When Public Health Research Meets Social Media: Knowledge Mapping From 2000 to 2018

Peer-to-peer sharing in public health interventions: strategies when people share health-related personal information on social media

PURPOSE

As sharing on social media has become an integrated part of everyday life, health and public health actors have started to show interest in the potential of people's peer-to-peer sharing of health-related personal information (HRI) for health interventions. In this article we focus on how people make sense of sharing HRI on social media.

METHODS

Twenty-two people between the ages 40 and 60 who had taken part in a regional health intervention were interviewed. Using theories about social media sharing, we explore their understandings and negotiations about whether, how much, and how to share HRI and discuss the results in relation to peer-to-peer sharing as a strategy in interventions.

RESULTS

We identified three aspects that were perceived as particularly risky: loss of control, effects on identity, and affecting others negatively, along with strategies that were used to manage risks in practice: avoiding sharing, allocating, and embedding HRI.

CONCLUSIONS

By allocating and embedding HRI, people can unlock motivating affordances for health work. However, strategies to manage risks can also be counterproductive. For actors to provide equality in health promotion, initiatives that include social media sharing need to be mindful of the sometimes counterproductive effects this may have on people's engagement.

The use of sentiment and emotion analysis and data science to assess the language of nutrition-, food- and cooking-related content on social media: a systematic scoping review

Social media data are rapidly evolving and accessible, which presents opportunities for research. Data science techniques, such as sentiment or emotion analysis which analyse textual emotion, provide an opportunity to gather insight from social media. This paper describes a systematic scoping review of interdisciplinary evidence to explore how sentiment or emotion analysis methods alongside other data science methods have been used to examine nutrition, food and cooking social media content. A PRISMA search strategy was used to search nine electronic databases in November 2020 and January 2022. Of 7325 studies identified, thirty-six studies were selected from seventeen countries, and content was analysed thematically and summarised in an evidence table. Studies were published between 2014 and 2022 and used data from seven different social media platforms (Twitter, YouTube, Instagram, Reddit, Pinterest, Sina Weibo and mixed platforms). Five themes of research were identified: dietary patterns, cooking and recipes, diet and health, public health and nutrition and food in general. Papers developed a sentiment or emotion analysis tool or used available open-source tools. Accuracy to predict sentiment ranged from 33·33% (open-source engine) to 98·53% (engine developed for the study). The average proportion of sentiment was 38·8% positive, 46·6% neutral and 28·0% negative. Additional data science techniques used included topic modelling and network analysis. Future research requires optimising data extraction processes from social media platforms, the use of interdisciplinary teams to develop suitable and accurate methods for the subject and the use of complementary methods to gather deeper insights into these complex data.

What methods are used to examine representation of mental ill-health on social media? A systematic review

There has been an increasing number of papers which explore the representation of mental health on social media using various social media platforms and methodologies. It is timely to review methodologies employed in this growing body of research in order to understand their strengths and weaknesses. This systematic literature review provides a comprehensive overview and evaluation of the methods used to investigate the representation of mental ill-health on social media, shedding light on the current state of this field. Seven databases were searched with keywords related to social media, mental health, and aspects of representation (e.g., trivialisation or stigma). Of the 36 studies which met inclusion criteria, the most frequently selected social media platforms for data collection were Twitter (n = 22, 61.1%), Sina Weibo (n = 5, 13.9%) and YouTube (n = 4, 11.1%). The vast majority of studies analysed social media data using manual content analysis (n = 24, 66.7%), with limited studies employing more contemporary data analysis techniques, such as machine learning (n = 5, 13.9%). Few studies analysed visual data (n = 7, 19.4%). To enable a more complete understanding of mental ill-health representation on social media, further research is needed focussing on popular and influential image and video-based platforms, moving beyond text-based data like Twitter. Future research in this field should also employ a combination of both manual and computer-assisted approaches for analysis.

More than a hundred thousand respondents within 48 h: How the power of social media helped to understand pregnancy loss in Poland - A retrospective population-based cohort study

BACKGROUND

Miscarriage is defined as the loss of pregnancy before 20-24 weeks of gestation, and it is the most common complication of early pregnancy. The aim of the study was to determine the prevalence and risk factors of spontaneous abortion in the population of Polish females to provide a reference for clinical work.

METHODS

A cross-sectional self-administered on-line survey was distributed between 4th and 5th of October 2019 in the social media across Poland. A total of 100,026 recipients responded to the questionnaire and 93,636 valid respondents were included in the analyses.

RESULTS

Among respondents who had ever been pregnant, 31.2% reported at least one spontaneous abortion. The prevalence of miscarriage varied based on age, parity, place of residence and the education level. The first symptom of miscarriage was a vaginal bleeding (56.2%) and abdominal cramps (25.8%), while 43% of respondents had no symptoms and found out during doctor's visit. No medical assistance was required after complete spontaneous abortion in 39.2% of cases.

CONCLUSIONS

Miscarriage is a common complication of pregnancy, but it is not yet fully understood. The goal of future medicine is to minimize the medicalization of spontaneous abortion and excessive medical intervention by raising awareness about natural miscarriage route.

International multidisciplinary survey on the initial management of acute pancreatitis: Perspective of point-of-care specialists focused on daily practice

BACKGROUND

The initial management of patients with acute pancreatitis impacts both morbidity and mortality. Point-of-care decisions have been reported to differ from clinical guideline recommendations.

METHODS

An online anonymous questionnaire was distributed through scientific associations and social media using REDCap. Multivariable logistic regression was used to identify the characteristics of participants associated with compliance with the recommendations.

RESULTS

A total of 1054 participants from 94 countries completed the questionnaire; median age (IQR) was 39 (32-47) years; 30.7% were women. Among the participants, 37% opted for nonmoderate flow of i.v. fluid, 31% for fluid type other than Ringer's lactate; 73.4% were in favor of nil per os to patients who could eat, 75.5% for other than enteral feeding to patients with oral intolerance; 15.5% used prophylactic antibiotic in patients with severe acute pancreatitis, 34.1% in necrotizing acute pancreatitis, and 27.4% in patients with systemic inflammatory response syndrome; 27.8% delayed cholecystectomy after biliary acute pancreatitis. Participants with publications in PubMed on acute pancreatitis showed better compliance (OR, 1.62; 95% CI: 1.15-2.32; P = .007) with recommendations of the clinical guidelines.

CONCLUSIONS

Feeding and nutrition require the greatest improvement efforts, but also the use of prophylactic antibiotics and timing of cholecystectomy should be improved.

Examination of the Public's Reaction on Twitter to the Over-Turning of Roe v Wade and Abortion Bans

The overturning of Roe v Wade reinvigorated the national debate on abortion. We used Twitter data to examine temporal, geographical and sentiment patterns in the public's reaction. Using the Twitter API for Academic Research, a random sample of publicly available tweets was collected from 1 May-15 July in 2021 and 2022. Tweets were filtered based on keywords relating to Roe v Wade and abortion (227,161 tweets in 2021 and 504,803 tweets in 2022). These tweets were tagged for sentiment, tracked by state, and indexed over time. Time plots reveal low levels of conversations on these topics until the leaked Supreme Court opinion in early May 2022. Unlike pro-choice tweets which declined, pro-life conversations continued with renewed interest throughout May and increased again following the official overturning of Roe v Wade. Conversations were less prevalent in some these states had abortion trigger laws (Wyoming, North Dakota, South Dakota, Texas, Louisiana, and Mississippi). Collapsing across topic categories, 2022 tweets were more negative and less neutral and positive compared to 2021 tweets. In network analysis, tweets mentioning woman/women, supreme court, and abortion spread faster and reached to more Twitter users than those mentioning Roe Wade and Scotus. Twitter data can provide real-time insights into the experiences and perceptions of people across the United States, which can be used to inform healthcare policies and decision-making.

Detecting the research structure and topic trends of social media using static and dynamic probabilistic topic models

Purpose

A huge volume of published research articles is available on social media which evolves because of the rapid scientific advances and this paper aims to investigate the research structure of social media.

Design/methodology/approach

This study employs an integrated topic modeling and text mining-based approach on 30381 Scopus index titles, abstracts, and keywords published between 2006 and 2021. It combines analytical analysis of top-cited reviews with topic modeling as means of semantic validation. The output sequences of the dynamic model are further analyzed using the statistical techniques that facilitate the extraction of topic clusters, communities, and potential inter-topic research directions.

Findings

This paper brings into vision the research structure of social media in terms of topics, temporal topic evolutions, topic trends, emerging, fading, and consistent topics of this domain. It also traces various shifts in topic themes. The hot research topics are the application of the machine or deep learning towards social media in general, alcohol consumption in different regions and its impact, Social engagement and media platforms. Moreover, the consistent topics in both models include food management in disaster, health study of diverse age groups, and emerging topics include drug violence, analysis of social media news for misinformation, and problems of Internet addiction.

Originality/value

This study extends the existing topic modeling-based studies that analyze the social media literature from a specific disciplinary viewpoint. It focuses on semantic validations of topic-modeling output and correlations among the topics and also provides a two-stage cluster analysis of the topics.

Spontaneously generated online patient experience data - how and why is it being used in health research: an umbrella scoping review

PURPOSE

Social media has led to fundamental changes in the way that people look for and share health related information. There is increasing interest in using this spontaneously generated patient experience data as a data source for health research. The aim was to summarise the state of the art regarding how and why SGOPE data has been used in health research. We determined the sites and platforms used as data sources, the purposes of the studies, the tools and methods being used, and any identified research gaps.

METHODS

A scoping umbrella review was conducted looking at review papers from 2015 to Jan 2021 that studied the use of SGOPE data for health research. Using keyword searches we identified 1759 papers from which we included 58 relevant studies in our review.

RESULTS

Data was used from many individual general or health specific platforms, although Twitter was the most widely used data source. The most frequent purposes were surveillance based, tracking infectious disease, adverse event identification and mental health triaging. Despite the developments in machine learning the reviews included lots of small qualitative studies. Most NLP used supervised methods for sentiment analysis and classification. Very early days, methods need development. Methods not being explained. Disciplinary differences - accuracy tweaks vs application. There is little evidence of any work that either compares the results in both methods on the same data set or brings the ideas together.

CONCLUSION

Tools, methods, and techniques are still at an early stage of development, but strong consensus exists that this data source will become very important to patient centred health research.

Online reach and engagement of a child nutrition peer-education program (PICNIC): insights from social media and web analytics

BACKGROUND

Parents frequently seek parental advice online and on social media; thus, these channels should be better utilized in child health interventions. The Parents in Child Nutrition Informing Community (PICNIC) program aims to facilitate peer-to-peer sharing of evidence-based child feeding information and support parents within their social networks. The present study aimed to explore web and social media analytics to evaluate reach and user engagement with the PICNIC online components.

METHODS

Online user activity data from the PICNIC Facebook closed group and public Page were collected through Facebook Insights, and program-specific website traffic data through Google Analytics. Analytics data from Nov-2019 to April-2021 was evaluated through visualisation and summary statistics to obtain insights into program growth and current reach in Australia, compare demographics of audience reached through the online channels, and explore parents' use and engagement in PICNIC content.

RESULTS

Results showed steady program growth in the 18 months of recruitment; participant numbers grew from 102 to 261 peer educators while the Facebook Page audience increased threefold, totalling 1615 followers. Intervention posts shared on Facebook (4-5 posts/week) typically reached only a portion of PICNIC Page followers each week, but also reached a wider audience through their friends. Throughout the evaluated period, Facebook users actively engaged in PICNIC posts, although the level of engagement varied considerably from post to post. Furthermore, results from this study suggest the strategy of directing potentially interested parents from social media to the website for program sign-up was successful. Finally, the explored data gave insights into users' availability, demographics and engagement, which will be used to inform refinement of the PICNIC website and social media strategies.

CONCLUSIONS

Our findings confirm the benefits of using a peer education approach and existing social network channels to disseminate evidence-based child feeding information to parents. This study also demonstrates the usefulness of web and social media analytics to be used as part of a continuous evaluation for gaining insight to inform further development and improvement of program strategies.

TRIAL REGISTRATION

The PICNIC project was retrospectively submitted for registration with the Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN12622000230752 (09/02/2022).

Global Scientific Research Landscape on Medical Informatics From 2011 to 2020: Bibliometric Analysis

Background

With the emerging information and communication technology, the field of medical informatics has dramatically evolved in health care and medicine. Thus, it is crucial to explore the global scientific research landscape on medical informatics.

Objective

This study aims to present a visual form to clarify the overall scientific research trends of medical informatics in the past decade.

Methods

A bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection (WoSCC) database was performed to analyze global scientific research trends on medical informatics, including publication year, journals, authors, institutions, countries/regions, references, and keywords, from January 1, 2011, to December 31, 2020.

Results

The data set recorded 34,742 articles related to medical informatics from WoSCC between 2011 and 2020. The annual global publications increased by 193.86% from 1987 in 2011 to 5839 in 2020. Journal of Medical Internet Research (3600 publications and 63,932 citations) was the most productive and most highly cited journal in the field of medical informatics. David W Bates (99 publications), Harvard University (1161 publications), and the United States (12,927 publications) were the most productive author, institution, and country, respectively. The co-occurrence cluster analysis of high-frequency author keywords formed 4 clusters: (1) artificial intelligence in health care and medicine; (2) mobile health; (3) implementation and evaluation of electronic health records; (4) medical informatics technology application in public health. COVID-19, which ranked third in 2020, was the emerging theme of medical informatics.

Conclusions

We summarize the recent advances in medical informatics in the past decade and shed light on their publication trends, influential journals, global collaboration patterns, basic knowledge, research hotspots, and theme evolution through bibliometric analysis and visualization maps. These findings will accurately and quickly grasp the research trends and provide valuable guidance for future medical informatics research.

Impact of the COVID-19 Pandemic on the Dental Preferences of Patients in the Private Sector

Proper oral health care has an impact on the health of the entire body. The COVID-19 pandemic has affected the functioning of the healthcare sector, including dental services. The aim of this study was to analyse the behaviour of patients with regard to their use of dental services during the pandemic. The data were obtained from paper registration forms taken from five dental offices in the city of Cracow between March 2019 and February 2021. During the analysed periods, interest among first-time patients in dental services decreased to 37% (during the month when interest in dental services was at its lowest) compared to the year preceding the COVID-19 pandemic. The number of cancelled visits increased by between 15% and 50% compared to the pre-pandemic period. During the pandemic, appointments made by existing patients increased by up to 84% compared to 2019. The decision by patients to postpone dental treatment not only has adverse effects on their oral and body health, but in turn results in higher health care costs. Given the potential for another pandemic, further long-term research is required to develop and implement special protocols to make the public aware of the safety of health care.

Understanding the Lived Experience of Patients with Melanoma: Real-World Evidence Generated through a European Social Media Listening Analysis (Preprint)

Background

Cutaneous melanoma is an aggressive malignancy that is proposed to account for 90% of skin cancer–related mortality. Individuals with melanoma experience both physical and psychological impacts associated with their diagnosis and treatment. Health-related information is being increasingly accessed and shared by stakeholders on social media platforms.

Objective

This study aimed to assess how individuals living with melanoma across 14 European countries use social media to discuss their needs and provide their perceptions of the disease.

Methods

Social media sources including Twitter, forums, and blogs were searched using predefined search strings of keywords relating to melanoma. Manual and automated relevancy approaches filtered the extracted data for content that provided patient-centric insights. This contextualized data was then mined for insightful concepts around the symptoms, diagnosis, treatment, impacts, and lived experiences of melanoma.

Results

A total of 182,400 posts related to melanoma were identified between November 2018 and November 2020. Following exclusion of irrelevant posts and using random sampling methodology, 864 posts were identified as relevant to the study objectives. Of the social media channels included, Twitter was the most commonly used, followed by forums and blogs. Most posts originated from the United Kingdom (n=328, 38%) and Spain (n=138, 16%). Of the relevant posts, 62% (n=536) were categorized as originating from individuals with melanoma. The most frequently discussed melanoma-related topics were treatment (436/792, 55%), diagnosis and tests (261/792, 33%), and remission (190/792, 24%). The majority of treatment discussions were about surgery (292/436, 67%), followed by immunotherapy (52/436, 12%). In total, 255 posts discussed the impacts of melanoma, which included emotional burden (n=179, 70%), physical impacts (n=61, 24%), effects on social life (n=43, 17%), and financial impacts (n=10, 4%).

Conclusions

Findings from this study highlight how melanoma stakeholders discuss key concepts associated with the condition on social media, adding to the conceptual model of the patient journey. This social media listening approach is a powerful tool for exploring melanoma stakeholder perspectives, providing insights that can be used to corroborate existing data and inform future studies.