Evidence map›Paper›PMID 37340358›Full record

ArticleBMC oral health2023

Harnessing the power of collective intelligence in dentistry: a pilot study in Victoria, Australia.

Mahen Ganhewa, Alison Lau, Angela Lay, Min Jae Lee, Weiyu Liang, Emmy Li, Xue Li, Lee Yen Khoo, Su Min Lee, Rodrigo Mariño and 1 more

Abstract read
In one paragraph

Article in BMC oral health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Mahen GanhewaCoTreat, CoTreat Pty Ltd, Melbourne, VIC, Australia.
Alison LauMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Angela LayMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Min Jae LeeMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Weiyu LiangMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Emmy LiMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Xue LiMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Lee Yen KhooMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Su Min LeeMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia.
Rodrigo MariñoMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia. r.marino@unimelb.edu.au.
Nicola CirilloMelbourne Dental School, The University of Melbourne, 720 Swanston Street, Carlton, VIC, 3053, Australia. nicola.cirillo@unimelb.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn many dental settings, diagnosis and treatment planning is the responsibility of a single clinician, and this process is inevitably influenced by the clinician's own heuristics and biases. Our aim was to test whether collective intelligence increases the accuracy of individual diagnoses and treatment plans, and whether such systems have potential to improve patient outcomes in a dental setting.

methodsThis pilot project was carried out to assess the feasibility of the protocol and appropriateness of the study design. We used a questionnaire survey and pre-post study design in which dental practitioners were involved in the diagnosis and treatment planning of two simulated cases. Participants were provided the opportunity to amend their original diagnosis/treatment decisions after viewing a consensus report made to simulate a collaborative setting.

resultsAround half (55%, n = 17) of the respondents worked in group private practices, however most practitioners (74%, n = 23) did not collaborate when planning treatment. Overall, the average practitioners' self-confidence score in managing different dental disciplines was 7.22 (s.d. 2.20) on a 1-10 scale. Practitioners tended to change their mind after viewing the consensus response, particularly for the complex case compared to the simple case (61.5% vs 38.5%, respectively). Practitioners' confidence ratings were also significantly higher (p < 0.05) after viewing the consensus for complex case.

conclusionOur pilot study shows that collective intelligence in the form of peers' opinion can lead to modifications in diagnosis and treatment planning by dentists. Our results lay the foundations for larger scale investigations on whether peer collaboration can improve diagnostic accuracy, treatment planning and, ultimately, oral health outcomes.

Indexed as

DentistsProfessional RoleDentistryHumansIntelligencePilot ProjectsSurveys and QuestionnairesVictoriaCollective intelligenceDentistryDiagnosisTreatment planWisdom of crowds

Identifiers

PMID37340358
PMCPMC10280903

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.