Analyzing the impact of unemployment on mental health among Chinese university graduates: a study of emotional and linguistic patterns on Weibo.

Purpose: This study explores the intricate relationship between unemployment rates and emotional responses among Chinese university graduates, analyzing how these factors correlate with specific linguistic features on the popular social media platform Sina Weibo. The goal is to uncover patterns that elucidate the psychological and emotional dimensions of unemployment challenges among this demographic. Methods: The analysis utilized a dataset of 30,540 Sina Weibo posts containing specific keywords related to unemployment and anxiety, collected from January 2019 to June 2023. The posts were pre-processed to eliminate noise and refine the data quality. Linear regression and textual analyses were employed to identify correlations between unemployment rates for individuals aged 16-24 and the linguistic characteristics of the posts. Results: The study found significant fluctuations in urban youth unemployment rates, peaking at 21.3% in June 2023. A corresponding increase in anxiety-related expressions was noted in the social media posts, with peak expressions aligning with high unemployment rates. Linguistic analysis revealed that the category of "Affect" showed a strong positive correlation with unemployment rates, indicating increased emotional expression alongside rising unemployment. Other categories such as "Negative emotion" and "Sadness" also showed significant correlations, highlighting a robust relationship between economic challenges and emotional distress. Conclusion: The findings underscore the profound impact of unemployment on the emotional well-being of university students, suggesting that economic hardships are closely linked to psychological stress and heightened negative emotions. This study contributes to a holistic understanding of the socio-economic challenges faced by young adults, advocating for comprehensive support systems that address both the economic and psychological facets of unemployment.

Evaluating machine learning-enabled and multimodal data-driven exercise prescriptions for mental health: a randomized controlled trial protocol.

Background: Mental illnesses represent a significant global health challenge, affecting millions with far-reaching social and economic impacts. Traditional exercise prescriptions for mental health often adopt a one-size-fits-all approach, which overlooks individual variations in mental and physical health. Recent advancements in artificial intelligence (AI) offer an opportunity to tailor these interventions more effectively. Objective: This study aims to develop and evaluate a multimodal data-driven AI system for personalized exercise prescriptions, targeting individuals with mental illnesses. By leveraging AI, the study seeks to overcome the limitations of conventional exercise regimens and improve adherence and mental health outcomes. Methods: The study is conducted in two phases. Initially, 1,000 participants will be recruited for AI model training and testing, with 800 forming the training set, augmented by 9,200 simulated samples generated by ChatGPT, and 200 as the testing set. Data annotation will be performed by experienced physicians from the Department of Mental Health at Guangdong Second Provincial General Hospital. Subsequently, a randomized controlled trial (RCT) with 40 participants will be conducted to compare the AI-driven exercise prescriptions against standard care. Assessments will be scheduled at 6, 12, and 18 months to evaluate cognitive, physical, and psychological outcomes. Expected outcomes: The AI-driven system is expected to demonstrate greater effectiveness in improving mental health outcomes compared to standard exercise prescriptions. Personalized exercise regimens, informed by comprehensive data analysis, are anticipated to enhance participant adherence and overall mental well-being. These outcomes could signify a paradigm shift in exercise prescription for mental health, paving the way for more personalized and effective treatment modalities. Registration and ethical approval: This is approved by Human Experimental Ethics Inspection of Guangzhou Sport University, and the registration is under review by ChiCTR.

The effects of inspiratory muscle training on swimming performance: A study on the cohort of swimming specialization students.

PURPOSE: Current evidence posits a strong correlation between respiratory muscle function and swimming performance. Despite this, few studies have explored the integration of inspiratory muscle training (IMT) into standard swimming training regimens, which remains an unexplored avenue for improving performance in swimmers. This study aims to evaluate the potential advantages of IMT for enhancing respiratory function and swimming performance and determine whether such training could induce beneficial physiological adaptations. METHODS: We designed and conducted a randomized controlled trial involving 43 swimming specialization students aged 18-25 years. Participants were randomly allocated to two groups: a control group, which followed regular swimming training, and an experimental group, which complemented the standard training with IMT. The intervention lasted for six weeks. Key outcomes measured included swimming performance metrics (time of 50 m freestyle, number of breaths in 50 m freestyle, distance before first breath in freestyle, time of 100 m freestyle) and various inspiratory muscle function parameters such as vital capacity (VC), maximum inspiratory pressure (MIP), maximum inspiratory flow (MIF), and maximum inspiratory capacity (MIC). We also assessed certain biochemical parameters, including hemoglobin, creatine kinase (CK), blood urea nitrogen (BUN), testosterone, and cortisol concentrations. RESULTS: Following the training period, the experimental group exhibited significant improvements in swimming performance and respiratory function parameters. We also noted an increase in hemoglobin levels and a reduction in testosterone concentrations in this group, suggesting beneficial physiological adaptations in response to the combined IMT and swimming training. CONCLUSION: Our findings underline the potential of IMT as a supplementary training modality for enhancing respiratory function and improving swimming performance. The changes in biochemical parameters suggest physiological adaptations that might contribute to these observed improvements. This study opens the door for future research on the benefits of integrating IMT into training regimens for competitive swimmers. Further investigation is warranted to fully elucidate the mechanisms behind the observed benefits and to validate these findings in a larger cohort and other athlete populations.

Effects of Tai Chi Exercise on Balance Function in Stroke Patients: An Overview of Systematic Review.

Background: Tai chi (TC) has received increased attention in stroke rehabilitation, yet services are greatly underutilized. An increasing number of systematic reviews and meta-analyses (SRs/MAs) have begun to investigate the effects of TC on balance function in stroke patients. The aim of this current study was to systematically collate, appraise, and synthesize the results of these SRs/MAs using a systematic overview. Methods: Eight databases were searched: PubMed, Cochrane Library, Embase, Web of Science, CNKI, SinoMed, Chongqing VIP, and Wanfang Data. SRs/MAs of TC on balance function in stroke patients were included. Literature selection, data extraction, and assessment of the review quality were performed by two independent reviewers. Methodological quality was assessed by the Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR-2), reporting quality by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and evidence quality by Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Results: Nine SRs/MAs were included in this study. For methodological quality, what resulted in unsatisfactory methodological quality was noncompliance with critical item 4 (using a comprehensive literature search strategy) and critical item 7 (providing the list of excluded research literature). For reporting quality, what resulted in unsatisfactory reporting quality was inadequate reporting of Q1 (protocol and registration), Q8 (search), Q15 (risk of bias across studies), Q16 (additional analyses), Q22 (risk of bias across studies), Q23 (additional analysis), and Q27 (funding). For GRADE, the evidence quality was high in 0, moderate in 3, low in 11, and very low in 6. Risk of bias was the most common factor leading to downgrading of evidence, followed by inconsistency, imprecision, publication bias, and indirectness. Conclusions: TC may have beneficial effects on balance function in stroke survivors; however, this finding is limited by the generally low methodology, reporting quality, and evidence quality for published SRs/MAs.

Effects of Acute Exercise and Learning Strategy Implementation on Memory Function.

BACKGROUND AND OBJECTIVES: Long-term potentiation (LTP), the functional connectivity among neurons, is considered a mechanism of episodic memory. Both acute exercise and learning are thought to influence memory via an LTP-related mechanism. Limited research has evaluated the individual and combined effects of acute exercise and learning strategy implementation (e.g., 3-R technique, cue-integration) on memory, which was the purpose of this study. MATERIALS AND METHODS: For Experiment 1, participants (n = 80; Mage = 20.9 years) were randomized into one of four experimental groups, including Exercise + Learning (E + L), Learning Only (L), Exercise Only (E), and Control Group (C; no exercise and no learning strategy implementation). The exercise stimulus involved an acute 15-min bout of lower-intensity (60% of heart rate max) walking exercise and the learning strategy involved the implementation of the 3-R technique. Experiment 2 (n = 77; Mage = 21.1 years) replicated Experiment 1 but addressed limitations (e.g., exposure level of the memory task) from Experiment 1 and employed a higher-intensity bout of exercise (77% of heart rate max). Experiment 3 (n = 80; Mage = 21.0 years) evaluated these same four experimental conditions but employed a cue-integration learning strategy and a moderate-intensity bout of acute exercise (64% of heart rate max). RESULTS: These three experiments demonstrate that both learning techniques were effective in enhancing memory and we also provided evidence of a main effect for acute exercise (Experiment 3). However, we did not observe consistent evidence of a learning by exercise interaction effect. CONCLUSIONS: We demonstrate that both acute exercise and different learning techniques are effective in enhancing long-term memory function.