Bibliometric analysis of the scientific production on crowdsourcing in health
DOI:
https://doi.org/10.56294/saludcyt2023597Keywords:
Bibliometric Analysis, Crowdsourcing, Collaborative Decisions, Bibliometric Indicators, Health ServicesAbstract
Introduction: online collaborative decision-making processes in health have developed over time and surpass the academic field. The objective of the research is to analyze the scientific production on crowdsourcing in health during the period 2019 - 2023.
Methods: the research was developed under the quantitative paradigm approach, from a retrospective - descriptive and bibliometric study. A systematic search was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.
Results: the search was conducted in the SCOPUS database and 289 research results on crowdsourcing in health in the selected period were identified. Of the 289 research studies analyzed, 60 % are original articles. The area of knowledge that stands out the most is medicine with 159 research papers. A total of 162 journals were identified in which the research was published, the most cited being Translational Psychiatry with 364 citations. In addition, the institutions with the highest representation are The University of North Carolina at Chapel Hill and London School of Hygiene & Tropical Medicine with 23 and 17 researches respectively. The most relevant author is Tucker, J.D. with 17 publications. The country that published the most was the United States with 122 publications.
Conclusions: it is concluded that crowdsourcing in health as an online collaborative process between institutions, specialists, patients or experts in the health sector allows solving research problems, based on tasks directed by the crowdsourcing administrator, has developed over time and surpasses the academic field
References
1. Deal SB, Lendvay TS, Haque MI, Brand T, Comstock B, Warren J, et al. Crowd-sourced assessment of technical skills: an opportunity for improvement in the assessment of laparoscopic surgical skills. The American Journal of Surgery 2016;211:398-404.
2. van Niekerk L, Ongkeko A, Hounsell RA, Msiska BK, Mathanga DP, Mothe J, et al. Crowdsourcing to identify social innovation initiatives in health in low-and middle-income countries. Infectious Diseases of Poverty 2020;9:1-12.
3. John-Matthews JS, Robinson L, Martin F, Newton P, Grant A. Crowdsourcing: A novel tool to elicit the student voice in the curriculum design process for an undergraduate diagnostic radiography degree programme. Radiography 2020;26:S54-61.
4. Kuosmanen E, Huusko E, van Berkel N, Nunes F, Vega J, Goncalves J, et al. Exploring crowdsourced self-care techniques: A study on Parkinson’s disease. International Journal of Human-Computer Studies 2023;177:103062.
5. Hosio SJ, van Berkel N, Oppenlaender J, Goncalves J. Crowdsourcing personalized weight loss diets. Computer 2020;53:63-71.
6. Martínez LC, Rodríguez AU, Mendoza VVS, Cañarte BJS. Turismo y actividad económica estratégica para el desarrollo local en México. Revista Científica Empresarial Debe-Haber 2023;1:75-86.
7. Toza JFP, Paniagua DGC. Responsabilidad social empresarial y calidad de servicio en una Caja Municipal de Ahorro y Crédito de la región Tacna. Sincretismo 2021;2.
8. Adekanmbi O, Oyewusi WF, Ogundepo E. Real-Time Crowdsourcing of Health Data in a Low-Income Country: A Case Study of Human Data Supply on Malaria First-Line Treatment Policy Tracking in Nigeria., 2020, p. 14-8.
9. Bahrami Rad A, Galloway C, Treiman D, Xue J, Li Q, Sameni R, et al. Atrial fibrillation detection in outpatient electrocardiogram monitoring: An algorithmic crowdsourcing approach. Plos one 2021;16:e0259916.
10. Dissanayake I, Nerur S, Singh R, Lee Y. Medical crowdsourcing: Harnessing the “wisdom of the crowd” to solve medical mysteries. Journal of the Association for Information Systems 2019;20:4.
11. St John-Matthews J, Newton P, Grant A, Robinson L. Crowdsourcing in health professions education: What radiography educators can learn from other disciplines. Radiography 2019;25:164-9.
12. Ranard BL, Ha YP, Meisel ZF, Asch DA, Hill SS, Becker LB, et al. Crowdsourcing—harnessing the masses to advance health and medicine, a systematic review. Journal of general internal medicine 2014;29:187-203.
13. Fuentes-Ormachea GR, Chalco-Quispitupa J, Millones-Liza DY. Empowerment como herramienta estratégica de mejora productiva en las municipalidades de Lima Metropolitana. Revista Científica Empresarial Debe-Haber 2023;1:19-34.
14. Eslava Zapata R, Mogollón Calderón OZ, Chacón Guerrero E. Organizational socialization in universities: an empirical study. Reg Cient 2023:202369. https://doi.org/10.58763/rc202369.
15. Machuca-Contreras F, Canova-Barrios C, Castro MF. An approach to the concepts of radical, incremental and disruptive innovation in organizations. Reg Cient 2023:202324. https://doi.org/10.58763/rc202324.
16. Sánchez Suárez Y, Marqués León M, Hernández Nariño A, Suárez Pérez MM. Methodology for the diagnosis of patient pathway management in hospitals. Reg Cient 2023:2023115. https://doi.org/10.58763/rc2023115.
17. Khwanngern K, Natwichai J, Kaveeta V, Nantawad P, Changkai S, Suwiwattana S. Challenges of Crowdsourcing Platform: Thai Healthcare Information Case Study, Springer; 2021, p. 126-35.
18. Ricardo Jiménez LS. Dimensions of entrepreneurship: educational relationship. The case of the cumbre program. Reg Cient 2022:202210. https://doi.org/10.58763/rc202210.
19. Malhotra A, Majchrzak A, Bonfield W, Myers S. Engaging customer care employees in internal collaborative crowdsourcing: Managing the inherent tensions and associated challenges. Human Resource Management 2020;59:121-34.
20. Сафронова ЖС, Труханова ЮА. РАЗВИТИЕ КРАУДСОРСИНГА-НОВЫЙ ВЫЗОВ ДЛЯ РОССИЙСКИХ ФАРМАЦЕВТИЧЕСКИХ КОМПАНИЙ. Мониторинг общественного мнения: экономические и социальные перемены 2022:212-29.
21. Sha Y, Li C, Xiong Y, Hazra A, Lio J, Jiang I, et al. Co-creation using crowdsourcing to promote PrEP adherence in China: study protocol for a stepped-wedge randomized controlled trial. BMC public health 2022;22:1697.
22. Ling R, Sit HF, Balaji S, Lam AI, Latkin CA, Tucker JD, et al. Crowdsourcing to design a marketing package to promote a WHO digital mental health intervention among Chinese young adults. Internet interventions 2021;25:100397.
23. Soledispa GBL, Cañarte BJS, Soledispa VAC, González ORF. Análisis de la Cadena de Suministros en las empresas industriales de Guayaquil, Ecuador. Revista Científica Empresarial Debe-Haber 2023;1:3-24.
24. Guo H, Kafalı Ö, Jeukeng A-L, Williams L, Singh MP. Çorba: Crowdsourcing to obtain requirements from regulations and breaches. Empirical Software Engineering 2020;25:532-61.
25. Kotronoulas G, Papadopoulou C. A primer to experimental and nonexperimental quantitative research: the example case of tobacco-related mouth cancer. vol. 39, Elsevier; 2023, p. 151396.
26. Joyce A, Pellatt R, Ranse J, Doumany A, Hall E, Sweeny A, et al. Occupational violence in a tertiary emergency department: A retrospective descriptive study. Australasian emergency care 2023.
27. Yin X, Wang H, Wang W, Zhu K. Task recommendation in crowdsourcing systems: A bibliometric analysis. Technology in Society 2020;63:101337.
28. Ledesma F, Malave González BE. Patterns of scientific communication on E-commerce: a bibliometric study in the Scopus database. Reg Cient 2022:202214. https://doi.org/10.58763/rc202214.
29. Helbach J, Hoffmann F, Pieper D, Allers K. Reporting according to the preferred reporting items for systematic reviews and meta-analyses for abstracts (PRISMA-A) depends on abstract length. Journal of Clinical Epidemiology 2023;154:167-77.
30. Kamaraj A, Kyriacou H, Seah KM, Khan WS. Use of human induced pluripotent stem cells for cartilage regeneration in vitro and within chondral defect models of knee joint cartilage in vivo: a Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic literature review. Cytotherapy 2021;23:647-61.
31. Castillo VS, Cano CAG, Gonzalez-Argote J. Telemedicine and mHealth Applications for Health Monitoring in Rural Communities in Colombia: A Systematic Review. EAI Endorsed Transactions on Pervasive Health and Technology 2023;9.
32. Kambhampati SB, Vasudeva N, Vaishya R, Patralekh MK. Top 50 cited articles on Covid-19 after the first year of the pandemic: a bibliometric analysis. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2021;15:102140.
33. Ruiz É, Beretta M. Managing internal and external crowdsourcing: An investigation of emerging challenges in the context of a less experienced firm. Technovation 2021;106:102290.
34. Niu X, Qin S. Integrating crowd-/service-sourcing into digital twin for advanced manufacturing service innovation. Advanced Engineering Informatics 2021;50:101422.
35. De Felice F, Polimeni A. Coronavirus disease (COVID-19): a machine learning bibliometric analysis. in vivo 2020;34:1613-7.
36. ElHawary H, Salimi A, Diab N, Smith L. Bibliometric analysis of early COVID-19 research: the top 50 cited papers. Infectious diseases: research and treatment 2020;13:1178633720962935.
37. Vilchez SAD, Ramos RJF, Rey MRM. Análisis bibliométrico de los 100 artículos más citados en Scopus sobre educación médica y COVID-19. Revista Cubana de Información en Ciencias de la Salud 2023;34:12.
38. Muñoz-Estrada GK, Caycho HEC, Barja-Ore J, Valverde-Espinoza N, Verde-Vargas L, Mayta-Tovalino F. Análisis bibliométrico de la producción científica mundial sobre el aula invertida en la educación médica. Educación Médica 2022;23:100758.
39. Jacobs CD, Cross PC. The value of medical student research: the experience at Stanford University School of Medicine. Medical education 1995;29:342-6.
40. Lizcano PAC, Quintero YCM, Cano CAG. Análisis del impacto en la implementación de la facturación electrónica en el sector automotriz en la ciudad de Florencia, Caquetá. Revista Científica Empresarial Debe-Haber 2023;1:25-40.
41. Jaffe K, Ter Horst E, Gunn LH, Zambrano JD, Molina G. A network analysis of research productivity by country, discipline, and wealth. Plos one 2020;15:e0232458.
42. Pericàs JM, Arenas A, Torrallardona-Murphy O, Valero H, Nicolás D. Published evidence on COVID-19 in top-ranked journals: a descriptive study. European journal of internal medicine 2020;79:120-2
Published
Issue
Section
License
Copyright (c) 2023 Carlos Alberto Gómez-Cano, Juan Carlos Miranda-Passo, René Ramírez Fernández (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
