Fernandez-Luque L, Karlsen R, Melton GB
HealthTrust: A Social Network Approach for Retrieving Online Health Videos
J Med Internet Res 2012;14(1):e22
http://www.jmir.org/2012/1/e22/
How do radiologists use social media? This lecture gives a better insight about both the advantages and downsides of using social media as a medical professional.
Social media and people with HIV. Results from an Italian surveyGiuseppe Fattori
As it is evident from the literature, the use of Internet, particularly Web 2.0 in
healthcare, is now under debate. Mainly, in Italy there is a shortage of specific studies concerning
the use of social media and new technologies in the infectious disease field, particularly in HIV/AIDS.
In order to explore this issue, we carried out a survey to understand how, today, the use of new
media could influence the behaviour of people living with HIV (PLWH) and their physician-patient
relationship.
Presentation at the 2017 joint annual convention of the Philippine Society of Hypertension & the Philippine Lipid & Atherosclerosis Society 23 Feb 2017 at Crowne Plaza Galleria Manila.
Also presented at the 2017 #HealthXPH Social Media & Healthcare summit 25 Apr 2017 at Marco Polo Hotel, Cebu City.
Analysis of the online networking activities of 100,625 globally distributed healthcare professionals (HCPs) on Twitter indicates an increase in their use of public social media for clinical and professional purposes.
The international healthcare community are increasingly using public social media channels for professional network building and clinical conversation. Through focused clusters related to professional interest, healthcare professionals (HCPs) are recognizing the value of online connections for discovering and discussing: clinical cases; practice matters; research; treatments; and news.
Social Media Research and Practice in the Health Domain - Tutorial, Part IIIngmar Weber
Second part of tutorial given at Weill Cornell Medicine Qatar on February 18, 2017 (https://qatar-weill.cornell.edu/bchp/socialMediaResearchPracticeHealthDomain.html). First part given by Luis Luque (see https://www.slideshare.net/luis.luque/social-media-research-in-the-health-domain-tutorial).
How do radiologists use social media? This lecture gives a better insight about both the advantages and downsides of using social media as a medical professional.
Social media and people with HIV. Results from an Italian surveyGiuseppe Fattori
As it is evident from the literature, the use of Internet, particularly Web 2.0 in
healthcare, is now under debate. Mainly, in Italy there is a shortage of specific studies concerning
the use of social media and new technologies in the infectious disease field, particularly in HIV/AIDS.
In order to explore this issue, we carried out a survey to understand how, today, the use of new
media could influence the behaviour of people living with HIV (PLWH) and their physician-patient
relationship.
Presentation at the 2017 joint annual convention of the Philippine Society of Hypertension & the Philippine Lipid & Atherosclerosis Society 23 Feb 2017 at Crowne Plaza Galleria Manila.
Also presented at the 2017 #HealthXPH Social Media & Healthcare summit 25 Apr 2017 at Marco Polo Hotel, Cebu City.
Analysis of the online networking activities of 100,625 globally distributed healthcare professionals (HCPs) on Twitter indicates an increase in their use of public social media for clinical and professional purposes.
The international healthcare community are increasingly using public social media channels for professional network building and clinical conversation. Through focused clusters related to professional interest, healthcare professionals (HCPs) are recognizing the value of online connections for discovering and discussing: clinical cases; practice matters; research; treatments; and news.
Social Media Research and Practice in the Health Domain - Tutorial, Part IIIngmar Weber
Second part of tutorial given at Weill Cornell Medicine Qatar on February 18, 2017 (https://qatar-weill.cornell.edu/bchp/socialMediaResearchPracticeHealthDomain.html). First part given by Luis Luque (see https://www.slideshare.net/luis.luque/social-media-research-in-the-health-domain-tutorial).
Presentation at the 2017 joint annual convention of the Philippine Society of Hypertension & Philippine Lipid & Atherosclerosis Society 25 Feb 2017, Crowne Plaza Galleria Manila.
A Warm Welcome Matters! The Link Between Social Feedback and Weight Loss in /...Ingmar Weber
Presentation in the Web Science track at WWW'17. Full paper https://ingmarweber.de/wp-content/uploads/2017/04/A-Warm-Welcome-Matters-The-Link-Between-Social-Feedback-and-Weight-Loss-in-r-loseit.pdf. Work led by Tiago Cunha (https://twitter.com/tocunha).
Abstract of paper:
Social feedback has long been recognized as an important
element of successful health-related behavior change. However, most of the existing studies look at the effect that online social feedback has. This paper fills gaps in the literature by proposing a framework to study the causal effect
that receiving social support in the form of comments in an
online weight loss community has on (i) the probability of
the user to return to the forum, and, more importantly, on
(ii) the weight loss reported by the user. Using a matching
approach for causal inference we observe a difference of 9
lbs lost between users who do or do not receive comments.
Surprisingly, this effect is mediated by neither an increase in
lifetime in the community nor by an increased activity level
of the user. Our results show the importance that a "warm
welcome" has when using online support forums to achieve
health outcomes.
Wake up Pharma and look into your Big data Yigal Aviv
The vast volumes of medical data collected offers pharma the opportunity to harness the information in big data sets
Unlocking the potential in these data sources can ultimately lead to improved patients outcomes
This presentation describes consideration how to maximize the impact of Big Data.
its methodology, practical challenges and implications.
The rise of online fake news on social media highlights an increasing problem. This talk, given at University of Michigan, explores why health professionals have a professional obligation to ensure patients get accurate, understandable health information.
Social media in health--what are the safety concerns for health consumers? Luis Fernandez Luque
Social media in health--what are the safety concerns for health consumers? by Lau AY, Gabarron E, Fernandez-Luque L, Armayones M. HIM J. 2012;41(2):30-5. https://www.ncbi.nlm.nih.gov/pubmed/23705132
Abstract: Recent literature has discussed the unintended consequences of clinical information technologies (IT) on patient safety, yet there has been little discussion about the safety concerns in the area of consumer health IT. This paper
presents a range of safety concerns for consumers in social media, with a case study on YouTube. We conducted a scan of abstracts on ‘quality criteria’ related to YouTube. Five areas regarding the safety of YouTube for consumers were identified: (a) harmful health material targeted at consumers (such as inappropriate marketing of tobacco or direct-to-consumer drug advertising); (b) public display of unhealthy behaviour (such as people displaying self-injury behaviours or hurting others); (c) tainted public health messages (i.e. the rise of negative voices against public health messages); (d) psychological impact from accessing inappropriate, offensive or biased social media content; and (e) using social media to distort policy and research funding agendas. The examples presented should contribute to a better understanding about how to promote a safe consumption and production of social
media for consumers, and an evidence-based approach to designing social media interventions for health. The
potential harm associated with the use of unsafe social media content on the Internet is a major concern. More empirical and theoretical studies are needed to examine how social media influences consumer health decisions, behaviours and outcomes, and devise ways to deter the dissemination of harmful influences in social media.
My talk 5/19/2016 for the Massachusetts Medical Society's Residents Fellows Section (RFS) annual meeting in Boston. Many doctors want to know how to get involved online. I discuss why to get online and highlight MMS' recently updated guidelines.
Top 7 Physicians Networks for you to Join as a Medical ProfessionalNet Pro Referral
As a medical professional or a medical specialist, there are numerous benefits of being engaged in physicians networks. Not only for being up to date with the developments on the field but also to be open to newer opportunities.
Doctors in social media: the story so far, with Creation Pinpoint (slides)CREATION
Today we are seeing an explosion in doctors using public social media channels to talk with each other about clinical and practice matters. In this webcast, Daniel Ghinn presents some milestones in doctors' use of social media from recent years and reveals first-time insights from millions of analysed conversations between doctors online using Creation Pinpoint.
Also available as video webcast here: http://www.slideshare.net/CreationHealthcare/doctors-in-social-media-the-story-so-far
This presentation describes the Clinical Studies Directory at the University of Southern California. It was presented to the national Clinical and Translational Science Awards (CTSA) Recruitment and Retention Working Group.
Social media research in the health domain (tutorial) - [part 1]Luis Fernandez Luque
Tutorial about the use of social media in the health domain. The tutorial is designed for healthcare professionals interested in eHealth. It was done for Weill Cornell Medicine - Qatar.
See the part II of the tutorial here: https://www.slideshare.net/IngmarWeber/social-media-research-and-practice-in-the-health-domain-tutorial-part-ii
Learn more about social media for health here https://www.futurelearn.com/courses/social-media-in-healthcare
Digital Health Revolution and the Opportunity for Dietitians to Lead Viable Synergy LLC
This is a presentation that was given at the 96th Annual Conference of the Ohio Academy of Nutrition and Dietetics conference on May 18, 2017. During the session we discussed the rise of digital health and its impact and role in health and healthcare delivery. Innovative software, hardware, and communication solutions were described and use cases discussed. Innovative programs and services being provided by dietitians in our region and around the world were highlighted.
Detailed Clinical Models and their relation with Electronic Health Recordsyampeku
Presentation of my PhD dissertation. Contains three main subjects:
-Archetype representation of non-dual model architectures
-Archetype-based mapping between clinical information models
-Automatic generation of implementation guides from clinical information models
Presentation at the 2017 joint annual convention of the Philippine Society of Hypertension & Philippine Lipid & Atherosclerosis Society 25 Feb 2017, Crowne Plaza Galleria Manila.
A Warm Welcome Matters! The Link Between Social Feedback and Weight Loss in /...Ingmar Weber
Presentation in the Web Science track at WWW'17. Full paper https://ingmarweber.de/wp-content/uploads/2017/04/A-Warm-Welcome-Matters-The-Link-Between-Social-Feedback-and-Weight-Loss-in-r-loseit.pdf. Work led by Tiago Cunha (https://twitter.com/tocunha).
Abstract of paper:
Social feedback has long been recognized as an important
element of successful health-related behavior change. However, most of the existing studies look at the effect that online social feedback has. This paper fills gaps in the literature by proposing a framework to study the causal effect
that receiving social support in the form of comments in an
online weight loss community has on (i) the probability of
the user to return to the forum, and, more importantly, on
(ii) the weight loss reported by the user. Using a matching
approach for causal inference we observe a difference of 9
lbs lost between users who do or do not receive comments.
Surprisingly, this effect is mediated by neither an increase in
lifetime in the community nor by an increased activity level
of the user. Our results show the importance that a "warm
welcome" has when using online support forums to achieve
health outcomes.
Wake up Pharma and look into your Big data Yigal Aviv
The vast volumes of medical data collected offers pharma the opportunity to harness the information in big data sets
Unlocking the potential in these data sources can ultimately lead to improved patients outcomes
This presentation describes consideration how to maximize the impact of Big Data.
its methodology, practical challenges and implications.
The rise of online fake news on social media highlights an increasing problem. This talk, given at University of Michigan, explores why health professionals have a professional obligation to ensure patients get accurate, understandable health information.
Social media in health--what are the safety concerns for health consumers? Luis Fernandez Luque
Social media in health--what are the safety concerns for health consumers? by Lau AY, Gabarron E, Fernandez-Luque L, Armayones M. HIM J. 2012;41(2):30-5. https://www.ncbi.nlm.nih.gov/pubmed/23705132
Abstract: Recent literature has discussed the unintended consequences of clinical information technologies (IT) on patient safety, yet there has been little discussion about the safety concerns in the area of consumer health IT. This paper
presents a range of safety concerns for consumers in social media, with a case study on YouTube. We conducted a scan of abstracts on ‘quality criteria’ related to YouTube. Five areas regarding the safety of YouTube for consumers were identified: (a) harmful health material targeted at consumers (such as inappropriate marketing of tobacco or direct-to-consumer drug advertising); (b) public display of unhealthy behaviour (such as people displaying self-injury behaviours or hurting others); (c) tainted public health messages (i.e. the rise of negative voices against public health messages); (d) psychological impact from accessing inappropriate, offensive or biased social media content; and (e) using social media to distort policy and research funding agendas. The examples presented should contribute to a better understanding about how to promote a safe consumption and production of social
media for consumers, and an evidence-based approach to designing social media interventions for health. The
potential harm associated with the use of unsafe social media content on the Internet is a major concern. More empirical and theoretical studies are needed to examine how social media influences consumer health decisions, behaviours and outcomes, and devise ways to deter the dissemination of harmful influences in social media.
My talk 5/19/2016 for the Massachusetts Medical Society's Residents Fellows Section (RFS) annual meeting in Boston. Many doctors want to know how to get involved online. I discuss why to get online and highlight MMS' recently updated guidelines.
Top 7 Physicians Networks for you to Join as a Medical ProfessionalNet Pro Referral
As a medical professional or a medical specialist, there are numerous benefits of being engaged in physicians networks. Not only for being up to date with the developments on the field but also to be open to newer opportunities.
Doctors in social media: the story so far, with Creation Pinpoint (slides)CREATION
Today we are seeing an explosion in doctors using public social media channels to talk with each other about clinical and practice matters. In this webcast, Daniel Ghinn presents some milestones in doctors' use of social media from recent years and reveals first-time insights from millions of analysed conversations between doctors online using Creation Pinpoint.
Also available as video webcast here: http://www.slideshare.net/CreationHealthcare/doctors-in-social-media-the-story-so-far
This presentation describes the Clinical Studies Directory at the University of Southern California. It was presented to the national Clinical and Translational Science Awards (CTSA) Recruitment and Retention Working Group.
Social media research in the health domain (tutorial) - [part 1]Luis Fernandez Luque
Tutorial about the use of social media in the health domain. The tutorial is designed for healthcare professionals interested in eHealth. It was done for Weill Cornell Medicine - Qatar.
See the part II of the tutorial here: https://www.slideshare.net/IngmarWeber/social-media-research-and-practice-in-the-health-domain-tutorial-part-ii
Learn more about social media for health here https://www.futurelearn.com/courses/social-media-in-healthcare
Digital Health Revolution and the Opportunity for Dietitians to Lead Viable Synergy LLC
This is a presentation that was given at the 96th Annual Conference of the Ohio Academy of Nutrition and Dietetics conference on May 18, 2017. During the session we discussed the rise of digital health and its impact and role in health and healthcare delivery. Innovative software, hardware, and communication solutions were described and use cases discussed. Innovative programs and services being provided by dietitians in our region and around the world were highlighted.
Detailed Clinical Models and their relation with Electronic Health Recordsyampeku
Presentation of my PhD dissertation. Contains three main subjects:
-Archetype representation of non-dual model architectures
-Archetype-based mapping between clinical information models
-Automatic generation of implementation guides from clinical information models
By eating grains, fruits and vegetables as the foundation of each meal and healthy eating plan, you'll consume about 55 to 65% of your calories from carbohydrates
Learn about the Mediterranean diet, including its role in preventing cardiovascular disease. Find out how the Mediterranean diet can help protect and improve your health and increase your odds for a long life.
This is the food pyramid which helps to understand what healthy eating is about. Discover the crucial weight loss factors here - http://fitbodybuzz.com/weight-loss-basics-factors/
Presentation about the use of social media in anorexia based on those two studies:
Syed-Abdul S, Fernandez-Luque L, Jian WS, Li YC, Crain S, Hsu MH, Wang YC, Khandregzen D, Chuluunbaatar E, Nguyen PA, Liou DM
Misleading Health-Related Information Promoted Through Video-Based Social Media: Anorexia on YouTube
J Med Internet Res 2013;15(2):e30
DOI: 10.2196/jmir.2237
PMID: 23406655
PMCID: PMC3636813
Yom-Tov E, Fernandez-Luque L, Weber I, Crain SP
Pro-Anorexia and Pro-Recovery Photo Sharing: A Tale of Two Warring Tribes
J Med Internet Res 2012;14(6):e151
DOI: 10.2196/jmir.2239
PMID: 23134671
PMCID: PMC3510717
The Good, the Bad and the Ugly: a portrait of health social media trends and ...Luis Fernandez Luque
The Good, the Bad and the Ugly: a portrait of health social media trends and anti-vaccination.
This presentation was made for the Norwegian Knowledge Centre for the Health Service. Global Health Unit Open Seminar – 6th August 2013
In this presentation, we will introduce how social media is being used in transforming communication with patients. We will use study cases, such as the ‘zombi invasion’ organised by the CDC and online puzzles for biomedical research, to provide an overview of current trends. In addition, we will present research conducted at Norut (Northern Research Institute) about the challenges of finding trustworthy health social media. Our focus will be directed towards harmful online communities promoting anorexia as a lifestyle or anti-vaccination online groups.
Mitochondrial Disease Community Registry: First look at the data, perspectiv...SophiaZilber
Patient-populated registries are an important component of rare disease communities for many
reasons, including their use as a tool for gathering opinions on specific topics. The Mitochondrial
Disease Community Registry (MDCR) was launched in 2014 for this purpose as well as to identify and
characterize mitochondrial disease patients from the patient perspective. Data collected over a four
year period and provided by adult mitochondrial disease patients and caregivers of pediatric
mitochondrial disease patients in response to a single survey are presented. Primary findings include
the importance of clinician-patient communication, need for treatment and cure, impact of the disease
on the entire life of a person, and quality of life as top issues as described by patients. Despite multiple
challenges, patients are hopeful about the future and thankful for the survey. Efforts should be made
to identify ways to better support patients, improve communication, and create more trusting and
healing relationships between patients and doctors. Additionally, data quality checks showed that more
clear and simple questions and shorter more-targeted surveys are needed in order to get accurate
and meaningful data that can be used for analysis and research in the future.
Potential of social media as a tool to combat foodborne illnessMarcella Zanellato
Abstract
The use of social media platforms, such as Facebook and Twitter, has been increasing
substantially in recent years and has affected the way that people access information online.
Social media rely on high levels of interaction and user-generated context shared through
established and evolving social networks. Health information providers must know how to
successfully participate through social media in order to meet the needs of these online
audiences. This article reviews the current research on the use of social media for public health
communication and suggests potential frameworks for developing social media strategies. The
extension to food safety risk communication is explored, considering the potential of social
media as a tool to combat foodborne illness.
Assignment One Health and the media Due 1155pm ET Sunday Week 2 meghanthrelkeld256
Assignment One: Health and the media Due: 11:55pm ET Sunday Week 2 Overview The media plays an important role in providing information for the public. In terms of health, social media, documentaries, and other news sources can provide health education to those without access to health education and information, or supplement the education and information that people have access to. The purpose of this assignment is for us to examine a health focused documentary, identify the agenda of the fimmakers, evaluate the quality of the sources used in the film, and describe the positive and/or negative role that media can play in health education. Instructions Construct a 3-4 page paper that explores each of these three areas: 1.Identifies a documentary focused on a major health issue 2.Summarizes the agenda of the documentary, providing sociological relevance 3.Evaluates the quality and credibility of the sources used in the documentary 4.Describes the role that popular media, and increased access to documentaries can play in educating the public about major health issues. Identify both strengths and challenges.
...
DELIVERABLE OF YOUTUBE PLATFORM AS A COMMERCIAL HEALTH AWARENESS COMMUNICATIO...ijma
YouTube video search is the number one source of views in aggregation, the related video recommendation is the main source of views for most of the videos on YouTube. Health awareness also significant to economic progress, as healthy population live longer and will be increasingly productivity. Positive mental and physical health is a state of well-being in which the individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully and can contribute to his or her community. In addition, our results reveal that there is a strong correlation between the view count of a video and the average view count of its top referrer videos. The aim of this study are to know the impacts of YouTube as a health awareness video to traveler from Malaysia, and also to find out factors of usage of YouTube rather than other medium applications . Besides that, the factors and the impact of usage is influencing the YouTube as a main website popular and the most websites trending in the worldwide. Health awareness is very crucial information that each person needs to know to ensure that they can maintain a better and healthier life. This study conducted out of 68 respondents where is 35 of female and 33 of male. Most of respondents are in range 15 to 45 years old that are users of new media platforms especially YouTube and interact frequently on these platforms. The questionnaire is made up of three major sections which collect data on the respondents’ demographic profile, their exposure to YouTube, and their knowledge about health awareness video. As the result, this study showed that YouTube as a main platform to find any precautions about health awareness video or materials. In the meanwhile, the researcher agrees personally that YouTube is the best place to look for any videos or materials on health awareness precautions. With this study, it is made evident that YouTube's effects as a health awareness film for travelers from Malaysia altered a respondent's willingness to agree with the study's objectives
DELIVERABLE OF YOUTUBE PLATFORM AS A COMMERCIAL HEALTH AWARENESS COMMUNICATIO...ijma
YouTube video search is the number one source of views in aggregation, the related video recommendation
is the main source of views for most of the videos on YouTube. Health awareness also significant to
economic progress, as healthy population live longer and will be increasingly productivity. Positive mental
and physical health is a state of well-being in which the individual realizes his or her own abilities, can
cope with the normal stresses of life, can work productively and fruitfully and can contribute to his or her
community. In addition, our results reveal that there is a strong correlation between the view count of a
video and the average view count of its top referrer videos. The aim of this study are to know the impacts
of YouTube as a health awareness video to traveler from Malaysia, and also to find out factors of usage of
YouTube rather than other medium applications . Besides that, the factors and the impact of usage is
influencing the YouTube as a main website popular and the most websites trending in the worldwide.
Health awareness is very crucial information that each person needs to know to ensure that they can
maintain a better and healthier life. This study conducted out of 68 respondents where is 35 of female and
33 of male. Most of respondents are in range 15 to 45 years old that are users of new media platforms
especially YouTube and interact frequently on these platforms. The questionnaire is made up of three
major sections which collect data on the respondents’ demographic profile, their exposure to YouTube, and
their knowledge about health awareness video. As the result, this study showed that YouTube as a main
platform to find any precautions about health awareness video or materials. In the meanwhile, the
researcher agrees personally that YouTube is the best place to look for any videos or materials on health
awareness precautions. With this study, it is made evident that YouTube's effects as a health awareness film
for travelers from Malaysia altered a respondent's willingness to agree with the study's objectives
In this presentation, I review how social media and eHealth, in general, can be used to communicate around vaccination. This was part of an expert meeting organized by #Vaccines4Life in Berlin in Jan 2019
Talk I gave at the College of Medical Science and Technology - Taipei Medical University. The topic was about the use of technology for participatory and open health.
Sleep, Eat & Play: The Role of Mobile & Wearable Technologies for Health Empo...Luis Fernandez Luque
New technologies such as mobile and wearables play a major role in the control of the epidemic of unhealthy lifestyles and chronic conditions in Qatar and beyond. This slides provide an overview of current trends and experiences in Qatar.
The Science of Sweet Dreams: Predicting Sleep Efficiency from Wearable Devic...Luis Fernandez Luque
Lack of sleep can erode mental and physical well-being, often exacerbating health problems such as obesity. Wearable devices that capture and analyze sleep quality through predictive methodologies can help patients and medical practitioners make behavioral health decisions that can lead to better sleep and improved health.
http://doi.ieeecomputersociety.org/10.1109/MC.2017.91
HealthRecSys: A semantic content-based recommender system to complement healt...Luis Fernandez Luque
This study investigates the feasibility of building a content-based recommender system that links health consumers to reputable health educational websites from MedlinePlus for a given health video from YouTube.
Our study demonstrates the feasibility of using a semantic content-based recommender system to enrich YouTube health videos. Evaluation with end-users, in addition to healthcare professionals, will be required to identify the acceptance of these recommendations in a information-seeking context.
Sleep quality prediction from wearable data using deep learningLuis Fernandez Luque
Sathyanarayana A, Joty S, Fernandez-Luque L, Ofli F, Srivastava J, Elmagarmid A, Arora T, Taheri S. Sleep Quality Prediction From Wearable Data Using Deep Learning. JMIR Mhealth Uhealth 2016;4(4):e125. http://doi.org/10.2196/mhealth.6562
The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep.
Online Diabetes: Inferring Community Structure in Healthcare Forums. Luis Fernandez Luque
Inferring community structure in healthcare forums. An empirical study by Chomutare T, Arsand E, Fernandez-Luque L, Lauritzen J, Hartvigsen G. Methods Inf Med. 2013;52(2):160-7. https://www.ncbi.nlm.nih.gov/pubmed/23392282
Abstract
BACKGROUND:
Detecting community structures in complex networks is a problem interesting to several domains. In healthcare, discovering communities may enhance the quality of web offerings for people with chronic diseases. Understanding the social dynamics and community attachments is key to predicting and influencing interaction and information flow to the right patients.
OBJECTIVES:
The goal of the study is to empirically assess the extent to which we can infer meaningful community structures from implicit networks of peer interaction in online healthcare forums.
METHODS:
We used datasets from five online diabetes forums to design networks based on peer-interactions. A quality function based on user interaction similarity was used to assess the quality of the discovered communities to complement existing homophily measures.
RESULTS:
Results show that we can infer meaningful communities by observing forum interactions. Closely similar users tended to co-appear in the top communities, suggesting the discovered communities are intuitive. The number of years since diagnosis was a significant factor for cohesiveness in some diabetes communities.
CONCLUSION:
Network analysis is a tool that can be useful in studying implicit networks that form in healthcare forums. Current analysis informs further work on predicting and influencing interaction, information flow and user interests that could be useful for personalizing medical social media.
Keynote delivered at Health 2.0 Europe 2015
Trust and communication are crucial elements for the control of the deadly Ebola outbreak in West Africa. In this presentation Luis will explain how social media and mobile technology has been a major element in the Ebola communication crisis. Diving into the natural "cures" for Ebola have been heavily marketed online, Luis will tackle how digital communication is a crucial part in the ongoing efforts to control the ebola outbreak in West Africa.
This is the trial lecture of my PhD, which will be defended the 24th of October 2014 in the Arctic Univ of Norway (UiT).
In this lecture I will provide an overview of the benefits and challenges of using social media in crisis management. As study case we use the ongoing ebola crisis.
Esta presentación la realicé para el Congreso de Pacientes con Cáncer de Espana en Madrid el 23 Noviembre 2013.
En la presantación repaso las últimas tendencias en salud e internet y sobre los epacientes
Presentación para el taller Diabetes Click organizado por la Escuela Andaluza de Salud Publica. Granada, 16 Noviembre 2013
Lectura recomendada:
Gomez-Galvez P, Suarez Mejias C, Fernandez-Luque L. Social media for empowering people with diabetes: Current status and future trends. Conf Proc IEEE Eng Med Biol Soc. 2015;2015:2135-8. https://www.ncbi.nlm.nih.gov/pubmed/26736711
Presentación sobre Salud Móvil en Diabetes en la conferencia Salud 2.0 Euskadi 2013 (salud20euskadi.org)
Lectura recomendada:
Gomez-Galvez P, Suarez Mejias C, Fernandez-Luque L. Social media for empowering people with diabetes: Current status and future trends. Conf Proc IEEE Eng Med Biol Soc. 2015;2015:2135-8. https://www.ncbi.nlm.nih.gov/pubmed/26736711
Lectura recomendada:
Brox E, Fernandez-Luque L, Tøllefsen T. Healthy Gaming - Video Game Design to promote Health. Appl Clin Inform. 2011 Apr 27;2(2):128-42. https://www.ncbi.nlm.nih.gov/pubmed/23616865
Presentation about the use of YouTube for the education of healthcare professionals. Presented in the 1st International Conference on Medical Education Informatics – MEI 2012
Recommended reading:
Konstantinidis S, Fernandez-Luque L, Bamidis P, Karlsen R. The role of taxonomies in social media and the semantic web for health education. A study of SNOMED CT terms in YouTube health video tags. Methods Inf Med. 2013;52(2):168-79. https://www.ncbi.nlm.nih.gov/pubmed/23450378
Lectura recomendada:
Fernandez-Luque L, Bau T. Health and social media: perfect storm of information. Healthc Inform Res. 2015 Apr;21(2):67-73. https://www.ncbi.nlm.nih.gov/pubmed/25995958
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
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Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
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2 Case Reports of Gastric Ultrasound
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
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Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Basavarajeeyam is a Sreshta Sangraha grantha (Compiled book ), written by Neelkanta kotturu Basavaraja Virachita. It contains 25 Prakaranas, First 24 Chapters related to Rogas& 25th to Rasadravyas.
HealthTrust: A PhD Dissertation on the Retrieval of Trustworthy Health Social Media
1. HealthTrust: A PhD Dissertation on the
Retrieval of Trustworthy Health Social Media
PhD Defence, 24th October 2014
“How can computing techniques
support the retrieval of trustworthy
health social media?“
Luis Fernandez Luque (@luisluque), eHealth
Researcher, Norut Tromsø (Norway)
2. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
2
3. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
3
4. “Do not search: Twin-to-Twin
transfusion syndrome”
Part 1- A personal example 4
7. Results
• Hospitals: out-dated focused on worse case
scenarios
• Research literature: focused on complicated
cases
• Social Media of Patients: obituaries
• Social Media of Hospitals: to the point accurate
information
Part 1- A personal example 7
8. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
8
11. Main open questions
• How to find the “good” content?
• What is “good” content?
• Why sometimes “Google” is failing?
• Is it just content? Is it content-based
communities?
• How is bad content disseminated or filtered? And
good content?
Part 2 - Introduction 11
12. Research Gaps
• Lack of knowledge about health social media:
motivations, dynamics, harmful content.
• Lack of information about technical solutions
for finding health social media: new
techniques were emerging for retrieving social
media, but none specialized in the health context
• Lack of trust-based approaches for retrieving
health social media: previous online information
retrieval tools focused on metadata and not
leverage in trust from online health communities.
Part 2 - Introduction 12
13. Research Questions
How can computing techniques support the retrieval of trustworthy
health social media?
•RQ1) What are the characteristics of health social videos?
•RQ2) Are there technical solutions for modelling health social media?
•RQ3) How can Social Network Analysis be used to extract information
about the characteristics of health social media?
•RQ4) Can trust-based metrics improve the retrieval of social videos
about diabetes?
Part 2 - Introduction 13
16. Papers I
RQ1.Paper 1: Gómez-Zúñiga B, Fernandez-Luque L, Pousada M, Hernández-Encuentra
E, Armayones M. ePatients on YouTube: Analysis of Four Experiences From the Patients'
Perspective. Med 2.0 2012;1(1):e1
RQ1.Paper 2: Fernandez-Luque L, Elahi N, Grajales FJ 3rd. An analysis of personal
medical information disclosed in YouTube videos created by patients with multiple
sclerosis. Stud Health Technol Inform. 2009;150:292-6.
RQ1.Paper 3: S Konstantinidis, L Fernandez-Luque, P Bamidis, R Karlsen. The Role of
Taxonomies in Social Media and the Semantic Web for Health Education. Methods Inf
Med 2013; 52
RQ1.Paper 4: E Gabarron, L Fernandez-Luque, M Armayones, A YS
Lau. Identifying measures used for assessing quality of YouTube videos with patient
health information: A Review of Current Literature. Interact J Med Res 2013;2(1):
RQ1.Paper 5: Syed-Abdul S, Fernandez-Luque L, Jian WS, Li YC, Crain S, Hsu MH,
Wang YC, Khandregzen D, Chuluunbaatar E, Nguyen PA, Liou DM. Misleading health-related
information promoted through video-based social media: anorexia on YouTube. J
Med Internet Res. 2013 Feb 13;15(2):e30.
Part 2 - Introduction 16
17. Papers II
RQ2.Paper 1: Fernandez-Luque L, Karlsen R, Bonander J. Review of extracting
information from the Social Web for health personalization. J Med Internet Res. 2011 Jan
28;13(1):e15. doi: 10.2196/jmir.1432.
RQ3.Paper 1: Yom-Tov E, Fernandez-Luque L, Weber I, Crain SP. Pro-anorexia and pro-recovery
photo sharing: a tale of two warring tribes. J Med Internet Res. 2012 Nov
7;14(6):e151. doi: 10.2196/jmir.2239.
RQ3.Paper 2: Chomutare T, Arsand E, Fernandez-Luque L, Lauritzen J, Hartvigsen G.
Inferring community structure in healthcare forums. An empirical study. Methods Inf Med.
2013;52(2):160-7. Epub 2013 Feb 8.
RQ4.Paper 1: Fernandez-Luque L, Karlsen R, Melton GB. HealthTrust: Trust-based
Retrieval of YouTube's Diabetes Channels, 2011, 20th ACM international conference on
Information and knowledge management.
RQ4.Paper 2: Fernandez-Luque L, Karlsen R, Melton GB. HealthTrust: A Social Network
Approach for Retrieving Online Health Videos. J Med Internet Res. 2012 Jan
31;14(1):e22.
Part 2 - Introduction 17
18. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
18
19. RQ1: What are the characteristics of health
social videos?
• RQ1.1: Does the online community influence the
motivation of people with chronic conditions to publish
videos about their health?
• RQ1.2: Do health videos contain relevant medical
vocabulary in their textual metadata?
• RQ1.3: What are the quality features of online health
videos?
• RQ1.4: Do misleading and informative online videos on
the topic of anorexia have different characteristics?
Part 3 - RQ1 Health Videos 19
20. RQ1.Study 1: Characteristics of metadata in
health social videos
L. Fernandez-Luque et al. / An Analysis 294 of Personal Medical Information
REALLY have MS). Overall, 70 comments (22%) contained personal health
information concerning their creators or a third party (e.g., relatives).
The comments with personal health information (PHI) were further stratified. As
Figure 2 denotes, almost half of the comments contained information about
medications (73%, n=51). Comments about symptoms (50%, n=35) and diagnoses
(39%, n=27) were also prevalent. In one case, the information disclosed was the PHI of
a third party:
S Konstantinidis, L Fernandez-Luque, P Bamidis, R Karlsen.
The Role of Taxonomies in Social Media and the Semantic Web
for Health Education. Methods Inf Med 2013; 52
Figure 1. Total number of comments classified into the main categories
Fernandez-Luque L, Elahi N, Grajales FJ 3rd. An analysis
of personal medical information disclosed in YouTube videos
created by patients with multiple sclerosis. Stud Health
Technol Inform. 2009;150:292-6.
I have been watching your videos since my daughter was diagnosed with
MS on 28-12-07. She was diagnosed with an aggressive form of MS.
Betaferon caused liver problems in a very short time. She has now had 4
infusions of tysabri and now feels she is well enough to try and go back
to work. Tysabri only became available in Aust on July 1/08. This drug
has given her hope that she still has a future to look forward to as she is
26 yrs old. Your improvement since your first dose gave us all hope.
Part 3 - RQ1 Health Videos 20
21. RQ1.Study 2: What is quality of health social
videos?
E Gabarron, L Fernandez-Luque, M Armayones, A YS Lau. Identifying measures used for assessing quality of
YouTube videos with patient health information: A Review of Current Literature. Interact J Med Res 2013;2(1):e6
22. RQ1.Study 3: Motivations of patients sharing
videos
...And part of why I started my blog in the first
place was because, even though I’ve lived
with diabetes for such a long time and I didn’t
known (sic) anyone else who had it, and I
literally felt like the only diabetic on the planet.
[KS]
I met so many people from all over the world that I
would never have been able to talk to, before the
Internet of course, and then now, with the MS
community on YouTube it’s incredible. [VB]
Gómez-Zúñiga B, Fernandez-Luque L, Pousada M, Hernández-Encuentra E, Armayones M. ePatients
on YouTube: Analysis of Four Experiences From the Patients' Perspective. Med 2.0 2012;1(1):e1
23. RQ1.Study 4: Study about pro- and
anti- anorexia videos
Syed-Abdul S, Fernandez-Luque L, Jian WS, Li YC, et al. Misleading health-related information promoted
through video-based social media: anorexia on YouTube. J Med Internet Res. 2013 Feb 13;15(2):e30.
24. RQ1.Study 4: Study about pro- and
anti- anorexia videos
Syed-Abdul S, Fernandez-Luque L, Jian WS, Li YC, et al. Misleading health-related information promoted
through video-based social media: anorexia on YouTube. J Med Internet Res. 2013 Feb 13;15(2):e30.
25. RQ1: Characterizing Health Social Media
Key Findings
• Social interaction is one of the main driving forces behind
those publishing videos about their health.
• Textual metadata can be of very heterogeneous quality,
but still contains a lot of relevant health information for
modeling.
• The quality of health videos is a multidimensional
concept. Reliability of the content and its provider are
very important quality criteria according the literature.
Part 3 - RQ1 Health Videos 25
26. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
26
27. Modeling Health Social Media
RQ2: Are there technical solutions
for modeling health social media?
Part 4- RQ2 Modeling Health Social Media 27
28. RQ2.Study 1: Review on techniques for
modeling health social media
Fernandez-Luque L, Karlsen R, Bonander J. Review of extracting information from the Social Web for
health personalization. J Med Internet Res. 2011 Jan 28;13(1):e15. doi: 10.2196/jmir.1432.
29. RQ2: Extracting Information from
Health Social Media
Key Findings
• Most technical solutions for modeling social
media will have shortcomings in the health
domain due to text analysis complexities.
• Questions about privacy issues.
• Link and Social Network Analysis is promising but
has not been studied in detail in the health
domain.
Fernandez-Luque L, Karlsen R, Bonander J. Review of extracting information from the Social Web for
health personalization. J Med Internet Res. 2011 Jan 28;13(1):e15. doi: 10.2196/jmir.1432.
30. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
30
31. RQ3.Study 1: Structure of Pro-anorexia
& pro-recovery groups in Flickr
Yom-Tov E, Fernandez-Luque L, Weber I, Crain SP Pro-Anorexia and Pro-Recovery Photo
Sharing: A Tale of Two Warring Tribes J Med Internet Res 2012;14(6):e151
32. RQ3.Study 1: Structure of Pro-anorexia
& pro-recovery groups in Flickr
Figure 4. Network graphs according to four connection
types (from top left, clockwise): Contacts, Favorites,
Tags, Comments.
Yom-Tov E, Fernandez-Luque L, Weber I, Crain SP Pro-Anorexia and Pro-Recovery Photo
Sharing: A Tale of Two Warring Tribes J Med Internet Res 2012;14(6):e151
33. RQ3.Study 2: Structure of diabetes
communities
Chomutare T, Arsand E, Fernandez-Luque L, Lauritzen J, Hartvigsen G. Inferring community structure in
healthcare forums. An empirical study. Methods Inf Med. 2013;52(2):160-7. Epub 2013 Feb 8.
34. RQ3: Social Network Analysis for
characterizing Health Social Media.
Key Findings
• On a photo-sharing site, the best predictors of users
belonging to the sub-community promoting anorexia are
social network metrics. Tag-based classification was less
accurate.
• Most centric members on online diabetes communities
had longer experience living with the disease.
Part 5 - SNA Health 34
Communities
35. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
35
36. Online search of health diabetes videos
HealthTrust - a trust-based
metric for retrieving diabetes
videos
36
37. Online Search: PageRank & TKC
effect (Tightly Knit Community)
Sergey Brin and Lawrence Page. 1998. The
anatomy of a large-scale hypertextual Web
search engine. Comput. Netw. ISDN Syst.
30, 1-7 (April 1998), 107-117.
DOI=10.1016/S0169-7552(98)00110-X
http://dx.doi.org/10.1016/S0169-
7552(98)00110-X
37
http://en.wikipedia.org/wiki/PageRank
R. Lempel and S. Moran. 2000. The stochastic
approach for link-structure analysis (SALSA)
and the TKC effect. Comput. Netw. 33, 1-6
(June 2000), 387-401. DOI=10.1016/S1389-
1286(00)00034-7
http://dx.doi.org/10.1016/S1389-
1286(00)00034-7
38. RQ4: HealthTrust - a trust-based metric for retrieving
diabetes videos
Fernandez-Luque L, Karlsen R, Melton GB. HealthTrust: A Social Network Approach for
Retrieving Online Health Videos. J Med Internet Res. 2012 Jan 31;14(1):e22.
39. RQ4: HealthTrust - a trust-based metric for retrieving
diabetes videos
YouTube’s API
Videos, Tags,
Users
Fernandez-Luque L, Karlsen R, Melton GB. HealthTrust: A Social Network Approach for
Retrieving Online Health Videos. J Med Internet Res. 2012 Jan 31;14(1):e22.
40. RQ4: HealthTrust - a trust-based metric for retrieving
diabetes videos
Fernandez-Luque L, Karlsen R, Melton GB. HealthTrust: A Social Network Approach for
Retrieving Online Health Videos. J Med Internet Res. 2012 Jan 31;14(1):e22.
41. RQ4: HealthTrust - a trust-based metric
for retrieving diabetes videos
Fernandez-Luque L, Karlsen R, Melton GB. HealthTrust: A Social Network Approach for
Retrieving Online Health Videos. J Med Internet Res. 2012 Jan 31;14(1):e22.
42. RQ4: HealthTrust - a trust-based metric
for retrieving diabetes videos
Key Findings
• In diabetes online communities the most
reputable members are those with more
experience with diabetes.
• The HealthTrust metric based on Social Network
Analysis to infer quality of health videos performs
well for filtering misleading content compared to
YouTube searches.
Fernandez-Luque L, Karlsen R, Melton GB. HealthTrust: A Social Network Approach for
Retrieving Online Health Videos. J Med Internet Res. 2012 Jan 31;14(1):e22.
43. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
43
44. Claimed contributions
• C1: increase in the knowledge about health
social videos.
– Published results have been cited more 400 times since 2009.
– Startups and journalists have requested interviews to share my
knowledge. Also keynotes in Taiwan and Norway.
• C2: increased knowledge on the challenges
related to model health social media
– The RQ2.P1 is the first paper that systematically reviews the
challenges of modeling health social media. It has been cited 25
times since 2011.
Part 7 - Discussion 44
45. Claimed contributions
• C3: social network analysis of online health
communities
– Research in this PhD has increased the understanding
of the social dynamics in health related communities
(e.g. anorexia, diabetes).
• C4: social network analysis of health social
media to infer quality
– The algorithm HealthTrust is the first one focused on the use of
social network analysis to retrieve trustworthy health videos for
patients.
– The algorithm has been designed, tested and evaluated.
Part 7 - Discussion 45
46. Discussion & Limitations
• Social network features of health communities can provide
clues regarding quality and trustworthiness of content.
• Each platform and disease is different. Evaluation was
online done in Diabetes in a offline experiment. Can we
generalize HealthTrust?
• Social media is becoming more heterogeneous (Twitter,
YouTube, etc.), but HealthTrust has been tested only with
one type of content (i.e. videos).
Part 7 - Discussion 46
47. Agenda
1 2 Modelling Health
3 4 Why? A personal
example
Social Media
Health Social
Media & Online
Introduction &
Overview
Videos
7 8 Social Network
Analysis of Health
Communities
6 Discussion Future work
5 HealthTrust and
Information
Retrieval
47
48. Future Work
• Creation of a portal (spin-off) to access many
users for better experimentation and evaluation.
• To expand our knowledge about why misleading
and harmful content is highly visible and ranked.
– Better strategies for disseminating good health social
media.
– Better information retrieval tools to help finding
content.
• Study case: the visibility of the online anti-vaccination
movement might be already killing
children.
Part 8 – Future work 48
Searching was not a easy task: problems with research literature, webs from hospitals, and also social media (specially patients).
After 1 whole (and very tense) afternoon I found one video explaining everything (I wanted to know) in 3 minutes
By the time this PhD started Health Social Media was ”new” in the health domain. Today it is an overwhelimgn reality
Not everything is good, but most important to find the good is very hard
1) There is a huge amount of health content in social media channels. Thousands of videos from hospitals, health authorities, patients, etc. Sadly, that content is not always on top when searching-
During the first week of December 2008 we searched for YouTube users who had published at least three videos in English about living with multiple sclerosis. In total we found 27 of such users. Using a crawler I developed we extracted a total of 769 videos, 7,047 comments generated by 2,426 users. Using a random method we selected 25 of those videos with their 557 comments. Comments that were not in English or posted in non health-related videos were excluded. A final set of 320 comments were analyzed and classified as follows:
Personal health information: comments containing personal health experiences such as diagnosis, symptoms, etc.
Video discussion: comments with discussions about the videos (e.g. adding information about the videos).
Appreciation: appreciations from the commenters towards the video author.
Criticism: complains about the quality of the video or any other aspect.
Unrelated: comments that are not covered in any of the other categories (e.g. comments about the haircut style)
YOUTUBE MS: 27 of MS ePatients with 769 videos7,047 comments generated by 2,426 users. Random selection of 25 videos we analyzed 320 comments.
YOUTUBE TAG: 4,307 videos (64,367 tags) from 500 US Hospital channels..BioPortal REST services were used within our portal to match SNOMED CT terms. The average percentage of YouTube tags that were expressed using SNOMED CT terms was about 22.5%
RESULTS: 456 abstracts were extracted and 13 papers. (1) quality of content in 10/13 (77%), (2) view count in 9/13 (69%), (3) health professional opinion in 8/13 (62%), (4) adequate length or duration in 6/13 (46%), (5) public ratings in 5/13 (39%), (6) adequate title, tags, and description in 5/13 (39%), (7) good description or a comprehensive narrative in 4/13 (31%), (8) evidence-based practices included in video in 4/13 (31%), (9) suitability as a teaching tool in 4/13 (31%), (10) technical quality in 4/13 (31%), (11) credentials provided in video in 4/13 (31%), (12) enough amount of content to identify its objective in 3/13 (23%), and (13) viewership share in 2/13 (15%).
In this qualitative study, we performed an analysis of the videos created by 4 patients about their self-reported motivations and challenges they face as YouTube users. First, two judges compared the transcriptions and decided the exact wording when confusing content was found. Second, two judges categorized the content of the videos to identify the major themes.
RESULTS: four main categories emerged: (1) the origin or cause for making the first video, (2) the objectives that they achieve by continuing to make videos, (3) the perception of community, and (4) the negative consequences of the experience.
Three doctors reviewed 140 videos with approximately 11 hours of video content, classifying them as informative, pro-anorexia, or others. Statistical analisys of the top 40 most viewed in each category
The interrater agreement of classification was moderate (Fleiss' kappa=0.5), with 29.3% (n=41) being rated as pro-anorexia, 55.7% (n=78) as informative, and 15.0% (n=21) as others. Pro-anorexia videos were favored 3 times more than informative videos (odds ratio [OR] 3.3, 95% CI 3.3-3.4, P<.001).
Three doctors reviewed 140 videos with approximately 11 hours of video content, classifying them as informative, pro-anorexia, or others. Statistical analisys of the top 40 most viewed in each category
The interrater agreement of classification was moderate (Fleiss' kappa=0.5), with 29.3% (n=41) being rated as pro-anorexia, 55.7% (n=78) as informative, and 15.0% (n=21) as others. Pro-anorexia videos were favored 3 times more than informative videos (odds ratio [OR] 3.3, 95% CI 3.3-3.4, P<.001).
1) There is a huge amount of health content in social media channels. Thousands of videos from hospitals, health authorities, patients, etc. Sadly, that content is not always on top when searching-
identify relevant research literature that addressed the following aspects of health personalization in the Social Web: (1) studies about the disclosure of health information in the Social Web, (2) techniques to extract that information, and (3) examples of applications. Major scientific databases in computer science (eg, ACM Digital Library) and biomedicine (eg, PubMed) were searched. In addition, we searched through the references of the selected papers, contributions to conferences, and nonresearch literature (eg, websites, books, technical reports). The background section provides an overview of the different research areas where the search was performed.
The multidisciplinary team of authors performed the selection and analysis of the relevant articles. Their backgrounds cover the different domains of the review (eg, information retrieval, computer science, health informatics, and public health). The different studies were analyzed to understand the implications for health personalization, including technical and socioethical aspects.
Methods: The extraction of pro-anorexia and pro-recovery photographs Flickr pertaining to 242,710 photos from 491 users
The ROC using the comments or contacts was 0.74, whereas the area using favorites was 0.53 and 0.52 using the tags network
The forums have a total in excess of 140,000 registered users and over 1.6 million posts. Years of diagnosis was only available in 3 forums. We used datasets from five online diabetes forum. We use two well-known community detection algorithms that deal very well with large datasets; Greedy Optimization(GO) [27] and the Affinity Propagation(AP) [28] algorithms. GO is based on the Girvan-Newman algorithm; hierarchical agglomeration. We developed a web data extraction program in Python to crawl five diabetes forums on the Internet, comprising Spanish and English forums, and two of them were dedicated to juvenile diabetes.
Results: Results show that we can infer meaningful communities by observing forum interactions. Closely similar users tended to co-appear in the top communities, suggesting the discovered communities are intuitive. The number of years since diagnosis was a significant factor for cohesiveness in some diabetes communities. The figure illustrates the dominant star topology, and shows how the central nodes in the network have at least two years’ experience with diabetes. (78%) of the users who provided the data have been diagnosed less than two years ago (green). (78%) of the users who provided the data have been diagnosed less than two years ago (green)
Objectives: To explore approaches for extracting metrics about authoritativeness in online health communities and how these
metrics positively correlate with the quality of the content.
Methods: We designed a metric, called HealthTrust, that estimates the trustworthiness of social media content (eg, blog posts
or videos) in a health community. The HealthTrust metric calculates reputation in an online health community based on link
analysis. We used the metric to retrieve YouTube videos and channels about diabetes. In two different experiments, health
consumers provided 427 ratings of 17 videos and professionals gave 162 ratings of 23 videos. In addition, two professionals
reviewed 30 diabetes channels.
In two different experiments, health consumers provided 427 ratings of 17 videos and professionals gave 162 ratings of 23 videos. In addition, two professionals reviewed 30 diabetes channels.
Of 20 potential channels, HealthTrust’s filtering allowed only 3 bad channels (15%) versus 8 (40%) on the
YouTube list.
When comparing video ratings from our reviewers, we found that HealthTrust achieved a positive and statistically significant correlation with professionals (Pearson r10= .65, P = .02) and a trend toward significance with health consumers (r7 = .65, P = .06) with videos on hemoglobinA1c, but it did not perform as well with diabetic foot videos.
Conclusions: The trust-based metric HealthTrust showed promising results when used to retrieve diabetes content from YouTube.
Our research indicates that social network analysis may be used to identify trustworthy social media in health communities.