ArticleBMC oral health2026
A scoping review of crowdsourcing and collective intelligence in oral healthcare.
Article in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
5 authors.
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Abstract
objectiveDiagnostic and treatment errors are detrimental yet relatively common in primary healthcare settings. Crowdsourcing and collective intelligence (CI) in the form of peers' opinion and group decision-making can lead to modifications in diagnosis and treatment planning by dentists. In this review, it was explored their use in oral healthcare delivery, investigating specific applications and evaluating their merits and drawbacks in oral healthcare.
methodsA scoping review approach was chosen as the optimal study design, due to the complexity of the topic. A literature search from 1980 to December 2024 using selected search terms and a search strategy was implemented across six databases: Medline, Scopus, Web of Science, SciELO, LILACS, and CINAHL. Inclusion criteria specified studies published in English, Spanish, and Portuguese, focusing on CI applications in oral healthcare settings.
resultsOf the 265 identified studies, 63 abstracts and 20 full-text studies were screened, and 7 studies were included in the qualitative synthesis. The findings suggest that CI may significantly enhance patient management in primary healthcare settings by employing various group decision-making models such as multidisciplinary teams (MDTs) and the Delphi method. MDTs, comprising professionals from different disciplines, can enhance patient care through collaborative problem-solving and holistic approaches. The Delphi method allows for reliable, expert-driven decisions through anonymous feedback rounds. CI not only addresses diagnosis and treatment planning challenges but also improves resource allocation. While these approaches can reduce individual biases and systematic errors, challenges such as conformity bias and groupthink were also acknowledged.
conclusionThis review highlights the significance of diverse expert opinions and structured consensus-building in advancing collective intelligence in oral healthcare. It emphasizes CI's potential to improve patient management through collaborative decision-making models. However, further research is necessary to explore CI's specific applications and effectiveness in oral healthcare.
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