Evidence map›Paper›PMID 40124260›Full record

ArticleAJPM focus2025

Identifying Patterns in Dental Visit Attendance Among Pregnant Women: A Retrospective Cohort Study.

Nisreen Al Jallad, Samantha Manning, Xinyue Mao, Parshad Mehta, TongTong Wu, Rita Cacciato, Jiebo Luo, Yihong Li, Jin Xiao

Abstract read
In one paragraph

Article in AJPM focus, 2025. 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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0cells of the map it votes in
0citing papers in PubMed
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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

9 authors.

Nisreen Al JalladEastman Institute for Oral Health, University of Rochester Medical Center, Rochester, New York.
Samantha ManningDepartment of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York.
Xinyue MaoDepartment of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York.
Parshad MehtaMaster of Public Health Program, Department of Public & Ecosystem Health, Cornell University, Ithaca, New York.
TongTong WuDepartment of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York.
Rita CacciatoEastman Institute for Oral Health, University of Rochester Medical Center, Rochester, New York.
Jiebo LuoDepartment of Computer Science, University of Rochester Medical Center, Rochester, New York.
Yihong LiMaster of Public Health Program, Department of Public & Ecosystem Health, Cornell University, Ithaca, New York.
Jin XiaoEastman Institute for Oral Health, University of Rochester Medical Center, Rochester, New York.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Understanding the factors influencing dental care utilization is crucial for enhancing treatment adherence and outcomes. This study evaluates dental care-seeking patterns among pregnant women in low-income community. Methods: The authors analyzed data from 311 pregnant patients and 1,111 visits (2019-2022) synchronized from dental and medical records. The primary outcome was showing up for scheduled dental visits. To identify visit-attending patterns, the authors used a model-based clustering method to cluster longitudinal data with categorical outcomes. A penalized generalized linear mixed-effects model was applied to identify relevant variables for the visit attendance trajectories within each cluster. Results: The study participants comprised 49.6% Black, 32.2% White, and 12.5% Hispanic women. The majority (89.07%) were holding Medicaid insurance. Among the 1,111 scheduled visits, 432 resulted in no-shows (38.8%), including failed and canceled appointments. The authors identified 3 distinct clusters of visit-attending patterns on the basis of their show-up rates: low demand/low appointment risk (85% attendance), high demand/high appointment risk (57% attendance despite multiple scheduled visits), and moderate demand/high appointment risk (55% attendance with fewer scheduled visits). Various determinants, such as race; age; inner-city residence; appointment timing; the COVID-19 era; type of scheduled dental treatment; and prior medical visits for conditions such as anxiety, depression, hypertension, and allergies, influenced the visit-attending behaviors within each patient group. Conclusions: The innovative clustering approach of this study successfully identified dental care-seeking patterns among pregnant women, suggesting its applicability to a broader demographic. Identifying potential modifiable factors that could enhance attendance at dental visits is essential for improving oral healthcare outcomes among underserved pregnant patients.

Indexed as

care-seeking patternsPregnancyprenatal oral healthcaresocial determinants of health

Identifiers

PMID40124260
PMCPMC11930118

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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.