Effects of smartphone-based hypnotic intervention for undergraduate students' shyness during the COVID-19 pandemic: A randomized controlled trial.

BACKGROUND: Since the outbreak of the COVID-19 pandemic, university students have been exposed to a heightened vulnerability towards developing psychological issues, such as psychological distress and shyness. Internet-based interventions offer a convenient avenue for scalability, thus prompting the development of a smartphone-based hypnotic intervention aimed at addressing shyness among university students. OBJECTIVE: We devised an innovative smartphone-based hypnotic intervention called mHypnosis to examine its impact on shyness among undergraduate students. Furthermore, we aimed to investigate whether the apprehension of negative evaluations before treatment could serve as a predictor for the effectiveness of the intervention on shyness. METHODS: Eighty students with high shyness scores were randomly assigned to the experimental group and the control group. Another 40 participants with low shyness score were selected as the baseline group. The Shyness Scale (SS), Fear of Negative evaluation scale (FNE), Self-Acceptance Questionnaire (SAQ), and Self-Esteem Scale (SES) were used to evaluate the effect of hypnotic intervention. RESULTS: Before the intervention, the scores of the experimental and control groups on the SS, FNE, SAQ, and SES were higher than those in the baseline group (p < 0.05). There was no significant difference in scores between the experimental and control group (p > 0.05). After the intervention, the scores of the SS, FNE, SAQ, and SES were significantly lower in the experimental group than those in the control group (p < 0.05). The pretest score of FNE could predict the shyness score after hypnotic intervention (B = 0.35, p < 0.05). CONCLUSION: Smartphone-based hypnotic intervention had a significant effect on ameliorating shyness during the COVID-19 pandemic; fear of negative evaluation can be a target for treating shyness.

Analyzing 20 years of Resting-State fMRI Research: Trends and collaborative networks revealed.

Resting-state functional magnetic resonance imaging (rs-fMRI), initially proposed by Biswal et al. in 1995, has emerged as a pivotal facet of neuroimaging research. Its ability to examine brain activity during the resting state without the need for explicit tasks or stimuli has made it an integral component of brain imaging studies. In recent years, rs-fMRI has witnessed substantial growth and found widespread application in the investigation of functional connectivity within the brain. To delineate the developmental trajectory of rs-fMRI over the past two decades, we conducted a comprehensive analysis using bibliometric tool Citespace. Our analysis encompassed publication trends, authorship networks, institutional affiliations, international collaborations, as well as emergent themes in references and keywords. Our study reveals a remarkable increase in the volume of rs-fMRI publications over the past two decades, underscoring the burgeoning interest and potential within this field. Harvard University stands out as the institution with the highest number of research papers published in the realm of RS-fMRI, while the United States holds the highest overall influence in this domain. The recent emergence of keywords such as "machine learning" and "default mode," coupled with citation surges in reference to rs-fMRI, have paved new avenues for research within this field. Our study underscores the critical importance of integrating machine learning techniques into rs-fMRI investigations, offering valuable insights into brain function and disease diagnosis. These findings hold profound significance for the field of neuroscience and may furnish insights for future research employing rs-fMRI as a diagnostic tool for a wide array of neurological disorders, thus emphasizing its pivotal role and potential as a tool for investigating brain functionality.