Relationship between acute stress and sleep disorder in grass-root military personnel:Mediating effect of social support

Background: To explore the relationship between acute stress, social support and sleep disorder in grass-root military personnel, and construct the relational model through structural equation modeling. Methods: A total of 2,411 grass-root military personnel were randomly selected by cluster sampling, and administered the Chinese Military Personnel Sleep Disorder Scale, Military Acute Stress Scale and Social Support Rating Scale.Results: The total score of acute stress scale was positively correlated with the total score and factor scores of sleep disorder scale(r=0.209~0.465, P【0.01); The total score of social support scale was positively correlated with the total score of acute stress scale and the total score and factor scores of sleep disorder scale(r=0.356~0.537, P【0.01). The analysis of mediating effects showed that lack of social support partially mediated between acute stress and the factors of sleep disorder. The analysis of structural equation model showed that acute stress not only had a direct effect on sleep disorder(the path coefficient was 0.29, P=0.000), but also on lack of social support(the path coefficient was 0.39, P=0.000); lack of social support had a direct effect on sleep disorder(the path coefficient was 0.48, P=0.000).Conclusions: Acute stress and lack of social support are two significant factors of sleep disorder in grass-root military personnel. Well-established social support could alleviate sleep disorder induced by acute stress. Lack of social support was a partial mediator between acute stress and sleep disorder.

Artificial intelligence meets traditional Chinese medicine: a bridge to opening the magic box of sphygmopalpation for pulse pattern recognition

Artificial intelligence(AI) aims to mimic human cognitive functions and execute intellectual activities like that performed by humans dealing with an uncertain environment. The rapid development of AI technology provides powerful tools to analyze massive amounts of data, facilitating physicians to make better clinical decisions or even replace human judgment in healthcare.Advanced AI technology also creates novel opportunities for exploring the scientific basis of traditional Chinese medicine(TCM) and developing the standardization and digitization of TCM pulse diagnostic methodology. In the present study, we review and discuss the potential application of AI technology in TCM pulse diagnosis. The major contents include the following aspects:(1) a brief introduction of the general concepts and knowledge of TCM pulse diagnosis or palpation,(2) landmark developments in AI technology and the applications of common AI deep learning algorithms in medical practice,(3) the current progress of AI technology in TCM pulse diagnosis,(4) challenges and perspectives of AI technology in TCM pulse diagnosis. In conclusion, the pairing of TCM with modern AI technology will bring novel insights into understanding the scientific principles underlying TCM pulse diagnosis and creating opportunities for the development of AI deep learning technology for the standardization and digitalization of TCM pulse diagnosis.

Risk of group aggregative behavior during COVID-19 outbreak: A case report

BACKGROUND At the end of 2019,a new epidemic of viral pneumonia emerged in China and was determined to be caused by a novel coronavirus,which was named coronavirus disease 2019(COVID-19)by the World Health Organization.The epidemic quickly spread,causing a worldwide pandemic.Scientists and clinicians across the globe have shifted their research efforts towards understanding the virus itself and its epidemiology.CASE SUMMARY In mid-January 2020,a Chinese family made a visit to a local city,and within the next 2 wk one after another fell ill with COVID-19.At the beginning of their first illness onset,the family had eaten in a restaurant,which led to the subsequent illness onset in another two families.All cases were diagnosed as COVID-19 by real-time fluorescent reverse transcription-polymerase chain reaction.Epidemiological investigation showed that the transmission chain was complete.CONCLUSION This chain of social exposure highlights the danger of group aggregative behavior for spread of COVID-19.