Evidence map›Paper›PMID 40060992›Full record

ArticleJournal of multidisciplinary healthcare2025

The Impact of COVID-19 on Dental Clinic Transmission: Leveraging Internet of Things Technology.

Banu Uygun-Can, Parla Meva Durmazpınar, Şirin Hatipoğlu, Bilge Acar-Bolat, Çağla Özen, Hesna Sazak-Öveçoğlu, Tanju Kadir

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2025. 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

7 authors.

Banu Uygun-CanDepartment of Microbiology, Dental Faculty, Marmara University, Istanbul, Turkey.ORCID 0000-0002-9577-0352
Parla Meva DurmazpınarDepartment of Endodontics, Dental Faculty, Marmara University, Istanbul, Turkey.
Şirin HatipoğluDepartment of Orthodontics, Dental Faculty, Biruni University, Istanbul, Turkey.ORCID 0000-0001-5466-2876
Bilge Acar-BolatDepartment of Numerical Methods, Business Administration Faculty, Istanbul University, Istanbul, Turkey.
Çağla ÖzenDepartment of Management Information Systems, Computer and Information Sciences Faculty, Yeditepe University, Istanbul, Turkey.ORCID 0000-0003-1817-9806
Hesna Sazak-ÖveçoğluDepartment of Endodontics, Dental Faculty, Marmara University, Istanbul, Turkey.
Tanju KadirDepartment of Microbiology, Dental Faculty, Marmara University, Istanbul, Turkey.ORCID 0000-0002-4668-9988

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study focused on the risk posed by pre-symptomatic and asymptomatic carriers in dental clinics during the period (February-June 2022) when Covid-19 transmission was highest and aimed to investigate the effectiveness of infection control protocols in the prevention of SARS-CoV-2 transmission. It also evaluated the potential of wearable sensors as part of the Internet of Things (IoT) to prevent cross-infection. Material and Methods: Swab samples were collected from surfaces and air filters in dental clinics and analyzed using RT-PCR both before and after disinfection processes. Clinicians also used IoT-enabled wearable sensors and completed surveys (n=100) evaluating the impact of these technologies on infection control practices. The sensors monitored clinicians' movements and patient interactions to assess cross-infection risks. Results: All RT-PCR tests returned negative results, indicating that no SARS-CoV-2 was detected on the sampled surfaces or air filters. Surveys revealed that 70% of resident clinicians trusted the effectiveness of wearable sensors in infection control. The technology was particularly well received among younger clinicians and was found to be effective in strengthening contact tracing, control measures, and awareness. Conclusion: Strict infection control measures have contributed to preventing Covid-19 infections in dental clinics, although asymptomatic cases may still be present. These findings highlight the importance of adopting advanced technologies such as wearable sensors to support current infection control measures. With further studies, the scalability and integration of IoT technologies into routine infection control practices in diverse healthcare settings can be better understood, enhancing infection control potential and significantly contributing to the safety of healthcare workers and patients.

Indexed as

asymptomatic transmissionCOVID-19dental clinicsinfection controlRT-PCRwearable sensors

Identifiers

PMID40060992
PMCPMC11889996

What OpenQuestion holds

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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 OpenQuestion graph.