Search

Objective: Teledentistry is a promising innovation for improving service quality and patient outcomes. While studies have shown the relevance of theoretical frameworks in understanding behaviour change predictors for telehealth implementation efforts, their application in dentistry is limited. This study aimed to test different theoretical approaches to identify the factors affecting dental students' behavioural intention to use teledentistry., Methods: This cross-sectional study involved students in their final two years of undergraduate dental programmes, from three Canadian provinces (Quebec, Nova Scotia, and Saskatchewan) using an electronic self-reported questionnaire. Following descriptive analyses, we tested three theoretical models (the technology acceptance model, psychosocial model, and integrated model) using path analysis and multiple linear regression analysis. We analyzed the modifying effect of sociodemographic characteristics and prior use of teledentistry., Results: Out of the 46 students who participated, the majority were female (53.5%) and aged over 25 years (62.8%). The three models successfully explained a substantial portion of the variance in behavioural intention to use teledentistry, ranging from 58.0% to 76.6%. Social role beliefs ( p  < 0.001) and control beliefs ( p  < 0.001) were the most significant predictors of behavioural intention to use. Prior use of teledentistry modified the association between control beliefs and behavioural intention to use teledentistry., Conclusions: The original technology acceptance model was a good predictive model of behavioural intention to use teledentistry with perceived use as the strongest predictor. However, the integrated model performed the best in highlighting the relevance of training and education to foster teledentistry implementation in dental schools. The generalizability of the findings is constrained by the modest sample size, warranting larger studies for validation., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Extensive molecular characterization of human colorectal cancer (CRC) via Next Generation Sequencing (NGS) indicated that genetic or epigenetic dysregulation of a relevant, but limited, number of molecular pathways typically occurs in this tumor. The molecular picture of the disease is significantly complicated by the frequent occurrence of individually rare genetic aberrations, which expand tumor heterogeneity. Inter- and intratumor molecular heterogeneity is very likely responsible for the remarkable individual variability in the response to conventional and target-driven first-line therapies, in metastatic CRC (mCRC) patients, whose median overall survival remains unsatisfactory. Implementation of an extensive molecular characterization of mCRC in the clinical routine does not yet appear feasible on a large scale, while multigene panel sequencing of most commonly mutated oncogene/oncosuppressor hotspots is more easily achievable. Here, we report that clinical multigene panel sequencing performed for anti-EGFR therapy predictive purposes in 639 formalin-fixed paraffin-embedded (FFPE) mCRC specimens revealed previously unknown pairwise mutation associations and a high proportion of cases carrying actionable gene mutations. Most importantly, a simple principal component analysis directed the delineation of a new molecular stratification of mCRC patients in eight groups characterized by non-random, specific mutational association patterns (MAPs), aggregating samples with similar biology. These data were validated on a The Cancer Genome Atlas (TCGA) CRC dataset. The proposed stratification may provide great opportunities to direct more informed therapeutic decisions in the majority of mCRC cases., (Copyright © 2020 Belardinilli, Capalbo, Malapelle, Pisapia, Raimondo, Milanetti, Yasaman, Liccardi, Paci, Sibilio, Pepe, Bonfiglio, Mezi, Magri, Coppa, Nicolussi, Gradilone, Petroni, Di Giulio, Fabretti, Infante, Coni, Canettieri, Troncone and Giannini.)