METHODS: Twenty-seven adolescents with OCD and 46 controls completed a predictive-inference task, designed to probe how subjects' actions and confidence ratings fluctuate in response to unexpected outcomes. We investigated how subjects update actions in response to prediction errors (indexing mismatches between expectations and outcomes) and used parameters from a Bayesian model to predict how confidence and action evolve over time. Confidence-action association strength was assessed using a regression model. We also investigated the effects of serotonergic medication.
RESULTS: Adolescents with OCD showed significantly increased learning rates, particularly following small prediction errors. Results were driven primarily by unmedicated patients. Confidence ratings appeared equivalent between groups, although model-based analysis revealed that patients' confidence was less affected by prediction errors compared to controls. Patients and controls did not differ in the extent to which they updated actions and confidence in tandem.
CONCLUSIONS: Adolescents with OCD showed enhanced action adjustments, especially in the face of small prediction errors, consistent with previous research establishing 'just-right' compulsions, enhanced error-related negativity, and greater decision uncertainty in paediatric-OCD. These tendencies were ameliorated in patients receiving serotonergic medication, emphasising the importance of early intervention in preventing disorder-related cognitive deficits. Confidence ratings were equivalent between young patients and controls, mirroring findings in adult OCD research.
RESULT: We tested Naive Bayes, Logistic Regression, KNN, J48, Random Forest, SVM, and Deep Neural Network algorithms to ASD screening dataset and compared the classifiers' based on significant parameters; sensitivity, specificity, accuracy, receiver operating characteristic, area under the curve, and runtime, in predicting ASD occurrences. We also found that most of previous studies focused on classifying health-related dataset while ignoring the missing values which may contribute to significant impacts to the classification result which in turn may impact the life of the patients. Thus, we addressed the missing values by implementing imputation method where they are replaced with the mean of the available records found in the dataset.
CONCLUSION: We found that J48 produced promising results as compared to other classifiers when tested in both circumstances, with and without missing values. Our findings also suggested that SVM does not necessarily perform well for small and simple datasets. The outcome is hoped to assist health practitioners in making accurate diagnosis of ASD occurrences in patients.
METHODS: A questionnaire was developed based on the Dental Student Attitude to the Handicapped Scale, Scale of Attitudes to the Disabled Persons and Health Action Process Approach. The self-administered, validated questionnaire was tested for reliability (Cronbach's alpha = .71-.81), before being distributed to clinical dental students of both genders from two universities (University A, n = 176 and University B, n = 175). Quantitative data were analysed via t test and ANOVA (p
METHODS: Forty third-year undergraduate dental students were randomly assigned to two groups: FC (n = 20) and LD (n = 20). Students in group FC attended FC, while students in group LD attended LD. Both groups underwent a series of standardized teaching sessions to acquire skills in fabricating six types of orthodontic wire components. Eight students (four high achievers and four low achievers) from each group were randomly selected to attend separate focus group discussion (FGD) sessions. Students' perceptions on the strengths, weaknesses, and suggestions for improvement on each teaching method were explored. Audio and video recordings of FGD were transcribed and thematically analyzed using NVivo version 12 software.
RESULTS: Promoting personalized learning, improvement in teaching efficacy, inaccuracy of three-dimensional demonstration from online video, and lack of standardization among instructors and video demonstration were among the themes identified. Similarly, lack of standardization among instructors was one of the themes identified for LD, in addition to other themes such as enabling immediate clarification and vantage point affected by seating arrangement and class size.
CONCLUSIONS: In conclusion, FC outperformed LD in fostering personalized learning and improving the efficacy of physical class time. LD was more advantageous than FC in allowing immediate question and answer. However, seating arrangement and class size affected LD in contrast to FC.