Three-dimensional (3D) printing technology is highly regarded in the field of dentistry. Three-dimensional printed resin restorations must undergo a washing process to remove residual resin on the surface after they have been manufactured. However, the effect of the use of different washing solutions and washing times on the biocompatibility of the resulting resin restorations is unclear. Therefore, we prepared 3D-printed denture teeth and crown and bridge resin, and then washed them with two washing solutions (isopropyl alcohol and tripropylene glycol monomethyl ether) using different time points (3, 5, 10, 15, 30, 60, and 90 min). After this, the cell viability, cytotoxicity, and status of human gingival fibroblasts were evaluated using confocal laser scanning. We also analyzed the flexural strength, flexural modulus, and surface SEM imaging. Increasing the washing time increased the cell viability and decreased the cytotoxicity (p < 0.001). Confocal laser scanning showed distinct differences in the morphology and number of fibroblasts. Increasing the washing time did not significantly affect the flexural strength and surface, but the flexural modulus of the 90 min washing group was 1.01 ± 0.21 GPa (mean ± standard deviation), which was lower than that of all the other groups and decreased as the washing time increased. This study confirmed that the washing time affected the biocompatibility and mechanical properties of 3D printed dental resins.

Since the start of the 2019 coronavirus pandemic, interest in digital therapeutics (DTx) has increased. Temporomandibular disorder (TMD) fundamentally requires cognitive behavioral therapy (CBT), including physical self-regulation. An application that records TMD pain and parafunctional activities for CBT has recently been developed. However, evidence of the reduction of clinical symptoms in patients via repetitive software-driven CBT is lacking. The purpose of the present study was to evaluate the impact of applications that support CBT regarding the performance of CBT and the improvement of clinical symptoms in temporomandibular joint patients. From 20 October 2020 to 7 January 2021, we randomly assigned 41 participants diagnosed with TMD to control (conventional treatment) and experimental (conventional treatment + application use) groups. We randomly assigned 41 participants diagnosed with TMD to control (conventional treatment) and experimental (conventional treatment + application use) groups. Improvements regarding the number of tender points, mouth opening, visual analog scale score, pain level upon palpation, joint sound, and stress were compared between the two groups. Compared with the control group, the experimental group showed significant improvements in the number of tender points and degree of mouth opening. They also showed improvements in pain level, joint sound, and locking, although not statistically significantly, as compared with the control group. Thus, further studies with a greater sample size need to be conducted to confirm the findings. Nevertheless, our results showed that repetitive cognitive behavioral therapy using a smartphone application can be used as digital therapeutics for temporomandibular disorder patients.

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 (CBCT and MRI) in 500 patients with temporomandibular disorder (TMD). The research focused on three diagnostic categories: the initial specialist diagnoses, the final diagnoses after imaging, and the mobile app’s diagnoses. The concordance rates, sensitivities, specificities, and positive predictive values of the diagnoses were examined, with further imaging serving as the gold standard. The mobile app demonstrated a high concordance rate compared to both the final (0.93) and the initial specialists’ diagnoses (0.86). The sensitivities, specificities, 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 the imaging results (CBCT and MRI), the specialists’ diagnoses yielded similar results. The study suggests that user-friendly diagnostic mobile applications, based on the diagnostic criteria for TMD, 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.

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.