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Managing Children's Cancer Pain in Morocco

2004· article· en· W2151155535 on OpenAlexaff
Patricia McCarthy, Georgette Chammas, Judith A. Wilimas, F. Msefer Alaoui, Mohamed Harif

Bibliographic record

VenueJournal of Nursing Scholarship · 2004
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsCancer painMedicineCancerPsychologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To identify issues in managing pain of children with cancer in the two pediatric oncology centers in Morocco. METHODS: Focus groups were conducted with pediatric oncology nurses and physicians. FINDINGS: Four themes were identified: (a) children's cancer pain is an overwhelming concern to the Moroccan nurses and physicians who participated in this study; (b) training and resources for children's cancer pain management are lacking in Morocco; (c) some impediments to pain relief were verbalized, such as a stoic approach to suffering and limited use of some drugs; and (d) a critical need exists for a comprehensive pain management approach for children with cancer in Morocco. CONCLUSIONS: This study elucidated issues in managing children's cancer pain in Morocco and increased knowledge of current practice issues. A program of policy research has been initiated with the aim of establishing guidelines for practice policies for managing children's cancer pain in Morocco.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

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 studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.029
GPT teacher head0.345
Teacher spread0.316 · 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

Citations29
Published2004
Admission routes1
Has abstractyes

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