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Record W1513723212 · doi:10.2196/resprot.2813

The OnTrack Diabetes Web-Based Program for Type 2 Diabetes and Dysphoria Self-Management: A Randomized Controlled Trial Protocol

2015· article· en· W1513723212 on OpenAlexvenueno aff
Mandy Cassimatis, David J. Kavanagh, Anthony C Smith, Paul Scuffham, Christian A. Gericke, Sophie Parham

Bibliographic record

VenueJMIR Research Protocols · 2015
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialType 2 diabetesGlycated hemoglobinGlycemicDistressPopulationDiabetes mellitusPsychological interventionDiabetes managementAnxietyPhysical therapyClinical psychologyNursingPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location OBJECTIVE: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. METHODS: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. RESULTS: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. CONCLUSIONS: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registration number: ACTRN12612000620820; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12612000620820 (Archived by WebCite at http://www.webcitation.org/6a3BeXC5m).

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)0.017
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.081
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.014
Meta-epidemiology (narrow)0.0060.002
Meta-epidemiology (broad)0.0110.004
Bibliometrics0.0030.003
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0810.010

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 head0.124
GPT teacher head0.510
Teacher spread0.386 · 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 designRandomized 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

Citations6
Published2015
Admission routes1
Has abstractyes

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