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Record W2154148897 · doi:10.1177/1043454206291349

Children Receiving Chemotherapy at Home: Perceptions of Children and Parents

2006· article· en· W2154148897 on OpenAlexaff
Bonnie Stevens, Patricia McKeever, Madelyn Law, Marilyn Booth, Mark Greenberg, Stacey Daub, Amiram Gafni, Janet Gammon, Janet Yamada, Iris Epstein

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2006
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHome and Community Care Support ServicesSickKids FoundationHospital for Sick ChildrenMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsAttendanceMedicineExploratory researchChemotherapyPerceptionPreferenceQualitative researchPerspective (graphical)Family medicinePsychology

Abstract

fetched live from OpenAlex

The aim of this descriptive exploratory study was to determine the perspectives of parents and children with cancer on a home chemotherapy program. Qualitative analyses were used to organize data from 24 parents and 14 children into emerging themes. Themes included (1) financial and time costs, (2) disruption to daily routines, (3) psychological and physical effects, (4) recommendations and caveats, and (5) preference for home chemotherapy. When home chemotherapy was compared with hospital clinic-based chemotherapy, parents reported fewer financial and time costs and less disruption to their work and family schedules, and children reported more time to play/study, improved school attendance, and engagement in normal activities. Although some parents felt more secure with hospital chemotherapy, most found it more exhausting and stressful. At home, children selected places for their treatment and some experienced fewer side effects. Although some coordination/communication problems existed, the majority of parents and children preferred home chemo-therapy. Home chemotherapy treatment is a viable, acceptable, and positive health care delivery alternative from the perspective of parents and 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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.016
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.012
GPT teacher head0.323
Teacher spread0.312 · 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

Citations42
Published2006
Admission routes1
Has abstractyes

Explore more

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