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电子学习对药物依赖孕妇的临床管理对助产士知识和临床技能表现的影响:一项随机对照试验。

Effect of E-learning clinical management of substance-dependent pregnant women on the knowledge and clinical skill performance of midwives: a randomized controlled trial.

作者信息

Heidarian Hasti, Mehrabi Manoosh, Ghaemmaghami Parvin, Janghorban Roksana

机构信息

Student Research Committee, Department of Midwifery, School of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran.

Department of E-Learning Planning in Medical Sciences, Virtual School, Shiraz University of Medical Sciences, Shiraz, Iran.

出版信息

BMC Pregnancy Childbirth. 2025 Jan 8;25(1):11. doi: 10.1186/s12884-024-07130-6.

Abstract

BACKGROUND

Drug use during pregnancy and post-partum undoubtedly significantly affects maternal and infant morbidity. Healthcare providers, especially midwives who care for pregnant and postpartum women, must possess adequate knowledge and clinical skills to manage their patients appropriately. This study aimed to determine the effect of an e-learning intervention on midwives' knowledge and clinical performance skills in caring for substance-dependent pregnant women during labor and post-partum.

METHODS

A randomized controlled trial based on e-learning was conducted in Shiraz, Iran. One hundred midwives working in governmental maternity hospitals were recruited and randomly assigned to the intervention (n = 50) or control (n = 50) group through blocked randomization. The intervention group underwent e-learning for 4 weeks on clinical considerations during labor and post-partum of substance-dependent mothers. The control group received no educational intervention from the research group. Pre-test, post-test, and one-month retention tests included a knowledge assessment questionnaire and an objective structured clinical examination test to assess clinical skill performance in both groups. The data were analyzed using SPSS 16 software at a significance level of P < .05. Analysis of variance with repeated measures was used to compare the mean data between and within the groups.

RESULTS

A total of 93 midwives with a mean age of 36.78 ± 8.06 years were recruited and randomly assigned to the control group (n = 47) and the intervention group (n = 46). Seven midwives dropped out for different reasons. Immediately after and one month after the intervention, both the level of knowledge and the level of clinical skill performance of the midwives in the intervention group increased compared to those before the intervention (P < .001) and compared to those in the control group (P < .001). The knowledge of the intervention group in the one-month retention test was significantly reduced compared to that immediately after the intervention (P < .001), but clinical skill performance in the intervention group at one month after the intervention was not significantly different from that immediately after the intervention (P = 1.00).

CONCLUSIONS

E-learning about clinical considerations during labor and post-partum in substance-dependent mothers can be an effective way to improve midwives' knowledge and clinical skill performance. Although knowledge decreased one month after training, clinical skill performance improved.

TRIAL REGISTRATION

http://www.irct.ir/ , IRCT20180928041164N1 registered November 13, 2018.

摘要

背景

孕期和产后用药无疑会显著影响母婴发病率。医疗服务提供者,尤其是照顾孕妇和产后妇女的助产士,必须具备足够的知识和临床技能以妥善管理患者。本研究旨在确定电子学习干预对助产士在护理分娩期和产后药物依赖孕妇方面的知识及临床操作技能的影响。

方法

在伊朗设拉子进行了一项基于电子学习的随机对照试验。招募了100名在政府妇产医院工作的助产士,并通过区组随机化将其随机分为干预组(n = 50)和对照组(n = 50)。干预组就药物依赖母亲分娩期和产后的临床注意事项进行了4周的电子学习。对照组未接受研究组的任何教育干预。前测、后测和为期一个月的留存测试包括一份知识评估问卷和一项客观结构化临床考试,以评估两组的临床技能操作。使用SPSS 16软件对数据进行分析,显著性水平为P < 0.05。采用重复测量方差分析来比较组间和组内的均值数据。

结果

共招募了93名平均年龄为36.78 ± 8.06岁的助产士,并将其随机分为对照组(n = 47)和干预组(n = 46)。7名助产士因不同原因退出。干预后即刻及干预后一个月,干预组助产士的知识水平和临床技能操作水平与干预前相比均有所提高(P < 0.001),且与对照组相比也有所提高(P < 0.001)。干预组在为期一个月的留存测试中的知识水平与干预后即刻相比显著降低(P < 0.001),但干预组在干预后一个月的临床技能操作与干预后即刻相比无显著差异(P = 1.00)。

结论

关于药物依赖母亲分娩期和产后临床注意事项的电子学习可以是提高助产士知识和临床技能操作的有效方法。尽管培训后一个月知识有所下降,但临床技能操作有所提高。

试验注册

http://www.irct.ir/ ,IRCT20180928041164N1,于2018年11月13日注册。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b696/11707862/a70a4a37babf/12884_2024_7130_Fig1_HTML.jpg

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