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Record W4409666669 · doi:10.35568/healthcare.v7i1.5753

Implementation of Telenursing on The Behavior of Type 2 Diabetic Foot Care

2025· article· en· W4409666669 on OpenAlexaff
Ade Iwan Mutiudin, Siti Jundiah, Nur Intan Husnul Khatimah, Yani Maryani, Natasya Aulia Putri, Siti Amara Davaina

Bibliographic record

VenueHealthcare Nursing Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsDiabetic footFoot (prosody)Foot careMedicineNursingDiabetes mellitusEndocrinologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Diabetes is one of the health emergencies that require serious treatment. Diabetic foot complications have an impact on the quality of life and have the potential to threaten the lives of sufferers. Telenursing intervention programs have a lot of influence in improving health. However, there has been no research that proves that this method can have a positive impact on foot care behavior. The purpose of this study was to analyze the implementation of telenursing on foot care behavior. The research design used pre-experimental, with a one group pre-test - post-test design. 23 samples were obtained through purposive sampling techniques. The instrument used was Foot Self-Care (DFSQ-UMA). Data normality test using Shapiro - Wilk, and paired sample t-test. The results of the statistical test showed a p-value of 0.001 (p <0.05), which means that telenursing interventions are effective in improving foot care behavior. Telenursing programs need to be implemented in communities and various health facilities by involving families as an innovative solution for foot care education for diabetes mellitus patients.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.199

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 head0.033
GPT teacher head0.410
Teacher spread0.378 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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