Qin Shijia, Zhang Jianzhong, Sun Xiaomin, Meng Ge, Zhuang Xinqi, Jia Yitong, Shi Wen-Xin, Zhang Yin-Ping
Faculty of Nursing, Xi'an Jiaotong University Health Science Center, No.76, West Yanta Road, Xi'an, Shaanxi, 710061, China.
Department of Nursing, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Xi'an, Shaanxi, 710018, China.
BMC Nurs. 2024 May 31;23(1):366. doi: 10.1186/s12912-024-02030-8.
The adoption of digitization has emerged as a new trend in the advancement of healthcare systems. To ensure high-quality care, nurses should possess sufficient skills to assist in the digital transformation of healthcare practices. Suitable tools have seldom been developed to assess nurses' skills in digital applications. This study aimed to develop the Nursing Digital Application Skill Scale (NDASS) and test its psychometric properties.
The Nursing Digital Application Skill Scale was developed in three phases. In Phase 1, an item pool was developed based on previous literature and the actual situation of nursing work. Phase 2 included 14 experts' assessment of content validity and a focus group interview with 30 nurses to pretest the scale. In phase 3, 429 registered nurses were selected from March to June 2023, and item analysis, exploratory factor analysis, and confirmatory factor analysis were used to refine the number of items and explore the factor structure of the scale. Additionally, reliability was determined by internal consistency and test-retest reliability.
The final version of the NDASS consisted of 12 items. The content validity index of NDASS reached 0.975 at an acceptable level. The convergent validity test showed that the average variance extracted value was 0.694 (> 0.5) and the composite reliability value was 0.964 (> 0.7), both of which met the requirements. The principal component analysis resulted in a single-factor structure explaining 74.794% of the total variance. All the fitting indices satisfied the standard based upon confirmatory factor analyses, indicating that the single-factor structure contributed to an ideal model fit. The internal consistency appeared high for the NDASS, reaching a Cronbach's alpha value of 0.968. The test-retest reliability was 0.740, and the split-half coefficient was 0.935.
The final version of the NDASS, which possesses adequate psychometric properties, is a reliable and effective instrument for nurses to self-assess digital skills in nursing work and for nursing managers in designing nursing digital skill training.
数字化的应用已成为医疗系统发展的新趋势。为确保高质量护理,护士应具备足够的技能以协助医疗实践的数字化转型。很少有合适的工具用于评估护士在数字应用方面的技能。本研究旨在开发护理数字应用技能量表(NDASS)并测试其心理测量特性。
护理数字应用技能量表分三个阶段开发。在第一阶段,根据以往文献和护理工作实际情况建立项目池。第二阶段包括14位专家对内容效度的评估以及对30名护士进行焦点小组访谈以对量表进行预测试。在第三阶段,于2023年3月至6月选取429名注册护士,采用项目分析、探索性因素分析和验证性因素分析来优化项目数量并探索量表的因素结构。此外,通过内部一致性和重测信度来确定信度。
NDASS的最终版本由12个项目组成。NDASS的内容效度指数达到0.975,处于可接受水平。收敛效度测试表明,平均方差抽取值为0.694(>0.5),组合信度值为0.964(>0.7),均符合要求。主成分分析产生单因素结构,解释总方差的74.794%。基于验证性因素分析,所有拟合指标均满足标准,表明单因素结构有助于理想的模型拟合。NDASS的内部一致性较高,克朗巴哈系数值为0.968。重测信度为0.740,分半系数为0.935。
NDASS的最终版本具有足够的心理测量特性,是护士自我评估护理工作中数字技能以及护理管理者设计护理数字技能培训的可靠有效工具。