Postpartum fatigue is an important issue that threatens women’s health.The incidence of postpartum fatigue is high.Failure to intervene in time may lead to adverse outcomes such as postpartum depression,premature ter...Postpartum fatigue is an important issue that threatens women’s health.The incidence of postpartum fatigue is high.Failure to intervene in time may lead to adverse outcomes such as postpartum depression,premature termination of breastfeeding,child abuse,and low infant development.This article reviews the concepts,characteristics,related factors,adverse effects,and interventions of postpartum fatigue.The aim is to improve doctors’and nurses’awareness of on postpartum fatigue in pregnant women,enrich the research content and methods,stimulate the interest of nurses,and actively carry out targeted intervention research to prevent or reduce the occurrence of adverse outcomes.展开更多
In analyzing data from clinical trials and longitudinal studies, the issue of missing values is always a fundamental challenge since the missing data could introduce bias and lead to erroneous statistical inferences. ...In analyzing data from clinical trials and longitudinal studies, the issue of missing values is always a fundamental challenge since the missing data could introduce bias and lead to erroneous statistical inferences. To deal with this challenge, several imputation methods have been developed in the literature to handle missing values where the most commonly used are complete case method, mean imputation method, last observation carried forward (LOCF) method, and multiple imputation (MI) method. In this paper, we conduct a simulation study to investigate the efficiency of these four typical imputation methods with longitudinal data setting under missing completely at random (MCAR). We categorize missingness with three cases from a lower percentage of 5% to a higher percentage of 30% and 50% missingness. With this simulation study, we make a conclusion that LOCF method has more bias than the other three methods in most situations. MI method has the least bias with the best coverage probability. Thus, we conclude that MI method is the most effective imputation method in our MCAR simulation study.展开更多
文摘Postpartum fatigue is an important issue that threatens women’s health.The incidence of postpartum fatigue is high.Failure to intervene in time may lead to adverse outcomes such as postpartum depression,premature termination of breastfeeding,child abuse,and low infant development.This article reviews the concepts,characteristics,related factors,adverse effects,and interventions of postpartum fatigue.The aim is to improve doctors’and nurses’awareness of on postpartum fatigue in pregnant women,enrich the research content and methods,stimulate the interest of nurses,and actively carry out targeted intervention research to prevent or reduce the occurrence of adverse outcomes.
文摘In analyzing data from clinical trials and longitudinal studies, the issue of missing values is always a fundamental challenge since the missing data could introduce bias and lead to erroneous statistical inferences. To deal with this challenge, several imputation methods have been developed in the literature to handle missing values where the most commonly used are complete case method, mean imputation method, last observation carried forward (LOCF) method, and multiple imputation (MI) method. In this paper, we conduct a simulation study to investigate the efficiency of these four typical imputation methods with longitudinal data setting under missing completely at random (MCAR). We categorize missingness with three cases from a lower percentage of 5% to a higher percentage of 30% and 50% missingness. With this simulation study, we make a conclusion that LOCF method has more bias than the other three methods in most situations. MI method has the least bias with the best coverage probability. Thus, we conclude that MI method is the most effective imputation method in our MCAR simulation study.
