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Record W4367592802 · doi:10.2196/40000

A Nurse-Led Telehealth Program for Diabetes Foot Care: Feasibility and Usability Study

2023· article· en· W4367592802 on OpenAlexvenueno aff
Hsiao-Hui Ju, Rashmi Momin, Stanley G. Cron, Jed Jularbal, Jeffery Alford, Constance Johnson

Bibliographic record

VenueJMIR Nursing · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsTelehealthUsabilityMedicineFoot (prosody)TelemedicineDiabetes mellitusPhysical therapyVideoconferencingHealth careNursingFamily medicineMultimedia

Abstract

fetched live from OpenAlex

BACKGROUND: Diabetes mellitus can lead to severe and debilitating foot complications, such as infections, ulcerations, and amputations. Despite substantial progress in diabetes care, foot disease remains a major challenge in managing this chronic condition that causes serious health complications worldwide. OBJECTIVE: The primary aim of this study was to examine the feasibility and usability of a telehealth program focused on preventive diabetes foot care. A secondary aim was to descriptively measure self-reported changes in diabetes knowledge, self-care, and foot care behaviors before and after participating in the program. METHODS: The study used a single-arm, pre-post design in 2 large family medical practice clinics in Texas. Participants met individually with the nurse practitioner once a month for 3 months using synchronous telehealth videoconferencing. Each participant received diabetes foot education guided by the Integrated Theory of Health Behavior Change. Feasibility was measured with rates of enrollment and program and assessment completion. Usability was measured with the Telehealth Usability Questionnaire. Diabetes knowledge, self-care, and foot care behaviors were measured with validated survey instruments at baseline, 1.5 months, and 3 months. RESULTS: Of 50 eligible individuals, 39 (78%) enrolled; 34 of 39 (87%) completed the first videoconference and 29 of 39 (74%) completed the second and third videoconferences. Of the 39 who consented, 37 (95%) completed the baseline assessment; 50% (17/34) of those who attended the first videoconference completed the assessment at 1.5 months, and 100% (29/29) of those who attended the subsequent videoconferences completed the final assessment. Overall, participants reported a positive attitude toward the use of telehealth, with a mean Telehealth Usability Questionnaire score of 6.24 (SD 0.98) on a 7-point scale. Diabetes knowledge increased by a mean of 15.82 (SD 16.69) points of 100 (P<.001) from baseline to 3 months. The values for the Summary of Diabetes Self-Care Activities measure demonstrated better self-care, with participants performing foot care on average 1.74 (SD 2.04) more days per week (P<.001), adhering to healthy eating habits on average 1.57 (SD 2.12) more days per week (P<.001), and being physically active on average 1.24 (SD 2.21) more days per week (P=.005). Participants also reported an improvement in the frequency of foot self-examinations and general foot care behaviors. The mean scores for foot care increased by a mean of 7.65 (SD 7.04) points (scale of 7 to 35) from baseline to 3 months postintervention (P<.001). CONCLUSIONS: This study demonstrates that a nurse-led telehealth educational program centered on diabetes foot care is feasible, acceptable, and has the potential to improve diabetes knowledge and self-care, which are precursors to preventing debilitating foot complications.

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)0.008
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.399
Teacher spread0.364 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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