Centralized monitoring is a risk-based remote monitoring mode that can effectively improve monitoring efficiency and quality. From July to September 2023, this study developed a centralized monitoring scheme for investigator initiated trials(IIT). This scheme utilized electronic data collection system and clinical research document management system, using programming techniques to compare the consistency of key project processes and data, monitor data filling, distribution trends, logical relationships, as well as documents such as informed consent forms, protocol violation records, and adverse event reports. It could timely identify problems in clinical trials and develop targeted response measures. From October to December 2023, 6 experts conducted centralized monitoring for 153 IIT projects using this scheme and found common issues in program execution(86 projects), ethical approvals(68 projects), and informed consent forms(67 projects), and so on. At the scome time, corresponding measures were developed. The process took a total of 20 days, with an average time of 6.27 hours per project. Compared with traditional on-site monitoring, the centralized monitoring scheme developed in this study had shown certain advantages in terms of timeliness, which could help guide the efficient implementation of on-site monitoring work and provide references for tertiary public hospitals to improve the quality of clinical trials.

Centralized monitoring is a risk-based remote monitoring mode that can effectively improve monitoring efficiency and quality. From July to September 2023, this study developed a centralized monitoring scheme for investigator initiated trials(IIT). This scheme utilized electronic data collection system and clinical research document management system, using programming techniques to compare the consistency of key project processes and data, monitor data filling, distribution trends, logical relationships, as well as documents such as informed consent forms, protocol violation records, and adverse event reports. It could timely identify problems in clinical trials and develop targeted response measures. From October to December 2023, 6 experts conducted centralized monitoring for 153 IIT projects using this scheme and found common issues in program execution(86 projects), ethical approvals(68 projects), and informed consent forms(67 projects), and so on. At the scome time, corresponding measures were developed. The process took a total of 20 days, with an average time of 6.27 hours per project. Compared with traditional on-site monitoring, the centralized monitoring scheme developed in this study had shown certain advantages in terms of timeliness, which could help guide the efficient implementation of on-site monitoring work and provide references for tertiary public hospitals to improve the quality of clinical trials.

ObjectiveTo study the relationship between occupational stress/sleep quality and job satisfaction of internet enterprise programmers， to explore the mediating effect of sleep quality between occupational stress and job satisfaction， and to provide a theoretical basis for taking effective measures to improve job satisfaction. MethodsA total of 271 programmers from an Internet company in Shanghai were investigated by job content questionnaire， Pittsburgh Sleep Index Scale and the third part of the McLean occupational stress questionnaire. The results were statistically analyzed ResultsThe positive rate of occupational stress of programmers in this enterprise was 66.7%， 34.3% of them had average sleep quality， 28.0% had poor sleep quality， and the score of job satisfaction was 47.70±6.78. Correlation analysis showed that the higher the occupational stress， the worse the sleep quality and the lower the job satisfaction. Effects of occupational stress and sleep quality on job satisfaction were both statistically significant. The total effect of occupational stress on job satisfaction was -0.35， and the mediating effect of sleep quality between occupational stress and job satisfaction was -0.04， accounting for 12.0% of the total effect. ConclusionSleep quality of internet enterprise programmers plays a partial mediating role between occupational stress and job satisfaction， and a series of measures such as improving sleep can be taken to improve programmer’s job satisfaction.

ObjectiveTo develop a professional occupational stress scale for medical staff （CSSM） and test its reliability and validity， so as to provide a technical tool for the evaluation and management of medical staff occupational stress. MethodsThe initial index item pool was formed by literature retrieval， in-depth interview and expert evaluation. Pre-survey questionnaires were distributed in April 2021， stratified sampling was used to randomly select 1 tertiary hospital， 2 secondary hospitals and 1 community health service center in Shanghai. Sampling was performed according to the number of medical staff in all level hospitals and the proportion of doctors， nurses and medical technicians. 848 valid questionnaires were collected. Item differentiation method， correlation analysis and exploratory factor analysis were used to filter the pre-survey item pool and form a formal scale. From June to July 2021， stratified sampling method was used to carry out formal survey with formal scale， and the reliability and validity of the scale were verified. A total of 5 510 valid questionnaires were collected. Confirmatory factor analysis was used to test the construct validity of the scale. Job burnout， sleep disorder and job demand-autonomy （-support） model occupational stress scales were used as calibration scales， respectively. Pearson correlation analysis was used to test the scale's calibration validity and aggregate validity， and Cronbach's α coefficient was used to evaluate the scale's reliability. ResultsThrough project differentiation method， correlation analysis， exploratory factor analysis on the preliminary survey item pool， we produced the formal scale of7 dimensions and 32 items， respectively， including "career development"， "interpersonal relationship"， "working overtime and work-life imbalance"， "physical environment"， "the doctor-patient relationship"， "social environment"， "work load". The cumulative variance contribution rate of common factors in exploratory factor analysis was 65.937%， and the factor loading value of each item ranged from 0.513 to 0.880. The scale was used for formal investigation to verify the reliability and validity of the scale. The goodness of fit index （GFI）， comparative fit index （CFI） and root mean square error of approximation （RMSEA） were 0.913， 0.909 and 0.064， respectively. The scores of the scale and all dimensions were positively correlated with the scores of occupational stress in the mode of job burnout， sleep disorder symptoms and job demand-autonomy （r=0.235‒0.754， P<0.05）. The Cronbach's α coefficients of the total amount table and each dimension ranged from 0.743 to 0.937， showing good reliability and validity. ConclusionCSSM has good reliability and validity， which provides a measurement and assessment tool for the targeted prevention of occupational stress in medical staff. The popularization and use of this scale in other regions need further verification.