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Record W1978972602 · doi:10.1191/0269216305pm1052oa

Validation of the McGill Quality of Life Questionnaire in home hospice settings in Israel

2005· article· en· W1978972602 on OpenAlexaboutno aff
Netta Bentur, Shirli Resnizky

Bibliographic record

VenuePalliative Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative careQuality of life (healthcare)MedicineMeaning (existential)HebrewExistentialismQuality (philosophy)PopulationGerontologyTest (biology)Reliability (semiconductor)NursingFamily medicinePsychologyPsychotherapistLinguisticsEnvironmental health

Abstract

fetched live from OpenAlex

Given that the meaning and significance of 'quality of life' can differ among language and cultural groups, it is incumbent upon researchers to assess whether the tool they have chosen is appropriate to the population under study. This study aimed to test the reliability and validity of the McGill Quality of Life Questionnaire (MQOL) translated into Hebrew for use with palliative care patients in Israel. In this, as in previous studies, the 16 questions of the tool clustered into four domains (physical, psychological, existential well-being and support), although the distribution of items among them differed somewhat. The existential well-being and psychological domains had an independent effect on the overall quality of life of patients in Israel, as in other countries. It seems that this tool produces similar responses in metastatic cancer patients around the world, and hence can be used to compare palliative care services in different countries.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.108
GPT teacher head0.424
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), 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

Citations27
Published2005
Admission routes1
Has abstractyes

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