Evidence map›Paper›PMID 42388738›Full record

ArticleFrontiers in public health2026

Factors associated with oral health behaviors of older diabetic patients in Shanghai, China: a structural equation modeling analysis based on the COM-B model.

Shuran Fan, Yanhong Gu

Abstract read
In one paragraph

Article in Frontiers in public 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.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Shuran FanShanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Yanhong GuShanghai Fifth People's Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: The study aims to analyze the association pathways of factors related to oral health behaviors among older diabetic patients in Shanghai, China, using the COM-B model. Methods: A convenience sample of 358 older diabetic patients was enrolled between July 2025 and December 2025 from one tertiary hospital and a community health service center in Shanghai. Information was collected via a general information questionnaire, the Older Oral Health Knowledge, Belief and Behavior Questionnaire, the 14-item Health Literacy in Dentistry Scale, the Perceived Social Support Scale, the Geriatric Self-Efficacy for Oral Health Scale, and the 5-item Geriatric Depression Scale. Descriptive statistics, univariate analysis, correlation analysis, and path analysis were adopted to analyze the relevant factors and pathways of oral health behaviors. Results: The constructed structural equation model showed satisfactory goodness of fit (χ Conclusion: Capability factors, opportunity factors, and motivational factors are directly or indirectly associated with the oral health behaviors among older diabetic patients. This suggests that clinicians regularly conduct diabetes-related oral health education and cleaning skills training, encourage relatives to provide supervision, improve access to oral healthcare, and provide psychological counseling to improve patients' oral health behaviors in terms of capability, opportunity, and motivation.

Indexed as

Diabetes MellitusHealth BehaviorHealth Knowledge, Attitudes, PracticeOral HealthAgedAged, 80 and overChinaFemaleHealth LiteracyHumansLatent Class AnalysisMaleSelf EfficacySocial SupportSurveys and Questionnairesassociation pathwaysolder diabetic patientsoral health behaviorsstructural equation modelingthe COM-B model

Identifiers

PMID42388738
PMCPMC13318739

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.