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Record W2973028609 · doi:10.1007/s13300-019-00687-y

Family Members: The Forgotten Players in the Diabetes Care Team (The TALK-HYPO Study)

2019· article· en· W2973028609 on OpenAlexaff
Alexandria Ratzki‐Leewing, Ehsan Parvaresh Rizi, Stewart B. Harris

Bibliographic record

VenueDiabetes Therapy · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsWestern University
FundersNovo Nordisk
KeywordsHypoglycemiaMedicineDiabetes mellitusType 1 diabetesFamily medicineType 2 diabetesHealth carePediatricsNursingEndocrinology

Abstract

fetched live from OpenAlex

INTRODUCTION: The objective of this study was to establish the burden of hypoglycemia on family members of people with diabetes (PWDs) and to gain an understanding of how conversations about hypoglycemia can contribute to diabetes care. METHODS: This was a multinational cross-sectional study of family members of people with type 1 or type 2 diabetes taking insulin and/or secretagogues for ≥ 12 months who voluntarily completed an online questionnaire. RESULTS: Overall, 4300 family members of PWDs (type 1 [29%], type 2 [46%], unknown [25%]) were surveyed. Two in three family members (66%) reported thinking about the hypoglycemia of the PWD at least monthly, and 64% felt worried or anxious about the PWD's risk for hypoglycemia. There was general agreement among family members that more conversations about hypoglycemia would have a positive impact on the PWD's life (76%). CONCLUSIONS: Hypoglycemia can present a burden on the lives of family members of PWDs. Conversations about hypoglycemia, facilitated by a healthcare professional, may reduce this burden and hypoglycemia risk. FUNDING: Novo Nordisk A/S.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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