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Developing and pilot testing an oral health screening tool for diabetes care providers

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posted on 2023-06-21, 06:19 authored by Ajesh GeorgeAjesh George, P Poudel, A Kong, A Villarosa, Hanny CalacheHanny Calache, A Arora, R Griffiths, VW Wong, Mark GussyMark Gussy, Rachel Martin, P Lau
Background: People with poorly managed diabetes are at greater risk of periodontal disease. Periodontal disease that is not effectively managed can affect glycaemic levels. Diabetes care providers, including general practitioners and diabetes educators, are encouraged to promote oral health of their clients. However, valid and reliable oral health screening tools that assess the risk of poor oral health, that are easy to administer among non-dental professionals, currently do not exist. Existing screening tools are difficult to incorporate into routine diabetes consultations due to their length. Thus, this study aimed to develop and pilot a short oral health screening tool that would identify risk of existing oral diseases and encourage appropriate referrals to the dental service. Methods: A three-item screening tool was developed after a comprehensive review of the literature and consensus from an expert panel. The tool was then piloted as part of a larger cross-sectional survey of 260 adults with diabetes who were accessing public diabetes clinics at two locations in Sydney, Australia. As part of the survey, participants completed the three-item screening tool and a 14-item validated tool, the Oral Health Impact Profile (OHIP-14), which has been used previously in the preliminary validation of screening tools. Sensitivity and specificity analyses were then undertaken comparing the results of the two tools. Results: A statistically significant correlation was found between the shorter screening tool and the OHIP-14 (rho = 0.453, p < 0.001), indicating adequate validity. The three-item tool had high sensitivity (90.5%, 95% CI 84.9%, 94.7%), with a specificity of 46.3% (95% CI 37.7%, 55.2%). The negative predictive value was 81.4% (95% CI 71.3, 89.3). No single item performed as well regarding sensitivity and negative predictive value when compared to the three items collectively. Conclusions: The three-item screening tool developed was found to be valid and sensitive in identifying risk of poor oral health, requiring oral health referrals, among people with diabetes in this pilot. This is a simple, accessible tool that diabetes care providers could incorporate into their routine consultations. Further validation against comprehensive dental assessments is needed to reassess the tool’s specificity and sensitivity in diverse settings.

Funding

This research was supported by the Australian Government Research Training Program Stipend Scholarship (Doctor of Philosophy) through Western Sydney University and a partnership Grant (Western Sydney University and The Centre of Oral Health Strategy NSW, Australia).

History

Publication Date

2022-12-01

Journal

BMC Primary Care

Volume

23

Issue

1

Article Number

202

Pagination

8p.

Publisher

BioMed Central Ltd.

ISSN

2731-4553

Rights Statement

© The Author(s) 2022. Licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the licence, and indicate if changes were made. The images or other third party material in this article are included in the article's licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view the licence: http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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