Attitudes Toward the Ethics of Research Using Social Media: A Systematic Review

Ethical implications of artificial intelligence in sport: A systematic scoping review

BACKGROUND

Although there is growing evidence of the use of artificial intelligence (AI) techniques in sports, ethical issues surrounding AI use are being discussed at a minimal level. Thus, this systematic scoping review aimed to summarize the current ethical implications associated with using AI in sports.

METHODS

In this study, a total of 9 databases-MEDLINE/PubMed, Embase, Cochrane Library, ProQuest, EBSCOhost, IEEE Xplore, Web of Science, Scopus, and Google Scholar-were searched. The review protocol was registered (https://osf.io/42a8q) before extracting data. The search yielded 397 studies, and 25 studies met the inclusion and exclusion criteria.

RESULTS

The 25 studies were categorized into 4 primary ethical concerns: fairness and bias, transparency and explainability, privacy and data ethics, and accountability in AI's application in sports. These categorizations were derived based on the systematic review of ethical issues highlighted across the selected studies. Fifteen studies delved into fairness and bias, focusing on how AI can perpetuate existing inequalities in sports. Thirteen studies addressed the lack of transparency, emphasizing the challenges in interpretability and trust in AI-driven decisions. Privacy and data ethics emerged as significant in 22 studies, highlighting risks related to the misuse of athletes' sensitive data. Finally, accountability was examined in 8 studies, stressing the ethical obligations of AI developers and users in sports contexts. The thematic analysis revealed overlapping concerns, as some studies addressed multiple issues simultaneously.

CONCLUSION

Future research should focus on developing ethical frameworks tailored to underrepresented sports contexts and creating global standards for AI regulation in sports. This includes investigating the implications of AI applications in amateur sports, enhancing diversity in AI training datasets, and exploring the integration of ethical AI practices across various sports governance structures.

Factors that affect clinical youth engagement in digital mental health research: a qualitative sub-study nested within a prospective cohort study

BACKGROUND

There has been extensive debate about the role of social media and smartphone use in youth mental health and self-harm. Research to date lacks sufficient detail to determine the mechanisms underpinning any associations. The Social Media, Smartphone use and Self-harm in Young People (3S-YP) study is a prospective cohort study that was co-produced with young people to investigate temporal patterns of social media and smartphone use prior to an episode of self-harm in a clinical youth sample. Young people were actively involved in all key stages of the research process to ensure the research would be relevant and acceptable to the intended population. This included defining the research question and designing the methods. This qualitative sub-study nested within the main 3S-YP study aimed to evaluate young people's experiences of engaging in this innovative digital mental health study. This will help inform understanding regarding the added value of co-production and future research in this field.

METHODS

Semi-structured interviews were conducted with a purposive sample of participants from the 3S-YP study. Interview data was analysed using codebook thematic analysis.

RESULTS

Sixteen young people (mean 19.8 years old, SD 2.9; n = 10 female, 63%) participated in the interviews. Participants were generally comfortable answering questions about sensitive topics using remote digital tools, appreciating the greater privacy, convenience and opportunity for self-reflection they provide, whilst noting periods of poor mental health may affect study engagement. The remote research methods (including the participation information and tools for recruitment and data collection) were considered user-friendly and were complemented by the active role of the research team who facilitated young people's engagement with the study. Despite the relevance and support for research on the impact of digital technology use on youth mental health, concerns about data sharing and a complex process for accessing data from social media platforms complicated study engagement. The role of parental involvement was also described.

CONCLUSIONS

User-friendly remote research methods, coupled with proactive, responsive researchers and parental support are beneficial for conducting research with clinical youth populations. Whilst young people endorse research in this field, concerns about data sharing and barriers to data access need addressing if researchers are to effectively employ innovative solutions to investigating the impact of smartphones and social media use on youth mental health and self-harm. The findings from this study demonstrate the value of actively involving those with lived experience throughout the research process and provide useful insight for researchers intending to conduct similar research.

TRIAL REGISTRATION

This study is registered on ClinicalTrials.gov (ID no. NCT04601220).

Exploring the Views of Young People, Including Those With a History of Self-Harm, on the Use of Their Routinely Generated Data for Mental Health Research: Web-Based Cross-Sectional Survey Study

BACKGROUND

Secondary use of routinely collected health care data has great potential benefits in epidemiological studies primarily due to the large scale of preexisting data.

OBJECTIVE

This study aimed to engage respondents with and without a history of self-harm, gain insight into their views on the use of their data for research, and determine whether there were any differences in opinions between the 2 groups.

METHODS

We examined young people's views on the use of their routinely collected data for mental health research through a web-based survey, evaluating any differences between those with and without a history of self-harm.

RESULTS

A total of 1765 respondents aged 16 to 24 years were included. Respondents' views were mostly positive toward the use and linkage of their data for research purposes for public benefit, particularly with regard to the use of health care data (mental health or otherwise), and generally echoed existing evidence on the opinions of older age groups. Individuals who reported a history of self-harm and subsequently contacted health services more often reported being "extremely likely" or "likely" to share mental health data (contacted: 209/609, 34.3%; 95% CI 28.0-41.2; not contacted: 169/782, 21.6%; 95% CI 15.8-28.7) and physical health data (contacted: 117/609, 19.2%; 95% CI 12.7-27.8; not contacted: 96/782, 12.3%; 95% CI 6.7-20.9) compared with those who had not contacted services. Respondents were overall less likely to want to share their social media data, which they considered to be more personal compared to their health care data. Respondents stressed the importance of anonymity and the need for an appropriate ethical framework.

CONCLUSIONS

Young people are aware, and they care about how their data are being used and for what purposes, irrespective of having a history of self-harm. They are largely positive about the use of health care data (mental or physical) for research and generally echo the opinions of older age groups raising issues around data security and the use of data for the public interest.

Patient Information Needs and Decision-Making Before a Cardiac Implantable Electronic Device: A Qualitative Study Utilizing Social Media Data

The decision to receive a cardiac implantable electronic device (CIED) represents a challenging experience for patients. However, the majority of previous research has only considered retrospective accounts of patient experiences. This study aimed to use social media data to characterize the information sought by people anticipating or considering CIED implantation and factors that influence their decision-making experiences. A Python-based script was used to collect posts made to a community intended for discussions concerning CIEDs on the social media platform Reddit. Reflexive content analysis was used to analyze the collected data. From 799 posts collected, 101 made by 86 participants were analyzed. The reported median (range) age of participants was 34 (16-67), and most were anticipating or considering a pacemaker. Three overarching categories classified the data: "Use of social media to meet informational and other needs"; "Factors influencing acceptance of the need for implantation"; and "Specific concerns considered during decision-making." Participants anticipating or considering a CIED predominantly sought experiential information. Among asymptomatic participants, doubts were prevalent, with acceptance being an influential factor in decision-making. Healthcare professionals should recognize the informational and emotional needs of prospective CIED patients and tailor support mechanisms to better facilitate their decision-making.

AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges

BACKGROUND

Mental health disorders are currently the main contributor to poor quality of life and years lived with disability. Symptoms common to many mental health disorders lead to impairments or changes in the use of language, which are observable in the routine use of social media. Detection of these linguistic cues has been explored throughout the last quarter century, but interest and methodological development have burgeoned following the COVID-19 pandemic. The next decade may see the development of reliable methods for predicting mental health status using social media data. This might have implications for clinical practice and public health policy, particularly in the context of early intervention in mental health care.

OBJECTIVE

This study aims to examine the state of the art in methods for predicting mental health statuses of social media users. Our focus is the development of artificial intelligence-driven methods, particularly natural language processing, for analyzing large volumes of written text. This study details constraints affecting research in this area. These include the dearth of high-quality public datasets for methodological benchmarking and the need to adopt ethical and privacy frameworks acknowledging the stigma experienced by those with a mental illness.

METHODS

A Google Scholar search yielded peer-reviewed articles dated between 1999 and 2024. We manually grouped the articles by 4 primary areas of interest: datasets on social media and mental health, methods for predicting mental health status, longitudinal analyses of mental health, and ethical aspects of the data and analysis of mental health. Selected articles from these groups formed our narrative review.

RESULTS

Larger datasets with precise dates of participants' diagnoses are needed to support the development of methods for predicting mental health status, particularly in severe disorders such as schizophrenia. Inviting users to donate their social media data for research purposes could help overcome widespread ethical and privacy concerns. In any event, multimodal methods for predicting mental health status appear likely to provide advancements that may not be achievable using natural language processing alone.

CONCLUSIONS

Multimodal methods for predicting mental health status from voice, image, and video-based social media data need to be further developed before they may be considered for adoption in health care, medical support, or as consumer-facing products. Such methods are likely to garner greater public confidence in their efficacy than those that rely on text alone. To achieve this, more high-quality social media datasets need to be made available and privacy concerns regarding the use of these data must be formally addressed. A social media platform feature that invites users to share their data upon publication is a possible solution. Finally, a review of literature studying the effects of social media use on a user's depression and anxiety is merited.

#BeSeen: understanding young people's views of the motivation and impacts of sharing self-harm imagery online and use of their social media data for research-a UK participatory arts-led qualitative study

OBJECTIVES

This study explored the views of young people from diverse backgrounds, with or without a history of self-harm, on the motivation and impacts of sharing self-harm imagery online and the use of their social media data for mental health research.

DESIGN

Thematic analysis of 27 semi-structured one-to-one interviews.

SETTING

Two workshops were conducted in 2021.

PARTICIPANTS

We recruited 27 study participants aged 16-24 (60% male). Sixteen (59%) participants were refugee and asylum seekers (RAS).

RESULTS

Two main themes were generated: (1) Online imagery of self-harm captured perceived motivations for sharing such images, the potential impacts on others and possible need of censorship. This theme was characterised by mixed attitudes towards motivations for sharing, with some perceiving this as attention seeking, while others thought of it as help seeking or sharing of pain. Overall, participants agreed that images of self-harm can be triggering and should include trigger warnings. (2) Data sharing for mental health and self-harm research captured views on the use of social media posts and images for research purposes, and levels of trust in public and private organisations. It outlined positive views on their data being shared for research for public benefit, but highlighted issues of consent. The two most trusted organisations to hold and conduct research were the National Health Service and Universities. Participants from the RAS group were more inclined to agree to their data being used and had higher levels of trust in government.

CONCLUSION

Young people care about their privacy and use of their data even when it is publicly available. Coproduction with young people of resources to support understanding and develop innovative solutions to gaining informed consent for data sharing and research for public benefit is required. Young people from excluded communities, post-immigration RAS and males should be purposively involved in future social media research.

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.

Reporting of Ethical Considerations in Qualitative Research Utilizing Social Media Data on Public Health Care: Scoping Review

BACKGROUND

The internet community has become a significant source for researchers to conduct qualitative studies analyzing users' views, attitudes, and experiences about public health. However, few studies have assessed the ethical issues in qualitative research using social media data.

OBJECTIVE

This study aims to review the reportage of ethical considerations in qualitative research utilizing social media data on public health care.

METHODS

We performed a scoping review of studies mining text from internet communities and published in peer-reviewed journals from 2010 to May 31, 2023. These studies, limited to the English language, were retrieved to evaluate the rates of reporting ethical approval, informed consent, and privacy issues. We searched 5 databases, that is, PubMed, Web of Science, CINAHL, Cochrane, and Embase. Gray literature was supplemented from Google Scholar and OpenGrey websites. Studies using qualitative methods mining text from the internet community focusing on health care topics were deemed eligible. Data extraction was performed using a standardized data extraction spreadsheet. Findings were reported using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines.

RESULTS

After 4674 titles, abstracts, and full texts were screened, 108 studies on mining text from the internet community were included. Nearly half of the studies were published in the United States, with more studies from 2019 to 2022. Only 59.3% (64/108) of the studies sought ethical approval, 45.3% (49/108) mentioned informed consent, and only 12.9% (14/108) of the studies explicitly obtained informed consent. Approximately 86% (12/14) of the studies that reported informed consent obtained digital informed consent from participants/administrators, while 14% (2/14) did not describe the method used to obtain informed consent. Notably, 70.3% (76/108) of the studies contained users' written content or posts: 68% (52/76) contained verbatim quotes, while 32% (24/76) paraphrased the quotes to prevent traceability. However, 16% (4/24) of the studies that paraphrased the quotes did not report the paraphrasing methods. Moreover, 18.5% (20/108) of the studies used aggregated data analysis to protect users' privacy. Furthermore, the rates of reporting ethical approval were different between different countries (P=.02) and between papers that contained users' written content (both direct and paraphrased quotes) and papers that did not contain users' written content (P<.001).

CONCLUSIONS

Our scoping review demonstrates that the reporting of ethical considerations is widely neglected in qualitative research studies using social media data; such studies should be more cautious in citing user quotes to maintain user privacy. Further, our review reveals the need for detailed information on the precautions of obtaining informed consent and paraphrasing to reduce the potential bias. A national consensus of ethical considerations such as ethical approval, informed consent, and privacy issues is needed for qualitative research of health care using social media data of internet communities.

Ethical guidance for conducting health research with online communities: A scoping review of existing guidance

Online research methods have grown in popularity due in part to the globalised and far-reaching nature of the internet but also linked to the Covid-19 pandemic whereby restrictions to travel and face to face contact necessitated a shift in methods of research recruitment and data collection. Ethical guidance exists to support researchers in conducting online research, however this is lacking within health fields. This scoping review aims to synthesise formal ethical guidance for applying online methods within health research as well as provide examples of where guidance has been used. A systematic search of literature was conducted, restricted to English language records between 2013 and 2022. Eligibility focused on whether the records were providing ethical guidance or recommendations, were situated or relevant to health disciplines, and involved the use or discussion of online research methods. Following exclusion of ineligible records and duplicate removal, three organisational ethical guidance and 24 research papers were charted and thematically analysed. Four key themes were identified within the guidance documents, 1) consent, 2) confidentiality and privacy, 3) protecting participants from harm and 4) protecting researchers from harm with the research papers describing additional context and understanding around these issues. The review identified that there are currently no specific guidelines aimed at health researchers, with the most cited guidance coming from broader methodological perspectives and disciplines or auxiliary fields. All guidance discussed each of the four key themes within the wider context of sensitive topics and vulnerable populations, areas and issues which are often prominent within health research thus highlighting the need for unifying guidance specific for health researchers. Further research should aim to understand better how online health studies apply ethical principles, to support in informing gaps across both research and guidance.

Toward Fairness, Accountability, Transparency, and Ethics in AI for Social Media and Health Care: Scoping Review

BACKGROUND

The use of social media for disseminating health care information has become increasingly prevalent, making the expanding role of artificial intelligence (AI) and machine learning in this process both significant and inevitable. This development raises numerous ethical concerns. This study explored the ethical use of AI and machine learning in the context of health care information on social media platforms (SMPs). It critically examined these technologies from the perspectives of fairness, accountability, transparency, and ethics (FATE), emphasizing computational and methodological approaches that ensure their responsible application.

OBJECTIVE

This study aims to identify, compare, and synthesize existing solutions that address the components of FATE in AI applications in health care on SMPs. Through an in-depth exploration of computational methods, approaches, and evaluation metrics used in various initiatives, we sought to elucidate the current state of the art and identify existing gaps. Furthermore, we assessed the strength of the evidence supporting each identified solution and discussed the implications of our findings for future research and practice. In doing so, we made a unique contribution to the field by highlighting areas that require further exploration and innovation.

METHODS

Our research methodology involved a comprehensive literature search across PubMed, Web of Science, and Google Scholar. We used strategic searches through specific filters to identify relevant research papers published since 2012 focusing on the intersection and union of different literature sets. The inclusion criteria were centered on studies that primarily addressed FATE in health care discussions on SMPs; those presenting empirical results; and those covering definitions, computational methods, approaches, and evaluation metrics.

RESULTS

Our findings present a nuanced breakdown of the FATE principles, aligning them where applicable with the American Medical Informatics Association ethical guidelines. By dividing these principles into dedicated sections, we detailed specific computational methods and conceptual approaches tailored to enforcing FATE in AI-driven health care on SMPs. This segmentation facilitated a deeper understanding of the intricate relationship among the FATE principles and highlighted the practical challenges encountered in their application. It underscored the pioneering contributions of our study to the discourse on ethical AI in health care on SMPs, emphasizing the complex interplay and the limitations faced in implementing these principles effectively.

CONCLUSIONS

Despite the existence of diverse approaches and metrics to address FATE issues in AI for health care on SMPs, challenges persist. The application of these approaches often intersects with additional ethical considerations, occasionally leading to conflicts. Our review highlights the lack of a unified, comprehensive solution for fully and effectively integrating FATE principles in this domain. This gap necessitates careful consideration of the ethical trade-offs involved in deploying existing methods and underscores the need for ongoing research.

Patient listening on social media for patient-focused drug development: a synthesis of considerations from patients, industry and regulators

Patients, life science industry and regulatory authorities are united in their goal to reduce the disease burden of patients by closing remaining unmet needs. Patients have, however, not always been systematically and consistently involved in the drug development process. Recognizing this gap, regulatory bodies worldwide have initiated patient-focused drug development (PFDD) initiatives to foster a more systematic involvement of patients in the drug development process and to ensure that outcomes measured in clinical trials are truly relevant to patients and represent significant improvements to their quality of life. As a source of real-world evidence (RWE), social media has been consistently shown to capture the first-hand, spontaneous and unfiltered disease and treatment experience of patients and is acknowledged as a valid method for generating patient experience data by the Food and Drug Administration (FDA). While social media listening (SML) methods are increasingly applied to many diseases and use cases, a significant piece of uncertainty remains on how evidence derived from social media can be used in the drug development process and how it can impact regulatory decision making, including legal and ethical aspects. In this policy paper, we review the perspectives of three key stakeholder groups on the role of SML in drug development, namely patients, life science companies and regulators. We also carry out a systematic review of current practices and use cases for SML and, in particular, highlight benefits and drawbacks for the use of SML as a way to identify unmet needs of patients. While we find that the stakeholders are strongly aligned regarding the potential of social media for PFDD, we identify key areas in which regulatory guidance is needed to reduce uncertainty regarding the impact of SML as a source of patient experience data that has impact on regulatory decision making.

Understanding and preventing the advertisement and sale of illicit drugs to young people through social media: A multidisciplinary scoping review

ISSUES

The sale of illicit drugs online has expanded to mainstream social media apps. These platforms provide access to a wide audience, especially children and adolescents. Research is in its infancy and scattered due to the multidisciplinary aspects of the phenomena.

APPROACH

We present a multidisciplinary systematic scoping review on the advertisement and sale of illicit drugs to young people. Peer-reviewed studies written in English, Spanish and French were searched for the period 2015 to 2022. We extracted data on users, drugs studied, rate of posts, terminology used and study methodology.

KEY FINDINGS

A total of 56 peer-reviewed papers were included. The analysis of these highlights the variety of drugs advertised and platforms used to do so. Various methodological designs were considered. Approaches to detecting illicit content were the focus of many studies as algorithms move from detecting drug-related keywords to drug selling behaviour. We found that on average, for the studies reviewed, 13 in 100 social media posts advertise illicit drugs. However, popular platforms used by adolescents are rarely studied.

IMPLICATIONS

Promotional content is increasing in sophistication to appeal to young people, shifting towards healthy, glamourous and seemingly legal depictions of drugs. Greater inter-disciplinary collaboration between computational and qualitative approaches are needed to comprehensively study the sale and advertisement of illegal drugs on social media across different platforms. This requires coordinated action from researchers, policy makers and service providers.

Netnography: A novel methodology for nursing research

AIM

The aim of this paper is to critically reflect on our team's experience of using netnography to explore vaccine-hesitant parents and pregnant women, a group who have traditionally been difficult to recruit to research studies and a methodology that is underutilized in nursing research.

DESIGN

This paper takes the form of a discussion paper that will utilize data obtained from a qualitative netnographic study. Relevant literature was searched including 2015-2023.

METHOD

This paper utilized data obtained from a qualitative study that used netnography as methodology and an online minable data source. Netnography is a relatively new methodology that uses the online environment to explore digital cultures and study networked society. It pays particular attention to cultural insights and conditions that impact the human experience. This methodology is particularly relevant to nursing research which is often humanistic and always conducted to ensure optimal patient outcomes.

RESULTS

Using netnography for the first time has resulted in four main insights. These include the adaptability of the process; the creativity involved in designing the site; the ready acceptance of the site by participants and the co-creation knowledge that resulted.

CONCLUSIONS

Netnography is a creative methodology that was successful in accessing and engaging the vaccine-hesitant community, a group who are often marginalized. Netnography has the advantage of using a platform that is familiar and safe for many people and provides access to an extensive minable data source.

Ethical and Information Governance Considerations for Promoting Digital Social Interventions in Primary Care

Promoting online peer support beyond the informal sector to statutory health services requires ethical considerations and evidence-based knowledge about its impact on patients, health care professionals, and the wider health care system. Evidence on the effectiveness of digital interventions in primary care is sparse, and definitive guidance is lacking on the ethical concerns arising from the use of social media as a means for health-related interventions and research. Existing literature examining ethical issues with digital interventions in health care mainly focuses on apps, electronic health records, wearables, and telephone or video consultations, without necessarily covering digital social interventions, and does not always account for primary care settings specifically. Here we address the ethical and information governance aspects of undertaking research on the promotion of online peer support to patients by primary care clinicians, related to medical and public health ethics.

Joy at work and vocational identity during COVID-19: A structural equation model

OBJECTIVE

This study aims to explore the interrelations between joy at work, vocational identity, and COVID-19-related latent variables.

DESIGN

A cross-sectional design was adopted to survey 253 registered nurses through nursing organizations and social networking sites during the time of the COVID-19 pandemic.

METHODS

Structural Equation Modeling through Partial Least Squares (SEM-PLS) was employed to accurately analyze and estimate relationships among joy at work, vocational identity, and COVID-19-related constructs in compliance with published standards and guidelines.

RESULTS

Thirty-one items received convergent validity measures to represent the five study constructs related to joy at work, vocational identity, and Work life Impact of COVID-19 pandemic: Meaning, Engagement, and Growth (MEG), Compassion, Sensitivity, and Respect (CSR), Trust, Support, and Flexibility (TSF), Vocational Identity Questionnaire (VIQ), and Work life Impact of COVID-19 pandemic (CI). The generated model exhibited good model fit and consistent quality indices. The data fit statistically with the model: (Average Path Coefficient = 0.195, p < 0.000); Average R-Squared = 0.156, p < 0.003; Average Adjusted R-Squared = 0.151, p < 0.004; Average Variance Inflation Factor = 2.193 (within the ideal range); Average Full collinearity VIF = 2.388 (within the ideal range), and Tenenhaus Goodness of Fit (GoF) = 0.329. The perceived Work life Impact of COVID-19 pandemic (CI) was a significant predictor of joy at work constructs (MEG, CSR, and TSF) and VIQ with direct effects. It also exerted a negative influence over MEG and TSF, but positively on CSR and VIQ. Notably, joy at work constructs significantly mediated the effects of CI on VIQ.

CONCLUSION

A structural model was developed that offers insights and a parsimonious explanation for the interrelations of COVID-19, joy at work, and vocational identity variables. The pandemic unquestionably influences the nurses' perceived joy, sense of calling, and meaning in life's work, and joy at work enhances nurses' work-life worth during challenging times.

CLINICAL RELEVANCE

An increased understanding of nurses' joy at work during challenging times can potentially influence work culture, informs individual nurses, nurse leaders, and healthcare systems in all professional domains of practice and provides the foundational information to identify barriers to joy and strategies that enhance joy.

COVID-19 Anti-Vaccine Sentiments in Malaysia: Narratives of Comments from Facebook Post

The anti-vaccination movement was an ongoing issue in Malaysia, a Muslim-majority country, even before the COVID-19 pandemic. It is unclear whether the introduction of new COVID-19 vaccines would similarly provoke anti-vaccine sentiments. This study analyzed COVID-19 anti-vaccine sentiments in the Malaysian community. Anti-vaccine comments from Facebook page posts were extracted. The qualitative software QSR-NVivo 10 was used to manage, code and analyze the data. The fast-track COVID-19 vaccine evoked the fear of unknown long-term effects, safety, effectiveness and the duration of protection. The halal status of the COVID-19 vaccines is important. Although it is permissible to use vaccines that are not certified halal under the state of darurah (emergency), there was doubt that the current state has reached the stage of darurah that warrants the use of vaccines. COVID-19 vaccine microchip conspiracy theories were raised. COVID-19 is viewed as only severe for vulnerable populations, and hence vaccination is not needed for the healthy. There were opinions that coronavirus treatments would be more beneficial than vaccination. The anti-COVID-19 vaccine sentiments uncovered in this study provide important insights for the formulation of public health messages to instill confidence in new COVID-19 vaccines. Despite the pandemic being nearly over and many people worldwide having received COVID-19 vaccines, the findings provide important insight into potential issues regarding the introduction of new vaccines in the event of future pandemics.

A Blog Text Analysis to Explore Psychosocial Support in Adolescents and Young Adults With Cancer

BACKGROUND

The achievement of developmental milestones of adolescents and young adults (AYAs) is significantly challenged by a cancer diagnosis and treatment. To help with challenges in AYAs with cancer, various types of psychosocial support have been studied to cope with cancer and seek optimal well-being. However, despite differences among AYAs' developmental stages, AYAs with cancer are often treated as a homogeneous group in research and hospital settings.

OBJECTIVE

The aim of this study was to identify and compare psychosocial support that facilitates the well-being of AYAs with cancer.

METHODS

Quantitative and qualitative analyses were conducted on AYAs' perceived psychosocial support as expressed on an online cancer community. Themes were identified using qualitative content analysis, and descriptive quantitative methods were used to compare themes by age and gender.

RESULTS

Seven themes emerged: coping skill building, self-transcendence, family support, support from friends, professional support, peer support including online and offline support groups, and accommodation. There were no significant differences in the frequency of posts between age and gender variables by theme. However, the details of the themes were qualitatively different by age and gender.

CONCLUSIONS

The psychosocial support AYAs perceived may differ by age and gender. This study suggests opportunities for nurses to contribute their support to AYAs' perceived psychosocial support throughout AYAs' cancer journeys.

IMPLICATION FOR PRACTICE

The sources of support that can help AYAs with cancer should be routinely available rather than in response to crisis.

Ethical principles for infodemiology and infoveillance studies concerning infodemic management on social media

Big data originating from user interactions on social media play an essential role in infodemiology and infoveillance outcomes, supporting the planning and implementation of public health actions. Notably, the extrapolation of these data requires an awareness of different ethical elements. Previous studies have investigated and discussed the adoption of conventional ethical approaches in the contemporary public health digital surveillance space. However, there is a lack of specific ethical guidelines to orient infodemiology and infoveillance studies concerning infodemic on social media, making it challenging to design digital strategies to combat this phenomenon. Hence, it is necessary to explore if traditional ethical pillars can support digital purposes or whether new ones must be proposed since we are confronted with a complex online misinformation scenario. Therefore, this perspective provides an overview of the current scenario of ethics-related issues of infodemiology and infoveillance on social media for infodemic studies.

A Social Media Listening Study to Understand the Unmet Needs and Quality of Life in Adult and Pediatric Amblyopia Patients

INTRODUCTION

Amblyopia is an important cause of monocular vision impairment worldwide, and it negatively impacts patients' quality of life (QoL). Understanding patients' perspectives may help to optimize treatment outcomes and improve treatment adherence.

METHODS

This was a non-interventional, retrospective analysis of social media data available in the public domain posted by patients and caregivers on selected social media channels (Twitter®, forums, blogs, and news) from 12 countries between July 2018 and June 2020.

RESULTS

Approximately 2662 conversations relevant to the research objective were analyzed. The patient journey for adults and children was constructed based on the conversations. Eyeglasses, eye patches, contact lenses, and vision exercises were the common treatment options for amblyopia. Patients also reported vision improvement with emerging technologies such as digital therapeutics. Amblyopia and its treatment had a negative impact on QoL, and increased caregiver burden. Insurance coverage, long appointment waiting times, and recurring expenses of treatment options were reported as barriers to treatment. Non-compliance, switching between treatment options or technology, or discontinuation of treatment options was found to emanate from various issues including no improvement of the condition, discomfort with the treatment option, bullying, dissatisfaction with healthcare professional (HCP) recommendation, cost of treatment/issues with insurance coverage, side effects, and/or other unspecified reasons. The need for regular eye examinations, better diagnostic tests, awareness of the disease, awareness amongst HCPs about treatment options, and the need for better health insurance coverage policies emerged as unmet needs.

CONCLUSION

This social media listening study generated insights on patients with amblyopia and their caregivers regarding the patient journey, treatment options, reasons for non-compliance, reasons for switching HCPs, barriers to treatment, and unmet needs. Further qualitative research is required to validate the findings.

Ethical and Methodological Considerations of Twitter Data for Public Health Research: Systematic Review

BACKGROUND

Much research is being carried out using publicly available Twitter data in the field of public health, but the types of research questions that these data are being used to answer and the extent to which these projects require ethical oversight are not clear.

OBJECTIVE

This review describes the current state of public health research using Twitter data in terms of methods and research questions, geographic focus, and ethical considerations including obtaining informed consent from Twitter handlers.

METHODS

We implemented a systematic review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, of articles published between January 2006 and October 31, 2019, using Twitter data in secondary analyses for public health research, which were found using standardized search criteria on SocINDEX, PsycINFO, and PubMed. Studies were excluded when using Twitter for primary data collection, such as for study recruitment or as part of a dissemination intervention.

RESULTS

We identified 367 articles that met eligibility criteria. Infectious disease (n=80, 22%) and substance use (n=66, 18%) were the most common topics for these studies, and sentiment mining (n=227, 62%), surveillance (n=224, 61%), and thematic exploration (n=217, 59%) were the most common methodologies employed. Approximately one-third of articles had a global or worldwide geographic focus; another one-third focused on the United States. The majority (n=222, 60%) of articles used a native Twitter application programming interface, and a significant amount of the remainder (n=102, 28%) used a third-party application programming interface. Only one-third (n=119, 32%) of studies sought ethical approval from an institutional review board, while 17% of them (n=62) included identifying information on Twitter users or tweets and 36% of them (n=131) attempted to anonymize identifiers. Most studies (n=272, 79%) included a discussion on the validity of the measures and reliability of coding (70% for interreliability of human coding and 70% for computer algorithm checks), but less attention was paid to the sampling frame, and what underlying population the sample represented.

CONCLUSIONS

Twitter data may be useful in public health research, given its access to publicly available information. However, studies should exercise greater caution in considering the data sources, accession method, and external validity of the sampling frame. Further, an ethical framework is necessary to help guide future research in this area, especially when individual, identifiable Twitter users and tweets are shared and discussed.

TRIAL REGISTRATION

PROSPERO CRD42020148170; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=148170.

Barriers to Reporting Sexual Violence: A Qualitative Analysis of #WhyIDidntReport

The present study conducted thematic analyses of tweets including #WhyIDidntReport (N = 500) to examine barriers to reporting sexual victimization. Barriers to reporting were identified across individual, interpersonal, and sociocultural levels of the social ecology. Common barriers to reporting included labeling of the experience, age, fear, privacy concerns, self-blame, betrayal/shock, the relation/power of the perpetrator, negative reactions to disclosure, and the belief-or personal experience-that reporting would not result in justice and societal norms.

Motivations for sharing personal information and self-disclosure in public and private Facebook groups of mentally ill people

Purpose

This study explores the motivations for sharing personal information and self-disclosure by mentally ill people in public and private Facebook groups. The purpose of the self-disclosure comparison between public and private groups is to understand how mentally ill people use different kinds of online communication channels in order to advance their goals and needs concerning their illness.

Design/methodology/approach

The study was carried out using questionnaires distributed in Facebook groups for people with mental illnesses. A total of 123 full and valid questionnaires were received. Statistical analysis was performed on the data.

Findings

Findings revealed that there are no significant differences between public and private groups concerning motivations for self-disclosure and that both types of groups create a safe and supportive place for mentally ill people. However, findings suggest that participants in public groups tend to display higher social involvement than those who participate in private groups.

Originality/value

This is a path breaking study on the entire subject of discourse of people with mental illnesses in private Facebook groups and its importance is derived from this. The study clarified and emphasized the importance of the sense of belonging to a community. Moreover, findings encourage people with mental illnesses to make use of social media channels to meet their social and personal needs.

Days with and without self-injurious thoughts and behaviors: Impact of childhood maltreatment on adolescent online social networking

INTRODUCTION

Among adolescents, an increasing rate of interpersonal interactions occurs online. Previous research has shown that interpersonal context exerts a robust impact on suicidal thoughts or behaviors, yet little attention has focused on examining the content of online interactions surrounding self-injurious thoughts or behaviors. As such, the present study sought to compare online social networking behaviors among adolescents on days with and without experiencing self-injurious thoughts or behaviors, as influenced by childhood maltreatment history.

METHOD

Adolescents aged 13-18 hospitalized for self-injurious thoughts or behaviors were recruited as part of an ongoing longitudinal study. A subsample (N = 22) of adolescents provided data from their online social networking platforms (i.e., text messages, Facebook, Instagram, and Twitter). Using a mixed-methods approach, online social networking data on days of experiencing self-injurious thoughts or behaviors and days of not experiencing self-injurious thoughts or behaviors were compared.

RESULTS

Results indicate the frequency and content of online social networking messaging do not change by day of self-injurious thoughts or behaviors or history of childhood maltreatment. However, childhood maltreatment predicts received conflictual messages as well as sent symptomatic messages on days of experiencing self-injurious thoughts or behaviors.

CONCLUSIONS

Childhood maltreatment may play a role in the content of adolescent online behaviors, particularly on days when they experience self-injurious thoughts or behaviors. Implications for intervention are discussed.

Unmet needs in adolescents and young adults with cancer: A mixed-method study using social media

PURPOSE

The purpose of this study is to identify and compare the unmet needs of adolescents and young adults (AYAs) with cancer by age and gender.

DESIGN AND METHODS

This is a mixed-methods study to analyze textual data from blog posts on AYAs' unmet needs. Themes were identified using a qualitative descriptive method with content analysis, and a quantitative method was used to compare themes by age and gender.

RESULTS

The findings from blog posts of 100 AYAs showed that AYAs with cancer expressed somewhat different needs by age and gender. Young adults (26-39 years) with cancer tended to describe significantly more feelings of fear (p = .043) and parenting needs (p < .001) and significantly fewer educational needs (p < .001) than did emerging adults (18-25 years) with cancer. Female AYAs with cancer described significantly more feelings of guilt (p = .020), sexual needs (p = .003), fertility issues (p = .023), and social needs (p = .013) than did male AYAs with cancer. There were no statistically significant differences in the remaining themes between age and gender groups, although how they described unmet needs differed qualitatively.

CONCLUSIONS

AYAs with cancer have various unmet needs and their unmet needs were different by age and gender.

PRACTICE IMPLICATIONS

Nurses should proactively provide integrated systematic screening by offering a safe, non-judgmental environment to encourage AYAs to express their needs across their cancer journey. Nurses also should respond with developmentally appropriate support, resources, and referrals based on these expressed needs.

Ethical Views on Sharing Digital Data for Public Health Surveillance: Analysis of Survey Data Among Patients

Digital data, including social media, wearable device data, electronic health records, and internet search data, are increasingly being integrated into public health research and policy. Because of the current issues around public distrust of science and other ethical issues in public health research, it is essential that researchers conduct ongoing studies assessing people's perceptions around and willingness to share digital data. This study aims to examine participants' social media use and comfort sharing their data with health researchers. One hundred and sixty-one participants with medical conditions were recruited through social media paid advertisements and referral from a website, and invited to complete surveys on social media use and ethical perspectives on data sharing. Eligibility criteria were adults 18 years old or older, living in the US, self-reported having been diagnosed by a physician with a medical condition, belonging to at least one social media platform, using social media at least twice a week, and owning a smartphone. Study participants were mostly female, White, and with a mean age of 36.31 years. More than one third of participants reported being very comfortable sharing electronic health data and social media data for personalized healthcare and to help others. Findings suggest that participants are very uncomfortable sharing their location and text message data with researchers, with primary concerns centered around loss of privacy, disclosing private information, and that friends, family, and others may find out that they shared text messages with researchers. We discuss the implications of this research before and after the COVID-19 pandemic, along with its potential implications for future collection of digital data for public health.

Natural language processing applied to mental illness detection: a narrative review

Mental illness is highly prevalent nowadays, constituting a major cause of distress in people’s life with impact on society’s health and well-being. Mental illness is a complex multi-factorial disease associated with individual risk factors and a variety of socioeconomic, clinical associations. In order to capture these complex associations expressed in a wide variety of textual data, including social media posts, interviews, and clinical notes, natural language processing (NLP) methods demonstrate promising improvements to empower proactive mental healthcare and assist early diagnosis. We provide a narrative review of mental illness detection using NLP in the past decade, to understand methods, trends, challenges and future directions. A total of 399 studies from 10,467 records were included. The review reveals that there is an upward trend in mental illness detection NLP research. Deep learning methods receive more attention and perform better than traditional machine learning methods. We also provide some recommendations for future studies, including the development of novel detection methods, deep learning paradigms and interpretable models.

A Novel Method of Generating Geospatial Intelligence from Social Media Posts of Political Leaders

Social media platforms such as Twitter have been used by political leaders, heads of states, political parties, and their supporters to strategically influence public opinions. Leaders can post about a location, a state, a country, or even a region in their social media accounts, and the posts can immediately be viewed and reacted to by millions of their followers. The effect of social media posts by political leaders could be automatically measured by extracting, analyzing, and producing real-time geospatial intelligence for social scientists and researchers. This paper proposed a novel approach in automatically processing real-time social media messages of political leaders with artificial intelligence (AI)-based language detection, translation, sentiment analysis, and named entity recognition (NER). This method automatically generates geospatial and location intelligence on both ESRI ArcGIS Maps and Microsoft Bing Maps. The proposed system was deployed from 1 January 2020 to 6 February 2022 to analyze 1.5 million tweets. During this 25-month period, 95K locations were successfully identified and mapped using data of 271,885 Twitter handles. With an overall 90% precision, recall, and F1score, along with 97% accuracy, the proposed system reports the most accurate system to produce geospatial intelligence directly from live Twitter feeds of political leaders with AI.

Applications of quantitative social media listening to patient-centric drug development

Social media listening has been increasingly acknowledged as a tool with applications in many stages of the drug development process. These applications were created to meet the need for patient-centric therapies that are fit-for-purpose and meaningful to patients. Such applications, however, require the leverage of new quantitative approaches and analytical methods that draw from developments in artificial intelligence and real-world data (RWD) analysis. Here, we review the state-of-the-art in quantitative social media listening (QSML) methods applied to drug discovery from the perspective of the pharmaceutical industry.

Social Media and Health Care (Part II): Narrative Review of Social Media Use by Patients

Background

People are now connected in a borderless web-based world. The modern public, especially the younger generation, relies heavily on the internet as the main source of health-related information. In health care, patients can use social media for more tailored uses such as telemedicine, finding a provider, and for peer support.

Objective

The aim of this narrative review is to discuss how social media has been used in the health care industry from the perspective of patients and describe the main issues surrounding its use in health care.

Methods

Between March and June 2020, a review of the literature was conducted on PubMed, Google Scholar, and Web of Science for English studies that were published since 2007 and discussed the use of social media in health care. In addition to only English publications that discussed the use of social media by patients, publications pertaining to ethical and legal considerations in the use of social media were included. The studies were then categorized as health information, telemedicine, finding a health care provider, peer support and sharing experiences, and influencing positive health behavior. In addition, two more sections were added to the review: issues pertaining to social media use in health care and ethical considerations.

Results

Initially, 75 studies were included. As the study proceeded, more studies were included, and a total of 91 studies were reviewed, complemented by 1 textbook chapter and 13 web references. Approximately half of the studies were reviews. The first study was published in 2009, and the last was published in 2021, with more than half of the studies published in the last 5 years. The studies were mostly from the United States (n=40), followed by Europe (n=13), and the least from India (n=1). WhatsApp or WeChat was the most investigated social media platform.

Conclusions

Social media can be used by the public and patients to improve their health and knowledge. However, due diligence must be practiced to assess the credibility of the information obtained and its source. Health care providers, patients, and the public need not forget the risks associated with the use of social media. The limitations and shortcomings of the use of social media by patients should be understood.

Originality in online dating profile texts: How does perceived originality affect impression formation and what makes a text original?

This paper investigates origins and consequences of perceived profile text originality. The first goal was to examine whether the perceived originality of authentic online dating profile texts affects online daters' perceptions of attractiveness, and whether perceptions of (less) desired partner personality traits mediate this effect. Results showed the positive impact of perceived profile text originality on impression formation: text originality positively affects perceptions of intelligence and sense of humor, which improve impressions of attractiveness and boost dating intention. The second goal was to explore what profile text features increase perceptions of profile text originality. Results revealed profile texts which were stylistically original (e.g., include metaphors) and contained more and concrete self-disclosure statements were considered more original, explaining almost half of the variance in originality scores. Taken together, our results suggest that perceived originality in profile texts is manifested in both meaning and form, and is a balancing act between novelty and appropriateness.

Ethical issues of collecting, storing, and analyzing geo-referenced tweets for mental health research

Spatial approaches to epidemiological research with big social media data provide tremendous opportunities to study the relationship between the socio-ecological context where these data are generated and health indicators of interest. Such research poses a number of ethical challenges, particularly in relation to issues such as privacy, informed consent, data security, and storage. While these issues have received considerable attention by researchers in relation to research for physical health purposes in the past 10 years, there have been few efforts to consider the ethical challenges of conducting mental health research, particularly with geo-referenced social media data. The aim of this article is to identify strengths and limitations of current recommendations to address the specific ethical issues of geo-referenced tweets for mental health research. We contribute to the ongoing debate on the ethical implications of big data research and also provide recommendations to researchers and stakeholders alike on how to tackle them, with a specific focus on the use of geo-referenced data for mental health research purposes. With increasing awareness of data privacy and confidentiality issues (even for non-spatial social media data) it becomes crucial to establish professional standards of conduct so that compliance with ethical standards of conducting research with health-related social media data can be prioritized and easily assessed.

Esthetic Dentistry on Twitter: Benefits and Dangers

Objectives

The demand for esthetic dentistry is growing, and social media constitute the main driving force behind this revolution. Twitter is a leading social media platform; however, there is a lack of research on the pattern of communications and the impact of Twitter on esthetic dentistry. The purpose of this study was to analyze the content of tweets related to esthetic dentistry and to investigate how Twitter has affected the perception of, and demand for, esthetic dentistry. Moreover, it aimed to assess the potential benefits and risks of esthetic dentistry advertising strategies on Twitter as a potential social media platform.

Materials and Methods

Using a specialized web scrapping tool made available by the Python programming language, a total of 54,000 public tweets were downloaded from Twitter at real-time by matching specific keywords. The downloaded tweets were manually filtered, and 13,787 tweets were included and categorized into four tweet sets by content.

Results

The main categories were tweets regarding specific cosmetic procedure, totaling 56.53% (43.2% for veneers, 13.3% for whitening), advertisements (36.72%), information (5.53%), and general cosmetic dentistry (1.22%). Negative opinions towards veneers and whitening were the most common themes (68.03% and 43.44%). For veneers, illegal use for kids was the most common negative theme (59.7%) and being destructive for whitening (86.3%). Positive opinions counted 6.26% of veneers and 4.3% of whitening tweets. Advertising for whitening products was the second most common between all tweets (16.6%), and advertising for dental practices was the third (14.7%). Presenting facilities/services was the most common marketing strategy for dental practices (49.7%). Twitter was weakly used to circulate educational content (5.5%) and to post reviews (0.75%).

Conclusion

Twitter was extensively used to share experiences/opinions towards dental cosmetic interventions. Advertising is another vital use of this platform. However, circulating information was the least common use of this social media. Additionally, tweeters were rarely to post online reviews and specific advices and recommendations regarding esthetic dentistry. Moreover, females tended to participate and tweet more significantly in cosmetic-related topics than males. This platform should be tailored efficiently to target users' priorities and to improve health literacy and self-care. Twitter was weakly used to circulate educational content according to this study and rarely used to share online reviews.

Digital Public Health Surveillance Tools for Alcohol Use and HIV Risk Behaviors

There is a need for real-time and predictive data on alcohol use both broadly and specific to HIV. However, substance use and HIV data often suffer from lag times in reporting as they are typically measured from surveys, clinical case visits and other methods requiring extensive time for collection and analysis. Social big data might help to address this problem and be used to provide near real-time assessments of people's alcohol use and/or alcohol. This manuscript describes three types of social data sources (i.e., social media data, internet search data, and wearable device data) that might be used in surveillance of alcohol and HIV, and then discusses the implications and potential of implementing them as additional tools for public health surveillance.

A Neural Network Approach for Understanding Patient Experiences of Chronic Obstructive Pulmonary Disease (COPD): Retrospective, Cross-sectional Study of Social Media Content

Background

The abundance of online content contributed by patients is a rich source of insight about the lived experience of disease. Patients share disease experiences with other members of the patient and caregiver community and do so using their own lexicon of words and phrases. This lexicon and the topics that are communicated using words and phrases belonging to the lexicon help us better understand disease burden. Insights from social media may ultimately guide clinical development in ways that ensure that future treatments are fit for purpose from the patient’s perspective.

Objective

We sought insights into the patient experience of chronic obstructive pulmonary disease (COPD) by analyzing a substantial corpus of social media content. The corpus was sufficiently large to make manual review and manual coding all but impossible to perform in a consistent and systematic fashion. Advanced analytics were applied to the corpus content in the search for associations between symptoms and impacts across the entire text corpus.

Methods

We conducted a retrospective, cross-sectional study of 5663 posts sourced from open blogs and online forum posts published by COPD patients between February 2016 and August 2019. We applied a novel neural network approach to identify a lexicon of community words and phrases used by patients to describe their symptoms. We used this lexicon to explore the relationship between COPD symptoms and disease-related impacts.

Results

We identified a diverse lexicon of community words and phrases for COPD symptoms, including gasping, wheezy, mucus-y, and muck. These symptoms were mentioned in association with specific words and phrases for disease impact such as frightening, breathing discomfort, and difficulty exercising. Furthermore, we found an association between mucus hypersecretion and moderate disease severity, which distinguished mucus from the other main COPD symptoms, namely breathlessness and cough.

Conclusions

We demonstrated the potential of neural networks and advanced analytics to gain patient-focused insights about how each distinct COPD symptom contributes to the burden of chronic and acute respiratory illness. Using a neural network approach, we identified words and phrases for COPD symptoms that were specific to the patient community. Identifying patterns in the association between symptoms and impacts deepened our understanding of the patient experience of COPD. This approach can be readily applied to other disease areas.

COVID-19 Anti-Vaccine Sentiments: Analyses of Comments from Social Media

PURPOSE

This study analyzed the insights and sentiments of COVID-19 anti-vaccine comments from Instagram feeds and Facebook postings. The sentiments related to the acceptance and effectiveness of the vaccines that were on the verge of being made available to the public.

PATIENTS AND METHODS

The qualitative software QSR-NVivo 10 was used to manage, code, and analyse the data.

RESULTS

The analyses uncovered several major issues concerning COVID-19 vaccine hesitancy. The production of the COVID-19 vaccine at an unprecedented speed evoked the fear of skipping steps that would compromise vaccine safety. The unknown long-term effects and duration of protection erode confidence in taking the vaccines. There were also persistent concerns with regard to vaccine compositions that could be harmful or contain aborted foetal cells. The rate of COVID-19 death was viewed as low. Many interpreted the 95% effectiveness of the COVID-19 vaccine as insufficient. Preference for immunity gains from having an infection was viewed as more effective. Peer-reviewed publication-based data were favoured as a source of trust in vaccination decision-making.

CONCLUSIONS

The anti-COVID-19 vaccine sentiments found in this study provide important insights for the formulation of public health messages to instill confidence in the vaccines.

Spontaneously Generated Online Patient Experience of Modafinil: A Qualitative and NLP Analysis

Objective: To compare the findings from a qualitative and a natural language processing (NLP) based analysis of online patient experience posts on patient experience of the effectiveness and impact of the drug Modafinil.

Methods: Posts (n = 260) from 5 online social media platforms where posts were publicly available formed the dataset/corpus. Three platforms asked posters to give a numerical rating of Modafinil. Thematic analysis: data was coded and themes generated. Data were categorized into PreModafinil, Acquisition, Dosage, and PostModafinil and compared to identify each poster's own view of whether taking Modafinil was linked to an identifiable outcome. We classified this as positive, mixed, negative, or neutral and compared this with numerical ratings. NLP: Corpus text was speech tagged and keywords and key terms extracted. We identified the following entities: drug names, condition names, symptoms, actions, and side-effects. We searched for simple relationships, collocations, and co-occurrences of entities. To identify causal text, we split the corpus into PreModafinil and PostModafinil and used n-gram analysis. To evaluate sentiment, we calculated the polarity of each post between −1 (negative) and +1 (positive). NLP results were mapped to qualitative results.

Results: Posters had used Modafinil for 33 different primary conditions. Eight themes were identified: the reason for taking (condition or symptom), impact of symptoms, acquisition, dosage, side effects, other interventions tried or compared to, effectiveness of Modafinil, and quality of life outcomes. Posters reported perceived effectiveness as follows: 68% positive, 12% mixed, 18% negative. Our classification was consistent with poster ratings. Of the most frequent 100 keywords/keyterms identified by term extraction 88/100 keywords and 84/100 keyterms mapped directly to the eight themes. Seven keyterms indicated negation and temporal states. Sentiment was as follows 72% positive sentiment 4% neutral 24% negative. Matching of sentiment between the qualitative and NLP methods was accurate in 64.2% of posts. If we allow for one category difference matching was accurate in 85% of posts.

Conclusions: User generated patient experience is a rich resource for evaluating real world effectiveness, understanding patient perspectives, and identifying research gaps. Both methods successfully identified the entities and topics contained in the posts. In contrast to current evidence, posters with a wide range of other conditions found Modafinil effective. Perceived causality and effectiveness were identified by both methods demonstrating the potential to augment existing knowledge.

The Ethical Implications of Using Social Media to Engage and Retain Justice-Involved Youth in Behavioral Health Research

Given its popularity among youth ages 13-17, social media is a promising avenue for engaging and retaining historically hard-to-reach youth in longitudinal research. Social media use in longitudinal research involving youth, however, has preceded development of best practices for ethical use. This article describes the ethical challenges and considerations of using social media to engage and retain youth within the context of a randomized controlled trial of a group-based adolescent substance use intervention. Best practices for addressing ethical challenges are also provided using the Belmont Principle as a guiding framework. As social media becomes more commonly used to engage and retain youth in clinical research studies, researchers must address emerging ethical concerns within project protocols.

A Proposed Approach for Conducting Studies That Use Data From Social Media Platforms

The prominence of social media in contemporary society has extended significantly into the health care arena, where both patients and health care providers have used social media platforms to gather, communicate, learn, and share medical content and personal experience in real time. The medical literature has also seen an exponential increase in the number of studies that use data derived from social media coverage of various medical issues and topics. In this guide, we present a step-by-step framework for health care professionals and researchers to conduct studies that use data from social media platforms. We present 6 overarching steps: focus on framing a question that is appropriate for social media evaluation, identification of social media outlet and selection criteria of content, systematic data extraction, assessment of quality of content and sources of bias, analysis of data, and interpretation of study findings. Each step is illustrated with published examples.

What are dental professionals posting on Facebook? A cross-sectional content analysis

OBJECTIVE

To profile the posts on open orthodontic Facebook groups and identify which communication strategies and media modalities generate the most engagement from users.

DESIGN

A cross-sectional content analysis.

SETTING

Facebook Internet-based search.

METHODS

Post data were collected over a one-month period from the 10 largest public orthodontic Facebook groups. Evaluation of group characteristics included membership levels, number of administrators, time each group had been in existence and growth rate of each group. The number of posts, the numbers and types of engagement (likes, emojis, comments, shares) and engagement rate were calculated. The communication strategies (e.g. case presentation, course promotion, etc.) and media modalities (e.g. plain text, photograph, etc.) were recorded.

RESULTS

The study identified 190,268 Facebook members from the 10 largest orthodontic Facebook groups (median 17,811; interquartile range [IQR] 11,977). The median time the groups had existed was six years (median 2175 days; IQR 2311 days) and the median number of new group members in the past month was 1257 (IQR 2773). The median number of new group members in the past month was 1257 (IQR 2773). There were 227 postings during the study period with 2546 engagements. The overall median number of engagements was 196 (IQR 445) and the engagement rate of posts was 1.3% overall. Posts relating to course promotion (n = 63, 28%) followed by product promotion (n = 42, 19%) were the most common. Case presentation style posts accounted for 15% (n = 35). The level of engagement was greater for posts that had a clinical component compared to posts that did not (P < 0.001). For media modality, posts that included a photograph had greater engagement (P < 0.001).

CONCLUSION

There are frequent posts on course and product promotion in orthodontic Facebook groups; however, these are associated with low levels of engagement. Posts that are clinically orientated and include photographs have higher levels of engagement.

Twitter Users' Views on Mental Health Crisis Resolution Team Care Compared With Stakeholder Interviews and Focus Groups: Qualitative Analysis

BACKGROUND

Analyzing Twitter posts enables rapid access to how issues and experiences are socially shared and constructed among communities of health service users and providers, in ways that traditional qualitative methods may not.

OBJECTIVE

To enrich the understanding of mental health crisis care in the United Kingdom, this study explores views on crisis resolution teams (CRTs) expressed on Twitter. We aim to identify the similarities and differences among views expressed on Twitter compared with interviews and focus groups.

METHODS

We used Twitter's advanced search function to retrieve public tweets on CRTs. A thematic analysis was conducted on 500 randomly selected tweets. The principles of refutational synthesis were applied to compare themes with those identified in a multicenter qualitative interview study.

RESULTS

The most popular hashtag identified was #CrisisTeamFail, where posts were principally related to poor quality of care and access, particularly for people given a personality disorder diagnosis. Posts about CRTs giving unhelpful self-management advice were common, as were tweets about resource strains on mental health services. This was not identified in the research interviews. Although each source yielded unique themes, there were some overlaps with themes identified via interviews and focus groups, including the importance of rapid access to care. Views expressed on Twitter were generally more critical than those obtained via face-to-face methods.

CONCLUSIONS

Traditional qualitative studies may underrepresent the views of more critical stakeholders by collecting data from participants accessed via mental health services. Research on social media content can complement traditional or face-to-face methods and ensure that a broad spectrum of viewpoints can inform service development and policy.

Monitoring drug trends in the digital environment-New methods, challenges and the opportunities provided by automated approaches

Developments in information technology have impacted on all areas of modern life and in particular facilitated the growth of globalisation in commerce and communication. Within the drugs area this means that both drugs discourse and drug markets have become increasingly digitally enabled. In response to this, new methods are being developed that attempt to research and monitor the digital environment. In this commentary we present three case studies of innovative approaches and related challenges to software-automated data mining of the digital environment: (i) an e-shop finder to detect e-shops offering new psychoactive substances, (ii) scraping of forum data from online discussion boards, (iii) automated sentiment analysis of discussions in online discussion boards. We conclude that the work presented brings opportunities in terms of leveraging data for developing a more timely and granular understanding of the various aspects of drug-use phenomena in the digital environment. In particular, combining the number of e-shops, discussion posts, and sentiments regarding particular substances could be used for ad hoc risk assessments as well as longitudinal drug monitoring and indicate "online popularity". The main challenges of digital data mining involve data representativity and ethical considerations.

Social Media and Health Care, Part I: Literature Review of Social Media Use by Health Care Providers

BACKGROUND

As the world continues to advance technologically, social media (SM) is becoming an essential part of billions of people's lives worldwide and is affecting almost every industry imaginable. As the world is becoming more digitally oriented, the health care industry is increasingly visualizing SM as an important channel for health care promotion, employment, recruiting new patients, marketing for health care providers (HCPs), building a better brand name, etc. HCPs are bound to ethical principles toward their colleagues, patients, and the public in the digital world as much as in the real world.

OBJECTIVE

This review aims to shed light on SM use worldwide and to discuss how it has been used as an essential tool in the health care industry from the perspective of HCPs.

METHODS

A literature review was conducted between March and April 2020 using MEDLINE, PubMed, Google Scholar, and Web of Science for all English-language medical studies that were published since 2007 and discussed SM use in any form for health care. Studies that were not in English, whose full text was not accessible, or that investigated patients' perspectives were excluded from this part, as were reviews pertaining to ethical and legal considerations in SM use.

RESULTS

The initial search yielded 83 studies. More studies were included from article references, and a total of 158 studies were reviewed. SM uses were best categorized as health promotion, career development or practice promotion, recruitment, professional networking or destressing, medical education, telemedicine, scientific research, influencing health behavior, and public health care issues.

CONCLUSIONS

Multidimensional health care, including the pairing of health care with SM and other forms of communication, has been shown to be very successful. Striking the right balance between digital and traditional health care is important.

Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Background

Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user’s uptake and sustained interactions with these interventions.

Objective

This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs.

Methods

A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included.

Results

A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one’s own health.

Conclusions

Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions.

Ethical Perspectives in Sharing Digital Data for Public Health Surveillance Before and Shortly After the Onset of the COVID-19 Pandemic

Data from digital technologies are increasingly integrated in public health research. In April of 2020, we interviewed a subset of participants (N=25) who completed a survey approximately one month earlier (just prior to the declaration of the COVID-19 pandemic in the United States). Using the survey, we contacted and interviewed participants who had expressed their willingness or unwillingness to share digital data (e.g., from contact tracing apps) for use in public health. We followed a directed content analysis approach for the analysis of the interview data. Among participants who had reported being unwilling to share data, concerns about privacy, confidentiality, and the purpose of the research were cited. During the interviews, 76.9% of the participants who had previously indicated that they were unwilling to share their data, expressed willingness to share data in order to assist with COVID-19 prevention. Our results contribute to our understanding of people's perspectives on sharing personal data and of the way their perspectives can vary as a function of potential uses of their personal information (e.g., prevention of COVID-19).

Public Perspectives of Using Social Media Data to Improve Adverse Drug Reaction Reporting: A Mixed-Methods Study

Introduction

Information on suspected adverse drug reactions (ADRs) voluntarily submitted by patients can be a valuable source of information for improving drug safety; however, public awareness of reporting mechanisms remains low. Whilst methods to automatically detect ADR mentions from social media posts using text mining techniques have been proposed to improve reporting rates, it is unclear how acceptable these would be to social media users.

Objective

The objective of this study was to explore public opinion about using automated methods to detect and report mentions of ADRs on social media to enhance pharmacovigilance efforts.

Methods

Users of the online health discussion forum HealthUnlocked participated in an online survey (N = 1359) about experiences with ADRs, knowledge of pharmacovigilance methods, and opinions about using automated data mining methods to detect and report ADRs. To further explore responses, five qualitative focus groups were conducted with 20 social media users with long-term health conditions.

Results

Participant responses indicated a low awareness of pharmacovigilance methods and ADR reporting. They showed a strong willingness to share health-related social media data about ADRs with researchers and regulators, but were cautious about automated text mining methods of detecting and reporting ADRs.

Conclusions

Social media users value public-facing pharmacovigilance schemes, even if they do not understand the current framework of pharmacovigilance within the UK. Ongoing engagement with users is essential to understand views, share knowledge and respect users’ privacy expectations to optimise future ADR reporting from online health communities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01042-6.

Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review

Background: Text-mining techniques are advancing all the time and vast corpora of social media text can be analyzed for users' views and experiences related to their health. There is great promise for new insights into health issues such as drug side effects and spread of disease, as well as patient experiences of health conditions and health care. However, this emerging field lacks ethical consensus and guidance. We aimed to bring together a comprehensive body of opinion, views, and recommendations in this area so that academic researchers new to the field can understand relevant ethical issues. Methods: After registration of a protocol in PROSPERO, three parallel systematic searches were conducted, to identify academic articles comprising commentaries, opinion, and recommendations on ethical practice in social media text mining for health research and gray literature guidelines and recommendations. These were integrated with social media users' views from qualitative studies. Papers and reports that met the inclusion criteria were analyzed thematically to identify key themes, and an overarching set of themes was deduced. Results: A total of 47 reports and articles were reviewed, and eight themes were identified. Commentators suggested that publicly posted social media data could be used without consent and formal research ethics approval, provided that the anonymity of users is ensured, although we note that privacy settings are difficult for users to navigate on some sites. Even without the need for formal approvals, we note ethical issues: to actively identify and minimize possible harms, to conduct research for public benefit rather than private gain, to ensure transparency and quality of data access and analysis methods, and to abide by the law and terms and conditions of social media sites. Conclusion: Although social media text mining can often legally and reasonably proceed without formal ethics approvals, we recommend improving ethical standards in health-related research by increasing transparency of the purpose of research, data access, and analysis methods; consultation with social media users and target groups to identify and mitigate against potential harms that could arise; and ensuring the anonymity of social media users.

Ethical approval: none sought. How discourse analysts report ethical issues around publicly available online data

Although ethical guidelines for doing Internet research are available, most prominently those of the Association of Internet Researchers ( www.aoir.org ), ethical decision-making for research on publicly available, naturally-occurring data remains a major challenge. As researchers might also turn to others to inform their decisions, this article reviews recent research papers on publicly available, online data. Research involving forums such as Facebook pages, Twitter, YouTube, news comments, blogs, etc. is examined to see how authors report ethical considerations and how they quote these data. We included 132 articles published in discourse analysis-oriented journals between January 2017 and February 2020. Roughly one third of the articles (85 out of 132) did not discuss ethical issues, mostly claiming the data were publicly available. Quotations nevertheless tended to be anonymized, although retrievability of posts was generally not taken into account. In those articles in which ethical concerns were reported, related decisions appeared to vary substantially. In most cases it was argued that informed consent was not required. Similarly, approval from research ethics committees was mostly regarded unnecessary. Other ethical issues like consideration of users’ expectations and intentions, freedom of choice, possible harm, sensitive topics, and vulnerable groups were rarely discussed in the articles. We argue for increased attention to ethical issues and legal aspects in discourse analytic articles involving online data beyond mentioning general concerns. Instead, we argue for more involvement of users/participants in ethical decision-making, for consideration of retrievability of posts and for a role for journal editors.