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Record W3106290335 · doi:10.1136/bmjdrc-2020-001268

Diabetes knowledge, risk perception, and quality of life among South Asian caregivers in young adulthood

2020· article· en· W3106290335 on OpenAlexafffund
Angela Koipuram, Sandra Carroll, Zubin Punthakee, Diana Sherifali

Bibliographic record

VenueBMJ Open Diabetes Research & Care · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsMcMaster University
FundersMcMaster UniversityHamilton Health Sciences
KeywordsMedicineDiabetes mellitusQuality of life (healthcare)PerceptionGerontologyYoung adultSouth asiaEarly adulthoodNursingPsychologyEndocrinologyNeuroscience

Abstract

fetched live from OpenAlex

Introduction Persons of South Asian descent have a higher prevalence of type 2 diabetes mellitus (T2DM). The management of T2DM in the South Asian community has required the support of adult children, potentially impacting the quality of life, diabetes-related knowledge, and risk perception among these caregivers. Research design and methods To investigate diabetes-related knowledge, quality of life, risk perception, and actual risk of developing diabetes among South Asian young adults whose parents are living with T2DM. A cross-sectional study was conducted (n=150). An online survey was administered. Data were analyzed with descriptive and inferential statistics. Results There was a statistically significant difference in diabetes-related knowledge between males and females (p<0.001). Males (in comparison to females) had a lower risk perception of developing diabetes (p=0.06). Further, risk perception and diabetes-related knowledge were positively associated with caregiver’s physical health (p = 0.002). Conclusion Findings highlight the importance of providing gender-specific and culturally tailored diabetes educational interventions.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.090
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
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 science0.0010.001
Research integrity0.0000.001
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 head0.097
GPT teacher head0.420
Teacher spread0.323 · 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

Citations11
Published2020
Admission routes2
Has abstractyes

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