Research in Nursing & Health最新文献

Currently, the number of pregnant women at high risk for gestational diabetes mellitus (GDM) and using assisted reproductive technology (ART) is increasing. The present study aims to explore the relationship between ART and physical activity in Chinese pregnant women at high risk for GDM in early pregnancy. A cross-sectional study was conducted in a regional teaching hospital in Guangzhou, China, between July 2022 and March 2023. Three hundred fifty-five pregnant women at high risk for GDM in early pregnancy completed the Chinese version of the Pregnant Physical Activity Questionnaire (PPAQ), the Pregnancy Physical Activity Knowledge Scale, the Pregnancy Physical Activity Self-Efficacy Scale, the Pregnancy Physical Activity Social Support Scale, and a sociodemographic and obstetric characteristics data sheet. Compared to women who conceived naturally, women who used ART were more likely to be 35 years or older, unemployed, primigravidae, and to have intentionally planned their pregnancies. Women who used ART had significantly lower levels of physical activity and self-efficacy compared to their counterparts who conceived naturally. Over half (55.6%) of women who used ART reported being physically inactive, and those with lower self-efficacy, as well as the unemployed, were significantly more likely to be inactive. Physical inactivity is a critical clinical issue among women who use ART, especially in the context of GDM risk. Future research should develop and test physical activity programs, including enhancing physical activity self-efficacy for women who use ART. Patient or public contribution: In this study, survey questionnaires were completed by participants among Chinese pregnant women at high risk for GDM in early pregnancy.

This study was to describe the cognitive function status in patients with depressive disorder and to construct a nomogram model to predict the risk factors of cognitive impairment in these patients. From October 2019 to February 2021, a total of 141 patients with depressive disorder completed the survey in two hospitals. The Montreal cognitive assessment (MoCA) was used with a cutoff score of 26 to differentiate cognitive impairment. Univariable and multivariable logistic regression analyses were conducted to identify independent risk factors. A nomogram was then constructed based on the results of the multivariable logistic regression analysis. The patients had an average MoCA score of 23.99 ± 3.02. The multivariable logistic regression analysis revealed that age (OR: 1.096, 95% CI: 1.042-1.153, p < 0.001), education (OR: 0.065, 95% CI: 0.016-0.263, p < 0.001), depression severity (OR: 1.878, 95% CI: 1.021-3.456, p = 0.043), and sleep quality (OR: 2.454, 95% CI: 1.400-4.301, p = 0.002) were independent risk factors for cognitive impairment in patients with depressive disorder. The area under receiver operating characteristic (ROC) curves was 0.868 (95% CI: 0.807-0.929), indicating good discriminability of the model. The calibration curve of the model and the Hosmer-Lemeshow test (p = 0.571) demonstrated a well-fitted model with high calibration. Age, education, depression severity, and sleep quality were found to be significant predictors of cognitive function. A nomogram model was developed to predict cognitive impairment in patients with depressive disorder, providing a solid foundation for clinical interventions.