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Record W1979343768 · doi:10.1177/1043454207304907

Understanding the Supportive Care Needs of Parents of Children With Cancer: An Approach to Local Needs Assessment

2007· article· en· W1979343768 on OpenAlexaffabout
Laura Kerr, Margaret B. Harrison, Jennifer Medves, Joan Tranmer, Margaret I. Fitch

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2007
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsSunnybrook Health Science CentreQueen's University
Fundersnot available
KeywordsNeeds assessmentPerspective (graphical)Exploratory researchConceptual frameworkNursingSpecial needsPsychologyChildhood cancerMedicineCancerPsychiatry

Abstract

fetched live from OpenAlex

The objective of this study was to conduct an assessment of supportive care needs from the perspective of parents of children diagnosed with cancer within an urban-rural region in Eastern Ontario, Canada. Guided by a conceptual framework for supportive care, the exploratory, mixed-method study used a standard needs survey and semistructured interviews. Fifteen parents completed (75% response rate) the survey, and 3 parents participated as key informants in the follow-up interview. Parents reported needs in all 6 of the need categories outlined within the Supportive Care Needs Framework. The proportion of parents expressing a need ranged from 23% to 39%. Dealing with the fear of their child's cancer spreading was frequently identified by parents. Emotional and informational needs were the 2 most frequently acknowledged categories of need. With further refinement, the use of the conceptual framework will provide a methodology for planning care based on the individual needs identified by parents of children 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 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)0.005
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.063
GPT teacher head0.389
Teacher spread0.326 · 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

Citations88
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Pediatric Oncology NursingSame topicChildhood Cancer Survivors' Quality of LifeFrench-language works237,207