriculum, delivery methods (including ever-changing healthcare environments and systems), and continuous advances in healthcare and information technology. Currently, theory is considered foundational and is wholly integrated with practice within curricula; physiotherapy entry-level education is scientifi cally based, with less focus on ‘recipe approaches’ and observation and opinion-based decision-making; and evidence-based practice is now considered an essential element of physiotherapy programmes worldwide.1,2 Th ese education changes are well aligned with evolutionary shift s in the physiotherapy profession. Physiotherapy is an area of study that involves an expansive body of knowledge, and as a profession it has developed a distinct domain. Current physiotherapy speciality areas are numerous and varied, and physiotherapists work with a multitude of client populations. In addition to practising in diverse practice settings, from more traditional settings to schools, hospices and industry, physiotherapists also practise in non-patient care areas including the medico-legal fi eld, health policy and health administration. Direct access to physiotherapy services in many jurisdictions worldwide has resulted in professional autonomy, making physiotherapists responsible for their professional judgements and actions.3 Th e outcome of this independent and self-determined authority and accountability for decision-making is an everincreasing complexity of physiotherapy care and clinical practice environments.

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)0.031
metaresearch head score (Gemma)0.163
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.163
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.007
Science and technology studies0.0010.004
Scholarly communication0.0080.006
Open science0.0040.005
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0360.007

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 head0.240
GPT teacher head0.563
Teacher spread0.323 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2005
Admission routes1
Has abstractyes

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