ArticleCanadian family physician Medecin de famille canadien2019
Chronic disease prevention and management programs in primary care: Realist synthesis of 6 programs in Quebec.
Article in Canadian family physician Medecin de famille canadien, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Methods of Engaging Interest-Holders in Healthcare Evidence Syntheses: A Scoping Review.Cochrane evidence synthesis and methods · 2026Review
- Nursing Intervention to Improve Positive Mental Health and Self-Care Skills in People with Chronic Physical Health Conditions.International journal of environmental research and public health · 2022Article
- The challenges facing programs for the prevention and control of non-communicable diseases in Iran: a qualitative study of senior managers' viewpoints.BMC health services research · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo identify the mechanisms associated with success and failure of chronic disease prevention and management (CDPM) programs, as well as their key contexts.
designRealist synthesis.
settingSix primary care CDPM programs funded between 2011 and 2013 in Quebec.
participantsPatients, health providers, program leaders, and other stakeholders involved in CDPM programs.
methodsA collaborative research process was implemented, involving representatives from the executive and advisory committees: researchers, health care providers, decision makers, and patients and families. Leaders were asked to provide all documents related to their programs to the research team. The documents were selected depending on their relevance and rigour. The thematic analysis of each program consisted of identifying the outcomes and mechanisms, as well as the specific contexts associated with these outcomes. Results for each program were validated by its leader before synthesizing the results of all programs together. MAIN
findingsA total of 108 documents (eg, grant applications, scientific reports) were collected from the programs. Positive and negative outcomes were observed at the patient, health care provider, and health care system levels. Four main mechanism categories were associated with outcomes: patient-centred interdisciplinary care; self-management support and a motivational approach; professional support; and care coordination and relationships with partners. The main contextual factors that influenced the successes of these mechanisms were related to patients (multimorbidity, involvement of family caregivers), to health care providers (professional training, culture of interprofessional collaboration, mobilization of family physician), and to health care organizations (coordination between services, history of collaboration between partners, funding).
conclusionThis study confirms the essential role of patient-centred interdisciplinary care; self-management support and a motivational approach; professional support; and care coordination and relationships with partners when caring for patients with chronic diseases. It constitutes a relevant contribution for stakeholders involved in primary care transformation and should be used to inform the sustainability and scaling up of CDPM programs.
Indexed as
Identifiers
31413028PMC6693614What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.