Purpose: The purpose of this study is to investigate the patient safety status and patient safety education contents and methods perceived by nurses working in psychiatric hospitals.Methods: Data were collected using a semi-structured questionnaire for psychiatric hospital nurses who had worked for more than one year. A total of 157 questionnaires were filled and were used for analysis using descriptive statistics. Open-ended questions about the contents and methods of patient safety education were classified by each researcher and a reclassification was conducted by consensus through discussions.Results: Overall, 142 nurses (90.4%) experienced patient safety accident during the previous 1 month. Among those who experienced a patient safety accident, profanity, violence, and aggression-related accident counted for the highest percentage (82.8%). The demand for education on workplace stress management and education on psychiatric medication were the highest. Required education methods included case-by-case education on patient safety accidents, regular and continuous education, and small-scale face-to-face education.Conclusion: In the future, it is necessary to actively utilize the results of this study as basic data for in-depth research on the causes of patient safety accidents, accident prevention, and the workload of nursing personnel.

Purpose: This study applied in-depth research methods on the level of securing mental health nurses in mental medical institutions targeting a group of experts in mental health nursing personnel, and sought paths toward revising enforcement regulations of the Mental Health Welfare Act in the future.Methods: Focus group interviews were conducted with experts experienced in conducting research on mental nursing staffing or policy development for nursing staffing.Results: Many experts in the field of psychiatric nursing must obtain additional accurate and valid support data to focus attention on the level of securing psychiatric nurses and discussing active efforts and short-and long-term strategies.Conclusion: It is important to prepare evidence for the quality level of psychiatric nursing, as well as to secure adequate manpower for psychiatric nurses. In the future, it is necessary to actively use these data for policies and research relative to psychiatric nurse workforce planning.

Limited expressivity of emotion is one of the most common symptoms of major depression, particularly in older adults. Although assessing facial and vocal expressivity is very important for accurate clinical evaluation of geriatric depression, research has rarely examined older adults via telehealth technology. This study aims to quantify facial and vocal expressivity via a multimodal affective system with deep learning. A total of 19 Korean adults aged over 65 years with severe depressive symptoms participated in this research. Using smartphone video recording, 1,429 facial and vocal data were collected between July and December 2020. Recorded videos were transmitted automatically to the cloud system. Basic facial movements were extracted using combined video frames and mel spectrogram images. Compared to the AI hub of Korean images from big data, mood status was classified into seven categories (anger, disgust, fear, happiness, neutrality, sadness, and surprise). Frequencies of each mood were coded into continuous variables for each participant in each recording. When comparing video and text prediction to determine “true labels,” the overall accuracy was 0.69, with F1 scores ranging from 0.57 to 0.79. In addition, the most common emotions were angry, happy, neutral, sad, and surprised. This study suggests that smartphone-recorded video could function as a useful tool for quantifying mood expressivity. This study established a preliminary method of affective assessment for older adults for telecare use based on socially assistive technology at a distance from the clinic.