35,66 €
Mehr erfahren.
- Herausgeber: Bentham Science Publishers
- Kategorie: Fachliteratur
- Sprache: Englisch
The internet provides a major source of exchanging health informationthrough online portals and new media. Internet users can access health sitesand online forums to obtain health information. In turn, these informationsources act as a catalyst for wellbeing and improving personal health carebehaviors and routines. Competent health institutions encourage the development of theseindividual behaviors that enable individuals to increase health empowerment and totake responsibility for their own health needs, diagnosis and treatment. Online Health Forums andServices: Benefits, Risks and Perspectives is an investigation of the useof online health forums and services. The author first introduces the reader tothe theories that define online social behaviors in terms of health careservices. The chapters following this introduction attempt to account for the variationsin online health care portal use and to what extent does social networkinginduce variations in health behaviors grounded in theory. A summary of mediaused for affecting health behavior change is also provided along with adiscussion of the socioeconomic attributes of the individuals most likely to beaffected in terms of their health behaviors. The book provides a comprehensive perspective that links the aspects ofthe micro-level use of the Internet for health purposes (accessing healthrelated websites, participation in health forums and networking sites) to themacro level practices of telemedicine. Readers will be able to understand thesocial and health characteristics of the different groups of patients andestimate the extent to which individuals in need of health and medicalinformation are taking advantage of the availability of information andcommunication platforms to improve their health, or if they are being left behind.This is a timely reference for healthcare professionals, researchers andconsultants involved in digital health care initiatives and public health administration who areseeking information about how access to online health information can influencelifestyles in a way that impacts human behavior in a positive, meaningful way.
Das E-Book können Sie in Legimi-Apps oder einer beliebigen App lesen, die das folgende Format unterstützen:
Seitenzahl: 794
Veröffentlichungsjahr: 2022
Ähnliche
BENTHAM SCIENCE PUBLISHERS LTD.
End User License Agreement (for non-institutional, personal use)
This is an agreement between you and Bentham Science Publishers Ltd. Please read this License Agreement carefully before using the ebook/echapter/ejournal (“Work”). Your use of the Work constitutes your agreement to the terms and conditions set forth in this License Agreement. If you do not agree to these terms and conditions then you should not use the Work.
Bentham Science Publishers agrees to grant you a non-exclusive, non-transferable limited license to use the Work subject to and in accordance with the following terms and conditions. This License Agreement is for non-library, personal use only. For a library / institutional / multi user license in respect of the Work, please contact: [email protected].
Usage Rules:
All rights reserved: The Work is the subject of copyright and Bentham Science Publishers either owns the Work (and the copyright in it) or is licensed to distribute the Work. You shall not copy, reproduce, modify, remove, delete, augment, add to, publish, transmit, sell, resell, create derivative works from, or in any way exploit the Work or make the Work available for others to do any of the same, in any form or by any means, in whole or in part, in each case without the prior written permission of Bentham Science Publishers, unless stated otherwise in this License Agreement.You may download a copy of the Work on one occasion to one personal computer (including tablet, laptop, desktop, or other such devices). You may make one back-up copy of the Work to avoid losing it.The unauthorised use or distribution of copyrighted or other proprietary content is illegal and could subject you to liability for substantial money damages. You will be liable for any damage resulting from your misuse of the Work or any violation of this License Agreement, including any infringement by you of copyrights or proprietary rights.Disclaimer:
Bentham Science Publishers does not guarantee that the information in the Work is error-free, or warrant that it will meet your requirements or that access to the Work will be uninterrupted or error-free. The Work is provided "as is" without warranty of any kind, either express or implied or statutory, including, without limitation, implied warranties of merchantability and fitness for a particular purpose. The entire risk as to the results and performance of the Work is assumed by you. No responsibility is assumed by Bentham Science Publishers, its staff, editors and/or authors for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products instruction, advertisements or ideas contained in the Work.
Limitation of Liability:
In no event will Bentham Science Publishers, its staff, editors and/or authors, be liable for any damages, including, without limitation, special, incidental and/or consequential damages and/or damages for lost data and/or profits arising out of (whether directly or indirectly) the use or inability to use the Work. The entire liability of Bentham Science Publishers shall be limited to the amount actually paid by you for the Work.
General:
Any dispute or claim arising out of or in connection with this License Agreement or the Work (including non-contractual disputes or claims) will be governed by and construed in accordance with the laws of Singapore. Each party agrees that the courts of the state of Singapore shall have exclusive jurisdiction to settle any dispute or claim arising out of or in connection with this License Agreement or the Work (including non-contractual disputes or claims).Your rights under this License Agreement will automatically terminate without notice and without the need for a court order if at any point you breach any terms of this License Agreement. In no event will any delay or failure by Bentham Science Publishers in enforcing your compliance with this License Agreement constitute a waiver of any of its rights.You acknowledge that you have read this License Agreement, and agree to be bound by its terms and conditions. To the extent that any other terms and conditions presented on any website of Bentham Science Publishers conflict with, or are inconsistent with, the terms and conditions set out in this License Agreement, you acknowledge that the terms and conditions set out in this License Agreement shall prevail.Bentham Science Publishers Pte. Ltd. 80 Robinson Road #02-00 Singapore 068898 Singapore Email: [email protected]
PREFACE
A turning point to better health care includes the introduction of the Internet as a media source. Online access to health information and communication about health is associated with improved knowledge about health issues. Individuals in the past obtained information mainly through health professionals, their friends and families. They are now turning to virtual sources of information and social media to gather health information. They do so for a variety of reasons, including identifying symptoms of a health ailment and self-diagnosis, collecting knowledge on available treatment strategies and their effectiveness, evaluating the costs involved, and finding coping strategies for better self-management.
Individuals are becoming more aware and interested in adopting health changes in dietary and wellbeing routines. 61% of U.S. adults look online for health information, and the number of people using the Internet has almost tripled between 2011 and 2018, and more than 50% of users today look for online health information (Seth & Grant Harrington, 2018). Another recent survey indicates that 65% of online adults in the United States, or half of all US adults, use social media, with Facebook and Twitter being the most widely used (Madden & Zickuhr, 2017). Each minute, 695 000 Facebook statuses are updated, and 98,000 tweets are sent (Teiman, 2019). The use of online social media and online health forums for information seeking is especially noted when individuals face a serious health issue (Pew Research Center, 2013). “Dr. Google” has indeed become a favorite choice when seeking information from a virtual health center and was soon followed by the increase in the use of networking sites (Rosenberg et al., 2017).
Following the rise of internet use, the phenomenon of digital health, including electronic health and mobile health, has risen as well. Using the web to access information and communication with peers can help individuals fulfill unmet informational needs and prepare them to consider changes in health habits. This is more likely for individuals who perceive the need for changing unhealthy habits to improve their health status when exposed to online information. In that sense, exposure to online health information through browsing and online communication might increase the likelihood of making a change in health habits empowering individuals to take responsibility for their health status (Lustria et al., 2011; Pena-Purcell, 2008; Mano, 2018).
The health empowerment process involves the understanding that some means are better facilitators towards the desired health end. When individuals recognize their right to express aspirations and are able to define them as an outcome, they develop a critical “consciousness” of the existing situation. This consciousness increases their sense of self-efficacy (Bandura, 1997) and contributes to a healthy lifestyle throughout an individual’s life span. The health empowerment process is possible by introducing, adjusting, and developing services that are easily accessed, regardless of lack of technical skills and basic health literacy (Mesch et al., 2012; Mano, 2016; 2019) and is expanding among different social groups (Kummervold et al., 2008; Wessels, 2013) shaped by individuals’ health expectations and health attitudes. While technology plays a central role in health empowerment, knowledge alone cannot guarantee the adoption of healthy behaviors (Iverson et al.,2008; Shim et al., 2006; Eisenberg & Berkowitz, 2009). Neither the access nor the use of the Internet is similar for all individuals in all social groups (Mano, 2017; 2019; Rosenberg et al., 2020). As a result, health institutions and policy-makers encourage the development of services and programs that enable individuals to endorse the health empowerment process and assume responsibility for their own health needs, diagnosis, and treatment.
eHealth and mHealth technologies have enormous potential advancing health information exchange and improving healthcare access and public as well as personalized medicine (Bashshur and Shannon 2009; Wentzer and Bygholm 2013). The World Health Organization (WHO) and the International Telecommunication Union (ITU) defined the term “eHealth” as the field “concerned with improving the flow of information, through electronic means, to support the delivery of health services and the management of health systems” (p.1, World Health Organization, 2012c). A new definition shows that the World Health Organization (WHO; 2016) has defined Electronic Health (eHealth) as: “the cost-effective and secure use of information and communications technologies in support of health and health-related fields, including healthcare services, health surveillance, health literature, health education, knowledge, and research.” WHO defined Mobile Health (mHealth) as: “mobile computing, medical sensor, and communications technologies for health care” (WHO, 2009). mHealth is also defined as the use of portable devices to deliver medical and public health services and is a subset of eHealth (Betjeman et al., 2013; Wittet, 2012). Both phenomena are related to the commitment of individuals and health care providers to enhance healthcare and health management practices and form the basis of the health empowerment phenomenon which became a major theme in health-oriented western societies (Sillence et al., 2007; Andreassen, et al., 2007) often considered as the “holy grail of health promotion” (Rissel, 1994).
Health consumers arriving at the health provider with the information they found on the web, with a preconceived idea about their diagnosis, want to actively participate in therapeutic decisions relying on misleading or misinterpreted health information. Health institutions and health policy-makers prompt individuals to claim more responsibility, and they have eagerly employed technology to provide more effective and efficient services in order to handle health budgets in order to successfully combine between effective and efficient administration of virtual health devices (Aceijas, 2011; Mattke et al., 2012; Balatsoukas et al., 2015). These systems play a critical part in unifying communications, allowing people to access, process, store, and transmit data through fully integrated audiovisual, data communications, and electronic systems (Henriquez-Camacho et al.,2014). This means that the potential of social media to reach a large segment of the younger as well as the adult population searching for online insights to their health concerns. These systems seek to minimize digital divide effects and increase health literacy (Wessels, 2013) by introducing macro level systems based on online Information and communication technology (ICT).
At the same time, the empowered “Information control” process challenges the institutional health care provider into equality-based roles with patients. These challenges first and foremost included the outcomes of the shift in the “Information control” process from the authority of the institutional healthcare provider into the power of the informed individuals facing situations hardships in health. The empowered “Information control” process challenges the institutional health care provider into equality like roles with patients. In this process questions about differences in health attitudes and health behavior rise because knowledge alone cannot guarantee the adoption of healthy behaviors (Iverson et al., 2008; Shim et al., 2006; Eisenberg & Berkowitz, 2009).
Moreover, despite major investment in the development and introduction of advanced digital health services and programs, also seeking to reduce costs, health literacy is still low and access to online health services limited increasing doubts about the level of equality among socio economic groups. Even today the Internet is not accessible or used with similar levels of knowledge and skills in particular among the disadvantaged who need it most (Mattke et al., 2012; Baran & Davis, 2009; Eisenberg & Berkowitz, 2009; Aceijas, 2011; Mano, 2016). Disadvantaged groups in terms of technology skills and/or access to online health information and services may ignore health issues, they do not ask for help and support, and have little motivation to deal with prevention of illness. The phenomenon of first and second-level effects of the digital divide is therefore discussed more often because they can affect health management and perhaps even life expectancy (Renahy et al., 2008; Lorence et al., 2006; Mesch et al. 2012; Rosenberg et al., 2019). They terms describe lower investment in improved health whether or not they access online health services and the existence of mistrust (Gibbons, 2008; Mesch et al.,2012; Rosenberg et al., 2019). As a result, health empowerment and successful self-management practices among those who need it most - the elderly, those located in remote geographic areas, and/or facing chronic illness and disabilities maybe missed (Hadwich et al., 2006; Eisenberg & Berkowitz, 2009; Aceijas, 2011; Mano, 2016). This is why it is important to consider the sources of individual level variations in the health empowerment process including health attitudes, differences between health behaviors, trust and technology skills (Mano, 2019). The gap between the willingness and actual behavior to adopt digital services have profound impact for different sectors and they may affect decision making and allocation of resources to the online tools used by institutional health providers that manifest in the delivery of health services and health programs.
The purpose of this book is to provide the theoretical and empirical background to instigate an interdisciplinary perspective to issues of digital health in the 21st century.
In order to so, we discuss the factors associated with the use of online sources of health. The fundamental assumptions of this book refer to three dimensions of use of online forums for health purpose: first, at the micro level health attitudes and behaviors reflect a wide range of personal differences in terms of socioeconomic characteristics, technology skills, and preferences. Second, we refer to the quality of these sources of information regarding their suitability and accuracy is limited raising concerns about its usefulness to patients (Manchaiah et al., 2020) raising doubts about the effectiveness of the health empowerment process. Third, we will discuss how variations at the individual level affect both the access and extent of use of virtual sources of health information and health services. Finally, we will present the basic problems associated with the use of virtual sources of health information and services at the level of institutional health practices and the association between the micro-level use of the Internet for health purposes and macro level challenges in the promotion of virtual sources of health products and health services.
We seek to present a comprehensive perspective that link between the aspects of the micro-level use of the Internet for health purposes (accessing health related websites, participation in health forums, bulletin boards and health related social networking sites) and the macro level practices of digital health that promote health empowerment. We also seek to identify the social and health characteristics of the different groups of patients and estimate to what extent individuals in need of health and medical information (chronic illness) are taking advantage of the availability of information and communication platforms to improve their health or are being left behind. More specifically, we intend to seek the differences in health outcomes -access to quantity and quality of health information, involvement in decision making empowerment in health behavior and health changes. In doing so, we refer to the following aspects of health:
access to online health informationuse of online health servicessocial media and participation online health forumsmobile health applications and health riskslifestyle health behaviorsself-management of healthdigital divides in healthhealth systemsDue to its interdisciplinary nature, this book is a valuable source of empirical evidence information and theoretical contribution for an academic audience including students and researchers- as well as for public health practice institutions and policy makers. This is also a valuable source of those working in the field of health for the general public who have become very much health-aware these recent years since the internet has allowed for a great number of individuals a quick and immediate access to health information. Finally, the book enables a wide-audience friendly approach to issues of health to be used in connection with teaching, training and consulting activity in digital health. As the importance of particular and general concerns increases among the public, affecting current health policies, so does the importance of understanding the patterns of access and use of online platforms. After all, knowledge and information alone cannot guarantee the adoption of healthy behaviors (Iverson et al., 2008; Eisenberg & Berkowitz, 2009).
CONSENT FOR PUBLICATION
Not applicable
CONFLICT OF INTEREST
The authors declare no conflict of interest, financial or otherwise.
ACKNOWLEDGEMENTS
Declared none.
Theories
Rita ManoThe internet is an integral part of the lives of millions of people around the world. It has brought about changes in individuals’ social, political, and economic practices (Srinivasan & Fish, 2017) and has promoted the introduction of new forms of thinking and new assumptions about the central role of digital communications and information in everyday life. Online health searches, online health services and social media on health websites, blogs, and portals are all easily accessed (Li et al. 2015; Lin et al. 2016). These new trends have intrigued academic researchers, who aspire to find new paradigms to explain these trends. Theories and paradigms play a paramount role in understanding issues related to health. All theories, both old and new, seek to determine how society, individuals, and health behaviors and outcomes are related. Often the choice of a particular theory or paradigm can lead to different and sometimes contradictory hypotheses, resulting in different outcomes for similar data. Here, we provide a glimpse into the prominent theories of health and technology.
SOCIOLOGICAL THEORIES OF HEALTH AND TECHNOLOGY
Studies addressing issues of health in sociology are divided into two principal groups: sociology in medicine and sociology of medicine (Bradby et al., 2017). The first group focuses on the role of sociologists in providing guidelines to various sponsors in health-related fields, among them government agencies, foundations, hospitals, or medical schools. They do this by developing health surveys that address topics related to health care, including access to care, use of services, health status determinants, and more (Higgs & Gilleard, 2015). The second group of studies focuses on testing sociological hypotheses with respect to inequalities and social stratification (Kapilashrami, & Meer, 2015), socialization, social values and norms (Mackenbach, 2016; Karnoven et al., 2018), thus contributing to the analysis of health institutions and health policies. Such analysis is central in examining emergent themes, such as the health of vulnerable groups and international comparisons of social inequalities and quality of care. It is within this set of studies that the role of technology has gained special attention.
Early studies on technological determinism or the impact of technology on society (Postman, 1954) identified technology or technological advances as the central causal element in processes of social change (Croteau & Hoynes, 1967). As a particular technology becomes stable, its design tends to dictate users' behaviors, consequently diminishing human agency. There are two types of technology determinism: hard determinism and soft determinism. According to the hard determinism perspective, technology emerges regardless of social concerns and creates an institutional force of its own that shapes social norms and behaviors. Its autonomous activation serves the interests of technology-oriented agents, and individuals cannot control its outcomes. This perspective, however, overlooks the social and cultural circumstances in which the technology was developed. In contrast, soft determinism in technology is a moderate perspective, which posits that technology agents leave enough space for individuals to decide how technology is used and how its outcomes are defined.
One form of technological determinism is media determinism, a philosophical and sociological standpoint, according to which the media have the power to impact society. The theory of technological determinism in media gained attention when Marshall McLuhan's statement, “the medium is the message” became a central theme in technology studies for describing the essence of civilization. McLuhan (1962) later claimed that not all types of technology matter and that in the area of communication, only certain communication media can significantly affect social behaviors. Extending this line of thought, the media ecology perspective suggests that new forms of media communication technology may become the main framework that will facilitate the implementation of a wide range of social norms and behaviors (Chipidza & Leidner, 2019; Gencarelli, 2006), including health behaviors (Verhoeven & Tonkens, 2013). In fact, the more information and communication technologies (ICT) penetrate the lives of individuals, the more likely they will become more engaged in technology-based information, with the intensity and wide range of ICT crosscutting national and international borders (Verhoeven & Tonkens, 2013; Amnå, 2012). In nations that invest more in technology, the flow of information will be more intense and the odds of higher exposure to health issues will be greater (Chaeyoon & Sander, 2013; Jho & Song, 2015; Carty, 2010). This trend will affect existing institutions that organize support for and further develop new technology (Lenzi et al., 2015).
Indeed, the expanded influence and expansion of ICT in society has led to the normalization hypothesis. This hypothesis posits that when technology affects the processes through which practices become routinely embedded in everyday life and implemented across a range of individuals’ life. These processes will gradually become fully embedded, even in previously conflicted areas of social interactions that are of primary importance (May & Finch, 2009; Kim & Zhang, 2015). In fact, the Media-System Dependency theory, suggests that “the more a person depends on having his or her needs met by media use, the more important will be the role that media play in the person’s life, and therefore the more influence those media will have on the person” (p. 273). As a result, the rise of the information society and the adoption of the Internet will reduce social inequalities because accessing and using the Internet at home and at work can increase access to services, including health services (Mesch et al., 2012).
The social stratification perspective maintains though, that the use of technology will benefit primarily those who already have better resources, therefore amplifying existing social inequalities (Chen et al., 2014; Neves et al., 2018). Internet use among advantaged groups will expand their social capital and consequently enhance their position of domination in society (Rosenberg, 2020). This is why knowing how to create and use technology needs to be connected with social processes at the time when socially bound knowledge is introduced and advanced and should find expression in how other institutions change and adapt to evolving situations (Mano, 2015; Mesch, 2016).
The interactive play between technology and social institutions facilitates making adjustments in use according to how individuals respond to technology innovations. Indeed, as opposed to hard and soft technology determinism approaches, the social determinism approach suggests that social circumstances “select” which technologies are adopted, while technology intertwines with implicated social processes. This interplay has led to the development of a novel approach to the use of online health information and access to online health forums. Known as social construction of technology (also referred to as SCOT), this approach contends that no technology can determine human action, but rather that human action shapes how technology is used. This is because technology is “embedded” in different social contexts, and different groups will use technology in various ways and to different extents (Rosenblum et al., 2017). As a result, the degree that technology is adopted necessitates that individuals are in favor of its use.
MEDIA THEORIES OF TECHNOLOGY ADOPTION
The Technology Acceptance Model (TAM) (Davis, 1989) is a general model that considers how variations in accepting computerized technology reflect a set of facilitating conditions, including expected effort, performance and social influence (Al-Ali & Haddad, 2004; Venkatesh & Bala, 2008). First, individuals will adopt technology when they assess its perceived usefulness and perceived ease of use as high. In fact, existing studies suggest that individuals who are skilled in and/or accustomed to using mobile devices, as is often the case with the younger generation, are more likely to identify with a perspective that justifies, enhances and expands the use of mobile technology. Second, ICT use shapes a new set of attitudes regarding technology's potential to contribute to health purposes. These attitudes not only reflect individuals' personal experiences prior to using mobile health applications, but their overall evaluations of technology as well. Such attitudes are likely to further enhance technology use (Ahadzadeh et al., 2015; Chung & Koo, 2015).
Another perspective in technology adoption is the Uses and Gratifications Theory (UGT), which focuses on how differences in motivation affect the extent of technology use (Coyne et al., 2015; Elhai et al., 2017). Individuals seek to attain objects and processes to meet their needs and goals. Variations in motivation stem from many factors, among them age (Coyne et al., 2015), personal inclinations (Mano, 2014) entertainment (Rokito et al., 2019) and health (Mano, 2019). The main gratification categories are:
content gratification stemming from accessing the right information;process gratification stemming from the satisfaction in using a particular media form; social gratification stemming from creating and vitalizing social relationships.A higher level of gratification is likely to increase the perceived functionality of mobile health applications, while familiarity with mobile health applications will increase their level of use and the need to update them (Ranck, 2016). Underlying this approach are the assumptions of the Social Diversification Hypothesis (Mesch, 2007; Mesh et al., 2012).
The Social Diversification Hypothesis (hereafter SDH) expands the theoretical background provided by the aforementioned communication and technology approaches, illustrating how application of a social science perspective increases our potential to compare the sociability patterns of individuals and communities (Mesch, 2007; Mesh et al., 2012). Since ICT serves as a low-cost medium (Bundorf et al., 2006; DiMaggio & Bonikowski, 2008), the use of health-related communication can expand the alternatives available to sociable individuals for entering into an extended span of social interactions, providing an additional source of health information despite geographic distance and time gaps. Clearly, then, ICT lowers the barriers to accessing health information and facilitates higher health literacy among disadvantaged groups, thus increasing their motivation to use ICT for an expanded range of services (Sillence et al., 2007). SDH remains skeptical about these assumptions and is concerned with differential use of ICT according to people’s social position in society, positing that ICT adoption may replicate or even amplify existing social inequalities. Inherent in SDH is the notion that individuals differ in their ability to gain access to social services, as services reflect residential and social capital (Korup & Szydlik, 2005; Mano, 2016). These skeptical assumptions are partially addressed by theories focusing on individual-level psychological aspects of technology adoption. Health adoption models test these assumptions.
Behavioral models of online health uses
The behavioral approach to online health uses necessitates the introduction of psychological components addressing the link between technology and health behaviors.
Health Belief Model
The Health Belief Model (hereinafter: HBM) applies the concepts of self-efficacy and health empowerment to examining health beliefs. It was originally developed for predicting the performance of screening behaviors and vaccinations (Redding et al., 2000), but since then it has been used to explain other behaviors. The HBM incorporates two categories of relevant effects in health-related technology adoption:
(1) The category of perceived threats to health (Ahadzadeh et al., 2015; Akompab et al., 2013) addresses the importance of evaluating perceived risks of health threats (Redding et al., 2000). This concept reflects the degree of perceived susceptibility (also referred to as vulnerability) and perceived severity of health concerns. Individuals exhibiting this vulnerability may need to assess the likelihood of contracting a disease or developing a particular behavior. This necessitates to evaluate the vulnerability of close family members facing a history of disease and the likelihood of a close partner contracting a disease (Ahadzadeh et al., 2015; Jones et al., 2014).
(2) The category of behavior evaluation includes the perceived benefits and perceived barriers of carrying out a particular health-improving behavior (Lajunen & Rasanen, 2004). The benefits refer to the perceived effectiveness of performing or changing a behavior, while the barriers refer to the perceived costs or obstacles in doing so (Redding et al., 2000). Perceived usefulness refers to the belief that the adopted technology helps individuals perform a task better. Perceived ease of use is the belief that technology can be used with little or no effort, especially in m-Health, eHealth and telemedicine research (Or et al., 2011; Keselman et al., 2008).
Health Empowerment Model
Empowerment is a general term that captures the transition from a state of powerlessness to a state of relative control over any specific aspect of an individual's life. Health empowerment is often considered to be the “holy grail of health promotion” (Rissel, 1994). The Health Empowerment Perspective explains the empowering effect of information (Lemire et al., 2008; Mano, 2014a), such that its consumers become pro-active in terms of health care (Rains, 2007). This empowerment finds expression in better and more equal relationships with health professionals (HPs) (Caiata-Zufferey et al., 2010), better decisions regarding one’s own health and adopting or changing one’s health behavior (Mano, 2014a, 2014b; McKinley & Wright, 2014).
Online searches for health information satisfy two purposes: functionality, because online health searches cover a wide range of issues and enable selective processing, channel complementation and more (Dutta & Bodie, 2008; Mesch, 2011), and gratification, because online information-seeking improves the user’s level of knowledge about health concerns (Dutta-Bergman, 2004b, 2006). According to Bandura's self-efficacy hypothesis (1997), health can be promoted by social cognitive means (Bandura, 2004). When people believe they can produce desired effects by their actions, they have higher incentive to act or persevere in the face of difficulties (Dutta-Bergman, 2004c). As individuals become more conscious of health concerns, they are more likely to search for health information for themselves as well as for family members and friends (McKinley & Wright, 2014), leading to a higher level of health empowerment. Indeed, having a defined purpose when seeking out information is important. Yet there is a difference between seeking a specific type of background information about a particular medication and searching through a list of possible sources for a more detailed description of a disease (Dutta-Bergman, 2004d). Reports indicate that 56% of online users look for information about new treatments and medications (Fox & Connolly, 2018; Rana & Dwivedi, 2015; Rana et al., 2015).
In fact, health information-seekers, whether intentionally or not, are interested in increasing their level of empowerment toward some kind of health change. The Internet is a convenient medium that is easily accessed and provides a wide range of options for all individuals. Online health information seems to offer an efficient means of attaining health information (best process), although not necessarily in the most effective manner (best outcome). In this case, knowing that the Internet is a reliable source of information triggers a process that promotes attainment of the necessary resources and skills. When individuals reach a state of “critical consciousness” regarding the existing situation and when the resources are made available, the process is actualized and health outcomes can be attained (Shareef et al., 2011; Shaw & Sergueeva, 2019). In fact, the Internet is now regarded as a complementary source of health information rather than as a substitute for more traditional media sources (Mesch et al., 2012). Consequently, Dutta-Bergman (2006) differentiates between professional, consumer and community approaches (Dutta-Bergamn & Bodie, 2008).
The professional approach posits that empowerment is cultivated when individuals internalize aspects of health and disease, for internalization makes active engagement possible. This perspective implies that individuals search more for health-related information when they become more willing and are more likely to take an active role in preventing, attending to and following up on health issues (Salmond & Hall, 2003). The consumer approach suggests that information consumption leads to empowerment and increases the odds of making optimal decisions. Rational thinking is a basic prerequisite that enables individuals to exercise proper judgment in evaluating information and provides them the potential to process information through comparison with additional sources of information. The community approach suggests that community-based links, including virtual links, increase participants’ potential to be exposed both to old and to new information as well as to the experiences of other members while providing opportunities to share personal experiences.
The relative weight of benefits versus barriers affects the likelihood of taking preventive action. When individuals perceive that the barriers are high, they are less likely to engage in healthy lifestyle behavior. The E(extended) HBM model (Bylund et al., 2011) adopted notions from the health empowerment perspective to include cues to action and self-efficacy. Cues to action are environmental triggers that can motivate an individual to adopt a health-improving behavior or change an existing one (Akompab et al., 2013; Redding et al., 2000). Triggers can be both external (such as illness, death of a relative due to disease or information about the behavior or disease from media sources) and internal (health status) (Redding et al., 2000). All three behavioral approaches to health assume that having a defined purpose when seeking out information is important and that communicating personal needs (Fox et al., 2005) necessitates taking responsibility and posing questions and expects individuals’ willingness to play an active role in preventing, treating and following up on health issues for themselves and others (Dutta-Bergman, 2006; Lee et al., 2018).
The Health Attainment Process
The combination of sociological behavioral and ecological models of health showcases the existence of variations in health behaviors pointing to the complex nature of the health attainment process (Rosenberg, 2018). This study focuses on three types of actions sharing personal experiences regarding chronic health conditions (Kendall Roundtree, 2017), discussing the work of health institutions—a variation of posting reviews of doctors (Thackeray et al., 2013), and posting or commenting on health-related content—a variation of “liking” or commenting on content provided by others (Kendall Roundtree, 2017). Similarly, Mano shows how differences between health attitudes and health behaviors are related to variations in the use of online health sources (Mano, 2019a; 2019b). In line with the well-established decision-making model (Adjen, 1983), we distinguish between (Mano, 2019);
health attitudeshealth behaviorshealth changesHealth Attitudes
Online health-related activity may increase people's sense that their trust has been misplaced (Tustin 2010; Gibbons 2008), hence boosting their motivation to look for alternative health services/products/providers (Sciamanna et al., 2004; Mccomas et al., 2015), especially in the case of older individuals (Makai et al., 2015). These motivations increase one’s evaluations of positive health attitudes (Mano, 2018). Positive health attitudes about the online process affect one’s choice about being treated by a specific physician, as well as the type of questions one asks when visiting a physician, such as questions relating to treatment type. In addition, drug recommendations are also affected by the extent of individuals’ knowledge and the information they possess (Katz et al., 2004), even when this information is of little or no relevance (Wagner et al., 2004; Bundorf et al., 2006).
Additional factors associated with health attitudes stem from the desire to change health habits, such as weight loss and smoking (Rice, 2006; Fox et al., 2011). Being unable to attain physical access to a physician because of geographic distance or mobility restrictions can also affect health attitudes (Purcell & Fox, 2010). Nonetheless, gaps often emerge when information is not accompanied by intentions to use it to extend the scope of the search.
The Theory of Reasoned Action must be mentioned in this context (Redding et al., 2000; Sutton, 2001; Venkatesh & Davis, 2000). According to this theory, the strongest predictor of an end behavior is the intention to perform it (Sutton, 2001). Among other things, this intention is shaped by attitudes towards technology (Redding et al., 2000). The Technology Acceptance Model was developed based on this theory (Davis, 1989; Venkatesh & Davis, 2000; Venkatesh & Bala, 2008). In brief, this model posits that the more positive an attitude and the more importance others attribute to performing a behavior, the higher the intention to perform this behavior. Frequency of use and previous experience improve search skills, enabling users to place more trust in social media (McKinley & Wright, 2014; Park et al., 2009). Trusting the source of health information is important because health information accessed on the Internet may be misleading or misinterpreted, leading individuals to request inappropriate interventions and medications (Goodyear-Smith & Buetow 2001; Purcell & Fox 2010). Lack of consideration of and attention to the individual-level factors mentioned above will increase the risk of generating and deepening differences in access and use of eHealth and mHealth services (Iverson et al., 2008; Mano, 2016). For this reason, health institutions must address notions of effectiveness and efficiency in order to increase successful implementation of programs for illness prevention, early diagnosis and regular attention to leading a healthy lifestyle (Aceijas, 2011; Mattke et al., 2012).
Health Behavior
Health behavior includes several important factors: It involves channeling certain individual behaviors toward a goal within a time and content context. This channeling process reflects expected outcomes and motivations. When an individual’s involvement is high, the level of health empowerment increases and so does the need for a higher level of involvement in health decisions, thus enabling individuals to make health changes (Dutta-Berman, 2008). An important assumption in this process is that accessing and using online health information affect users’ health habits. Several studies have addressed differential needs and roles of technology for health purposes (Rosenberg et al., 2017) among patients diagnosed with cancer (Ahadzadeh et al., 2015), heart conditions (Kerr et al., 2010), diabetes (Pereira et al., 2015) and other long-term conditions (Kennedy et al., 2007; Rogers et al., 2011). Perceived ease of use is an important factor in these cases in the context of needing to perform daily routines, with the aim of lowering sources of dysfunction or sense of disease (Mano, 2015). Moreover, individuals’ judgments of their ability to organize and adopt proper health behaviors must be adapted to designated types of performance (Bandura, 1986). This is especially important when using technology such as computers and smartphones.
Indeed, self-efficacy can trigger behavioral intention (Irani et al., 2009; Alalwan et al., 2015; 2016). Recent studies (Lim & Noh, 2017) show that self-efficacy promotes healthy behavior and the adoption of fitness applications. Fox and Connolly (2018) showed that self-efficacy exerts a positive influence on intentions to adopt mHealth applications. Nevertheless, in a more recent study Mano (2019) raises doubts regarding the extent to which self-efficacy is sufficient in introducing health behaviors. In fact, according to recent studies (Asimakopoulos et al., 2017) neither general self-efficacy nor computer self-efficacy has any effect on participants’ attitudes toward mobile fitness-tracking health technology and may even restrain individuals from adopting mHealth programs (Bhatnagar et al., 2017). This may be why health empowerment stresses the importance of two types of motivations: a) general health-related searches that allow individuals to search on their own time and at their own pace and shape their understanding of their medical condition; and b) access to specific and relevant information that can increase chances of recovery because it allows individuals to eliminate sources of concern and misunderstandings, thus helping them gain a better perspective on a condition, treatment, or medication (Bandura, 1997, 2004).
Health Changes
Considering the topic of health changes as a communication issue suggests that individuals will be differentially affected by the use of online health information. Access to relevant information increases understanding, making it easier for individuals to acquire a complete perspective on their medical condition, treatment, or medication and thereby increasing their chances of recovery (Bandura, 2004). Indeed, individuals with specific medical conditions search for health and medical information about their condition in order to understand the symptoms and the side effects of a medication and even to search for alternative treatments. Easy access to a wide range of online forums and services, among them feedback, goal-setting and self-monitoring, has proven successful in addressing eating disorders (Azar et al., 2013) and alcohol use disorders (Fowler et al.,2016), in encouraging physical activity (Coughlin et al., 2016) and self-monitoring behaviors during weight loss (Rusin et al., 2013), in recording food intake during weight loss programs (Hutchesson et al., 2015) and in providing support in psychotherapy (Prentice & Dobson, 2014). Similarly, individuals with heart conditions (Kerr et al., 2010), diabetes (Miller & Bauman, 2014; Pereira et al., 2015), cancer (Mobasheri et al., 2014) and other long-term conditions (Kennedy et al., 2007; Rogers et al., 2011) are more likely to make health changes to alleviate bothersome symptoms.
Health tracking behaviors include those that increase one's ability to monitor health concerns and detect early signs of health disturbances (Mano, 2015). Individuals will adopt rational behavior that reflects the benefits associated with the probability of adopting such behavior (Champion & Skinner, 2008). These changes can be also viewed along a risk-related nexus ranging from low risk to high risk (Mano, 2018; 2019). The effect of this approach was twofold: First, it led health policymakers and practitioners to reconsider the usability of digital tools in self-management practices for assessing clinical utility, benefits and risks, especially in the context of prevention and management of disease among those diagnosed with chronic conditions (Prentice & Dobson, 2014; Mosa et al., 2012; Anglada-Martínez et al., 2016). Second, it promoted further interest in public health and motivated communication studies that sought to assess the effect of online health forums on lifestyle and health-related changes (Mohaptra et al., 2015). This is the reason why recent studies in public health adopt the ecological perspective that focuses on an integrative approach to health studies.
Ecological Models
Individuals, groups, organizations and health systems play an important role in supplying health services and are significant agents in many aspects of service provision that generate health practices and effective health habits and changes among the service recipients (Schultze, 2005). Ecological models following this health perspective assume not only that multiple levels of influence exist but also that these levels interact and reinforce one another. This perspective is at the core of public health models and referred to as the social ecology perspective.
The ecological perspective assumes that individuals addressing health issues seek to be linked to other social entities in order effectively solve difficulties and concerns. As a result, individual are willing to adopt the concepts and ideas of others and to alter their behavior accordingly (Ronfenbrenner, 1979). Accordingly, the social ecology perspective proposes to link multiple levels of social interaction in issues of health. According to Stokols (1992, 1996), the social, physical, and cultural aspects of an environment have a cumulative effect on health. Stokols further contends that the environment itself is multilayered, since institutions and neighborhoods are embedded in the larger social and economic structures, and that the environmental context may exert a differential influence on the health of individuals, depending on their unique beliefs and practices. The social ecology framework for health research and practice is used to explain the etiology of a number of health problems. Social ecological analyses can also be useful in examining health problems in the context of life span developmental, sociodemographic, and societal circumstances that influence susceptibility to disease. Therefore, creating sustainable improvements in health is most effective when all of these factors are targeted simultaneously. Nevertheless, Stokols (1996) also notes that influencing all environmental aspects and all individual characteristics may be impractical. He therefore recommends focusing interventions on different levels of influence as well as considering the risks associated with the adoption of health behaviors (Mano, 2019). Indeed, social conditions in an individual’s environment may impede the application of desired health regimes. This is why the social ecology can serve as a basis for developing educational, therapeutic, and policy interventions to enhance personal and community well-being (Stokols, 2000).
The ecology perspective suggests that searching for health information refer to a selectivity effect. Individuals who a priori are highly interested in health and medical issues are more likely to search for information because they must deal with their own health conditions more frequently (Purcell & Fox 2010; Dutta-Bergman 2004a). These individuals consider the possible effects of this decision on their condition. Some decisions have an impact on well-being, whereas others may have far-reaching consequences with respect to a particular medical issue. We must therefore distinguish between the goals shaping health decisions and health changes that affect (a) wellbeing, (b) health care and (c) chronic illness. Lifestyle behaviors include practices that increase the likelihood of feeling better through day-to-day routines, including exercise and better nutrition (Mano, 2014; 2016; 2019; Rosenberg et al., 2020).
