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Record W4309465346 · doi:10.2196/43208

Development and Exploration of the Effectiveness and Feasibility of a Digital Intervention for Type 2 Diabetes Mellitus (DEsireD): Protocol for a Clinical Nonrandomized Pilot Trial in Brunei Darussalam

2022· article· en· W4309465346 on OpenAlexvenueno aff
Hiu Nam Chan, Hong Shen Lim, Pui Lin Chong, Chee Kwang Yung, Musjarena Abd Mulok, Wei Yuan, Alice Moi Ling Yong

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Type 2 Diabetes MellitusMedicineIntervention (counseling)Pilot trialClinical trialDigital healthDiabetes mellitusRandomized controlled trialPhysical therapyAlternative medicineHealth careNursingSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence of type 2 diabetes mellitus (T2DM) is increasing worldwide. Digital interventions that incorporate the use of mobile phones and wearables have been getting popular. A combination of a digital intervention with support from professional management can enhance users' self-efficacy better than a digital intervention alone and provide better accessibility to a lifestyle intervention. However, there are limited studies exploring the feasibility and efficacy of applying a digital intervention in Muslim-majority countries, and none have been conducted in Brunei Darussalam. OBJECTIVE: , BMI, lipid profile, and EQ-5D-5L score. METHODS: This single-arm nonrandomized pilot study will recruit participants using web-based (with the national health care app [BruHealth] and official social media platforms being used for outreach) and offline (in-person recruitment at health centers) approaches. A target of 180 individuals with T2DM aged between 20 and 70 years that meet the inclusion criteria will be enrolled in a 16-week digital intervention program. Baseline and postintervention markers will be evaluated. RESULTS: The study received approval from the Medical and Health Research & Ethics Committee of the Brunei Darussalam Ministry of Health (MHREC/MOH/2022/4(1)). The recruitment process is ongoing, and we anticipate that the study will conclude by April 2023. This will be followed by data analysis and the reporting of outcomes with the intention to publish. The results of this study will be disseminated through scientific publications and conferences. This study will serve as a guide to launch T2DM digital therapeutic programs and extend to other noncommunicable diseases (NCDs) if proven as an effective and feasible approach in Brunei. CONCLUSIONS: The Development and Exploration of the Effectiveness and Feasibility of a Digital Intervention for Type 2 Diabetes Mellitus (DEsireD) study will be the first study to investigate the clinical effectiveness and feasibility of the proposed 16-week T2DM digital intervention program tailored for Brunei, a Muslim-majority country. The findings of this study can potentially scale up the proposed model of care to other NCDs as a national approach for health management solutions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05364476; https://clinicaltrials.gov/ct2/show/NCT05364476. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43208.

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)0.036
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.048
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.024
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0020.002
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0480.009

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 head0.668
GPT teacher head0.684
Teacher spread0.015 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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

Citations4
Published2022
Admission routes1
Has abstractyes

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