Validity of a mobile application to diagnose temporomandibular disorders
Yoo Ree Hong, Na-Kyung Hwangbo, Alec Hyung Kim, Seong Taek Kim
Abstract
Open-access reader
Yoo Ree Hong, Na-Kyung Hwangbo, Alec Hyung Kim, Seong Taek Kim
Abstract
Open-access reader
This study aimed to assess the diagnostic accuracy of a mobile application by comparing its diagnoses to those of Orofacial Pain and Oral Medicine specialists and further imaging results (TMJ CBCT and MRI) in 500 patients with temporomandibular disorder (TMD). The research focused on three diagnostic categories: initial specialist diagnoses, final diagnoses after imaging, and the mobile app's diagnoses. The concordance rate, sensitivity, specificity, and positive predictive value of the diagnoses were examined, with further imaging serving as the gold standard. The mobile app demonstrated a high concordance rate compared to both final (0.93) and initial specialist diagnoses (0.86). Sensitivity, specificity, and positive predictive values also indicated strong reliability, affirming the app's diagnostic validity. Although the concordance rate was slightly lower when comparing the app's diagnoses to imaging results (CBCT and MRI), specialist diagnoses yielded similar results. The study suggests that user-friendly diagnostic mobile applications, based on the Diagnostic Criteria for Temporomandibular Disorders, could enhance the clinical management of TMD. Given the reliability of mobile applications for diagnostic purposes, their wider implementation could facilitate the provision of appropriate and timely treatments for patients with TMD.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This study aimed to assess the diagnostic accuracy of a mobile application by comparing its diagnoses to those of Orofacial Pain and Oral Medicine specialists and further imaging results (TMJ CBCT and MRI) in 500 patients with temporomandibular disorder (TMD). The research focused on three diagnostic categories: initial specialist diagnoses, final diagnoses after imaging, and the mobile app's diagnoses. The concordance rate, sensitivity, specificity, and positive predictive value of the diagnoses were examined, with further imaging serving as the gold standard. The mobile app demonstrated a high concordance rate compared to both final (0.93) and initial specialist diagnoses (0.86). Sensitivity, specificity, and positive predictive values also indicated strong reliability, affirming the app's diagnostic validity. Although the concordance rate was slightly lower when comparing the app's diagnoses to imaging results (CBCT and MRI), specialist diagnoses yielded similar results. The study suggests that user-friendly diagnostic mobile applications, based on the Diagnostic Criteria for Temporomandibular Disorders, could enhance the clinical management of TMD. Given the reliability of mobile applications for diagnostic purposes, their wider implementation could facilitate the provision of appropriate and timely treatments for patients with TMD.
Key concepts: Medical diagnosis, Concordance, Gold standard (test), Medicine, Temporomandibular disorder, Diagnostic accuracy, Predictive value, Kappa