METHODS: Parents whose children aged below 12 years and were scheduled for elective surgery in a teaching hospital, were approached to participate in this survey. The reliability of the modified version of revised American Pain Society Patient Outcome Questionnaire was evaluated using Cronbach's alpha test, while the construct validity was assessed with a principal component analysis using a varimax rotation. The parental satisfaction with pain treatment received was measured.

RESULTS: A total of 108 parents completed the questionnaire. The internal consistency of the questionnaire shows a Cronbach's alpha of 0.798. Principal component analysis revealed a four-factor structure of the 12 items which explained 69.7% of the total variance. The factors are "Interference of sleep and activity," "Pain severity and drowsiness," "Perception of care," and "Adverse effects," respectively. Our study showed that this questionnaire is a valid and reliable measure for "Interference of sleep and activity" and "Pain severity and drowsiness" factors, but not for "Perception of care" and "Adverse effects." The results for "Perception of care" and "Adverse effects," therefore, should be reported as individual items instead of total score. The parental satisfaction with pain treatment given was good (median 8.0; IQR 3.0).

METHODOLOGY: An online cross-sectional study was conducted via non-probabilistic convenience sampling. Data were collected on sociodemographic characteristics, lifestyle, COVID-19 related influences. Mental health status was assessed with depression, anxiety, and stress scale (DASS-21).

RESULTS: 388 students participated this study (72.4% female; 81.7% Bachelor's student). The prevalence of moderate to severe depression, anxiety and stress among university students are 53.9%, 66.2% and 44.6%, respectively. Multivariable logistic regression analysis found that the odds of depression were lower among students who exercise at least 3 times per week (OR: 0.380, 95% CI: 0.203-0.711). The odd ratio of student who had no personal history of depression to had depression, anxiety and stress during this pandemic was also lower in comparison (OR: 0.489, 95% CI: 0.249-0.962; OR: 0.482, 95% CI: 0.241-0.963; OR: 0.252, 95% CI: 0.111-0.576). Surprisingly, students whose are currently pursuing Master study was associated with lower stress levels (OR: 0.188, 95% CI: 0.053-0.663). However, student who had poorer satisfaction of current learning experience were more likely to experience stress (OR: 1.644, 95% CI: 1.010-2.675).

LIMITATIONS: It is impossible to establish causal relationships between variables on mental health outcomes, and there is a risk of information bias.

METHODS: Eighteen students with prior experience in traditional PDPBL processes participated in the study, divided into three groups to perform PDPBL sessions with various triggers from pharmaceutical chemistry, pharmaceutics, and clinical pharmacy fields, while utilizing chat AI provided by ChatGPT to assist with data searching and problem-solving. Questionnaires were used to collect data on the impact of ChatGPT on students' satisfaction, engagement, participation, and learning experience during the PBL sessions.

RESULTS: The survey revealed that ChatGPT improved group collaboration and engagement during PDPBL, while increasing motivation and encouraging more questions. Nevertheless, some students encountered difficulties understanding ChatGPT's information and questioned its reliability and credibility. Despite these challenges, most students saw ChatGPT's potential to eventually replace traditional information-seeking methods.

MATERIALS AND METHODS: This was a retrospective study using computed tomography (CT) scans from 3 hospitals. Inclusion criteria were scans with 1-5 nodules of diameter ≥5 mm; exclusion criteria were poor-quality scans or those with nodules measuring <5mm in diameter. In the lesion detection phase, 2,147 nodules from 219 scans were used to develop and train the deep learning 3D-CNN to detect lesions. The 3D-CNN was validated with 235 scans (354 lesions) for sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) analysis. In the path planning phase, Bayesian optimization was used to propose possible needle trajectories for lesion biopsy while avoiding vital structures. Software-proposed needle trajectories were compared with actual biopsy path trajectories from intraprocedural CT scans in 150 patients, with a match defined as an angular deviation of <5° between the 2 trajectories.

RESULTS: The model achieved an overall AUC of 97.4% (95% CI, 96.3%-98.2%) for lesion detection, with mean sensitivity of 93.5% and mean specificity of 93.2%. Among the software-proposed needle trajectories, 85.3% were feasible, with 82% matching actual paths and similar performance between supine and prone/oblique patient orientations (P = .311). The mean angular deviation between matching trajectories was 2.30° (SD ± 1.22); the mean path deviation was 2.94 mm (SD ± 1.60).