Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia · 2025
Understanding patient perspectives in spine care: A social media analysis of 2,513 posts reveals distinct patterns in treatment perceptions.
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Schneider Daniel, Gluski Jacob, Brown Ethan D L, Mishra Akash, Shah Harshal A, Obeng-Gyasi Barnabas, Sciubba Daniel M, Lo Sheng-Fu Larry
Аннотация
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.
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.