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Record W2809779351 · doi:10.1188/18.onf.527-544

Children’s Experiences of Cancer Care: A Systematic Review and Thematic Synthesis of Qualitative Studies

2018· review· en· W2809779351 on OpenAlexaff
Lindsay Jibb, Lindsay Croal, Jingting Wang, Changrong Yuan, Joel Foster, Verna Cheung, Brenda Gladstone, Jennifer Stinson

Bibliographic record

VenueOncology nursing forum · 2018
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreHospital for Sick ChildrenUniversity of Ottawa
Fundersnot available
KeywordsMedicineQualitative researchThematic analysisRelevance (law)MEDLINESystematic reviewQuality of life (healthcare)Qualitative propertyFamily medicineNursing

Abstract

fetched live from OpenAlex

PROBLEM IDENTIFICATION: Improvements in pediatric cancer survival have increased interest in the experiences of children undergoing treatment; however, no review of the qualitative literature describing these experiences has been conducted. LITERATURE SEARCH: Databases were searched from January 2000 to January 2016 for qualitative studies describing the experience of children with cancer aged 18 years or younger. DATA EVALUATION: Two reviewers assessed abstracts for relevance and rated reporting comprehensiveness. Participant quotations and descriptions of participants' comments and behaviors were coded. Coded data were pooled to provide a thematic synthesis. SYNTHESIS: 51 studies were included. Five themes were identified. IMPLICATIONS FOR RESEARCH: Results provide data related to the experience of children with cancer that can inform practice changes and research activities aimed at enhancing quality of life.

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)0.054
metaresearch head score (Gemma)0.103
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.054
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.103
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0160.018
Science and technology studies0.0020.002
Scholarly communication0.0030.005
Open science0.0020.005
Research integrity0.0020.002
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 head0.118
GPT teacher head0.515
Teacher spread0.397 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations56
Published2018
Admission routes1
Has abstractyes

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