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Record W2587640535 · doi:10.1186/s13063-017-1795-9

The ACHRU-CPP versus usual care for older adults with type-2 diabetes and multiple chronic conditions and their family caregivers: study protocol for a randomized controlled trial

2017· article· en· W2587640535 on OpenAlexafffundabout
Maureen Markle‐Reid, Jenny Ploeg, Kimberly D. Fraser, Kathryn Fisher, Noori Akhtar‐Danesh, Amy Bartholomew, Amiram Gafni, Andrea Gruneir, Sandra P. Hirst, Sharon Kaasalainen, Caralyn Kelly Stradiotto, John Miklavcic, Carlos Rojas‐Fernandez, Cheryl A Sadowski, Lehana Thabane, Jean Triscott, Ross Upshur

Bibliographic record

VenueTrials · 2017
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsUniversity of TorontoSt. Joseph’s Healthcare HamiltonUniversity of CalgaryUniversity of AlbertaWaterloo CFD Engineering ConsultingMcMaster University
FundersCanadian Institutes of Health ResearchCanada Research ChairsOntario Ministry of Health and Long-Term CareMcMaster University
KeywordsMedicineRandomized controlled trialFamily medicineGeneral partnershipMental healthNursingGerontologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Many community-based self-management programs have been developed for older adults with type-2 diabetes mellitus (T2DM), bolstered by evidence from randomized controlled trials (RCTs) that T2DM can be prevented and managed through lifestyle modifications. However, the evidence for their effectiveness is contradictory and weakened by reliance on single-group designs and/or small samples. Additionally, older adults with multiple chronic conditions (MCC) are often excluded because of recruiting and retention challenges. This paper presents a protocol for a two-armed, multisite, pragmatic, mixed-methods RCT examining the effectiveness and implementation of the Aging, Community and Health Research Unit-Community Partnership Program (ACHRU-CPP), a new 6-month interprofessional, nurse-led program to promote self-management in older adults (aged 65 years or older) with T2DM and MCC and support their caregivers (including family and friends). METHODS/DESIGN: The study will enroll 160 participants in two Canadian provinces, Ontario and Alberta. Participants will be randomly assigned to the control (usual care) or program study arm. The program will be delivered by registered nurses (RNs) and registered dietitians (RDs) from participating diabetes education centers (Ontario) or primary care networks (Alberta) and program coordinators from partnering community-based organizations. The 6-month program includes three in-home visits, monthly group sessions, monthly team meetings for providers, and nurse-led care coordination. The primary outcome is the change in physical functioning as measured by the Physical Component Summary (PCS-12) score from the short form-12v2 health survey (SF-12). Secondary client outcomes include changes in mental functioning, depressive symptoms, anxiety, and self-efficacy. Caregiver outcomes include health-related quality of life and depressive symptoms. The study includes a comparison of health care service costs for the intervention and control groups, and a subgroup analysis to determine which clients benefit the most from the program. Descriptive and qualitative data will be collected to examine implementation of the program and effects on interprofessional/team collaboration. DISCUSSION: This study will provide evidence of the effectiveness of a community-based self-management program for a complex target population. By studying both implementation and effectiveness, we hope to improve the uptake of the program within the existing community-based structures, and reduce the research-to-practice gap. TRIAL REGISTRATION: ClinicalTrials.gov, Identifier: NCT02158741 . Registered on 3 June 2014.

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)0.050
metaresearch head score (Gemma)0.053
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 score0.085
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.053
Meta-epidemiology (narrow)0.0100.006
Meta-epidemiology (broad)0.0210.010
Bibliometrics0.0050.007
Science and technology studies0.0060.006
Scholarly communication0.0090.007
Open science0.0060.003
Research integrity0.0120.013
Insufficient payload (model declined to judge)0.0850.014

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 head0.064
GPT teacher head0.395
Teacher spread0.331 · 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

Citations14
Published2017
Admission routes3
Has abstractyes

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