Assessment of work-related stress utilizing the Find My Stress mobile application among university students and adult workers amidst the COVID-19 pandemic.

OBJECTIVES: This cross-sectional study aimed to evaluate work-related stress and the efficacy associated with the newly developed Find My Stress mobile application. The global impact of the COVID-19 pandemic has significantly influenced the quality of life, transcending geographical boundaries and inducing stress that has detrimentally affected health and work efficiency. METHODS: A total of 440 male and female participants, comprising university students and adult workers, were enrolled in the study. Participants completed an assessment in the application that consisted of three components: 1) perceived work stress, 2) environmental stress factors, and 3) application efficiency. RESULTS: University students exhibited higher perceived stress levels compared to adult workers (p = 0.031). The predominant physical factors contributing to musculoskeletal disorders in university students were identified as movement and posture factors, particularly related to vibration and organization. Conversely, environmental factors took precedence in adult workers, followed by posture and movement. The reliability of the perceived work stress questionnaire was evaluated by Cronbach's alpha coefficient and yielded a value of 0.96. The Find My Stress application demonstrated high efficiency. CONCLUSIONS: Elevated levels of work stress were observed in both university students and adult workers. Initial signs of musculoskeletal disorders in university students primarily manifested in the neck and upper back, arms, and hands, while adult workers predominantly reported complaints related to the arms and hands. The Find My Stress application emerges as a valuable tool for screening occupational stressors.

Development of a diagnostic support system for the fibrosis of nonalcoholic fatty liver disease using artificial intelligence and deep learning.

Liver fibrosis is a pathological condition characterized by the abnormal proliferation of liver tissue, subsequently able to progress to cirrhosis or possibly hepatocellular carcinoma. The development of artificial intelligence and deep learning have begun to play a significant role in fibrosis detection. This study aimed to develop SMART AI-PATHO, a fully automated assessment method combining quantification of histopathological architectural features, to analyze steatosis and fibrosis in nonalcoholic fatty liver disease (NAFLD) core biopsies and employ Metavir fibrosis staging as standard references and fat assessment grading measurement for comparison with the pathologist interpretations. There were 146 participants enrolled in our study. The correlation of Metavir scoring system interpretation between pathologists and SMART AI-PATHO was significantly correlated (Agreement = 68%, Kappa = 0.59, p-value <0.001), which subgroup analysis of significant fibrosis (Metavir score F2-F4) and nonsignificant fibrosis (Metavir score F0-F1) demonstrated substantial correlated results (agreement = 80%, kappa = 0.61, p-value <0.001), corresponding with the correlation of advanced fibrosis (Metavir score F3-F4) and nonadvanced fibrosis groups (Metavir score F0-F2), (agreement = 89%, kappa = 0.74, p-value <0.001). SMART AI-PATHO, the first pivotal artificially intelligent diagnostic tool for the color-based NAFLD hepatic tissue staging in Thailand, demonstrated satisfactory performance as a pathologist to provide liver fibrosis scoring and steatosis grading. In the future, developing AI algorithms and reliable testing on a larger scale may increase accuracy and contribute to telemedicine consultations for general pathologists in clinical practice.

Use of virtual reality in patient education program to reduce anxiety in upper gastrointestinal endoscopy: A randomized controlled trial.

Background and Aim: Virtual reality (VR) provides an immersive image-viewing experience that has recently been expanding its use in clinical medicine. We aimed to examine a patient education program by VR to reduce anxiety in patients undergoing esophagogastroduodenoscopy (EGD). Methods: We conducted a randomized controlled trial and consecutively enrolled patients who had an indication for unsedated EGD with topical anesthesia. Patients were randomly assigned to use Oculus GO with three-dimensionally specific software content (a stand-alone VR headset) for patient education or standard patient education using oral information (the control group) before EGD. The primary outcome was the variation in anxiety scores before and after patient education programs. Results: A total of 107 patients underwent EGD and received a VR (n = 58) and control (n = 49) patient education program. The mean anxiety score before starting the patient education program was 41.4 9.6 in the VR group and 41.9 7.7 in the control group. The mean anxiety score after the patient education program was 37.1 10.8 in the VR group and 38.9 8.07 in the control group (P-value = 0.354). The anxiety score in the VR group decreased more than in the control group but was not significant. The recall questionnaire scores were higher in the VR group (4.70.4) than the control group (3.91, P-value 0.001). Conclusion: A virtual reality-assisted patient education program before EGD did not significantly reduce anxiety but may provide more memory and understanding about the procedure to patients who underwent unsedated EGD.

Virtual reality distraction during upper gastrointestinal endoscopy: a randomized controlled trial.

BACKGROUND AND AIM: Virtual reality (VR) is an established and effective tool in reducing autonomic and somatic pain. We aimed to examine the analgesic effects of VR distraction during esophagogastroduodenoscopy (EGD). METHODS: We conducted a randomized controlled trial and enrolled patients who had indication for unsedated EGD with topical anesthesia. Patients were randomly assigned to use Oculus GO with three-dimensional specific software content (standalone VR headset), sham VR or without VR during EGD. The primary outcome was patient pain scores during EGD. RESULTS: A total of 96 patients undergoing diagnostic EGD were randomized to receive VR (n = 32), sham VR (n = 32), and no VR defined as the control group (n = 32). Patients in all groups reported no statistically different pain during esophageal intubation. The mean pain score was 2.7 ± 2.4 in the VR group, 2.7 ± 2.5 in the sham VR and 2.3 ± 2.3 in the control group, (P value = 0.751). No significant difference was observed in heart rate and blood pressure, and the endoscopists reported higher overall satisfaction scores in VR (4.3 ± 0.5) compared with the control group (4 ± 0.8) but without significance (P value = 0.156). CONCLUSION: Virtual reality-assisted anesthesia during EGD did not significantly reduce patient pain during esophageal intubation. There was no superiority in using VR distraction regarding patient's and endoscopist's satisfaction compared with standard EGD without VR Further studies are required to detect any true clinical advantage of VR distraction during EGD.

Performance of the Simple Clinical Score (SCS) and the Rapid Emergency Medicine Score (REMS) to predict severity level and mortality rate among patients with sepsis in the emergency department.

Nurses play a key role as the first line of service for patients with medical conditions and injuries in the emergency department (ED), which includes assessing patients for sepsis. The researchers evaluated tools to examine the performance of the Simple Clinical Score (SCS) and the Rapid Emergency Medicine Score (REMS) to predict sepsis severity and mortality among sepsis patients in the ED. A retrospective survey was performed, selecting participants by using a purposive sampling method, and including the medical records of all patients diagnosed with sepsis admitted to the ED at Singburi Hospital, Thailand. Data were analysed using the ROC curve and the Area Under Curve (AUC) to calculate the accuracy of each patient's mortality prediction. A total of 225 patients diagnosed with sepsis was identified, with a mortality rate of 59.11% after admission to the medical service and intensive care unit. The AUC analysis showed that the accuracy of the model generated from the REMS (88.6%) was higher than that of the SCS (76.7%). The authors also recommend that key variables identified in this research should be used to develop screening and assessment tools for sepsis in the context of the ED.