Dataset Information

Negative Impact of Fear of COVID-19 on Health-Related Quality of Life Was Modified by Health Literacy, eHealth Literacy, and Digital Healthy Diet Literacy: A Multi-Hospital Survey.

ABSTRACT:

Background

The COVID-19 pandemic has been disseminating fear in the community, which has affected people's quality of life, especially those with health problems. Health literacy (HL), eHealth literacy (eHEAL), and digital healthy diet literacy (DDL) may have potential impacts on containing the pandemic and its consequences. This study aimed to examine the association between the fear of COVID-19 scale (FCoV-19S) and the health-related quality of life (HRQoL), and to examine the effect modification by HL, eHEAL, and DDL on this association.

Methods

A cross-sectional study was conducted in 11 hospitals across Vietnam from 7 April to 31 May 2020. Data were collected on 4348 outpatients, including demographic characteristics, HL, eHEAL, DDL, FCoV-19S, and HRQoL. Multiple linear regression and interaction models were used to explore associations.

Results

Patients with higher FCoV-19S scores had lower HRQoL scores (unstandardized coefficient, B = -0.78, p < 0.001). HL (B = 0.20, p < 0.001), eHEAL (B = 0.24, p < 0.001), and DDL (B = 0.20, p < 0.001) were positively associated with higher HRQoL scores. The negative impact of FCoV-19S on HRQoL was significantly attenuated by higher eHEAL score groups (from one standard deviation (SD) below the mean, B = -0.93, p < 0.001; to the mean, B = -0.85, p < 0.001; and one SD above the mean, B = -0.77, p < 0.001); and by higher DDL score groups (from one SD below the mean, B = -0.92, p < 0.001; to the mean, B = -0.82, p < 0.001; and one SD above the mean, B = -0.72, p < 0.001).

Conclusions

eHealth literacy and digital healthy diet literacy could help to protect patients' health-related quality of life from the negative impact of the fear of COVID-19 during the pandemic.

SUBMITTER: Nguyen MH

PROVIDER: S-EPMC8124355 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundDigital health interventions (DHIs) are increasingly being adopted globally to address various public health issues. DHIs can be categorized according to four main types of technology: mobile based, web based, telehealth, and electronic health records. In 2006, Norman and Skinner introduced the eHealth literacy model, encompassing six domains of skills and abilities (basic, health, information, scientific, media, and computer) needed to effectively understand, process, and act on health-related information. Little is known about whether these domains are assessed or accounted for in DHIs.ObjectiveThis study aims to explore how DHIs assess and evaluate the eHealth literacy model, describe which health conditions are addressed, and which technologies are used.MethodsWe conducted a scoping review of the literature on DHIs, based on randomized controlled trial design and reporting the assessment of any domain of the eHealth literacy model. MEDLINE, CINAHL, Embase, and Cochrane Library were searched. A duplicate selection and data extraction process was performed; we charted the results according to the country of origin, health condition, technology used, and eHealth literacy domain.ResultsWe identified 131 unique DHIs conducted in 26 different countries between 2001 and 2020. Most DHIs were conducted in English-speaking countries (n=81, 61.8%), delivered via the web (n=68, 51.9%), and addressed issues related to noncommunicable diseases (n=57, 43.5%) or mental health (n=26, 19.8%). None of the interventions assessed all six domains of the eHealth literacy model. Most studies focused on the domain of health literacy (n=96, 73.2%), followed by digital (n=19, 14.5%), basic and media (n=4, 3%), and information and scientific literacy (n=1, 0.7%). Of the 131 studies, 7 (5.3%) studies covered both health and digital literacy.ConclusionsAlthough many selected DHIs assessed health or digital literacy, no studies comprehensively evaluated all domains of the eHealth literacy model; this evidence might be overlooking important factors that can mediate or moderate the effects of these interventions. Future DHIs should comprehensively assess the eHealth literacy model while developing or evaluating interventions to understand how and why interventions can be effective.

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Project description:BackgroundThe eHealth Literacy Scale (eHEALS) is a tool for the self-assessment of perceived comfort and skills in using the internet as a source for health-related information. Although evidence exists of the reliability and construct and structural validity of the scale, there is a lack of evidence in relation to what is proposed by Norman and Skinner in their theoretical lily model of eHealth literacy; in particular it is not clear whether having a higher level of health literacy can positively influence electronic health (eHealth) literacy as measured by the eHEALS.ObjectiveOur study aim was to assess whether real-life experiences from studying or working in the health field, as a proxy of higher functional health literacy, correlate with self-referred eHealth literacy as measured by the eHEALS.MethodsA Web-based survey was conducted among adults living in Northeast Italy using an Italian version of the eHEALS (IT-eHEALS). In order to be able to measure the effect of higher functional health literacy on eHealth literacy, we divided our sample into two groups, respectively characterized by studying or working experience in the health sector and by lack thereof. Mean differences between eHEALS were calculated using t test and effect size evaluated using Cohen d. To ensure the validity of the IT-eHEALS, we evaluated its psychometric properties (internal consistency and dimensionality) and construct validity (by evaluating its correlation with respondents age, gender, educational attainment, self-rated health, use of internet for health-related purposes, and working status).ResultsA total of 868 respondents that completed the IT-eHEALS were included for analysis, of which 259 had working or studying experience in the health field. Mean (SD) eHEALS total score was 28.2 (6.2) for the whole sample, with statistically significant differences (P<.001) between the two groups, with the higher health literate group scoring significantly better (31.9 (5.9) vs 26.7 (5.6), respectively), with a standardized mean difference (Cohen d) of 0.9. Interestingly, we found a weak, yet significant, correlation between eHealth literacy and respondent characteristics for the higher health literate group only, as measured by positive Spearman correlation coefficients for age (0.11, P=.001), educational attainment (0.19, P=.002) and self-rated health (0.14, P=.024). Also, in line with current literature, correlation of eHEALS score with frequency of internet use for health-related purposes was significant for both groups (0.32, P<.001 and 0.15, P<.001 for higher and lower health literacy group, respectively). In our study we could not find any difference related to gender, while a significant difference for working status was only present when considering the sample as a whole (P=.03).ConclusionsOur study demonstrates a sizeable effect of higher levels of functional health literacy on the eHEALS score, corroborating what was initially proposed by Norman and Skinner in the lily model of eHealth literacy.