Evidence map›Paper›PMID 42627600›Full record

ArticleThe Saudi dental journal2026

Digital infrastructure and readiness for artificial intelligence (AI) - enabled dentistry: technology adoption and barriers among dental practitioners in Bengaluru, India.

Ramesh Nagarajappa, Sowbhagyalakshmi Kariyappa, Deepa Bullappa, Mehak Batra

Abstract read
In one paragraph

Article in The Saudi dental journal, 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

4 authors.

Ramesh NagarajappaThe Oxford Dental College, Rajiv Gandhi University of Health Sciences, Bengaluru, India. rameshpcd@yahoo.co.in.
Sowbhagyalakshmi KariyappaCollege of Dental Sciences, Rajiv Gandhi University of Health Sciences, Bengaluru, India.
Deepa BullappaThe Oxford Dental College, Rajiv Gandhi University of Health Sciences, Bengaluru, India.
Mehak BatraSchool of Psychology and Public Health, La Trobe University, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To assess digital readiness for AI-enabled dentistry by evaluating the uptake of digital technologies, patterns of use, and implementation barriers among dentists in Bengaluru, India. A cross-sectional survey was conducted among 138 practising dentists using quota-based purposive sampling across predefined practice strata to include private practitioners, government or private academic institutions, and those engaged in both. A pretested structured questionnaire collected data on sociodemographic characteristics, availability, utilisation, and perceived barriers to digital technologies. Descriptive statistics summarised prevalence and usage, while chi-square and regression analyses explored associations with professional characteristics. Digital radiography (91.3%) and Cone Beam Computed Tomography (CBCT) (68.84%) were the most widely available technologies, whereas intraoral cameras (52.17%) and Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM) systems (34.06%) were less accessible. Higher age of the practitioners and higher years of clinical experience were positively associated with digital technology adoption. High cost, inadequate training, and maintenance expenses emerged as the most common barriers. Multivariable analysis demonstrated that greater clinical experience, male sex, and higher perceived implementation barriers were independently associated with greater digital technology uptake. Adoption of advanced digital technologies remains uneven across Bengaluru's dental sector, with disparities linked to experience, sex, and implementation barriers. Strengthening training, infrastructure, and implementation support is essential for equitable AI-readiness in Low- and Middle-Income Countries (LMICs) dentistry.

Indexed as

AI-enabled dentistryArtificial intelligence readinessCAD/CAMCone-beam CTDigital divideDigital transformationIntraoral scannerTechnology adoption

Identifiers

PMID42627600
PMCPMC13498527

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.