Global and Local Trends Affecting the Experience of US and UK Healthcare Professionals during COVID-19: Twitter Text Analysis

Investigating Health and Well-Being Challenges Faced by an Aging Workforce in the Construction and Nursing Industries: Computational Linguistic Analysis of Twitter Data

BACKGROUND

Construction and nursing are critical industries. Although both careers involve physically and mentally demanding work, the risks to workers during the COVID-19 pandemic are not well understood. Nurses (both younger and older) are more likely to experience the ill effects of burnout and stress than construction workers, likely due to accelerated work demands and increased pressure on nurses during the COVID-19 pandemic. In this study, we analyzed a large social media data set using advanced natural language processing techniques to explore indicators of the mental status of workers across both industries before and during the COVID-19 pandemic.

OBJECTIVE

This social media analysis aims to fill a knowledge gap by comparing the tweets of younger and older construction workers and nurses to obtain insights into any potential risks to their mental health due to work health and safety issues.

METHODS

We analyzed 1,505,638 tweets published on Twitter (subsequently rebranded as X) by younger and older (aged <45 vs >45 years) construction workers and nurses. The study period spanned 54 months, from January 2018 to June 2022, which equates to approximately 27 months before and 27 months after the World Health Organization declared COVID-19 a global pandemic on March 11, 2020. The tweets were analyzed using big data analytics and computational linguistic analyses.

RESULTS

Text analyses revealed that nurses made greater use of hashtags and keywords (both monograms and bigrams) associated with burnout, health issues, and mental health compared to construction workers. The COVID-19 pandemic had a pronounced effect on nurses' tweets, and this was especially noticeable in younger nurses. Tweets about health and well-being contained more first-person singular pronouns and affect words, and health-related tweets contained more affect words. Sentiment analyses revealed that, overall, nurses had a higher proportion of positive sentiment in their tweets than construction workers. However, this changed markedly during the COVID-19 pandemic. Since early 2020, sentiment switched, and negative sentiment dominated the tweets of nurses. No such crossover was observed in the tweets of construction workers.

CONCLUSIONS

The social media analysis revealed that younger nurses had language use patterns consistent with someone experiencing the ill effects of burnout and stress. Older construction workers had more negative sentiments than younger workers, who were more focused on communicating about social and recreational activities rather than work matters. More broadly, these findings demonstrate the utility of large data sets enabled by social media to understand the well-being of target populations, especially during times of rapid societal change.

Online social media poses opportunities and risks in autistic youth: implications for services from a qualitative study

Background

Autistic people are vulnerable to developing mental health problems due to their difficulties in managing social situations and interpersonal relationships. The popular online social media (OSM) can be a potential solution to these concerns for their social lives as it allows non-face-to-face social interactions, however it remained unclear how this group is using these online platforms. This study explored their experiences of using online social media, and their perceived benefits and risks associated with this use.

Method

Qualitative data was collected through in-depth face to face interviews. We recruited 13 autistic young adults who were with normal intelligence from two community centers in Hong Kong. Interviews were conducted in a semi-structured format by experienced clinical psychologist and social workers.

Results

Four themes were identified from the data, namely: (1) Paradox of using OSM to supplement social needs; (2) Unpleasant social interactions in the online environment; (3) Restricted and repetitive pattern of interest leading to troubles in OSM use, and; (4) Privacy and personal safety issues. The results suggested that while OSM could be a useful tool for our participants to connect with existing friends and to meet new ones, their limitations, such as difficulties in understanding languages and social interaction as well as restricted patterns of interests could potentially put them at risk, including interpersonal conflicts, cyber-bullying, financial scams, as well as unwanted sexual experiences. These experiences not only paradoxically increased their sense of loneliness and their distance from others, but also resulted in a negative impact on their mood and functioning.

Conclusion

This qualitative study provided some insights into the OSM use among autistic young adults. OSM could be a useful tool to overcome potential limitations in social interactions, but at the same time it could potentially bring detrimental consequences. In order to maximize the benefits of online social networking, there is a need for timely guidance and support to use OSM among autists, and for psychoeducation to promote awareness, and enable adequate skills and behaviors attainment associated with safe OSM use.

Web-Based Conversations Regarding Fathers Before and During the COVID-19 Pandemic: Qualitative Content Analysis

BACKGROUND

Studies of new and expecting parents largely focus on the mother, leaving a gap in knowledge about fathers.

OBJECTIVE

This study aimed to understand web-based conversations regarding new and expecting fathers on social media and to explore whether the COVID-19 pandemic has changed the web-based conversation.

METHODS

A social media analysis was conducted. Brandwatch (Cision) captured social posts related to new and expecting fathers between February 1, 2019, and February 12, 2021. Overall, 2 periods were studied: 1 year before and 1 year during the pandemic. SAS Text Miner analyzed the data and produced 47% (9/19) of the topics in the first period and 53% (10/19) of the topics in the second period. The 19 topics were organized into 6 broad themes.

RESULTS

Overall, 26% (5/19) of the topics obtained during each period were the same, showing consistency in conversation. In total, 6 broad themes were created: fatherhood thoughts, fatherhood celebrations, advice seeking, fatherhood announcements, external parties targeting fathers, and miscellaneous.

CONCLUSIONS

Fathers use social media to make announcements, celebrate fatherhood, seek advice, and interact with other fathers. Others used social media to advertise baby products and promote baby-related resources for fathers. Overall, the arrival of the COVID-19 pandemic appeared to have little impact on the excitement and resiliency of new fathers as they transition to parenthood. Altogether, these findings provide insight and guidance on the ways in which public health professionals can rapidly gather information about special populations-such as new and expecting fathers via the web-to monitor their beliefs, attitudes, emotional reactions, and unique lived experiences in context (ie, throughout a global pandemic).

HJ-Biplot as a Tool to Give an Extra Analytical Boost for the Latent Dirichlet Assignment (LDA) Model: With an Application to Digital News Analysis about COVID-19

This work objective is to generate an HJ-biplot representation for the content analysis obtained by latent Dirichlet assignment (LDA) of the headlines of three Spanish newspapers in their web versions referring to the topic of the pandemic caused by the SARS-CoV-2 virus (COVID-19) with more than 500 million affected and almost six million deaths to date. The HJ-biplot is used to give an extra analytical boost to the model, it is an easy-to-interpret multivariate technique which does not require in-depth knowledge of statistics, allows capturing the relationship between the topics about the COVID-19 news and the three digital newspapers, and it compares them with LDAvis and heatmap representations, the HJ-biplot provides a better representation and visualization, allowing us to analyze the relationship between each newspaper analyzed (column markers represented by vectors) and the 14 topics obtained from the LDA model (row markers represented by points) represented in the plane with the greatest informative capacity. It is concluded that the newspapers El Mundo and 20 M present greater homogeneity between the topics published during the pandemic, while El País presents topics that are less related to the other two newspapers, highlighting topics such as t_12 (Government_Madrid) and t_13 (Government_millions).