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Feeling States

2008· article· en· W2011399624 on OpenAlexaff
Roberta L. Woodgate

Bibliographic record

VenueCancer Nursing · 2008
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of ManitobaCanadian Cancer Society
Fundersnot available
KeywordsFeelingMedicineQualitative researchCancerQuality of life (healthcare)PsychotherapistPsychologyDevelopmental psychologyNursingSocial psychology

Abstract

fetched live from OpenAlex

Children with cancer experience short- and long-term symptoms. The symptoms can escalate child and family suffering and impact on their quality of life. Children's perspectives of their cancer symptoms have been increasingly investigated; however, there is still much more to be learned from children with cancer. Accordingly, a qualitative study that sought to arrive at an interpretive description of children's and adolescent's perspectives about their cancer symptoms was conducted, with a focus on exploring what children and adolescents with cancer think and feel about their cancer symptoms. Open-ended individual interviews were conducted with 13 children and adolescents with cancer. The patients ranged in age between 9 and 17 years. Data were analyzed by the constant comparative method of data analysis. Five themes emerged from the data: (1) It is all together, (2) Shared and unique ways of feeling, (3) I am feeling this way because..., (4) Feelings about my feelings, and (5) It is hard to explain. The findings reinforce that children have a lot to tell us about how cancer makes them feel but may have difficulty communicating how they feel to nurses and other healthcare providers.

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)0.000
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 score0.304
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.057
GPT teacher head0.366
Teacher spread0.309 · 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

Citations80
Published2008
Admission routes1
Has abstractyes

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