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Record W4413566282 · doi:10.2196/63894

Assessing the Clinical Feasibility of the DiaFocus System for Integrated Personalized Management of Type 2 Diabetes: 6-Month Pilot Cohort Study

2025· article· en· W4413566282 on OpenAlexvenueno aff
Nanna Lind, Per Bækgaard, Jakob E. Bardram, Claus Lundgaard Cramer-Petersen, Kirsten Nørgaard, Merete B. Christensen

Bibliographic record

VenueJMIR Diabetes · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersDanmarks Tekniske UniversitetEuropean CommissionSteno Diabetes Center Copenhagen
KeywordsMedicinemHealthType 2 diabetesDiabetes managementDiabetes mellitusCompetence (human resources)Physical therapyFamily medicineNursingPsychological interventionPsychology

Abstract

fetched live from OpenAlex

Background: Type 2 diabetes (T2D) is a complex, chronic condition that requires ongoing management. An important aspect of effective diabetes management is shared decision-making between the person with diabetes and the health care professionals (HCPs) to tailor individual treatment plans. Personal health technologies can play a crucial role in this collaborative effort by providing tools for monitoring, communication, and education. Objective: This study aims to test the clinical feasibility of DiaFocus, a mobile health system developed for adults with T2D. Methods: This was a single-arm, prospective, 6-month pilot study in a clinical outpatient setting at Steno Diabetes Center Copenhagen, Denmark. The DiaFocus system includes an app for the participants and a web portal for the HCPs. The system collects diabetes-related data, including participant-reported lifestyle surveys, sensor-based measures on physical activity, and participant-selected focus areas, aiming to support communication and shared decision-making at clinical visits. Participants were eligible if they were ≥18 years old, diagnosed with T2D≥12 months, spoke Danish, and had a smartphone (iOS 13+ or Android 8.0+). For each participant, 3 visits and 1 telephone call were scheduled during the 6-month study period. The DiaFocus system's acceptability and feasibility were assessed through retention rates, app usage, participant feedback, and by the CACHET Unified Method for Assessment of Clinical Feasibility (CUMACF) questionnaire. The clinical outcomes were assessed by the following questionnaires: Diabetes Distress Scale (DDS), Perceived Competence for Diabetes (PCDS), Diabetes Treatment Satisfaction Questionnaire (DTSQs+c), hemoglobin A1c levels, and body weight. Results: A total of 17 participants with T2D were included in the study, 15 completed the study, and data were analyzed on an intention-to-treat basis. The median age was 68 (IQR 56-72) years, 12 (71%) were males, the median diabetes duration was 18 (IQR 11-21) years, and the median hemoglobin A1c was 59 (IQR 49-68) mmol/mol. Participants found the DiaFocus system feasible to support diabetes management despite technical problems, and they valued the ability to set focus areas. The most common focus areas were "blood glucose" (n=10, 59%) and "exercise" (n=9, 53%), but areas such as "sleep" and "mood" were also used. The CUMACF questionnaire showed that 90% (9/10) of the participants had very favorable views of how easy the system is to understand, learn, and use, and 80% (8/10) of the participants agreed or strongly agreed that the system was useful. Feedback was generally positive, indicating participants would use a refined version. Despite these findings, no statistically significant changes in clinical outcomes were observed throughout the study period using the DiaFocus system. Conclusions: This pilot study demonstrated that the DiaFocus system is clinically feasible and acceptable for users with T2D, although there is a need for optimization of app functionality and stability.

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)0.006
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 score0.008
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.120
GPT teacher head0.511
Teacher spread0.390 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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