| Literature DB >> 34071469 |
Sunghee Kim1, Jihyun Oh2.
Abstract
The availability of a wide range of online health-related information on the internet has made it an increasingly popular source of health information, particularly for people in their 20s. This study aimed to explore possible multistep and indirect pathways of association between e-health literacy and health-promoting behaviors through social media use for health information, online health information-seeking behaviors, and self-care agency among nursing students. The study included 558 nursing students from three different universities in South Korea. Data were collected using structured questionnaires from 2 August to 29 August, 2019. The results show that e-health literacy had a significant direct effect on health-promoting behaviors through the three mediators. Moreover, the overall model explained 46% of the total variance in health-promoting behaviors. Based on these findings, it is necessary to introduce interventions that improve e-health literacy and develop a strategy to promote healthy behaviors. It is also necessary to develop programs to improve e-health literacy competency in nursing students. Moreover, health interventions that improve health-promoting behaviors should be developed, and research to evaluate the effect of the interventions should be conducted.Entities:
Keywords: e-health literacy; health-promoting behaviors; nursing students; online health information-seeking behaviors; self-care agency
Year: 2021 PMID: 34071469 PMCID: PMC8199246 DOI: 10.3390/ijerph18115804
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1The results of the multiple mediation model testing social media use for health information, online health information-seeking behaviors, and self-care agency as mediators of the effect of e-health literacy on health-promoting behaviors. ** p < 0.01.
Descriptive Statistics (n = 558).
| Characteristics | Mean (SD) | Range | |
|---|---|---|---|
| Age (year) | 20.3 (2.2) | 17–43 | |
| Gender | |||
| Male | 65 (11.6) | ||
| Female | 493 (88.4) | ||
| Grade | |||
| Freshman | 164 (29.4) | ||
| Sophomore | 129 (23.1) | ||
| Junior | 130 (23.3) | ||
| Senior | 135 (24.2) | ||
| Religion | |||
| Christianity | 142 (25.4) | ||
| Roman Catholicism | 44 (7.9) | ||
| Buddhism | 33 (5.9) | ||
| None | 339 (60.8) | ||
| Time spent using the internet per week (days) | |||
| 1 or 2 days | 47(8.4) | ||
| 3 or 4 days | 94(16.8) | ||
| More than 4 days | 417(74.7) | ||
| Time spent using the internet per day (hours) | |||
| <2 | 173 (31.0) | ||
| 2 to <3 | 142 (28.7) | ||
| 3 to <4 | 99 (20.0) | ||
| ≥4 | 101 (20.4) | ||
| Health status | |||
| Good | 309 (55.4) | ||
| Neutral | 211 (37.8) | ||
| Bad | 38 (6.8) | ||
| Self-care agency | 156.17 (20.17) | 105–204 | |
| E-health literacy | 30.53 (5.20) | 15–40 | |
| Social media use for health information | 2.22 (1.10) | 0–4 | |
| Online health information-seeking behaviors | 36.61 (9.93) | 13–65 | |
| Health-promoting behaviors | 2.50 (0.44) | 1.1–4.0 | |
| Health responsibility | 2.17 (0.58) | 1–4 | |
| Physical activity | 2.10 (0.72) | 1–4 | |
| Nutrition | 2.18 (0.61) | 1–4 | |
| Spiritual growth | 2.87 (0.61) | 1.1–4.0 | |
| Interpersonal support | 3.15 (0.57) | 1.2–4.0 | |
| Stress management | 2.55 (0.59) | 1.1–4.0 |
Correlations between self-care agency, e-health literacy, social media use for health information, online health information-seeking behaviors, and HPB (n = 558).
| r ( | |||||
|---|---|---|---|---|---|
| Variables | Self-Care Agency | E-Health Literacy | Social Media Use for Health Information | Online Health Information- Seeking Behaviors | HPB |
| Self-care agency | — | ||||
| E-health literacy | 0.45 | — | |||
| Social media use for health information | 0.26 | 0.26 | — | ||
| Online health information-seeking behaviors | 0.29 | 0.25 | 0.36 | — | |
| HPB | 0.64 | 0.37 | 0.25 | 0.39 | — |
Note. HPB = Health-Promoting Behaviors.
Total, direct, and indirect effects in the multiple mediator model.
| Model | Effect | SE | t |
| 95% BC CI |
|---|---|---|---|---|---|
| Total effect of e-HL on HPB | 1.61 | 0.16 | 9.61 | <0.001 | 1.28, 1.94 |
| Direct effect of e-HL on HPB | 0.30 | 0.15 | 1.97 | 0.048 | 0.001, 0.60 |
| Total indirect effect | 1.31 | 0.13 | 1.04, 1.58 | ||
| Indirect effect via social media use for health information | 0.01 | 0.04 | −0.05, 0.10, ns | ||
| Indirect effect via social media use for health information, OHISB | 0.07 | 0.02 | 0.03, 0.11 | ||
| Indirect effect via social media use for health information and self-care agency | 0.06 | 0.02 | 0.01, 0.12 | ||
| Indirect effect via social media use for health information, OHISB, and self-care agency | 0.03 | 0.01 | 0.01, 0.05 | ||
| Indirect effect via OHIS | 0.14 | 0.04 | 0.06, 0.24 | ||
| Indirect effect via self-care agency | 0.91 | 0.11 | 0.70, 1.14 | ||
| Indirect effect via OHIS and self-care agency | 0.06 | 0.02 | 0.02, 0.11 |
Note. e-HL = e-health literacy; HPB = Health-Promoting Behaviors; OHISB = Online Health Information-Seeking Behaviors; BC CI = bias-corrected confidence interval; ns = not significant.