Dijital Sağlık Alanında En Çok Alıntılan 100 Makalenin Altmetrik, Bibliyometrik ve Görselleştirilmiş Çalışması

Year 2024, , 262 - 275, 22.08.2024

Naime Meric Konar , Aslı Suner

https://doi.org/10.46413/boneyusbad.1420103

Abstract

Amaç: Dijital Sağlık, sağlık risklerini kontrol etmek ve refahı artırmak için tıpta ve diğer sağlık mesleklerinde bilgi teknolojisinin kullanılmasını ifade eder. Bu çalışma, bu konudaki araştırma trendlerini, bu alanda en çok alıntı yapılan 100 makale üzerinden değerlendirmeyi amaçlamaktadır.
Gereç ve Yöntem: Verilere ulaşmak için Web of Science Core Collection (www.webofknowledge.com) veri tabanından yararlanıldı. Söz konusu alandaki belgelerin nitelik ve niceliğini değerlendirmek için bibliyometrik analiz kullanıldı. Makalelerin sosyal medya üzerindeki etkisini ortaya koymak için altmetrik analizle elde edilen Altmetrik İlgi Puanı kullanıldı. Atıf Sayısı ve Altmetrik İlgi Puanı’na etki eden faktörleri ortaya çıkarmak için çoklu doğrusal regresyon analizleri uygulandı.
Bulgular: Dijital Sağlık Alanında en çok atıf alan 100 çalışmanın 2010 ile 2020 yılları arasında yayınlandığı gözlemlendi. İlk 100 listesindeki alıntıların ortalamasının 141,4 ± 78,0 olduğu görüldü. Bununla birlikte Atıf Sayısı ile Altmetrik İlgi Puanı arasında pozitif yönde de olsa zayıf bir korelasyon gözlendi. Regresyon analizi bulguları, Q2 düzeyinin (p=0,050), Altmetrik İlgi Puanının (p=0,002), 2013'ten Bu Yana Kullanım Sayısının (p<0,001) ve Yayın Sonrası Sürenin (p=0,002) Atıf Sayısını etkileyen önemli faktörler olduğu, Sayfa Sayısının (p=0,013) ve 5 yıllık dergi Etki Faktörünün (p<0,001) ise Altmetrik İlgi Puanı’nı etkileyen faktörler olduğu saptandı.
Sonuç: Elde edilen bulgular, ilgili alandaki en güncel gelişmeleri araştırmak için bir fırsat sağlamaktadır. Dahası, çalışmanın araştırma ve geliştirme konusundaki rehberliği, bu alandaki araştırma boşluklarını doldurulmasını olanaklı kılmaktadır.

Keywords

Altmetrik analiz, Bibliyometrik analiz, Dijital sağlık, Sağlık hizmeti, Bilişim, Sağlık bilişimi

Altmetric, Bibliometric, and Visualized Study of Top 100 Most Cited Papers in Digital Health

Abstract

Aim: This study aims to evaluate the research movements in the Digital Health topic through the most cited 100 products.
Material and Method: Top-100 list was obtained by the help of Web of Science Core Collection (www.webofknowledge.com) database. Bibliometric analysis was employed to analyze the documents in detail in the area in question. Altmetric attention score provided by altmetric analysis was utilized to demonstrate the effect of articles on social media. Multiple linear regression analyses were applied to reveal related factors of Citation Count and Altmetric Attention Score.
Results: The most-cited 100 papers in Digital Health topic were observed to be published between 2010 and 2020. Mean and standard deviation of the Citation Counts were 141.4±78. A poor positive association is noted between Citation Count and Altmetric Attention Score (r=0.256, p=0.012). Multiple linear regression analysis findings show that “Q2 level (p=0.050)”, “AAS” (p=0.002”), “Since 2013 Usage Count (p<0.001)” and “Duration after Publication (p=0.002)” are significant factors for Citation Count, while “Page Count (p=0.013)” and “5-Year-IF (p<0.001)” are factors associated with Altmetric Attention Score.
Conclusion: The findings provide an opportunity to investigate the most current improvements in Digital Health, and its guidance on research and development offers the exploration gaps to fill over this field.

Keywords

Altmetric analysis, Bibliometric analysis, Digital health, Healthcare, Informatics, Health informatics

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