ArticleBMJ open2020
Study protocol for the road to hierarchical diabetes management at primary care (ROADMAP) study in China: a cluster randomised controlled trial.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Mobile phone-based interventions for improving adherence to medication prescribed for the primary prevention of cardiovascular disease in adults.The Cochrane database of systematic reviews · 2021Pooled it
- Evaluation of an mHealth-enabled hierarchical diabetes management intervention in primary care in China (ROADMAP): A cluster randomized trial.PLoS medicine · 2021Trial
- Article
- The Key Digital Tool Features of Complex Telehealth Interventions Used for Type 2 Diabetes Self-Management and Monitoring With Health Professional Involvement: Scoping Review.JMIR medical informatics · 2024Article
- The Impact of Triangle Hierarchical Management on Self-Management Behavior and Quality of Survival in Parkinson's Patients.Frontiers in surgery · 2022Article
- Bypassing primary care facilities: health-seeking behavior of middle age and older adults in China.BMC health services research · 2021Article
- Road to Hierarchical Diabetes Management at Primary Care (ROADMAP) Study in China: Protocol for the Statistical Analysis of a Cluster Randomized Controlled Trial.JMIR research protocols · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionDiabetes management in primary care remains suboptimal in China, despite its inclusion in the essential public health service (EPHS). We aimed to evaluate the effectiveness of a mobile health (mHealth) based and three-tiered diabetes management system in diverse Chinese contexts. METHODS AND ANALYSIS: This is a cluster randomised controlled trial, named road to hierarchical diabetes management at primary care (ROADMAP). 19 008 patients with type 2 diabetes (T2D) were recruited from primary care clinics in 864 communities across 144 counties/districts of 24 provinces. Eligible participants were adult patients diagnosed with T2D and registered for diabetes management in communities. Patients within the same communities (clusters) were randomly allocated into the intervention or control arm for 1 year in a 2:1 ratio. The control arm patients received usual care as EPHS packaged: at least four blood glucose (BG) and blood pressure (BP) tests, and lifestyle and medication instruction, yearly, from primary care providers. The intervention arm patients received at least two BG and one BP tests, monthly, and lifestyle and treatment instruction from a three-tiered contracted team. A mHealth platform, ETHICS AND DISSEMINATION: The trial has been approved by the Institutional Review Board at Shanghai Sixth People's Hospital. Findings on the intervention effectiveness will be disseminated through peer-reviewed journals, conference presentations and other relevant mechanisms. TRIAL REGISTRATION NUMBER: ChiCTR-IOC-17011325.
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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.