Objectives This study aimed to address the acceptance of mHealth applications for a dental screening app that facilitates patient information entry and captures dental photos remotely to assist in caries diagnosis in preschool children in Australia. Methods All participants were recruited through the ORIGINS Project, a community-based interventional birth cohort study in Western Australia. Forty-two primary caregivers, who were the users of a teledental screening app, were given a questionnaire with 17 questions; these were constructed based on the theme of the Technology Acceptance Model: perceived ease of use (PE), perceived usefulness (PU), behavioural intention to adopt (BI), anxiety (ANX), attitude toward a behaviour (ATB), and self-efficacy (SE). Cronbach's alpha was estimated to determine internal consistency. Path analysis was employed to quantify the relationship between each theme. Results The mean values for most themes indicated high satisfaction with the intervention among caregivers (scores out of 5): PE (4.54 ± 0.55), PU (4.65 ± 0.49), BI (4.40 ± 0.65), ATB (4.23 ± 0.70), SE (4.36 ± 0.64). Results indicated high consistency in response in the PE, PU, ATB, and SE (α = 0.74-0.84) and moderate consistency was observed in ANX and BI (α = 0.50-0.62). The overall intention of using the dental screening app was significantly related to both PU and ATB (P Conclusion The perceived usefulness and attitude toward behaviours influenced the overall behavioural intention of the participants to use the telehealth model in dental screening. Recognising these relationships indicates community readiness for implementing the telehealth application in the dental program and enables identification of areas for improving its diffusion.
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http://dx.doi.org/10.1071/AH23110 | DOI Listing |
Spec Care Dentist
January 2025
Department of Diagnosis and Surgery, the Institute of Sciences and Technology of São Paulo State University, São José dos Campos, São Paulo, Brazil.
Cureus
December 2024
Department of Orthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, IRN.
Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.
View Article and Find Full Text PDFCureus
December 2024
Faculty of Dentistry, Pharos University, Alexandria, EGY.
Background Odontogenic maxillary sinusitis arises mainly from dental origins, emphasizing the connection between dental health and sinus issues. Understanding these relationships is crucial for implant planning, sinus augmentation procedures, and managing post-extraction complications. This knowledge can help clinicians make informed decisions about treatment timing and approach.
View Article and Find Full Text PDFMol Ther Nucleic Acids
March 2025
Telethon Institute of Genetics and Medicine (TIGEM), Via Campi Flegrei 34, 80078 Pozzuoli, Italy.
Inherited retinal diseases (IRDs) are clinically and genetically heterogeneous disorders characterized by progressive photoreceptor degeneration and irreversible vision loss. MicroRNAs (miRNAs), a class of endogenous non-coding RNAs with post-transcriptional regulatory properties, are known to play a major role in retinal function, both in physiological and pathological conditions. Given their ability to simultaneously modulate multiple molecular pathways, miRNAs represent promising therapeutic tools for disorders with high genetic heterogeneity, such as IRDs.
View Article and Find Full Text PDFInt J Dent
January 2025
Department of Oral and Maxillofacial Radiology, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Investigating the pattern of extension in the periapical (PA) inflammatory lesions is important in the treatment plan and prognosis of treatment. This study evaluated the topography of PA inflammatory lesions in the first molars using cone-beam computed tomography (CBCT). In this descriptive study, 197 CBCT images about patients in the age group of 14-77 years were analyzed.
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