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Health Literacy, eHealth Literacy, Adherence to Infection Prevention and Control Procedures, Lifestyle Changes, and Suspected COVID-19 Symptoms Among Health Care Workers During Lockdown: Online Survey
Journal of Medical Internet Research ( IF 7.4 ) Pub Date : 2020-11-12 , DOI: 10.2196/22894
Binh N Do , Tien V Tran , Dung T Phan , Hoang C Nguyen , Thao T P Nguyen , Huu C Nguyen , Tung H Ha , Hung K Dao , Manh V Trinh , Thinh V Do , Hung Q Nguyen , Tam T Vo , Nhan P T Nguyen , Cuong Q Tran , Khanh V Tran , Trang T Duong , Hai X Pham , Lam V Nguyen , Kien T Nguyen , Peter W S Chang , Tuyen Van Duong

Background: The COVID-19 pandemic has imposed a heavy burden on health care systems and governments. Health literacy (HL) and eHealth literacy (as measured by the eHealth Literacy Scale [eHEALS]) are recognized as strategic public health elements but they have been underestimated during the pandemic. HL, eHEALS score, practices, lifestyles, and the health status of health care workers (HCWs) play crucial roles in containing the COVID-19 pandemic. Objective: The aim of this study is to evaluate the psychometric properties of the eHEALS and examine associations of HL and eHEALS scores with adherence to infection prevention and control (IPC) procedures, lifestyle changes, and suspected COVID-19 symptoms among HCWs during lockdown. Methods: We conducted an online survey of 5209 HCWs from 15 hospitals and health centers across Vietnam from April 6 to April 19, 2020. Participants answered questions related to sociodemographics, HL, eHEALS, adherence to IPC procedures, behavior changes in eating, smoking, drinking, and physical activity, and suspected COVID-19 symptoms. Principal component analysis, correlation analysis, and bivariate and multivariate linear and logistic regression models were used to validate the eHEALS and examine associations. Results: The eHEALS had a satisfactory construct validity with 8 items highly loaded on one component, with factor loadings ranked from 0.78 to 0.92 explaining 76.34% of variance; satisfactory criterion validity as correlated with HL (ρ=0.42); satisfactory convergent validity with high item-scale correlations (ρ=0.80-0.84); and high internal consistency (Cronbach α=.95). HL and eHEALS scores were significantly higher in men (unstandardized coefficient [B]=1.01, 95% CI 0.57-1.45, P<.001; B=0.72, 95% CI 0.43-1.00, P<.001), those with a better ability to pay for medication (B=1.65, 95% CI 1.25-2.05, P<.001; B=0.60, 95% CI 0.34-0.86, P<.001), doctors (B=1.29, 95% CI 0.73-1.84, P<.001; B 0.56, 95% CI 0.20-0.93, P=.003), and those with epidemic containment experience (B=1.96, 95% CI 1.56-2.37, P<.001; B=0.64, 95% CI 0.38-0.91, P<.001), as compared to their counterparts, respectively. HCWs with higher HL or eHEALS scores had better adherence to IPC procedures (B=0.13, 95% CI 0.10-0.15, P<.001; B=0.22, 95% CI 0.19-0.26, P<.001), had a higher likelihood of healthy eating (odds ratio [OR] 1.04, 95% CI 1.01-1.06, P=.001; OR 1.04, 95% CI 1.02-1.07, P=.002), were more physically active (OR 1.03, 95% CI 1.02-1.03, P<.001; OR 1.04, 95% CI 1.03-1.05, P<.001), and had a lower likelihood of suspected COVID-19 symptoms (OR 0.97, 95% CI 0.96-0.98, P<.001; OR 0.96, 95% CI 0.95-0.98, P<.001), respectively. Conclusions: The eHEALS is a valid and reliable survey tool. Gender, ability to pay for medication, profession, and epidemic containment experience were independent predictors of HL and eHEALS scores. HCWs with higher HL or eHEALS scores had better adherence to IPC procedures, healthier lifestyles, and a lower likelihood of suspected COVID-19 symptoms. Efforts to improve HCWs’ HL and eHEALS scores can help to contain the COVID-19 pandemic and minimize its consequences.

This is the abstract only. Read the full article on the JMIR site. JMIR is the leading open access journal for eHealth and healthcare in the Internet age.


中文翻译:

卫生保健工作者在锁定期间的健康素养,eHealth素养,遵守感染预防和控制程序,生活方式改变以及可疑的COVID-19症状:在线调查

背景:COVID-19大流行给医疗保健系统和政府带来了沉重负担。健康素养(HL)和eHealth素养(通过eHealth扫盲量表[eHEALS]衡量)被认为是战略性公共卫生要素,但在大流行期间被低估了。HL,eHEALS得分,做法,生活方式以及医护人员(HCW)的健康状况在控制COVID-19大流行中起着至关重要的作用。目的:本研究的目的是评估eHEALS的心理测量特性,并检查HLW和eHEALS分数与锁定期间HCW中感染预防和控制(IPC)程序,生活方式的改变以及疑似COVID-19症状的依从性之间的关联。方法:我们于2020年4月6日至4月19日对越南15家医院和医疗中心的5209名HCW进行了在线调查。参与者回答了有关社会人口统计学,HL,eHEALS,遵守IPC程序,饮食,吸烟,饮酒行为改变,和身体活动,以及疑似COVID-19症状。主成分分析,相关性分析以及二元和多元线性和逻辑回归模型用于验证eHEALS和检查关联。结果:eHEALS具有令人满意的构建效度,在一个组件上高负载8个项目,因子负载范围从0.78到0.92,解释了76.34%的方差;与HL相关的令人满意的标准有效性(ρ= 0.42); 令人满意的收敛效度,具有较高的项目尺度相关性(ρ= 0.80-0.84);内部一致性高(Cronbachα= .95)。男性和女性的HL和eHEALS得分显着较高(非标准化系数[B] = 1.01,95%CI 0.57-1.45,P <.001; B = 0.72,95%CI 0.43-1.00,P <.001)。更好的药物支付能力(B = 1.65,95%CI 1.25-2.05,P <.001; B = 0.60,95%CI 0.34-0.86,P <.001),医生(B = 1.29,95%CI 0.73 -1.84,P <.001; B 0.56,95%CI 0.20-0.93,P = .003),以及有流行病遏制经验的人(B = 1.96,95%CI 1.56-2.37,P <.001; B = 0.64)分别为95%CI 0.38-0.91,P <.001)。HL或eHEALS得分较高的HCW对IPC程序的依从性更好(B = 0.13,95%CI 0.10-0.15,P <.001; B = 0.22,95%CI 0.19-0.26,P <.001),更高健康饮食的可能性(赔率[OR] 1.04,95%CI 1.01-1.06,P = .001; OR 1.04,95%CI 1.02-1.07,P =。002),身体活动活跃(OR 1.03,95%CI 1.02-1.03,P <.001; OR 1.04,95%CI 1.03-1.05,P <.001),并且怀疑COVID-19症状的可能性更低(OR 0.97,95%CI 0.96-0.98,P <.001; OR 0.96,95%CI 0.95-0.98,P <.001)。结论:eHEALS是有效且可靠的调查工具。性别,支付药物的能力,专业和流行病的遏制经验是HL和eHEALS得分的独立预测因子。HL或eHEALS得分较高的HCW对IPC程序的依从性更好,生活方式更健康,可疑COVID-19症状的可能性更低。努力提高医护人员的HL和eHEALS分数可有助于遏制COVID-19大流行并最大程度地减少其后果。并且分别具有较低的可疑COVID-19症状可能性(OR 0.97,95%CI 0.96-0.98,P <.001; OR 0.96,95%CI 0.95-0.98,P <.001)。结论:eHEALS是有效且可靠的调查工具。性别,支付药物的能力,专业和流行病的遏制经验是HL和eHEALS得分的独立预测因子。HL或eHEALS得分较高的HCW对IPC程序的依从性更好,生活方式更健康,可疑的COVID-19症状的可能性更低。努力提高医护人员的HL和eHEALS分数可有助于遏制COVID-19大流行并最大程度地减少其后果。并且分别具有较低的可疑COVID-19症状可能性(OR 0.97,95%CI 0.96-0.98,P <.001; OR 0.96,95%CI 0.95-0.98,P <.001)。结论:eHEALS是有效且可靠的调查工具。性别,支付药物的能力,专业和流行病的遏制经验是HL和eHEALS得分的独立预测因子。HL或eHEALS得分较高的HCW对IPC程序的依从性更好,生活方式更健康,可疑COVID-19症状的可能性更低。努力提高医护人员的HL和eHEALS分数可有助于遏制COVID-19大流行并最大程度地减少其后果。支付药物,职业和流行病控制经验的能力是HL和eHEALS得分的独立预测因子。HL或eHEALS得分较高的HCW对IPC程序的依从性更好,生活方式更健康,可疑COVID-19症状的可能性更低。努力提高医护人员的HL和eHEALS分数可有助于遏制COVID-19大流行并最大程度地减少其后果。支付药物,职业和流行病控制经验的能力是HL和eHEALS得分的独立预测因子。HL或eHEALS得分较高的HCW对IPC程序的依从性更好,生活方式更健康,可疑COVID-19症状的可能性更低。努力提高医护人员的HL和eHEALS分数可以帮助遏制COVID-19大流行并最大程度地减少其后果。

这仅仅是抽象的。阅读JMIR网站上的全文。JMIR是互联网时代电子健康和医疗保健领域领先的开放获取期刊。
更新日期:2020-11-12
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