Using Social Media to Generate and Collect Primary Data: The #ShowsWorkplaceCompassion Twitter Research Campaign

Harvesting Twitter Data for Studying Motor Behavior in Disabled Populations: An Introduction and Tutorial in Python

Social media platforms are rich and dynamic spaces where individuals communicate on a person-to-person level and to broader audiences. These platforms provide a wealth of publicly available data that can shed light on the lived experiences of people from numerous clinical populations. Twitter can be used to examine individual expressions and community discussions about specific characteristics (e.g., motor skills, burnout) associated with a diagnostic group. These data are useful for understanding the perspectives of a diverse, international group of self-advocates representing a wide range of clinical populations. Here, we provide a framework for how to harvest data from Twitter through their free, academic researcher application programming interface access using Python, a free, open-source programming language. We also provide a sample data set harvested using this framework and a set of analyses on these data specifically related to motor differences in neurodevelopmental conditions. This framework offers a cost-effective and flexible means of harvesting and analyzing Twitter data. Researchers should utilize these resources to advance our understanding of the lived experiences of clinical populations through social media platforms and to determine the critical questions that are of most importance to improving quality of life.

The impact of organizational compassion in health care on clinicians: A scoping review

BACKGROUND

The unprecedented exodus of workers from the healthcare system is a patient safety crisis. Organizational compassion in health care is the proactive, systematic, and continuous identification, alleviation, and prevention of all sources of suffering.

AIMS

This scoping review aimed to describe the evidence regarding the impact of organizational compassion on clinicians, identify gaps, and provide recommendations for future research.

METHODS

A comprehensive librarian-assisted database search was conducted. Databases searched were PubMed, SCOPUS, EMBASE, Web of Science, PsychInfo, and Business Source Complete. Combinations of search terms regarding health care, compassion, organizational compassion, and workplace suffering were used. The search strategy was limited to English language articles and those published between 2000 and 2021.

RESULTS

Database search yielded 781 articles. After removing duplicates, 468 were screened by title and abstract, and 313 were excluded. One-hundred and fifty-five underwent full-text screening, and 137 were removed, leaving 18 eligible articles, two of which were set in the United States. Ten articles evaluated barriers or facilitators to organizational compassion, four evaluated elements of compassionate leadership, and four evaluated the Schwartz Center Rounds intervention. Several described the need to create systems that are compassionate to clinicians. Lack of time, support staff, and resources impeded the delivery of such interventions.

LINKING EVIDENCE TO ACTION

Little research has been done to understand and evaluate the impact of compassion on US clinicians. Given the workforce crisis in American health care and the potential positive impact of increasing compassion for clinicians, there is an urgent need for researchers and healthcare administrators to fill this gap.

Student nurses' views on shift patterns: What do they prefer and why? Results from a Tweetchat

Aim

The main aim of the study was to understand student nurses’ views around shift patterns.

Design

Qualitative study.

Method

We held a Tweetchat in May 2019, where we asked questions around the frequency of 12‐hr shifts working on placement; schedule flexibility while on placement; which shift patterns they preferred and why. Data from the Tweetchat were analysed using reflexive thematic analysis to generate themes from initial codes.

Results

Seventy‐three nursing students participated in the Tweetchat. The majority reported that they work 12‐hr shifts on placements, particularly when based in a hospital. We identified three themes: ‘Achieving a personal equilibrium’; ‘Meeting the needs of the care environment’; ‘Factors affecting negotiation capacity’. Data highlighted a conflict for most students, where they preferred 12‐hr shifts because of more time off for study, paid work and leisure, while acknowledging 12‐hr shifts negatively affected their fatigue, exhaustion and led them to follow a poor diet and neglect exercise and sleep.

Coronavirus: the 7th C affecting the 6Cs. A focus on compassion, care and touch

The C0VID-19 pandemic has challenged everyone in society, from children who are no longer able to attend school and nursery to adults trying to juggle working at home and vulnerable members of society who have needed to self-isolate. NHS staff and key workers also need to juggle their family situations and many will have to adapt their practice and ways of working to address the demands placed on the NHS during this time. The current pandemic has altered the nature of services being provided to patients, and staff are now wearing personal protective equipment, with many being redeployed to ward areas. This article considers the 6Cs of nursing and the challenges faced by staff during the COVID-19 pandemic, with a primary focus on care and compassion. The vital role that touch has in the care of the patient and family is also considered.

Tweets by People With Arthritis During the COVID-19 Pandemic: Content and Sentiment Analysis

BACKGROUND

Emerging evidence suggests that people with arthritis are reporting increased physical pain and psychological distress during the COVID-19 pandemic. At the same time, Twitter's daily usage has surged by 23% throughout the pandemic period, presenting a unique opportunity to assess the content and sentiment of tweets. Individuals with arthritis use Twitter to communicate with peers, and to receive up-to-date information from health professionals and services about novel therapies and management techniques.

OBJECTIVE

The aim of this research was to identify proxy topics of importance for individuals with arthritis during the COVID-19 pandemic, and to explore the emotional context of tweets by people with arthritis during the early phase of the pandemic.

METHODS

From March 20 to April 20, 2020, publicly available tweets posted in English and with hashtag combinations related to arthritis and COVID-19 were extracted retrospectively from Twitter. Content analysis was used to identify common themes within tweets, and sentiment analysis was used to examine positive and negative emotions in themes to understand the COVID-19 experiences of people with arthritis.

RESULTS

In total, 149 tweets were analyzed. The majority of tweeters were female and were from the United States. Tweeters reported a range of arthritis conditions, including rheumatoid arthritis, systemic lupus erythematosus, and psoriatic arthritis. Seven themes were identified: health care experiences, personal stories, links to relevant blogs, discussion of arthritis-related symptoms, advice sharing, messages of positivity, and stay-at-home messaging. Sentiment analysis demonstrated marked anxiety around medication shortages, increased physical symptom burden, and strong desire for trustworthy information and emotional connection.

CONCLUSIONS

Tweets by people with arthritis highlight the multitude of concurrent concerns during the COVID-19 pandemic. Understanding these concerns, which include heightened physical and psychological symptoms in the context of treatment misinformation, may assist clinicians to provide person-centered care during this time of great health uncertainty.

Ways of Knowing Compassion: How Do We Come to Know, Understand, and Measure Compassion When We See It?

Over the last decade, empirical research on compassion has burgeoned in the biomedical, clinical, translational, and foundational sciences. Increasingly sophisticated understandings and measures of compassion continue to emerge from the abundance of multidisciplinary and cross-disciplinary studies. Naturally, the diversity of research methods and theoretical frameworks employed presents a significant challenge to consensus and synthesis of this knowledge. To bring the empirical findings of separate and sometimes siloed disciplines into conversation with one another requires an examination of their disparate assumptions about what compassion is and how it can be known. Here, we present an integrated theoretical review of methodologies used in the empirical study of compassion. Our goal is to highlight the distinguishing features of each of these ways of knowing compassion, as well as the strengths and limitations of applying them to specific research questions. We hope this will provide useful tools for selecting methods that are tailored to explicit objectives (methods matching), taking advantage of methodological complementarity across disciplines (methods mixing), and incorporating the empirical study of compassion into fields in which it may be missing.

Public Concern About Monitoring Twitter Users and Their Conversations to Recruit for Clinical Trials: Survey Study

Background

Social networks such as Twitter offer the clinical research community a novel opportunity for engaging potential study participants based on user activity data. However, the availability of public social media data has led to new ethical challenges about respecting user privacy and the appropriateness of monitoring social media for clinical trial recruitment. Researchers have voiced the need for involving users’ perspectives in the development of ethical norms and regulations.

Objective

This study examined the attitudes and level of concern among Twitter users and nonusers about using Twitter for monitoring social media users and their conversations to recruit potential clinical trial participants.

Methods

We used two online methods for recruiting study participants: the open survey was (1) advertised on Twitter between May 23 and June 8, 2017, and (2) deployed on TurkPrime, a crowdsourcing data acquisition platform, between May 23 and June 8, 2017. Eligible participants were adults, 18 years of age or older, who lived in the United States. People with and without Twitter accounts were included in the study.

Results

While nearly half the respondents—on Twitter (94/603, 15.6%) and on TurkPrime (509/603, 84.4%)—indicated agreement that social media monitoring constitutes a form of eavesdropping that invades their privacy, over one-third disagreed and nearly 1 in 5 had no opinion. A chi-square test revealed a positive relationship between respondents’ general privacy concern and their average concern about Internet research (P<.005). We found associations between respondents’ Twitter literacy and their concerns about the ability for researchers to monitor their Twitter activity for clinical trial recruitment (P=.001) and whether they consider Twitter monitoring for clinical trial recruitment as eavesdropping (P<.001) and an invasion of privacy (P=.003). As Twitter literacy increased, so did people’s concerns about researchers monitoring Twitter activity. Our data support the previously suggested use of the nonexceptionalist methodology for assessing social media in research, insofar as social media-based recruitment does not need to be considered exceptional and, for most, it is considered preferable to traditional in-person interventions at physical clinics. The expressed attitudes were highly contextual, depending on factors such as the type of disease or health topic (eg, HIV/AIDS vs obesity vs smoking), the entity or person monitoring users on Twitter, and the monitored information.

Conclusions

The data and findings from this study contribute to the critical dialogue with the public about the use of social media in clinical research. The findings suggest that most users do not think that monitoring Twitter for clinical trial recruitment constitutes inappropriate surveillance or a violation of privacy. However, researchers should remain mindful that some participants might find social media monitoring problematic when connected with certain conditions or health topics. Further research should isolate factors that influence the level of concern among social media users across platforms and populations and inform the development of more clear and consistent guidelines.