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La Crowdsourcing medicine. Opportunità e sfide per il futuro della ricerca clinica
Titolo Rivista: SALUTE E SOCIETÀ 
Autori/Curatori: Linda Lombi 
Anno di pubblicazione:  2019 Fascicolo: Lingua: Italiano 
Numero pagine:  18 P. 98-115 Dimensione file:  221 KB
DOI:  10.3280/SES2019-002009
Il DOI è il codice a barre della proprietà intellettuale: per saperne di più:  clicca qui   qui 




Crowdsourcing is an approach to accomplishing a task by opening up its completion to broad sections of the public (the "crowd"). Moving to the medical field, Crowdsourced health re-search studies have arisen as a natural extension of the grown of platforms in which sick peo-ple ask for receiving advices and help from clinical or lay experts. The spread of crowdsourc-ing medicine allows researchers to engage thousands of people to provide either data with lower cost and higher rapidity, giving a fundamental contribution to the spread of 4P medicine model (predictive, preventive, personalised, and participatory medicine). This article focuses on the present and future scenario of the crowdsourcing medicine. It de-scribes some experiences and platforms, considering the pros and cons from the point of view both of patients and researchers.
Keywords: Crowdsourcing medicine; Citizen Science; medicina delle 4P; medicina parteci-pativa; medicina di precisione; medicina personalizzata.

  1. Ajana B. (2017). Digital health and the biopolitics of the Quantified Self. Digital Health, 3: 1-18., 10.1177/205520761668950DOI: 10.1177/205520761668950
  2. Arksey H. (1994). Expert and Lay Participation in the Construction of Medical Knowledge. Sociology of Health & Illness, 16, 4: 448-468.
  3. Behrend T.S., Sharek D.J., Meade A.W., Wiebe E.N. (2011). The viability of crowdsourcing for survey research. Behav Res Methods, 43(3): 800-813.
  4. Brady C.J., Villanti A.C., Pearson J.L., Kirchner T.R., Gupta O.P., Shah C.P. (2014). Rapid grading of fundus photographs for diabetic retinopathy using crowdsourcing. J Med Internet Res, 16(10): e233.
  5. Bragazzi N.L. (2013). From P0 to P6 medicine, a model of highly participatory, narrative, interactive, and “augmented” medicine: Some considerations on Salvatore Iaconesi’s clinical story. Patient Preference and Adherence, 7: 353-359., 10.2147/PPA.S38578DOI: 10.2147/PPA.S38578
  6. David M.M., Babineau B.A., Wall D.P. (2016). Can we accelerate autism discoveries through crowd-sourcing?. Research in Autism Spectrum Disorders, 32: 80-83.
  7. Epstein S. (1995). The construction of lay expertise: AIDS activism and the forging of credibility in the reform of clinical trials. Science, Technology and Human Values, 20(4): 408-37.
  8. Epstein S. (1996). Impure Science: AIDS, Activism, and the Politics of Knowledge. Berkeley: University of California Press.
  9. Frost J.H., Massagli M.P. (2008). Social uses of personal health information within PatientsLikeMe, an online patient community: What can happen when patients have access to one another’s data. Journal of Medical Internet Research, 10(3): e15.
  10. Golubnitschaja O., Costigliola V. (2012). General Report & Recommendations in Predictive, Preventive and Personalised Medicine, White Paper of the European Association for Predictive, Preventive and Personalised Medicine. EPMA Journal, 3(1): 14., 10.1186/1878-5085-3-1DOI: 10.1186/1878-5085-3-1
  11. Greengard S. (2011). Following the Crowd. Communications of the ACM, 54(2): 20-22., 10.1145/1897816.189782DOI: 10.1145/1897816.189782
  12. Hachmann, S., Arsanjani, J.J., Vaz, E. (2018). Spatial data for slum upgrading: Volunteered Geographic Information and the role of citizen science. Habitat International, 72: 18-26.
  13. Hood L., Friend S.H. (2011). Predictive, personalized, preventive, participatory (P4) cancer medicine. Nat Rev Clin Oncol., 8(3): 184-187.
  14. Hood L.A. (2008). A Systems Approach to Medicine will transform the Healthcare. In: Zewail A.H., a cura di, Physical Biology: From Atoms to Medicine. London: Imperial College Press, pp. 337-366.
  15. Howe J. (2006). The rise of crowdsourcing. Wired Magazine, 14(6): 1-4.
  16. Husserl E. (2015). La crisi delle scienze europee e la fenomenologia trascendentale, Milano: il Saggiatore [ed. orig.: 1961].
  17. Iaconesi S., Persico O. (2012). La cura. Torino: Codice Edizioni.
  18. Irwin A. (2001). Constructing the scientific citizen: science and democracy in the biosciences. Public Understanding of Science, 10(1): 1-18.
  19. Lombi L. (2018). The Contribution of Digital Sociology to the Investigation of Air Pollution. In: Capello F., Gaddi V.A., a cura di, Clinical Handbook of Air Pollution-Related Diseases. Springer: Cham, pp. 621-636.
  20. Luengo-Oroz M.A., Arranz A., Frean J. (2012). Crowdsourcing malaria parasite quantification: An online game for analyzing images of infected thick blood smears. J Med Internet Res, 14(6): e167.
  21. Lupton D. (2013). Quantifying the body: monitoring and measuring health in the age of mHealth technologies. Critical Public Health, 23(4): 393-403., 10.1080/09581596.2013.79493DOI: 10.1080/09581596.2013.79493
  22. Lupton D. (2014). Apps as artefacts: Towards a critical perspective on mobile health and medical apps. Societies, 4(4): 606-622.
  23. Mavandadi S., Dimitrov S., Feng S., Yu F., Sikora U., Yaglidere O. et al. (2012). Distributed medical image analysis and diagnosis through crowd-sourced games: A malaria case study. PLoS One, 7(5): e37245.
  24. McKenna M.T., Wang S., Nguyen T.B., Burns J.E., Petrick N. (2012). Summers RM. Strategies for improved interpretation of computer-aided detections for CT colonography utilizing distributed human intelligence. Med Image Anal, 16(6): 1280-1292.
  25. Meisel Z.F., VonHoltz L.A.H., Merchant R.M. (2016). Crowdsourcing healthcare costs: Opportunities and challenges for patient centered price transparency. Healthcare, 4(1): 3-5.
  26. Meyer A.N.D., Longhurst C.A., Singh H. (2016). Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed. Journal of Medical Internet Research, 18(1): e12.
  27. Mueller J., Lu H., Chirkin A., Klein B., Schmitt G. (2018). Citizen Design Science: A strategy for crowd-creative urban design. Cities, 72: 181-188.
  28. Nguyen T.B., Wang S., Anugu V., Rose N., McKenna M., Petrick N. et al. (2012). Distributed human intelligence for colonic polyp classification in computer-aided detection for CT colonography. Radiology, 262(3): 824-833.
  29. Prainsack B. (2017). Research for Personalised Medicine: Time for Solidarity. Medicine & Law, 36(1): 87-98.
  30. Prior L. (2003). Belief, knowledge and expertise: the emergence of the lay expert in medical sociology. Sociology of Health & Illness, 25(3): 41-57., 10.1111/1467-9566.0033DOI: 10.1111/1467-9566.0033
  31. Ranard B.L., Ha Y.P., Meisel Z.F., Asch D.A., Hill S.S., Becker L.B. et al. (2014). Crowdsourcing - Harnessing the masses to advance health and medicine, a systematic review. J Gen Intern Med, 29(1): 187-203.
  32. Riesch H., Potter C. (2013). Citizen science as seen by scientists: Methodological, epistemological and ethical dimensions. Public Understanding of Science, 23(1): 107-120., 10.1177/096366251349732DOI: 10.1177/096366251349732
  33. Ritzer G. (2014). Prosumption: Evolution, revolution, or eternal return of the same?. J. Consum. Cult., 14: 3-24., 10.1177/146954051350964DOI: 10.1177/146954051350964
  34. Sagner M., McNeil A., Puska P., Auffray C., Price N.D., Hood L. et al. (2017). The P4 health spectrum-a predictive, preventive, personalized and participatory continuum for promoting healthspan. Progress in cardiovascular diseases, 59(5): 506-521.
  35. Sen K., Ghosh, K. (2017). Developing Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations. In: Proceedings of the 50th Hawaii International Conference on System Sciences: pp. 3289-3296
  36. Swan M. (2012). Crowdsourced health research studies: An important emerging complement to clinical trials in the public health research ecosystem. Journal of Medical Internet Research, 14(2): 186-198.
  37. Toffler A. (1980). The third wave: the classic study of tomorrow. New York, NY: Bantam.
  38. Wicks P., Massagli M., Kulkarni A., Dastani H. (2011). Use of an online community to develop patient-reported outcome instruments: the Multiple Sclerosis Treatment Adherence Questionnaire (MS-TAQ). J Med Internet Res, 13(1): e12.
  39. Woolley J.P., McGowan M.L., Teare H.J.A., Coathup V., Fishman J.R., Settersten R.A. et al. (2016). Citizen science or scientific citizenship? Disentangling the uses of public engagement rhetoric in national research initiatives. BMC Medical Ethics, 17(1).
  40. Zhao Y., Zhu Q. (2014). Evaluation on crowdsourcing research: Current status and future direction. Information Systems Frontiers, 16(3): 417-434.

Linda Lombi, in "SALUTE E SOCIETÀ" 2/2019, pp. 98-115, DOI:10.3280/SES2019-002009

   

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