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Record W2773112480 · doi:10.1177/1043454217741875

The Impact of a Childhood Cancer Diagnosis on the Children and Siblings’ School Attendance, Performance, and Activities: A Qualitative Descriptive Study

2017· article· en· W2773112480 on OpenAlexafffund
Argerie Tsimicalis, Laurence Genest, Bonnie Stevens, Wendy J. Ungar, Ronald D. Barr

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2017
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster UniversityUniversity of TorontoPediatric Oncology GroupMcGill UniversityHospital for Sick ChildrenShriners Hospitals for Children - Canada
FundersCanadian Institutes of Health Research
KeywordsChildhood cancerAttendanceDescriptive researchMedicinePsychologyCancerFamily medicinePediatricsInternal medicineSociology

Abstract

fetched live from OpenAlex

Families of children with cancer are confronted with unexpected out-of-pocket expenses and productivity costs associated with the diagnosis. One productivity cost that falls on children is the impact of cancer on children's school attendance, performance, and activities (eg, play, friendships, and socialization). Nested within the Childhood Cancer Cost Study, this qualitative descriptive study used convenience sampling to recruit and interview parents of children newly diagnosed with cancer. Content analysis techniques were used to inductively descriptive the semistructured interview data. Sixty-six parents of 65 children with cancer and of 73 siblings participated. The most commonly reported productivity loss in children with cancer was school absenteeism mainly due to cancer treatment. Children fell behind their classmates academically and lost important social time with peers. A few siblings also fell behind their peers primarily due to limited parental attention. Parents adopted various strategies to lessen the impact of the diagnosis on their children's school attendance, performance, and activities. Providing parents with additional resources and support may optimize their children's academic and social reintegration into school.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.061
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.050
GPT teacher head0.427
Teacher spread0.377 · 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

Citations68
Published2017
Admission routes2
Has abstractyes

Explore more

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