Evidence map›Paper›PMID 39864975›Full record

ArticleInternational dental journal2025

External Validation of an AI mHealth Tool for Gingivitis Detection among Older Adults at Daycare Centers: A Pilot Study.

Reinhard Chun Wang Chau, Andrew Chi Chung Cheng, Kaijing Mao, Khaing Myat Thu, Zhaoting Ling, In Meei Tew, Tien Hsin Chang, Hong Jin Tan, Colman McGrath, Wai-Lun Lo and 2 more

Registry-linked trialAbstract readValidation Study
In one paragraph

Article in International dental journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07187453 (Improving Gum Health Among Older Adults in Hong Kong Through Artificial Intelligence-Based Mobile Health for Personalized Oral Hygiene Instruction), which is not on this map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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.

NCT07187453 naactive not recruitingnot on this map

Improving Gum Health Among Older Adults in Hong Kong Through Artificial Intelligence-Based Mobile Health for Personalized Oral Hygiene Instruction

TypeinterventionalSponsorThe University of Hong KongRan2025 to 2026Enrolled88ConditionsGum Inflammation, Periodontal Diseases, Oral Hygiene, Oral HealthArmsPersonalized Oral Hygiene Advice using AI assisted mHealth Tool by Non-Dental Personnel
3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  4. Beyond the Drill: Can Digital Gadgets Redefine the Future of Dental Education?European journal of dental education : official journal of the Association for Dental Education in Europe · 2026
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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

12 authors.

Reinhard Chun Wang ChauFaculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Andrew Chi Chung ChengDepartment of Computer Science, Hong Kong Chu Hai College, Hong Kong Special Administrative Region, China.
Kaijing MaoFaculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Khaing Myat ThuFaculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Zhaoting LingFaculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
In Meei TewFaculty of Dentistry, The National University of Malaysia, Kuala Lumpur, Malaysia.
Tien Hsin ChangSchool of Dental Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, US.
Hong Jin TanEastman Dental Institute, University College London, London, UK.
Colman McGrathFaculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Wai-Lun LoDepartment of Computer Science, Hong Kong Chu Hai College, Hong Kong Special Administrative Region, China.
Richard Tai-Chiu HsungFaculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China; Department of Computer Science, Hong Kong Chu Hai College, Hong Kong Special Administrative Region, China. Electronic address: richardhsung@chuhai.edu.hk.
Walter Yu Hang LamFaculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China; Musketeers Foundation Institute of Data Science, The University of Hong Kong, Hong Kong Special Administrative Region, China. Electronic address: retlaw@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPeriodontal disease is a significant public health concern among older adults due to its relationship with tooth loss and systemic health disease. However, there are numerous barriers that prevent older adults from receiving routine dental care, highlighting the need for innovative screening tools at the community level. This pilot study aimed first, to evaluate the accuracy of GumAI, a new mHealth tool that uses AI and smartphones to detect gingivitis, and the user acceptance of personalized oral hygiene instructions provided through the new tool, among older adults in day-care community centers.

methodsParticipants were invited from 3 day-care community centers. Intraoral photographs were captured and assessed by both GumAI (test) and a panel consisting of 2 calibrated periodontists and a dentist (benchmark). Mean sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and F1 score were calculated to determine GumAI's diagnostic performance in comparison to the benchmark. User acceptance with this tool was assessed using 2 Rasch Theory-based 5-point Likert-type questions.

results44 participants were recruited out of 80 invited older adults. GumAI demonstrated a sensitivity of 0.93 and specificity of 0.50 compared to the panel's assessments, with a PPV of 0.90 and NPV of 0.56. The accuracy and F1 scores were 0.85 and 0.91, respectively. All participants expressed high acceptance of the process.

conclusionGumAI demonstrates high sensitivity, PPV, accuracy, and F1 score compared to the panel's assessments but falls relatively short in specificity and NPV. Despite this, the tool was highly accepted by older adults, indicating its potential to enhance gingivitis detection and oral hygiene management in community settings. Further refinements are necessary to improve specificity and validate usability measures. CLINICAL RELEVANCE: This study may pave the way for broader applications of mHealth systems in community settings, enabling greater health coverage and addressing oral health disparities.

Indexed as

GingivitisTelemedicineAgedAged, 80 and overFemaleHumansMaleMiddle AgedOral HygienePilot ProjectsSensitivity and SpecificitySmartphoneCommunity dentistryGingivitisMachine learningMobile healthPeriodontal diseasesTelemedicine

Identifiers

PMID39864975
PMCPMC12142741

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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.