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Record W2331125282 · doi:10.12968/ijpn.2016.22.3.111

Yoga as palliation in women with advanced cancer: a pilot study

2016· article· en· W2331125282 on OpenAlexaff
Tracey Carr, Elizabeth Quinlan, Susan J. Robertson, Wendy Duggleby, Roanne Thomas, Lorraine Holtslander

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2016
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of OttawaUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsMedicinePalliative careCancerFamily medicineGerontologyPhysical therapyNursingInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this pilot study was to investigate the palliative potential of home-based yoga sessions provided to women with advanced cancer. METHOD: Personalised 45-minute yoga sessions were offered to three women with advanced cancer by an experienced yoga teacher. Each woman took part in a one-to-one interview after the completion of the yoga programme and was asked to describe her experiences of the programme's impact. RESULTS: The personalised nature of the yoga sessions resulted in similar positive physical and psychosocial effects comparable to those demonstrated in other studies with cancer patients. Participants described physical, mental, and emotional benefits as well as the alleviation of illness impacts. The enhancement of mind-body and body-spirit connections were also noted. CONCLUSION: Personalised home-based yoga programmes for people with advanced cancer may produce similar benefits, including palliation, as those institutionally-based programmes for people with non-advanced cancer.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.418
Teacher spread0.368 · 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 designNon-randomized trial
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

Citations15
Published2016
Admission routes1
Has abstractyes

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