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Record W2065928745 · doi:10.1186/1472-6947-12-57

Designing and evaluating a web-based self-management site for patients with type 2 diabetes - systematic website development and study protocol

2012· article· en· W2065928745 on OpenAlexafffund
Catherine Yu, Janet Parsons, Muhammad Mamdani, Gerald Lebovic, Baiju R. Shah, Onil Bhattacharyya, Andreas Laupacis, Sharon E. Straus

Bibliographic record

VenueBMC Medical Informatics and Decision Making · 2012
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchCanadian Diabetes Association
KeywordsPsychological interventionSelf-managementUsabilityMedicineGlycemicHealth informaticsHealth careProtocol (science)Intervention (counseling)Intervention mappingNursingComputer sciencePublic healthHealth promotionDiabetes mellitusAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Given that patients provide the majority of their own diabetes care, patient self-management training has increasingly become recognized as an important strategy with which to improve quality of care. However, participation in self management programs is low. In addition, the efficacy of current behavioural interventions wanes over time, reducing the impact of self-management interventions on patient health. Web-based interventions have the potential to bridge the gaps in diabetes care and self-management. METHODS: Our objective is to improve self-efficacy, quality of life, self-care, blood pressure, cholesterol and glycemic control and promote exercise in people with type 2 diabetes through the rigorous development and use of a web-based patient self-management intervention. This study consists of five phases: (1) intervention development; (2) feasibility testing; (3) usability testing; (4) intervention refinement; and (5) intervention evaluation using mixed methods. We will employ evidence-based strategies and tools, using a theoretical framework of self-efficacy, then elicit user feedback through focus groups and individual user testing sessions. Using iterative redesign the intervention will be refined. Once finalized, the impact of the website on patient self-efficacy, quality of life, self-care, HbA1c, LDL-cholesterol, blood pressure and weight will be assessed through a non-randomized observational cohort study using repeated measures modeling and individual interviews. DISCUSSION: Increasing use of the World Wide Web by consumers for health information and ongoing revolutions in social media are strong indicators that users are primed to welcome a new era of technology in health care. However, their full potential is hindered by limited knowledge regarding their effectiveness, poor usability, and high attrition rates. Our development and research agenda aims to address these limitations by improving usability, identifying characteristics associated with website use and attrition, and developing strategies to sustain patient use in order to maximize clinical outcomes.

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)0.002
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 score0.673
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.037
GPT teacher head0.350
Teacher spread0.314 · 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

Citations43
Published2012
Admission routes2
Has abstractyes

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