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

Yıl 2024, Cilt: 6 Sayı: 2, 262 - 275, 22.08.2024

Naime Meric Konar , Aslı Suner

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

Öz

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.

Anahtar Kelimeler

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

Öz

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.

Anahtar Kelimeler

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

Kaynakça

• Aagja, J. Dr., Shome, S Dr., Chandra, A. Dr. (2023). A bibliometric analysis of digital health & mobile health related global research publications. Hospital Topics, 101(4), 319-325. doi: 10.1080/00185868.2022.2060155.
• Agac, G., Sevim, F., Celik, O., Bostan, S., Erdem, R. & Yalcin, Y. I. (2023). Research hotspots, trends and opportunities on the metaverse in health education: a bibliometric analysis. Library Hi Tech. doi: 10.1108/LHT-04-2023-0168.
• All of Us Research Program Investigators; Denny J. C., Rutter J. L., Goldstein D. B., … Dishman E. (2019). The all of us research program. New England Journal of Medicine, 381(7), 668-676. doi: 10.1056/NEJMsr1809937.
• Altmetric. (2023). What are altmetrics? Erişim tarihi: 17.05.2023, https://www.altmetric.com/about-us/what-are-altmetrics/
• Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. doi: 10.1016/j.joi.2017.08.007.
• Barrett, M. A., Humblet, O., Marcus, J. E., Henderson, K., Smith, T., Eid, N., ... Sublett, J. L. (2017). Effect of a mobile health, sensor-driven asthma management platform on asthma control. Annals of Allergy, Asthma & Immunology, 119(5), 415-421. doi: 10.1016/j.anai.2017.08.002.
• Bucher, A., Blazek, E. S., & West, A. B. (2022). Feasibility of a Reinforcement Learning–Enabled Digital health intervention to promote mammograms: retrospective, single-arm, observational study. JMIR Formative Research, 6(11), e42343. doi: 10.2196/42343.
• Charbonneau, D. H., Hightower, S., Katz, A., Zhang, K., Abrams, J., Senft, N., ... Thompson, H. S. (2020). Smartphone apps for cancer: A content analysis of the digital health marketplace. Digital health, 6, 2055207620905413. doi: 10.1177/2055207620905413.
• Clarivate Analytics Incites Help (2023). Erişim tarihi: 30.10.2023, https://incites.help.clarivate.com/Content/Indicators-Handbook/ih-journal-citation reports.htm? Highlight=Journal%20Impact%20Factor
• Darcy, A., Beaudette, A., Chiauzzi, E., Daniels, J., Goodwin, K., Mariano, T. Y., ... Robinson, A. (2023). Anatomy of a Woebot®(WB001): agent guided CBT for women with postpartum depression. Expert Review of Medical Devices, 20(12), 1035-1049. doi: 10.1080/17434440.2023.2280686
• Faujdar, D.S., Singh, T., Kaur, M., Sahay, S., & Kumar, R. (2021). Stakeholders' perceptions of the ımplementation of a patient-centric digital health application for primary healthcare in India. Healthcare Informatics Research, 27(4), 315-324. doi: 10.4258/hir.2021.27.4.315.
• Fosso, W., & Queiroz, M. M. (2021). Responsible artificial intelligence as a secret ıngredient for digital health: bibliometric analysis, insights, and research directions. Information Systems Frontiers, 1-16. doi: 10.1007/s10796-021-10142-8.
• Galvin, J. R., D'Alessandro, M. P., Erkonen, W. E., Smith, W. L., El-Khoury, G. Y., & Weinstein, J. N. (1995). The virtual hospital. Providing multimedia decision support tools via the Internet. Spine, 20(15), 1735-1738.
• Hajesmaeel-Gohari, S., & Bahaadinbeigy, K. (2022). The 100 most highly cited articles published in the telemedicine journals. Frontiers in Health Informatics. 11(1), 122. doi: 10.30699/fhi.v11i1.391.
• He, L., Guo, Q. F., Hu, Y., Tan, H. X., Chen, Y., Wang, C. H., ... Gao, Q. (2023). Bibliometric and visualised analysis on non-invasive cerebellar stimulation from 1995 to 2021. Frontiers in Neuroscience, 17, 1047238. doi: 10.3389/fnins.2023.1047238.
• Hirsch, J.E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National academy of Sciences, 102(46), 16569-16572.
• Hombaiah, C., Madhu, B., Gopi, A., Narayana Murthy, M.R. (2022). Effects of mobile Health (mHealth) application on cervical cancer prevention knowledge and screening among women social support groups with low-socioeconomic status in Mysuru city, Southern India. PloS One, 17(9), e0273070. doi: 10.1371/journal.pone.0273070.
• Hswen, Y., Brownstein, J. S., Liu, J., & Hawkins, J. B. (2017). Use of a digital health application for ınfluenza surveillance in China. American Journal of Public Health, 107(7), 1130-1136. doi: 10.2105/AJPH.2017.303767.
• Konar, N.M., Karaismailoglu, S., & Karaismailoglu, E. (2022). Status and trends of personalized medicine research from 2000 to 2020: a bibliometric analysis. Current Medical Research and Opinion, 38(5), 837-846. doi: 10.1080/03007995.2022.2052515.
• Konar, N. M. (2021). Research regarding the clinical decision support systems: A bibliometric analysis. Applied Medical Informatics, 43(4), 164-175. available at: https://ami.info.umfcluj.ro/index.php/AMI/article/view/884
• Li, J., Zhang, Y., Herjavić, G., Wine, P., & Klasinc, L. (2014). Bibliometric analysis of research on secondary organic aerosols: Update. Pure and Applied Chemistry, 86(7), 1169-1175. doi: 10.1515/pac-2014-0204.
• Li, T., Zeng, Y., Fan, X., Yang, J., Yang, C., Xiong, Q., … Liu, P. (2023). A bibliometric analysis of research articles on midwifery based on the web of science. Journal of Multidisciplinary Healthcare, 677-692. doi: 10.2147/JMDH.S398218.
• Merton, R. K. (1968). Social Theory and Social Structure. (5th ed.), New York, NY: Free Press.
• Park, S., Blackledge, K., Ananth, C., Sauer, M., & Brandt, J. (2022). Altmetric and bibliometric analysis of influential articles in reproductive biology, 1980-2019. Reproductive BioMedicine Online, 45(2), 384-390. doi: 10.1016/j.rbmo.2022.04.005.
• Priem, J., Taraborelli, D., Groth, P., & Neylon, C. (2010). Altmetrics: A manifesto, Erişim tarihi: 30.05.2023, http://altmetrics.org/manifesto
• Pritchard, A. (1969). Statistical bibliography or bibliometrics. Journal of Documentation, 25(4), 348-349.
• Rohmah, A. A., Rachmawati, R., & Mei, E. T. W. (2023), Smart city achievement through ımplementation of digital health services in handling Covid-19 Indonesia. Smart Cities, 6(1), 639-651. doi. 10.3390/smartcities6010030.
• Seemann, R. J., Mielke, A. M., Glauert, D. L., Gehlen, T., Poncette, A. S., Mosch, L. K., … Back, D. A. (2023). Implementation of a digital health module for undergraduate medical students: A comparative study on knowledge and attitudes. Technology and Health Care, 31(1), 157-164. doi: 10.3233/THC-220138.
• Shaikh, A. K., Alhashmi, S. M., Khalique, N., Khedr, A. M., Raahemifar, K., & Bukhari, S. (2023). Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector. Digital Health, 9, 20552076221149296. doi: 10.1177/20552076221149296.
• Sreedharan, S., Mian, M., Robertson, R. A., & Yang, N. (2020). The top 100 most cited articles in medical artificial intelligence: A bibliometric analysis. Journal of Medical Artificial Intelligence, 3, 1-2. doi: 10.21037/jmai.2019.11.04.
• Tian, H., & Chen, J. (2022). A bibliometric analysis on global eHealth. Digital Health, 8, 20552076221091352. doi: 10.1177/20552076221091352.
• Ueland, K., Sanchez, S. C., Rillamas-Sun, E., Shen, H., Schattenkerk, L., Garcia, G., ... Greenlee, H. (2022). A digital health intervention to improve nutrition and physical activity in breast cancer survivors: Rationale and design of the cook and move for your life pilot and feasibility randomized controlled trial. Contemporary Clinical Trials, 123, 106993. doi: 10.1016/j.cct.2022.106993.
• Warren, H. R., Raison, N., & Dasgupta, P. (2017). The rise of altmetrics. Journal of the American Medical Association, 317(2), 131-132. doi: 10.1001/jama.2016.18346.
• Were, M. C., Sinha, C., & Catalani, C. (2019). A systematic approach to equity assessment for digital health interventions: case example of mobile personal health records. Journal of the American Medical Informatics Association, 26(8-9), 884-890. doi: 10.1093/jamia/ocz071.
• Yáñez-Dávila, D., Santoyo, E., & Santos-Raga., G. (2023). Worldwide research progress and trends on geothermal water–rock interaction experiments: a comprehensive bibliometric analysis. Earth Science Informatics, 16(1), 1-24. doi: 10.1007/s12145-022-00926-0.
• Yang, F., Zhang, S., Wang, Q., Zhang, Q., Han, J., Wang, L., ... Xue, F. (2020). Analysis of the global situation of COVID-19 research based on bibliometrics. Health information science and systems, 8, 1-10. doi: 10.1007/s13755-020-00120-w.
• Yang, K., Hu, Y., & Qi, H. (2022). Digital health literacy: Bibliometric analysis. Journal of Medical Internet Research, 24(7), e35816. doi: 10.2196/35816.
• Yardley, L., Morrison, L., Bradbury, K., & Muller, I. (2015). The person-based approach to intervention development: application to digital health-related behavior change interventions. Journal of Medical Internet Research, 17(1), e4055. doi: 10.2196/jmir.4055.
• Zhao, X., Ye, R., Zhao, L., Lin, Y., Huang, W., He, X., ... Tong, X. (2015). Worldwide research productivity in the field of endocrinology and metabolism—a bibliometric analysis. Endokrynologia Polska, 66(5), 434-442. doi: 10.5603/EP.2015.0054.
• Zhu, R., Liu, M., Su, Y., Meng, X., Han, S., & Duan, Z. (2021). A bibliometric analysis of publication of funded studies in nursing research from Web of Science, 2008-2018. Journal of Advanced Nursing, 77(1), 176-188. doi: 10.1111/jan.14578