Harerimana Alexis, Mtshali Ntombifikile Gloria
Nursing and Midwifery, College of Healthcare Sciences, Division of Tropical Health and Medicine, James Cook University, Townsville, Queensland, Australia; Nursing and Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
Nursing and Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
Nurse Educ Today. 2020 Sep;92:104490. doi: 10.1016/j.nedt.2020.104490. Epub 2020 Jun 2.
The study aimed to establish the role played by technology in nursing education through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).
150 student nurses participated, with data being collected using a structured questionnaire with 14 items on a 5-point Likert scale. Parallel Analysis (PA) and Exploratory Factor Analysis (EFA) were conducted to identify the factors for the role of technology in nursing education, Confirmatory Factor analysis (CFA) was used to ascertain the model fit. ANOVA, t-test and binary regression analysis were used to identify among the factors the differences within the level of the study, and perceived abilities to use the computer.
The EFA identified five factors from 14 items, and through the CFA, the results indicated that the model was supported by the following indices: Comparative Fit Index (CFI) = 0.968 (>0.95); Incremental Fit Index (IFI) = 0.969 (>0.95); Tucker-Lewis Index (TLI) = 0.957 (>0.95); Root Mean Squared Error of Approximation (RMSEA) = 0.077 (<0.080); and SRMR = 0.0396 (<0.08). These results were within acceptable ranges, which indicated that the five factors obtained from EFA were validated. However, Chi-square goodness of fit statistics was not statistically significant (χ = 126.312, d.f = 67, p = .000). Overall, 89.3% (n = 134) nursing students had a positive perception of the role of technology in nursing education. Binary regression analysis indicated that 1st year nursing students positively perceived the role of technology 6.7 times more than other levels (OR = 6.710, 95% CI: 1.33-33.63, p = .021). Students with good ability to use the computers (92.9%) were 5.3 more likely to have a positive perception towards the role of technology in nursing than those with the poor ability (OR = 5.35, 95%CI = 1.76-16.26, p = .003).
Using innovative teaching strategies and ensuring that nursing students are skilled is essential to the future of the nursing profession. The five-factor model would be a useful tool to assess the perception of students towards the role of technology in nursing education.
本研究旨在通过探索性因素分析（EFA）和验证性因素分析（CFA）确定技术在护理教育中所起的作用。
150名护理专业学生参与研究，使用一份包含14个项目的结构化问卷收集数据，问卷采用5级李克特量表。进行平行分析（PA）和探索性因素分析（EFA）以确定技术在护理教育中所起作用的因素，使用验证性因素分析（CFA）来确定模型拟合度。采用方差分析、t检验和二元回归分析来确定各因素在研究水平和计算机使用感知能力方面的差异。
探索性因素分析从14个项目中识别出5个因素，通过验证性因素分析，结果表明该模型得到以下指标支持：比较拟合指数（CFI）=0.968（>0.95）；增值拟合指数（IFI）=0.969（>0.95）；塔克-刘易斯指数（TLI）=0.957（>0.95）；近似误差均方根（RMSEA）=0.077（<0.080）；标准化残差均方根（SRMR）=0.0396（<0.08）。这些结果在可接受范围内，表明从探索性因素分析中获得的5个因素得到了验证。然而，卡方拟合优度统计不具有统计学意义（χ=126.312，自由度=67，p=.000）。总体而言，89.3%（n=134）的护理专业学生对技术在护理教育中的作用持积极看法。二元回归分析表明，一年级护理专业学生对技术作用的积极看法是其他年级的6.7倍（比值比=6.710，95%置信区间：1.33 - 33.63，p=.021）。计算机使用能力良好的学生（92.9%）对技术在护理中作用持积极看法的可能性是能力较差学生的5.3倍（比值比=5.35，95%置信区间=1.76 - 16.26，p=.003）。
采用创新教学策略并确保护理专业学生具备技能对护理专业的未来至关重要。五因素模型将是评估学生对技术在护理教育中作用认知的有用工具。
