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Record W2126614331 · doi:10.3138/ptc.59.4.241

Weighing the Evidence: Clinical Decision Making in Neurological Physical Therapy

2007· article· en· W2126614331 on OpenAlexvenueaboutno aff
Mandy McGlynn, Cheryl Cott

Bibliographic record

VenuePhysiotherapy Canada · 2007
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsGrounded theoryVariety (cybernetics)Evidence-based practiceMedicineQualitative researchClinical PracticePhysical therapistPhysical activityMedical educationProcess (computing)PsychologyPhysical therapyAlternative medicineComputer science

Abstract

fetched live from OpenAlex

Purpose: The purpose of this study was to explore (1) the processes that neurological physical therapists go through in making dayto-day clinical decisions and (2) the sources of information or evidence that therapists use in their day-to-day practice. Method: A qualitative, grounded theory method was used consisting of semistructured, face-to-face in-depth interviews with 12 neurological physical therapists practising in a variety of settings in the Greater Toronto Area. Data were analyzed using a constant comparative approach. Results: Therapists weigh a variety of informal and formal sources of evidence as they go about their day-to-day practice. Our results fall into three main categories: (1) sources of evidence weighed, (2) when and why therapists weigh the evidence, and (3) factors that influence the process of weighing the evidence. Conclusions: The results of this study indicate that implementing evidence-based practice will be a challenge to the physical therapy profession unless we broaden our definition of evidence to include informal sources of evidence that are highly valued by clinicians.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.180
GPT teacher head0.585
Teacher spread0.404 · 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.

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

Citations34
Published2007
Admission routes2
Has abstractyes

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