Suppr超能文献

2022年埃塞俄比亚奥罗米亚地区公立转诊医院产科医护人员使用基于手机的产程图的意向及其预测因素:横断面问卷调查研究

Intention to Use Mobile-Based Partograph and Its Predictors Among Obstetric Health Care Providers Working at Public Referral Hospitals in the Oromia Region of Ethiopia in 2022: Cross-Sectional Questionnaire Study.

作者信息

Tilahun Kefyalew Naniye, Adem Jibril Bashir, Atinafu Wabi Temesgen, Walle Agmasie Damtew, Mengestie Nebyu Demeke, Birhanu Abraham Yeneneh

机构信息

College of Medicine and Health Sciences, Ambo University, Ambo, Ethiopia.

Department of Public Health, Arsi University, Asella, Ethiopia.

出版信息

Online J Public Health Inform. 2024 May 10;16:e51601. doi: 10.2196/51601.

Abstract

BACKGROUND

A partograph is a pictorial representation of the relationship between cervical dilatation and the time used to diagnose prolonged and obstructed labor. However, the utilization of paper-based partograph is low and it is prone to documentation errors, which can be avoided with the use of electronic partographs. There is only limited information on the proportion of intention to use mobile-based partographs and its predictors.

OBJECTIVE

The objective of this study was to determine the proportion of obstetric health care providers at public referral hospitals in Oromia, Ethiopia, in 2022 who had the intention to use mobile-based partographs and to determine the predictors of their intention to use mobile-based partographs.

METHODS

We performed an institution-based cross-sectional study from June 1 to July 1, 2022. Census was conducted on 649 participants. A self-administered structured English questionnaire was used, and a 5% pretest was performed. Data were entered into EpiData version 4.6 and exported to SPSS version 25 for descriptive analysis and AMOS (analysis of moment structure; version 23) for structural and measurement model assessment. Descriptive and structural equation modeling analyses were performed. The hypotheses developed based on a modified Technology Acceptance Model were tested using path coefficients and P values <.05.

RESULTS

About 65.7% (414/630; 95% CI 61.9%-69.4%) of the participants intended to use mobile-based electronic partographs, with a 97% (630/649) response rate. Perceived usefulness had a positive influence on intention to use (β=.184; P=.02) and attitude (β=.521; P=.002). Perceived ease of use had a positive influence on attitude (β=.382; P=.003), perceived usefulness (β=.503; P=.002), and intention to use (β=.369; P=.001). Job relevance had a positive influence on perceived usefulness (β=.408; P=.001) and intention to use (β=.185; P=.008). Attitude positively influenced intention to use (β=.309; P=.002). Subjective norms did not have a significant influence on perceived usefulness (β=.020; P=.61) and intention to use (β=-.066; P=.07).

CONCLUSIONS

Two-thirds of the obstetric health care providers in our study intended to use mobile-based partographs. Perceived usefulness, perceived ease of use, job relevance, and attitude positively and significantly influenced their intention to use mobile-based electronic partographs. The development of a user-friendly mobile-based partograph that meets job and user expectations can enhance the intention to use.

摘要

背景

产程图是宫颈扩张与诊断产程延长和产程梗阻所用时间之间关系的图形表示。然而,纸质产程图的使用率较低,且容易出现记录错误,而使用电子产程图可以避免这些问题。关于使用基于移动设备的产程图的意愿比例及其预测因素的信息有限。

目的

本研究的目的是确定2022年埃塞俄比亚奥罗米亚公共转诊医院中打算使用基于移动设备的产程图的产科医护人员比例,并确定其使用基于移动设备的产程图意愿的预测因素。

方法

我们于2022年6月1日至7月1日进行了一项基于机构的横断面研究。对649名参与者进行了普查。使用了一份自行填写的结构化英文问卷,并进行了5%的预测试。数据录入EpiData 4.6版本,并导出到SPSS 25版本进行描述性分析,以及导出到AMOS(结构方程模型分析;23版本)进行结构和测量模型评估。进行了描述性和结构方程模型分析。基于改进的技术接受模型提出的假设使用路径系数和P值<0.05进行检验。

结果

约65.7%(414/630;95%CI 61.9%-69.4%)的参与者打算使用基于移动设备的电子产程图,回复率为97%(630/649)。感知有用性对使用意愿(β=0.184;P=0.02)和态度(β=0.521;P=0.002)有积极影响。感知易用性对态度(β=0.382;P=0.003)、感知有用性(β=0.503;P=0.002)和使用意愿(β=0.369;P=0.001)有积极影响。工作相关性对感知有用性(β=0.408;P=0.001)和使用意愿(β=0.185;P=0.008)有积极影响。态度对使用意愿有积极影响(β=0.309;P=0.002)。主观规范对感知有用性(β=0.020;P=0.61)和使用意愿(β=-0.066;P=0.07)没有显著影响。

结论

我们研究中三分之二的产科医护人员打算使用基于移动设备的产程图。感知有用性、感知易用性、工作相关性和态度对他们使用基于移动设备的电子产程图的意愿有积极且显著的影响。开发一款符合工作和用户期望的用户友好型基于移动设备的产程图可以提高使用意愿。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/08b3/11127132/1cd7671d8735/ojphi_v16i1e51601_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验