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Record W2982181961 · doi:10.1186/s40814-019-0504-8

Pilot randomized controlled trial of a complex intervention for diabetes self-management supported by volunteers, technology, and interprofessional primary health care teams

2019· article· en· W2982181961 on OpenAlexafffund
Gina Agarwal, Jessica Gaber, Julie Richardson, Dee Mangin, Jenny Ploeg, Ruta Valaitis, Graham J. Reid, Larkin Lamarche, Fiona Parascandalo, Dena Javadi, Daria O’Reilly, Lisa Dolovich

Bibliographic record

VenuePilot and Feasibility Studies · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsWestern UniversityHamilton Health SciencesMcMaster UniversityImpactHealth Sciences Centre
FundersHealth CanadaOntario Ministry of Health and Long-Term CareMcMaster UniversityChildren's Health Research Institute
KeywordsMedicineReferralRandomized controlled trialeHealthIntervention (counseling)NursingFamily medicineHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: Most health care for people with diabetes occurs in family practice, yet balancing the time and resources to help these patients can be difficult. An intervention empowering patients, leveraging community resources, and assisting self-management could benefit patients and providers. Thus, the feasibility and potential for effectiveness of "Health Teams Advancing Patient Experience, Strengthening Quality through Health Connectors for Diabetes Management" (Health TAPESTRY-HC-DM) as an approach supporting diabetes self-management was explored to inform development of a future large-scale trial. METHODS: Four-month pilot randomized controlled trial (RCT), sequential explanatory qualitative component. Participants-patients of an interprofessional primary care team-were over age 18 years, diagnosed with diabetes and hypertension, and had Internet access and one of the following: uncontrolled HbA1c, recent diabetes diagnosis, end-stage/secondary organ damage, or provider referral. The Health TAPESTRY-HC-DM intervention focused on patient health goals/needs, integrating community volunteers, eHealth technologies, interprofessional primary care teams, and system navigation. Pilot outcomes included process measures (recruitment, retention, program participation), perceived program feasibility, benefits and areas for improvement, and risks or safety issues. The primary trial outcome was self-efficacy for managing diabetes. There were a number of secondary trial outcomes. RESULTS: = 20) met 28 clients in 234 client encounters (home visits, phone calls, electronic messages); 27 reports were sent to the interprofessional team. At 4 months, controlling for baseline, most outcomes were better in the intervention compared to control group; physical activity notably better. The most common goal domains set were physical activity, diet/nutrition, and social connection. Clients felt the biggest impact was motivation toward goal achievement. They struggled with some of the technologies. Several participants perceived that the program was not a good fit, mostly those that felt they were already well-managing their diabetes. CONCLUSIONS: Health TAPESTRY-HC-DM was feasible; a large-scale randomized controlled trial seems possible. However, further attention needs to be paid to improving recruitment and retention. The intervention was well received, though was a better fit for some participants than others. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02715791. Registered 22 March 2016-retrospectively registered.

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)0.011
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0160.002

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 head0.039
GPT teacher head0.360
Teacher spread0.321 · 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
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

Citations30
Published2019
Admission routes2
Has abstractyes

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