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Record W1696931838 · doi:10.3233/wor-2004-00379

Approaches to worker rehabilitation by occupational and physical therapists in the United States: Factors impacting practice

2004· article· en· W1696931838 on OpenAlexaff
Rosemary Lysaght

Bibliographic record

VenueWork · 2004
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsScope (computer science)Work (physics)RehabilitationScope of practiceValue (mathematics)Service (business)Best practicePsychologyMedical educationBusinessPublic relationsMedicineHealth carePolitical scienceMarketingComputer scienceEngineeringEconomic growthManagementEconomicsPhysical therapy

Abstract

fetched live from OpenAlex

Work-related rehabilitation services have changed in nature and scope since their inception in the late 1970s. A review of the literature reveals a large body of published data concerning the various approaches used by therapists in this practice area, but a limited number of comparison studies documenting the value of one approach over the other. This national survey of physical and occupational therapists in the US was conducted in 2002, and examined the prevailing trends in service provision, and factors that determine the nature of services provided to clients. Results indicate that services continue the move to onsite service provision and an emphasis on prevention, but that select services, such as onsite job analysis and comprehensive, inter-disciplinary programs are being used to a limited degree. Research that examines the relative contributions of selected work-related services to successful and efficient return to work outcomes is necessary to identify best practice approaches. Therapists and insurance providers should work more closely in exchange of data that will ensure optimal program design and funding.

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)0.017
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 score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.213
GPT teacher head0.480
Teacher spread0.267 · 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

Citations13
Published2004
Admission routes1
Has abstractyes

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