ArticleClinical and translational science2015
Team Science Approach to Developing Consensus on Research Good Practices for Practice-Based Research Networks: A Case Study.
Article in Clinical and translational science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
- Design and implementation of the participatory German network for translational dementia care research (TaNDem): A mixed-method study on the perspectives of healthcare providers and dementia researchers in dementia care research.Health expectations : an international journal of public participation in health care and health policy · 2023Review
- Strategies for working across Canadian practice-based research and learning networks (PBRLNs) in primary care: focus on frailty.BMC family practice · 2021Article
- Establishing family physician research networks in South Africa.South African family practice : official journal of the South African Academy of Family Practice/Primary Care · 2020Article
- Managing different intellectual personalities in scientific teams.Journal of clinical and translational science · 2019Article
- Prevention of central nervous system sequelae in sickle cell disease without evidence from randomized controlled trials: the case for a team-based learning collaborative.Hematology. American Society of Hematology. Education Program · 2016Article
- Practice-based Research Networks (PBRNs) Bridging the Gaps between Communities, Funders, and Policymakers.Journal of the American Board of Family Medicine : JABFMArticle
- Practitioner Participation in National Dental Practice-based Research Network (PBRN) Studies: 12-Year Results.Journal of the American Board of Family Medicine : JABFMArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
Using peer learning strategies, seven experienced PBRNs working in collaborative teams articulated procedures for PBRN Research Good Practices (PRGPs). The PRGPs is a PBRN-specific resource to facilitate PBRN management and staff training, to promote adherence to study protocols, and to increase validity and generalizability of study findings. This paper describes the team science processes which culminated in the PRGPs. Skilled facilitators used team science strategies and methods from the Technology of Participation (ToP®), and the Consensus Workshop Method to support teams to codify diverse research expertise in practice-based research. The participatory nature of "sense-making" moved through identifiable stages. Lessons learned include (1) team input into the scope of the final outcome proved vital to project relevance; (2) PBRNs with diverse domains of research expertise contributed broad knowledge on each topic; and (3) ToP® structured facilitation techniques were critical for establishing trust and clarifying the "sense-making" process.
Indexed as
Identifiers
What 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.