Mining long-COVID symptoms from Reddit: characterizing post-COVID syndrome from patient reports

Portrait of mental health identified by people with the post-covid syndrome

OBJECTIVES

This study aimed to produce a patient-centered understanding of mental health symptoms of people with the post-COVID-19 syndrome (PCS).

METHODS

A cross-sectional analysis of 414 participants in a longitudinal study was carried out involving people who self-identified as having symptoms of PCS. People were asked to name their most frequent and most bothersome mental health symptoms affected by PCS using the structure of the Patient Generated Index (PGI). The text threads from the PGI were grouped into topics using BERTopic analysis.

RESULTS

20 topics were identified from 818 text threads referring to PCS mental health symptoms. 35% of threads were identified as relating to anxiety, discussed in terms of five topics: generalized/social anxiety, fear/worry, post-traumatic stress, panic, and nervous. 29% of threads were identified as relating to low mood, represented by five topics: depression, discouragement, emotional distress, sadness, and loneliness. A cognitive domain (22% of threads) was covered by four topics referring to concentration, memory, brain fog, and mental fatigue. Topics related to frustration, anger, irritability. and mood swings (7%) were considered as one domain and there were separate topics related to motivation, insomnia, and isolation.

CONCLUSIONS

This novel method of digital transformation of unstructured text data uncovered different ways in which people think about classical mental health domains. This information could be used to evaluate whether existing measures cover the content identified by people with PCS, to initiate a clinical conversation, or to justify the development of a new measure of the mental health impact of PCS.

Too much focus on your health might be bad for your health: Reddit user's communication style predicts their Long COVID likelihood

Long Covid is a chronic disease that affects more than 65 million people worldwide, characterized by a wide range of persistent symptoms following a Covid-19 infection. Previous studies have investigated potential risk factors contributing to elevated vulnerability to Long Covid. However, research on the social traits associated with affected patients is scarce. This study introduces an innovative methodological approach that allows us to extract valuable insights directly from patients' voices. By analyzing written texts shared on social media platforms, we aim to collect information on the psychological aspects of people who report experiencing Long Covid. In particular, we collect texts of patients they wrote BEFORE they were afflicted with Long Covid. We examined the differences in communication style, sentiment, language complexity, and psychological factors of natural language use among the profiles of 6.107 Reddit users, distinguishing between those who claim they have never contracted Covid -19, those who claim to have had it, and those who claim to have experienced Long Covid symptoms. Our findings reveal that people in the Long Covid group frequently discussed health-related topics before the pandemic, indicating a greater focus on health-related concerns. Furthermore, they exhibited a more limited network of connections, lower linguistic complexity, and a greater propensity to employ emotionally charged expressions than the other groups. Using social media data, we can provide a unique opportunity to explore potential risk factors associated with Long Covid, starting from the patient's perspective.

Compassion Fatigue in a Cohort of South Italian Nurses and Hospital-Based Clinical Social Workers Following COVID-19: A Cross-Sectional Survey

Background/Objective: The COVID-19 pandemic has led to a significant increase in the workloads of healthcare workers (HCWs). The fear of contracting the new virus with the frequent medical consequences has affected their mental health. As a result, they are at high risk of compassion fatigue (CF). In this multicentric study, as a primary objective, we evaluate the incidence and/or prevalence of CF in a cohort of Italian nurses and HCWs (hospital-based clinical social workers of neurological patients) who have contracted SARS-CoV-2 infection. Our secondary aim is to evaluate the difference in experiencing CF between subjects with and without long-term COVID. Methods: In this study, 101 HCWs attending three different neurorehabilitation settings (the Neurorehabilitation Unit of the "Bonino Pulejo" Neurolesi Center of Messina, the Neurorehabilitation Department of Crotone, and the Psychiatric Unit of the University Hospital of Messina) were enrolled from May 2021 to May 2023. Data were collected through self-administered semi-structured interviews. Results: We observed high percentages of CF difficulties in both nurses and HCWs, related to mood alteration in 57.7%, headaches in 44.4%, and fatigue in 62%. Higher percentages were found in individuals with long-term COVID-19, including mood alteration in 93.9%, headache in 88.6%, and memory-related problems in 98.5%. Conclusions: The complexity of a patient's care pathway, especially in chronic disease situations, requires an enormous commitment that can lead to burnout and CF, which should be considered to initiate preventive interventions aimed at helping "those who help", for the well-being of patients, healthcare teams, and healthcare organizations.

Paving the way for COVID survivors' psychosocial rehabilitation: Mining topics, sentiments, and their trajectories over time from Reddit

Objective: This study examined major themes and sentiments and their trajectories and interactions over time using subcategories of Reddit data. The aim was to facilitate decision-making for psychosocial rehabilitation. Materials and Methods: We utilized natural language processing techniques, including topic modeling and sentiment analysis, on a dataset consisting of more than 38,000 topics, comments, and posts collected from a subreddit dedicated to the experiences of people who tested positive for COVID-19. In this longitudinal exploratory analysis, we studied the dynamics between the most dominant topics and subjects' emotional states over an 18-month period. Results: Our findings highlight the evolution of the textual and sentimental status of major topics discussed by COVID survivors over an extended period of time during the pandemic. We particularly studied pre- and post-vaccination eras as a turning point in the timeline of the pandemic. The results show that not only does the relevance of topics change over time, but the emotions attached to them also vary. Major social events, such as the administration of vaccines or enforcement of nationwide policies, are also reflected through the discussions and inquiries of social media users. In particular, the emotional state (i.e., sentiments and polarity of their feelings) of those who have experienced COVID personally. Discussion: Cumulative societal knowledge regarding the COVID-19 pandemic impacts the patterns with which people discuss their experiences, concerns, and opinions. The subjects' emotional state with respect to different topics was also impacted by extraneous factors and events, such as vaccination. Conclusion: By mining major topics, sentiments, and trajectories demonstrated in COVID-19 survivors' interactions on Reddit, this study contributes to the emerging body of scholarship on COVID-19 survivors' mental health outcomes, providing insights into the design of mental health support and rehabilitation services for COVID-19 survivors.

Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing

We used social media data from "covid19positive" subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021-09/2021) and Omicron (12/2021-03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The top five common symptoms extracted in the early period were coughing (57%), fever (55%), loss of sense of smell (41%), headache (40%), and sore throat (40%). During the Delta period, these symptoms remained as the top five symptoms with percent authors reporting symptoms reduced to half or fewer than the early period. During the Omicron period, loss of sense of smell was reported less while sore throat was reported more. Our study demonstrated that NLP can be used to identify COVID-19 cases accurately and extracted symptoms efficiently.

The Long COVID experience from a patient's perspective: a clustering analysis of 27,216 Reddit posts

Objective

This work aims to study the profiles of Long COVID from the perspective of the patients spontaneously sharing their experiences and symptoms on Reddit.

Methods

We collected 27,216 posts shared between July 2020 and July 2022 on Long COVID-related Reddit forums. Natural language processing, clustering techniques and a Long COVID symptoms lexicon were used to extract the different symptoms and categories of symptoms and to study the co-occurrences and correlation between them.

Results

More than 78% of the posts mentioned at least one Long COVID symptom. Fatigue (29.4%), pain (22%), clouded consciousness (19.1%), anxiety (17.7%) and headaches (15.6%) were the most prevalent symptoms. They also highly co-occurred with a variety of other symptoms (e.g., fever, sinonasal congestion). Different categories of symptoms were found: general (45.5%), neurological/ocular (42.9%), mental health/psychological/behavioral (35.2%), body pain/mobility (35.1%) and cardiorespiratory (31.2%). Posts focusing on other concerns of the community such as vaccine, recovery and relapse and, symptom triggers were detected.

Conclusions

We demonstrated the benefits of leveraging large volumes of data from Reddit to characterize the heterogeneity of Long COVID profiles. General symptoms, particularly fatigue, have been reported to be the most prevalent and frequently co-occurred with other symptoms. Other concerns, such as vaccination and relapse following recovery, were also addressed by the Long COVID community.

Barriers to opioid use disorder treatment: A comparison of self-reported information from social media with barriers found in literature

Introduction

Medications such as buprenorphine and methadone are effective for treating opioid use disorder (OUD), but many patients face barriers related to treatment and access. We analyzed two sources of data-social media and published literature-to categorize and quantify such barriers.

Methods

In this mixed methods study, we analyzed social media (Reddit) posts from three OUD-related forums (subreddits): r/suboxone, r/Methadone, and r/naltrexone. We applied natural language processing to identify posts relevant to treatment barriers, categorized them into insurance- and non-insurance-related, and manually subcategorized them into fine-grained topics. For comparison, we used substance use-, OUD- and barrier-related keywords to identify relevant articles from PubMed published between 2006 and 2022. We searched publications for language expressing fear of barriers, and hesitation or disinterest in medication treatment because of barriers, paying particular attention to the affected population groups described.

Results

On social media, the top three insurance-related barriers included having no insurance (22.5%), insurance not covering OUD treatment (24.7%), and general difficulties of using insurance for OUD treatment (38.2%); while the top two non-insurance-related barriers included stigma (47.6%), and financial difficulties (26.2%). For published literature, stigma was the most prominently reported barrier, occurring in 78.9% of the publications reviewed, followed by financial and/or logistical issues to receiving medication treatment (73.7%), gender-specific barriers (36.8%), and fear (31.5%).

Conclusion

The stigma associated with OUD and/or seeking treatment and insurance/cost are the two most common types of barriers reported in the two sources combined. Harm reduction efforts addressing barriers to recovery may benefit from leveraging multiple data sources.

Clair C, Liu W, Song JJ, Hua W, Falconer M, Eworuke E. Social media for early characterization of pandemic symptoms: A qualitative analysis of patient-reported COVID-19 experiences

BACKGROUND

Patients use social media forums to discuss their medical history and healthcare experiences, providing early insight into real-world patient experiences. We analyzed COVID-19 patient experiences from Reddit social media posts.

METHODS

We extracted Reddit Application Programming Interface data for the subreddit/COVID-19 positive from March to August 2020 and selected users tagged as "Tested Positive" or "Tested Positive- Me" flair and who posted at least thirty times in any calendar month, excluding users who explicitly stated location outside of the U.S. For tested-positive patients (users), we created and reviewed individual case profiles summarizing their COVID-19 symptoms, testing, and medications or treatments. Data were imported to Nvivo qualitative analysis software and qualitative coding was conducted.

FINDING

There were 31 759 posts and comments from 720 users in March to May 2020 (Q1) and 40 446 posts and comments from 1649 users from June to August 2020 (Q2). Final count of "Tested Positive" was 1296 users (280 in Q1 and 1016 in Q2). Across both quarters, frequently reported symptoms included sore throat, headaches, fevers, or chills. Loss of sense of smell or taste were reported by users in early March, prior to the inclusion of this symptom to the CDC list in April and GI-related symptoms and fatigue were reported in the March to May data, before they were added as a COVID-19 associated symptom in July 2020. Users also reported in-depth descriptions of their symptoms, motivations for testing, and long-term impacts such as post-viral fatigue.

INTERPRETATION

Social media data can potentially serve as an early surveillance data source in a pandemic and offer preliminary insights into patient disease experiences.

Attention and memory after COVID-19 as measured by neuropsychological tests: Systematic review and meta-analysis

COVID-19 is associated with a range of sequelae, including cognitive dysfunctions as long-standing symptoms. Considering that the number of people infected worldwide keeps growing, it is important to understand specific domains of impairments to further organize appropriate rehabilitation procedures. In this study we conducted a meta-analysis to investigate specific cognitive functions impacted by COVID-19. A literature search was conducted in Web of Science, Scopus, PubMed, Academic Search Premier, Health Source: Nursing/Academic Edition, and preprint databases (OSF and PsyArXiv via OSF Preprints, medRxiv, bioRxiv, Research Square). We included the studies that compared cognitive functioning in COVID-19 reconvalescents and healthy controls, and used at least one validated neuropsychological test. Our findings show that short-term memory in the verbal domain, and possibly, visual short-term memory and attention, are at risk in COVID-19 reconvalescents. The impact of COVID-19 on cognitive functioning has yet to be studied in detail. In the future more controlled studies with validated computerized tests might help deepen our understanding of the issue. PSYCINFO CLASSIFICATION: 3360 Health Psychology & Medicine.

Self-reported symptom severity, general health, and impairment in post-acute phases of COVID-19: retrospective cohort study of Swedish public employees

This study aimed to examine current symptom severity and general health in a sample of primarily non-hospitalized persons with polymerase chain reaction (PCR) confirmed COVID-19 in comparison to PCR negative controls. During the first quarter of 2021, we conducted an online survey among public employees in West Sweden, with a valid COVID-19 test result. The survey assessed past-month severity of 28 symptoms and signs, self-rated health, the WHO Disability Assessment Schedule (WHODAS) 2.0 and illness severity at the time of test. We linked participants' responses to their SARS-CoV-2 PCR tests results. We compared COVID-19 positive and negative participants using univariable and multivariable regression analyses. Out of 56,221 invited, 14,222 (25.3%) responded, with a response rate of 50% among SARS-CoV-2 positive individuals. Analysis included 10,194 participants (86.4% women, mean age 45 years) who tested positive 4-12 weeks (N = 1425; subacute) and > 12 weeks (N = 1584; postcovid) prior to the survey, and 7185 PCR negative participants who did not believe that they had had COVID-19. Symptoms were highly prevalent in all groups, with worst symptoms in subacute phase participants, followed by postcovid phase and PCR negative participants. The most specific symptom for COVID-19 was loss of smell or taste. Both WHODAS 2.0 score and self-rated health were worst in subacute participants, and modestly worse in postcovid participants than in negative controls. Female gender, older age and acute illness severity had larger effects on self-rated health and WHODAS 2.0 score in PCR positive participants than in PCR negative. Studies with longer follow-up are needed to determine the long-term improvement after COVID-19.

Psychological and Cognitive Effects of Long COVID: A Narrative Review Focusing on the Assessment and Rehabilitative Approach

Long COVID is a clinical syndrome characterized by profound fatigue, neurocognitive difficulties, muscle pain, weakness, and depression, lasting beyond the 3–12 weeks following infection with SARS-CoV-2. Among the symptoms, neurocognitive and psychiatric sequelae, including attention and memory alterations, as well as anxiety and depression symptoms, have become major targets of current healthcare providers given the significant public health impact. In this context, assessment tools play a crucial role in the early screening of cognitive alterations due to Long COVID. Among others, the general cognitive assessment tools, such as the Montreal Cognitive assessment, and more specific ones, including the State Trait Inventory of Cognitive Fatigue and the Digit Span, may be of help in investigating the main neurocognitive alterations. Moreover, appropriate neurorehabilitative programs using specific methods and techniques (conventional and/or advanced) through a multidisciplinary team are required to treat COVID-19-related cognitive and behavioral abnormalities. In this narrative review, we sought to describe the main neurocognitive and psychiatric symptoms as well as to provide some clinical advice for the assessment and treatment of Long COVID.

Online advice for the symptomatic management of post-stroke fatigue: A scoping review

BACKGROUND

Limited medical evidence for managing post-stroke fatigue leads stroke survivors to seek information through other sources. This scoping review aimed to identify and assess the range and quality of web-based recommendations for managing post-stroke fatigue.

METHODS

Publicly accessible websites providing advice for post-stroke fatigue management were considered for review using the Joanna Briggs Institute's methodology. Using the search term "fatigue stroke", the first two pages of results from each search engine (Google, Yahoo, and Bing) were assessed against predetermined criteria. Findings were reported in accordance with PRISMA-ScR checklist. Quality and readability were also assessed.

RESULTS

Fifty-seven websites were identified; 16 primary and 11 linked websites met the inclusion criteria and demonstrated moderate to high quality and high readability. Primary websites were curated by non-government organizations (n = 10/16), companies (n = 4/16) or were media and blog websites (n = 2/16). Additional resources were provided on linked websites. All websites provided non-pharmacological advice, with four also describing pharmacological management. Many websites included advice related to physical activity modification (n = 18/27) and energy conservation strategies (e.g. activity prioritization, planning, pacing) (n = 26/27). Direction to seek health professional advice appeared frequently (n = 16/27).

CONCLUSIONS

The quality of publicly available web-based advice for people with post-stroke fatigue was moderate to high in most websites, with high readability. Energy conservation strategies and physical activity modification appear frequently. The general nature of the advice provided on most websites is supported by direction to healthcare professionals (i.e., clinical referral) who may assist in the practical individualization of strategies for managing post-stroke fatigue.

Effects of SARS-CoV-2 Infection on Attention, Memory, and Sensorimotor Performance

BACKGROUND

Recovery after SARS-CoV-2 infection is extremely variable, with some individuals recovering quickly, and others experiencing persistent long-term symptoms or developing new symptoms after the acute phase of infection, including fatigue, poor concentration, impaired attention, or memory deficits. Many existing studies reporting cognitive deficits associated with SARS-CoV-2 infection are limited by the exclusive use of self-reported measures or a lack of adequate comparison groups.

METHODS

Forty-five participants, ages 18-70, (11 Long-COVID, 14 COVID, and 20 No-COVID) underwent behavioral testing with the NIH Toolbox Neuro-Quality of Life survey and selected psychometric tests, including a flanker interference task and the d2 Test of Attention.

RESULTS

We found greater self-reported anxiety, apathy, fatigue, emotional dyscontrol, sleep disturbance and cognitive dysfunction in COVID compared No-COVID groups. After categorizing COVID patients according to self-reported concentration problems, we observed declining performance patterns in multiple attention measures across No-COVID controls, COVID and Long-COVID groups. COVID participants, compared to No-COVID controls, exhibited worse performance on NIH Toolbox assessments, including the Eriksen Flanker, Nine-Hole Pegboard and Auditory Verbal Learning tests.

CONCLUSION

This study provides convergent evidence that previous SARS-CoV-2 infection is associated with impairments in sustained attention, processing speed, self-reported fatigue and concentration. The finding that some patients have cognitive and visuomotor dysfunction in the absence of self-reported problems suggests that SARS-CoV-2 infection can have unexpected and persistent subclinical consequences.

Trajectories of Neurologic Recovery 12 Months After Hospitalization for COVID-19: A Prospective Longitudinal Study

BACKGROUND AND OBJECTIVE

Little is known about trajectories of recovery 12 months after hospitalization for severe COVID-19.

METHODS

We conducted a prospective, longitudinal cohort study of patients with and without neurologic complications during index hospitalization for COVID-19 from March 10, 2020, to May 20, 2020. Phone follow-up batteries were performed at 6 and 12 months after COVID-19 onset. The primary 12-month outcome was the modified Rankin Scale (mRS) score comparing patients with or without neurologic complications using multivariable ordinal analysis. Secondary outcomes included activities of daily living (Barthel Index), telephone Montreal Cognitive Assessment (t-MoCA), and Quality of Life in Neurologic Disorders (Neuro-QoL) batteries for anxiety, depression, fatigue, and sleep. Changes in outcome scores from 6 to 12 months were compared using nonparametric paired-samples sign test.

RESULTS

Twelve-month follow-up was completed in 242 patients (median age 65 years, 64% male, 34% intubated during hospitalization) and 174 completed both 6- and 12-month follow-up. At 12 months, 197/227 (87%) had ≥1 abnormal metric: mRS >0 (75%), Barthel Index <100 (64%), t-MoCA ≤18 (50%), high anxiety (7%), depression (4%), fatigue (9%), or poor sleep (10%). Twelve-month mRS scores did not differ significantly among those with (n = 113) or without (n = 129) neurologic complications during hospitalization after adjusting for age, sex, race, pre-COVID-19 mRS, and intubation status (adjusted OR 1.4, 95% CI 0.8-2.5), although those with neurologic complications had higher fatigue scores (T score 47 vs 44; p = 0.037). Significant improvements in outcome trajectories from 6 to 12 months were observed in t-MoCA scores (56% improved, median difference 1 point; p = 0.002) and Neuro-QoL anxiety scores (45% improved; p = 0.003). Nonsignificant improvements occurred in fatigue, sleep, and depression scores in 48%, 48%, and 38% of patients, respectively. Barthel Index and mRS scores remained unchanged between 6 and 12 months in >50% of patients.

DISCUSSION

At 12 months after hospitalization for severe COVID-19, 87% of patients had ongoing abnormalities in functional, cognitive, or Neuro-QoL metrics and abnormal cognition persisted in 50% of patients without a history of dementia/cognitive abnormality. Only fatigue severity differed significantly between patients with or without neurologic complications during index hospitalization. However, significant improvements in cognitive (t-MoCA) and anxiety (Neuro-QoL) scores occurred in 56% and 45% of patients, respectively, between 6 and 12 months. These results may not be generalizable to those with mild or moderate COVID-19.

Social media mining to support drug repurposing: Exploring long-COVID self-medication reported by Reddit users (Preprint)

Background

Since the beginning of the COVID-19 pandemic, over 480 million people have been infected and more than 6 million people have died from COVID-19 worldwide. In some patients with acute COVID-19, symptoms manifest over a longer period, which is also called “long-COVID.” Unmet medical needs related to long-COVID are high, since there are no treatments approved. Patients experiment with various medications and supplements hoping to alleviate their suffering. They often share their experiences on social media.

Objective

The aim of this study was to explore the feasibility of social media mining methods to extract important compounds from the perspective of patients. The goal is to provide an overview of different medication strategies and important agents mentioned in Reddit users’ self-reports to support hypothesis generation for drug repurposing, by incorporating patients’ experiences.

Methods

We used named-entity recognition to extract substances representing medications or supplements used to treat long-COVID from almost 70,000 posts on the “/r/covidlonghaulers” subreddit. We analyzed substances by frequency, co-occurrences, and network analysis to identify important substances and substance clusters.

Results

The named-entity recognition algorithm achieved an F1 score of 0.67. A total of 28,447 substance entities and 5789 word co-occurrence pairs were extracted. “Histamine antagonists,” “famotidine,” “magnesium,” “vitamins,” and “steroids” were the most frequently mentioned substances. Network analysis revealed three clusters of substances, indicating certain medication patterns.

Conclusions

This feasibility study indicates that network analysis can be used to characterize the medication strategies discussed in social media. Comparison with existing literature shows that this approach identifies substances that are promising candidates for drug repurposing, such as antihistamines, steroids, or antidepressants. In the context of a pandemic, the proposed method could be used to support drug repurposing hypothesis development by prioritizing substances that are important to users.

Long Haul COVID-19 Videos on YouTube: Implications for Health Communication

The term COVID-19 “long haul” originated on social media and was later studied by the scientific community. This study describes content related to persistent COVID-19 symptoms on YouTube. The 100 most viewed English-language videos identified with the keywords “COVID-19 long haul” were assessed for video origin, engagement, and content related to COVID-19 long-haul. The findings indicate that the majority of videos were uploaded by television or internet news (56%), followed by consumers (members of the public, 32%), health professionals (only 9%), and lastly by entertainment TV (non-news programs, 3%). Videos originating from entertainment TV were significantly more likely to be “liked” than videos from other sources. The most commonly mentioned long-haul symptoms in the videos were physical (fatigue, 73%; difficulty breathing/shortness of breath, 56%; and joint or muscle pain, 49%) and cognitive (difficulty thinking or concentrating; 69%). The case of COVID-19 long haul demonstrates that social media are significant fora whereon the public identify health concerns. It is necessary for healthcare professionals to assume an active and responsible role in social media.