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Record W4229504917 · doi:10.1177/104345420201900607

The Development of an Off-Therapy Needs Questionnaire and Protocol for Survivors of Childhood Cancer

2002· article· en· W4229504917 on OpenAlexaff
Kim Nagel, Marilyn Eves, Linda Waterhouse, Cheryl Alyman, Susan Posgate, Janet R. Jamieson, V. Metzger, Marilyn Wright

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2002
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster Children's Hospital
Fundersnot available
KeywordsCohortProtocol (science)AnxietyFamily medicineMedicineChildhood cancerPsychologyCancerNursingPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

The purpose of this project was to obtain input from the families of survivors of childhood cancer regarding their needs surrounding the "coming off treatment" (COT) period. A questionnaire was developed to record their needs, their wishes, and their satisfaction surrounding this period of time. Closer examination of the time surrounding COT was undertaken in an attempt to enhance this area of service for patients and families in our clinic setting. Establishing a structured protocol is likely to alleviate some of the anxiety that surrounds this time for families and help us to provide better continuity of care. After identifying a cohort of patients and families, the reason for the survey was explained and they were asked to complete the questionnaire before they left the clinic setting. At the completion of the study, 82% of the cohort had been approached, and 100% of this group had completed the survey (n = 41). Less than 50% of participants felt they had had a formal "coming off treatment" review but, of that same group, 89% were satisfied with the process. Participants identified areas of importance and health care professionals who they would like involved in the COT process. After reviewing the responses to the questionnaires, the decision was made to proceed in preparing a COT protocol.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.053
GPT teacher head0.398
Teacher spread0.345 · 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

Citations11
Published2002
Admission routes1
Has abstractyes

Explore more

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