The Influence of Social Media on Consumer Empowerment
Bukolaod1
PPT-Assignment4Socialmediaandconsumerempowerment_OnlineHealthCommunities1.pptxOnline HEALTH communities
The influence of social media on consumer empowerment
Presented by Maxine Rand, DNP, NEA-BC, RN-BC, CPHIMS
There are no readings from the textbook for this assignment.
The purpose of this assignment is to validate information from an online health community (OHC) that focuses on a specific disease condition.
Learning Objectives
Compare the critical content on a website/blog to information published on known reputable websites.
Evaluate whether you would recommend that site to a patient/client with that condition.
Rate your satisfaction with the usability of an OHC based on each of these four dimensions of experience: (1) Relevance, (2) unique value, (3) credibility and (4) comprehensibility.
This assignment requires the composition of a brief paper evaluating three online communities from the patient experience perspective. You will use Nambisan’s four-dimensional online community experience (OCE) construct to evaluate three online health communities.
Use a one to two pages for each OHC website evaluation. You may want to consider creating a subheading as you discuss each dimension.
Post your 3 to 6 page paper to the Assignment # 4 link. The paper is due on Sunday by 11:59pm.
Assignment
Step 1. Review this power point presentation. Read the 2011 Nambisan article “Evaluating patient experience in online health communities: Implications for health care organizations, “in Weekly Materials.
Step 2. Explore the internet for virtual health communities including wikis, logs, and websites sponsored by individuals and organizations. Consider selecting OHCs that focus on a disease condition that you are familiar with (https://www.pinterest.com/restministries/health-communities-online/). Choose three online communities other than those discussed in this presentation. WebMD© also offers access to a variety of online communities (https://exchanges.webmd.com/default.htm)
Step 3. Take a screenshot of the homepage for each of the online communities that you choose to evaluate.
Step 4. Compose your paper. Assign at least one page per OHC website evaluation and respond to activities a, b, and c below for each OHC.
Describe the purpose of the virtual health community that you selected.
Evaluate the website based on 4 dimensions of experience: Pragmatic, empathic, sociability, and
usability experience. The parameters for evaluation are described in Nambisan’s article (Weekly Folder) with details in the next slide.
c) Describe why or why not you would recommend each site to a patient/client with that condition.
Four dimensions of patient experience in an online health community (From Nambisan, 2011)
Pragmatic – The website offers Information exchange, especially personalized information, social and emotional support, 24-hour access, anonymity, and opportunities for self-help. Provides FAQs and archives of messages, clustering of similar topics, and providing links to reputed patient education sites.
Empathic – The design of the website offers special forums within the community that bring together people with similar diseases or health backgrounds. Provides participants with a bird's-eye view of the number of people who have similar disease or health background as themselves.
on ability to post messages, read the threads, and find FAQs. The member derives feelings of compassion, warmth, sincerity, and sensitiveness toward oneself and toward the health problems they discuss with other members of the OHC.
Sociability – The website contains features that will allow members to form their own groups-groups that share a purpose, such as weight loss or treatment adherence-can enhance sociability potential. Many people find that difficult-to-adhere-to treatments are easier to manage through group interaction. You will find positive comments that are supportive, friendly, and polite vs. rude and insulting.
Usability – The website interface that allows users to navigate and participate in the online community environment smoothly and effortlessly and without any obstructions or annoyances that might distract them from their goals or interest in the community. Making the community accessible through mobile telephones is another way to improve the usability experience.
Healthcare institutions use technology as a means of providing services to promote health and guide patients toward resources that will foster a lifestyle free from illness and disability.
Consumers are stepping away from these institutional websites as a means of acquiring information to the use of the Internet through blogs, messageboards, and online communities.
In 2007, Tom Ferguson, with the e-Patient Scholars Working Group, coined the term “e-patient,” and established three groups: (1) the well and their caregivers (“The Well”), (2) those facing a new medical challenge and their caregivers (“The Acutes”), and (3) those with chronic but stable illnesses and their caregivers (“The Chronics”). Chronics are more likely to develop websites for their condition, post content designed to help others, and to respond to questions raised by members of the community.
Origins of OHC
Communityware is a valuable resource to help networks of people with common interests accomplish tasks that formerly required centralized control and coordination, such as choosing the best doctor, deciding on the most appropriate treatment for a disease, and advice on resources and referrals.
Communityware is software that includes blogs, list-servs, web forums and chat rooms. It has continued to evolve as a result of Health 2.0, a term introduced in the mid-2000s to include health care technologies that promote collaboration between patients, their and healthcare professionals, and other stakeholders in health. Health 2.0 built on the possibilities for changing health care, which started with the introduction of eHealth in the mid-1990s following the emergence of the world wide web (The Economist, 2007}.
Communityware
Consumer exploration of the world wide web over the years supported the evolution from static pages to interactive tools. Social media and Web 2.0 empowered individuals to contribute their own content and provides easy access to information from online communities.
A growing number of virtual health communities emerged as consequence of ease in internet access using personal computers and cell phones. A 2011 Pew report found that of the 74 percent of adults who used the Internet, 80 percent (more than half of all US adults) looked for information on a specific disease or treatment. Populations like Feguson’s “The Chronics,” seeking advice from others undergoing similar health problems, were overall more likely to seek out informal sources of peer-to-peer assistance than consult with medical professionals (Fox, 2011).
Social media
According to Innovate MedTech, a digital health network, social media in the healthcare ecosystem opens up the possibilities for many novel applications of social media in healthcare such as:
Promotion of awareness about diseases, precautions and other health-related information.
Tailoring consumer health-related wants, needs and preferences. Online applications like WebMD offer platforms for both consumer and physician-moderated health-related conversations.
Healthcare organizations use online communities for disease management. For example, Inspire.com offers patients 24/7 access to its peer communities.
Clinical investigators and contract research organizations use online communities to recruit volunteers for clinical trials.
Social scientists are exploring the advantages of participating in virtual health communities and how online social networks influence the spread of health information and behavior change (Centola, 2010, 2011).
The foundation for this research was established in 1954 when Lazarsfield and Merton attempted to determine if people select ties “homophilously,” i.e., based on preferences for others with similar characteristics. They coined the term “choice homophily,” where people preferentially make ties to others who are similar to themselves. Although social attributes establish a pathway toward selection, current research reveals that the selection of online health communities is centered around information seeking and establishing a standard against which to evaluate personal success (Centola & van der Rijt, 2014).
Online social networks
The number of users of online health communities such as PatientsLikeMe and, Braintalk, is growing.
PatientsLikeMe, for example, has approximately 400,000+ patients, quadruple the number of users it had in 2011.
In 2005, Hoch and Ferguson evaluated Braintalk, a community of neurology patients and caregivers designed to promote education and awareness of various neurological conditions and general health related concerns .
Although their findings span a period of 8 years, the impetus for joining online health communities remains similar.
| Braintalk | PatientsLikeMe |
| Provision of information and advice from others undergoing similar health problems. | Advice they received from other members as reasons for their membership in the community |
| Exchange of emotional support | Emotional support received from other members |
| Positive psychosocial outcomes and enhanced well-being from frequent posts that focus on gaining insight into their struggles. | |
| Development of a sense of community | Motivation they got from other members |
| Adherence to treatment | Accountability the sites provided them for reaching their health-related goals |
OHCs
Research related to the value of virtual health communities through the analysis of user interactions could improve our understanding of health-related behaviors, the accuracy of information provided, and the design of technological solutions that support behavior change.
In 2016, researchers at The University of Texas School of Biomedical Informatics at Houston, Texas and Georgetown University Medical School, in Washington, DC, set out to explore communication patterns of users of a health-related community called QuitNet, one of the first online social networks aiming to promote health behavior change.
I had the opportunity to attend the American Medical Informatics Association 2016 annual conference and listen to them present the results of their research.
Patterns of use in an OHC
QuitNet is one of the first online social networks aiming to promote health behavior change, and has been in continuous existence for the past 14 years. It is widely used, with over 100,000 new registrants per year.. QuitNet indicated that participation in the online community was strongly correlated with abstinence.
Researchers processed 16,492 Quitnet messages, from a database of 16,492 messages generated from March through April 2007 using an automated classification system. The computer-annotated QuitNet data were then used to create theme-specific categories, that could be analyzed to understand patterns of social dynamics.
The users of QuitNet were classified into five mutually exclusive classes based on their self-reported abstinence.
Class 1: users who have remained abstinent throughout the study period
Class 2: users who were active smokers throughout the study period
Class 3: users who have relapsed (ex-smoker, active smoker) during the study period
Class 4: users who have successfully quit smoking (active smoker, ex-smoker) during the study period
Class 5: users who have relapsed multiple times during the study period.
Findings
Comments made by each class of users were categorized into subsets including
‘Quit Benefits,’ ‘Cravings,’ ‘Quit Progress,’ ‘Social support’, and ‘Quit Readiness.’
Ex-smokers focused most of their communication with peers on content related to
exchange of social support and monitoring their quit progress, reflecting on how far
each of them have come in their efforts to quit smoking.
Users exchanging information about benefits and cravings were strongly connected
among themselves in comparison with the rest of the network.
Themes identified in QuitNet messages included relapse, QuitNet-specific traditions,
and cravings. QuitNet members who were exposed to other abstinent members through the exchange of content related to interpersonal themes (e.g., social support, traditions, progress) tended to abstain.
Other themes showed no significant correlation with abstinence.
Use of an automated system that can analyze user interactions in an online health-related community lends to cohesion of communication themes across many behavioral states related to smoking cessation.
As demonstrated in the evaluation of online health communities (PatientsLikeMe, Braintalk) and research associated with hemophily, ex-smokers mostly focused their communication with peers on content related to exchange of social support and monitoring their quit progress, reflecting on how far each of them have come in their efforts to quit smoking.
Understanding benefits associated with this OHC will allow for the development of user specific approaches to smokers seeking to quit smoking, patterns of user participation in a robust network formation, and the development of targeted support within technology platforms such as QuitNet.
This analysis can enable the identification of specific OHC content that supports higher abstinence rates among community members, and facilitate the development of strategies that promote targeted health promotion.
Findings
What’s the right OHC for you?
Whether you choose to participate or explore, there is an online health community that will meet your personal needs or interests.
References
Braintalk website. Accessed January 1, 2017 at http://www.braintalkcommunities.org/forum.php
Centola, D., & van der Rijt, A. (2014). Choosing your network: Social preferences in an online health community. Social Science & Medicine, 125, 19-31. Retrieved from http://ndg.asc.upenn.edu/wp-content/uploads/2016/04/Centola-Van_de_Rijt-2014-Choosing_Your_Network.pdf
Centola, D. (2010). The spread of behavior in an online social network experiment.
Science, 329(5996), 1194–1197. Retrieved from http://www.sciencedirect.com.vlib.excelsior.edu/science/article/pii/S027795361400313X?
Ferguson, T. (2007). ePatients: how they can help us heal healthcare. Retrieved from http://www.e-patients.net/e-Patients_White_Paper.
Fox S. (2011). The Social Life of Health Information. Washington, DC: Pew Research Center. Retrieved from http://www.pewinternet.org/~/ media//Files/Reports/2011/ PIP_Social_Life_of_Health_Info.pdf.
Hajli, M. (2013). A research framework for social commerce adoption. Information Management & Computer Security, 21, 144–154.
He, W., Zha, S., & Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management, 33, 464–472. doi:10. 1016/j.ijinfomgt.2013.01.001
Health 2.0: Technology and society: Is the outbreak of cancer videos, bulimia blogs and other forms of 'user generated' medical information a healthy trend?". The Economist. September 6, 2007. pp. 73–74. Retrieved from http://www.economist.com/node/9719054
Innovate Medtech website. Health 2.0-Social Media in Healthcare. Accessed January 2, 2017 at http://innovatemedtec.com/digital-health/health-social-media-in-healthcare
Lazarsfeld, P., Merton, R.K.,(1954). Friendship as a social process: a substantive and methodological analysis. In: Berger, M., Abel, T., & Page, C.H. (Eds.). Van Nostrand, New York, pp. 18e66.
Myneni, S., Cobb, N.K., & Cohen, T. (2016). Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation. Paper presented at the American Medical Informatics Association Annual Conference, Chicago, Illinois, 14 November (pp. 934-943).
References
Nambisan, P. (2011). Evaluating patient experience in online health communities: Implications for health care organizations. Health Care Management Review, 36(2), 124-133.
Nath, C., Huh, J., Adupa, A.K., & Jonnalagadda, S.R. (2016). Website Sharing in Online Health Communities: A Descriptive Analysis.
Journal of Medical Internet Research, 8(1), e11. DOI: 10.2196/jmir.5237
PatientsLikeMe website. Accessed January 1, 2017 at https://www.patientslikeme.com/
Pinterest Health Communities Online website. Accessed January 1, 2017 at https://www.pinterest.com/restministries/health-communities-online/
Solberg, L. B. (2014). The benefits of online health communities. Virtual Mentor, 16(4), 270-274.2011)
References
