Multipl skleroz tedavisine ilişkin internet kaynaklarının kalitesi, güvenilirliği ve yapay zekâ katkısının değerlendirilmesi

Öz

Amaç: Bu çalışmada, multipl skleroz tedavisi ile ilgili çevrimiçi bilgilerin kalite, güvenilirlik ve tahmini yapay zekâ katkısı açısından değerlendirilmesi amaçlandı. Gereç ve Yöntemler: “Multipl skleroz tedavisi” anahtar kelimesi kullanılarak Google arama motorunda elde edilen ilk 100 sonuç incelendi. Video içerikleri, PDF dokümanları ve erişilemeyen web siteleri çalışma dışı bırakıldı. Toplam 84 uygun web sayfası analize dahil edildi. Her sayfa kaynak türüne göre; hastane, bireysel hekim, blog, fizyoterapi merkezi veya dernek olarak sınıflandırıldı. İçerik kalitesi DISCERN ve JAMA ölçütleri kullanılarak değerlendirildi. Tahmini yapay zekâ katkısı Turnitin yapay zekâ yazım tespit aracı kullanılarak değerlendirildi. Bulgular: İncelenen içeriklerin %52,4’ü (n=44) hastane web sitelerinden, %22,6’sı (n=19) bireysel hekim sitelerinden, %14,3’ü (n=12) bloglardan, %6,0’ı (n=5) fizyoterapi merkezlerinden ve %4,8’i (n=4) derneklerden oluşmaktaydı. Ortalama DISCERN skoru 3,38 ± 0,72 olup orta-yüksek düzeyde güvenilirliğe işaret ederken, ortalama JAMA skoru 2,03 ± 0,85 olarak bulundu ve yazarlık ile kaynak şeffaflığı açısından sınırlılıklar olduğunu gösterdi. İncelenen web sitelerinde değişen oranlarda tahmini yapay zekâ katkısı saptandı. Özellikle bireysel hekim web sitelerinde yapay zekâ katkısı (%61,8), hastane web sitelerine kıyasla (%49,9) anlamlı derecede daha yüksekti (p = 0,039). Bununla birlikte, web sitesi türleri arasında DISCERN ve JAMA skorları açısından anlamlı farklılık izlenmedi (p=0.724, p=0.336). Sonuç: Multipl skleroz tedavisine ilişkin çevrimiçi bilgiler orta düzeyde güvenilirlik göstermekte olup, tahmini yapay zekâ katkısının özellikle bireysel hekim web sitelerinde daha yüksek olduğu görülmüştür. Bu bulgular, dijital sağlık içeriklerinin üretiminde standardizasyon ve denetim gereksinimini ortaya koymaktadır.

Anahtar Kelimeler

• Multipl Skleroz
• Çevrimiçi Sağlık Bilgileri
• Yapay Zekâ
• DISCERN
• JAMA Skoru

Evaluating the quality, reliability and artificial intelligence involvement of online information on multiple sclerosis treatment

Öz

Aim: This study aimed to evaluate the quality, reliability and estimated artificial intelligence contribution of online information related to multiple sclerosis treatment. Material and Methods: The first 100 Google search results for "multiple sclerosis treatment" were screened. Video content, PDF documents, and inaccessible websites were excluded from the analysis. A total of 84 eligible web pages were assessed. Each page was categorized by source type (hospital, individual physician, blog, physiotherapy center, or association). Quality was evaluated using the DISCERN and JAMA benchmarks. Estimated artificial intelligence involvement was assessed using Turnitin's AI writing detection tool. Results: Of the analyzed content, 52.4% (n=44) originated from hospital websites, followed by individual physician websites (22.6%, n=19), blogs (14.3%, n=12), physiotherapy centers (6.0%, n=5), and associations (4.8%, n=4). The mean DISCERN score was 3.38 ± 0.72, indicating moderate-to-high reliability, while the mean JAMA score was 2.03 ± 0.85, highlighting limitations in authorship and source transparency. Varying levels of estimated artificial intelligence involvement were identified across the analyzed websites. Notably, individual physician websites demonstrated higher estimated artificial intelligence involvement (61.8%) than hospital websites (49.9%), with a statistically significant difference (p = 0.039). However, no significant differences were observed among website types regarding DISCERN and JAMA scores (p=0.724, p=0.336). Conclusion: Online information on multiple sclerosis treatment exhibits moderate reliability, with varying levels of estimated artificial intelligence involvement, particularly among individual healthcare providers. These findings underscore the need for standardization and oversight in the production of digital health content.

Anahtar Kelimeler

• Multiple Sclerosis
• Online Health Information
• Artificial Intelligence
• DISCERN
• JAMA Score

Kaynakça

1. Hirsch M, Aggarwal S, Barker C, Davis CJ, Duffy JMN. Googling endometriosis: a systematic review of information available on the Internet. Am J Obstet Gynecol. 2017;216(5):451-458.e1. https://doi.org/10.1016/j.ajog.2016.11.1007
2. Leira-Feijoo Y, Ledesma-Ludi Y, Seoane-Romero JM, Blanco-Carrión J, Seoane J, Varela-Centelles P. Available web-based dental implants information for patients. How good is it? Clin Oral Implants Res. 2015;26(11):1276-1280. https://doi.org/10.1111/clr.12451
3. Truumees D, Duncan A, Mayer EK, Geck M, Singh D, Truumees E. Cross sectional analysis of scoliosis-specific information on the internet: potential for patient confusion and misinformation. Spine Deform. 2020;8(6):1159-1167. https://doi.org/10.1007/s43390-020-00156-8
4. Seymour N, Lakhani R, Hartley B, Cochrane L, Jephson C. Cochlear implantation: An assessment of quality and readability of web-based information aimed at patients. Cochlear Implants Int. 2015;16(6):321-325. https://doi.org/10.1179/1754762815Y.0000000015
5. Altunisik E, Firat YE, Kiyak Keceli Y. Content and quality analysis of videos about multiple sclerosis on social media: The case of YouTube. Mult Scler Relat Disord. 2022;65:104024. https://doi.org/10.1016/j.msard.2022.104024
6. Meyer B, Betz LT, Jacob GA, Krause N, Riemann-Lorenz K, Gold SM, et al. Effectiveness of a digital lifestyle management intervention (levidex) to improve quality of life in people with multiple sclerosis: results of a randomized controlled trial. BMC Neurol. 2024;24(1):347. https://doi.org/10.1186/s12883-024-03843-5
7. Dursun D, Bilici Geçer R. Can artificial intelligence models serve as patient information consultants in orthodontics? BMC Med Inform Decis Mak. 2024;24(1):211. https://doi.org/10.1186/s12911-024-02619-8
8. Bourdache LR, Ould Brahim L, Wasserman S, Nicolas-Joseph M, Frati FYE, Belzile E, et al. Evaluation of quality, readability, suitability, and usefulness of online resources available to cancer survivors. J Cancer Surviv. 2023;17(2):544-555. https://doi.org/10.1007/s11764-022-01318-5

9. Sun Y, Liu X, Zhang X, Xu Q, Li A. Health information analysis of cryptorchidism-related short videos: Analyzing quality and reliability. Digit Health. 2025;11:20552076251317578. https://doi.org/10.1177/20552076251317578
10. Corredera E, Davis KS, Simons JP, Jabbour N. What parents are reading about laryngomalacia: Quality and readability of internet resources on laryngomalacia. Int J Pediatr Otorhinolaryngol. 2018;108:175-179. https://doi.org/10.1016/j.ijporl.2018.02.036
11. Guo WJ, Wang WK, Xu D, Qiao Z, Shi YL, Luo P. Evaluating the Quality, Content, and Readability of Online Resources for Failed Back Spinal Surgery. Spine (Phila Pa 1976). 2019;44(7):494-502. https://doi.org/10.1097/BRS.0000000000002870
12. Shazil Jamal M, Hurley ET, Davey MS, Asad H, Gaafar M, Mullett H. Evaluation of the quality of information online for arthroscopic Bankart repair. Ann R Coll Surg Engl. 2023;105(5):394-399. https://doi.org/10.1308/rcsann.2022.0024
13. Connelly TM, Khan MS, Alzamzami M, Cooke F. An evaluation of the quality and content of web-based stoma information. Colorectal Dis. 2019;21(3):349-356. https://doi.org/10.1111/codi.14497
14. Sheridan GA, O'Brien C, Masri BA, Duncan CP, Garbuz DS. Revision total hip arthroplasty: An analysis of the quality and readability of information on the internet. World J Orthop. 2020;11(2):82-89. https://doi.org/10.5312/wjo.v11.i2.82
15. Ding R, Kong Q, Sun L, Liu X, Xu L, Li Y, et al. Health information in short videos about metabolic dysfunction-associated steatotic liver disease: Analysing quality and reliability. Liver Int. 2024;44(6):1373-1382. https://doi.org/10.1111/liv.15871
16. Musbahi A, Ali N, Brown L, Brown S, Viswanath YKS, Etherson K, et al. A Systematic Review of Online Patient Resources to Support Shared Decision Making for Laparoscopic Cholecystectomy. World J Surg. 2021;45(9):2719-2733. https://doi.org/10.1007/s00268-021-06189-y