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Record W2090227074 · doi:10.1038/bjc.2014.445

Refinement of the Symptom Screening in Pediatrics Tool (SSPedi)

2014· article· en· W2090227074 on OpenAlexaff
Cróchán J. O’Sullivan, L. Lee Dupuis, Paul Gibson, Donna L. Johnston, Christina Baggott, Carol Portwine, Brenda J. Spiegler, Susan Kuczynski, Deborah Tomlinson, Sophie de Mol Van Otterloo, George Tomlinson, Lillian Sung

Bibliographic record

VenueBritish Journal of Cancer · 2014
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsOntario Institute for Cancer ResearchHealth Sciences CentreLondon Health Sciences CentreMcMaster Children's HospitalInstitute for Clinical Evaluative SciencesChildren's Hospital of Eastern OntarioToronto General HospitalSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineCognitionPediatricsFamily medicinePediatric cancerMEDLINECancerPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Objective was to evaluate and refine a new instrument for paediatric cancer symptom screening named the Symptom Screening in Pediatrics Tool (SSPedi). METHODS: Respondents were children 8-18 years of age undergoing active cancer treatment and parents of eligible children. Respondents completed SSPedi once and then responded to semi-structured questions. They rated how easy or difficult SSPedi was to complete. For items containing two concepts, we asked respondents whether concepts should remain together or be separated into two questions. We also asked about each item's importance and whether items were missing. Cognitive probing was conducted in children to evaluate their understanding of items and the response scale. After each group of 10 children and 10 parents, responses were reviewed to determine whether modifications were required. Recruitment ceased with the first group of 10 children in which modifications were not required. RESULTS: Thirty children and 20 parents were required to achieve a final version of SSPedi. Fifteen items remain in the final version; the score ranges from 0 to 60. CONCLUSIONS: Using opinions of children with cancer and parents of paediatric cancer patients, we successfully developed a symptom screening tool that is easy to complete, is understandable and demonstrates content validity.

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)0.001
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 score0.285
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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

Citations60
Published2014
Admission routes1
Has abstractyes

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