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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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 score0.023
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.017
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