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Record W2794699375 · doi:10.1177/1043454218764889

A Standardized Education Checklist for Parents of Children Newly Diagnosed With Cancer: A Report From the Children’s Oncology Group

2018· article· en· W2794699375 on OpenAlexaff
Cheryl Rodgers, Vanessa Bertini, Mary Ashe Conway, Ashley Crosty, Angela Filice, Ruth Anne Herring, Julie Isbell, E. Anne Lown, Kristina Miller, Margaret Perry, Paula Sanborn, Nicole Spreen, Nancy Tena, Cindi Winkle, Joan Darling, Abigail Slaven, Jeneane Sullivan, Kathryn Tomlinson, Kate Windt, Marilyn Hockenberry, Wendy Landier

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster Children's HospitalStollery Children's Hospital
FundersNational Cancer Institute
KeywordsChecklistPediatric oncologyMedicineNursingFamily medicineSet (abstract data type)CancerMedical educationPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Parents of children newly diagnosed with cancer must acquire new knowledge and skills in order to safely care for their child at home. Institutional variation exists in the methods and content used by nurses in providing the initial education. The goal of this project was to develop a checklist, standardized across institutions, to guide nursing education provided to parents of children newly diagnosed with cancer. A team of 21 members (19 nurses and 2 parent advocates) used current hospital educational checklists, expert consensus recommendations, and a series of iterative activities and discussions to develop one standardized checklist. The final checklist specifies primary topics that are essential to teach prior to the initial hospital discharge, secondary topics that should be discussed within the first month after the cancer diagnosis, and tertiary topics that should be discussed prior to completion of therapy. This checklist is designed to guide education and will set the stage for future studies to identify effective teaching strategies that optimize the educational process for parents of children newly diagnosed with 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 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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.158
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.375
Teacher spread0.355 · 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 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

Citations36
Published2018
Admission routes1
Has abstractyes

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