Learning Outcomes of Flipped Classroom on Community Health Nursing Course.

PURPOSE: To improve the quality of community health nursing practice, the learning outcomes of nursing students in community health nursing courses must be enhanced. Although the flipped classroom is considered an effective innovative teaching strategy, evidence of its application in community health nursing courses is limited. Therefore, this study aimed to examine the effects of a flipped classroom approach on community nursing competence, academic performance, course engagement, and learning satisfaction for a community health nursing course. DESIGN: A quasi-experimental study design was adopted between September 2021 and January 2022. METHODS: Two classes of nursing students (n = 92) from a 2-year nursing program at a university in Taiwan were recruited. The classes were randomly assigned to the intervention group (n = 50) that attended a flipped classroom and the control group (n = 42) that received traditional lecture-based instruction. FINDINGS: Compared with the control group, the intervention group demonstrated significantly greater improvements in community nursing competence (p = .012) and significantly higher academic performance (p = .005). In addition, the course engagement and learning satisfaction of the two groups were high, but not significantly different. CONCLUSIONS: A flipped classroom can be an important strategy to enhance community nursing competence and academic performance. CLINICAL EVIDENCE: The flipped classroom strategy can enhance community nursing competence of nursing students, which may improve the quality of population-based healthcare.

Disparities in medical recommendations from AI-based chatbots across different countries/regions.

This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) and three platforms (Bard, Bing, ChatGPT-3.5). Utilizing previously published cases, we asked identical questions to chatbots from each location within a 24-h window. Responses were evaluated in a double-blinded manner on relevance, clarity, depth, focus, and coherence by ten experts in endometrial cancer. Our analysis revealed significant variations across different countries/regions (p < 0.001). Interestingly, Bing's responses in Nigeria consistently outperformed others (p < 0.05), excelling in all evaluation criteria (p < 0.001). Bard also performed better in Nigeria compared to other regions (p < 0.05), consistently surpassing them across all categories (p < 0.001, with relevance reaching p < 0.01). Notably, Bard's overall scores were significantly higher than those of ChatGPT-3.5 and Bing in all locations (p < 0.001). These findings highlight disparities and opportunities in the quality of AI-powered healthcare information based on user location and platform. This emphasizes the necessity for more research and development to guarantee equal access to trustworthy medical information through AI technologies.

Low Levels of IgM Recognizing 4-Hydroxy-2-Nonenal-Modified Apolipoprotein A-I Peptide and Its Association with the Severity of Coronary Artery Disease in Taiwanese Patients.

Autoantibodies against apolipoprotein A-I (ApoA-I) are associated with cardiovascular disease risks. We aimed to examine the 4-hydroxy-2-nonenal (HNE) modification of ApoA-I in coronary artery disease (CAD) and evaluate the potential risk of autoantibodies against their unmodified and HNE-modified peptides. We assessed plasma levels of ApoA-I, HNE-protein adducts, and autoantibodies against unmodified and HNE-peptide adducts, and significant correlations and odds ratios (ORs) were examined. Two novel CAD-specific HNE-peptide adducts, ApoA-I251-262 and ApoA-I70-83, were identified. Notably, immunoglobulin G (IgG) anti-ApoA-I251-262 HNE, IgM anti-ApoA-I70-83 HNE, IgG anti-ApoA-I251-262, IgG anti-ApoA-I70-83, and HNE-protein adducts were significantly correlated with triglycerides, creatinine, or high-density lipoprotein in CAD with various degrees of stenosis (<30% or >70%). The HNE-protein adduct (OR = 2.208-fold, p = 0.020) and IgM anti-ApoA-I251-262 HNE (2.046-fold, p = 0.035) showed an increased risk of progression from >30% stenosis in CAD. HNE-protein adducts and IgM anti-ApoA-I251-262 HNE may increase the severity of CAD at high and low levels, respectively.

Comparison of continuous 24-hour and 14-day ECG monitoring for the detection of cardiac arrhythmias in patients with ischemic stroke or syncope.

BACKGROUND: Previous studies show that using 12-lead electrocardiogram (ECG) or 24-h ECG monitor for the detection of cardiac arrhythmia events in patients with stroke or syncope is ineffective. HYPOTHESIS: The 14-day continuous ECG patch has higher detection rates of arrhythmias compared with conventional 24-h ECG monitoring in patients with ischemic stroke or syncope. METHODS: This cross-sectional study of patients with newly diagnosed ischemic stroke or syncope received a 24-h ECG monitoring and 14-day continuous cardiac monitoring patch and the arrhythmia events were measured. RESULTS: This study enrolled 83 patients with ischemic stroke or syncope. The detection rate of composite cardiac arrhythmias was significantly higher for the 14-day ECG patch than 24-h Holter monitor (69.9% vs. 21.7%, p = .006). In patients with ischemic stroke, the detection rates of cardiac arrhythmias were 63.4% for supraventricular tachycardia (SVT), 7% for ventricular tachycardia (VT), 5.6% for atrial fibrillation (AF), 4.2% for atrioventricular block (AVB), and 1.4% for pause by 14-day ECG patch, respectively. The significant difference in arrhythmic detection rates were found for SVT (45.8%), AF (6%), pause (1.2%), AVB (2.4%), and VT (9.6%) by 14-day ECG patch but not by 24-h Holter monitor in patients with ischemic stroke or syncope. CONCLUSIONS: A 14-day ECG patch can be used on patients with ischemic stroke or syncope for the early detection of AF or other cardiac arrhythmia events. The patch can be helpful for physicians in planning medical or mechanical interventions of patients with ischemic stroke and occult AF.

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study.

BACKGROUND: Sentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its colloquialism and multilingualism, make it different from other languages and pose additional challenges to sentiment analysis. Recent advances in models such as ChatGPT offer potential viable solutions. OBJECTIVE: This study investigated the efficacy of GPT-3.5 and GPT-4 in Cantonese sentiment analysis in the context of web-based counseling and compared their performance with other mainstream methods, including lexicon-based methods and machine learning approaches. METHODS: We analyzed transcripts from a web-based, text-based counseling service in Hong Kong, including a total of 131 individual counseling sessions and 6169 messages between counselors and help-seekers. First, a codebook was developed for human annotation. A simple prompt ("Is the sentiment of this Cantonese text positive, neutral, or negative? Respond with the sentiment label only.") was then given to GPT-3.5 and GPT-4 to label each message's sentiment. GPT-3.5 and GPT-4's performance was compared with a lexicon-based method and 3 state-of-the-art models, including linear regression, support vector machines, and long short-term memory neural networks. RESULTS: Our findings revealed ChatGPT's remarkable accuracy in sentiment classification, with GPT-3.5 and GPT-4, respectively, achieving 92.1% (5682/6169) and 95.3% (5880/6169) accuracy in identifying positive, neutral, and negative sentiment, thereby outperforming the traditional lexicon-based method, which had an accuracy of 37.2% (2295/6169), and the 3 machine learning models, which had accuracies ranging from 66% (4072/6169) to 70.9% (4374/6169). CONCLUSIONS: Among many text analysis techniques, ChatGPT demonstrates superior accuracy and emerges as a promising tool for Cantonese sentiment analysis. This study also highlights ChatGPT's applicability in real-world scenarios, such as monitoring the quality of text-based counseling services and detecting message-level sentiments in vivo. The insights derived from this study pave the way for further exploration into the capabilities of ChatGPT in the context of underresourced languages and specialized domains like psychotherapy and natural language processing.

Patterns in suicide by marital status in Hong Kong, 2002-2020: Is marriage still a protective factor against suicide?

BACKGROUND: Marriage has long been considered protective against suicide, but shifting social norms since 2000 in Hong Kong raise doubts regarding whether this is still the case. The aim of the study was to investigate the changing association between suicide and marital status. METHODS: Official suicide data for 2002-2020 in Hong Kong were obtained. Suicide rates and suicide risk ratios were calculated by gender, age group, and marital status (married, never-married, widowed, divorced/separated). RESULTS: Suicide risk decreased significantly over time for men and women of all ages. People who were never-married, divorced/separated, had significantly higher suicide risks than their married counterparts. Increasing suicide risks over time were observed for never-married men aged 20-49 years, never-married women aged 35-49 years, and divorced/separated men aged 20-34 years. Widowed men and women of any age had higher suicide risks compared with previous studies in Hong Kong. LIMITATIONS: Marital status is a time-varying covariate, and the time spent in a given marital status could affect suicide risk. Some age and gender subgroups had much smaller sample sizes than others, thus it is possible that our suicide risk estimates were overestimated. CONCLUSIONS: Despite rapidly social changing in Hong Kong during the study period, marriage remains a strong protective factor against suicide for men and women. The protective effect is particularly evident for younger people. Increasing suicide rates for divorced/separated, never-married, or widowed people suggest that they require more psychosocial support.