Purpose: This study aimed to identify the factors influencing premedical students’ satisfaction with early clinical experience and determine the mediating effect of self-efficacy on the relationship between learning motivation and satisfaction. Methods: This cross-sectional study included 35 second-year premedical students who completed the early clinical experience course and responded to course evaluation questionnaires on self-efficacy, transfer motivation, and student satisfaction. The data were analyzed using descriptive statistics, Pearson’s correlation, Baron and Kenny’s hierarchical multiple regression analyses, and the Sobel test. Results: Student satisfaction was significantly correlated with self-efficacy (r=0.724, p<0.01) and transfer motivation (r=0.538, p<0.01). Self-efficacy and transfer motivation were also highly correlated (r=0.789, p<0.01). Multiple regression analyses and Sobel test indicated that self-efficacy fully mediated the relationship between student satisfaction and transfer motivation (Z=2.704, p<0.01). Conclusion In this study, early clinical experience program increased premedical students’ self-efficacy and transfer motivation for clinical knowledge and confirmed that self-efficacy mediated student satisfaction. These findings demonstrate the positive effects of early clinical experience on the medical school curriculum and suggest the need for educational strategies to increase self-efficacy in learning.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Purpose: This study aimed to identify the factors influencing premedical students’ satisfaction with early clinical experience and determine the mediating effect of self-efficacy on the relationship between learning motivation and satisfaction. Methods: This cross-sectional study included 35 second-year premedical students who completed the early clinical experience course and responded to course evaluation questionnaires on self-efficacy, transfer motivation, and student satisfaction. The data were analyzed using descriptive statistics, Pearson’s correlation, Baron and Kenny’s hierarchical multiple regression analyses, and the Sobel test. Results: Student satisfaction was significantly correlated with self-efficacy (r=0.724, p<0.01) and transfer motivation (r=0.538, p<0.01). Self-efficacy and transfer motivation were also highly correlated (r=0.789, p<0.01). Multiple regression analyses and Sobel test indicated that self-efficacy fully mediated the relationship between student satisfaction and transfer motivation (Z=2.704, p<0.01). Conclusion In this study, early clinical experience program increased premedical students’ self-efficacy and transfer motivation for clinical knowledge and confirmed that self-efficacy mediated student satisfaction. These findings demonstrate the positive effects of early clinical experience on the medical school curriculum and suggest the need for educational strategies to increase self-efficacy in learning.

Background: Factors influencing the decline in forced expiratory volume in one second (FEV1 )/forced vital capacity (FVC) for chronic obstructive pulmonary disease (COPD) progression remain uncertain. We aimed to identify risk factors associated with rapid FEV1 / FVC decline in patients with COPD. Methods: This multi-center observational study was conducted from January 2012 to December 2022. Eligible patients were monitored with symptoms, spirometric tests, and treatment patterns over 3 years. Rapid FEV1 /FVC decliners were defined as the quartile of patients exhibiting the highest annualized percentage decline in FEV1 /FVC. Results: Among 1,725 patients, 435 exhibited rapid FEV1 /FVC decline, with an annual change of −2.5%p (interquartile range, −3.5 to −2.0). Rapid FEV1 /FVC decliners exhibited lower body mass index (BMI), higher smoking rates, elevated post-bronchodilator (BD) FEV1 , higher post-BD FEV1 / FVC, and a lower prevalence of Staging of Airflow Obstruction by Ratio (STAR) stage IV. Rapid FEV1 /FVC decline was not linked to the annual exacerbation rate, but there was an association with symptom deterioration and FEV1 decline. In multivariable analyses, low BMI, current smoking, increased modified Medical Research Council dyspnoea score, low post-BD FEV1 , low STAR stage, high forced mid-expiratory flow (FEF 25-75% ), accelerated FEV1 decline, and not initiating dual BD therapy were identified as independent risk factors for rapid FEV1 /FVC decline. Conclusion We identified the risk factors for rapid FEV1 /FVC decline, including BMI, smoking, symptoms deterioration, FEV1 decline, and adherence to standard inhaler treatment. Our findings underscore the potential benefits of maintaining consistent use of long-acting beta-agonist/long-acting muscarinic antagonist even in the presence of worsening symptoms, in attenuating FEV1 /FVC decline.

Background: Factors influencing the decline in forced expiratory volume in one second (FEV1 )/forced vital capacity (FVC) for chronic obstructive pulmonary disease (COPD) progression remain uncertain. We aimed to identify risk factors associated with rapid FEV1 / FVC decline in patients with COPD. Methods: This multi-center observational study was conducted from January 2012 to December 2022. Eligible patients were monitored with symptoms, spirometric tests, and treatment patterns over 3 years. Rapid FEV1 /FVC decliners were defined as the quartile of patients exhibiting the highest annualized percentage decline in FEV1 /FVC. Results: Among 1,725 patients, 435 exhibited rapid FEV1 /FVC decline, with an annual change of −2.5%p (interquartile range, −3.5 to −2.0). Rapid FEV1 /FVC decliners exhibited lower body mass index (BMI), higher smoking rates, elevated post-bronchodilator (BD) FEV1 , higher post-BD FEV1 / FVC, and a lower prevalence of Staging of Airflow Obstruction by Ratio (STAR) stage IV. Rapid FEV1 /FVC decline was not linked to the annual exacerbation rate, but there was an association with symptom deterioration and FEV1 decline. In multivariable analyses, low BMI, current smoking, increased modified Medical Research Council dyspnoea score, low post-BD FEV1 , low STAR stage, high forced mid-expiratory flow (FEF 25-75% ), accelerated FEV1 decline, and not initiating dual BD therapy were identified as independent risk factors for rapid FEV1 /FVC decline. Conclusion We identified the risk factors for rapid FEV1 /FVC decline, including BMI, smoking, symptoms deterioration, FEV1 decline, and adherence to standard inhaler treatment. Our findings underscore the potential benefits of maintaining consistent use of long-acting beta-agonist/long-acting muscarinic antagonist even in the presence of worsening symptoms, in attenuating FEV1 /FVC decline.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.