ArticleHealth expectations : an international journal of public participation in health care and health policy2025
Assessing the Quality of Community Jury Deliberations in Online and In-Person Community Juries Using a Deductive Coding Framework.
Article in Health expectations : an international journal of public participation in health care and health policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Assessing the Quality of Community Jury Deliberations in Online and In-Person Community Juries Using a Deductive Coding Framework.Health expectations : an international journal of public participation in health care and health policy · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
introductionCommunity juries require participants to engage in group deliberations, seeking to reach a consensus or verdict on the research question(s). Community juries have traditionally taken place in-person, although holding them online or in a hybrid format is increasingly common, particularly following the COVID-19 pandemic. In order for the community jury method to be used successfully, it is crucial to ensure that the goals of the deliberative process are accomplished.
objectiveTo assess the quality of unfacilitated deliberation in community juries held either online or in-person.
methodsWe conducted a secondary analysis of three community juries exploring the public acceptability of novel cancer screening and referral policies informed by personal risk. Two juries were held online, and one was held in-person. We analysed the deliberations via framework analysis, using a previously developed deductive coding framework that addresses the theoretical goals underlying the deliberative process. Participants also completed post-jury surveys including questions relating to their experiences of the online or in-person setting.
resultsNine participants attended the in-person jury, and a total of 15 attended online. Both online and in-person juries achieved all six deliberative goals to some extent with juries in both settings able to participate in successful deliberation and produce well-informed recommendations from a societal perspective.
conclusionThese findings suggest that community juries delivered both online and in-person have the potential to facilitate high-quality deliberations, and both settings can be used to successfully conduct community juries. PATIENT OR PUBLIC CONTRIBUTION: Four PPI representatives, who represented people with different characteristics, including a personal history of cancer, were involved throughout this research. Their contribution included the formation of the research question for the funding application, design of participant-facing aspects of the research, such as presentations used within the juries, and creation of lay summaries of findings.
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.