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Record W2910130934 · doi:10.1002/nop2.236

A survey on patients' characteristics, perception of family support and diabetes self‐management among type 2 diabetes patients in South‐West Nigeria

2019· article· en· W2910130934 on OpenAlexfundno aff
Lucia Yetunde Ojewale, Abimbola Oluwatosin, Adesoji Adedipe Fasanmade, Olatunde Odusan

Bibliographic record

VenueNursing Open · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
FundersAfrican Population and Health Research CenterInternational Development Research Centre
KeywordsDiabetes mellitusPerceptionMedicineFamily supportCross-sectional studyDiabetes managementType 2 diabetesFamily historyResearch designGerontologyDemographyFamily medicineClinical psychologyPsychologyPhysical therapyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

AIM: To determine the association between patients' characteristics, perception of family support and diabetes self-management (DSM) behaviours among type 2 diabetes patients. DESIGN: A descriptive cross-sectional design was used and data were collected between July-September 2016. The study is part of a larger quasi-experimental study. METHODS: One hundred and ninety-seven diabetes mellitus (DM) patients from two teaching hospitals in south-west Nigeria participated. Questionnaire was used in collecting information on sociodemographic, clinical data, DSM and perception of family support. RESULTS: : 11.3) years and 11.7% had had DM for over 20 years. Overall, DSM was positively influenced by previous diabetes education and duration of diabetes. Perception of family support was also positively associated with and influenced DSM.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.273
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 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

Citations22
Published2019
Admission routes1
Has abstractyes

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