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Record W1594258751 · doi:10.1093/pch/16.8.468

Complementary and alternative medicine use in children and adolescents with type 1 diabetes

2011· article· en· W1594258751 on OpenAlexaff
Jean-François Lemay, Aditi Amin, Danièle Pacaud

Bibliographic record

VenuePaediatrics & Child Health · 2011
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineType 1 diabetesDiabetes mellitusFamily medicineAlternative medicineCross-sectional studyPediatricsPatient satisfactionMetabolic control analysisSurgeryEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: The use of complementary and alternative medicine (CAM) in paediatric patients varies between 11% and 68%. There are limited reports of its use in children with type 1 diabetes mellitus (T1DM). OBJECTIVE: To describe the use of CAM in children with T1DM, and the perceptions of both users and nonusers regarding the effect of CAM on diabetes management. DESIGN/METHODS: A cross-sectional, anonymous questionnaire survey was mailed to a randomly selected subgroup of patients with T1DM. Each patient's main caregiver was asked to complete the questionnaire. RESULTS: Of 403 questionnaires mailed, 195 (48%) were completed. The mean (± SD) age of the children was 12.2±4.0 years (56% boys). Use of CAM was reported in 110 children (56%) (vitamins/minerals [n=99], herbal medicine [n=22], dietary supplement [n=13]). When excluding the use of vitamins/minerals, the CAM number dropped to 47 children (24%). Only the current age of the child was significantly different between users and nonusers of CAM. In users, reasons cited for using CAM were to minimize symptoms, improve control, prevent complications and add benefits to insulin. Only 30% of CAM users stated that CAM improved diabetes control. Nonusers cited satisfaction with current diabetes treatment and lack of knowledge as reasons for not using CAM. CONCLUSIONS: CAM use in children with T1DM was frequent, and appeared to be an attempt to improve control or prevent diabetes complications. However, improved control was not reported as a benefit. Diabetes care teams should assess the use of CAM in children with T1DM, and monitor for any potential positive or negative effects.

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 score0.005
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.300
Teacher spread0.257 · 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

Citations15
Published2011
Admission routes1
Has abstractyes

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