Social media in epilepsy: A quantitative and qualitative analysis

Meng, Ying; Elkaim, Lior M.; Wang, Justin; Liu, Jessica; Alotaibi, Naif M.; Ibrahim, George M.; Fallah, Aria; Weil, Alexander G.; Valiante, Taufik A.; Lozano, Andrés M.; Rutka, James T.

doi:10.1016/j.yebeh.2017.04.033

Cited by 63 publications

(51 citation statements)

References 25 publications

(25 reference statements)

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“…Previous studies have analyzed the use of social media for epilepsy 26 . One study showed that the number of online users interested in epilepsy is likely the highest among all neurologic conditions 14 . It also found that the most common content on social media on the topic relates to providing more information and resolving misconceptions about epilepsy 14 .…”

Section: Discussionmentioning

confidence: 99%

“…One study showed that the number of online users interested in epilepsy is likely the highest among all neurologic conditions 14 . It also found that the most common content on social media on the topic relates to providing more information and resolving misconceptions about epilepsy 14 . Such information should be very useful to teenagers because the analysis of the mindset behind epilepsy and suicide‐related online conversations suggest that a large majority (63%) of teenagers are bothered by not knowing what to expect from their condition and live in fear of the “unknown.” This is a stark difference from adults, as only 12% of them are fearful of the “unknown,” likely due to their longer life experience.…”

Section: Discussionmentioning

confidence: 99%

“…There are many recent examples of successful uses of social media in healthcare research 10–13 . Some studies have explored the use of social media by PWE to understand and explore their experiences and concerns 14 . Teenagers are the most avid users of social media and spend a substantial portion of their time on it 15,16 .…”

Section: Introductionmentioning

confidence: 99%

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Digital conversations about suicide among teenagers and adults with epilepsy: A big‐data, machine learning analysis

et al. 2020

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Epilepsia. 2020;61:951-958. | 951 wileyonlinelibrary.com/journal/epi Abstract Objective: Digital media conversations can provide important insight into the concerns and struggles of people with epilepsy (PWE) outside of formal clinical settings and help generate useful information for treatment planning. Our study aimed to explore the big data from open-source digital conversations among PWE with regard to suicidality, specifically comparing teenagers and adults, using machine learning technology. Methods: Advanced machine-learning empowered methodology was used to mine and structure open-source digital conversations of self-identifying teenagers and adults who endorsed suffering from epilepsy and engaged in conversation about suicide. The search was limited to 12 months and included only conversations originating from US internet protocol (IP) addresses. Natural language processing and text analytics were employed to develop a thematic analysis. Results: A total of 222 000 unique conversations about epilepsy, including 9000(4%) related to suicide, were posted during the study period. The suicide-related conversations were posted by 7.8% of teenagers and 3.2% of adults in the study. Several critical differences were noted between teenagers and adults. A higher percentage of teenagers are: fearful of "the unknown" due to seizures (63% vs 12% adults), concerned about social consequences of seizures (30% vs 21%), and seek emotional support (29% vs 19%). In contrast, a significantly higher percentage of adults show a defeatist ("given up") attitude compared to teenagers (42% vs 4%). There were important differences in the author's determined sentiments behind the conversations among teenagers and adults. Significance: In this first of its kind big data analysis of nearly a quarter-million digital conversations about epilepsy using machine learning, we found that teenagers engage in an online conversation about suicide more often than adults. There are some key differences in the attitudes and concerns, which may have implications for the treatment of younger patients with epilepsy. |FALCONE Et AL.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Digital conversations about suicide among teenagers and adults with epilepsy: A big‐data, machine learning analysis

et al. 2020

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“…31,[40][41][42][43][44][45][46][47][48] Moreover, while the social milestones examined here, including divorce and fractured family dynamics, are common across any population, what we have described are changes in social trajectories that patients attribute to the process of undergoing surgery. In such research, a specific "control" group, healthy or medical, is typically not relevant.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Identifying the trajectory of social milestones 15‐20 years after epilepsy surgery: Realistic timelines for postsurgical expectations

2019

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Objective Patients often undertake epilepsy surgery with the expectation that it will lead to improvements in their social situation. Short‐ to medium‐term research consistently points toward improvements in social outcomes; however, no study has mapped out postsurgical social timelines, particularly for longer‐term (>15 years) outcomes. Methods We recruited 39 patients who had undergone anterior temporal lobectomy (ATL) for drug‐resistant temporal lobe epilepsy (TLE) between 1994 and 2002. The cohort (24 females) had a median age of 49 years (range 38‐67), age of habitual seizure onset was 9.5 years (range 0.5‐29 years), and age at surgery was 31 years (range 20‐53). Patients were followed up for a median of 18.4 years postsurgery (IQR = 4.4). Using data obtained from semistructured interviews, we conducted a comprehensive qualitative analysis of patients' self‐reported postsurgical social trajectories. Self‐report questionnaires were used to assess mood and health‐related quality of life (HRQOL) at the time of interview. Results There was a common sequence of social milestone achievement, spanning 20 years postsurgery. Typically, patients first (re)gained their license, then attempted educational and vocational gains, followed by establishing long‐term relationships and finally a family unit. Rare, intermittent seizures postsurgery did not appear to have detrimental effects on social trajectories. Those who experienced a reduction in seizures showed increased likelihood of attaining social milestones compared to those with ongoing seizures. Significance Achieving social milestones after epilepsy surgery may take considerably longer than patients are expecting prior to surgery. The pattern of social milestone outcome resembled a process of psychosocial development. These findings have important implications for presurgical counseling and postsurgical rehabilitation.

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“…Moreover, the qualitative and quantitative relevance of tweets has been shown in various investigations, including analyses of the interests and feelings of the general population with respect to health/disease, the interactions between patients and doctors/health providers and the generation of the scientific impact of medical research in the news media. Furthermore, patient attitudes toward various medical topics, including vaccines, illnesses, pain, drug use, and both oncological and cardiovascular disease, have been analyzed [23][24][25][26][27][28][29][30][31]. Consequently, the analysis of distributed tweets by primary social media channels on mental health disease and the frequency of retweets generated may be effective tools for assessing social and individual interest toward psychiatric diseases.…”

Section: Introductionmentioning

confidence: 99%

Increasing Interest of Mass Communication Media and the General Public in the Distribution of Tweets About Mental Disorders: Observational Study (Preprint)

Alvarez-Mon¹,

Barco²,

Lahera³

et al. 2017

Preprint

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Background: The contents of classical communication media and new Internet social media reflect the interests of society. Barriers and a lack of attention for mental diseases have been previously observed. Objective: To measure the relevance given by the main American social communication media (ASCM) to psychiatric information and the interest generated in their Twitter followers. Methods: We investigated the tweets generated about mental health conditions and disease by 15 main United States of America (USA) general communication media from January 2007 to December 2016. Our study strategy focused on identifying several psychiatric terms of main interest. The number of retweets generated by the selected tweets was also investigated. For a control, we used tweets generated about the main causes of death in the USA, the main chronic neurological degenerative diseases and infection by the human immunodeficiency virus (HIV). Results: In total, 13,119 tweets sent by the ASCM about mental health disorders show a heterogeneous distribution with preferential accumulation in a reduced number of conditions. Suicide and gender dysphoria accumulated half of the number of sent tweets. Variability in the number of tweets related to each control disease was also found (5,998). The number of tweets sent regarding each different psychiatric or organic disease analyzed was significantly correlated with the number of retweets generated by followers (1,030,974 and 424,813 responses to metal health disorders and organic diseases, respectively). However, the probability of a tweet being retweeted was statistically different between the conditions and diseases analyzed. Furthermore, the retweeted/tweet ratio was significantly higher in psychiatric diseases than in the control organic diseases (OR=1.11 [1.07-1.14], p<0.001). Conclusions: According to the use of Twitter, the ASCM and the general public demonstrate a preferential interest for psychiatric diseases. The heterogeneous weight given by the ASCM to the different mental health disorders and conditions is reflected in the response of Twitter followers.

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Social media in epilepsy: A quantitative and qualitative analysis

Cited by 63 publications

References 25 publications

Digital conversations about suicide among teenagers and adults with epilepsy: A big‐data, machine learning analysis

Digital conversations about suicide among teenagers and adults with epilepsy: A big‐data, machine learning analysis

Identifying the trajectory of social milestones 15‐20 years after epilepsy surgery: Realistic timelines for postsurgical expectations

Increasing Interest of Mass Communication Media and the General Public in the Distribution of Tweets About Mental Disorders: Observational Study (Preprint)

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