METHODS: The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system.
RESULTS: Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results.
CONCLUSION: The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.
OBJECTIVE: The three main objectives are to analyze published pen-and-paper observational methods, to extract and understand the risk levels of each method and to identify their associated health effects.
METHODOLOGY: The authors searched scientific databases and the Internet for materials from 1970 to 2013 using the following keywords: ergo, posture, method, observational, postural angle, health effects, pain and diseases. Postural assessments of upper arms, lower arms, wrists, neck, back and legs in six pen-and-paper-based observational methods are highlighted, extracted in groups and linked with associated adverse health effects.
RESULTS: The literature reviewed showed strengths and limitations of published pen-and-paper-based observational methods in determining the work activities, risk levels and related postural angles to adverse health effects. This provided a better understanding of unsafe work postures and how to improve these postures.
CONCLUSION: Many pen-and-paper-based observational methods have been developed. However, there are still many limitations of these methods. There is, therefore, a need to develop a new pen-and-paper-based observational method for assessing postural problems.
AIM AND OBJECTIVES: This study aimed to assess healthcare university students' knowledge, attitude, and practice regarding ChatGPT for academic purposes. It explored chatbot usage frequency, purposes, satisfaction levels, and associations between age, gender, and ChatGPT variables.
METHODOLOGY: Four hundred forty-three undergraduate students at a Malaysian tertiary healthcare institute participated, revealing varying awareness levels of ChatGPT's academic utility. Despite concerns about accuracy, ethics, and dependency, participants generally held positive attitudes toward ChatGPT in academics.
RESULTS: Multiple logistic regression highlighted associations between demographics, knowledge, attitude, and academic ChatGPT use. MBBS students were significantly more likely to use ChatGPT for academics than BDS and FIS students. Final-year students exhibited the highest likelihood of academic ChatGPT use. Higher knowledge and positive attitudes correlated with increased academic usage. Most users (45.8%) employed ChatGPT to aid specific assignment sections while completing most work independently. Some did not use it (41.1%), while others heavily relied on it (9.3%). Users also employed it for various purposes, from generating questions to understanding concepts. Thematic analysis of responses showed students' concerns about data accuracy, plagiarism, ethical issues, and dependency on ChatGPT for academic tasks.
CONCLUSION: This study aids in creating guidelines for implementing GAI chatbots in healthcare education, emphasizing benefits, and risks, and informing AI developers and educators about ChatGPT's potential in academia.