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Health literacy describes skills and competencies that enable people to gain access to, understand and apply health information to positively influence their own health and the health of those in their social environments. In an increasingly media saturated and digitized world, these skill sets are necessary for accessing and navigating sources of health information and tools, such as television, the Internet, and mobile apps. The concepts of Media Health Literacy (MHL) and eHealth Literacy (eHL) describe the specific competencies such tasks require. This article introduces the two concepts, and then reviews findings on the associations of MHL and eHL with several contextual variables in the social environment such as socio-demographics, social support, and system complexity, as a structural variable. As eHL and MHL are crucial for empowering people to actively engage in their own health, there is a growing body of literature reporting on the potential and the effectiveness of intervention initiatives to positively influence these competencies. From an ethical standpoint, equity is emphasized, stressing the importance of accessible media environments for all-including those at risk of exclusion from (digital) media sources. Alignment of micro and macro contextual spheres will ultimately facilitate both non-digital and digital media to effectively support and promote public health.
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International Journal of
Environmental Research
and Public Health
Review
Media Health Literacy, eHealth Literacy, and the Role
of the Social Environment in Context
Diane Levin-Zamir 1, 2,* and Isabella Bertschi 3
1Department of Health Education and Promotion, Clalit Health Services, Tel Aviv 62098, Israel
2School of Public Health, University of Haifa, Haifa 31905, Israel
3Department of Psychology, University of Zurich, Zürich 8050, Switzerland;
isabella.bertschi@psychologie.uzh.ch
*Correspondence: diamos@zahav.net.il; Tel.: +972-50-626-3033
Received: 17 July 2018; Accepted: 30 July 2018; Published: 3 August 2018
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Abstract:
Health literacy describes skills and competencies that enable people to gain access to,
understand and apply health information to positively influence their own health and the health
of those in their social environments. In an increasingly media saturated and digitized world,
these skill sets are necessary for accessing and navigating sources of health information and tools,
such as television, the Internet, and mobile apps. The concepts of Media Health Literacy (MHL)
and eHealth Literacy (eHL) describe the specific competencies such tasks require. This article
introduces the two concepts, and then reviews findings on the associations of MHL and eHL with
several contextual variables in the social environment such as socio-demographics, social support,
and system complexity, as a structural variable. As eHL and MHL are crucial for empowering people
to actively engage in their own health, there is a growing body of literature reporting on the potential
and the effectiveness of intervention initiatives to positively influence these competencies. From an
ethical standpoint, equity is emphasized, stressing the importance of accessible media environments
for all—including those at risk of exclusion from (digital) media sources. Alignment of micro and
macro contextual spheres will ultimately facilitate both non-digital and digital media to effectively
support and promote public health.
Keywords:
health literacy; Media Health Literacy; eHealth Literacy; social environment; health apps;
social support; digital health; empowerment
1. Introduction
Several factors have led, and continue to lead, to the development of health systems that enable,
but also partly expect their users to adopt a much more active role in their health management than
was customary some decades ago. The empowerment of groups and individuals to engage in their
own health, for example by shared decision-making with health professionals, or by adoption of
health-promoting lifestyles, is an important goal of public health in the 21st century and a priority in
the UN Sustainable Development Goals. Being able to actively manage one’s health is very demanding
of citizens. It is largely, although by no means entirely, dependent on the availability, accessibility,
and appropriateness of health information. To reflect the skill set required to effectively manage
health and navigate the health system from health care to disease prevention and health promotion,
the concept of health literacy was developed. A wide variety of definitions exist, but in general Health
literacy (HL) is conceptualized as skills and competences enabling people to obtain and interpret health
information and apply their knowledge to inform health-related decision-making (for an overview of
definitions see e.g., [1,2]).
Int. J. Environ. Res. Public Health 2018,15, 1643; doi:10.3390/ijerph15081643 www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2018,15, 1643 2 of 12
In an increasingly media saturated and digital environment, a large proportion of health-related
messages and information today is circulated and accessed through the media and digital sources. Thus,
researchers together with health practitioners have developed two closely linked, but nonetheless
distinct concepts related to HL: Media Health Literacy [
3
] and eHealth Literacy [
4
]. Media Health
Literacy and eHealth Literacy have both proven to be associated with health information seeking and
with health outcomes such as health behavior and health status across various population groups.
Environmental factors linked to the social, organizational or economic context play an important role
(a) in shaping individual, group or population MHL and eHL skills and (b) by posing specific demands
on the situations in which such skills are required by the individual or group.
This article aims to introduce readers to the concepts of Media Health Literacy and eHealth
Literacy, emphasizing their role in the social environment while demonstrating how context variables
are relevant when applying the concepts in research and practice. We will critically discuss issues
related to the two concepts and explore the ethical aspects of these concepts in research, practice,
and policy.
2. The Concepts of Media Health Literacy and eHealth Literacy
Media Health Literacy (MHL) [
3
] is based on and builds on the synthesis of health literacy and
media literacy [
5
]—two essential concepts for understanding the scope and significance of eHealth
Literacy. The concept of Media Health Literacy is unique in that it takes into consideration not only
information that has been communicated through the media to offer health guidance; but it also
considers implicit and explicit mass media content commonly generated by commercial entities or
health systems that can be either health-promoting or health-compromising. Based on the typology of
the Nutbeam model of Health Literacy [
6
], Media Health Literacy is conceptualized as a continuum,
ranging from (1) the ability to identify health-related content (explicit and/or implicit) in the various
types of media; (2) recognize its influence on health behavior; (3) critically analyze the content
(comparable to Critical Health Literacy), and (4) express intention to respond through action measured
through personal health behavior or advocacy (comparable to Interactive Health Literacy). Thus,
the validated measure of Media Health Literacy is comprised of these four categories and was shown
to be highly correlated with health empowerment. As such, Media Health Literacy can be considered
the precursor to eHealth literacy and is highly relevant for both non-digital (television, print, radio,
etc.) and digital media (Internet, social media, and mobile tools).
While media in general has long since been recognized as the only social institution that
accompanies the individual throughout the entire life course [
7
], over the past decade, digital media
has received particular attention with regards to use for health purposes. The number of digital health
offers has grown with impressive speed—an annual growth rate of about 25%. According to data
from Research2Guidance, approximately 325,000 health apps were available in 2017, with 78,000 new
mobile health applications being released between 2016 and 2017. Although it has been shown that
only 7% of mHealth apps have more than 50,000 monthly active users, usage proportions are very
likely to increase significantly in the near future [
8
]. The growing importance of digital media has
led researchers, practitioners, and policy makers to reflect on the skills necessary for users, and the
challenges they face to achieve effective outcomes, namely navigating the services, accessing relevant
health information and adopting lifestyle changes. Well over a decade ago, Norman and Skinner [
4
]
as pioneers in the field introduced the term eHealth Literacy (eHL) meaning ”the ability to seek,
find, understand, and appraise health information from electronic sources and apply the knowledge
gained to addressing or solving a health problem” (p. 1). They also developed a measurement tool
for eHealth Literacy that has been used in many different settings around the globe, the eHealth
Literacy Scale (eHEALS) [
9
]. It consists of eight items for which respondents self-rate their ease and
skills when navigating Internet sources for valid health information. The original English scale has
been translated into many languages, including Japanese, Korean, German, Italian, Spanish, Greek,
and Hebrew. Although widely used, the eHEALS’ validity has been questioned, mainly due to the
Int. J. Environ. Res. Public Health 2018,15, 1643 3 of 12
lack of correlation between eHEALS scores and actual task performance in online health information
seeking [
10
,
11
], and because it does not sufficiently address critical and interactive health literacy
skills [
12
,
13
]. Cameron Norman, the first author of the eHEALS, has also expressed some concern as
to whether the scale is able to measure eHealth Literacy in its totality in a world that has witnessed
the rise of Web 2.0, and that is generally characterized by the use of ever-changing technology:
“The fundamental collection of skills that comprise eHealth Literacy have not likely changed, but the
contexts in which they are expressed (...) have” [
12
] (p. 3). This illustrates the dynamic nature of the
concept of eHealth Literacy, and thus also of Media Health Literacy, as both terms qualify skill sets
that can only be understood and analyzed within the media environment in which they are applied.
3. Media Health Literacy and eHealth Literacy in Context
The media, and especially the realm of digital media, constitute a complex social environment to
be navigated by consumers in order to promote and maintain health using the information available in
this environment. Tasks related to Media and eHealth Literacy are thus by no means trivial. In order
to understand how demanding they are, we illustrate the multi-faceted nature with a case study
before focusing on context variables associated with Media Health Literacy and eHealth Literacy
task performance.
Chan and Kaufman [
14
] used Cognitive Task Analysis to map consumers’ performance during
information-seeking and decision-making tasks involving eHealth tools. To disentangle knowledge,
thought processes and skills necessary for task completion, they coded every reported step in a
matrix involving facets of eHealth Literacy and levels of cognitive complexity. They drew on Norman
and Skinner’s [
4
] Lily model which postulates that eHealth Literacy combines six literacy domains:
traditional literacy, information literacy, scientific literacy, media literacy, computer literacy, and health
literacy. Any given eHealth Literacy task requires a certain degree of skills and knowledge in the
said areas. In their study, detailed analyses of performance in a six-step task involving a consumer
health webpage showed that any step required skills from at least two literacy domains, often more,
with the cognitive complexity most often rated 4 or 5 out of 6 levels by experts. The most frequently
identified barriers to task completion were encountered with steps requiring information and computer
literacy. Surprisingly, the majority of challenges faced by participants fell within the lower ranges of
cognitive demands.
This example demonstrates that eHealth Literacy, as mentioned, is by no means a trivial set of
skills in a highly digitalized environment. On the contrary, it combines knowledge and skills from a
wide variety of domains and is inherently relevant within the social contexts in which Health Literacy,
Media Health Literacy, and eHealth Literacy are developed and applied by an individual or group.
The following sections, as illustrated in Figure 1, will elaborate on what is known regarding how
factors in an ecological model affect Media Health Literacy and eHealth Literacy. Growing academic
attention has been given to system complexity, personal and socio-demographic factors such as age,
gender, and education, social environment and context that together play a major role in shaping skills
in performing health literacy related tasks in digital media environments.
Int. J. Environ. Res. Public Health 2018,15, 1643 4 of 12
Int.J.Environ.Res.PublicHealth2018,15,xFORPEERREVIEW 4of12
Figure1.ThecomplexityofeHealthLiteracy(eHL)andMediaHealthLiteracy(MHL)incontext.
3.1.ComplexityofSystemsandEnvironments
In2009,Parker[15]madeanimportantstatementthatisoccasionallyforgotteninadiscourse
thatfocusesitsattentionpredominantlyonhealthliteracyasanindividualcombinationofskills:
“Onemustalignskillsandabilitieswiththedemandsandcomplexitiesofthesystem”(p.92).She
illustratedthiswithasimpledrawingoftwoarrowspointingtowardeachother,onerepresenting
“skills/abilities”andtheotherlabelled“demands/complexity”.Wherethetwoarrowsmeet,she
wrote,iswherehealthliteracyisexpressed.
Digitalmediasourcesofhealthinformationhaveparticularpotentialtoreducesystem
complexity.Usabilityandaccessibilityaretopicsthatreceivespecificattentionfromsoftware
developersandwebdesigners.Severalfindingssuggestthatfocusingonuserexperienceand
designingwiththeaimofreducingcomplexityarebeneficialfordigitalhealthliteracy.Forexample,
disadvantageinwrittenandspokenlanguageskillscanbebarrierstoaccessingonlinehealth
information[16].Informationshould,therefore,bemadeincreasinglyavailableinmoreinteractive
formatsthatdependlessonformalliteracyandknowledgeofthelocallanguage[17].Meppelinkand
colleagues[18]provideempiricalsupportforthisclaim.Inanexperimentalstudytheyshowthat
recallandattitudechangeweresignificantlyhigherinlowhealthliterateparticipantswhen
informationwaspresentedverballyandenrichedwithanimationssupportingthecontentcompared
tostandardwrittentextandillustrations.Contentmustbeadaptedtoberelevanttothespecific
population,forexampletakingintoconsiderationculturaleatinghabitswhendesigninga
smartphoneapptosupportweightloss[19].Thus,(digital)mediasolutionsforhealthactuallydo
havethepotentialtocontributetomakinghealthinformationmoreaccessibleandunderstandable
forbroadsectionsofthepopulation,eventuallyfosteringpositiveeffectsonhealth[20].
Systemcomplexityisalsoreducedwhenpeoplebecomemoreexperiencedwithhealthliteracy
tasksandwiththetechnologythatcanbeusedtoapplyhealthliteracyskills.Accordingly,eHealth
LiteracyscoresarepositivelyassociatedwithfrequencyofuseoftheInternet[21,22]andwiththe
numberofWebsearchesforhealthinformation[23].HigheHealthLiteracylevelsareassociatedwith
theuseofsocialmediaforthepurposeofseekinghealthinformation,andwithfrequentuseof
electronicdevicesingeneral[24].ItcanalsobeshownthateHealthLiteracyscoresarehigherfor
studentswhohadbeenactivelyinvolvedinsearchingforhealthinformationonlinethanfornon
experiencedpeers[25].Similarly,datasuggestthatparentalonlinehealthinformationseekingis
positivelyassociatedwithadolescents’eHealthLiteracyandengagementinonlinesearchesforhealth
information[26].ThesefindingssupporttheconclusionthateHealthLiteracyskillsarestrongly
Figure 1. The complexity of eHealth Literacy (eHL) and Media Health Literacy (MHL) in context.
3.1. Complexity of Systems and Environments
In 2009, Parker [
15
] made an important statement that is occasionally forgotten in a discourse that
focuses its attention predominantly on health literacy as an individual combination of skills: “One must
align skills and abilities with the demands and complexities of the system” (p. 92). She illustrated this
with a simple drawing of two arrows pointing toward each other, one representing “skills/abilities”
and the other labelled “demands/complexity”. Where the two arrows meet, she wrote, is where health
literacy is expressed.
Digital media sources of health information have particular potential to reduce system complexity.
Usability and accessibility are topics that receive specific attention from software developers and web
designers. Several findings suggest that focusing on user experience and designing with the aim of
reducing complexity are beneficial for digital health literacy. For example, disadvantage in written and
spoken language skills can be barriers to accessing online health information [
16
]. Information should,
therefore, be made increasingly available in more interactive formats that depend less on formal literacy
and knowledge of the local language [
17
]. Meppelink and colleagues [
18
] provide empirical support
for this claim. In an experimental study they show that recall and attitude change were significantly
higher in low health literate participants when information was presented verbally and enriched with
animations supporting the content compared to standard written text and illustrations. Content must
be adapted to be relevant to the specific population, for example taking into consideration cultural
eating habits when designing a smartphone app to support weight loss [
19
]. Thus, (digital) media
solutions for health actually do have the potential to contribute to making health information more
accessible and understandable for broad sections of the population, eventually fostering positive
effects on health [20].
System complexity is also reduced when people become more experienced with health literacy
tasks and with the technology that can be used to apply health literacy skills. Accordingly,
eHealth Literacy scores are positively associated with frequency of use of the Internet [
21
,
22
] and
with the number of Web searches for health information [
23
]. High eHealth Literacy levels are
associated with the use of social media for the purpose of seeking health information, and with
frequent use of electronic devices in general [
24
]. It can also be shown that eHealth Literacy scores
are higher for students who had been actively involved in searching for health information online
Int. J. Environ. Res. Public Health 2018,15, 1643 5 of 12
than for non-experienced peers [
25
]. Similarly, data suggest that parental online health information
seeking is positively associated with adolescents’ eHealth Literacy and engagement in online searches
for health information [
26
]. These findings support the conclusion that eHealth Literacy skills are
strongly shaped by exposure to technology, the Internet, and online health information sources in
particular. It may therefore be deduced that the higher the usability of the underlying technology,
i.e., reducing system complexity, the greater the exposure, and the greater the engagement of digital
resources by the population.
3.2. The Role of Socio-Demographics
A number of socio-demographic variables are linked to Media Health Literacy, and specifically to
online health information seeking and eHealth Literacy, measured at the individual level. Media Health
Literacy, to date, measured mainly among adolescents, is highly associated with socioeconomic status
(SES) and mothers’ level of education [
3
]. Regarding digital sources of health information, people
from different age groups, socioeconomic backgrounds, and from diverse ethnic groups refer to
online sources when looking for information on health topics [
27
]. As early as 2006, 80 percent
of adult American Internet users confirmed to have browsed the Web for health information [
28
].
Similar numbers of online health information seeking have more recently been shown in Eurobarometer
data from 28 member states of the European Union [
29
]. American college students even seem to
consider the Internet as their single most important source of health information [
30
]. Still, studies also
identified some socioeconomic differences in online health information seeking. Low rates of online
health information seeking were reported among older adults, among people with low educational
attainment, and in men compared to women [
31
34
]. Regarding the use of eHealth tools among
ethnic minorities, the data is inconclusive. According to recent studies, as opposed to previous ones,
no significant differences between groups have been evidenced [
35
]. Yet, the cultural context of eHealth
literacy including mobile health (mHealth) has been recognized [36].
According to Neter and Brainin [
37
], people with high eHealth Literacy are younger and better
educated than people with low eHealth Literacy scores. These associations of eHealth Literacy with
age and education are confirmed by data from various samples, e.g., financially disadvantaged US
families [
38
] and immigrant communities in Canada [
39
]. These socio-demographic differences are
consistent for mHealth use, health literacy, eHealth Literacy, and Media Health Literacy, particularly
with regard to education and age, and secondarily with regard to gender and ethnic background.
Cultural background has also been considered to significantly influence eHealth Literacy and Media
Health Literacy such that researchers in South Korea [
40
] and Italy [
41
], conducted several validation
studies for the eHEALS model to assure its relevancy to local culture.
3.3. Social Networks
Socio-demographics and experience with media and technology are factors on the individual
level that influence eHealth Literacy and Media Health Literacy skill sets. Certainly, individual
level variables contribute to shaping health literacy levels. However, caution is warranted as to
“the individualistic premise of current literature (on health literacy) in which individuals are treated
as isolated and passive actors” [
42
] (p. 1309). Several findings suggest that eHealth Literacy levels
are shaped and can possibly be improved through guidance in online health information seeking
activities by more experienced users as well as in structured learning environments. For example,
Chang and colleagues [
26
] showed that active parental mediation of their adolescent children’s Internet
use predicted adolescents’ eHealth Literacy. Participants in focus groups conducted among Spanish
primary school students reported use of the Internet as a tool for learning about health topics and habits,
but preferred their searches to be guided and supervised by their parents to promote their efficacy and
confidence in dealing with online (health) content [
43
]. Similarly, in a sample of elderly living with
chronic disease, participants reported the Internet as a useful information source on their condition.
Still, they often relied on the help of relatives and friends when assessing the information [
44
]. A similar
Int. J. Environ. Res. Public Health 2018,15, 1643 6 of 12
strategy has been observed for Hispanic breast cancer survivors in the United States; managing online
health information in their case was a responsibility they consistently shared with their offline social
networks [
45
]. Results from a nationally representative Israeli survey indicate that participants with
low eHealth Literacy for whom finding someone (offline) to help them perform and analyze their
online health information searches was easy, partly compensated for their lack of proficiency with
digital health literacy through social support [
46
]. Caregivers’ or significant others’ guidance and
support are thus vital in the development of abilities relevant to eHealth Literacy in context.
4. Improving Media Health Literacy and eHealth Literacy
Studies focused on the implementation and effectiveness of Media Health Literacy and eHealth
literacy training programs, are relatively few. Regarding Media Health Literacy, as it inherently
includes exercising critical thinking, and acknowledging that new channels of intervention need to
be developed and applied for health promotion among adolescents, Wharf Higgins and Begoray [
47
]
developed the concept of Critical Media Health Literacy. The concept focuses on attributes that include
skill sets, empowerment, and competency of engaged citizenship. While the conceptual basis has been
established, related intervention has been tested primarily on children and adolescents, focusing on
media literacy related to health topics, e.g., alcohol [
48
]. Among adults, health literacy has been
incorporated into media driven interventions, to learn of the differential effects of low and high
health literacy. In order to influence the consumption of sugar sweetened beverages among the rural
community in the US, a media driven intervention was developed and implemented while measuring
the effects among various levels of health literacy. The program was found to be just as effective
among participants with low health literacy as compared to high health literacy [
49
]. Media health
literacy has also been given serious attention not only by public health entities, but also by media
stakeholders, just as journalists, exemplified by the seriousness with which news media serves the
public’s health literacy needs while influencing public health policy as well [
50
]. Still, interventions
aimed at improving Media Health Literacy across the lifespan, based on, and including critical health
literacy, have yet to take a prominent place in intervention research.
Regarding eHealth literacy, a systematic review on eHealth Literacy among college students
concluded that even this young, well-educated population has major shortcomings, the findings of
which show that interventions to improve eHealth Literacy would not only benefit traditional at-risk
groups [
51
]. While literature on interventions aiming to improve digital health literacy is scarce to date,
some promising findings have been published. eHealth Literacy can be developed and improved by
offering structured learning opportunities. For example, an intervention to improve eHealth Literacy
among adolescents composed of three online training lessons yielded significant, though marginal
improvements of digital health literacy levels among the participants. High identification with,
and involvement in the intervention, i.e., feeling that improving eHealth Literacy was important and
relevant, was one of the strongest predictors of changes in skill level, stressing the need to make eHealth
Literacy personally relevant to potential intervention participants [
52
]. An intervention consisting
of four two-hour sessions aimed at helping older adults perform online health information searches
yielded significant improvements of eHealth Literacy from pre- to post-intervention. Participants also
reported changes in health-related attitudes and behaviors following the intervention [
53
55
]. It should,
however, be noted that a systematic review on eHealth Literacy intervention studies for older
adults [
56
] concluded that many studies apply weak study designs and that some interventions
lack a thorough theoretical base. Therefore, further research in the area is greatly needed. Likewise,
it should be noted that the reported interventions are primarily skill-based interventions aimed at
increasing individual competence. This type of intervention has its justification, however, coupling
with interventions focusing more on empowerment and change in the environment where health
literacy is applied, is of great importance in an increasingly digitized and media-saturated environment.
Finally, as mentioned, reducing system complexity and improving the accessibility of new health
Int. J. Environ. Res. Public Health 2018,15, 1643 7 of 12
technologies and media content ultimately benefit the general population, not only those with low
levels of Media or eHealth Literacy.
5. Ethical Considerations in Media and eHealth Literacy Practice, Research, and Policy
The need for ethical considerations is just as pertinent and imminent in the areas of media and
digital health literacy as in all areas of public health research. Ethical concerns need to be considered
comprehensively—in practice, research, and policy.
5.1. Media and eHealth Literacy Ethics in Research
Regarding the ethical considerations of research on eHealth and digital/Media Health Literacy,
two main aspects need to be considered for ethical scrutiny—namely sampling framework and
generalizability of results. Increasingly, public health research relies on both samples that are drawn
from big data, and self-reporting through digital systems. In normal research protocol, the use of
personal data would require the consent of the participants. The use of big data systems for sampling
should comply with the same standards even though the data is usually not identified [
57
]. Secondly,
using digital technology (e.g., Smartwatches, fitness trackers) for data collection can seriously limit the
extent to which data is collected from digitally excluded populations, often under-representing those
whom have already been mentioned to tend to have low eHealth Literacy and Media Health Literacy.
Thus, the results of such research cannot claim to be valid for all populations, nor is the principle of
equity in research upheld.
5.2. Media and eHealth Literacy Ethics in Practice and Policy
As mentioned above, interventions with regard to MHL and eHealth literacy have two focal
aspects: improving these areas of health literacy and/or adjusting interventions so that they
are appropriate for the diversity of Media Health Literacy and eHealth Literacy skills. As such,
ethical practice needs to be exercised as in any intervention, and applied to Media and eHealth
Literacy practice. Intervention in the digital world requires that special attention be given to equity,
allowing access according to need, guaranteeing cultural appropriateness, overcoming the digital
divide, and taking into consideration various stages of digital development. Whether the intervention
is through the digital media or in non-digital media, the characters, storyline, visuals, and content
must be population appropriate. Finally, as the media and digital worlds attract commercial investors,
public health practitioners must exercise scrupulous ethical standards in order to guarantee that no
commercial vested interest is influencing any aspect of the intervention.
In light of all of the above, and in the interests of equity, it is essential that policies for health
promotion, for improving health literacy of the individual, and for promoting organizational health
literacy for the population, take into account the diversity of Media and eHealth Literacy skill levels.
6. Discussion
Media Health Literacy and eHealth Literacy are two concepts closely linked to health literacy
which is defined as skills and competencies that enable people to obtain and interpret health
information and empower them to maintain and improve their health and the health of the people
around them. In Media and eHealth Literacy, the sources of the said health information and tools are
specified to be the media, or in the case of eHealth Literacy more specifically digital media. Identifying,
extracting, and understanding health information from media sources are by no means straightforward
tasks, even less when the information is to be applied, leading to health decisions and adoption or
change of health behavior. The complexity of processes underlying health literacy tasks explains why
contextual and environmental variables play such an important role in shaping both the development
and the actual use of the necessary skill sets.
Several research findings have indicated that health literacy levels vary by educational background
e.g., [
58
,
59
], and similar findings have been summarized for eHealth Literacy and Media Health
Int. J. Environ. Res. Public Health 2018,15, 1643 8 of 12
Literacy e.g., [
3
], in earlier sections of this article. This may be the result of education acting as an SES
proxy [
35
], as well as skill sets developed through educational settings in the lifespan. The latter is a
standpoint supported by scholars who closely link the development of health literacy to school health
education [
6
,
60
]. Still, caution needs to be exercised neither to interpret these findings as limitations of
populations with low educational backgrounds, nor to conclude that formal education is the only key
to improving general health literacy, Media Health Literacy and eHealth Literacy.
Beyond education, studies on general eHealth Literacy have repeatedly shown that the more
often an individual engages in the search and interpretation of health information, the more confident
they feel doing so. This has yet to be specifically measured for Media Health Literacy. A more
overarching conclusion would thus be that self-efficacy [
61
], a strong predictor of health behavior
adoption, is relevant for the eHL and MHL skills sets as well, supported by experience in the lifespan
(“practice makes perfect”). It thus may be of secondary importance whether this practice is acquired in
structured learning environments provided by formal education or elsewhere. As a third conclusion
from findings summarized previously, it can be understood that social support is paramount for many,
in executing tasks related to health information from media sources. Over a decade ago, Lee, Arozullah,
and Cho [
42
] proposed a research agenda that would examine the associations of health literacy, social
support, and health outcomes. Several studies have researched this assumption, with interesting
results. For example, de Wit and colleagues [
62
] conducted a meta-analysis showing that social support
and co-learning in communities were essential for critical health literacy based on qualitative evidence.
Furthermore, not only the social relevance of the practice of health literacy related tasks is of great
importance, but also system complexity. Digital and non-digital media—and any other—environments
where people encounter health-related information, vary greatly as to how difficult they are to interpret
and navigate. Options exist to reduce complexity of content and presentation mode, as some examples
introduced above can corroborate. It is the joint responsibility of public health researchers and
practitioners, policy makers, and developers to apply what is known and to monitor whether necessary
changes in system complexity are applied, leading to ease of access and usability for the actual
end users. Thus, not only technical accessibility but also the content and modes of presentation
of health information in the media are crucial. Specialists in health promotion, health technology,
and health communication need to work together to create the tools that will empower patients to take
responsibility for their health [63].
While an abundance of studies has been published in recent years on eHealth Literacy and
Media Health Literacy, several limitations are noted, namely the lack of real-time surveys of usage,
the response rates not reflecting the majority of users (30–35% response rates) and lack of research
studying causal pathways (currently most studies are cross-sectional). In addition, comparative
studies between Media and eHealth Literacy may be limited, as general Media Health Literacy
includes media that are often not interactive, such as television, while specifically digital media is
predominantly interactive.
Lastly, the media are unfortunately subjugated to vast commercial interests that in many cases
conflict with the best health interest of consumers. As mentioned above, this leads to very pertinent
ethical challenges in the realm of Media and eHealth Literacy research, further stressing the need for
inter-sectorial cooperation and involvement of political stakeholders in the discourse on health literacy
in media environments.
7. Conclusions
The influence of the social environment on public health is significant, as shown in a wealth of
studies. As society and the social environment on the global level increasingly move towards use of
digital and media tools for delivering health messages, offering health information, navigating health
services, while also increasing the use of the Internet for commercial advertising, then eHealth literacy
and Media Health Literacy skills will likewise play an increasingly essential role. eHealth Literacy
has taken Media Health Literacy to a different level of meaning, as it enables and invites the public to
Int. J. Environ. Res. Public Health 2018,15, 1643 9 of 12
actively interact, respond, and participate in creating, criticizing, and sharing health messages and
information. Future research needs to be expanded to understand the symbiotic relationship between
Media Health Literacy, eHealth Literacy, and the social and cultural environment. On the one hand,
a clearer understanding is necessary to learn of how Media and eHealth Literacy can influence the
social environment that promotes health, while also taking into consideration the influence of the
social and cultural environment on all aspects of the involved skill sets. The pervasive and increasing
access to mobile tools globally will ultimately transform what was once considered the “digital divide”
into numerous degrees of “digital development”. Continued concern must be exercised to enable and
ensure access to media and digital tools for all, such that new technologies can fulfil their primary
purpose: to promote health.
Author Contributions:
Investigation, D.L-Z. and I.B.; Methodology, D.L-Z. and I.B.; Writing—original draft,
D.L-Z. and I.B.; Writing—review and editing, D.L-Z. and I.B.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest.
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... eHealth literacy expands upon the traditional concept of HL and is associated with similar variables, such as age, education, income, culture, and experience using digital media [39]. Several studies and reviews have found that there is great potential for eHealth and eHealth tools as a manner of patient care and communication [38,[40][41][42]. However, several challenges hinder its efficiency, including the type of technology used, the social environment, its evolving definition and measurements, and a lack of theoretical grounding in developing interventions [40]. ...
... Several studies and reviews have found that there is great potential for eHealth and eHealth tools as a manner of patient care and communication [38,[40][41][42]. However, several challenges hinder its efficiency, including the type of technology used, the social environment, its evolving definition and measurements, and a lack of theoretical grounding in developing interventions [40]. In addition, the concept of eHealth literacy is significantly associated with an individual's level of overall HL, with higher overall HL positively correlated with greater eHealth literacy [38]. ...
... Although significant correlations have been found between higher levels of HL and increased HISB, studies suggest that the link between HISB and HL is moderated by other factors, such as social networks, socioeconomic factors, and motivation to seek information [51]. Knowledge transfer within families and communities, social capital, and social engagement in the community contribute to an individual's level of both HL and HISB [40]. Age and sex are well-known factors that affect HL and HISB. ...
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Background: The transmission of health information from in-person communication to web-based sources has changed over time. Patients can find, understand, and use their health information without meeting a health care provider and are able to participate more in their health care management. In recent years, the internet has emerged as the primary source of health information, although clinical providers remain the most credible source. The ease of access, anonymity, and busy schedules may be motivating factors to seek health information on the web. Social media has surfaced as a popular source of health information, as it can provide news in real time. The increase in the breadth and depth of health information available on the web has also led to a plethora of misinformation, and individuals are often unable to discern facts from fiction. Competencies in health literacy (HL) can help individuals better understand health information and enhance patient decision-making, as adequate HL is a precursor to positive health information-seeking behaviors (HISBs). Several factors such as age, sex, and socioeconomic status are known to moderate the association between HL and HISBs. Objective: In this study, we aimed to examine the relationship between HL and HISBs in individuals living in a southern state in the United States by considering different demographic factors. Methods: Participants aged ≥18 years were recruited using Qualtrics Research Services and stratified to match the statewide demographic characteristics of race and age. Demographics and source and frequency of health information were collected. The Health Literacy Questionnaire was used to collect self-reported HL experiences. SPSS (version 27; IBM Corp) was used for the analysis. Results: A total of 520 participants met the criteria and completed the survey (mean age 36.3, SD 12.79 years). The internet was cited as the most used source of health information (mean 2.41, SD 0.93). Females are more likely to seek health information from physicians than males (r=0.121; P=.006). Older individuals are less likely to seek health information from the internet (r=-0.108; P=.02), social media (r=-0.225; P<.001), and friends (r=-0.090; P=.045) than younger individuals. Cluster analysis demonstrated that individuals with higher levels of HISBs were more likely to seek information from multiple sources than those with lower levels of HISBs (mean range 3.05-4.09, SD range 0.57-0.66; P<.001). Conclusions: Age and sex are significantly associated with HISB. Older adults may benefit from web-based resources to monitor their health conditions. Higher levels of HL are significantly associated with greater HISB. Targeted strategies to improve HISB among individuals with lower levels of HL may improve their access, understanding, and use of health information.
... Women are more likely to adopt health protective behavior as compared to males (36, 37) and may be more likely to find, comprehend and evaluate health-related information from electronic sources and apply that information to solve or detect a health problem but this can be different in the cultural and social contexts of regions and countries. According to the results of a study, contextual, environmental, and sociodemographic factors affect e-health literacy (38). The results of the previous study demonstrated low levels of education and income status were barriers to achieving e-health literacy (39)(40)(41). ...
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Background Several vaccines have recently been generated and are being utilized to prevent COVID-19 mortality. Although the disease is causing many fatalities worldwide, preventative practices should be prioritized, even if vaccines are available. Therefore, this study aimed to identify the role of e-health literacy and some cognitive factors in adopting protective behaviors against COVID-19 in Khalkhal residents. Methods In the present cross-sectional study we recruited 380 people aged 18–65 according to cluster sampling from September 2021 to December 2021 in Khalkhal County, Iran. Reliable and validated tools were applied to data collection, including the eHealth Literacy Scale (eHEALS) in Persian and the Cognitive factors assessment questionnaire based on the Health Belief Model (HBM). Data were analyzed using Chi-square, one-way ANOVA, independent samples t -test, and bivariate correlation. The predictors were also determined using hierarchical linear regression analysis. Results The average age of the participants was 35.26 ± 11.51 years. The regression analysis implied that gender ( p- value = 0.032), education level ( p- value = 0.001), occupational status ( p- value = 0.002), income ( p- value = 0.001), and marriage ( p- value = 0.001) had statistically significant associations with e-HL. Additionally, education level ( p- value = 0.001), occupational status ( p- value = 0.001), income ( p- value = 0.001), and marriage ( p- value = 0.002) revealed statistically significant associations with COVID-19 preventive behaviors. Approximately 16.5% of the variation in the COVID-19 protective behaviors is explained by the cognitive factors and the demographic variables. Overall, demographic, cognitive, and e-HL variables were able to explain roughly 35.5% of the variation in COVID-19 protective behaviors. Furthermore, self-efficacy was the strongest predictor of protective behaviors (β = 0.214). Conclusions HBM constructs successfully predicted the role of e-health literacy and some cognitive factors in adopting COVID-19 protective behaviors. People with high socioeconomic levels were better at e-health literacy and COVID-19 protective behaviors during the pandemic. Moreover, applying approaches to adopting COVID-19 protective behaviors is essential, especially in low socioeconomic status (SES) groups.
... 12 Language barriers additively contribute to poor digital health literacy. 12,13 In addition, digital user interfaces are not always designed to account for cultural and ethnic factors contributing to further inequality, poor patient experience, and patients' reluctance to use technology in the future. 14 A nationwide study of 3473 adults surveyed showed that digital health literacy is a predictor of digital health technology adoption, 15 underscoring the importance of assessing digital literacy of patients, especially for those residing in underserved areas. ...
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The COVID-19 pandemic led to digital health service expansion that widened the existing digital divide. Residing in areas of limited broadband internet connectivity, lacking access to smart devices, and/or having low digital health literacy (ease, comfort, and skills to use technology) pose barriers to receiving health care remotely. This unequal access to healthcare is further exacerbated for older adults, those with lower income and less education, racial and ethnic minorities, and those who do not speak English. Because an individual’s digital access (broadband internet connectivity and access to smart devices) and literacy can affect healthcare quality and outcomes, it is proposed that those 2 factors should be categorized as a key domain of social determinants of health. In this commentary, the authors highlight digital access and literacy barriers in the context of the United States health care service delivery. They underscore the importance of screening every patient during regular clinical visits for digital access and literacy as social determinants of health, using the electronic health record. The authors believe this will enhance digital healthcare by creating a more person-centered, inclusive method for clinicians and health care systems to digitally connect to patients of all backgrounds. (PDF) A Need for Digitally Inclusive Health Care Service in the United States: Recommendations for Clinicians and Health Care Systems. Available from: https://www.researchgate.net/publication/362149650_A_Need_for_Digitally_Inclusive_Health_Care_Service_in_the_United_States_Recommendations_for_Clinicians_and_Health_Care_Systems [accessed Jul 24 2022].
... 9 Five social media platforms were built for Next Gen Hawaiʻi to share public health knowledge and resources with those who spoke NHPI and Filipino languages, hoping to leverage social media as a public health tool 10-12 with a goal of reaching, engaging, and empower-ing youth to stay informed. [13][14][15][16][17][18][19] As NHPI and Filipino communities often include collectivist perspectives, inter-generational households, and strong family and communal relationships, 20 reaching NHPI and Filipino youth was considered a meaningful pathway for sharing critical public health information into families, social networks, and communities and, thus, building individual, community, and digital health literacy. 21,22 This article provides an overview of Next Gen Hawai'i's activities and achievements as well as lessons learned for other youth-focused public health social media campaigns. ...
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The Next Gen Hawai'i social media project was initiated in the fall of 2020 to address ongoing public health concerns and the need for accessible and reliable information across Hawai'i's diverse communities by strategically amplifying the voices of Hawai'i's youth in their Native languages. The collaborative effort arose from conversations within the Hawai'i's Native Hawaiian & Pacific Islander COVID-19 Response, Recovery, and Resilience Team, composed of diverse public and private organizations involved in statewide COVID-19 response efforts for Native Hawaiian and Pacific Islander communities. Next Gen Hawai'i's focus was on Native Hawaiian, Pacific Islander, Filipino, and other populations disproportionately suffering from COVID-19. Five social media platforms were developed to spread messaging to youth and young adults about COVID-19. Public Health Ambassadors (from high school to young adults) were recruited and engaged to create culturally and linguistically rooted messaging to promote public health and prevention-based social norms. This strength-based approach recognized youth as important community leaders and ambassadors for change and empowered them to create content for dissemination on platforms with national and global reach. Messaging was designed to build individual, community, and digital health literacy while integrating core cultural values and strengths of Native Hawaiian, Pacific Islander, and Filipino communities. Over 250 messages have been delivered across Next Gen Hawai'i social media channels on topics including vaccine information, mask-wearing, staying together over distances, mental health, and in-languages resources in Chuukese, Chamorro, Marshallese, Samoan, Hawaiian, Ilocano, Tagalog, and other Pacific-basin languages. Reach has included more than 75 000 views from various social media channels, media features, successful webinars, and relevant conference presentations. This Public Health Insights article provides an overview of Next Gen Hawai'i's activities and achievements as well as lessons learned for other youth-focused public health social media campaigns and organizations.
... Mass media has been cited as a highly efficient tool in enhancing health literacy. The dissemination of health information via radio and television has been shown to be an empowering tool for improving individual and public health [32]. Regarding creating awareness of BC and BSE, the mass media has played a great role. ...
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... 17,35,41,[46][47][48][50][51][52][53][54][55][56][57][58][59][60][61][62] Further, disparities in digital health literacy, including users' ability to understand and act on available digital information were highlighted as another major equity challenge. 35,38,48,49,53,55,56,58,[60][61][62][63][64][65][66][67][68][69][70] Further, digital technologies in public health may disproportionately benefit already privileged groups in society, and exclude marginalized populations. 26,33,46,50,71,72 This may be further exacerbated through the economic incentive to target high-income users with commercial digital health interventions. ...
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Background “Digital public health” has emerged from an interest in integrating digital technologies into public health. However, significant challenges which limit the scale and extent of this digital integration in various public health domains have been described. We summarized the literature about these challenges and identified strategies to overcome them. Methods We adopted Arksey and O’Malley's framework (2005) integrating adaptations by Levac et al. (2010). OVID Medline, Embase, Google Scholar, and 14 government and intergovernmental agency websites were searched using terms related to “digital” and “public health.” We included conceptual and explicit descriptions of digital technologies in public health published in English between 2000 and June 2020. We excluded primary research articles about digital health interventions. Data were extracted using a codebook created using the European Public Health Association's conceptual framework for digital public health. Results and analysis Overall, 163 publications were included from 6953 retrieved articles with the majority (64%, n = 105) published between 2015 and June 2020. Nontechnical challenges to digital integration in public health concerned ethics, policy and governance, health equity, resource gaps, and quality of evidence. Technical challenges included fragmented and unsustainable systems, lack of clear standards, unreliability of available data, infrastructure gaps, and workforce capacity gaps. Identified strategies included securing political commitment, intersectoral collaboration, economic investments, standardized ethical, legal, and regulatory frameworks, adaptive research and evaluation, health workforce capacity building, and transparent communication and public engagement. Conclusion Developing and implementing digital public health interventions requires efforts that leverage identified strategies to overcome diverse challenges encountered in integrating digital technologies in public health.
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With the rapidly changing climate, assessing the global trends of cardiovascular diseases (CVDs) attributed to high and low temperatures in different climate zones and under varying socio-demographic levels is crucial for regulations, preparation, intervention, and clinical practice for CVD. Our study included 204 countries with global CVD data ranging from 1990 to 2019. We obtained the age-standardized mortality rate (ASMR); disability-adjusted life rate of CVD attributed to high, low, and non-optimal temperatures; and socio-demographic index (SDI) data from the Global Health Data Exchange. We also downloaded the temperature data from the Climatic Research Unit. These 204 countries were divided into five climate zones and five SDI levels according to the annual average temperature data and SDI in 2019. The temporal trends of CVD burden attributed to high, low, and non-optimal temperatures were estimated by using the cubic regression spline and the generalized additive mixed model (GAMM). The total burden of temperature-related CVD has been declining in the last 30 years. However, the burden of CVD attributed to high temperature showed an increasing trend. Among different climate regions, the ASMRs of CVD attributed to high temperature were the highest in the tropical regions, followed by subtropical regions, and the lowest in the boreal regions. In the past 30 years, the burden of CVD attributed to high temperatures has shown a significant increasing trend, while declining trends are observed for non-optimal and low temperatures. The CVD burden attributed to high temperatures is particularly pronounced in warmer and low-SDI regions with an increasing trend of CVD burden due to high temperature.
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Abstract The aim of this review is to discuss the incidence, issues, and barriers to care for women with breast cancer in Afghanistan that can increase mortality in women. Worldwide many people lose their life due to cancer every year. Mortality and morbidity rates due to cancer are estimated to increase in males and females in the future. The predictions are that nearly two-thirds of mortality for patients due to cancer might happen in developing countries due to issues access. Along with mortality and morbidity, cancer can negatively strain the economy and workforce of in underserved or economically challenged communities.Afghanistan is one of the low and middle-income countries that suffers from increased mortality rates due to cancer and its negative consequences. Afghanistan does not have a cancer patient registry and health coverage all over the country is limited. The limited data on cancer and evaluation of the burden of disease in developing countries is challenging. This article reviews data collected from Jamhoriat hospital in Kabul city Afghanistan. It is essential to perform studies on the incidences of cancers in different provinces of developing and economically challenged countries to appropriately formulate strategies and guidelines for the management of risk factors to decrease the burden of cancer on health systems and communities. Keywords: Health literacy, breast cancer, access, developing countries, breast cancer treatment.
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Background: Caregivers of children and youth with complex care needs (CCN) often require considerable support to ensure the well-being of their families. Social media presents an opportunity to better support caregivers through computer-mediated communication for social support. Peer-to-peer (P2P) support groups are one way that caregivers are accessing needed support; however, the experiences of caregivers who use these groups and the perceived impact that participation has on caregivers of children and youth with CCN is not known. Objective: This study aimed to: (1) explore the experiences of caregivers of children and youth with CCN who use a Facebook-based P2P support group to communicate; (2) understand their motivations to use the group; and (3) investigate its perceived impact on knowledge of programs and services and sense of community belonging in caregivers. Methods: A qualitative descriptive design was used to explore the experiences and perceived impact of a Facebook-based P2P support group for caregivers of children and youth with CCN in New Brunswick, Canada. The group was launched online in October 2020, during the COVID-19 pandemic, and resulted in 108 caregivers joining the group. An online survey was distributed, and semi-structured interviews were conducted in February 2021 with a sub-sample of members. Thematic analysis was used to identify, and report patterns related to caregiver experiences and perceived impacts of participation. Results: A sub-sample of members in the Facebook group completed the online survey (n=39) and interviews (n=14). Five themes emerged from interviews: (1) Safe Space; (2) Informational Support and Direction; (3) Virtually Connect with Peers; (4) Impact on Knowledge of Programs and Services; and (5) Degree of Community Belonging. Participants reported joining the group to obtain geographic-specific information support and to connect with peers. Many participants reported an improvement in knowledge of programs and services and felt connected to the community; however, the short observation period and diversity among the caregiver population were cited as barriers to community belonging. Conclusions: Social media presents an important opportunity to facilitate the exchange of support between patients and caregivers in an accessible and curated environment. Findings from this study suggest that involvement in online, geographic-specific P2P support groups can influence perceived knowledge of services and resources and sense of community belonging among caregivers of children and youth with CCN. This work further provides insight into the experiences and motivations of caregivers of children and youth with CCN who participate in a private social media environment.
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Background US health care providers are increasingly demanding patient engagement with digital health technologies to enroll in care, access personal health information, communicate with providers, and monitor their own health. Such engagement may be difficult for disadvantaged populations who may have limited health literacy, time constraints, or competing priorities. Objective We aimed to understand the extent of adoption and use of digital health tools and to identify key perceived psychological motivators of technology use among disadvantaged first-time pregnant women and mothers of young children. Methods We recruited women from health organizations serving low-income communities in the Midwest and on the East and West coasts. A total of 92 women participated in 14 focus groups. During each session, we administered worksheets that measured 3 utilization outcomes: the number of recent Web-based health-seeking activities, current use of digital health-management practices (eg, accessing personal health information, communicating with providers, and scheduling appointments), and potential adoption of digital health-management tools among low users or nonusers. Responses to the worksheets and to a pre-focus group survey on demographics, technology access, and motivators of use were examined to create user profiles. Separate regression models identified the motivators (eHealth literacy, internal health orientation, and trust in digital information) associated with these outcomes. Qualitative data were incorporated to illustrate the worksheet responses. Results Whereas 97% of the participants reported that they had searched for health information on the Internet in the past year, 42% did not engage in digital health-management practices. Among the low users and nonusers, 49% expressed interest in future adoption of digital health tools. Web-based health information-seeking activities were associated with digital health-management practices (P<.001). When controlling for covariates, eHealth literacy was positively correlated with the number of Web-based health-seeking activities (beta=.03, 95% CI 0.00-0.07). However, an internal health orientation was a much stronger correlate of digital health-management practices (beta=.13, 95% CI 0.02-0.24), whereas trust in digital information increased the odds of potential adoption (vs no adoption) in adjusted models (OR 5.21, 95% CI 0.84-32.53). Demographic characteristics were not important drivers of digital health use and few differences distinguished use among mothers and pregnant women. Conclusions Seeking health information on the Internet may be an important gateway toward engaging in digital health-management practices. Notably, different consumer motivators influence digital health tool use. The relative contributions of each must be explored to design tools and interventions that enhance competencies for the management of self and child health among disadvantaged mothers and pregnant women. Unless we address disparities in digital health tool use, benefits from their use will accrue predominantly to individuals with the resources and skills to use technology effectively.
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International and cultural perspectives of health literacy help deepen the understanding of the global context within which health literacy plays an important role. Throughout this article, we explore the significance of health literacy initiatives, interventions, practices, and research for addressing health challenges on a variety of levels in the international and global context. More specifically, the notion of health literacy as a dynamic construct is introduced, after which we examine health literacy throughout the life course, emphasizing the impact of health literacy among children and the elderly in their families and in the community. Cultural norms and family interpersonal relations, and values influence health literacy and need to be considered when closing the health literacy disparities. Global trends of migration and immigration bring to the forefront the need for unravelling the complexity of health systems, for which health literacy plays a central role; health literacy initiatives address cultural differences between providers and patients to help narrow the communication gap. The importance of cultural competency among health care providers exemplifies how capacity building in health literacy is critical for maximizing the benefits to the public of the health care system. Health literacy provides a conceptual foundation for community participatory research, involving members of the public to take part in the planning, execution and evaluation of health education interventions. Selected case studies and picture boxes from around the globe, exemplify aforementioned topics of interest. Practical recommendations for policy makers, practitioners and research are offered based on the studies conducted in the international context.
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The second biggest Legionnaires’ disease outbreak worldwide occurred in Portugal in 2014. It was classified by the WHO as a “great public health emergency,” and it was subject to a unique media coverage in Portugal. The media coverage of this outbreak lasted for 2 weeks, which is not very common in similar cases, and it was characterized by the control of information by official sources. These were put together in a joint task force that disseminated all information. Nonetheless, they did not generate a hegemonic discourse which is usually characteristic of power elites. That happened mostly due to the promotion of health and risk literacy. Through infographics, descriptive maps, and questions and answers, the media were able to generate an alternative discourse to that of official sources. That was the basis of a unique media coverage.
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p>Background: Diabetes self-management education (DSME) is generally considered to be a key determinant of the treatment outcomes and related costs of diabetes mellitus. While DSME programmes generally have positive outcomes, their effects may depend on certain factors, such as the type of programmes provided and patients’ level of health literacy (HL). Low HL has been associated with poorer self-management behaviours and poor medication adherence in diabetic patients, but its impact on the effects of DSME has not yet been systematically investigated. This study aimed to investigate the influence of HL on the self-reported effects of DSME programmes while taking the type of programme into consideration. Method: A total of 366 diabetic patients from nine countries completed a questionnaire measuring HL, self-management behaviours, problem perception, coping, perceived general health and well-being, before and after participating in a DSME programme. Results: DSME programmes were found to have positive effects on self-reported self-management behaviours and almost all psychological and health outcomes, regardless of HL level. Patients with high HL scored better on several diabetes outcomes than those with low HL, but all patients described benefiting from DSME. Individual and group-based programmes resulted in more positive effects on several diabetes outcomes than self-help groups, but no interaction with HL was found. Conclusion: Our findings confirm those of previous studies showing that DSME programmes have positive effects and that low HL is associated with lower diabetes outcomes but do not support the assumption that the effects of DSME programmes are influenced by the patient’s HL. However, due to the limitations of this study, further investigation is necessary to support these findings and improve our understanding about the impact of HL on DSME programmes’ effectiveness.</p
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Background Mobile phone use and the adoption of healthy lifestyle software apps (“health apps”) are rapidly proliferating. There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions to change, and actual health behaviors. Objective The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended guidelines for fruit and vegetable intake and physical activity. Methods Data on users of mobile devices and health apps were analyzed from the National Cancer Institute’s 2015 Health Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss. Results From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+ years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a mobile device, especially if that person was a college graduate (OR 3.30). Individuals with apps were significantly more likely to report intentions to improve fruit (63.8% with apps vs 58.5% without apps, P=.01) and vegetable (74.9% vs 64.3%, P<.01) consumption, physical activity (83.0% vs 65.4%, P<.01), and weight loss (83.4% vs 71.8%, P<.01). Individuals with apps were also more likely to meet recommendations for physical activity compared with those without a device or health apps (56.2% with apps vs 47.8% without apps, P<.01). Conclusions The main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income. Although differences persist for gender, age, and educational attainment, many individual sociodemographic factors are becoming less potent in influencing engagement with mobile devices and health app use. App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations.
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Objectives Access to the Internet has grown dramatically over the past two decades. Using data from a population-based survey, we aimed to determine the prevalence and predictors of (i) access to the Internet, and (ii) use of the Internet to search for health information. Methods We analyzed data from the 2011–12 California Health Interview Survey (CHIS) and included all individuals 18 years of age and older. Our outcomes were (i) prior use of the Internet, and (ii) use of the Internet to find health or medical information within the past year. We performed survey-weighted logistic regression models on our outcomes to adjust for potentially confounding demographic and socioeconomic factors. Results Our study included an unweighted and survey-weighted sample of 42,935 and 27,796,484 individuals, respectively. We found that 81.5% of the weighted sample reported having previously used the Internet. Among Internet users, 64.5% stated that they used the Internet within the past year to find health or medical information. Racial/ethnic minorities, older individuals, and those who lived in lower income households and rural areas were less likely to have access to and use the Internet to search for health information. Conversely, English-proficiency and increasing levels of education were positively associated with online health information-seeking. Conclusions We found that most Californians have access to and use the Internet to search for health information, but still noted a persistent digital divide. Interventions to narrow the divide are needed, otherwise this may lead to a continued widening of existing healthcare disparities.