Sleep disturbance and fatigue are prevalent in nurses. Little is known about the characteristics of shift work nurses’ sleep-wake features and their subsequent impact on work performance. The study aimed to describe the characteristics of the sleep-wake index, reaction time, saliva cortisol level, and fatigue severity among female shift work nurses. This is a cross‐sectional exploratory study. A convenience sample of 152 female nurses (8-hour day-evening-night, n = 70; 12-hour day–night, n = 82) participated in this study from nine intensive care units (ICUs) from two teaching hospitals in Beijing, China. A consecutive 7-day actigraphy data were used to analyse sleep-wake indexes, including total sleep time (TST) and circadian activity rhythms (CAR). Before and after shifts, the following data were collected, psychomotor vigilance task for reaction time, saliva cortisol for the level of alertness, and self-reported fatigue severity with the Lee Fatigue Scale-Short Form. All nurses reported clinically significant fatigue severity. Compared with the 8-hour shift nurses, the 12-hour shift nurses had significantly more TST (456 vs. 364 min), higher saliva cortisol levels before the day shift (0.54 vs. 0.31), but longer reaction time before the night shift (286 vs. 277 ms). In both shifts, those with better CAR had significantly longer TST. Female nurses experienced fatigue and desynchronized CAR, especially nurses on a 12-hour shift. The CAR-friendly shift work schedule is needed to minimize the health and safety impacts of circadian misalignment for nurses. Key messages This is the first use of consecutive 7-day actigraphy data to explore the link between sleep disturbances as a stressor to CAR, salivary cortisol, and reaction time among clinical nurses. CAR may be a helpful indicator for overworked nurses, and it can serve as a modifiable target for interventions to enhance nurses’ well-being.

Childhood injury is a major public health problem around the world and those injuries have negative impacts on children and their families. The purpose of this study was to compare the behavioral characteristics between Chinese school-age children (6 to 11 years of age) with and without unintentional injuries and to identify behavioral risk factors for school-age children with unintentional injury. This cross-sectional predictive study was conducted in five elementary schools in Daqing, China. The Achenbach Child Behavior Checklist (CBCL) was used to assess the children’s behavioral characteristics. A total of 725 school-age children were screened. Of these, 116 children who had experienced unintentional injury in the past year were recruited as the study group, and 123 children who had not experienced an unintentional injury were randomly selected and assigned to the control group. The total scores of CBCL in the study group children were significantly higher than those in the control group. The significant behavior disorder predictors for unintentional injury in boys were schizoid behavior problem (OR = 2.43), anxiety/depression (OR = 2.76) and hyperactive (OR = 2.42). The predictors for unintentional injury in girls were anxiety/depression (OR = 2.12) and delinquent behavior (OR = 2.81). Children with behavior disorders are more likely to suffer from unintentional injuries. Teachers and pediatricians should identify the behavior disorders and assist parents to help children, thereby reducing the rate and severity of injuries.

Extractions of the underground parts of valerian were prepared with water and ethanol (25–95%) at 25–75 °C. Extraction yields, bioactive compounds, and the 1,1-Diphenyl-2-picrylhydrazyl (DPPH) radical scavenging ability of lyophilized extracts were determined. The inhibitory effects of the extracts, valerenic acid derivatives and phenolic acids, on metabolic syndrome (MS)-related enzymes activities were further examined. Both roots and rhizomes extracted with 95% ethanol at 75 °C had the highest levels of bioactive compounds. The antioxidant capacity and inhibition of MS-related enzymes of the roots extract were better than those of the rhizomes. The roots extract more strongly inhibited pancreatic lipase (inhibition of 50% of enzyme activity (IC₅₀), 17.59 mg/mL), angiotensin-converting enzyme (ACE, IC₅₀, 3.75 mg/mL), α-amylase (IC₅₀, 12.53 mg/mL), and α-glucosidase (IC₅₀, 15.40 mg/mL). These four phenolic acids inhibited the activity of MS-related enzymes. Valerenic acid demonstrated more of an inhibitory ability for ACE (IC₅₀, 0.225 mg/mL, except for caffeic acid) and α-glucosidase (IC₅₀, 0.617 mg/mL) than phenolic acids. Valerian extract inhibited key enzyme activities that were associated with obesity (lipase), hypertension (ACE), and type 2 diabetes (α-amylase and α-glucosidase), suggesting that it is a potential candidate for the development of functional supplements.

Objective: The aim of the study is to identify the hospitalized children at risk of peripheral intravenous catheter (PIVC) complications by severity prediction. Methods: The study included the data of 301 hospitalized children with PIVC complications in 2 tertiary teaching hospitals. A researcher-designed tool was used to collect risk factors associated with PIVC complications. Predictors of PIVC complications at univariate analysis and multivariable logistic regression analysis by backward stepwise. A nomogram was constructed based on the results of the final multivariable model, making it possible to estimate the probability of developing complications. Results: A total of 182 participants (60.5%) had a moderate injury from PIVC complications. Multivariable logistic regression analysis indicated that the vascular condition, limb immobilization, needle adjustment in venipuncture, infusion length, infusion speed, and insertion site were independent predictors. The nomogram for assessing the severity of PIVC complications indicated good predictive accuracy (area under the curve = 0.79) and good discrimination (concordance index = 0.779). Decision curve analysis demonstrated that the nomogram was a good clinical value with a wide range of threshold probabilities (4%–100%). Conclusions: The risk prediction model has good predictive performance, and the nomogram provides an easy-to-use visualization to identify the severity of PIVC complications and guide timely nursing care management.