The rapid growth in the use of social media applications on the internet has significant impacts on mental health, especially among university students. This study aims to explore the network characteristics and core symptoms between social media addiction, mental health issues (anxiety, depression, stress), and academic burnout. Understanding these relationships is crucial for enhancing psychological interventions and improving academic performance in the digital age. A cross-sectional study was conducted with undergraduates and doctoral students from Air Force Medical University. Participants (n = 432) completed self-report scales, including the Depression Anxiety and Stress Scale, Academic Burnout Inventory, and Bergen Social Media Addiction Scale. Network analysis was performed using R to model the relationships between study variables, employing Gaussian Graphical Models and the least absolute shrinkage and selection operator technique for robust network estimation. Bridge Expected Influence results indicate that “Depression” is consistently the most central node, playing a critical role in the network connecting social media addiction, academic burnout, and psychological stress. The study reveals a significant positive correlation between social media addiction and both academic burnout and mental health issues. Particularly, excessive use of social media can distract students, leading to academic burnout, and exacerbating feelings of anxiety and depression. Social media addiction has a significant impact on the psychological health and academic performance of college students. This study highlights the potential risks associated with social media usage behaviors and provides a scientific basis for developing related intervention measures. These interventions aim to help college students reduce their dependence on social media, thereby restoring a healthy state of life and study.

Introduction: It is clear that mental fatigue can have many negative impacts on individuals, such as impairing cognitive function or affecting performance. The aim of this study was to investigate the role of sound interventions in combating mental fatigue. Method: The subjects were assessed on various scales, a psychomotor vigilance task (PVT) task, and a 3 min resting-state electroencephalogram (EEG), followed by a 20 min mental fatigue–inducing task (Time Load Dual Back, TloadDback), during which subjects in different condition groups listened to either 15 Hz binaural beats, 40 Hz binaural beats, relaxing music, or a 240 Hz pure tone. After the mental fatigue–inducing task, subjects were again assessed on various scales, a PVT task, and a 3 min resting-state EEG. Results: After the fatigue-inducing task, there was no significant difference between the four groups on the scales or the PVT task performance. In TloadDback, the accuracy rate of the 40 Hz binaural beats group and the relaxing music group decreased in the middle stage of the task, while the 15 Hz binaural beats group and the 240 Hz pure tone group remained unchanged in all stages of the task. The EEG results showed that after fatigue inducement, the average path length of the 15 Hz binaural beats group decreased, and local efficiency showed an increasing tendency, indicating enhanced brain network connectivity. Meanwhile, the 240 Hz pure tone group showed enhanced functional connectivity, suggesting a state of mental fatigue in the group. Conclusions: The results of this study show that listening to 15 Hz binaural beats is a proven intervention for mental fatigue that can contribute to maintaining working memory function, enhancing brain topological structure, and alleviating the decline in brain function that occurs in a mentally fatigued state. As such, these results are of great scientific and practical value.

(1) Background: The combined n-back + Go/NoGo paradigm was used to investigate whether audiovisual interactions interfere with or facilitate WM. (2) Methods: College students were randomly assigned to perform the working memory task based on either a single (visual or auditory) or dual (audiovisual) stimulus. Reaction times, accuracy, and WM performance were compared across the two groups to investigate effects of audiovisual interactions. (3) Results: With low cognitive load (2-back), auditory stimuli had no effect on visual working memory, whereas visual stimuli had a small effect on auditory working memory. With high cognitive load (3-back), auditory stimuli interfered (large effect size) with visual WM, and visual stimuli interfered (medium effect size) with auditory WM. (4) Conclusions: Audiovisual effects on WM follow the resource competition theory, and the cognitive load of a visual stimulus is dominated by competition; vision always interferes with audition, and audition conditionally interferes with vision. With increased visual cognitive load, competitive effects of audiovisual interactions were more obvious than those with auditory stimuli. Compared with visual stimuli, audiovisual stimuli showed significant interference only when visual cognitive load was high. With low visual cognitive load, the two stimulus components neither facilitated nor interfered with the other in accordance with a speed–accuracy trade-off.

Background: This research analyses the relations between anxiety symptoms from the network perspective to deepen the understanding of anxiety in front-line medical staff during the COVID-19 pandemic and can also provide a reference for determining potential goals of clinical interventions. Methods: A convenience sampling was adopted, and the Generalized Anxiety Disorder 7-item scale (GAD-7) was administered to front-line medical staff through online platforms. A regularized partial correlation network of anxiety was constructed and then we evaluated its accuracy and stability. The expected influence and predictability were used to describe the relative importance and the controllability, using community detection to explore community structure. The gender-based differences and the directed acyclic graph were implemented. Results: The connections between A1 “Feeling nervous, anxious or on edge” and A2 “Not being able to stop or control worrying”, A6 “Becoming easily annoyed or irritable” and A7 “Feeling afraid as if something awful might happen”, etc., were relatively strong; A2 “Not being able to stop or control worrying” and A3 “Worrying too much about different things” had the highest expected influence, and A2 “Not being able to stop or control worrying” had the highest predictability. The community detection identified two communities. The results of the gender network comparison showed the overall intensity of the anxiety network in women was higher than that in men; DAG indicated that A2 “Not being able to stop or control worrying” had the highest probabilistic priority; the lines from A2 “Not being able to stop or control worrying” to A1 “Feeling nervous, anxious or on edge” and A2 “Not being able to stop or control worrying” to A7 “Feeling afraid as if something awful might happen” represented the most important arrows. Conclusion: There exist broad interconnections among anxiety symptoms of front-line medical staff on the GAD-7. A2 “Not being able to stop or control worrying” might be the core symptom and a potential effective intervention target. It was possible to bring an optimal result for the entire GAD symptom network by interfering with A2 “Not being able to stop or control worrying”. GAD may have two “subsystems”. The modes of interconnection among anxiety may be consistent between genders.

Background: Anxiety and depression have significant impacts on individuals’ mental health and social functioning, particularly among college students. Psychological resilience is considered a crucial resource for coping with adversity and stress and may play a key role in alleviating anxiety and depression symptoms. The aim of this study is to explore the finer-grained potential relationships between psychological resilience, anxiety, and depression among college students.Methods: This study employed network analysis to examine the psychological resilience, anxiety, and depression status of a randomly sampled cohort of 855 college students (51.8% female; M = 18.70, SD = 1.13). Statistical analyses and network visualization were conducted using R version 4.2.2 and the qgraph package. Bridge centrality indices of variables within the network were computed, with particular emphasis on the significance of bridge symptoms within the network structure.Results: Significant covariation was observed between anxiety and depression symptoms. Psychological resilience exhibited a negative correlation with both anxiety and depression, with a negative bridge expected influence value for R10 “Can handle unpleasant feelings”, indicating a potential protective role of psychological resilience in mitigating these mental health issues. R10 “Can handle unpleasant feelings” occupies the most central position within the psychological resilience network, with the smallest BEI value (-0.01), indicating its protective role in the overall network. To some extent, it can regulate anxiety and depression symptoms.Conclusion: This study highlights the complex interrelationships between psychological resilience, anxiety, and depression among college students through network analysis. Bridge expected influence analysis identified “R10” as a protective factor and “A7” as a key risk factor. The findings suggest that interventions targeting bridge symptoms and enhancing resilience may help alleviate anxiety and depression. Prioritizing these two symptoms in future research could yield greater intervention benefits.

Objectives: With the advancement of modern society, people in cognitively demanding jobs are increasingly exposed to occupational stress. Prolonged and high-intensity cognitive activities are prone to inducing mental fatigue (MF), which adversely affects both psychological and physiological well-being, as well as task performance. Existing methods for inducing MF often demonstrate limited effectiveness due to insufficient cognitive load from overly simplistic tasks and the potential emotional disturbance caused by prolonged task duration. This study aims to explore a comprehensive cognitive task paradigm that integrates task complexity and time pressure, thereby developing a novel and effective method for inducing MF based on high mental workload (HMW) and the effects of time on task (ToT). Methods: Using convenience sampling, university students from a medical college were recruited as participants. The study was conducted in three steps. In the first step, we constructed a 1-back Stroop (BS) task paradigm by designing tasks with varying levels of complexity and incorporating time pressure through experimental manipulation. In the second step, the efficacy of the BS task paradigm was validated by comparing it with the traditional 2-back cognitive task in inducing HMW. In the third step, an MF induction protocol was established by combining the BS task paradigm with the ToT effect (i.e., a continuous 30 min task). Effectiveness was assessed using validated subjective measures (NASA Task Load Index [NASA-TLX] and Visual Analog Scale [VAS]) and objective behavioral metrics (reaction time and accuracy). Statistical analyses were performed using analysis of variance (ANOVA) and t-tests. Results: The BS task paradigm, which integrates complex cognitive abilities such as attention, working memory, inhibitory control, cognitive flexibility, and time pressure, demonstrated significantly higher NASA-TLX total scores, as well as elevated scores in mental demand, temporal demand, performance, and frustration scales, compared to the 2-back task. Additionally, the BS task paradigm resulted in longer reaction times and lower accuracy. As the BS task progressed, participants exhibited significant increases in mental fatigue (MF), mental effort (ME), mental stress (MS), and subjective feelings of fatigue, while the overall number of correct trials and accuracy showed a significant decline. Furthermore, reaction times in the psychomotor vigilance test (PVT) were significantly prolonged, and the number of lapses significantly increased between pre- and post-task assessments. Conclusions: The BS task paradigm based on complex cognitive abilities and time pressure could effectively induce an HMW state. Combined with the ToT effect, the BS paradigm demonstrated effective MF induction capabilities. This study provides a novel and reliable method for inducing HMW and MF, offering a valuable tool for future research in related fields.