The Role of Social Media in Promoting Women's Health Education in Saudi Arabia.
01 Jan 2015-Studies in health technology and informatics (Stud Health Technol Inform)-Vol. 213, pp 259-262
TL;DR: Analysis of Tweet feeds of Saudi-based Twitter account showed that a majority of the Twitter followers were seeking gynecological information, followed by pregnancy related information, breast-feeding advice, and other health related information and an increased level of health awareness and comprehension among Twitter followers.
Abstract: Social media has the potential to improve women's health in developing countries through health education and promotion. In the Arab world, women's health interventions are lacking. However, with a high penetration rate of social media in the Arab world, there is good opportunity to utilize social media platforms such as Twitter to promote women's health. In this paper, we analyze the Tweet feeds of Saudi-based Twitter account to promote women's health. A total of 5167 Tweets were extracted and analyzed retrospectively, using NVivo Ncapture between June 2014 and March 2015. There were a total number of 3449 followers by March 20, 2015. Results showed that a majority of the Twitter followers (61%, n=2104) were seeking gynecological information, followed by pregnancy related information (27%, n=931), breast-feeding advice (9%, n=310), and other health related information (3%, n=103). Results also showed an increased level of health awareness and comprehension among Twitter followers. Further research is needed to promote women's health in Saudi Arabia and the Arab world through social media platforms such as Twitter and similar platforms including Instagram, Facebook, and YouTube which are also popular in the Arab world.
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TL;DR: The demographic characteristics of patients that may demonstrate their attitudes toward medical information shared on social media networks are described and how information found through social media affects the way people deal with their health is addressed.
Abstract: Background: Major social networking platforms, such as Facebook, WhatsApp, and Twitter, have become popular means through which people share health-related information, irrespective of whether messages disseminated through these channels are authentic. Objective: This study aims to describe the demographic characteristics of patients that may demonstrate their attitudes toward medical information shared on social media networks. Second, we address how information found through social media affects the way people deal with their health. Third, we examine whether patients initiate or alter/discontinue their medications based on information derived from social media. Methods: We conducted a cross-sectional survey between April and June 2015 on patients attending outpatient clinics at King Abdulaziz University, Jeddah, Saudi Arabia. Patients who used social media (Facebook, WhatsApp, and Twitter) were included. We designed a questionnaire with closed-ended and multiple-choice questions to assess the type of social media platforms patients used and whether information received on these platforms influenced their health care decisions. We used chi-square test to establish the relationship between categorical variables. Results: Of the 442 patients who filled in the questionnaires, 401 used Facebook, WhatsApp, or Twitter. The majority of respondents (89.8%, 397/442) used WhatsApp, followed by Facebook (58.6%, 259/442) and Twitter (42.3%, 187/442). In most cases, respondents received health-related messages from WhatsApp and approximately 42.6% (171/401) reported ever stopping treatment as advised on a social media platform. A significantly higher proportion of patients without heart disease (P=.001) and obese persons (P=.01) checked the authenticity of information received on social media. Social media messages influenced decision making among patients without heart disease (P=.04). Respondents without heart disease (P=.001) and obese persons (P=.01) were more likely to discuss health-related information received on social media channels with a health care professional. A significant proportion of WhatsApp users reported that health-related information received on this platform influenced decisions regarding their family’s health care (P=.001). Respondents’ decisions regarding family health care were more likely to be influenced when they used two or all three types of platforms (P=.003). Conclusions: Health education in the digital era needs to be accurate, evidence-based, and regulated. As technologies continue to evolve, we must be equipped to face the challenges it brings with it.
51 citations
Cites background from "The Role of Social Media in Promoti..."
...Another study that investigated the effect of Twitter on women’s health education demonstrated that women in Saudi Arabia were interested in discussing gynecological complains and breastfeeding-related issues on Twitter [9]....
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TL;DR: There is a significant and growing activity in the Twitter discussion on urologic oncology, particularly on #prostatecancer, and merits attention of stakeholders in health care as a promising communication tool.
Abstract: Objectives To analyse the activity, content, contributors, and influencers of the Twitter discussion on urologic oncology. Materials and methods We performed a comprehensive quantitative and qualitative Twitter analysis for the hashtags #prostatecancer, #bladdercancer, #kidneycancer, and #testicularcancer. Symplur was used to analyse activity over different time periods and the top influencers of the Twitter discussion. Tweet Archivist and Twitonomy analysis tools were used to assess characteristics of content and contributors. Results Twitter discussion on urologic oncology in 2014 contained 100,987 tweets created by 39,326 participants. Mean monthly tweet activity was 6,603±2,183 for #prostatecancer, 866±923 for #testicularcancer, 457±477 for #bladdercancer and 401±504 for #kidneycancer. Twitter activity increased by 41% in 2013 and by 122% in 2014. The content analysis detected awareness, cancer, and risk as frequently mentioned words in urologic oncology tweets. Prevalently used related hashtags were the general hashtag #cancer, awareness hashtags, and the respective cancer/urology tag ontology hashtags. Contributors originated from 41 countries on 6 continents and had a mean of 5,864±4,747 followers. They tweeted from platforms on exclusively mobile devices (39%) more frequently than from desktop devices (29%). Health care organizations accounted for 58% of the top influencers in all cancers. The largest proportion of physicians were among the #prostatecancer and #kidneycancer (each 9%) influencers and individual contributors were most frequent in the discussion on #kidneycancer (57%) and #testicularcancer (50%). Conclusion There is a significant and growing activity in the Twitter discussion on urologic oncology, particularly on #prostatecancer. The Twitter discussion is global, social, and mobile, and merits attention of stakeholders in health care as a promising communication tool.
47 citations
Cites background from "The Role of Social Media in Promoti..."
...Awareness campaigns on Twitter have been reported for women's health [24] and breast cancer [23] before and urologists should make use of Twitter to better promote men's health awareness campaigns such as the most popular Movember campaign [25]....
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TL;DR: This article will focus on the initiation and progress of one such Twitter hematology/oncology community, #mpnsm, which was originally created for the purpose of serving as a venue for improving the interaction among patients, providers, researchers, and organizations with interest in the myeloproliferative neoplasms.
Abstract: The advent of social media has led to the ability for individuals all over the world to communicate with each other, in real time, about mutual topics of interest in an unprecedented manner. Recently, the use of social media has increased among people interested in healthcare and medical research, particularly in the field of hematology and oncology, a field which frequently experiences rapid shifts of information and novel, practice-changing discoveries. Among the many social media platforms available to cancer patients and providers, one platform in particular, Twitter, has become the focus for the creation of disease-specific communities, especially for those interested in, affected by, or those who perform research in the fields of rare cancers, which historically have had a dearth of reliable information available. This article will focus on the initiation and progress of one such Twitter hematology/oncology community, #mpnsm, which was originally created for the purpose of serving as a venue for improving the interaction among patients, providers, researchers, and organizations with interest in the myeloproliferative neoplasms (MPNs) and to further the availability of reliable up-to-date analysis; relevant expert commentary; and readily usable information for patients, providers, and other groups interested in this field.
23 citations
Cites background from "The Role of Social Media in Promoti..."
...Social media gives individuals the opportunity to reach and engage large audiences and has the potential to provide access to high-quality, expert-based information in a cost-effective manner, which is a very important aspect especially for resource-constrained areas of the world [34]....
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TL;DR: Most adolescents preferred using SM to receive OHI, and this was associated with previous OHI seeking practices and convenience of using SM, which has implications for designing SM-based health education campaigns targeting adolescents.
Abstract: Objectives: To assess (1) adolescents’ preference to use social media (SM) to receive oral health information (OHI) and (2) factors associated with this preference.Materials and methods: A cross-se...
18 citations
TL;DR: The major outcomes of this work are development of labeled dataset of Arabic tweets, an intelligent behavior analysis of tweets using six machine learning algorithms to detect suspicious messages, a comparative analysis of six machineLearning algorithms, and a development of a statistical benchmark that can be used for future studies about the detection of crimes on social media.
Abstract: With the widespread use of messaging via social networks such as Twitter, Instagram, and Facebook, it is becoming imperative for researchers to devise intelligent systems for data analytics in the range of domains like business, health, communication, security, etc. The complex morphological and syntactic structure of Arabic sentences makes them difficult to analyze. This paper presents an intelligent system to analyze Arabic tweets for detecting suspicious messages. We acquired Arabic tweet data from micro-blogging social network Twitter via Twitter Streaming Application Programming Interface and save it in a required file format. The system tokenizes and preprocesses the tweet dataset. Manual labeling is performed on tweet dataset for suspicious (label 1) and not-suspicious (label 0) classes. The labeled tweet dataset is used to train a classifier using supervised machine learning algorithms for the detection of suspicious activities. During the testing phase, the system processes unlabeled tweet data and detects either it belongs to a suspicious or not-suspicious class. We tested the system using six supervised machine learning algorithms: (1) decision tree, (2) k-nearest neighbors, (3) linear discriminant algorithm, (4) support vector machine, (5) artificial neural networks, and (6) long short-term memory networks. A comparative analysis in terms of accuracy, execution time, and confusion matrices of the six classifiers is presented. The execution speed of ANN is lowest. In terms of predicting correct results, the SVM performs best among all the classifiers and yields 86.72% mean accuracy. The major outcomes of this work are development of labeled dataset of Arabic tweets, an intelligent behavior analysis of tweets using six machine learning algorithms to detect suspicious messages, a comparative analysis of six machine learning algorithms, and a development of a statistical benchmark that can be used for future studies about the detection of crimes on social media.
18 citations