Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective: Self-determination theory (SDT) deems that people have three causality orientations: autonomy orientation, control orientation, and impersonal orientation. Previous studies suggested that lower autonomy orientation or higher control and impersonal orientations may be associated with more addictive behaviors. Our study aimed to investigate if these associations exist in Internet gaming disorder (IGD), and if sensation seeking, anxiety, and depression could influence the associations between causality orientations and IGD symptoms. Methods: A total of 1,400 college students completed the Internet Gaming Disorder Scale, General Causality Orientation Scale, Brief Sensation Seeking Scale, Generalized Anxiety Disorder Scale, and Patient Health Questionnaire. Correlation, multiple linear regressions, structural equation model (SEM) analyses, and moderation analyses were conducted to explore the associations. Results: The control and impersonal orientations were positively associated with IGD symptoms, while the autonomy orientation was negatively associated with them. Moreover, SEM analyses showed that the autonomy-IGD relationship was totally mediated by anxiety and depression, the impersonal-IGD relationship was partially mediated by anxiety, and the control-IGD relationship was partially mediated by depression. Finally, the effects of causality orientations on IGD were moderated by sensation seeking. Conclusion Overall, autonomy orientation is linked to fewer gaming problems, whereas control and impersonal orientations are associated with more gaming problems. Moreover, the relationships between causality orientations and IGD symptoms are mediated by anxiety and depression and moderated by sensation seeking. Our findings inform theory on the motivations of gaming behaviors and may shed light on the prevention and intervention of IGD from the perspective of SDT.

Objective: Self-determination theory (SDT) deems that people have three causality orientations: autonomy orientation, control orientation, and impersonal orientation. Previous studies suggested that lower autonomy orientation or higher control and impersonal orientations may be associated with more addictive behaviors. Our study aimed to investigate if these associations exist in Internet gaming disorder (IGD), and if sensation seeking, anxiety, and depression could influence the associations between causality orientations and IGD symptoms. Methods: A total of 1,400 college students completed the Internet Gaming Disorder Scale, General Causality Orientation Scale, Brief Sensation Seeking Scale, Generalized Anxiety Disorder Scale, and Patient Health Questionnaire. Correlation, multiple linear regressions, structural equation model (SEM) analyses, and moderation analyses were conducted to explore the associations. Results: The control and impersonal orientations were positively associated with IGD symptoms, while the autonomy orientation was negatively associated with them. Moreover, SEM analyses showed that the autonomy-IGD relationship was totally mediated by anxiety and depression, the impersonal-IGD relationship was partially mediated by anxiety, and the control-IGD relationship was partially mediated by depression. Finally, the effects of causality orientations on IGD were moderated by sensation seeking. Conclusion Overall, autonomy orientation is linked to fewer gaming problems, whereas control and impersonal orientations are associated with more gaming problems. Moreover, the relationships between causality orientations and IGD symptoms are mediated by anxiety and depression and moderated by sensation seeking. Our findings inform theory on the motivations of gaming behaviors and may shed light on the prevention and intervention of IGD from the perspective of SDT.