Investigation of Geographic and Macrolevel Variations in LGBTQ Patient Experiences: Longitudinal Social Media Analysis

Mpox Discourse on Twitter by Sexual Minority Men and Gender-Diverse Individuals: Infodemiological Study Using BERTopic

BACKGROUND

The mpox outbreak resulted in 32,063 cases and 58 deaths in the United States and 95,912 cases worldwide from May 2022 to March 2024 according to the US Centers for Disease Control and Prevention (CDC). Like other disease outbreaks (eg, HIV) with perceived community associations, mpox can create the risk of stigma, exacerbate homophobia, and potentially hinder health care access and social equity. However, the existing literature on mpox has limited representation of the perspective of sexual minority men and gender-diverse (SMMGD) individuals.

OBJECTIVE

To fill this gap, this study aimed to synthesize themes of discussions among SMMGD individuals and listen to SMMGD voices for identifying problems in current public health communication surrounding mpox to improve inclusivity, equity, and justice.

METHODS

We analyzed mpox-related posts (N=8688) posted between October 2020 and September 2022 by 2326 users who self-identified on Twitter/X as SMMGD and were geolocated in the United States. We applied BERTopic (a topic-modeling technique) on the tweets, validated the machine-generated topics through human labeling and annotations, and conducted content analysis of the tweets in each topic. Geographic analysis was performed on the size of the most prominent topic across US states in relation to the University of California, Los Angeles (UCLA) lesbian, gay, and bisexual (LGB) social climate index.

RESULTS

BERTopic identified 11 topics, which annotators labeled as mpox health activism (n=2590, 29.81%), mpox vaccination (n=2242, 25.81%), and adverse events (n=85, 0.98%); sarcasm, jokes, and emotional expressions (n=1220, 14.04%); COVID-19 and mpox (n=636, 7.32%); government or public health response (n=532, 6.12%); mpox symptoms (n=238, 2.74%); case reports (n=192, 2.21%); puns on the naming of the virus (ie, mpox; n=75, 0.86%); media publicity (n=59, 0.68%); and mpox in children (n=58, 0.67%). Spearman rank correlation indicated significant negative correlation (ρ=-0.322, P=.03) between the topic size of health activism and the UCLA LGB social climate index at the US state level.

CONCLUSIONS

Discussions among SMMGD individuals on mpox encompass both utilitarian (eg, vaccine access, case reports, and mpox symptoms) and emotionally charged (ie, promoting awareness, advocating against homophobia, misinformation/disinformation, and health stigma) themes. Mpox health activism is more prevalent in US states with lower LGB social acceptance, suggesting a resilient communicative pattern among SMMGD individuals in the face of public health oppression. Our method for social listening could facilitate future public health efforts, providing a cost-effective way to capture the perspective of impacted populations. This study illuminates SMMGD engagement with the mpox discourse, underscoring the need for more inclusive public health programming. Findings also highlight the social impact of mpox: health stigma. Our findings could inform interventions to optimize the delivery of informational and tangible health resources leveraging computational mixed-method analyses (eg, BERTopic) and big data.

Health activism, vaccine, and mpox discourse: BERTopic based mixed-method analyses of tweets from sexual minority men and gender diverse (SMMGD) individuals in the U.S

Objectives

To synthesize discussions among sexual minority men and gender diverse (SMMGD) individuals on mpox, given limited representation of SMMGD voices in existing mpox literature.

Methods

BERTopic (a topic modeling technique) was employed with human validations to analyze mpox-related tweets (n = 8,688; October 2020-September 2022) from 2,326 self-identified SMMGD individuals in the U.S.; followed by content analysis and geographic analysis.

Results

BERTopic identified 11 topics: health activism (29.81%); mpox vaccination (25.81%) and adverse events (0.98%); sarcasm, jokes, emotional expressions (14.04%); COVID-19 and mpox (7.32%); government/public health response (6.12%); mpox symptoms (2.74%); case reports (2.21%); puns on the virus' naming (i.e., monkeypox; 0.86%); media publicity (0.68%); mpox in children (0.67%). Mpox health activism negatively correlated with LGB social climate index at U.S. state level, ρ = -0.322, p = 0.031.

Conclusions

SMMGD discussions on mpox encompassed utilitarian (e.g., vaccine access, case reports, mpox symptoms) and emotionally-charged themes-advocating against homophobia, misinformation, and stigma. Mpox health activism was more prevalent in states with lower LGB social acceptance.

Public Health Implications

Findings illuminate SMMGD engagement with mpox discourse, underscoring the need for more inclusive health communication strategies in infectious disease outbreaks to control associated stigma.

A Decade of Tweets: Visualizing Racial Sentiments Towards Minoritized Groups in the United States Between 2011 and 2021

BACKGROUND

Research has demonstrated the negative impact of racism on health, yet the measurement of racial sentiment remains challenging. This article provides practical guidance on using social media data for measuring public sentiment.

METHODS

We describe the main steps of such research, including data collection, data cleaning, binary sentiment analysis, and visualization of findings. We randomly sampled 55,844,310 publicly available tweets from 1 January 2011 to 31 December 2021 using Twitter's Application Programming Interface. We restricted analyses to US tweets in English using one or more 90 race-related keywords. We used a Support Vector Machine, a supervised machine learning model, for sentiment analysis.

RESULTS

The proportion of tweets referencing racially minoritized groups that were negative increased at the county, state, and national levels, with a 16.5% increase at the national level from 2011 to 2021. Tweets referencing Black and Middle Eastern people consistently had the highest proportion of negative sentiment compared with all other groups. Stratifying temporal trends by racial and ethnic groups revealed unique patterns reflecting historical events specific to each group, such as the killing of George Floyd regarding sentiment of posts referencing Black people, discussions of the border crisis near the 2018 midterm elections and anti-Latinx sentiment, and the emergence of COVID-19 and anti-Asian sentiment.

CONCLUSIONS

This study demonstrates the utility of social media data as a quantitative means to measure racial sentiment over time and place. This approach can be extended to a range of public health topics to investigate how changes in social and cultural norms impact behaviors and policy.A supplemental digital video is available at http://links.lww.com/EDE/C91.

Patient Experience of Sjögren's Disease and its Multifaceted Impact on Patients' Lives

INTRODUCTION

The symptoms associated with Sjögren's disease (Sjögren's) are well-documented from the physician's perspective. However, from the patient's perspective, there is limited information on symptoms and their impact on health-related quality of life (HRQoL). This study aimed to provide an expanded understanding of patients' experience of Sjögren's and how symptoms impact HRQoL using a novel multi-method social media listening (SML) approach.

METHODS

A total of 26,950 social media posts with relevant content on Sjögren's posted by social media users from the USA, Canada, Australia, UK, France, Germany, Italy, Spain and China were analysed using an artificial intelligence natural language processing tool to explore patient conversations. Symptoms by level of impact on patients were characterised based on 'commonness' and 'bothersomeness'. Applied concept association analysis was used to assess relationships between symptom domains and impact domains. A qualitative framework was applied to explore words and phrases patients use to describe symptoms and their impacts.

RESULTS

Five of the identified symptom domains were very impactful: Pain; Dry Mouth and Throat; Fatigue, Energy and Sleep; Emotional Balance; and Dry Eye. The symptom domains Pain and Dry Mouth and Throat were the most common, while those of Emotional Balance and Fatigue, Energy and Sleep were the most bothersome. Symptom domains most closely associated with four HRQoL impact domains were Fatigue, Energy and Sleep, Dry Mouth and Throat and Dry Eye with Daily Functioning; Fatigue, Energy and Sleep with Financial Health; Emotional Balance with Psychological Wellbeing and Gynaecological Issues with Social Wellbeing.

CONCLUSION

The results of this SML study show that Sjögren's affects diverse aspects of patients' lives, with symptoms extending beyond dry eyes and mouth and impacting daily living and functioning. Because symptoms may affect patients differently, these results highlight the importance of measuring impact on HRQoL to assess patient outcomes and treatment options in routine clinical practice and clinical trials.

They "Don't Know How to Deal with People Like Me": Assessing Health Care Experiences of Gender Minorities in Indiana

Purpose

Within the LGBTQ+ community, the transgender and nonbinary (TGNB) population experience a disproportionate amount of discrimination when seeking health care. Such disparities may arise from lack of proper medical training and resources for providers or biases. In this study, we examine the health care experiences of TGNB individuals living in Southern Indiana.

Methods

We analyzed responses from TGNB respondents to an LGBTQ+ health care needs assessment survey in Southern Indiana. Respondents were asked about demographic data, their self-assessed health status, quality of health care received, whether they have a provider with whom they feel comfortable sharing their gender identity with, and if they have to commute to see their provider. Finally, respondents were asked an open-ended question about their health care experiences while living in Southern Indiana. Responses were coded and several themes emerged and were analyzed.

Results

Eighty-five TGNB individuals completed our survey. Less than half of respondents indicated that they had an LGBTQ+-welcoming provider (44.7%). Individuals with an LGBTQ+-welcoming provider were more likely to report their self-assessed health as excellent/good (p=0.02) and quality of health as excellent/very good (p=0.03) compared to individuals without an LGBTQ+-welcoming provider. Five themes emerged from the write-in responses (n=64): discrimination (34.4%), invalidation (32.8%), distrust (28.1%), logistic concerns (35.9%), and positive experiences (35.9%).

Conclusion

The TGNB community living in Southern Indiana reports numerous barriers related to provider attitudes when obtaining health care. Additional training is needed to address provider biases and improve LGBTQ+ community health disparities.

Risks and Opportunities to Ensure Equity in the Application of Big Data Research in Public Health

The big data revolution presents an exciting frontier to expand public health research, broadening the scope of research and increasing the precision of answers. Despite these advances, scientists must be vigilant against also advancing potential harms toward marginalized communities. In this review, we provide examples in which big data applications have (unintentionally) perpetuated discriminatory practices, while also highlighting opportunities for big data applications to advance equity in public health. Here, big data is framed in the context of the five Vs (volume, velocity, veracity, variety, and value), and we propose a sixth V, virtuosity, which incorporates equity and justice frameworks. Analytic approaches to improving equity are presented using social computational big data, fairness in machine learning algorithms, medical claims data, and data augmentation as illustrations. Throughout, we emphasize the biasing influence of data absenteeism and positionality and conclude with recommendations for incorporating an equity lens into big data research.

The Impact of Primary Care Providers' Bias on Depression Screening for Lesbian Women

Primary care providers' (PCPs) implicit and explicit bias can adversely affect health outcomes of lesbian women including their mental health. Practice guidelines recommend universal screening for depression in primary care settings, yet the guidelines often are not followed. The intersection of PCPs' implicit and explicit bias toward lesbian women may lead to even lower screening and diagnosis of depression in the lesbian population than in the general population. The purpose of this secondary analysis was to examine the relationship between PCPs' implicit and explicit bias toward lesbian women and their recommendations for depression screening in this population. PCPs (n = 195) in Kentucky completed a survey that included bias measures and screening recommendations for a simulated lesbian patient. Bivariate inferential statistical tests were conducted to compare the implicit and explicit bias scores of PCPs who recommended depression screening and those who did not. PCPs who recommended depression screening demonstrated more positive explicit attitudes toward lesbian women (p < .05) and their implicit bias scores were marginally lower than the providers who did not recommend depression screening (p = .068). Implications for practice: Depression screening rates may be even lower for lesbian women due to implicit and explicit bias toward this population. Training to increase providers' awareness of bias and its harm is the first step to improve primary care for lesbian women. Policies must protect against discrimination based on sexual orientation or gender identity.

A 10-Year Social Media Analysis Exploring Hospital Online Support of Black Lives Matter and the Black Community

IMPORTANCE

Tensions around COVID-19 and systemic racism have raised the question: are hospitals advocating for equity for their Black patients? It is imperative for hospitals to be supportive of the Black community and acknowledge themselves as safe spaces, run by clinicians and staff who care about social justice issues that impact the health of the Black community; without the expression of support, Black patients may perceive hospitals as uncaring and unsafe, potentially delaying or avoiding treatment, which can result in serious complications and death for those with COVID-19.

OBJECTIVE

To explore how hospitals showed public-facing support for the Black community as measured through tweets about social equity or the Black Lives Matter (BLM) movement.

DESIGN, SETTING, AND PARTICIPANTS

Using a retrospective longitudinal cohort study design, tweets from the top 100 ranked hospitals were collected, starting with the most recent over a 10-year span, from May 3, 2009, to June 26, 2020. The date of the George Floyd killing, May 25, 2020, was investigated as a point of interest. Data were analyzed from June 11 to December 4, 2020.

MAIN OUTCOMES AND MEASURES

Tweets were manually identified based on 4 categories: BLM, associated with the BLM movement; Black support, expressed support for Black population within the hospital's community; Black health, pertained to health concerns specific to and the creation of health care for the Black community; or social justice, associated with general social justice terms that were too general to label as Black. If a tweet did not contain any hashtags from these categories, it remained unlabeled.

RESULTS

A total of 281 850 tweets from 90 unique social media accounts were collected. Each handle returned at least 1279 tweets, with 85 handles (94.4%) returning at least 3000 tweets. Tweet publication dates ranged from 2009 to 2020. A total of 274 tweets (0.097%) from 67 handles (74.4%) used a hashtag to support the BLM movement. Among the tweets labeled BLM, the first tweet was published in 2018 and only 4 tweets (1.5%) predated the killing of George Floyd. A similar trend of low signal observed was detected for the other categories (Black support: 244 tweets [0.086%] from 42 handles [46.7%] starting in 2013; Black health: 28 tweets [0.0099%] from 15 handles [16.7%] starting in 2018; social justice: 40 tweets [0.014%] from 21 handles [23.3%] starting in 2015).

CONCLUSIONS AND RELEVANCE

These findings reflect the low signal of tweets regarding the Black community and social justice in a generalized way across approximately 10 years of tweets for all the hospital handles within the data set. From 2009 to 2020, hospitals rarely engaged in issues pertaining to the Black community and if so, only within the last half of this time period. These later entrances into these discussions indicate that these discussions are relatively recent.

Analysis of Social Media Discussions on (#)Diet by Blue, Red, and Swing States in the U.S

The relationship between political affiliations and diet-related discussions on social media has not been studied on a population level. This study used a cost- and -time effective framework to leverage, aggregate, and analyze data from social media. This paper enhances our understanding of diet-related discussions with respect to political orientations in U.S. states. This mixed methods study used computational methods to collect tweets containing "diet" or "#diet" shared in a year, identified tweets posted by U.S. Twitter users, disclosed topics of tweets, and compared democratic, republican, and swing states based on the weight of topics. A qualitative method was employed to code topics. We found 32 unique topics extracted from more than 800,000 tweets, including a wide range of themes, such as diet types and chronic conditions. Based on the comparative analysis of the topic weights, our results revealed a significant difference between democratic, republican, and swing states. The largest difference was detected between swing and democratic states, and the smallest difference was identified between swing and republican states. Our study provides initial insight on the association of potential political leanings with health (e.g., dietary behaviors). Our results show diet discussions differ depending on the political orientation of the state in which Twitter users reside. Understanding the correlation of dietary preferences based on political orientation can help develop targeted and effective health promotion, communication, and policymaking strategies.