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Record W4362606532 · doi:10.1136/bmjopen-2022-068694

Older adults’ experiences and perceived impacts of the Aging, Community and Health Research Unit-Community Partnership Program (ACHRU-CPP) for diabetes self-management in Canada: a qualitative descriptive study

2023· article· en· W4362606532 on OpenAlexafffundabout
Marie‐Lee Yous, Rebecca Ganann, Jenny Ploeg, Maureen Markle‐Reid, Melissa Northwood, Kathryn Fisher, Ruta Valaitis, Tracey Chambers, William Montelpare, France Légaré, Ron Beleno, Gary Gaudet, Luisa Giacometti, Deborah Levely, Craig Lindsay, Allan J. Morrison, Frank Tang

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsUniversité LavalUniversity of Prince Edward IslandMcMaster University
FundersFonds de Recherche du Québec - SantéMcMaster Institute for Research on Aging, McMaster UniversityDiabetes Action Research and Education FoundationCanadian Institutes of Health ResearchMcMaster UniversityFonds de recherche du Québec
KeywordsMedicineGerontologyThematic analysisCommunity healthIntervention (counseling)Qualitative researchPublic healthDiabetes managementDescriptive statisticsChronic conditionNursingFamily medicineType 2 diabetesDiabetes mellitus

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the experiences and perceived impacts of the Aging, Community and Health Research Unit-Community Partnership Program (ACHRU-CPP) from the perspectives of older adults with diabetes and other chronic conditions. The ACHRU-CPP is a complex 6-month self-management evidence-based intervention for community-living older adults aged 65 years or older with type 1 or type 2 diabetes and at least one other chronic condition. It includes home and phone visits, care coordination, system navigation support, caregiver support and group wellness sessions delivered by a nurse, dietitian or nutritionist, and community programme coordinator. DESIGN: Qualitative descriptive design embedded within a randomised controlled trial was used. SETTING: Six trial sites offering primary care services from three Canadian provinces (ie, Ontario, Quebec and Prince Edward Island) were included. PARTICIPANTS: The sample was 45 community-living older adults aged 65 years or older with diabetes and at least one other chronic condition. METHODS: Participants completed semistructured postintervention interviews by phone in English or French. The analytical process followed Braun and Clarke's experiential thematic analysis framework. Patient partners informed study design and interpretation. RESULTS: The mean age of older adults was 71.7 years, and the mean length of time living with diabetes was 18.8 years. Older adults reported positive experiences with the ACHRU-CPP that supported diabetes self-management, such as improved knowledge in managing diabetes and other chronic conditions, enhanced physical activity and function, improved eating habits, and opportunities for socialisation. They reported being connected to community resources by the intervention team to address social determinants of health and support self-management. CONCLUSIONS: Older adults perceived that a 6-month person-centred intervention collaboratively delivered by a team of health and social care providers helped support chronic disease self-management. There is a need for providers to help older adults connect with available health and social services in the community. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov ID: NCT03664583; Results.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.400

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0080.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.420
GPT teacher head0.548
Teacher spread0.128 · 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 designQualitative
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

Citations12
Published2023
Admission routes3
Has abstractyes

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