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University of Groningen Faculty of Economics and Business
Msc BA – Change Management June 2015
Supervisors:
Prof. Dr. A. Boonstra Edin Smailhodzic
Second assessor:
Eveline Hage
Word count: 12,541 words
(including abstract, excluding figures, tables, appendices, and bibliography)
Social media use in healthcare: effects on patients and their relationship with healthcare professionals
A systematic literature review
Wyanda Hooijsma (S2203502)
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Abstract
Background: Since its emergence in 2004, a growing percentage of patients use social media for health related reasons. To reflect on the alleged beneficial and potentially harmful effects of social media use by patients for health related reasons, the aim of this study is to provide an overview of the extant literature on the effects of social media use by patients for health related reasons on patients and their relationship with the healthcare professional.
Methods: A systematic literature review on empirical research regarding the effects of social media use by patients for health related reasons was conducted. Databases used are EBSCO and Web of Knowledge. The included papers met the following selection criteria: (1) be from a peer-reviewed journal, (2) written in English, (3) full text available to the researcher, (4) contain primary empirical data, (5) the users of social media are patients, (6) the effects of patients using social media are clearly stated, (7) satisfying established quality criteria.
Results: Initially, a total of 1,743 articles were identified from which 21 met the selection criteria and were included in the study. From these articles six categories of patient‟s use of social media were identified, namely, emotional, information, esteem, and network support, together comprising social support, and two other types of use, which are social comparison and emotional expression. The types of use were found to lead to seven identified types of effects on patients, namely improved self-management and control, enhanced psychological well-being, and enhanced subjective well-being, together comprising patient empowerment, and some other types of effects, which are diminished subjective well-being, addiction, loss of privacy, and being targeted for promotion. Besides, the identified types of use were also found to affect the healthcare professional and patient relationship, by leading to more equal communication between the patient and healthcare professional, shorter relationships, harmonious relationships, and suboptimal interaction between the patient and healthcare professional.
Conclusions: Different effects of patients‟ use of social media for health related reasons have
been identified in this paper. The findings led to the creation of three propositions to stimulate
future research. Limitations of this research are that the majority of articles studied online
support groups and that patients who quit using social media due to the experience of negative
effects were not included in the study.
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Introduction
A 13 year old girl was brought to the emergency department by her parents for an assessment of depression and potential suicidal ideation. The girl had a past medical history of attention deficit hyperactivity disorder and oppositional defiant disorder. The girl‟s parents were alarmed by a teenage friend about postings on Facebook that signaled that something might be wrong with the girl, as she posted photographs showing her cutting herself and texts like “I want you to know my secret,‟‟ „„I‟m fat and ugly,‟‟ „„I want to kill myself,‟‟ and „„The Monster is me‟‟ (Bennett et al., 2014, p.94). Additionally, the mother found a box of razors in the girl‟s bag. Once in the emergency department the parents showed the physician screenshots from the girl‟s Facebook page. The girl did not deny these postings or their sincerity and was very cooperative, but she did deny to have any suicidal ideation. After a physical examination, other than some old cutting scars, no evidence was found to provide a basis for the diagnosis. Consequently, the physician relied on the Facebook postings and diagnosed the patient with suicidal risk. She was transferred to a children‟s hospital for inpatient psychiatric care where she was diagnosed with mood disorder (case presented by Bennett et al., 2014).
The case above demonstrates how the use of Facebook by patients can provide valuable clues for physicians to come to a diagnosis. Especially for a psychiatric diagnosis in which physical evidence can be scarce and a patient‟s emotional state may be fluctuating. In the case, Facebook provided the patient with a medium to express her true feelings, which she failed to express in her non-virtual life and provided a source of evidence to the parents and the physician. The patient‟s disclosure allowed her parents and later the physician to provide the proper level of medical care. Consequently, patients‟ social media postings can provide physicians with potentially life-saving information that is not easily obtained elsewhere.
However, besides the potential to provide physicians with valuable clues for a diagnosis,
within the health care system, which broadly refers to “all activities whose primary purpose is
to promote, restore, and maintain health” (WHO, 2000), social media use by patients for
health related purposes can play many different roles. For instance, enabling psychosocial
support to patients (Ho, O‟Connor, & Mulvaney, 2014), enable more patient centered
healthcare delivery (Hawn, 2009) and affect the healthcare provider‟s market position
(McCaughey et al., 2014). Consequently, the use of social media by patients for health related
purposes, does not merely affect patients, but also healthcare professionals.
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Previous studies already identified many different effects of social media use by patients for health related reasons within the healthcare system. Social media can serve as an aid to patients in that it for instance fosters patients‟ autonomy by complementing the information provided by healthcare professionals (Rupert et al., 2014) and by providing psychosocial support (Ho, O‟Connor, & Mulvaney, 2014). On the other hand, social media use by patients can be an aid to healthcare professionals by, for instance, providing a tool to strengthen the organization‟s market position (McCaughey et al., 2014; Williams, 2011) and to stimulate conversation for brand building and improved service delivery (Li & Bernoff, 2008;
Williams, 2011). In fact, according to Hawn (2009) social media are one route to greater patient happiness and to a more patient centered healthcare system. Though, social media use by patients does not merely provide desired effects. It can also provide a challenge within the healthcare system to both patients and healthcare professionals. Since everybody with access to social media can post „advice‟ on how to deal with a certain disease or an outbreak, it is important to create reliable online communication channels to prevent worse situations. For example, in Nigeria one hoax meme urged Nigerians to drink excessive amounts of salt water to combat Ebola through Twitter. However, this may have led to two deaths and more than 12 admissions to hospital (Carter, 2014). In fact, many healthcare professionals fear that the social media use by patients for health related purposes spreads misinformation among patients (Rupert et al., 2014).
The above makes clear that the use of social media by patients for health related reasons provides different effects, which can result in as well benefits as challenges. It is important to identify these effects of social media for the healthcare system, as Antheunis, Tates, and Nieboer (2013) have shown in their study that “a growing percentage of patients use social media for health-related reasons, so health professionals will have to reflect on the alleged beneficial effects and the potential harmful effects of social media use by patients in healthcare” (Antheunis, Tates & Nieboer, 2013, p.431). So, the benefits of social media use by patients can be reaped by healthcare professionals and the harmful effects can be anticipated or circumvented to reduce the impact.
However, to deal successfully with the increasing use of social media by patients for health-
related reasons it would be helpful to know what effects of social media use by patients in the
healthcare system have already been identified in extant literature. That literature could help
in generating more and deeper insights in the different effects and their interrelatedness and
could identify ways to deal with the increase of social media use by patients for health related
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reasons. Nevertheless, no systematic literature review on these effects has been identified yet.
Therefore, in order to provide an overview of what can be learned from previous studies on the effects of social media and to synthesize these findings this study provides a systematic literature review on the effects of social media use by patients for health related reasons on patients and their relationships with healthcare professionals.
The aim of this study is to gain insights in the benefits and challenges of the effects of social media use by patients within the healthcare system and especially the effects on patients and their relationships with healthcare professionals. The effects aimed at in this study can be both causal and reciprocal, but always start with the use of social media by patients. By performing a systematic literature review on these effects of social media, this study contributes with an overview of the existing literature on the topic of “social media use in healthcare”.
Additionally, this study can be utilized as a starting point for further research on the topic of the effects of social media use by patients within the healthcare system.
“Since the impact of the Internet and other technological developments on health care is expected to increase, health professionals will have to keep pace with the potential effects of social media usage on clinical practice” (Antheunis, Tates, & Nieboer, 2013, p. 430). As well, in 2011, the Dutch Medical Association (KNMG) presented the national guidelines on the use of social media, of which its first recommendation is to make use of the potential of social media. Consequently, to be an aid for healthcare professionals to uncover the effects, potentials and risks associated with social media use by patients, this study will contribute to the creation of a deep understanding of the effects of social media use by patients on patients and their relationship with the healthcare professional, as well its potential to increase the quality of services offered by the healthcare professional and the risks associated with social media use by patients.
The paper has been structured as following. After the introduction the background section is presented followed by a description of the methodology. Then the results are discussed and a discussion on the findings and the theoretical and practical relevance will be presented.
Finally, the paper will end with a brief conclusion.
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Background
In today‟s society, many people are using social media. In fact, 74% of all US internet surfers made use of social media as of January 2014 (Pew Research Center‟s Internet Project January Omnibus Survey, 2014). But despite this popularity, there is confusion about what is exactly meant by the term social media (Kaplan & Haenlein, 2010). Therefore, in this paper the definition of social media will be as the definition provided in the highly cited paper by Kaplan and Haenlein (2010, p.61), which describes social media as “a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content” The internet-based applications refer to the different categories of social media, which are blogs, content communities, social networking sites, collaborative projects, and virtual worlds, which are accessible to users to utilize it for, among other things, health related reasons.
Users of social media in healthcare
Within this study the main focus is on how the use of social media by patients for health related reasons affects patients and their relationships with healthcare professionals.
Consequently, the “users of social media in healthcare” in this study refer to the patients.
Patients are treated as any person who self-proclaims to be suffering from a certain disease, whether officially diagnosed by a healthcare professional or not. On the other hand, healthcare professionals are treated as people providing healthcare services. The following definition provided by the WHO (2010, p.1) has been used, which defines healthcare professionals as those who “study, advise on or provide preventive, curative, rehabilitative and promotional health services based on an extensive body of theoretical and factual knowledge in diagnosis and treatment of disease and other health problems. They may conduct research on human disorders and illnesses and ways of treating them, and supervise other workers.” This definition applies to a broad range of different specializations of healthcare professionals.
However, for this study we mainly focus on the general healthcare professions, like healthcare professional, doctor, and physician, as most patients first see a doctor or a general-physician before sent to a specialist.
Social media use in healthcare
Within the healthcare, the use of social media by patients for health related reasons is growing
due to an increase in the patients‟ quests for information (Antheunis, Tates, & Nieboer, 2013,
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McCaughey et al., 2014). Patients perceive social media to be a tool to increase knowledge about their health related problems, to receive emotional support, and to supplement the information received from healthcare professionals (Antheunis, Tates, & Nieboer, 2013;
Rupert et al. 2014). Hence, among others things patients perceive social media to be a tool for increasing their knowledge, which may shift the balance of power between patients and healthcare professionals and foster shared decision making (Colineau & Paris, 2010).
However, Rupert et al. (2014) found that many healthcare professionals fear that patients are misinformed by using social media as an information source rather than relying on experts and that social media might interfere with the patient-healthcare professional relationship.
Consequently, Rupert et al. (2014) discovered that due to the perceived negative consequences of social media use by patients, many healthcare professionals reacted negatively to online health community content raised by patients during a clinical interaction.
Likewise, Broom (2005) discovered that many healthcare professionals do not perceive social media use by patients to be desirable as it “transforms the potential risk to the specialist into a problem created not by the expert‟s insufficiencies but by the disagreeable character of individuals engaging in online support groups” (Broom, 2005, p.101). So, as has been presented in the literature by Rupert et al. (2014), Broom (2005), Antheunis, Tates, and Nieboer (2013), and Colineau and Paris (2010), is that the perceptions on the effects of social media use by patients for health related reasons are diversified. On one hand, it could empower patients with among other things increased knowledge, but on the other hand it could be a danger to patients by the spread of misinformation and so, impede the work of healthcare professionals.
Consequently, in order for healthcare professionals to successfully anticipate the potentially harmful or beneficial effects of social media use by patients on patients and their relationships with healthcare professionals, the mainly negative perceptions held by healthcare professionals on the effects of the use of social media by patients (Rupert et al. 2014; Broom, 2005) should be supplemented and/or altered by a synthesization of the existing empirical evidence on the actual effects of social media use by patients.
For healthcare professionals it is important to understand the actual effects of social media use
by patients, as they could be the informant to patients for safe social media use (Rupert et al.,
2014). For instance, healthcare professionals could advice patients on how to use social media
safely and on which sites provide reliable information and support. So patients can use social
media to receive the beneficial effects, e.g. psychosocial support (Ho, O‟connor, & Mulvaney,
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2014) and anticipate on the risks associated with using it, e.g. being misinformed (Broom, 2005). Even, healthcare professionals can prescribe social media use to patients as an additional service or treatment for their illness. Still, healthcare professionals might have to deal with the consequences when patients experience negative effects from their social media use, like wrong „advice‟ by peers on which treatment to use (Carter, 2014; Broom, 2005). But, by instructing patients about how to use social media safely for health related purposes the impact of the negative effects can be reduced. As stated by Antheunis, Tates, and Nieboer (2013) is that since social media is there and patients are actively using it for health related purposes anyway, healthcare professionals better accept its existence and use it to the patient‟s advantage and try to minimize the negative effects.
Nevertheless, not only the effects on patients should be understood, but also the effects on the healthcare professional and his/her relationship with the patient. Social media use by patients has the potential to stimulate conversation about the perceived quality of the healthcare professional‟s services and so affect his/her reputation (Li & Bernoff, 2008; Williams, 2011).
For instance, when a patient feels that during a consultation he/she is not being taken seriously by the healthcare professional, he/she can discuss the experience on social media and so affect the healthcare professional‟s reputation. Consequently, social media use by patients can affect the brand building of healthcare professionals and their market position, which can strengthen or weaken the healthcare professional‟s relationship with patients (Li &
Bernoff, 2008; Williams, 2011).
Therefore, in order to provide an overview of what can be learned from previous empirical studies on the effects of social media use by patients for health related reasons on patients and their relationships with healthcare professionals this study will provide a systematic literature review. To our knowledge no other systematic research on this topic has been performed yet, but it would be valuable as it provides the opportunity to extract general findings from specific studies. Subsequently, healthcare professionals can learn from these findings about the effects of social media use by patients and share this knowledge with other patients and use it to their own advantage. Hence this study presents a systematic literature review aiming at answering the following question:
What are, according to recent empirical research, the effects of social media use by patients
for health related reasons on patients and their relationships with healthcare professionals
and how can these effects be categorized?
8 Social media use
by patient for health related
reasons.
Effect on patients
Effect on the relationship between healthcare
professional and patient
To answer this question this study will use the model as shown in figure 1 below, which presents the concepts and relationships of interest for this study. From the model it becomes clear that first the types of social media use by patients, as identified in recent empirical research, will be clarified (1). This is followed by an investigation of the recent empirical literature on the identified effects of social media use by patient on patients, (2) and on the relationship between patients and their healthcare professionals (3). Finally, it is investigated whether the effects on patients affect the effects on the relationship between healthcare professional and patient (4).
Figure 1: Conceptual model
(1)
(2)
(3) (4)
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Methodology
With the aim to provide an overview of the different effects of social media use by patients for health related reasons on patients and their relationships with healthcare professionals, a systematic literature review has been conducted. To perform this literature review the guidelines on conducting a systematic literature review as prescribed by the Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses (PRISMA) have been followed (Moher et al., 2009). As well, the PRISMA flow diagram has been used to describe the flow of information through the different phases of a systematic literature review and the PRISMA checklist has been included (see Appendix A).
Key words
In order for this literature review to provide a comprehensive overview of the extant literature on the effects of social media use by patients on patients and their relationships with healthcare professionals, it is important that all relevant terms are covered in the search for literature. Additionally, relevant synonyms and related terms to the key concepts need to be included in the search. For social media the different categories identified by Kaplan and Haenlein (2010) have been used, which were complemented with the most popular examples of the respective social media platform. Moreover, by adding a * to the end of a search term, the search engine searches for conjugations of this term, and by adding “ “ around a complete term, the search engine searches for the entire term and not merely for the loose words the term is comprised of. Hence, covering social media are the following search terms: “social media”, blog*, “content communit*”, “social networking site*”, “online social network*”,
“virtual world”, “online communit*”, “online forum*”, Facebook, Twitter, Wikipedia, IMVU,
“second life” and YouTube. The second category concerns the patient and is covered by the term “patient*”. For the final category healthcare professionals, the following keywords were identified: “health* provider”, “health* professional”, “physician”, “doctor” and “hospital”.
Databases
Two search engines were utilized for finding the relevant literature and were chosen based on their availability to the researcher and their relevance to the subject. These search engines are Web of Science and EBSCOhost COMPLETE. Both search engines cover multiple databases.
However, not all databases were relevant for this research. Consequently, the databases that
did not cover the field of interest for this research were excluded from the search. This
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exclusion was based on the descriptions of the databases provided by the search engines. In Appendix B an overview of the utilized databases per search engine can be found.
Search strategies
In order to find the articles one search strategy consisting of three terms has been adopted.
The first term covers social media, the second term covers patients, and the third term covers healthcare professionals. The search strategy looks as following:
“social media” or blog* or “content communit*” or “social networking site*” or “online social network*” or “online social network*” or “virtual world*” or “online communit*” or
“online forum*” or Facebook or Twitter or Wikipedia or IMVU or “second life” or YouTube +
“Patient*”
+
“health* provider*” or “health* professional*” or “physician*” or “doctor*” or “hospital*”
The search strategy could be entered in both databases the same way. However, for each database the search options were slightly different. For EBSCO the irrelevant databases were excluded first (Appendix B) and no specific search field was selected for one of the three terms. Additionally, the option to search only in scholarly (peer reviewed) journals was used and the publication dates were selected to be after 2004. In the year 2004 the term Web 2.0 was used for the first time, which marks the start of the social media era (Kaplan & Haenlein, 2010). On the other hand, in Web of Science searching in the topic was selected for all three terms, which includes searching in the titles, abstracts, author keywords, and keywords plus fields of the articles. Additionally, just as in EBSCO the publication dates were selected to be from 2004 on. After the search was performed the results were limited on document type, as the „articles only‟ box was selected, and on language, so, only articles written in English were kept.
Selection criteria
For an article to be included in the study it had to meet several selection criteria. The first
criterion was that the article should come from a peer-reviewed journal. Secondly, in order to
be able to establish a deep understanding of the article, articles that were written in a language
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other than English were excluded. As well, if the full text of the article was not available online, the article was excluded. Additionally, the article needed to be based on empirical studies and comprise primary data about an effect of social media use by patients for health related purposes on patients and their relationships with healthcare professionals. Hence, if from the article it was not clear whether social media use or other usage of the internet, e.g.
email or apps, by the patient caused the effect, the article was excluded. As well, if there was no primary evidence on the occurrence of the effect of social media use by patients for health related purposes itself presented in the article, but rather the effect was identified as being a potential result insinuated by the researchers, the article was excluded. Finally, the articles were assessed on their quality by using the standard quality assessment criteria as identified by Kmet, Lee, and Cook (2004).
Selection process
In order to increase the reliability of this research, the selection process has been conducted by two researchers, W.H. and E.S. On two different occasions the two researchers agreed to read independently 100 pre-selected abstracts and select the articles which, according to the researcher, would be included in the study based on the selection criteria. Afterwards, the selected articles by the two researchers were compared and it turned out that in each case one researcher independently marked an article as “yes, this one will be included” the other researcher also marked this article as “yes”. Though, differences were found in the articles marked as “maybe”, but after a brief discussion both researchers could agree on which articles of the „maybe category‟ should be included and which not. The articles that were not included provided potential effects of social media use by patients in the discussion section. These effects were not confirmed by the data but were insinuated by the researcher. Hence, after the discussions, the researchers agreed that articles should contain an effect of social media use by patients supported by the collected data to be included in the study. As a result of the discussions between the two researchers the terms used in this study became clearer to both researchers. Within the first round of practice, both researchers immediately agreed that out of the 100 articles, 3 articles should be included and in the second round this were 4 articles.
After this practice one researcher conducted the selection process and discussed the articles marked as “maybe” with the second researcher to come to a final selection of articles.
Additionally, for the quality assessment the two researchers together assessed one qualitative
study and one quantitative study which led to the establishment of a good understanding of
the assessment criteria.
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Results
Search results
The search for relevant articles for this study has been performed on the 17
thof March 2015.
On this day both search engines have been searched. The application of the search strategy to the two search engines resulted initially in a total of 1,743 articles. Within the 1,743 articles many duplicates were found as well within the search engines as between the search engines.
By removing duplicates the first found article was kept and since the search engine EBSCO was used first, most of the remaining articles came from this search engine. By using the Refworks functions for identifying exact and close duplicates, 468 duplicates were identified and removed leaving 1,275 articles.
The remaining 1,275 articles have been screened on title and abstract with regards to the selection criteria. An article was removed when, for example, it became clear that the user of social media was not a patient but another user, like the hospital, a regular “healthy” person or healthcare professional. Also, in case of the virtual reality platform, it turned out that in many articles this referred to a training tool for healthcare professionals instead of use by patients.
Hence, these articles were removed as well. Additionally, several articles referred to internet use by patients for health related reasons and their effects, but did not specify the effects of social media. If after looking at the article the effect of social media could not be distinguished the article was removed. Moreover, articles that were written in a language other than English, like Lithuanian and Spanish, were removed as well as articles that did not comprise primary data or did not elaborate on an effect of patients using social media. In case the title and abstract were unclear about the purpose and results of the article, the paper was consulted. In total, due to unclear abstracts/titles, 37 articles have been visited, which eventually all have been removed. Additionally, 7 articles were removed due to the inability of the researchers to access the article. Eventually, the selection process resulted in the removal of 1,253 articles based on the selection criteria. The 22 articles that met the selection criteria were assessed on their quality.
The articles were assessed on their quality by using the Standard Quality Assessment Criteria
for Evaluating Primary Research Papers by Kmet et al., (2004). This assessment tool
distinguishes between qualitative and quantitative research and provides different quality
assessment criteria for each type of research. These criteria are rated on their presence in the
respective article and are either completely addressed in the article (resulting in 2 points),
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partly addressed (resulting in 1 point), or not addressed (resulting in 0 points). In case an article scored below the threshold of a 50% score of the total amount of points possible, the article is assumed to be of low quality and removed from this study. This cut-point for inclusion is relatively liberal according to the authors of the assessment tool (Kmet et al., 2004). In Appendix C the results of the quality assessment are presented and show that 1 article has a quality below the 50% cut-point. Hence, this article was removed leaving 21 articles.
When looking at the quality assessment it is noteworthy that regarding the qualitative study, many authors did not show any or much reflexivity on the impact of their personal characteristics or methods used.
The article selection process has been graphically shown in figure 2 below.
Figure 2: Flow chart of the article selection process
EBSCO:1,209 potentially relevant articles
Web of Science:
334 potentially relevant articles
Total of 1,743 potentially relevant articles
Total of 1,275 articles left for screening
Total of 22 articles meet selection criteria
Total of 21 articles included in the study
468 duplicates excluded
1,253 excluded based on selection criteria
1 excluded based on quality
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Overview of the articles
To gain more insight in the nature and objectives of the 21 remaining articles an overview is provided in table 1 below. In this table the articles are numbered as in later tables articles are referred to by this number. All studies except for three are published in or after 2010, which shows that in the past five years the interest in and the use of social media by patients for health related reasons has increased since the emergence of social media in 2004 (Kaplan &
Haenlein, 2010). Moreover, 18 out of the 21 articles have been published in journals that are related to the medical field, whereas only three articles are published in journal that do not have a connection to medicine. Hence, outside perspectives from the medical field on the use of social media by patients for health related reasons are in minority. Additionally, only 2 out of the 21 articles use a theory or a model to build their research on. Wentzer and Bygholm (2013) use Greimas‟ Actant model for analyzing the narratives posted on online support communities. Broom (2005), on the other hand, builds his research upon the concepts of masculinity and femininity and how this affects men‟s‟ emotional expression which is influenced by cultural expectations. The selection of articles consists of 6 mixed methods studies, 8 quantitative, and 7 qualitative studies. Additionally, when analyzing the samples used in the studies, it became clear that for some samples it remains uncertain whether the entire sample consists of patients. In four articles the sample consists of an amount of posts posted to an online health community, it cannot be checked whether these posts were actually posted by real patients. These posts could also have been posted by imposters or other people interested into the content raised by the online health community. As well, in four articles the sample was constructed by asking members of online health communities to fill out an online survey, though also in this case no certainty can be given about the amount of actual patients in the sample. From 15 articles the impact factor of the journal could be found in the Journal Citation Reports 2013 database. The impact factor shows the frequency with which a journal‟s articles are cited in the scientific literature.
When analyzing the articles on which social media platforms have been studied and which
illnesses (see Appendix D), it is striking to see that in total 12/21 articles studied online
support communities, from which 10/21 articles studied online support communities for
chronic illnesses, such as the platform of PatientsLikeMe for ALS. Other types of social
media platforms and illnesses were spread among the remaining articles.
15 Table 1: Overview of included studies in the literature review
Author(s) - Article no.
Year Journal Main objective of study Type of
research
Data collection Participants (sample) 5-year impact factor*
Bartlett &
Coulsen - No. 1
2011 Patient Education and Counseling
To investigate the potential of online support groups to foster empowerment and how membership might affect the patient/health professional relationship
Quantitative Online survey 246 individuals from 33 chronic illness online support groups
3.158
Bauer et al.
- No. 2
2013 Nordic Journal of Psychiatry
To evaluate if and how online self-help forums are used by patients with bipolar disorders, their relatives and treating professionals.
Qualitative and Quantitative
Content analysis of posts
2400 postings of 218 users (Patients with Bipolar Disorder (94%), Relatives (4%), or Professionals (2%))
1.452
Bers et al.
- No. 3
2010 Pedriatic Transplantation
To investigate the feasibility and safety of an online virtual community as a potential psychosocial intervention for post- transplant adolescents
Qualitative and Quantitative
Data analysis of the Zora system logs and interviews
22 patients with solid organ transplants aged between 11-15 years
x
Broom - No. 4
2005 Journal of Sociology
To explore the experiences of, and attitudes towards, online support groups
Qualitative Interviews 33 Australian men with prostate cancer and 18 specialists
1.463 Chiu & Hsieh
- No. 5
2013 Journal of Health Psychology
To explore how cancer patients’ writing and reading on the Internet play a role in their illness experience.
Qualitative Focus-group interviews
34 Cancer patients 2.175
Colineau &
Paris - No. 6
2010 New Review of Hypermedia &
Multimedia
To understand why and how people use health-related sites Quantitative Online survey 33 Patients with a medical condition (patients)
0.410
Coulson - No. 7
2013 JRSM short reports
To explore how participation in an online support community may impact upon the experience of inflammatory bowel disease
Qualitative and
Quantitative
Online survey 249 patients living with either Crohn’s Disease (65.9%) or Ulcerative Colitis (26.1%) or awaiting formal diagnosis (8%)
x
Frost &
Massagli - No. 8
2008 Journal of Medical Internet Research
To identify and analyze how users of the platform
PatientsLikeMe reference personal health information within patient-to-patient dialogues
Qualitative Analysis of comments
123 comments posted within the ALS community
5.724
Gómez- Zúñiga et al.
- No. 9
2012 Journal of Medical Internet research
To explore the motivations and challenges faced by patients who share videos about their health and experiences on YouTube
Qualitative Analysis of videos
Videos uploaded by 4 patients with a chronic disease
5.724
Kim & Yoon - No. 10
2012 Information Research
To examine the use of an online health forum by married Korean women living in the USA who sought help for health and medical issues
Qualitative Content analysis of posts
1000 messages posted to a health forum MissyUSA
x
Kofinas et al.
- No. 11
2014 Obstetrics &
Gynecology
To determine whether social media, specifically Facebook, is an effective tool for improving contraceptive knowledge
Quantitative Survey 143 Patients who had scheduled a routine visit to a gynecologist
4.755
16
Lee & Wu - No. 12
2014 Reproductive Health
To use the online platform of blogs to explore whether the framing effect of information content, situated learning of information content, and health knowledge involvement would affect health communication between doctors and patients and further explore whether this would increase patient willingness to seek treatment.
Quantitative Online survey 278 participants who were seeking medical treatment in a clinic or hospital in Taiwan
x
Malik &
Coulson - No. 13
2010 Journal of Psychosomatic Obstetrics &
Gynecology
To focus on investigating the perceived disadvantages of online infertility support communities from the perspective of those who access and participate in them
Qualitative and Quantitative
Online survey 295 participants coping with fertility problems
1.685
Menon et al.
- No. 14
2014 Indian Journal of Psychological Medicine
To explore the potentials of social networking sites as an adjunctive treatment modality for initiating treatment contact as well as for managing psychological problems.
Qualitative and Quantitative
Interviews and an online survey
28 patients with any of the depressive or anxiety spectrum disorder
x
Oh & Lee - No. 15
2012 Health
Communication
To examine the indirect effect of Computer Mediated Social Support on doctor–patient communication through utilizing the sense of empowerment.
Quantitative Online survey 464 Korean patients with diabetes x
Pagoto et al.
- No. 16
2014 Journal of the American Medical Informatics Association
To describe adults who use Twitter during a weight loss attempt and to compare the positive and negative social influences they experience from their offline friends, online friends, and family members.
Qualitative and Quantitative
Survey 100 participants trying to lose weight 4.182
Rupert et al.
- No. 17
2014 Patient Education
& Counseling
To explore how individuals use online health community content in clinical discussions and how healthcare providers react to it.
Qualitative Focus groups 89 members of an online health community
3.158
Setoyama et al.
- No. 18
2011 Journal of Medical Internet Research
To explore the differences in peer support received by lurkers and posters in online breast cancer communities
Quantitative Online survey 253 members of four Japanese online breast cancer communities
5.724
Van Uden- Kraan et al.
- No. 19
2008 Journal of Medical Internet Research
To explore whether lurkers in online patient support groups profit to the same extent as posters do.
Quantitative Online survey 528 members of Dutch online support groups for patients with breast cancer, fibromyalgia, and arthritis
5.724
Wentzer &
Bygholm - No. 20
2013 International Journal of Medical Informatics
To investigate whether communication in online patient support groups is a source of individual as well as collective empowerment or to be understood within the tradition of compliance.
Qualitative Analysis of posts
4301 posts from two online communities, one for patients with COPD and one for women with pregnancy problems
3.214
Wicks et al.
- No. 21
2010 Journal of Medical Internet Research
To describe the potential benefits of PatientsLikeMe in terms of treatment decisions, symptom management, clinical management, and outcomes.
Quantitative Online survey 1323 members from six
PatientsLikeMe communities (ALS, MS, Parkinson’s Disease, HIV, fibromyalgia, and mood disorders)
5.724
* The 5-year impact factor is identified by using the Journal Citation Reports 2013 database
17
Analysis of results
Extracting the main findings of the 21 included articles in this study resulted in the findings presented in this section. Since the aim of this article is to provide an overview of what previous empirical studies have identified about the effects of social media use by patients for health related reasons on as well patients as their relationship with healthcare professionals, these results will be presented, categorized and discussed in this section along the model presented in figure 1. First of all, an overview of the extracted findings are presented regarding the types of social media use by patients and the effects on patients. This is followed by a discussion and categorization of the types of use of social media by patients.
Afterwards the effects of social media use by patients on patients are discussed and categorized. Subsequently, an overview of the extracted findings regarding the effects of social media use by patients on the relationship between patients and healthcare professionals are presented, discussed, and categorized. Then, it is investigated whether the effects on patients affect the effects on the relationship between patients and healthcare professionals.
Finally, an overview of the main findings is presented in an extended version of figure 1.
Extracted findings regarding the effects of different types of usages of social media by
patients on patients. From the included articles in this study, the extracted findings regarding
the types of use of social media for health related reasons by patients and the effects on
patients are presented in table 2 below and in appendix E. Table 2 shows the different types of
social media use by patients for health related reasons and the related effect identified in the
article. The table has been included in this section as it provides a good overview of what
types of social media use by patients can lead to what types of effects. Though, table 2 does
not display all the identified types of social media use for health related reasons by patients
and all the effects, but only the effects on patients that could be traced to a type of use. Hence,
to provide a complete overview of the extracted findings, appendix E shows the remaining
extracted types of social media use by patients for health related reasons and effects on
patients for which no evidence was found in the article regarding whether the effect and a
specific type of use were related. As, the majority of the extracted findings did not report a
cause-effect relationship, and the aim of this research is to provide an overview incorporating
all extracted findings, the main focus of the results section will be on categorizing the
identified types of social media use by patients and the effects. Both tables, table 2 and
appendix E, show which specific type of use/effect has been placed under which category in
18
the „Cat.‟ column. The identified categories are discussed in the sections following table 2.
Table 2: Types of social media use by patients for health related reasons and their related effect on patients
Article no.
Patient use of social media Cat. Related effect on patients Cat.
1 - Exchanging social support EMS/
NS
- Enhanced social well-being - Enhanced self-esteem
- Increased acceptance of the illness
EPW ESW ESW - Comparison with other members SC - Feeling more informed
- Increased confidence in treatment
- Increased optimism and hope for the future - Increased acceptance of the illness
ISC ESW ESW ESW 2 - Share emotions with other people who are coping
with similar problems
NS/
EMO
- Feeling of being connected to other people EPW - Adjunct to traditional self-help groups due to the
online communication on many different topics
IS - Increase patient's self-management ISC 3 - Meeting other patients who had gone through
similar experiences
NS - Increased sense of normalcy - Enhanced sense of self
- Increased social network online as well as offline
ESW ESW EPW 4 - Allowing men to talk about, express themselves
and share experiences about the more sensitive aspects of the disease (prostate cancer) by the ability to distance themselves from their disease and masculine expectations
EE/
EMS
- Increased experiences of intimacy;
- Transcend cultural expectations of
masculinity;
- Providing men with a 'way out' of what it is to be a 'real man'
ESW ESW ESW
- Information seeking IS - Increased anxiety levels
- Increased confusion by the patient (both mentioned by a physician)
DSW DSW 5 - Writing to be known and remembered EE - Helps the patient face the uncertainties of
the disease prognosis and prepare for, especially psychologically, the possible inevitability of the end of life
ESW
- To release negative emotions EE - Relieving distress
- Giving patients the strength to survive
ESW ESW - To help fellow sufferers by sharing relevant
information and experiences about the disease
IS - Powerful influence on patient´s decisions ISC
- Search for survivors ESS/
NS
- Read other people's success story leading to increased confidence to fight the disease
ESW
- Search for survivors ESS/
NS
- Read about other people’s bad experiences which leads to mental
preparation for difficult times ahead instead of becoming scared.
ESW
- Interacting with other patients NS - Creating a sense of belonging EPW 6 - Seeking information about the medical
condition
IS - Patient empowerment leading to increased involvement in decision making
ISC - A means to connect with others in similar
situations
NS - Breaking loneliness
- Promotion of deep relationships - Receive empathy and understanding
EPW EPW EPW - Sharing experiences and information to learn
about their conditions, what people do, what treatment works
- Collectively building knowledge, pooling together fragments and contributions from everybody in the community
IS
IS
- Patient empowerment leading to increased involvement in decision making
ISC
7 - Find others in similar situations
NS - Knowing you are not alone
- Receive true understanding from others
EPW
19
- Learn new information about the condition - Ask a question about the condition - Share information with others
IS IS IS
- Increased knowledge about the condition ISC
- Find emotional support EMS - Encouragement ESW
- Share experiences on treatment options to find encouragement before starting it.
ESS - Finding comfort and reassurance when starting a new treatment
- Increased confidence and resilience
ESW ESW - Downward social comparison SC - See their own illness experience in a more
positive light
ESW
- Upward social comparison SC - Inspiration through success stories ESW
- Reading other people's stories about a negative experience
RS - Demoralization
- Increased sense of anxiety and concern
DSW DSW 8 - Seeking other people’s opinion
- Asking questions about treatments
- Using other members as a resource to inform treatment decisions
IS IS IS
- Improved decision making
ISC
9 - Finding peers to break isolation NS - Feeling a sense of belonging and a member of a large community
EPW - Share mistakes to prevent other people from
making the same mistakes
IS - Impacts other people´s decision making ISC - Share experiences in a positive light ESS - Encouraging others to make to make their
own decisions and cope with the challenges that come with the disease
ESW
- Provide personal support by sharing feelings EMS - Improvement in ability to manage the disease
ISC - Making and sharing videos to tell the patient's
story
IS - Loss of privacy
- Hurt feelings due to negative/rude feedback
- Being targeted to promote specific products
LP DSW PR 13 - Seek fertility related information and emotional
support by sharing feelings and experiences with peers
IS/
EMS/
NS
- Reading other people's stories about a negative experience, leading to:
- Increased feelings of worry and anxiety - Decreased optimism
DSW DSW
- Seek fertility related information and emotional support by sharing feelings and
experiences with peers
IS/
EMS/
NS
- Reading other people’s stories about successful pregnancies, leading to:
- Increased feelings of jealousy and pain - Experiencing a sense of alienation
DSW DSW
- Social comparison of treatment process SC - Increased feelings of anxiety DSW 15 - Informational support
- Esteem support - Emotional support
IS ESS EMS
- Increased motivation to achieve disease-related goals;
- Increased sense of confidence - Increased sense of control
ESW ESW ISC 18 - Emotional support/ helper therapy
- Emotional expression
- Receiving advice about relationships - Receiving advice about treatments - Receiving advice about day-to-day life
EMS EE IS IS IS
- Decreased anxiety ESW
- Meeting other patients who had gone through similar experiences
NS - Provide insight/universality which decreases anxiety
ESW 21 - Interacting with others
NS - Mood Disorder Patients: Starting therapy or counseling
ISC
Definition of the abbreviations
Types of use: Types of effects:
EMS = Emotional support ISC = improved self-management and control
ESS = Esteem support EPW = Enhanced psychological well-being
IS = Information support ESW = Enhanced subjective well-being
NS = Network support LP = Loss of privacy
EE = Emotional expression PR = Being targeted for promotion
SC = Social comparison DSW = Diminished subjective well-being
AD = Addiction
20
Types of social media use by patients for health related reasons. When analyzing all articles one thing that shows is that patients do not seem to use social media to circumvent healthcare professionals, but rather use it as a complement to healthcare professional services to fulfill the patients‟ needs that cannot be met by the healthcare professional. Coulineau and Paris (2010) showed in their study that the relationship between patients and healthcare professionals was viewed by the patients as a more clinical one, where healthcare professionals provide expert knowledge about the disease and recommend treatment based on their medical knowledge, but not on their first-hand experience. Additionally, Coulineau and Paris (2010) found that doctors often have difficulty expressing empathy and that they filter information for the patient, where the patient rather wants to be informed about all options, as he/she believes that doctors might not be aware of the latest breakthroughs. Moreover, Rupert et al. (2014) found that the main reason for patients to join online health communities is their dissatisfaction with their healthcare professional‟s inability to meet the patients‟ emotional and informational needs. Though, patients would like to discuss the online community content with their healthcare professional, to obtain expert feedback. Similarly Gómez-Zúñiga et al.
(2012), found that the main reason for patients to make and share videos on YouTube was to bridge the gap between traditional health information about their diseases and everyday life.
Whereas Kofinas et al. (2014) proved that social media, and especially Facebook, could serve as an adjunct to traditional in-office counseling to improve patient knowledge on contraceptives.
Consequently, it seems that patients do not use social media to circumvent or replace healthcare professionals. Instead, social media are used as an adjunct to traditional in-office counseling to meet the unmet needs of patients.
Therefore, the types of social media use by patients as identified in this study refer to the way
in which patients use social media intended to meet an unmet need. The types of social media
use by patients as identified in the articles are categorized as shown in table 3 and explained
below. These types are categorized into social support, consisting of emotional, esteem,
informational, and network support (Schaefer, Coyne & Lazarus, 1981), and other types of
use, which are emotional expression and social comparison.
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Table 3: Types of use of social media by patients for health related purposes by article
Type of use Article no.
Social support Emotional support 1, 2, 4, 7, 9, 13, 14 15, 17, 18, 19, 21 Esteem support 1, 5, 7, 9, 15, 16, 20
Information support All articles
Network support 2, 3, 5, 6, 7, 8, 9, 14, 16, 17, 18, 20, 21 Other types of use Emotional expression 4, 5, 6, 7, 10, 14, 18, 20
Social comparison 1, 7, 13, 16
Social support. The most common found type of social media use by patients for
