Feeling the Void: Lack of Support for Isolation and Sleep Difficulties in Pregnant Women during the COVID-19 Pandemic Revealed by Twitter Data Analysis
Abstract:Pregnant women face many physical and psychological changes during their pregnancy. It is known that stress, caused by many factors and life events such as the COVID-19 pandemic, can negatively impact the health of mothers and offspring. It is the first time social media, such as Twitter, are available and commonly used during a global pandemic; this allows access to a rich set of data. The objective of this study was to characterize the content of an international sample of tweets related to pregnancy and men… Show more
“…At the end of the screening process, 19 articles were included in the systematic review. 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 Fig. 1 Flow diagram of the study-selection process.…”
Section: Resultsmentioning
confidence: 99%
“…Among the 19 retrieved articles, 15 used a single-data source, whereas four used a combination of two or more data sets. In particular, Twitter was the source most frequently used alone (n = 4), 36 , 46 , 51 , 52 and in combination (n = 3) with YouTube and a forum, 37 Geographic information system (GIS) 39 and Weibo. 47 Google Trends was the second most frequently used data source (n = 6); 38 , 41 , 43 , 44 , 48 , 49 one study investigated Weibo 40 data and another investigated Baidu 34 data alone.…”
Section: Resultsmentioning
confidence: 99%
“…Regarding the country where the studies were conducted, four were internationally based, 41 , 42 , 43 , 52 whereas the rest were carried out in a single country. Specifically, the US was the most frequently explored country (n = 5), 36 , 38 , 39 , 46 , 50 followed by China (n = 3) 34 , 40 , 47 (including one study that compared data between Wuhan [China] and the Lombardy region [Italy]), 47 India (n = 3), 44 , 48 , 49 Australia, 35 , 51 Canada 45 and Spain.…”
Objectives
At the end of 2019, an acute infectious pneumonia (coronavirus disease 2019 [COVID-19]) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in Wuhan, China, and subsequently spread around the world starting a pandemic. Globally, to date, there have been >118 million confirmed cases, including >2 million deaths. In this context, it has been shown that the psychological impact of the pandemic is important and that it can be associated with an increase in internet searches related to fear, anxiety, depression, as well as protective behaviours, health knowledge and even maladaptive behaviours.
Study design
This is a systematic review.
Methods
This review aims to collect, analyse and synthesise available evidence on novel data streams for surveillance purposes and/or their potential for capturing the public reaction to epidemic outbreaks, particularly focusing on mental health effects and emotions.
Results
At the end of the screening process, 19 articles were included in this systematic review. Our results show that the COVID-19 pandemic had a great impact on internet searches for mental health of entire populations, which manifests itself in a significant increase of depressed, anxious and stressed internet users’ emotions.
Conclusions
Novel data streams can support public health experts and policymakers in establishing priorities and setting up long-term strategies to mitigate symptoms and tackle mental health disorders.
“…At the end of the screening process, 19 articles were included in the systematic review. 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 Fig. 1 Flow diagram of the study-selection process.…”
Section: Resultsmentioning
confidence: 99%
“…Among the 19 retrieved articles, 15 used a single-data source, whereas four used a combination of two or more data sets. In particular, Twitter was the source most frequently used alone (n = 4), 36 , 46 , 51 , 52 and in combination (n = 3) with YouTube and a forum, 37 Geographic information system (GIS) 39 and Weibo. 47 Google Trends was the second most frequently used data source (n = 6); 38 , 41 , 43 , 44 , 48 , 49 one study investigated Weibo 40 data and another investigated Baidu 34 data alone.…”
Section: Resultsmentioning
confidence: 99%
“…Regarding the country where the studies were conducted, four were internationally based, 41 , 42 , 43 , 52 whereas the rest were carried out in a single country. Specifically, the US was the most frequently explored country (n = 5), 36 , 38 , 39 , 46 , 50 followed by China (n = 3) 34 , 40 , 47 (including one study that compared data between Wuhan [China] and the Lombardy region [Italy]), 47 India (n = 3), 44 , 48 , 49 Australia, 35 , 51 Canada 45 and Spain.…”
Objectives
At the end of 2019, an acute infectious pneumonia (coronavirus disease 2019 [COVID-19]) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in Wuhan, China, and subsequently spread around the world starting a pandemic. Globally, to date, there have been >118 million confirmed cases, including >2 million deaths. In this context, it has been shown that the psychological impact of the pandemic is important and that it can be associated with an increase in internet searches related to fear, anxiety, depression, as well as protective behaviours, health knowledge and even maladaptive behaviours.
Study design
This is a systematic review.
Methods
This review aims to collect, analyse and synthesise available evidence on novel data streams for surveillance purposes and/or their potential for capturing the public reaction to epidemic outbreaks, particularly focusing on mental health effects and emotions.
Results
At the end of the screening process, 19 articles were included in this systematic review. Our results show that the COVID-19 pandemic had a great impact on internet searches for mental health of entire populations, which manifests itself in a significant increase of depressed, anxious and stressed internet users’ emotions.
Conclusions
Novel data streams can support public health experts and policymakers in establishing priorities and setting up long-term strategies to mitigate symptoms and tackle mental health disorders.
“…Since Twitter is a widely accessible and used public platform, tweets would be considered public conversation and hence publicly available information (Lachmar et al, 2017;Talbot et al, 2021). In this study, we do not specify usernames, user id, location, or any other identifiable information for our analysis.…”
Section: Use Of Twitter Data and Ethicsmentioning
confidence: 99%
“…With the exception of the few examples that have been paraphrased in Table 1, we have avoided quoting tweets from the data set to avoid any personally identifiable information. Since we have protected privacy of Twitter users and confidentiality by retracting any identifiable information and rephrasing tweets in the paper, ethics approval to use the data was not required (Talbot et al, 2021;Trochim & Donnelly, 2001).…”
Aim/Purpose: This article explores the content of PhD student tweets. It has three main aims: (a) to examine what is discussed regarding the PhD process, (b) to evaluate whether tweets express primarily positive or negative sentiments, and (c) to uncover the key themes discussed in both positive and negative tweets.
Background: Recent surveys of PhD students have raised concerns about their wellbeing by pointing to high prevalence rates of adverse mental health conditions. However, our understanding of which factors pose the highest risks is still evolving. Self-selection into surveys also raises the possibility of discounting positive aspects of the PhD experience. We use a different data source (Twitter) to explore both these issues.
Methodology: Using 16,928 tweets with the Twitter hashtags #phdlife and #phdchat, we first conduct dictionary-based sentiment analysis in R to determine whether tweets are dominated by positive or negative sentiment. We then hand-code the dominant sentiment of a randomly selected subset of 1,994 tweets and qualitatively analyse positive and negative tweets separately to uncover the key themes in each category.
Contribution: This article contributes to the emerging literature on the wellbeing and mental health of PhD students by using a novel data source (tweets). It highlights both positive and negative aspects of the PhD student experience.
Findings: We find that most tweets express positive rather than negative sentiment, indicating that PhD students do enjoy many aspects of their experience. Negative tweets are dominated by mental health concerns. They also highlight problems with academic culture (especially the normalization of overwork) and the effects of the pandemic on students.
Recommendations for Practitioners: Our results indicate that there is a need to change the academic culture of normalizing overwork, ensure adequate institutional provision of mental health support and ability to spot signs of emotional distress, devise strategies to combat the imposter phenomenon, and respond to the particular challenges that the pandemic has created for PhD students.
Recommendation for Researchers: The authors recommend that future research explore the specific challenges and opportunities faced by PhD students in different disciplines and geographical locations. As the data used here were collected during the pandemic, it would be useful to track post-pandemic sentiments to observe changes.
Impact on Society: Improving the graduate experience of PhD students and providing them adequate mental health support will help to ensure their continued productivity and wellbeing.
Future Research: Future research in this area should focus on the efficacy of different interventions to address key problems, such as the imposter phenomenon, stress, anxiety, depression, and isolation.
The impact of the Covid‐19 pandemic and ensuing social restrictions has been profound, affecting the health, livelihoods, and wellbeing of populations worldwide. Studies have shown widespread effects on mental health, with an increase in stress, loneliness, and depression symptoms related to the pandemic. Media plays a critical role in containing and managing crises, by informing society and fostering positive behavior change. Social restrictions have led to a large increase in reliance on online media channels, and this can influence mental health and wellbeing. Anxiety levels, for instance, may be exacerbated by exposure to Covid‐related content, contagion of negative sentiment among social networks, and “fake news.” In some cases, this may trigger abstinence, leading to isolation and limited access to vital information. To be able to communicate distressing news during crises while protecting the wellbeing of individuals is not trivial; it requires a deeper understanding of people's emotional response to online and social media content. This paper selectively reviews research into consequences of social media usage and online news consumption for wellbeing and mental health, focusing on and discussing their effects in the context of the pandemic. Advances in Artificial Intelligence and Data Science, for example, Natural Language Processing, Sentiment Analysis, and Emotion Recognition, are discussed as useful methods for investigating effects on population mental health as the pandemic situation evolves. We present suggestions for future research, and for using these advances to assess large data sets of users' online content, to potentially inform strategies that enhance the mental health of social media users going forward.
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