Daniel Schneider , Jacob Gluski , Ethan D.L. Brown , Akash Mishra , Harshal A. Shah , Barnabas Obeng-Gyasi , Daniel M. Sciubba , Sheng-Fu Larry Lo
{"title":"了解脊柱护理患者的观点:对2,513个帖子的社交媒体分析揭示了治疗观念的不同模式","authors":"Daniel Schneider , Jacob Gluski , Ethan D.L. Brown , Akash Mishra , Harshal A. Shah , Barnabas Obeng-Gyasi , Daniel M. Sciubba , Sheng-Fu Larry Lo","doi":"10.1016/j.jocn.2025.111624","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>As patients increasingly turn to social media for health information, understanding online patterns of social discourse around medical conditions has become increasingly crucial. This study aimed to identify patient perceptions of common symptoms and interventions in spine care using data from large online communities.</div></div><div><h3>Methods</h3><div>Posts were extracted using the Python Reddit API Wrapper (PRAW) based on 39 predefined keywords covering symptoms (n = 8), interventions (n = 25), and risk factors (n = 6). Natural language processing techniques, including sentiment analysis, were employed to assess relationships between symptoms, interventions, and patient sentiment. Clustering and temporal analyses were used to identify trends in patient discussions.</div></div><div><h3>Results</h3><div>Analysis of 2,513 posts revealed pain as the predominant symptom (74.1 %, n = 1,862), followed by numbness (11.1 %, n = 280) and sciatica (9.7 %, n = 245). Physical therapy was the most discussed intervention (10.8 %, n = 272), followed by medication (5.6 %, n = 140) and microdiscectomy (3.9 %, n = 99). Significant associations emerged between numbness and surgical interventions (microdiscectomy: X<sup>2</sup> = 14.37, p = 0.014; spinal fusion: X<sup>2</sup> = 11.94, p = 0.026). Sentiment analysis revealed modestly positive scores for most interventions, with numbness-microdiscectomy showing the highest positive sentiment (0.066 [0.008, 0.125]). The five identified clusters showed distinct characteristics: Sciatica-Medication (mean sentiment = 0.024, SD = 0.134), Pain-Medication (0.048, SD = 0.119), Numbness-Physical Therapy (0.007, SD = 0.134), Pain-Physical Therapy (0.057, SD = 0.138), and Numbness-Microdiscectomy (0.038, SD = 0.113). Age dominated risk factor discussions (97.6 % of mentions), suggesting limited emphasis on modifiable risk factors. Temporal analysis showed an increase in discussion volume after 2022, particularly around pain-related topics.</div></div><div><h3>Conclusions</h3><div>Our findings highlight how social media analysis can reveal distinct patterns in patient experiences with regards to spine care. Variable sentiment towards interventions and the notable lack of discussion around modifiable risk factors suggest opportunities to enhance preoperative counseling.</div></div>","PeriodicalId":15487,"journal":{"name":"Journal of Clinical Neuroscience","volume":"142 ","pages":"Article 111624"},"PeriodicalIF":1.8000,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding patient perspectives in spine care: A social media analysis of 2,513 posts reveals distinct patterns in treatment perceptions\",\"authors\":\"Daniel Schneider , Jacob Gluski , Ethan D.L. Brown , Akash Mishra , Harshal A. Shah , Barnabas Obeng-Gyasi , Daniel M. Sciubba , Sheng-Fu Larry Lo\",\"doi\":\"10.1016/j.jocn.2025.111624\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>As patients increasingly turn to social media for health information, understanding online patterns of social discourse around medical conditions has become increasingly crucial. This study aimed to identify patient perceptions of common symptoms and interventions in spine care using data from large online communities.</div></div><div><h3>Methods</h3><div>Posts were extracted using the Python Reddit API Wrapper (PRAW) based on 39 predefined keywords covering symptoms (n = 8), interventions (n = 25), and risk factors (n = 6). Natural language processing techniques, including sentiment analysis, were employed to assess relationships between symptoms, interventions, and patient sentiment. Clustering and temporal analyses were used to identify trends in patient discussions.</div></div><div><h3>Results</h3><div>Analysis of 2,513 posts revealed pain as the predominant symptom (74.1 %, n = 1,862), followed by numbness (11.1 %, n = 280) and sciatica (9.7 %, n = 245). Physical therapy was the most discussed intervention (10.8 %, n = 272), followed by medication (5.6 %, n = 140) and microdiscectomy (3.9 %, n = 99). Significant associations emerged between numbness and surgical interventions (microdiscectomy: X<sup>2</sup> = 14.37, p = 0.014; spinal fusion: X<sup>2</sup> = 11.94, p = 0.026). Sentiment analysis revealed modestly positive scores for most interventions, with numbness-microdiscectomy showing the highest positive sentiment (0.066 [0.008, 0.125]). The five identified clusters showed distinct characteristics: Sciatica-Medication (mean sentiment = 0.024, SD = 0.134), Pain-Medication (0.048, SD = 0.119), Numbness-Physical Therapy (0.007, SD = 0.134), Pain-Physical Therapy (0.057, SD = 0.138), and Numbness-Microdiscectomy (0.038, SD = 0.113). Age dominated risk factor discussions (97.6 % of mentions), suggesting limited emphasis on modifiable risk factors. Temporal analysis showed an increase in discussion volume after 2022, particularly around pain-related topics.</div></div><div><h3>Conclusions</h3><div>Our findings highlight how social media analysis can reveal distinct patterns in patient experiences with regards to spine care. Variable sentiment towards interventions and the notable lack of discussion around modifiable risk factors suggest opportunities to enhance preoperative counseling.</div></div>\",\"PeriodicalId\":15487,\"journal\":{\"name\":\"Journal of Clinical Neuroscience\",\"volume\":\"142 \",\"pages\":\"Article 111624\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2025-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Clinical Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0967586825005971\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967586825005971","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Understanding patient perspectives in spine care: A social media analysis of 2,513 posts reveals distinct patterns in treatment perceptions
Background
As patients increasingly turn to social media for health information, understanding online patterns of social discourse around medical conditions has become increasingly crucial. This study aimed to identify patient perceptions of common symptoms and interventions in spine care using data from large online communities.
Methods
Posts were extracted using the Python Reddit API Wrapper (PRAW) based on 39 predefined keywords covering symptoms (n = 8), interventions (n = 25), and risk factors (n = 6). Natural language processing techniques, including sentiment analysis, were employed to assess relationships between symptoms, interventions, and patient sentiment. Clustering and temporal analyses were used to identify trends in patient discussions.
Results
Analysis of 2,513 posts revealed pain as the predominant symptom (74.1 %, n = 1,862), followed by numbness (11.1 %, n = 280) and sciatica (9.7 %, n = 245). Physical therapy was the most discussed intervention (10.8 %, n = 272), followed by medication (5.6 %, n = 140) and microdiscectomy (3.9 %, n = 99). Significant associations emerged between numbness and surgical interventions (microdiscectomy: X2 = 14.37, p = 0.014; spinal fusion: X2 = 11.94, p = 0.026). Sentiment analysis revealed modestly positive scores for most interventions, with numbness-microdiscectomy showing the highest positive sentiment (0.066 [0.008, 0.125]). The five identified clusters showed distinct characteristics: Sciatica-Medication (mean sentiment = 0.024, SD = 0.134), Pain-Medication (0.048, SD = 0.119), Numbness-Physical Therapy (0.007, SD = 0.134), Pain-Physical Therapy (0.057, SD = 0.138), and Numbness-Microdiscectomy (0.038, SD = 0.113). Age dominated risk factor discussions (97.6 % of mentions), suggesting limited emphasis on modifiable risk factors. Temporal analysis showed an increase in discussion volume after 2022, particularly around pain-related topics.
Conclusions
Our findings highlight how social media analysis can reveal distinct patterns in patient experiences with regards to spine care. Variable sentiment towards interventions and the notable lack of discussion around modifiable risk factors suggest opportunities to enhance preoperative counseling.
期刊介绍:
This International journal, Journal of Clinical Neuroscience, publishes articles on clinical neurosurgery and neurology and the related neurosciences such as neuro-pathology, neuro-radiology, neuro-ophthalmology and neuro-physiology.
The journal has a broad International perspective, and emphasises the advances occurring in Asia, the Pacific Rim region, Europe and North America. The Journal acts as a focus for publication of major clinical and laboratory research, as well as publishing solicited manuscripts on specific subjects from experts, case reports and other information of interest to clinicians working in the clinical neurosciences.