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Maintenance of good health and a healthy lifestyle have significant impacts on the lives of university students. However, university students are prone to engage in risky health behaviors, resulting in impaired health status. Electronic health (eHealth) literacy is an important factor in maintaining a healthy lifestyle. However, no studies have assessed the eHealth literacy levels and the associated lifestyle behaviors among university students in Japan.
The purposes of this study were to clarify the eHealth literacy level, the participant characteristics associated with eHealth literacy, and the association of eHealth literacy with lifestyle behaviors of students in a Japanese university.
A questionnaire-based cross-sectional study of 3183 students at a national university in Japan was conducted. eHealth literacy was quantified using the Japanese version of the eHealth Literacy Scale (eHEALS). The association between participant characteristics (gender, school year, department of study, and living status) and eHEALS score was assessed using
The mean eHEALS score was 23.6/40 points. The mean eHEALS score for students in medical departments was 27.0/40 points, which was 2.9 points higher than that of nonmedical students (
The eHealth literacy level of university students in Japan was comparable to that of the general Japanese population. Graduate students, as well as those in medical departments, had higher eHealth literacy. Furthermore, students with higher eHealth literacy had better exercise routines.
Healthy lifestyle behaviors, such as exercising regularly, sleeping well, and eating breakfast, have a significant impact on university student life. For example, students with healthy lifestyles achieve higher academic degrees than those without [
Health literacy is defined as an individual’s knowledge, motivation, and skills to access, understand, evaluate, and apply health information [
In the general population, many personal and social background characteristics, including age, gender, household income, educational level, and occupation, are associated with health literacy levels [
Studies have shown that people with higher eHealth literacy have healthier lifestyles than those with lower eHealth literacy in the general population [
The purposes of this study were to clarify the eHealth literacy level, the participant characteristics associated with eHealth literacy, and the association of eHealth literacy with lifestyle behaviors of students in a Japanese university.
This study was a questionnaire-based cross-sectional study performed at Chiba University, Japan. Chiba University is a national university with 13,983 students at the time of the study. Of those, 5306/13,983 (37.9%) were female and 8677/13,983 (62.1%) were male. Furthermore, 10,547/13,983 (75.4%) were undergraduate students, and 2430/13,983 (17.4%) students were studying medical sciences, including medicine, nursing, and pharmacy. Inclusion criteria were students who underwent on-campus medical examinations from April to May 2019. Exclusion criteria were students who declined to participate and who did not understand the Japanese questionnaire. Furthermore, students with incomplete answers to the questionnaire were excluded. We recruited participants during 12/19 checkup days. Of 13,983 university students, 5310 (38.0%) underwent the checkup during the 12 days. Of those, 1918/5310 (36.1%) declined to participate, and the remaining 3392 students (63.9%) answered the questionnaire. No student was excluded because of inability to understand the Japanese questionnaire. After excluding 209 students with incomplete answers, the data from 3183 students were used for analysis. The Chiba University Ethics Committee approved this study (approval number 01-02). The data were collected anonymously. No gifts or payments were given to participants for participating in this study.
The questionnaire consisted of questions on eHealth literacy, participant characteristics, and lifestyle behaviors.
The Japanese version of the eHealth Literacy Scale (eHEALS) was used to quantify eHealth literacy [
The participant characteristics included gender, school year, department of study, and living status. Answers for school year (first to sixth year of undergraduate studies and first to fourth year of graduate school) were dichotomized into undergraduate and graduate [
Lifestyle behaviors were assessed using the questions on exercise, breakfast, smoking, alcohol consumption, and hours of sleep. Answers for exercise frequency (≥3 days/week, 1-2 days/week, 1-2 days/month, none) were dichotomized into ≥1 day/week and <1 day/week for statistical analysis [
Demographic data on the participants’ characteristics and lifestyle were expressed using descriptive statistics. Numbers and frequencies were used for categorical variables. Means and standard deviations were used for continuous variables because most of the data had a normal distribution. Participants were dichotomized into two groups depending on the characteristic (eg, undergraduate/graduate). The eHEALS scores were compared between groups using Student
Of the 3183 participants, 878 (27.6%) were female, and 2549 (80.1%) were undergraduate students (
For lifestyle behaviors, 1757/3183 (55.2%) participants exercised ≥1 day/week (
Participant characteristics (N=3183).
Characteristic | Participants, n (%) | ||
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Male | 2305 (72.4) | |
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Female | 878 (27.6) | |
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1 | 606 (19.0) |
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2 | 622 (19.5) |
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3 | 608 (19.1) |
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4 | 613 (19.3) |
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5 | 45 (1.4) |
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6 | 55 (1.7) |
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1 | 320 (10.1) |
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2 | 271 (8.5) |
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3 | 28 (0.9) |
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4 | 15 (0.5) |
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Medicine | 606 (19.0) |
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Nursing | 55 (1.7) |
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Pharmacy | 125 (3.9) |
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Graduate school of medical and pharmaceutical science | 14 (0.4) |
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Graduate school of nursing | 13 (0.4) |
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Nonmedicala | 2837 (89.1) | |
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Living alone | 1600 (50.2) | |
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Living with parents | 1530 (48.1) |
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Living in dormitory | 46 (1.4) |
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Other | 7 (0.2) |
aThe 2837 nonmedical students were studying education (n=436, 15.4%), engineering (n=887), science (n=257, 31.3%), horticulture (n=68, 2.4%), law, politics, and economics (n=402, 14.2%), liberal arts and science (n=101, 3.6%), literature (n=179, 6.3%), graduate education (n=28, 1.0%), graduate horticulture (n=7, 0.2%), graduate humanities and studies on public affairs (n=34, 1.2%), graduate science and engineering (n=427, 15.1%), and law (n=11, 0.4%).
Lifestyle behaviors of the participants (N=3183).
Lifestyle behavior | Participants, n (%) | ||
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≥3 days/week | 657 (20.6) |
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1-2 days/week | 1100 (34.6) |
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1-2 days/month | 632 (19.9) |
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None | 794 (24.9) |
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Every day | 1651 (51.9) |
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5-6 days/week | 481 (15.1) |
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1-4 days/week | 557 (17.5) |
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None | 494 (15.5) |
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No | 2967 (93.2) |
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Previously | 76 (2.4) |
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Smoker | 140 (4.4) | |
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None | 1208 (38.0) |
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1-2 days /month | 1189 (37.4) |
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1-2 days/week | 620 (19.5) |
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≥3 days/week | 166 (5.2) | |
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7-8 hours | 1822 (57.2) |
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≥9 hours | 56 (1.8) |
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Insufficient (≤6 hours) | 1305 (41.0) | |
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Normal (≥18.5, <25) | 2422 (76.1) | |
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Underweight (<18.5) | 480 (15.1) | |
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≥25, <30 | 230 (7.2) |
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≥30 | 51 (1.6) |
The mean eHEALS score was 23.6/40 points (SD 6.8). The mean scores for each item ranged from 2.7 to 3.1. The lowest score for was obtained for Q6: “I have the skills I need to evaluate the health resources I found on the internet,” and the highest score was obtained for Q8: “I feel confident in using information from the Internet to make health decisions.”
The mean eHEALS score for medical students was 2.9 points higher than that for nonmedical students (
Association between participant characteristics and eHEALS score (N=3183).
Characteristic (n) | eHEALSa score, mean (SD) | ||
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Male (2305) | 23.6 (7.0) | .18 |
Female (878) | 23.3 (6.3) |
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Undergraduate (2549) | 23.4 (6.8) | .003 |
Graduate (634) | 24.3 (6.6) |
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Medical (346) | 27.0 (6.6) | <.001 |
Nonmedical (2837) | 23.1 (6.7) |
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Living alone (1600) | 23.8 (6.9) | .02 |
Living with others (1583) | 23.3 (6.7) |
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aeHEALS: eHealth Literacy Scale.
Overall, participants in the high eHEALS score group had a healthier lifestyle than those in the low score group (
Association of eHEALS score with lifestyle (N=3183). OR values are for the high eHEALS score group (n=1659) relative to the low score group (n=1524).
Lifestyle behavior | Unadjusted ORa (95% CI) | Adjustedb OR (95% CI) | Model |
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Regular exercise | 1.42 (1.23-1.63) | <.001 | 1.39 (1.21-1.61) | <.001 | <.001 |
Regular breakfast | 1.18 (1.02-1.37) | .02 | 1.24 (1.06-1.45) | .007 | <.001 |
No smoking | 1.24 (0.88-1.74) | .22 | 1.18 (0.8-1.67) | .36 | <.001 |
Alcohol <3 days/week | 0.80 (0.59-1.10) | .17 | 0.82 (0.59-1.12) | .21 | <.001 |
Sufficient sleep | 1.10 (0.96-1.27) | .17 | 0.91 (0.79-1.06) | .22 | <.001 |
Overweight (n=2703)c | 1.58 (1.23-2.05) | <.001 | 1.49 (1.20-2.02) | <.001 | <.001 |
Underweight (n=2902)d | 0.93 (0.76-1.13) | .47 | .94 (0.77-1.15) | .54 | .14 |
aOR: odds ratio.
bAdjusted for gender, school year, department of study, and living status.
cn=1421 (52.6%) and n=1282 (47.4%) in the high and low eHEALS score groups, respectively.
dn=1476 (50.9%) and n=1426 (49.1%) in the high and low eHEALS score groups, respectively.
We showed that the average eHEALS score of students at a Japanese national university was approximately 24 points out of 40. Several personal background characteristics, including school year and department of study, were associated with a high eHEALS score. Additionally, students with higher eHEALS scores demonstrated better exercise behaviors. To the best of our knowledge, this is the first such study of Japanese students and one of the largest studies to clarify the eHealth literacy levels and related lifestyle behaviors of university students. Our results provide important information to help university students improve their eHealth literacy and achieve healthier lifestyles.
In this study, the mean eHEALS score of the participants was 23.6/40 points. This value is comparable to that of general Japanese adults, whose mean score was 23.5 points [
In this study, undergraduate and graduate students in the medical sciences (ie, medicine, nursing, and pharmacy) had higher eHEALS scores than those in nonmedical departments. This result was consistent with a study of 566 Taiwanese college students, in which medical students had higher eHealth literacy in all dimensions than nonmedical students [
The graduate student participants had higher eHEALS scores than undergraduate students, although the difference in the mean score was only 0.9 points. In studies of medical and nursing students, a higher school year was associated with higher eHealth literacy [
This study showed that participants in the high eHEALS score group exercised more frequently than those in the low score group. This association was significant after adjusting for participant characteristics. A relationship between higher eHealth literacy and better exercise behaviors is consistently found in Taiwanese, American, and Greek university students [
In this study, a higher eHEALS score was associated with regularly eating breakfast. Our result was in line with previous studies, which showed that higher eHealth literacy was correlated with healthy diet behavior among American and Taiwanese college students [
Smoking and excessive alcohol were not associated with eHEALS score. Our results were consistent with general surveys of Japanese adults, in which the eHEALS score [
This study has several limitations. First, this study was conducted at a single national university. Therefore, the results may not apply to university students from other backgrounds. For example, the type of university (ie, public or private) could affect the students’ eHealth literacy levels [
The eHealth literacy level of Chiba University students was comparable to that of the general Japanese population. Graduate students, as well as those in medical departments, had higher eHealth literacy levels. Furthermore, the students with higher eHealth literacy levels demonstrated better exercise behaviors. Interventions to address eHealth literacy could help improve students’ lifestyles, although further research is warranted.
eHealth Literacy Scale
electronic health
European Health Literacy Survey Questionnaire
odds ratio
None declared.