"We hear and we fear" - Insights of 1203 Women on Personnel Conversations During Cesarean Delivery
MATERNAL AND CHILD HEALTH JOURNAL(2024)
摘要
Objective To assess the preferences of women undergoing cesarean delivery regarding intraoperative conversations among healthcare personnel.Methods This cross-sectional study was conducted by distribution of an open anonymous questionnaire on social media platforms during March 2022, targeting respondents with a history of cesarean delivery. The primary outcome was patients' experience of "being disturbed by professional and casual conversations of the personnel", rated on a 1-5 Likert scale.Results 1203 participants completed the questionnaire, with 97.6% reporting intraoperative conversations among personnel. Casual conversations were perceived as "disturbing" by more respondents vs. professional talk (33.4% vs. 27.6%, respectively, p = 0.0077). Logistic regression analysis revealed associations between feeling disturbed and higher intraoperative stress and pain - adjusted Odds Ratio (OR) 3.1, 95% confidence interval (CI) 2.1-4.5, and OR 2.7, 95%CI 1.8-4.0, respectively, for professional conversations; OR 3.0, 95%CI 2.0-4.4, and OR 1.7, 95%CI 1.1-2.7, respectively, for casual conversations. Feeling disturbed by professional conversations was also associated with urgent vs. elective operations (OR 2.0, 95%CI 1.4-3.0). Direct personnel-patient communication was associated with significantly lower stress levels (60.8% vs. 72.5% in the remaining cohort, p < 0.001).Discussion Intraoperative conversations of the personnel occur during vast majority of cesarean deliveries. Given that a substantial proportion of patients find these conversations disturbing, it is advisable to conduct a preliminary assessment of maternal preferences. This proactive step can help tailor communication strategies to individual patient comfort and preferences, ultimately enhancing the birthing experience and maternal well-being.
更多查看译文
关键词
Cesarean delivery,Communication,Patient's experience
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要