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Record W2897642551 · doi:10.4103/ijpc.ijpc_33_18

A comparison of symptom management for children with cancer in Iran and in the selected countries: A comparative study

2018· article· en· W2897642551 on OpenAlexaboutno aff
Shahram Baraz, Maryam Pakseresht, Maryam Rassouli, Nahid Rejeh, Shahnaz Rostami, Leila Khanali Mojen

Bibliographic record

VenueIndian Journal of Palliative Care · 2018
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative careMedicineFamily medicineSpecialtyDeveloping countryDeveloped countryService (business)NursingPopulationBusinessEnvironmental healthEconomic growth

Abstract

fetched live from OpenAlex

AIM: The aim of this study is to describe the experiences of other countries regarding the status of pediatric palliative care in the field of symptom management and to compare it with the current status in Iran to achieve an appropriate level of symptom management for children with cancer. MATERIALS AND METHODS: This is a comparative study. The research population includes the palliative care systems of Jordan, England, Australia, and Canada, which were ultimately compared with Iran's palliative care system. RESULTS: The results showed that in the leading countries in the field of palliative care, such as Australia and Canada, much effort has been made to improve palliative care and to expand its service coverage. In the UK, as a pioneer in the introduction of palliative care, a significant portion of clinical performance, education and research, is dedicated to childhood palliative care. Experts in this field and policymakers are also well aware of this fact. In developing countries, including Jordan, palliative care is considered a nascent specialty, facing many challenges. In Iran, there is still no plan for providing these services coherently even for adults. CONCLUSION: Children with cancer experience irritating symptoms during their lives and while they are hospitalized. Regarding the fact that symptom management in developed countries is carried out based on specific and documented guidelines, using the experiences of these successful countries and applying them as an operational model can be useful for developing countries such as Iran.

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 score0.119
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.054
GPT teacher head0.404
Teacher spread0.350 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

Explore more

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