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Record W2761834452 · doi:10.4103/ijpc.ijpc_63_17

The psychometric properties and factor structure of persian version of edmonton symptom assessment scale in cancer patients

2017· article· en· W2761834452 on OpenAlexaboutno aff
Mehdi Heidarzadeh, Younes Khalili-Parapary, Naser Mozaffari, Parisa Naseri

Bibliographic record

VenueIndian Journal of Palliative Care · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCronbach's alphaConstruct validityDiscriminant validityConfirmatory factor analysisClinical psychologyPersianContent validityScale (ratio)Face validityReliability (semiconductor)PsychometricsStatisticsInternal consistencyStructural equation modelingMathematics

Abstract

fetched live from OpenAlex

CONTEXT: Edmonton Symptom Assessment Scale (ESAS) was developed to assess objective and subjective symptoms in patients with cancer in all stages of their disease. AIM: The aim of the study was to translate and determine the psychometric properties of ESAS in an Iranian population. MATERIALS AND METHODS: The current study was carried out to determine reliability and validity of ESAS using 246 patients with cancer in Imam Khomeini Hospital, Ardabil, Iran. After translating the instrument to Persian, content and face validity, discriminant validity, internal consistency, and test-retest were done to determine psychometric properties of ESAS. Furthermore, the construct validity was determined using confirmatory factor analysis to evaluate factor structure of the tool in two models: single factor and three factor. RESULTS: < 0001). CONCLUSIONS: This study showed that Persian version of ESAS with same factor structure mentioned in the original version is an applicable tool for assessing objective and subjective symptoms in Iranian patients 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)0.000
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 score0.012
Threshold uncertainty score0.244

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 head0.029
GPT teacher head0.326
Teacher spread0.298 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

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