A Mixed Methods Investigation of the Prevalence and Influencing Factors of Compassion Fatigue among Midwives in Different Areas of China.

Objective: Exploring the influencing factors of compassion fatigue among midwives to prevent compassion fatigue from occurring and improve their mental health. Methods: A method integrating the quantitative research method and qualitative research method is used. For the quantitative research, a cross-sectional study was carried out. State-run hospitals from three economic areas in China were selected as investigation scope from June 2018 to May 2021. A total of 515 midwives were chosen randomly from three economic areas. SPSS 22.0 was used for data cleaning and statistical description and analysis. The influencing factors of compassion fatigue among midwives were analyzed by fitting these two-level logistic models. For qualitative research, purposive sampling and maximum variation strategy were used to select midwives with mild or above compassion fatigue in the questionnaire survey. Field study and interviews were used to collect data. Results: The results in the quantitative research showed that 515 valid questionnaires were received with 82.14% of midwives whose compassion fatigue were moderate or above. Multilevel statistical model analysis demonstrated that hospital level, children situation, area, working atmosphere, experiences of traumatic delivery, sleep quality, and social support level had impacts on the degree of midwives' compassion fatigue (p < 0.05). The result in the qualitative research showed that 34 midwives were interviewed, and 7 topic ideas were refined. Conclusion: Overall, the incidence of compassion fatigue among midwives is high. Risk factors influencing the degree of midwives' compassion fatigue include lower social support, disharmonious working atmosphere, toddler situation, huge workload, experiences of traumatic delivery, and poor quality of sleep.

Downregulation of LEMD1-AS1 and Its Influences on the Diagnosis, Prognosis, and Immune Infiltrates of Epithelial Ovarian Cancer.

Previous studies have confirmed long noncoding RNA LEMD1-AS1 (LEMD1-AS1) as a functional factor in several tumors. The present work is aimed at exploring the prognostic and diagnostic values of LEMD1-AS1 in patients with epithelial ovarian cancer (EOC). We examined the expressions of LEMD1-AS1 in pan-cancer from TCGA microarray datasets and GTEx Project. The expressions of LEMD1-AS1 were detected by qRT-PCR in EOC specimens and normal ovarian specimens from 30 EOC patients. The χ 2 test was applied to compare the clinicopathological characteristics of different groups. ROC curves were established to determine the diagnostic values of LEMD1-AS1 in screening EOC tissues. The association of LEMD1-AS1 expression with clinical outcome was determined by the Kaplan-Meier methods and COX assays. A decreased expression of LEMD1-AS1 was observed in EOC tissues compared to matched normal specimens (p < 0.01). Low LEMD1-AS1 expression could be used to distinguish EOC from adjacent normal specimens. A clinical study revealed that patients with low LEMD1-AS1 expression have a shorter overall survival (p = 0.035) and progress-free interval (p = 0.041) than those with high LEMD1-AS1 expression. The Spearman correlation test revealed that LEMD1-AS1 expressions were negatively associated with the expressions of neutrophil and myeloid dendritic cell. Overall, our finding suggested that LEMD1-AS1 may have potential roles as a potential biomarker and/or a therapeutic target in EOC.