MétaCan
Menu
Back to cohort
Record W2119595194 · doi:10.5737/1181912x2312834

A Canadian online survey of oncology nurses’ perspectives on the management of breakthrough pain in cancer (BTPc)

2013· article· en· W2119595194 on OpenAlexaffvenueabout
Margaret I. Fitch, Alison McAndrew, Stephanie Burlein‐Hall

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsHydromorphoneMedicineCancer painOxycodonePain managementConcordanceSwallowingFentanylModalitiesOncology nursingOpioidFamily medicineCancerNursingOncologyInternal medicinePhysical therapyAnesthesiaNurse educationSurgery

Abstract

fetched live from OpenAlex

This paper explores Canadian oncology nurses' perception of management of breakthrough pain in cancer (BTPc). An online questionnaire was distributed to 668 oncology nurses across Canada, and 201 participated. More nurses reported that patients used hydromorphone (99.5%), morphine (97.0%), codeine (88.1%), or oxycodone (88.1%) for BTPc, than fentanyl preparations (64.7%). Problems with opioid administration reported by nurses included failure to work quickly enough (35.7%), difficulty swallowing (16.6%), need for caregiver assistance (13.2%), mouth sores (12.6%) and dry mouth (11.5%). Although most nurses discussed BTPc management with their patients, the vast majority (72.2%) were not very satisfied with current treatment modalities. Effective dialogue with patients and access to educational resources/tools may help optimize therapy and enhance concordance with BTPc medications.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.355
Teacher spread0.313 · 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.

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

Citations6
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Oncology Nursing JournalSame topicPain Management and Opioid UseFrench-language works237,207