JMIR J Med Internet Res Journal of Medical Internet Research 1438-8871 JMIR Publications Toronto, Canada v22i11e22894 33122164 10.2196/22894 Original Paper Original Paper 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 Eysenbach Gunther Messer Melanie Werts Niya Batten Ryan Stylianides Antonis Do Binh N MD, PhD 1 2 3 https://orcid.org/0000-0002-1377-3921 Tran Tien V MD, PhD 1 2 3 https://orcid.org/0000-0002-3348-2566 Phan Dung T RN, MPH, PhD 4 5 https://orcid.org/0000-0002-9034-5752 Nguyen Hoang C MD, PhD 6 7 https://orcid.org/0000-0003-0826-1785 Nguyen Thao T P MD 8 9 https://orcid.org/0000-0003-1320-964X Nguyen Huu C MD, PhD 10 11 https://orcid.org/0000-0002-6076-2491 Ha Tung H MD, PhD 12 https://orcid.org/0000-0003-1856-5803 Dao Hung K MD, PhD 13 https://orcid.org/0000-0002-1979-0925 Trinh Manh V MD 14 https://orcid.org/0000-0002-8823-4498 Do Thinh V MD 15 https://orcid.org/0000-0003-0370-8330 Nguyen Hung Q MD, MSc 16 https://orcid.org/0000-0001-6034-1657 Vo Tam T MD 17 https://orcid.org/0000-0001-6683-2158 Nguyen Nhan P T MD, PhD 18 https://orcid.org/0000-0003-1428-836X Tran Cuong Q MD, MPH, MBA 19 20 https://orcid.org/0000-0001-5447-404X Tran Khanh V MD 21 https://orcid.org/0000-0002-0121-6212 Duong Trang T RN, MPH 22 https://orcid.org/0000-0003-3596-0741 Pham Hai X MD 23 https://orcid.org/0000-0001-6960-6770 Nguyen Lam V MD, PhD 24 25 https://orcid.org/0000-0001-5970-0528 Nguyen Kien T MA 26 https://orcid.org/0000-0002-7176-8055 Chang Peter W S MD, ScD 27 28 https://orcid.org/0000-0001-6651-3624 Duong Tuyen Van BNSc, MNSc, PhD 29
School of Nutrition and Health Sciences Taipei Medical University 250 Wuxing St Taipei, 11031 Taiwan 886 2 2736 1661 ext 6545 tvduong@tmu.edu.tw
https://orcid.org/0000-0002-2287-0723 Department of Infectious Diseases Vietnam Military Medical University Hanoi Vietnam Division of Military Science Military Hospital 103 Hanoi Vietnam Director Office Military Hospital 103 Hanoi Vietnam Faculty of Nursing Hanoi University of Business and Technology Hanoi Vietnam Nursing Office Viet Duc University Hospital Hanoi Vietnam Director Office Thai Nguyen National Hospital Thai Nguyen Vietnam President Office Thai Nguyen University of Medicine and Pharmacy Thai Nguyen Vietnam Health Management Training Institute Hue University of Medicine and Pharmacy Thua Thien Hue Vietnam Department of Health Economics Corvinus University of Budapest Budapest Hungary Department of Thoracic and Cardiovascular Surgery E Hospital Hanoi Vietnam Director Office E Hospital Hanoi Vietnam Director Office General Hospital of Agricultural Hanoi Vietnam Director Office Bac Ninh Obstetrics and Pediatrics Hospital Bac Ninh Vietnam Director Office Quang Ninh General Hospital Quang Ninh Vietnam Director Office Bai Chay Hospital Quang Ninh Vietnam Director Office Quang Ninh Obstetrics and Pediatrics Hospital Quang Ninh Vietnam Director Office Trieu Phong District Health Center Quang Tri Vietnam General Planning Department Da Nang Oncology Hospital Da Nang Vietnam Director Office Thu Duc District Health Center Ho Chi Minh Vietnam Faculty of Health Mekong University Vinh Long Vietnam Director Office Hospital District 2 Ho Chi Minh Vietnam Nursing Office Tan Phu District Hospital Ho Chi Minh Vietnam Director Office District 9 Health Center Ho Chi Minh Vietnam President Office Can Tho University of Medicine and Pharmacy Can Tho Vietnam Aesthetic Plastic Surgery & Skin Care Center Can Tho University of Medicine and Pharmacy Hospital Can Tho Vietnam Department of Health Education Faculty of Social Sciences, Behavior and Health Education Hanoi University of Public Health Hanoi Vietnam School of Medicine Chung Shan Medical University Taichung Taiwan Department of Public Health and Community Medicine Tufts University School Of Medicine Boston, MA United States School of Nutrition and Health Sciences Taipei Medical University Taipei Taiwan Corresponding Author: Tuyen Van Duong tvduong@tmu.edu.tw 11 2020 12 11 2020 22 11 e22894 26 7 2020 23 9 2020 25 9 2020 28 10 2020 ©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. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.11.2020. 2020

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

 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.

 COVID-19 health literacy eHealth literacy health care workers personal protective equipment handwashing masks disposing lifestyle Vietnam eHealth adherence infection prevention control Introduction

COVID-19, the disease caused by SARS-CoV-2, has created unprecedented challenges worldwide [1-6], with significant socioeconomic burdens [7], morbidity, and mortality [8,9]. Multidisciplinary and multidimensional approaches are required to contain the pandemic [10-12]. Social and behavioral changes [13,14] and improving health literacy (HL) [15] and eHealth literacy (as measured by the eHealth Literacy Scale [eHEALS]) [16] are highly recommended to control this global health crisis while effective treatments and vaccines are unavailable.

Lockdown measures were applied in many countries, including Vietnam [17]. Lockdown is a necessary public health approach to contain COVID-19. During the lockdown period, health care workers (HCWs) still needed to work and provide health services to patients, which made them more vulnerable to COVID-19 infection. In addition, the pandemic itself and social distancing measures have had negative impacts on psychological health [18,19] and health-related behavior (eg, unhealthy eating habits and behaviors, less physical activity, and more smoking [20-23] and drinking to cope amid the COVID-19 pandemic [24]).

Online consultations from hospitals and health care centers were found to be a safe and effective way to reduce the negative effects of the pandemic [25]. In addition, social media can provide insights for effective communication among public health authorities [26], researchers [27], and the public [28-30]. However, social media spreads panic and anxiety among the public [31]. Disinformation and misinformation have been raised as highly concerning issues for the public [32-34]. HL plays an important role in evaluating online health information [35]. HL is critical for people who interact with the digital world, with its diverse information and sources [36], especially during the COVID-19 pandemic. HCWs play an important role in supporting the public to combat misinformation and disinformation [28,37]. The HCWs’ consultations cannot be altered by social media networks [37,38]. Continuous training and education have been recognized as effective approaches to improving HCWs’ HL, further improving health care delivery [39,40], communication [39,41,42], shared decision making [43], and patient health outcomes [40]. Furthermore, raising awareness of behavioral pitfalls could support appropriate behavioral changes and containment of the crisis [44]. HL and eHealth literacy are more important than ever due to the COVID-19 pandemic [16,45]. However, these issues have been underestimated during the pandemic [15].

We evaluated the psychometric properties of the eHEALS and examined the predictors of HL and eHEALS scores. We also examined the associations between HL and eHEALS scores with adherence to infection prevention and control (IPC) measures, lifestyle changes, and suspected COVID-19 symptoms among HCWs during the lockdown period in Vietnam.

 Methods Study Design and Settings

A cross-sectional study was conducted with HCWs April 6-19, 2020, using online-based questionnaires (Text 1 in Multimedia Appendix 1). The HCWs were recruited from 12 hospitals and 3 health centers across Vietnam, including 8 hospitals in the nation’s north, 1 hospital and 1 health center in the central region, and 3 hospitals and 2 health centers in the country’s south.

 Study Participants and Data Collection

No HCWs (doctors and nurses) in our study had provided any direct care or had contact with patients with COVID-19. A total sample of 5209 HCWs (out of 11,517 possible participants) completed an online survey. The studied and possible participants from public hospitals and health centers are presented in Table 1.

Participants from the studied hospitals and health centers by geographic location.

Geographic location and hospital/health center Possible participants Studied participants
North
Ha Noi city
Military Hospital 103 1660 177
E hospital 1125 335
General Hospital of Agricultural 555 424
Thai Nguyen province
Thai Nguyen National Hospital 1186 988
Bac Ninh city
Bac Ninh Obstetrics and Pediatrics Hospital 391 364
Quang Ninh province
Quang Ninh General Hospital 922 675
Bai Chay Hospital 819 476
Quang Ninh Obstetrics and Pediatrics Hospital 478 290
Center
Quang Tri province
Trieu Phong District Health Center 271 203
Da Nang city
Da Nang Oncology Hospital 555 134
South
Ho Chi Minh city
Tan Phu District Hospital 530 241
Hospital District 2 812 318
District 9 Health Center 170 102
Thu Duc District Health Center 302 291
Can Tho city
Can Tho University of Medicine and Pharmacy Hospital 424 191
Total 11,517 5209

Vietnam applied a nationwide lockdown measure April 1-15, 2020 [17], which was extended to April 22, 2020 [46,47]. In this study, HCWs took the online survey during the lockdown period. We used Google Forms to design and conduct the survey. The online survey links were sent to HCWs by researchers via email, Messenger, or Zalo. QR codes were also displayed in different departments of hospitals and health centers. It took about 15 minutes to complete the questionnaire. All survey questions were mandatory; therefore, there is no missing data in our study. All responses were exported to Google Sheets and saved on Google Drive. Finally, the data was coded, cleaned, and analyzed confidentially by researchers.

 Measures Sociodemographics

HCWs reported their age (21-40 years versus 41-60 years), gender (woman versus man), marital status (never married versus ever married), ability to pay for medication (very or fairly difficult versus very or fairly easy), social status (low versus middle to high), profession (doctor, nurse, or other, the last of which included medical technicians, midwives, pharmacists, pharmacy technicians, administrative staff, catering staff, and cleaners), type of health care facility (second-line versus frontline, the latter of which includes the outpatient department, emergency department, quarantine and isolation areas, medical imaging and laboratory diagnosis department, and patient administration areas), and previous epidemic (eg, SARS, tuberculosis, influenza A) containment experience (no versus yes). Additionally, comorbidity was assessed using the Charlson comorbidity index items [48,49].

 Health Literacy

A 12-item short-form health literacy questionnaire (HLS-SF12) was used. The questionnaire was validated and used in Asian countries [50], including Vietnam [51-54]. HCWs rated their perceived difficulty of items based on a 4-point Likert scale from 1=Very difficult to 4=Very easy. The health literacy index score was standardized to an unified metric from 0 to 50, with higher scores representing better health literacy [50,55].

 eHealth Literacy

The widely used eHealth literacy scale (eHEALS) with 8 items was used to assess HCWs’ eHealth literacy skills [56]. The questionnaire was translated into Vietnamese by the researchers. The content was then validated by an expert panel (28 medical doctors, 7 nurses, and 9 nutrition and public health professionals). The expert panel suggested retaining the original rating and scoring system. HCWs rated their experiences using the internet for health information based on a 5-point Likert scale from 1=Strongly disagree to 5=Strongly agree. Scores range from 8 to 40, with high eHEALS scores representing better eHealth literacy.

 Adherence to IPC Procedures

Participants reported the practices and activities performed related to COVID-19 IPC during health care interactions. The questionnaire was adapted from the interim guidance of the World Health Organization [57]. The IPC measures included the following: (1) wearing single-use gloves, (2) wearing a medical mask, (3) wearing a face shield or goggles/protective glasses, (4) wearing a disposable gown, (5) removing and replacing personal protective equipment (PPE) according to protocol, (6) performing hand hygiene before and after touching patients, (7) performing hand hygiene before and after performing any clean or aseptic procedure, (8) performing hand hygiene after exposure to body fluid, (9) performing hand hygiene after touching patients’ surroundings, and (10) decontaminating high-touch surfaces. HCWs quantified the frequency of performance of the above IPC procedures as recommended, where 0=Never, 1=Rarely (<20% of the time), 2=Occasionally (20% to <50% of the time), 3=Most of the time (50% to <95% of the time), and 4=Always (≥95% of the time). The total performance score of the 10 activities ranged from 0 to 40, with higher scores indicating better adherence to IPC procedures.

 Lifestyle Changes

HCWs reported their current smoking (never/stopped/less versus unchanged or more), drinking (never/stopped/less versus unchanged or more), physical activity (never/stopped/less versus unchanged or more), and eating (less healthy versus unchanged or healthier) behaviors as compared with that before the pandemic [54].

 Suspected COVID-19 Symptoms

HCWs were screened for suspected COVID-19 symptoms [58], including the common symptoms of fever, cough, and dyspnea, along with the less common symptoms of myalgia, fatigue, sputum production, confusion, headache, sore throat, rhinorrhea, chest pain, hemoptysis, diarrhea, and nausea/vomiting. HCWs with any of those symptoms were classified as having symptoms indicative of COVID-19.

 Ethical Consideration

The study was reviewed and approved by the Institutional Ethical Review Committee of Hanoi University of Public Health, Vietnam (Institutional Review Board number 133/2020/YTCC-HD3). The HCWs voluntarily took the survey.

 Data Analysis Psychometric Properties of the eHEALS Construct Validity

The construct validity of the eHEALS was examined using principal component analysis (PCA). An Kaiser-Meyer Olkin (KMO) value ≥0.6 was set to measure sampling adequacy and a Bartlett Test of Sphericity value <0.05 was set to determine the suitability of the data for PCA [59]. The oblique rotation (Promax) method was used.

 Convergent Validity

The Spearman correlation was used to check the correlations between the eHEALS and its eight items.

 Criterion Validity

The Pearson correlation between eHEALS and HLS-SF12 was estimated to provide evidence of criterion validity [60].

 Floor and Ceiling Effects

The percentages of the lowest and highest score among HCWs were calculated. Minimal percentages (<15%) were recommended to eliminate floor and ceiling effects [61].

 Reliability Analysis

The internal consistency of the eHEALS was estimated using the Cronbach α test. A Cronbach α value ≥.70 was designated as satisfactory reliability [62].

 Health Literacy, eHealth Literacy, and Associated Factors

The distributions of HL and eHEALS scores in different categories of studied variables were explored using a one-way analysis of variance (ANOVA) test. In addition, bivariate and multivariate linear regression models were used to examine predictors of HL and eHEALS scores and to investigate the associations of HL and eHEALS scores with adherence to IPC measures. Next, bivariate and multivariate logistic regression models were used to examine the associations of HL and eHEALS scores with lifestyle changes and suspected COVID-19 symptoms. The factors that demonstrated associations with outcome variables at P values <.20 in the bivariate models were included in multivariate models [63]. To exclude colliders, which may cause multicollinearity, we checked the correlations between them using the Spearman correlation test. The representative factors were selected in the multivariate analysis. The regression coefficient (B), odds ratio (OR), and 95% confidence interval (95% CI) were reported appropriately.

Data were analyzed using IBM SPSS (Version 20.0; IBM Corp). The significance level was set at a P value <.05.

 Results Characteristics of HCWs

Table 2 indicates that, of 5209 HCWs, 905 (17.4%) were aged 41-60 years, 1714 (32.9%) were men, 3915 (75.2%) were ever married, 2458 (47.2%) could very or fairly easily pay for medication, 4506 (86.5%) had a middle or high social status, 2540 (48.8%) were nurses, 1453 (27.9%) were doctors, 2299 (44.1%) were frontline HCWs, 1999 (38.4%) had epidemic containment experience, 270 (5.2%) had comorbidities, 769 (14.8%) had had suspected COVID-19 symptoms, 5042 (96.8%) ate at an “unchanged or healthier” level, 228 (4.4%) smoked at an “unchanged or more” level, 234 (4.5%) drank at an “unchanged or more” level, and 3553 (68.2%) had an “unchanged or more” physical activity level during the pandemic. The mean (SD) scores of adherence to IPC measures, HL, and eHEALS were 30.6 (6.2), 36.2 (7.3), and 33.1 (4.8), respectively. The HL scores varied by age, gender, ability to pay for medication, social status, type of health care personnel, epidemic containment experience, BMI, suspected COVID-19 symptoms, dietary intake, smoking, and physical activity (P<.05). The eHEALS scores varied by gender, ability to pay for medication, type of health care personnel, epidemic containment experience, BMI, suspected COVID-19 symptoms, dietary intake, smoking, and physical activity (Table 2).

Characteristics, health literacy, and eHealth literacy among health care workers.

Variables Total (N=5209) Health literacy eHealth Literacy Scale
Participants, n (%) Mean (SD) P valuea Mean (SD) P valuea
Age (years) .02 N/Ab .88
21-40 4304 (82.6) 36.1 (7.2) N/A 33.1 (4.7) N/A
41-60 905 (17.4) 36.7 (7.5) N/A 33.1 (5.0) N/A
Gender <.001 N/A <.001
Women 3495 (67.1) 35.7 (7.0) N/A 32.8 (4.5) N/A
Men 1714 (32.9) 37.1 (7.8) N/A 33.8 (5.3) N/A
Marital status .04 N/A .29
Never married 1294 (24.8) 35.8 (7.0) N/A 33.0 (4.8) N/A
Ever married 3915 (75.2) 36.3 (7.4) N/A 33.2 (4.7) N/A
Ability to pay for medication <.001 N/A <.001
Very or fairly difficult 2751 (52.8) 35.3 (7.4) N/A 32.8 (4.9) N/A
Very or fairly easy 2458 (47.2) 37.2 (7.0) N/A 33.5 (4.6) N/A
Social status <.001 N/A .27
Low 703 (13.5) 35.0 (7.7) N/A 32.9 (4.7) N/A
Middle or high 4506 (86.5) 36.3 (7.2) N/A 33.2 (4.8) N/A
Type of health care personnel <.001 N/A <.001
Other 1216 (23.3) 35.7 (7.6) N/A 33.1 (5.1) N/A
Nurse 2540 (48.8) 35.7 (7.2) N/A 32.7 (4.6) N/A
Doctor 1453 (27.9) 37.3 (7.1) N/A 33.9 (4.8) N/A
Type of health care facilityc .77 N/A .46
Non-frontline 2910 (55.9) 36.2 (7.4) N/A 33.2 (4.7)
Frontline 2299 (44.1) 36.1 (7.1) N/A 33.1 (4.8) N/A
Epidemic containment experience <.001 N/A <.001
No 3210 (61.6) 35.4 (7.2) N/A 32.9 (4.6) N/A
Yes 1999 (38.4) 37.4 (7.3) N/A 33.5 (5.0) N/A
Comorbidity .38 N/A .37
None 4939 (94.8) 36.1 (7.3) N/A 33.1 (4.8) N/A
One or more 270 (5.2) 36.5 (7.6) N/A 32.9 (5.0) N/A
Suspected COVID-19 symptomsd <.001 N/A <.001
No 4440 (85.2) 36.4 (7.3) N/A 33.3 (4.7) N/A
Yes 769 (14.8) 34.7 (7.2) N/A 32.3 (5.1) N/A
Dietary intakee <.001 N/A .002
Eat less healthy 167 (3.2) 34.2 (6.9) N/A 32.0 (5.9) N/A
Unchanged or healthier 5042 (96.8) 36.2 (7.3) N/A 33.2 (4.7) N/A
Smoking tobaccof .046 N/A .03
Never, stopped, or less 4981 (95.6) 36.1 (7.2) N/A 33.1 (4.7) N/A
Unchanged or more 228 (4.4) 37.1 (8.6) N/A 33.8 (5.5) N/A
Drinking alcoholf .18 N/A .53
Never, stopped, or less 4975 (95.5) 36.1 (7.2) N/A 33.1 (4.7) N/A
Unchanged or more 234 (4.5) 36.8 (8.3) N/A 33.3 (5.7) N/A
Physical activityf <.001 N/A <.001
Never, stopped, or less 1656 (31.8) 35.2 (7.6) N/A 32.5 (5.2) N/A
Unchanged or more 3553 (68.2) 36.6 (7.1) N/A 33.4 (4.6) N/A
Adherence to infection prevention and control measures, mean (SD) 30.6 (6.2) N/A N/A N/A N/A
Health literacy index, mean (SD) 36.2 (7.3) N/A N/A N/A N/A
eHealth Literacy Scale score, mean (SD) 33.1 (4.8) N/A N/A N/A N/A

aP value: result of one-way analysis of variance (ANOVA) test.

bN/A: not applicable.

cFrontline areas include the outpatient department, emergency department, isolation areas, imaging and laboratory diagnosis department, and patient administration areas.

dSuspected COVID-19 symptoms include common symptoms (fever, cough, dyspnea) and less common symptoms (myalgia, fatigue, sputum production, confusion, headache, sore throat, rhinorrhea, chest pain, hemoptysis, diarrhea, and nausea/vomiting).

fHealth care workers were asked whether their lifestyle behaviors got worse, better, or were unchanged during the COVID-19 pandemic as compared to before the pandemic.

 Psychometric Properties of eHealth Literacy

As shown in Table 3, the KMO value of the overall scale was 0.93 and the values of its 8 items ranged from 0.92 to 0.95. The Bartlett Test of Sphericity value was <0.001, which is a satisfactory level. In addition, the average communality value of 0.76 was satisfactory, demonstrating the accuracy of the approach [59]. Overall, the 8 items of the eHEALS were strongly loaded on one component and explained 76.34% of the scale variance. The factor loading values of 8 items were ranked from 0.78 to 0.92, as shown in Table 3. The correlations between each item and the scale range from 0.80 to 0.84, indicating satisfactory convergent validity [50,51]. In addition, the correlation between eHEALS and HL scores was moderate (ρ=0.42), providing evidence of criterion validity [60]. Furthermore, the Cronbachα value of .95 indicated a high level of internal consistency. There was no significant floor effect, with 0.70% of participants having the lowest potential response. A marginal ceiling effect was found, with 16.1% of participants having the highest potential response (slightly higher than the recommended percentage of <15%; Table 3).

Construct, convergent, and criterion validity, internal consistency, and floor and ceiling effects of the 8-item eHealth Literacy Scale (N=5209).

Construct validity, factor loadings Values
eHealth Literacy scale items
I know what health resources are available on the internet 0.85
I know where to find helpful health resources on the internet 0.90
I know how to find helpful health resources on the internet 0.92
I know how to use the internet to answer my questions about health 0.90
I know how to use the health information I find on the internet to help me 0.92
I have the skills I need to evaluate the health resources I find on the internet 0.89
I have the skills needed to tell high-quality health resources from low-quality health resources on the internet 0.82
I feel confident in using information from the internet to make health decisions 0.78
Percentage of variance, % 76.34
Item-scale convergent validity, mean of ρa (range) 0.83 (0.80-0.84)
Criterion validity, correlation with health literacy, ρb 0.42
Internal consistency, Cronbach α .95
Floor effect, % 0.70
Ceiling effect, % 16.10

aρ: Spearman correlation coefficient.

bρ: Pearson correlation coefficient.

 Determinants of HL and eHealth Literacy

The week correlations among independent variables (ρ <0.30) suggest that there is no collider which might affect the results (Table 1 in Multimedia Appendix 1). Results of the multivariate analysis shown in Table 4 indicated that HCWs with higher HL scores were men (unstandardized regression coefficient [B]=1.01, 95% CI 0.57-1.45, P<.001), those with a very or fairly easy ability to pay for medication (B=1.65, 95% CI 1.25-2.05, P<.001), those with a middle or high social status (B=0.586, 95% CI 0.003-1.169, P=.049), doctors (B=1.29, 95% CI 0.73-1.84, P<.001), and those with epidemic containment experience (B=1.96, 95% CI 1.56-2.37, P<.001), as compared to their counterparts, respectively.

HCWs with higher eHEALS scores were men (B=0.72, 95% CI 0.43-1.00, P<.001), those with a very or fairly easy ability to pay for medication (B=0.60, 95% CI 0.34-0.86, P<.001), doctors (B=0.56, 95% CI 0.20-0.93, P=.003), and those with epidemic containment experience (B=0.64, 95% CI 0.38-0.91, P<.001), as compared to their counterparts, respectively (Table 4).

Determinants of health literacy and eHealth literacy among health care workers (N=5209).

Variables Health literacy eHealth literacy
Bivariate Multivariate Bivariate Multivariate
Ba (95% CI) P value B (95% CI) P value B (95% CI) P value B (95% CI) P value
Age (years)
21-40 Reference N/Ab Reference N/A Reference N/A Reference N/A
41-60 0.62 (0.10 to 1.14) .02 –0.05 (–0.58 to 0.49) .86 –0.03 (–0.37 to 0.31) .88 –0.30 (–0.65 to 0.04) .08
Gender
Female Reference N/A Reference N/A Reference N/A Reference N/A
Male 1.36 (0.94 to 1.78) <.001 1.01 (0.57 to 1.45) <.001 0.99 (0.72 to 1.27) <.001 0.72 (0.43 to 1.00) <.001
Marital status
Never married Reference N/A Reference N/A Reference N/A N/A N/A
Ever married 0.47 (0.01 to 0.93) .04 0.34 (–0.12 to 0.81) .15 0.16 (–0.14 to 0.46) .29 N/A N/A
Ability to pay for medication
Very or fairly difficult Reference N/A Reference N/A Reference N/A Reference N/A
Very or fairly easy 1.9 (1.51 to 2.29) <.001 1.65 (1.25 to 2.05) <.001 0.72 (0.46 to 0.98) <.001 0.60 (0.34 to 0.86) <.001
Social status
Low Reference N/A Reference N/A Reference N/A N/A N/A
Middle or high 1.29 (0.72 to 1.87) <.001 0.586 (0.003 to 1.169) .049 0.22 (–0.16 to 0.59) .27 N/A N/A
Type of health care personnel
Other Reference N/A Reference N/A Reference N/A Reference N/A
Nurse 0.09 (–0.41 to 0.58) .73 0.18 (–0.32 to 0.68) .48 –0.40 (–0.72 to –0.07) .02 –0.32 (–0.65 to 0.01) .06
Doctor 1.68 (1.13 to 2.24) <.001 1.29 (0.73 to 1.84) <.001 0.76 (0.39 to 1.12) <.001 0.56 (0.20 to 0.93) .003
Type of health care facilityc
Non-frontline Reference N/A N/A N/A Reference N/A N/A N/A
Frontline –0.06 (–0.46 to 0.34) .77 N/A N/A –0.10 (–0.36 to 0.16) .46 N/A N/A
Epidemic containment experience
No Reference N/A Reference N/A Reference N/A Reference N/A
Yes 1.95 (1.54 to 2.35) <.001 1.96 (1.56 to 2.37) <.001 0.55 (0.29 to 0.82) <.001 0.64 (0.38 to 0.91) <.001
Comorbidity
None Reference N/A Reference N/A Reference N/A N/A N/A
One or more 0.40 (–0.49 to 1.29) .378 N/A N/A –0.27 (–0.85 to 0.32) .369 N/A N/A

aB: unstandardized regression coefficient.

bN/A: not applicable.

cFrontline areas are the outpatient department, emergency department, isolation areas, imaging and laboratory diagnosis department, and patient administration areas.

 Association Between HL and eHealth Literacy and Adherence to IPC Procedures

According to the results of a multivariate linear regression analysis (Table 5), higher HL (B=0.13, 95% CI 0.10-0.15, P<.001) and eHEALS scores (B=0.22, 95% CI 0.19-0.26, P<.001) were found to be associated with better adherence to IPC measures after adjusting for age, gender, ability to pay for medication, social status, profession, type of health care facility, epidemic containment experience, and comorbidities. These adjusted factors showed the associations with adherence to IPC measures at P<.20 (Table 2 in Multimedia Appendix 1).

Associations of health literacy and eHealth literacy with adherence to infection prevention and control measures, lifestyle changes, and suspected COVID-19 symptoms among health care workers (N=5209).

Variables Adherence to IPC measuresa Dietary intakeb Smoking tobaccoc Drinking alcohold Physical activitye Suspected COVID-19 symptomsf
Bg (95% CI) P value ORh (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value
Health literacy, 1-score increment
Bivariate model 0.13 (0.11-0.15) <.001 1.04 (1.02-1.06) <.001 1.02 (1.00-1.04) .046 1.01 (0.99-1.03) .18 1.03 (1.02-1.04) <.001 0.97 (0.96-0.98) <.001
Multivariate model 0.13 (0.10-0.15) <.001 1.04 (1.01-1.06) .001 1.01 (0.99-1.03) .34 1.01 (0.99-1.02) .47 1.03 (1.02-1.03) <.001 0.97 (0.96-0.98) <.001
eHealth Literacy Scale, 1-score increment
Bivariate model 0.22 (0.18-0.25) <.001 1.04 (1.02-1.07) .002 1.03 (1-1.07) .03 1.01 (0.98-1.04) .53 1.04 (1.03-1.05) <.001 0.96 (0.95-0.98) <.001
Multivariate model 0.22 (0.19-0.26) <.001 1.04 (1.02-1.07) .002 1.01 (0.99-1.04) .30 0.99 (0.97-1.02) .69 1.04 (1.03-1.05) <.001 0.96 (0.95-0.98) <.001

aAdherence to infection prevention and control procedures; adjusted for age, gender, ability to pay for medication, social status, type of health care personnel, type of health care facility, epidemic containment experience, and comorbidity in the multivariate model.

bAdjusted for age, gender, marital status, ability to pay for medication, and social status in the multivariate model. The reference group is “less healthy diet” and the test group is “unchanged or healthier diet.”

cAdjusted for age, gender, marital status, social status, and type of health care personnel in the multivariate model. The reference group is “never, stopped, or less smoking,” and the test group is “unchanged or more smoking.”

dAdjusted for age, gender, social status, type of health care personnel, and epidemic containment experience in the multivariate model. The reference group is “never, stopped, or less drinking,” and the test group is “unchanged or more drinking.”

eAdjusted for age, gender, ability to pay for medication, social status, type of health care personnel, type of health care facility, and epidemic containment experience in the multivariate model. The reference group is “never, stopped, or less physical activity,” and the test group is “unchanged or more physical activity.”

fSuspected COVID-19 symptoms include common symptoms (fever, cough, dyspnea) and less common symptoms (myalgia, fatigue, sputum production, confusion, headache, sore throat, rhinorrhea, chest pain, hemoptysis, diarrhea, and nausea/vomiting). Adjusted for age, gender, marital status, ability to pay for medications, social status, type of health care personnel, and comorbidity in the multivariate model.

gB: unstandardized regression coefficient.

hOR: odds ratio.

 Association Between HL and eHealth Literacy and Lifestyle Changes

The results of the multivariate logistic regression analysis shown in Table 5 indicated that HCWs with higher HL (OR 1.04, 95% CI 1.01-1.06, P=.001) and higher eHEALS scores (OR 1.04, 95% CI 1.02-1.07, P=.002) had a higher likelihood of eating at an “unchanged or healthier” level after being adjusted for age, gender, marital status, ability to pay for medication, and social status. These adjusted factors had associations with eating behavior changes at P<.20 (Table 2 in Multimedia Appendix 1). In addition, HCWs with higher HL scores (OR 1.03, 95% CI 1.02-1.03, P<.001) and higher eHEALS scores (OR 1.04, 95% CI 1.03-1.05, P<.001) had a higher likelihood of doing physical activity at an “unchanged or more” level after adjusting for age, gender, ability to pay for medication, social status, profession, type of health care facility, and epidemic containment experience. These adjusted factors had associations with physical activity at P<.20 (Table 2 in Multimedia Appendix 1). No association was found between HL and eHEALS scores and smoking or drinking behaviors.

 Associations of HL and eHealth Literacy With Suspected COVID-19 Symptoms

As shown in Table 5, HCWs with higher HL scores (OR 0.97, 95% CI 0.96-0.98, P<.001) and higher eHEALS scores (OR 0.96, 95% CI 0.95-0.98, P<.001) had a lower likelihood of having suspected COVID-19 symptoms after adjusting for age, gender, marital status, ability to pay for medication, social status, profession, and comorbidities. These adjusted factors had associations with suspected COVID-19 symptoms at P<.20 (Table 2 in Multimedia Appendix 1).

 Discussion Principal Findings

The eHEALS questionnaire was found to be valid and reliable for assessing the eHealth literacy of HCWs. The tool was found to have satisfactory construct validity, convergent validity, criterion validity, and reliability. There was no flooring effect. A marginal ceiling effect was found. A high percentage of participants with the highest possible score was also observed in a previous study that validated the digital health literacy scale [64]. This could be because HCWs have been recognized as a group that has a higher standard of health knowledge and skills than the average person. Therefore, it is reasonable that many participants had a higher or maximum score.

In this study, male HCWs had higher HL and eHEALS scores. This finding is inconsistent with a previous study conducted among the general population in Europe [65], in which men had lower HL scores than women. Another study conducted among the general population in Taiwan showed that men also had lower scores of HL and digital health diet literacy than women [66]. In addition, eHealth literacy was found to be higher in women than men in the general population in Hungary [67] and in health care professionals in Ethiopia [68]. This inconsistency could be explained by the fact that although the total HCW population had fewer males (32.9% versus 67.1% female), the proportion of male doctors (797/1453 or 54.9%) was higher than that of female doctors (656/1453 or 45.1%).

Doctors had higher HL and eHEALS scores than other HCWs in this study. Similarly, HCWs with epidemic containment experience had higher HL and eHEALS scores in this study. Among HCWs, doctors receive longer professional training and they have been recognized as the group with the highest level of ability to find, understand, justify, and use health-related information. In addition, they are involved in educating and counseling other HCWs and patients [69]. HCWs who were involved in containing previous outbreaks or epidemics logically had better health knowledge and skills that made their HL and eHEALS scores higher. HL was found to be a strategic approach for improving communication between patients and HCWs [41], further contributing to the containment of the pandemic and its consequences [45].

HCWs with a better ability to pay for medication had higher HL and eHEALS scores. A positive association between the ability to pay for medication was prominently found in many previous studies [51,52,66,70,71]. In addition, HCWs with middle or high social status had higher HL scores. This was similar to the findings of previous studies conducted in Asia [51,52,66,70-72] and Europe [65]. This implies that socioeconomic factors are independent indictors that should be taken into consideration in intervention development to improve HL and eHEALS scores.

In this study, HCWs with higher HL or eHEALS scores had better adherence to IPC procedures. This is the first study investigating these associations. In the literature, higher HL scores were found to be associated with better adherence to therapies among people with chronic diseases [73-76]. Receiving COVID-19–related information online during the pandemic could be beneficial for various preventive behaviors [77]. Therefore, more efforts are needed to increase the distribution of accurate information and encourage appropriate behaviors [78]. HCWs should be aware of and strictly adhere to the guidelines for IPC to contain the COVID-19 pandemic.

Our study found that HCWs with higher HL and eHEALS scores had a lower likelihood of suspected COVID-19 symptoms. It has been noted that individuals with higher HL scores had better health status [71,79] and well-being [80,81]. This could be further explained by the fact that higher HL and eHEALS scores were associated with healthier eating and physical activity behaviors in this study. In a previous study, we also found that medical and nursing students with higher digital healthy diet literacy had healthier eating behaviors during the pandemic [82]. In addition, eHealth literacy was found to be associated with key issues related to seeking out exercise regime information and maintaining a healthy diet [83]. In addition, it has been reported that people with higher HL scores had healthier behaviors (eg, exercise, balanced diet) [66,84], further protecting and improving their health and well-being [85].

This study has some limitations. First, the study was conducted online and the suspected COVID-19 symptoms were self-reported; therefore, we cannot confirm COVID-19 cases and exclude them from our study. Fortunately, there were no new confirmed cases during the data collection period [86]. Second, during the lockdown period, people were ordered to stay at home and only go out to buy food or medicine, for emergencies, or to work at businesses producing and providing essential goods and services. This may cause a measurement bias in the application domain of HL, as the questionnaire cannot distinguish between an individual’s ability and restrictions during lockdown (eg, on questions such as “on a scale from very easy to very difficult, how easy would you say it is to join a sports club or exercise class if you want to?”). Third, a cross-sectional design was used, which cannot provide evidence of the causal relationships among studied variables. Furthermore, the convenient sampling technique used may limit the generalizability of the findings. In addition, the differences between some categories were not examined due to small sample sizes (eg, widowed/separated/divorced participants [140/5209, 2.7%] or those with high social status 63/5209, 1.2%]). However, we surveyed a relatively large sample of HCWs from 15 hospitals and health centers across Vietnam, which can help with exploring associations in future research and provides evidence for potential interventions.

 Conclusions

The eHEALS questionnaire is a valid and reliable tool for assessing eHealth literacy among HCWs. HL and eHealth literacy were significantly higher in men, those with better ability to pay for medication, doctors, and those with previous epidemic containment experience. Both HL and eHealth literacy were associated with better adherence to IPC procedures, healthier lifestyles (eg, healthier eating behavior and more physical activity during the pandemic), and a lower likelihood of having suspected COVID-19 symptoms. Integrative and multidisciplinary approaches are required to improve HCWs’ HL and eHealth literacy, which could help improve adherence to IPC measures, promote healthy behaviors, and protect the health of HCWs. This would further contribute to containing the COVID-19 pandemic and minimizing its consequences.

Supplementary data.

 Abbreviations B

unstandardized regression coefficient

 eHEALS

eHealth Literacy Scale

 HCWs

health care workers

 HL

health literacy

 HLS-SF12

12-item short-form health literacy questionnaire

 IPC

infection prevention and control

 KMO

Kaiser-Meyer Olkin Measure

 PCA

principal component analysis

 PPE

personal protective equipment

 WHO

World Health Organization

We appreciate and acknowledge the participation of HCWs from the selected hospitals and health centers. This work was supported by Military Hospital 103, Vietnam, and Taipei Medical University, Taiwan (108-3805-022-400).

BND, TVT, and TVD analyzed the data and drafted the manuscript. BND, TVT, DTP, HCN, TTPN, HCN, THH, HKD, MVT, TVD, HQN, TTN, NPTN, CQT, KVT, TTD, HXP, LVN, KTN, PWC, and TVD contributed to conceptualization, investigation, methodology, validation, and manuscript revision. BND, TVT, DTP, HCN, TTPN, HCN, THH, HKD, MVT, TVD, HQN, TTN, NPTN, CQT, KVT, TTD, HXP, LVN, KTN, and TVD conducted data curation. All authors gave final approval of the manuscript.

None declared.

 Greenberg N Docherty M Gnanapragasam S Wessely S Managing mental health challenges faced by healthcare workers during covid-19 pandemic BMJ 2020 03 26 368 m1211 10.1136/bmj.m1211 32217624 Bassetti M Vena A Giacobbe DR The novel Chinese coronavirus (2019-nCoV) infections: Challenges for fighting the storm Eur J Clin Invest 2020 03 50 3 e13209 10.1111/eci.13209 32003000 PMC7163647 Phelan AL Katz R Gostin LO The Novel Coronavirus Originating in Wuhan, China: Challenges for Global Health Governance JAMA 2020 02 25 323 8 709 710 10.1001/jama.2020.1097 31999307 2760500 Rubin R The Challenge of Preventing COVID-19 Spread in Correctional Facilities JAMA 2020 05 12 323 18 1760 1761 10.1001/jama.2020.5427 32259189 2764379 Xiang Y Jin Y Cheung T Joint International Collaboration to Combat Mental Health Challenges During the Coronavirus Disease 2019 Pandemic JAMA Psychiatry 2020 10 01 77 10 989 990 10.1001/jamapsychiatry.2020.1057 32275289 2764583 Campion J Javed A Sartorius N Marmot M Addressing the public mental health challenge of COVID-19 The Lancet Psychiatry 2020 08 7 8 657 659 10.1016/s2215-0366(20)30240-6 Nicola M Alsafi Z Sohrabi C Kerwan A Al-Jabir A Iosifidis C Agha M Agha R The socio-economic implications of the coronavirus pandemic (COVID-19): A review Int J Surg 2020 06 78 185 193 10.1016/j.ijsu.2020.04.018 32305533 S1743-9191(20)30316-2 PMC7162753 Clark A Jit M Warren-Gash C Guthrie B Wang HHX Mercer SW Sanderson C McKee M Troeger C Ong KL Checchi F Perel P Joseph S Gibbs HP Banerjee A Eggo RM Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study Lancet Glob Health 2020 08 8 8 e1003 e1017 10.1016/S2214-109X(20)30264-3 32553130 S2214-109X(20)30264-3 PMC7295519 Banerjee A Pasea L Harris S Gonzalez-Izquierdo A Torralbo A Shallcross L Noursadeghi M Pillay D Sebire N Holmes C Pagel C Wong WK Langenberg C Williams B Denaxas S Hemingway H Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study Lancet 2020 05 30 395 10238 1715 1725 10.1016/S0140-6736(20)30854-0 32405103 S0140-6736(20)30854-0 PMC7217641 Moradian N Ochs HD Sedikies C Hamblin MR Camargo CA Martinez JA Biamonte JD Abdollahi M Torres PJ Nieto JJ Ogino S Seymour JF Abraham A Cauda V Gupta S Ramakrishna S Sellke FW Sorooshian A Wallace Hayes A Martinez-Urbistondo M Gupta M Azadbakht L Esmaillzadeh A Kelishadi R Esteghamati A Emam-Djomeh Z Majdzadeh R Palit P Badali H Rao I Saboury AA Jagan Mohan Rao L Ahmadieh H Montazeri A Fadini GP Pauly D Thomas S Moosavi-Movahed AA Aghamohammadi A Behmanesh M Rahimi-Movaghar V Ghavami S Mehran R Uddin LQ Von Herrath M Mobasher B Rezaei N The urgent need for integrated science to fight COVID-19 pandemic and beyond J Transl Med 2020 05 19 18 1 205 10.1186/s12967-020-02364-2 32430070 10.1186/s12967-020-02364-2 PMC7236639 Holmes EA O'Connor RC Perry VH Tracey I Wessely S Arseneault L Ballard C Christensen H Cohen Silver R Everall I Ford T John A Kabir T King K Madan I Michie S Przybylski AK Shafran R Sweeney A Worthman CM Yardley L Cowan K Cope C Hotopf M Bullmore E Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science Lancet Psychiatry 2020 06 7 6 547 560 10.1016/S2215-0366(20)30168-1 32304649 S2215-0366(20)30168-1 PMC7159850 Nazir M Hussain I Tian J Akram S Mangenda Tshiaba S Mushtaq S Shad MA A Multidimensional Model of Public Health Approaches Against COVID-19 Int J Environ Res Public Health 2020 05 26 17 11 3780 10.3390/ijerph17113780 32466581 ijerph17113780 PMC7312600 Betsch C How behavioural science data helps mitigate the COVID-19 crisis Nat Hum Behav 2020 05 27 4 5 438 438 10.1038/s41562-020-0866-1 32221514 10.1038/s41562-020-0866-1 PMC7101898 Bavel JJV Baicker K Boggio PS Capraro V Cichocka A Cikara M Crockett MJ Crum AJ Douglas KM Druckman JN Drury J Dube O Ellemers N Finkel EJ Fowler JH Gelfand M Han S Haslam SA Jetten J Kitayama S Mobbs D Napper LE Packer DJ Pennycook G Peters E Petty RE Rand DG Reicher SD Schnall S Shariff A Skitka LJ Smith SS Sunstein CR Tabri N Tucker JA Linden SVD Lange PV Weeden KA Wohl MJA Zaki J Zion SR Willer R Using social and behavioural science to support COVID-19 pandemic response Nat Hum Behav 2020 05 30 4 5 460 471 10.1038/s41562-020-0884-z 32355299 10.1038/s41562-020-0884-z Paakkari L Okan O COVID-19: health literacy is an underestimated problem Lancet Public Health 2020 05 5 5 e249 e250 10.1016/S2468-2667(20)30086-4 32302535 S2468-2667(20)30086-4 PMC7156243 Chong YY Cheng HY Chan HYL Chien WT Wong SYS COVID-19 pandemic, infodemic and the role of eHealth literacy Int J Nurs Stud 2020 08 108 103644 10.1016/j.ijnurstu.2020.103644 32447127 S0020-7489(20)30128-0 PMC7255119 PM orders strict nationwide social distancing rules, starting April 1 Vietnam Law Magazine 2020 2020-03-31 https://vietnamlawmagazine.vn/pm-orders-strict-nationwide-social-distancing-rules-starting-april-1-27108.html Hao F Tan W Jiang L Zhang L Zhao X Zou Y Hu Y Luo X Jiang X McIntyre RS Tran B Sun J Zhang Z Ho R Ho C Tam W Do psychiatric patients experience more psychiatric symptoms during COVID-19 pandemic and lockdown? A case-control study with service and research implications for immunopsychiatry Brain Behav Immun 2020 07 87 100 106 10.1016/j.bbi.2020.04.069 32353518 S0889-1591(20)30626-7 PMC7184991 Ozamiz-Etxebarria N Idoiaga Mondragon N Dosil Santamaría M Picaza Gorrotxategi M Psychological Symptoms During the Two Stages of Lockdown in Response to the COVID-19 Outbreak: An Investigation in a Sample of Citizens in Northern Spain Front Psychol 2020 11 1491 10.3389/fpsyg.2020.01491 32625157 PMC7314923 Di Renzo L Gualtieri P Pivari F Soldati L Attinà A Cinelli G Leggeri C Caparello G Barrea L Scerbo F Esposito E De Lorenzo A Eating habits and lifestyle changes during COVID-19 lockdown: an Italian survey J Transl Med 2020 06 08 18 1 229 10.1186/s12967-020-02399-5 32513197 10.1186/s12967-020-02399-5 PMC7278251 Ammar A Brach M Trabelsi K Chtourou H Boukhris O Masmoudi L Bouaziz B Bentlage E How D Ahmed M Müller P Müller N Aloui A Hammouda O Paineiras-Domingos LL Braakman-Jansen A Wrede C Bastoni S Pernambuco CS Mataruna L Taheri M Irandoust K Khacharem A Bragazzi NL Chamari K Glenn JM Bott NT Gargouri F Chaari L Batatia H Ali GM Abdelkarim O Jarraya M Abed KE Souissi N Van Gemert-Pijnen L Riemann BL Riemann L Moalla W Gómez-Raja J Epstein M Sanderman R Schulz SVW Jerg A Al-Horani R Mansi T Jmail M Barbosa F Ferreira-Santos F Šimunič B Pišot R Gaggioli A Bailey SJ Steinacker JM Driss T Hoekelmann A Effects of COVID-19 Home Confinement on Eating Behaviour and Physical Activity: Results of the ECLB-COVID19 International Online Survey Nutrients 2020 05 28 12 6 1583 10.3390/nu12061583 32481594 nu12061583 PMC7352706 Sidor A Rzymski P Dietary Choices and Habits during COVID-19 Lockdown: Experience from Poland Nutrients 2020 06 03 12 6 1657 10.3390/nu12061657 32503173 nu12061657 PMC7352682 Rodríguez-Pérez C Molina-Montes E Verardo V Artacho R García-Villanova B Guerra-Hernández EJ Ruíz-López MD Changes in Dietary Behaviours during the COVID-19 Outbreak Confinement in the Spanish COVIDiet Study Nutrients 2020 06 10 12 6 1730 10.3390/nu12061730 32531892 nu12061730 PMC7353108 Wardell J Kempe T Rapinda K Single A Bilevicius E Frohlich J Hendershot Christian S Keough Matthew T Drinking to Cope During COVID-19 Pandemic: The Role of External and Internal Factors in Coping Motive Pathways to Alcohol Use, Solitary Drinking, and Alcohol Problems Alcohol Clin Exp Res 2020 09 01 1 10.1111/acer.14425 32870516 Gong K Xu Z Cai Z Chen Y Wang Z Internet Hospitals Help Prevent and Control the Epidemic of COVID-19 in China: Multicenter User Profiling Study J Med Internet Res 2020 04 14 22 4 e18908 10.2196/18908 32250962 v22i4e18908 PMC7159055 Sesagiri Raamkumar A Tan S Wee H Measuring the Outreach Efforts of Public Health Authorities and the Public Response on Facebook During the COVID-19 Pandemic in Early 2020: Cross-Country Comparison J Med Internet Res 2020 05 19 22 5 e19334 10.2196/19334 32401219 PMC7238862 Shen C Chen A Luo C Zhang J Feng B Liao W Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study J Med Internet Res 2020 05 28 22 5 e19421 10.2196/19421 32452804 v22i5e19421 PMC7257484 Abd-Alrazaq A Alhuwail D Househ M Hamdi M Shah Z Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study J Med Internet Res 2020 04 21 22 4 e19016 10.2196/19016 32287039 v22i4e19016 PMC7175788 Liu Q Zheng Z Zheng J Chen Q Liu G Chen S Chu B Zhu H Akinwunmi B Huang J Zhang CJP Ming W Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach J Med Internet Res 2020 04 28 22 4 e19118 10.2196/19118 32302966 v22i4e19118 PMC7189789 Liao Q Yuan J Dong M Yang L Fielding R Lam WWT Public Engagement and Government Responsiveness in the Communications About COVID-19 During the Early Epidemic Stage in China: Infodemiology Study on Social Media Data J Med Internet Res 2020 05 26 22 5 e18796 10.2196/18796 32412414 v22i5e18796 PMC7284407 Ahmad AR Murad HR The Impact of Social Media on Panic During the COVID-19 Pandemic in Iraqi Kurdistan: Online Questionnaire Study J Med Internet Res 2020 05 19 22 5 e19556 10.2196/19556 32369026 v22i5e19556 PMC7238863 Bao Y Sun Y Meng S Shi J Lu L 2019-nCoV epidemic: address mental health care to empower society Lancet 2020 02 22 395 10224 e37 e38 10.1016/S0140-6736(20)30309-3 32043982 S0140-6736(20)30309-3 PMC7133594 Shimizu K 2019-nCoV, fake news, and racism Lancet 2020 02 29 395 10225 685 686 10.1016/S0140-6736(20)30357-3 32059801 S0140-6736(20)30357-3 PMC7133552 Brooks SK Webster RK Smith LE Woodland L Wessely S Greenberg N Rubin GJ The psychological impact of quarantine and how to reduce it: rapid review of the evidence Lancet 2020 03 14 395 10227 912 920 10.1016/S0140-6736(20)30460-8 32112714 S0140-6736(20)30460-8 PMC7158942 Diviani N van den Putte Bas Giani S van Weert Julia Cm Low health literacy and evaluation of online health information: a systematic review of the literature J Med Internet Res 2015 05 07 17 5 e112 10.2196/jmir.4018 25953147 v17i5e112 PMC4468598 Norman CD Skinner HA eHealth Literacy: Essential Skills for Consumer Health in a Networked World J Med Internet Res 2006 06 16 8 2 e9 10.2196/jmir.8.2.e9 16867972 v8i2e9 PMC1550701 Park HW Park S Chong M Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea J Med Internet Res 2020 05 05 22 5 e18897 10.2196/18897 32325426 v22i5e18897 PMC7202309 Ko N Lu W Chen Y Li D Wang P Hsu S Chen C Lin Y Chang Y Yen C COVID-19-related information sources and psychological well-being: An online survey study in Taiwan Brain Behav Immun 2020 07 87 153 154 10.1016/j.bbi.2020.05.019 32389702 S0889-1591(20)30720-0 PMC7204755 Mackert M Ball J Lopez N Health literacy awareness training for healthcare workers: improving knowledge and intentions to use clear communication techniques Patient Educ Couns 2011 12 85 3 e225 8 10.1016/j.pec.2011.02.022 21474264 S0738-3991(11)00134-0 Yunyongying P Rich M Jokela J Patient-Centered Performance Metrics JAMA 2019 05 14 321 18 1829 10.1001/jama.2019.2056 31087017 2733201 McKinn S Linh DT Foster K McCaffery K Communication Between Health Workers and Ethnic Minorities in Vietnam Health Lit Res Pract 2017 10 01 1 4 e163 e172 10.3928/24748307-20170629-01 31294262 PMC6607781 Tavakoly Sany SB Behzhad F Ferns G Peyman N Communication skills training for physicians improves health literacy and medical outcomes among patients with hypertension: a randomized controlled trial BMC Health Serv Res 2020 01 23 20 1 60 10.1186/s12913-020-4901-8 31973765 10.1186/s12913-020-4901-8 PMC6979365 Wang M Hung L Lo Y Glycemic control in type 2 diabetes: role of health literacy and shared decision-making Patient Prefer Adherence 2019 13 871 879 10.2147/PPA.S202110 31213781 202110 PMC6538834 Redelmeier DA Shafir E Pitfalls of judgment during the COVID-19 pandemic Lancet Public Health 2020 06 5 6 e306 e308 10.1016/S2468-2667(20)30096-7 32334647 S2468-2667(20)30096-7 PMC7180015 Sentell T Vamos S Okan O Interdisciplinary Perspectives on Health Literacy Research Around the World: More Important Than Ever in a Time of COVID-19 Int J Environ Res Public Health 2020 04 26 17 9 3010 10.3390/ijerph17093010 32357457 ijerph17093010 PMC7246523 Govt extends social distancing for at least one week in 28 localities VGP News 2020 2020-04-15 http://news.chinhphu.vn/Home/Govt-extends-social-distancing-for-at-least-one-week-in-28-localities/20204/39735.vgp Govt to gradually ease COVID-19 control measure in cautious manner VGP News 2020 2020-04-20 http://primeminister.chinhphu.vn/Home/Govt-to-gradually-ease-COVID19-control-measure-in-cautious-manner/20204/3759.vgp Quan H Li B Couris CM Fushimi K Graham P Hider P Januel J Sundararajan V Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries Am J Epidemiol 2011 03 15 173 6 676 82 10.1093/aje/kwq433 21330339 kwq433 Charlson ME Pompei P Ales KL MacKenzie C A new method of classifying prognostic comorbidity in longitudinal studies: development and validation J Chronic Dis 1987 40 5 373 83 10.1016/0021-9681(87)90171-8 3558716 Duong TV Aringazina A Kayupova G Nurjanah Pham TV Pham KM Truong TQ Nguyen KT Oo WM Su TT Majid HA Sørensen K Lin I Chang Y Yang S Chang PWS Development and Validation of a New Short-Form Health Literacy Instrument (HLS-SF12) for the General Public in Six Asian Countries Health Lit Res Pract 2019 04 3 2 e91 e102 10.3928/24748307-20190225-01 31294310 PMC6607763 Duong TV Nguyen TTP Pham KM Nguyen KT Giap MH Tran TDX Nguyen CX Yang S Su C Validation of the Short-Form Health Literacy Questionnaire (HLS-SF12) and Its Determinants among People Living in Rural Areas in Vietnam Int J Environ Res Public Health 2019 09 11 16 18 3346 10.3390/ijerph16183346 31514271 ijerph16183346 PMC6765800 Van Hoa H Giang HT Vu PT Van Tuyen D Khue PM Factors Associated with Health Literacy among the Elderly People in Vietnam Biomed Res Int 2020 03 27 2020 3490635 7 10.1155/2020/3490635 32309429 PMC7139882 Nguyen HC Nguyen MH Do BN Tran CQ Nguyen TTP Pham KM Pham LV Tran KV Duong TT Tran TV Duong TH Nguyen TT Nguyen QH Hoang TM Nguyen KT Pham TTM Yang S Chao JC Duong TV People with Suspected COVID-19 Symptoms Were More Likely Depressed and Had Lower Health-Related Quality of Life: The Potential Benefit of Health Literacy J Clin Med 2020 03 31 9 4 965 10.3390/jcm9040965 32244415 jcm9040965 PMC7231234 Nguyen HT Do BN Pham KM Kim GB Dam HT Nguyen TT Nguyen TT Nguyen YH Sørensen K Pleasant A Duong TV Fear of COVID-19 Scale-Associations of Its Scores with Health Literacy and Health-Related Behaviors among Medical Students Int J Environ Res Public Health 2020 06 11 17 11 4164 10.3390/ijerph17114164 32545240 ijerph17114164 PMC7311979 HLS-EU Consortium Comparative report of health literacy in eight EU member states The European Health Literacy Project 2009 2012-10-22 https://www.healthliteracyeurope.net/hls-eu Norman CD Skinner HA eHEALS: The eHealth Literacy Scale J Med Internet Res 2006 11 14 8 4 e27 10.2196/jmir.8.4.e27 17213046 v8i4e27 PMC1794004 World Health Organization Risk assessment and management of exposure of health care workers in the context of COVID-19: Interim guidance 2020 2020-03-19 https://www.who.int/publications/i/item/risk-assessment-and-management-of-exposure-of-health-care-workers-in-the-context-of-covid-19-interim-guidance Editorial Team Overview of novel coronavirus (2019-nCoV) BMJ Best Practice 2020 2020-02-10 https://bestpractice.bmj.com/topics/en-gb/3000165 Field A Discovering statistics using IBM SPSS statistics 2013 Washington DC, USA Sage Publications Ltd Kimberlin C Winterstein A Validity and reliability of measurement instruments used in research Am J Health Syst Pharm 2008 12 01 65 23 2276 84 10.2146/ajhp070364 19020196 65/23/2276 Terwee CB Bot SDM de Boer MR van der Windt DAWM Knol DL Dekker J Bouter LM de Vet HCW Quality criteria were proposed for measurement properties of health status questionnaires J Clin Epidemiol 2007 01 60 1 34 42 10.1016/j.jclinepi.2006.03.012 17161752 S0895-4356(06)00174-0 Cronbach LJ Shavelson RJ My Current Thoughts on Coefficient Alpha and Successor Procedures Educational and Psychological Measurement 2016 07 02 64 3 391 418 10.1177/0013164404266386 Maldonado G Greenland S Simulation study of confounder-selection strategies Am J Epidemiol 1993 12 01 138 11 923 36 10.1093/oxfordjournals.aje.a116813 8256780 van der Vaart R Drossaert C Development of the Digital Health Literacy Instrument: Measuring a Broad Spectrum of Health 1.0 and Health 2.0 Skills J Med Internet Res 2017 01 24 19 1 e27 10.2196/jmir.6709 28119275 v19i1e27 PMC5358017 Sørensen K Pelikan JM Röthlin F Ganahl K Slonska Z Doyle G Fullam J Kondilis B Agrafiotis D Uiters E Falcon M Mensing M Tchamov K van den Broucke S Brand H HLS-EU Consortium Health literacy in Europe: comparative results of the European health literacy survey (HLS-EU) Eur J Public Health 2015 12 05 25 6 1053 8 10.1093/eurpub/ckv043 25843827 ckv043 PMC4668324 Van Duong T Chiu C Lin C Chen YC Wong TC Chang P Yang SH E-healthy diet literacy scale and its relationship with behaviors and health outcomes in Taiwan Health Promot Int 2020 04 08 E 10.1093/heapro/daaa033 32267935 5817914 Zrubka Z Hajdu O Rencz F Baji P Gulácsi L Péntek M Psychometric properties of the Hungarian version of the eHealth Literacy Scale Eur J Health Econ 2019 06 16 20 Suppl 1 57 69 10.1007/s10198-019-01062-1 31098883 10.1007/s10198-019-01062-1 PMC6544600 Shiferaw KB Mehari EA Internet use and eHealth literacy among health-care professionals in a resource limited setting: a cross-sectional survey Adv Med Educ Pract 2019 10 563 570 10.2147/AMEP.S205414 31440113 205414 PMC6664426 Palesy D Jakimowicz S Health literacy training for Australian home care workers: Enablers and barriers Home Health Care Serv Q 2019 04 20 38 2 80 95 10.1080/01621424.2019.1604458 31007141 Duong T Sørensen K Pelikan JM Van den Broucke S Lin I Lin Y Huang H Chang PW Health-related behaviors moderate the association between age and self-reported health literacy among Taiwanese women Women Health 2018 07 06 58 6 632 646 10.1080/03630242.2017.1333074 28537772 Kim D Chang H Key functional characteristics in designing and operating health information websites for user satisfaction: an application of the extended technology acceptance model Int J Med Inform 2007 76 11-12 790 800 10.1016/j.ijmedinf.2006.09.001 17049917 S1386-5056(06)00206-1 Duong TV Aringazina A Baisunova G Nurjanah Pham TV Pham KM Truong TQ Nguyen KT Oo WM Mohamad E Su TT Huang H Sørensen K Pelikan JM Van den Broucke S Chang PW Measuring health literacy in Asia: Validation of the HLS-EU-Q47 survey tool in six Asian countries J Epidemiol 2017 02 27 2 80 86 10.1016/j.je.2016.09.005 28142016 S0917-5040(16)30077-6 PMC5328731 Elisabeth Stømer U Klopstad Wahl A Gunnar Gøransson L Hjorthaug Urstad K Health Literacy in Kidney Disease: Associations with Quality of Life and Adherence J Ren Care 2020 06 16 46 2 85 94 10.1111/jorc.12314 31950601 Huang Y Shiyanbola OO Chan H A path model linking health literacy, medication self-efficacy, medication adherence, and glycemic control Patient Educ Couns 2018 11 101 11 1906 1913 10.1016/j.pec.2018.06.010 29935739 S0738-3991(18)30308-2 Lor M Koleck TA Bakken S Yoon S Dunn Navarra A Association Between Health Literacy and Medication Adherence Among Hispanics with Hypertension J Racial Ethn Health Disparities 2019 06 3 6 3 517 524 10.1007/s40615-018-00550-z 30607576 10.1007/s40615-018-00550-z PMC6545226 Skoumalova I Kolarcik P Madarasova Geckova A Rosenberger J Majernikova M Klein D van Dijk JP Reijneveld SA Is Health Literacy of Dialyzed Patients Related to Their Adherence to Dietary and Fluid Intake Recommendations? Int J Environ Res Public Health 2019 11 05 16 21 4295 10.3390/ijerph16214295 31694265 ijerph16214295 PMC6862452 Li S Feng B Liao W Pan W Internet Use, Risk Awareness, and Demographic Characteristics Associated With Engagement in Preventive Behaviors and Testing: Cross-Sectional Survey on COVID-19 in the United States J Med Internet Res 2020 06 16 22 6 e19782 10.2196/19782 32501801 v22i6e19782 PMC7299540 Alsan M Stantcheva S Yang D Cutler D Disparities in Coronavirus 2019 Reported Incidence, Knowledge, and Behavior Among US Adults JAMA Netw Open 2020 06 01 3 6 e2012403 10.1001/jamanetworkopen.2020.12403 32556260 2767261 PMC7303811 Duong VT Lin I Sorensen K Pelikan JM Van Den Broucke S Lin Y Chang PW Health Literacy in Taiwan: A Population-Based Study Asia Pac J Public Health 2015 11 29 27 8 871 80 10.1177/1010539515607962 26419635 1010539515607962 Watson R Europeans with poor "health literacy" are heavy users of health services BMJ 2011 11 29 343 nov29 4 d7741 d7741 10.1136/bmj.d7741 22127773 Greenhalgh T Health literacy: towards system level solutions BMJ 2015 02 24 350 feb24 13 h1026 h1026 10.1136/bmj.h1026 25712067 Duong TV Pham KM Do BN Kim GB Dam HTB Le VT Nguyen TTP Nguyen HT Nguyen TT Le TT Do HTT Yang S Digital Healthy Diet Literacy and Self-Perceived Eating Behavior Change during COVID-19 Pandemic among Undergraduate Nursing and Medical Students: A Rapid Online Survey Int J Environ Res Public Health 2020 09 30 17 19 7185 10.3390/ijerph17197185 33008102 ijerph17197185 PMC7579441 Britt RK Collins WB Wilson K Linnemeier G Englebert AM eHealth Literacy and Health Behaviors Affecting Modern College Students: A Pilot Study of Issues Identified by the American College Health Association J Med Internet Res 2017 12 19 19 12 e392 10.2196/jmir.3100 29258979 v19i12e392 PMC5750421 Mitsutake S Shibata A Ishii K Oka K Associations of eHealth Literacy With Health Behavior Among Adult Internet Users J Med Internet Res 2016 07 18 18 7 e192 10.2196/jmir.5413 27432783 v18i7e192 PMC4969548 Owen L Corfe B The role of diet and nutrition on mental health and wellbeing Proc Nutr Soc 2017 11 76 4 425 426 10.1017/S0029665117001057 28707609 S0029665117001057 Ministry of Health Coronavirus disease (COVID-19) outbreak in Vietnam 2020 2020-05-04 https://ncov.moh.gov.vn/