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Record W2006000849 · doi:10.3138/ptc.2011-53

Oncology Rehabilitation Provision and Practice Patterns across Canada

2012· article· en· W2006000849 on OpenAlexaffvenueabout
Alyssa Canestraro, Anthony Nakhle, Malissa Stack, Kelly C. Strong, Ashley Wright, Marla Beauchamp, Katherine Berg, Dina Brooks

Bibliographic record

VenuePhysiotherapy Canada · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRehabilitationMedicineSurvivorship curveIntervention (counseling)Rehabilitation counselingMultidisciplinary approachFamily medicineOccupational therapyNursingPhysical therapyCancerInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: Rehabilitation is increasingly recognized as an important therapeutic intervention for people with cancer. The main objective of this study was to explore the current practice pattern and provision of oncology rehabilitation in Canada. METHODS: A descriptive cross-sectional online survey was administered to Canadian facilities offering cancer treatment and/or listed as offering rehabilitation services during or after cancer treatment (cancer centres, rehabilitation hospitals, community centres, and private clinics). RESULTS: Of the 116 sites contacted, 62 completed the questionnaire, 20 of which reported having an oncology rehabilitation programme. The majority of respondents indicated that they are not meeting their clients' rehabilitation needs. Rehabilitation programmes were provided by multidisciplinary health care teams, the majority of which included a physiotherapist. Funding and availability of resources were identified as the main barriers to the development of oncology rehabilitation programmes. CONCLUSIONS: Formal oncology rehabilitation programmes appear to be scarce, despite growing evidence that rehabilitation offers benefits across the cancer survivorship continuum.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.343
Teacher spread0.333 · 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 designNot applicable
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

Citations52
Published2012
Admission routes3
Has abstractyes

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