Understanding Public Perceptions and Discussions on Fibromyalgia through Social Media: Cross-Sectional Infodemiology Study

Understanding Public Perceptions and Discussions on Fibromyalgia through Social Media: Cross-Sectional Infodemiology Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding Public Perceptions and Discussions on Fibromyalgia through Social Media: Cross-Sectional Infodemiology Study MT Valades, M Montero-Torres, FJ Lara-Abelenda, F Carabot, MA Ortega, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3992089/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Jul, 2024 Read the published version in BMC Musculoskeletal Disorders → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Fibromyalgia is a prevalent condition of unknown etiology, characterized by generalized chronic pain that leads to disability, and has significant direct and indirect costs. The objective of this study was to examine the content and key aspects of tweets pertaining to diseases associated with chronic pain. Methods: We investigated tweets published between January 1, 2018, and December 31, 2022, by English and Spanish-speaking Twitter users, as well as generated retweets. Additionally, emotions were extracted from these tweets and their dissemination was analysed. Similarly, the topics that users most frequently address were compiled. Results: In total, 72,874 tweets were analysed in both English (44,467) and Spanish (28,407). Paraplegia represented 23.3%, with 16,461 classifiable tweets, followed by headache and fibromyalgia, with 15,337 (21.7%) and 15,179 (21.5%) tweets, respectively. Multiple sclerosis generated 14,781 tweets (21%), while the lowest number of tweets was associated with neuropathy, totaling 8,830 tweets (12.5%). The findings revealed that the primary emotions extracted were "fear" and "sadness". Furthermore, the scope and impact of these tweets were investigated through the generated retweets, with those related to headaches being of the highest interest and having the greatest interaction among users. Conclusions: Our findings contribute to understanding the role that social media plays in fostering public awareness of chronic pain and improving patients' comprehension and treatment. Moreover, these results are likely to be applicable to other countries whose languages were not covered in our study. Twitter fibromyalgia headache paraplegia multiple sclerosis neuropathy chronic pain infodemiology and their equivalents in Spanish Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. BACKGROUND Chronic and recurrent pain is a highly prevalent medical condition that negatively impacts quality of life 1 and is associated with considerable functional disability 2 . Current efforts to diagnose and identify diseases that present with chronic pain, such as fibromyalgia, have become increasingly prominent. Fibromyalgia is a common condition of unknown etiology, characterized by widespread chronic pain, physical exhaustion, cognitive difficulties, depressed mood, sleep problems, and impaired health-related quality of life 3 . This condition causes disability with high direct (healthcare, medications) and indirect (productivity loss) costs 4 . The prevalence of fibromyalgia is estimated to be between 2% and 8% of the general population worldwide and the prevalence of fibromyalgia increases with the comorbidity of specific disorders 5 . It is more predominant in females 6 . The diagnosis of fibromyalgia is challenging; it requires differential diagnosis among various medical entities 7 . Additionally, diagnostic delay can have a significant impact on the quality of life and emotional state of patients, as well as on medical and social costs 8 . According to the International Association for the Study of Pain (IASP) criteria for the International Classification of Diseases, 11th Revision (ICD-11), the World Health Organization (WHO) classified fibromyalgia as primary generalized chronic pain (code MG30.01), with the basic diagnostic criteria being 6 : ( 1 ) Pain lasting at least 3 months that occurred in at least six parts of the body and was defined as multisite pain. Additionally, ( 2 ) the pain must be accompanied by fatigue (physical or mental) or sleep disturbances considered by a physician to be at least of moderate severity. In recent years, social media has become an important source of information where users express and share ideas, opinions, thoughts, and experiences on a multitude of topics 9 . Platforms such as Twitter (now X), with more than 320 million users, can provide rapid and wide-reaching dissemination of health-related information that can be collected and analysed for research, including infodemiology and infoveillance 10,11 . Information obtained through social media has been shown to be as reliable as traditional survey data 12 . Thus, using data analysis and mining techniques, this information can potentially be useful for determining specific health conditions 9 . However, until now, no research has evaluated the information about fibromyalgia circulated on social media. In this study, we aimed to: ( 1 ) examine the volume and type of tweets related to chronic pain; ( 2 ) analyse the emotions expressed on X regarding fibromyalgia and other diseases associated with chronic pain such as headache, paraplegia, neuropathy, and multiple sclerosis; and ( 3 ) compare the societal impact of different diseases associated with chronic pain. 2. METHODS 2.1. Data Collection: We used X to gather posts from users, both in English and Spanish, about diseases associated with chronic pain. The data collection period ranged from January 1, 2018, to December 31, 2022. To do this, we utilized Tweet Binder's API, allowing us to gather all publicly available tweets containing keywords for the diseases of interest. The keywords used were as follows: ( 1 ) "fibromyalgia"; ( 2 ) "headache", "migraine"; ( 3 ) "multiple sclerosis"; ( 4 ) "polyneuropathy", "neurophaty", "neuralgia"; and ( 5 ) "paraplegia", "tetraplegia", and their equivalents in Spanish. In total, 72,874 tweets were collected, and from each of them, data were obtained regarding the date and time of creation, the publicly displayed user name, the text, geolocation, and the status of "likes" and "retweets". 2.2. Data Processing: 2.2.1. Topic Modelling (LDA): This study adopted an unsupervised learning approach, using Latent Dirichlet Allocation (LDA) for topic modelling. After a comprehensive review of available techniques, LDA was chosen due to its simplicity and widespread utilization, as evidenced in existing work on X 13,14,15 . Our research primarily focuses on applying a well-documented technique within a novel database, aiming to extract meaningful insights from the data. Prior to the application of the topic modelling model, an extensive data preprocessing procedure was implemented. This preprocessing encompassed language classification, segregating Spanish tweets from others and subsequently translating the Spanish tweets into English using the Google translator application. The text was subsequently cleaned by removing stopwords, duplicate words, and nonstandard characters, such as emojis or hashtags. To find the optimal number of topics in topic modelling, a Cluster Validity Index (CVI) was employed. CVIs are measures used in unsupervised learning to evaluate the effectiveness of clustering by assessing how well data points are organized 16 . The silhouette coefficient was the CVI selected due to its ability to assess both intercluster and intracluster distances. Finally, LDA was applied to the 5 pain-related diseases analysed (fibromyalgia, headache, paraplegia, neuropathy, and multiple sclerosis). 2.2.2. Emotional Extraction: Finally, emotion detection was conducted using a model from Hugging Face's machine learning platform named "Emotional English DistilRoBERTa-base" 17 . This model is recognized as a state-of-the-art model for detecting Ekman's six basic emotions: namely, anger, disgust, fear, joy, sadness, and surprise, with the addition of neutral emotion 18 . Capturing these emotions is crucial in our case, as per the insights from physicians. The selected model has demonstrated superior performance in capturing these specified emotions demonstrating an accuracy of 66%, surpassing the random-chance baseline of 14% 13,18 . 3. RESULTS 3.1. Number of tweets: For this work, our search tool provided 72,874 original tweets, both in English and Spanish, from January 2018 to December 2022. The number of tweets generated in English was 44,467 (61.02%), while in Spanish, there were 28,407 tweets (38.98%). Of these tweets, 70,588 were analysed, with the remaining 2,286 tweets considered unclassifiable. The number of tweets related to each of the diseases ( Fig. 1 ) followed a homogeneous pattern except for the case of neuropathy, which had the lowest frequency of related publications, specifically 8,830 tweets (12.5%). However, there is a preferential accumulation in the case of paraplegia with 16,461 tweets, representing 23.3% of the classifiable tweets. It is followed by headache and fibromyalgia, with similar numbers of tweets, 15,337 (21.7%) and 15,179 (21.5%) tweets, respectively. Finally, 14,781 tweets related to multiple sclerosis represented 21% of the total classifiable tweets. 3.2. LDA: Through LDA, we detected the most frequently associated topics for each disease. In the case of headache, the most recurrent topics are its triggers, the association between headache and Coronavirus Disease 2019 (COVID-19), and the COVID-19 vaccine and treatments used. Advances in research on paraplegia have been made, as individuals with paraplegia participate in sporting events, and the etiology of the disease well known. out. Focusing on fibromyalgia, topics mainly revolve around the definition of the disease, symptoms, and available treatments. For multiple sclerosis, discussions involve the diagnosis of the disease, efforts to raise funds for research, and new treatments. Finally, when analysing tweets related to neuropathy, the most prominent topics were the effects of the COVID-19 vaccine, diseases associated with neuralgia, and available treatments. 3.3. Emotional Extraction: After extracting emotions from the collected tweets, we further investigated the distribution by disease and emotion, attempting to determine the types of emotions ( Fig. 2 ) associated with diseases associated with chronic pain. The results showed that both "fear" and "sadness" were the dominant types of emotions in each group, following the same frequency order according to disease, headache, fibromyalgia, paraplegia, multiple sclerosis, and neuropathy. In contrast, the number of tweets addressing emotions such as "joy," "surprise," "anger," and "disgust" was much lower, with paraplegia, multiple sclerosis, and headache standing out among the diseases. 3.4. Reach and Impact: Paraplegia was the content that generated the greatest number of tweets. However, no correlation was detected between the frequency of tweets published in each category and subsequent retweets, with tweets related to headache showing the highest interest and interaction among users. We investigated the interest generated by these tweets by examining the number of retweets per disease and emotion ( Fig. 3 ) received. When studying the reach of retweets, the potential impact of tweets addressing headache associated with emotions such as "joy," "surprise," "sadness," "anger," "fear," and "neutral" was discovered, followed by tweets related to multiple sclerosis and fibromyalgia. As an exception, tweets expressing a feeling of "disgust" were notable, as they showed a clear difference in the number of retweets related to multiple sclerosis, followed by headache and fibromyalgia. 3.5. Temporal Evolution: We evaluated the evolution of the number of tweets published by X users between January 2018 and December 2022 and represented it in a graph by four-month periods (Fig. 4-A). Throughout the years analysed, we observed a progressive increase in the number of tweets generated about fibromyalgia since January 2018, with a particular peak in the second four-month period of 2019. From this point, there was a progressive decrease in the number of publications until the third four-month period of 2020, followed by a plateau in subsequent years, with a new peak occurring from May to August 2022. Tweets related to paraplegia and neuropathy experienced a similar evolution in the studied five-year period, with a progressive increase in the number of publications starting from the third four-month period of 2021. On the other hand, the trend observed in tweets related to headache showed several peaks in the second and first four-month periods of 2018 and 2020, respectively. In the publications about multiple sclerosis, the quantity of tweets followed a homogeneous pattern with several peaks throughout the five years analysed. We also studied the kinetics of retweets (Fig. 4-B) and observed a homogeneous evolution of tweets related to paraplegia and neuropathy. On the other hand, it is important to note that we observed a particular peak in the number of headache retweets generated in the third four-month period of 2020, followed by a notable increase in subsequent years. However, the evolution of retweets was not homogeneous among the diseases fibromyalgia and multiple sclerosis, where we observed a constant increase or decrease during the years included in our search, especially in the distribution of retweets. 3.6. Geographic Location: We extracted the geographic locations of these tweets to analyse the trends in the volumes of the studied tweets. The distribution of the tweets by continent ( Fig. 5 ) was predominantly from America and Europe rather than from other continents, with their representation being anecdotal. 4. DISCUSSION 4.1 . Main Findings : In this study, based on published tweets, we found that X users were most interested in discussing paraplegia. Through LDA, we found that treatment was the most prevalent topic, followed by etiology and research advancements. Notably, in the case of fibromyalgia, symptoms and the definition of the disease have garnered much attention. The dominant emotions were "fear" and "sadness". Surprisingly, there was no correlation between the number of tweets and their impact measured through generated retweets; ultimately, when analysing the temporal evolution, the trend in the number of tweets was homogeneous, with a particular peak observed in fibromyalgia-related tweets. The interest generated by different chronic pain-related diseases among X users was homogeneous, except in the case of neuropathy, where the number of tweets was clearly lower. We know that neuropathy affects older populations more than younger populations, and generally, X users tend to be younger, limiting the information published regarding this condition. On the other hand, the diagnosis of neuropathic pain is underestimated, and these negative or stigmatizing attitudes have led to less interest from society 19 . However, we found studies where such stigmatization further increased the demand for validated information from sources other than formal institutions, more frequently from social media platforms 20,21 . Conversely, the popularity of paraplegia among X users could have a direct relationship with various clinical and preclinical studies from recent decades reporting on the potential effects of epidural electrical stimulation in the treatment of spinal cord injuries (SCIs) 22 , as well as the search for other alternative treatment strategies 23 . Social media plays a significant role in shaping opinions and emotions through the dissemination of information 24 , and we believe that retweets serve as a measure of users' particular interest in a topic, which is associated with the emotions evoked by tweets 25 . For instance, sentiment analysis of a large number of messages can provide valuable insights into the mood of the crowd 12 and their health status 26 . The predominance of emotions related to "sadness" and "fear" may be justified because chronic pain is one of the most common health problems in the population, and leads to functional disability, individual suffering, and high costs 27 . These negative emotions also stem from a lack of adequate treatment, as studies in Europe report that approximately 14% of patients discontinued treatment owing to side effects, and up to 40% received treatment they deemed inadequate 19 . In this way, diseases associated with chronic pain are a cause for concern among X users, as reflected in their posts, especially regarding headache, considered the most common neurological disorder in the population 28 , and fibromyalgia, both of which have a negative impact on people's well-being 29 . Furthermore, the subjectivity in the diagnosis of both conditions undermines the perception that the population has of these diseases. Like in individuals with mental illnesses, addiction, and many other painful disorders, migraine is invisible and cannot be measured or confirmed by an objective diagnostic test. Compared to individuals with epilepsy, which has a physical manifestation, individuals with chronic migraine are seen as less reliable, less inclined to exert themselves, and more prone to feigning illness 30,31 . Thus, "less visible" diseases or those causing greater societal rejection are the most feared and can lead to greater sadness, despite being less severe than conditions such as paraplegia or multiple sclerosis. On the other hand, the number of tweets addressing emotions such as "joy" and "surprise" regarding conditions such as paraplegia, multiple sclerosis, and headache is surprising. This relationship could be explained by recent studies indicating that the European population with SCIs 32 shows high or very high satisfaction with the availability of medical care related to these injuries. In multiple sclerosis, the exact etiology is still unclear, but there has been an association with an abnormal response within the central nervous system, possibly due to an infectious agent 33 . As knowledge about Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to advance, the literature has shown that a significant number of patients experience headaches, the most common and mildest neurological manifestation 34 . In this study, we found that users of X had greater interactions when the content of the tweets was related to headache, likely because headache is the most common neurological disorder in the population 28 . Many studies have demonstrated the use of social media platforms to share experiences with headaches 35,36 . Additionally, there are multiple reports linking headaches with social media use 29 , as somatic symptoms, including headaches, have been found primarily in patients with problematic use of social media 29,37 . Regarding the temporal evolution of the disease, our data showed that the number of tweets about fibromyalgia decreased between the second and third trimesters of 2019, reaching its lowest level in the third trimester of 2020 in the context of the SARS-CoV-2 pandemic. The uncertainty of the SARS-CoV-2 pandemic caused an abrupt interruption of treatment for patients suffering from chronic pain, resulting in potential unintended harm. For example, in the fibromyalgia population, there is an association between negative emotions ("fear" or "sadness") and less information dissemination, although user interaction is more common. Regarding the effects of the pandemic, studies confirm that COVID-19 has altered the daily functioning of departments by prioritizing hospital services exclusively for life 38 . This not only occurred with fibromyalgia; for instance, research has demonstrated the impact of the pandemic on the treatment of neurological diseases such as multiple sclerosis, especially due to the high risk of initiating immunosuppressive treatments 38,39 and delays or cancellations of electrodiagnostic studies 38,40 . On the other hand, there was a general reluctance to visit hospitals among the population. We can speculate that the incidence of neurological emergencies did not decrease during the COVID-19 pandemic but rather that differences in the number of patients were due to alterations in public health policy and users' reluctance to visit hospitals 38 . However, longer-term follow-up studies are needed to evaluate the lasting consequences of the pandemic on the prevalence of neurological diseases and the treatment of patients with chronic neurological disorders 38 . It is relevant to recognize the association of temporal evolution in the analysis of tweets about fibromyalgia and headache with the SARS-CoV-2 pandemic. The literature describes the persistence of a wide range of symptoms long after the acute phase of severe acute respiratory syndrome caused by SARS-CoV-2 41,42 , including extreme fatigue, musculoskeletal pain, headache, sleep disorders, anxiety, and depression 24,42,43 . This clinical picture is associated with poor quality of life and severe deterioration of functional capacity and is known as post-COVID-19 syndrome; these conditions may resemble fibromyalgia because they meet the same diagnostic criteria. Similarly, the exacerbation or onset of fibromyalgia symptoms can occur during or after SARS-CoV-2 infection or due to numerous and persistent stressors imposed daily by the pandemic environment 44 . Awareness among the general population and healthcare professionals about the development of this syndrome may have led to a decrease in interest in fibromyalgia. However, in the same context, publications and interactions about headache increase, because it is part of this syndrome. 4.2. Limitations: This study has several limitations. First, X users are typically younger; thus, sectors of the population without access to the Internet or social media (such as elderly people or those with low socioeconomic status) may be excluded. This limits the generalizability of our results, particularly in this field where the average age of patients is older than that of the most common users. Second, we limited our analysis to tweets in English and Spanish, which may limit the ability to extrapolate the results since populations not speaking these languages may have different interests or concerns regarding these diseases. Third, subjectivity could be a major limitation when specifically coding content that tends to trivialize, where emotional tone or double entry is crucial, as well as denial or irony, which can influence classification by emotions. Additionally, media outlets do not necessarily reflect the interests of society and may be influenced by financial conflicts of interest from companies 45 . However, it is worth noting that, despite these limitations, our methodology is consistent with previous medical research on Twitter (now X) 46 . 5. CONCLUSIONS In general, this study confirmed the opportunity for social media analysis to provide information about public sentiment toward chronic pain diseases, such as fibromyalgia. Our results contribute to understanding the role that social media plays in promoting public awareness of chronic pain and improving the comprehensive understanding of patients who suffer from it and its treatment. Although this study focused on two languages, these results offer relevant information that is likely applicable to other countries. Abbreviations COVID-19 (COronaVIrus Disease 2019) CVI (Cluster Validity Index) IASP (International Association for the Study of Pain) ICD-11 (International Classification of Diseases) LDA (Latent Dirichlet Allocation) RTs (Retweets) SARS-CoV-2 (Severe Acute Respiratory Syndrome COronaVirus 2) SCI (Spinal Cord Injury). WHO (World Health Organization) Declarations Ethics approval and consent to participate: This study received approval from the Research Ethics Committee of the University of Alcala and complied with the research ethics principles established in the Declaration of Helsinki. However, this research did not involve human subjects directly or included any human intervention, as it used publicly available tweets. Nevertheless, we took special care not to disclose the names of users and avoided quoting tweets that could reveal them. Consent for publication: Not applicable. Availability of data and materials : The datasets generated and/or analyzed during the current study are available upon reasonable request. Competing interests : The authors declare no competing interests. Funding: This work was funded by the Carlos III Health Institute (Ref. PI22/00653) (Spain). Authors' contributions: MTV, FC, and MAA-M were the main contributors to the research design, coordination of the data analysis, and manuscript preparation. MAA-M specifically coordinated the data acquisition. MTV and FC were tweet coders, and contributed to codebook development, training, and analysis of the tweets. MM-T and FJL-A conducted the data processing and statistical analysis. MAO and MA-M contributed to the manuscript as reviewers. MAA-M was the main supervisor in all phases of the project, with special involvement in the study design, data interpretation, and manuscript preparation. 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Curr Pain Headache Rep. 2021 Dec 6;25(11):75. DOI: 10.1007/s11916-021-00982-z. PMID: 34873646; PMCID: PMC8647964. Shapiro RE, Lipton RB, Reiner PB. EHMTI-0313. Factors influencing stigma towards persons with migraine. J Headache Pain. 2014;15(Suppl 1):E36. DOI: 10.1186/1129-2377-15-S1-E36. Epub 2014 Sep 18. PMCID: PMC4182198. Ronca E, Scheel-Sailer A, Koch HG, Essig S, Brach M, Münzel N, Gemperli A; SwiSCI Study Group. Satisfaction with access and quality of healthcare services for people with spinal cord injury living in the community. J Spinal Cord Med. 2020 Jan;43(1):111-121. DOI: 10.1080/10790268.2018.1486623. Epub 2018 Jul 2. PMID: 29965779; PMCID: PMC7006672. Amatya B, Young J, Khan F. Non-pharmacological interventions for chronic pain in multiple sclerosis. Cochrane Database Syst Rev. 2018 Dec 19;12(12):CD012622. DOI: 10.1002/14651858.CD012622.pub2. PMID: 30567012; PMCID: PMC6516893. Nepal G, Rehrig JH, Shrestha GS, Shing YK, Yadav JK, Ojha R, Pokhrel G, Tu ZL, Huang DY. Neurological manifestations of COVID-19: a systematic review. Crit Care. 2020 Jul 13;24(1):421. DOI: 10.1186/s13054-020-03121-z. PMID: 32660520; PMCID: PMC7356133. Goadsby P, Ruiz de la Torre E, Constantin L, Amand C. Social Media Listening and Digital Profiling Study of People With Headache and Migraine: Retrospective Infodemiology Study. J Med Internet Res. 2023 May 5;25:e40461. DOI: 10.2196/40461. PMID: 37145844; PMCID: PMC10199393. Pearson C, Swindale R, Keighley P, McKinlay AR, Ridsdale L. Not just a headache: qualitative study about web-based self-presentation and social media use by people with migraine. J Med Internet Res 2019;21(6):e10479. DOI: 10.2196/10479. Marino C, Lenzi M, Canale N, Pierannunzio D, Dalmasso P, Borraccino A, Cappello N, Lemma P, Vieno A; 2018 HBSC-Italia Group; the 2018 HBSC-Italia Group. Problematic social media use: associations with health complaints among adolescents. Ann Ist Super Sanita. 2020 Oct-Dec;56(4):514-521. DOI: 10.4415/ANN_20_04_16. PMID: 33346180. Gavriilaki M, Karlafti E, Moschou M, Notas K, Arnaoutoglou M, Kaiafa G, Savopoulos C, Kimiskidis V. COVID-19 pandemic impact on neurologic emergencies: a single-center retrospective cohort study. Pan Afr Med J. 2022 Mar 29;41:255. DOI: 10.11604/pamj.2022.41.255.33897. PMID: 35734332; PMCID: PMC9187993. Brownlee W, Bourdette D, Broadley S, Killestein J, Ciccarelli O. Treating multiple sclerosis and neuromyelitis optica spectrum disorder during the COVID-19 pandemic. Neurology. 2020 Jun 2;94(22):949-952. DOI: 10.1212/WNL.0000000000009507. Epub 2020 Apr 2. PMID: 32241953. Desai U, Kassardjian CD, Del Toro D, Gleveckas-Martens N, Srinivasan J, Venesy D, Narayanaswami P; AANEM Quality and Patient Safety Committee. Guidance for resumption of routine electrodiagnostic testing during the COVID-19 pandemic. Muscle Nerve. 2020 Aug;62(2):176-181. DOI: 10.1002/mus.26990. PMID: 32462675; PMCID: PMC7283872. Alvarez-Mon MA, Fernandez-Lazaro CI, Ortega MA, Vidal C, Molina-Ruiz RM, Alvarez-Mon M, Martínez-González MA. Analyzing Psychotherapy on Twitter: An 11-Year Analysis of Tweets From Major U.S. Media Outlets. Front Psychiatry. 2022 May 18;13:871113. DOI: 10.3389/fpsyt.2022.871113. PMID: 35664489; PMCID: PMC9159799. Rivera J, Rodríguez T, Pallarés M, Castrejón I, González T, Vallejo-Slocker L, Molina-Collada J, Montero F, Arias A, Vallejo MA, Alvaro-Gracia JM, Collado A. Prevalence of post-COVID-19 in patients with fibromyalgia: a comparative study with other inflammatory and autoimmune rheumatic diseases. BMC Musculoskelet Disord. 2022 May 19;23(1):471. DOI: 10.1186/s12891-022-05436-0. PMID: 35590317; PMCID: PMC9117853. Abbasi-Perez A, Alvarez-Mon MA, Donat-Vargas C, Ortega MA, Monserrat J, Perez-Gomez A, Sanz I, Alvarez-Mon M. Analysis of Tweets Containing Information Related to Rheumatological Diseases on Twitter. Int J Environ Res Public Health. 2021 Aug 28;18(17):9094. DOI: 10.3390/ijerph18179094. PMID: 34501681; PMCID: PMC8430833. Fialho MFP, Brum ES, Oliveira SM. Could the fibromyalgia syndrome be triggered or enhanced by COVID-19? Inflammopharmacology. 2023 Apr;31(2):633-651. doi: 10.1007/s10787-023-01160-w. Epub 2023 Feb 27. PMID: 36849853; PMCID: PMC9970139. Alvarez-Mon MA, Fernandez-Lazaro CI, Llavero-Valero M, Alvarez-Mon M, Mora S, Martínez-González MA, Bes-Rastrollo M. Mediterranean Diet Social Network Impact along 11 Years in the Major US Media Outlets: Thematic and Quantitative Analysis Using Twitter. Int J Environ Res Public Health. 2022 Jan 11;19(2):784. DOI: 10.3390/ijerph19020784. PMID: 35055605; PMCID: PMC8775755. Golder S, O'Connor K, Hennessy S, Gross R, Gonzalez-Hernandez G. Assessment of Beliefs and Attitudes About Statins Posted on Twitter: A Qualitative Study. JAMA Netw Open. 2020 Jun 1;3(6):e208953. DOI: 10.1001/jamanetworkopen.2020.8953. PMID: 32584408; PMCID: PMC7317605. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Jul, 2024 Read the published version in BMC Musculoskeletal Disorders → Version 1 posted Editorial decision: Revision requested 22 Apr, 2024 Reviews received at journal 15 Apr, 2024 Reviews received at journal 14 Apr, 2024 Reviewers agreed at journal 08 Apr, 2024 Reviewers agreed at journal 06 Apr, 2024 Reviewers invited by journal 06 Apr, 2024 Editor assigned by journal 18 Mar, 2024 Editor invited by journal 04 Mar, 2024 Submission checks completed at journal 04 Mar, 2024 First submitted to journal 26 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3992089","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276339398,"identity":"3deaf457-0211-4444-9fbc-f56efc7fd6db","order_by":0,"name":"MT 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Alcala","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"","lastName":"Montero-Torres","suffix":""},{"id":276339400,"identity":"df3e80e8-fbab-4662-a69a-ff6e9b74c67b","order_by":2,"name":"FJ Lara-Abelenda","email":"","orcid":"","institution":"University of Alcala","correspondingAuthor":false,"prefix":"","firstName":"FJ","middleName":"","lastName":"Lara-Abelenda","suffix":""},{"id":276339401,"identity":"502bfc80-85bd-4367-8c31-e5a84096f025","order_by":3,"name":"F Carabot","email":"","orcid":"","institution":"University of Alcala","correspondingAuthor":false,"prefix":"","firstName":"F","middleName":"","lastName":"Carabot","suffix":""},{"id":276339402,"identity":"2ffd1fb2-71cc-41e9-88d1-5286ecc95fce","order_by":4,"name":"MA Ortega","email":"","orcid":"","institution":"University of Alcala","correspondingAuthor":false,"prefix":"","firstName":"MA","middleName":"","lastName":"Ortega","suffix":""},{"id":276339403,"identity":"e9c08d7a-dd5a-457b-95f2-9bcb3533c446","order_by":5,"name":"M Álvarez-Mon","email":"","orcid":"","institution":"University of Alcala","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"","lastName":"Álvarez-Mon","suffix":""},{"id":276339404,"identity":"81dfc30a-3c38-40d2-8959-b716a958a131","order_by":6,"name":"MA Alvarez-Mon","email":"","orcid":"","institution":"University of Alcala","correspondingAuthor":false,"prefix":"","firstName":"MA","middleName":"","lastName":"Alvarez-Mon","suffix":""}],"badges":[],"createdAt":"2024-02-26 22:29:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3992089/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3992089/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12891-024-07687-5","type":"published","date":"2024-07-22T16:15:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52183858,"identity":"9315954e-a029-4adb-8039-a9cf0c071f9c","added_by":"auto","created_at":"2024-03-07 18:15:40","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45770,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of tweets per disease generated by X users between 2018 and 2022.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3992089/v1/d3f01cd88c25a963c0870a62.jpg"},{"id":52183857,"identity":"cf289b8b-cf32-471c-870a-8cdb50fa207a","added_by":"auto","created_at":"2024-03-07 18:15:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51981,"visible":true,"origin":"","legend":"\u003cp\u003eTweets distribution by disease and emotion between 2018 and 2022.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3992089/v1/0446cfc48e39bae5e29f6589.jpg"},{"id":52183859,"identity":"ecbff30f-a9bf-4f73-999b-69bfd4788683","added_by":"auto","created_at":"2024-03-07 18:15:40","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40108,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the total number of retweets by disease and emotion between 2018 and 2022.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3992089/v1/092ebe2e1f1818a2b33ff7b1.jpg"},{"id":52183856,"identity":"1986cc81-18ca-4b3e-a0c0-348641ef5048","added_by":"auto","created_at":"2024-03-07 18:15:40","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":94889,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA.\u003c/strong\u003e Number of tweets per quarter between 2018 and 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e. Tweets mean retweets distribution per quarter between 2018 and 2022.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe data are shown by disease, with each represented by a different color.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3992089/v1/fe88b1d7b0051475e39bfb86.jpg"},{"id":52183855,"identity":"44c8665a-01c7-4592-83ef-b4d55bc8a27a","added_by":"auto","created_at":"2024-03-07 18:15:40","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":76790,"visible":true,"origin":"","legend":"\u003cp\u003eGeolocation Map: Geographic distribution of tweets by disease.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEach color represents a different disease (yellow: paraplegia; orange: neuropathy; red: multiple sclerosis; blue: fibromyalgia; green: headache).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3992089/v1/54180550ee6d87026e87d35d.jpg"},{"id":61596418,"identity":"7a5939da-8991-4106-b2ed-add8f29dc4e0","added_by":"auto","created_at":"2024-08-01 17:27:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":755939,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3992089/v1/9ed6486a-cc69-4c38-b864-c05ee52f06a8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding Public Perceptions and Discussions on Fibromyalgia through Social Media: Cross-Sectional Infodemiology Study","fulltext":[{"header":"1. BACKGROUND","content":"\u003cp\u003eChronic and recurrent pain is a highly prevalent medical condition that negatively impacts quality of life\u003csup\u003e1\u003c/sup\u003e and is associated with considerable functional disability\u003csup\u003e2\u003c/sup\u003e. Current efforts to diagnose and identify diseases that present with chronic pain, such as fibromyalgia, have become increasingly prominent.\u003c/p\u003e \u003cp\u003eFibromyalgia is a common condition of unknown etiology, characterized by widespread chronic pain, physical exhaustion, cognitive difficulties, depressed mood, sleep problems, and impaired health-related quality of life\u003csup\u003e3\u003c/sup\u003e. This condition causes disability with high direct (healthcare, medications) and indirect (productivity loss) costs\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe prevalence of fibromyalgia is estimated to be between 2% and 8% of the general population worldwide and the prevalence of fibromyalgia increases with the comorbidity of specific disorders\u003csup\u003e5\u003c/sup\u003e. It is more predominant in females\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe diagnosis of fibromyalgia is challenging; it requires differential diagnosis among various medical entities\u003csup\u003e7\u003c/sup\u003e. Additionally, diagnostic delay can have a significant impact on the quality of life and emotional state of patients, as well as on medical and social costs\u003csup\u003e8\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAccording to the International Association for the Study of Pain (IASP) criteria for the International Classification of Diseases, 11th Revision (ICD-11), the World Health Organization (WHO) classified fibromyalgia as primary generalized chronic pain (code MG30.01), with the basic diagnostic criteria being\u003csup\u003e6\u003c/sup\u003e: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Pain lasting at least 3 months that occurred in at least six parts of the body and was defined as multisite pain. Additionally, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) the pain must be accompanied by fatigue (physical or mental) or sleep disturbances considered by a physician to be at least of moderate severity.\u003c/p\u003e \u003cp\u003eIn recent years, social media has become an important source of information where users express and share ideas, opinions, thoughts, and experiences on a multitude of topics\u003csup\u003e9\u003c/sup\u003e. Platforms such as Twitter (now X), with more than 320\u0026nbsp;million users, can provide rapid and wide-reaching dissemination of health-related information that can be collected and analysed for research, including infodemiology and infoveillance\u003csup\u003e10,11\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInformation obtained through social media has been shown to be as reliable as traditional survey data\u003csup\u003e12\u003c/sup\u003e. Thus, using data analysis and mining techniques, this information can potentially be useful for determining specific health conditions\u003csup\u003e9\u003c/sup\u003e. However, until now, no research has evaluated the information about fibromyalgia circulated on social media.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) examine the volume and type of tweets related to chronic pain; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) analyse the emotions expressed on X regarding fibromyalgia and other diseases associated with chronic pain such as headache, paraplegia, neuropathy, and multiple sclerosis; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) compare the societal impact of different diseases associated with chronic pain.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Data Collection:\u003c/h2\u003e \u003cp\u003eWe used X to gather posts from users, both in English and Spanish, about diseases associated with chronic pain. The data collection period ranged from January 1, 2018, to December 31, 2022. To do this, we utilized Tweet Binder's API, allowing us to gather all publicly available tweets containing keywords for the diseases of interest.\u003c/p\u003e \u003cp\u003eThe keywords used were as follows: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \"fibromyalgia\"; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \"headache\", \"migraine\"; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) \"multiple sclerosis\"; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) \"polyneuropathy\", \"neurophaty\", \"neuralgia\"; and (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) \"paraplegia\", \"tetraplegia\", and their equivalents in Spanish. In total, 72,874 tweets were collected, and from each of them, data were obtained regarding the date and time of creation, the publicly displayed user name, the text, geolocation, and the status of \"likes\" and \"retweets\".\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data Processing:\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Topic Modelling (LDA):\u003c/h2\u003e \u003cp\u003eThis study adopted an unsupervised learning approach, using Latent Dirichlet Allocation (LDA) for topic modelling. After a comprehensive review of available techniques, LDA was chosen due to its simplicity and widespread utilization, as evidenced in existing work on X\u003csup\u003e13,14,15\u003c/sup\u003e. Our research primarily focuses on applying a well-documented technique within a novel database, aiming to extract meaningful insights from the data. Prior to the application of the topic modelling model, an extensive data preprocessing procedure was implemented. This preprocessing encompassed language classification, segregating Spanish tweets from others and subsequently translating the Spanish tweets into English using the Google translator application. The text was subsequently cleaned by removing stopwords, duplicate words, and nonstandard characters, such as emojis or hashtags.\u003c/p\u003e \u003cp\u003eTo find the optimal number of topics in topic modelling, a Cluster Validity Index (CVI) was employed. CVIs are measures used in unsupervised learning to evaluate the effectiveness of clustering by assessing how well data points are organized\u003csup\u003e16\u003c/sup\u003e. The silhouette coefficient was the CVI selected due to its ability to assess both intercluster and intracluster distances. Finally, LDA was applied to the 5 pain-related diseases analysed (fibromyalgia, headache, paraplegia, neuropathy, and multiple sclerosis).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Emotional Extraction:\u003c/h2\u003e \u003cp\u003eFinally, emotion detection was conducted using a model from Hugging Face's machine learning platform named \"Emotional English DistilRoBERTa-base\"\u003csup\u003e17\u003c/sup\u003e. This model is recognized as a state-of-the-art model for detecting Ekman's six basic emotions: namely, anger, disgust, fear, joy, sadness, and surprise, with the addition of neutral emotion\u003csup\u003e18\u003c/sup\u003e. Capturing these emotions is crucial in our case, as per the insights from physicians. The selected model has demonstrated superior performance in capturing these specified emotions demonstrating an accuracy of 66%, surpassing the random-chance baseline of 14%\u003csup\u003e13,18\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Number of tweets:\u003c/h2\u003e\n \u003cp\u003eFor this work, our search tool provided 72,874 original tweets, both in English and Spanish, from January 2018 to December 2022. The number of tweets generated in English was 44,467 (61.02%), while in Spanish, there were 28,407 tweets (38.98%). Of these tweets, 70,588 were analysed, with the remaining 2,286 tweets considered unclassifiable.\u003c/p\u003e\n \u003cp\u003eThe number of tweets related to each of the diseases \u003cem\u003e(\u003c/em\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e followed a homogeneous pattern except for the case of neuropathy, which had the lowest frequency of related publications, specifically 8,830 tweets (12.5%). However, there is a preferential accumulation in the case of paraplegia with 16,461 tweets, representing 23.3% of the classifiable tweets. It is followed by headache and fibromyalgia, with similar numbers of tweets, 15,337 (21.7%) and 15,179 (21.5%) tweets, respectively. Finally, 14,781 tweets related to multiple sclerosis represented 21% of the total classifiable tweets.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. LDA:\u003c/h2\u003e\n \u003cp\u003eThrough LDA, we detected the most frequently associated topics for each disease. In the case of headache, the most recurrent topics are its triggers, the association between headache and Coronavirus Disease 2019 (COVID-19), and the COVID-19 vaccine and treatments used. Advances in research on paraplegia have been made, as individuals with paraplegia participate in sporting events, and the etiology of the disease well known. out. Focusing on fibromyalgia, topics mainly revolve around the definition of the disease, symptoms, and available treatments. For multiple sclerosis, discussions involve the diagnosis of the disease, efforts to raise funds for research, and new treatments. Finally, when analysing tweets related to neuropathy, the most prominent topics were the effects of the COVID-19 vaccine, diseases associated with neuralgia, and available treatments.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Emotional Extraction:\u003c/h2\u003e\n \u003cp\u003eAfter extracting emotions from the collected tweets, we further investigated the distribution by disease and emotion, attempting to determine the types of emotions \u003cem\u003e(\u003c/em\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e associated with diseases associated with chronic pain. The results showed that both \u0026quot;fear\u0026quot; and \u0026quot;sadness\u0026quot; were the dominant types of emotions in each group, following the same frequency order according to disease, headache, fibromyalgia, paraplegia, multiple sclerosis, and neuropathy. In contrast, the number of tweets addressing emotions such as \u0026quot;joy,\u0026quot; \u0026quot;surprise,\u0026quot; \u0026quot;anger,\u0026quot; and \u0026quot;disgust\u0026quot; was much lower, with paraplegia, multiple sclerosis, and headache standing out among the diseases.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. Reach and Impact:\u003c/h2\u003e\n \u003cp\u003eParaplegia was the content that generated the greatest number of tweets. However, no correlation was detected between the frequency of tweets published in each category and subsequent retweets, with tweets related to headache showing the highest interest and interaction among users.\u003c/p\u003e\n \u003cp\u003eWe investigated the interest generated by these tweets by examining the number of retweets per disease and emotion \u003cem\u003e(\u003c/em\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e received. When studying the reach of retweets, the potential impact of tweets addressing headache associated with emotions such as \u0026quot;joy,\u0026quot; \u0026quot;surprise,\u0026quot; \u0026quot;sadness,\u0026quot; \u0026quot;anger,\u0026quot; \u0026quot;fear,\u0026quot; and \u0026quot;neutral\u0026quot; was discovered, followed by tweets related to multiple sclerosis and fibromyalgia.\u003c/p\u003e\n \u003cp\u003eAs an exception, tweets expressing a feeling of \u0026quot;disgust\u0026quot; were notable, as they showed a clear difference in the number of retweets related to multiple sclerosis, followed by headache and fibromyalgia.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5. Temporal Evolution:\u003c/h2\u003e\n \u003cp\u003eWe evaluated the evolution of the number of tweets published by X users between January 2018 and December 2022 and represented it in a graph by four-month periods \u003cem\u003e(Fig.\u0026nbsp;4-A).\u003c/em\u003e Throughout the years analysed, we observed a progressive increase in the number of tweets generated about fibromyalgia since January 2018, with a particular peak in the second four-month period of 2019. From this point, there was a progressive decrease in the number of publications until the third four-month period of 2020, followed by a plateau in subsequent years, with a new peak occurring from May to August 2022.\u003c/p\u003e\n \u003cp\u003eTweets related to paraplegia and neuropathy experienced a similar evolution in the studied five-year period, with a progressive increase in the number of publications starting from the third four-month period of 2021. On the other hand, the trend observed in tweets related to headache showed several peaks in the second and first four-month periods of 2018 and 2020, respectively. In the publications about multiple sclerosis, the quantity of tweets followed a homogeneous pattern with several peaks throughout the five years analysed.\u003c/p\u003e\n \u003cp\u003eWe also studied the kinetics of retweets \u003cem\u003e(Fig.\u0026nbsp;4-B)\u003c/em\u003e and observed a homogeneous evolution of tweets related to paraplegia and neuropathy. On the other hand, it is important to note that we observed a particular peak in the number of headache retweets generated in the third four-month period of 2020, followed by a notable increase in subsequent years. However, the evolution of retweets was not homogeneous among the diseases fibromyalgia and multiple sclerosis, where we observed a constant increase or decrease during the years included in our search, especially in the distribution of retweets.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6. Geographic Location:\u003c/h2\u003e\n \u003cp\u003eWe extracted the geographic locations of these tweets to analyse the trends in the volumes of the studied tweets. The distribution of the tweets by continent \u003cem\u003e(\u003c/em\u003eFig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e was predominantly from America and Europe rather than from other continents, with their representation being anecdotal.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e4.1\u003c/b\u003e. \u003cb\u003eMain Findings\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eIn this study, based on published tweets, we found that X users were most interested in discussing paraplegia. Through LDA, we found that treatment was the most prevalent topic, followed by etiology and research advancements. Notably, in the case of fibromyalgia, symptoms and the definition of the disease have garnered much attention. The dominant emotions were \"fear\" and \"sadness\". Surprisingly, there was no correlation between the number of tweets and their impact measured through generated retweets; ultimately, when analysing the temporal evolution, the trend in the number of tweets was homogeneous, with a particular peak observed in fibromyalgia-related tweets.\u003c/p\u003e \u003cp\u003eThe interest generated by different chronic pain-related diseases among X users was homogeneous, except in the case of neuropathy, where the number of tweets was clearly lower. We know that neuropathy affects older populations more than younger populations, and generally, X users tend to be younger, limiting the information published regarding this condition. On the other hand, the diagnosis of neuropathic pain is underestimated, and these negative or stigmatizing attitudes have led to less interest from society\u003csup\u003e19\u003c/sup\u003e. However, we found studies where such stigmatization further increased the demand for validated information from sources other than formal institutions, more frequently from social media platforms\u003csup\u003e20,21\u003c/sup\u003e. Conversely, the popularity of paraplegia among X users could have a direct relationship with various clinical and preclinical studies from recent decades reporting on the potential effects of epidural electrical stimulation in the treatment of spinal cord injuries (SCIs)\u003csup\u003e22\u003c/sup\u003e, as well as the search for other alternative treatment strategies\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSocial media plays a significant role in shaping opinions and emotions through the dissemination of information\u003csup\u003e24\u003c/sup\u003e, and we believe that retweets serve as a measure of users' particular interest in a topic, which is associated with the emotions evoked by tweets\u003csup\u003e25\u003c/sup\u003e. For instance, sentiment analysis of a large number of messages can provide valuable insights into the mood of the crowd\u003csup\u003e12\u003c/sup\u003e and their health status\u003csup\u003e26\u003c/sup\u003e. The predominance of emotions related to \"sadness\" and \"fear\" may be justified because chronic pain is one of the most common health problems in the population, and leads to functional disability, individual suffering, and high costs\u003csup\u003e27\u003c/sup\u003e. These negative emotions also stem from a lack of adequate treatment, as studies in Europe report that approximately 14% of patients discontinued treatment owing to side effects, and up to 40% received treatment they deemed inadequate\u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this way, diseases associated with chronic pain are a cause for concern among X users, as reflected in their posts, especially regarding headache, considered the most common neurological disorder in the population\u003csup\u003e28\u003c/sup\u003e, and fibromyalgia, both of which have a negative impact on people's well-being\u003csup\u003e29\u003c/sup\u003e. Furthermore, the subjectivity in the diagnosis of both conditions undermines the perception that the population has of these diseases. Like in individuals with mental illnesses, addiction, and many other painful disorders, migraine is invisible and cannot be measured or confirmed by an objective diagnostic test. Compared to individuals with epilepsy, which has a physical manifestation, individuals with chronic migraine are seen as less reliable, less inclined to exert themselves, and more prone to feigning illness\u003csup\u003e30,31\u003c/sup\u003e. Thus, \"less visible\" diseases or those causing greater societal rejection are the most feared and can lead to greater sadness, despite being less severe than conditions such as paraplegia or multiple sclerosis.\u003c/p\u003e \u003cp\u003eOn the other hand, the number of tweets addressing emotions such as \"joy\" and \"surprise\" regarding conditions such as paraplegia, multiple sclerosis, and headache is surprising. This relationship could be explained by recent studies indicating that the European population with SCIs\u003csup\u003e32\u003c/sup\u003e shows high or very high satisfaction with the availability of medical care related to these injuries. In multiple sclerosis, the exact etiology is still unclear, but there has been an association with an abnormal response within the central nervous system, possibly due to an infectious agent\u003csup\u003e33\u003c/sup\u003e. As knowledge about Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to advance, the literature has shown that a significant number of patients experience headaches, the most common and mildest neurological manifestation\u003csup\u003e34\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we found that users of X had greater interactions when the content of the tweets was related to headache, likely because headache is the most common neurological disorder in the population\u003csup\u003e28\u003c/sup\u003e. Many studies have demonstrated the use of social media platforms to share experiences with headaches\u003csup\u003e35,36\u003c/sup\u003e. Additionally, there are multiple reports linking headaches with social media use\u003csup\u003e29\u003c/sup\u003e, as somatic symptoms, including headaches, have been found primarily in patients with problematic use of social media\u003csup\u003e29,37\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegarding the temporal evolution of the disease, our data showed that the number of tweets about fibromyalgia decreased between the second and third trimesters of 2019, reaching its lowest level in the third trimester of 2020 in the context of the SARS-CoV-2 pandemic. The uncertainty of the SARS-CoV-2 pandemic caused an abrupt interruption of treatment for patients suffering from chronic pain, resulting in potential unintended harm. For example, in the fibromyalgia population, there is an association between negative emotions (\"fear\" or \"sadness\") and less information dissemination, although user interaction is more common. Regarding the effects of the pandemic, studies confirm that COVID-19 has altered the daily functioning of departments by prioritizing hospital services exclusively for life\u003csup\u003e38\u003c/sup\u003e. This not only occurred with fibromyalgia; for instance, research has demonstrated the impact of the pandemic on the treatment of neurological diseases such as multiple sclerosis, especially due to the high risk of initiating immunosuppressive treatments\u003csup\u003e38,39\u003c/sup\u003e and delays or cancellations of electrodiagnostic studies\u003csup\u003e38,40\u003c/sup\u003e. On the other hand, there was a general reluctance to visit hospitals among the population. We can speculate that the incidence of neurological emergencies did not decrease during the COVID-19 pandemic but rather that differences in the number of patients were due to alterations in public health policy and users' reluctance to visit hospitals\u003csup\u003e38\u003c/sup\u003e. However, longer-term follow-up studies are needed to evaluate the lasting consequences of the pandemic on the prevalence of neurological diseases and the treatment of patients with chronic neurological disorders\u003csup\u003e38\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIt is relevant to recognize the association of temporal evolution in the analysis of tweets about fibromyalgia and headache with the SARS-CoV-2 pandemic. The literature describes the persistence of a wide range of symptoms long after the acute phase of severe acute respiratory syndrome caused by SARS-CoV-2\u003csup\u003e41,42\u003c/sup\u003e, including extreme fatigue, musculoskeletal pain, headache, sleep disorders, anxiety, and depression\u003csup\u003e24,42,43\u003c/sup\u003e. This clinical picture is associated with poor quality of life and severe deterioration of functional capacity and is known as post-COVID-19 syndrome; these conditions may resemble fibromyalgia because they meet the same diagnostic criteria. Similarly, the exacerbation or onset of fibromyalgia symptoms can occur during or after SARS-CoV-2 infection or due to numerous and persistent stressors imposed daily by the pandemic environment\u003csup\u003e44\u003c/sup\u003e. Awareness among the general population and healthcare professionals about the development of this syndrome may have led to a decrease in interest in fibromyalgia. However, in the same context, publications and interactions about headache increase, because it is part of this syndrome.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Limitations:\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, X users are typically younger; thus, sectors of the population without access to the Internet or social media (such as elderly people or those with low socioeconomic status) may be excluded. This limits the generalizability of our results, particularly in this field where the average age of patients is older than that of the most common users. Second, we limited our analysis to tweets in English and Spanish, which may limit the ability to extrapolate the results since populations not speaking these languages may have different interests or concerns regarding these diseases. Third, subjectivity could be a major limitation when specifically coding content that tends to trivialize, where emotional tone or double entry is crucial, as well as denial or irony, which can influence classification by emotions. Additionally, media outlets do not necessarily reflect the interests of society and may be influenced by financial conflicts of interest from companies\u003csup\u003e45\u003c/sup\u003e. However, it is worth noting that, despite these limitations, our methodology is consistent with previous medical research on Twitter (now X)\u003csup\u003e46\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eIn general, this study confirmed the opportunity for social media analysis to provide information about public sentiment toward chronic pain diseases, such as fibromyalgia. Our results contribute to understanding the role that social media plays in promoting public awareness of chronic pain and improving the comprehensive understanding of patients who suffer from it and its treatment.\u003c/p\u003e \u003cp\u003eAlthough this study focused on two languages, these results offer relevant information that is likely applicable to other countries.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul\u003e\n \u003cli\u003eCOVID-19 (COronaVIrus Disease 2019)\u003c/li\u003e\n \u003cli\u003eCVI (Cluster Validity Index)\u003c/li\u003e\n \u003cli\u003eIASP (International Association for the Study of Pain)\u003c/li\u003e\n \u003cli\u003eICD-11 (International Classification of Diseases)\u003c/li\u003e\n \u003cli\u003eLDA (Latent Dirichlet Allocation)\u003c/li\u003e\n \u003cli\u003eRTs (Retweets)\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSARS-CoV-2 (Severe Acute Respiratory Syndrome COronaVirus 2)\u003c/li\u003e\n \u003cli\u003eSCI (Spinal Cord Injury).\u003c/li\u003e\n \u003cli\u003eWHO (World Health Organization)\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThis study received approval from the Research Ethics Committee of the University of Alcala and complied with the research ethics principles established in the Declaration of Helsinki. However, this research did not involve human subjects directly or included any human intervention, as it used publicly available tweets. Nevertheless, we took special care not to disclose the names of users and avoided quoting tweets that could reveal them.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: The datasets generated and/or analyzed during the current study are available upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This work was funded by the Carlos III Health Institute (Ref. PI22/00653) (Spain).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eMTV, FC, and MAA-M were the main contributors to the research design, coordination of the data analysis, and manuscript preparation. MAA-M specifically coordinated the data acquisition. MTV and FC were tweet coders, and contributed to codebook development, training, and analysis of the tweets. MM-T and FJL-A conducted the data processing and statistical analysis. MAO and MA-M contributed to the manuscript as reviewers. MAA-M was the main supervisor in all phases of the project, with special involvement in the study design, data interpretation, and manuscript preparation. All the authors have read and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSchopflocher D, Taenzer P, Jovey R. The prevalence of chronic pain in Canada. Pain Res Manag. 2011 Nov-Dec;16(6):445-50. 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PMID: 32584408; PMCID: PMC7317605.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Twitter, fibromyalgia, headache, paraplegia, multiple sclerosis, neuropathy, chronic pain, infodemiology, and their equivalents in Spanish","lastPublishedDoi":"10.21203/rs.3.rs-3992089/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3992089/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Fibromyalgia is a prevalent condition of unknown etiology, characterized by generalized chronic pain that leads to disability, and has significant direct and indirect costs. The objective of this study was to examine the content and key aspects of tweets pertaining to diseases associated with chronic pain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We investigated tweets published between January 1, 2018, and December 31, 2022, by English and Spanish-speaking Twitter users, as well as generated retweets. Additionally, emotions were extracted from these tweets and their dissemination was analysed. Similarly, the topics that users most frequently address were compiled.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In total, 72,874 tweets were analysed in both English (44,467) and Spanish (28,407). Paraplegia represented 23.3%, with 16,461 classifiable tweets, followed by headache and fibromyalgia, with 15,337 (21.7%) and 15,179 (21.5%) tweets, respectively. Multiple sclerosis generated 14,781 tweets (21%), while the lowest number of tweets was associated with neuropathy, totaling 8,830 tweets (12.5%). The findings revealed that the primary emotions extracted were \"fear\" and \"sadness\". Furthermore, the scope and impact of these tweets were investigated through the generated retweets, with those related to headaches being of the highest interest and having the greatest interaction among users.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Our findings contribute to understanding the role that social media plays in fostering public awareness of chronic pain and improving patients' comprehension and treatment. Moreover, these results are likely to be applicable to other countries whose languages were not covered in our study.\u003c/p\u003e","manuscriptTitle":"Understanding Public Perceptions and Discussions on Fibromyalgia through Social Media: Cross-Sectional Infodemiology Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-07 18:15:35","doi":"10.21203/rs.3.rs-3992089/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-22T04:46:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-15T15:08:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-14T04:35:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1381b1fd-ed2a-48e5-b2ed-eec4ed111c8b","date":"2024-04-08T22:23:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90877ada-5cf1-4ed6-9807-a0f9a3ba1fe0_SNPRID","date":"2024-04-07T01:07:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-06T21:42:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-18T16:33:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-04T18:54:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-04T18:51:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Musculoskeletal Disorders","date":"2024-02-26T22:16:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b437b46d-9632-470f-96fa-a786ce3228a0","owner":[],"postedDate":"March 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-01T17:09:04+00:00","versionOfRecord":{"articleIdentity":"rs-3992089","link":"https://doi.org/10.1186/s12891-024-07687-5","journal":{"identity":"bmc-musculoskeletal-disorders","isVorOnly":false,"title":"BMC Musculoskeletal Disorders"},"publishedOn":"2024-07-22 16:15:44","publishedOnDateReadable":"July 22nd, 2024"},"versionCreatedAt":"2024-03-07 18:15:35","video":"","vorDoi":"10.1186/s12891-024-07687-5","vorDoiUrl":"https://doi.org/10.1186/s12891-024-07687-5","workflowStages":[]},"version":"v1","identity":"rs-3992089","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3992089","identity":"rs-3992089","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}