Mapiranje crowdsourcinga u zdravstvu: sistematski pregled.
Journal of medical Internet research
Sažetak istraživanja
Pozadina Crowdsourcing uključuje pribavljanje ideja, potrebnih usluga ili sadržaja traženjem web-baziranih doprinosa od gomile. 4 vrste zadataka iz grupe (rešavanje problema, obrada podataka, nadzor ili praćenje i anketiranje) mogu se primijeniti u 3 kategorije zdravlja (promocija, istraživanje i njega).
Cilj Ova studija je imala za cilj da mapira različite primjene crowdsourcinga u zdravstvu kako bi se procijenila područja zdravlja koja koriste crowdsourcing i zadatke koji se koriste. Također opisujemo logistiku crowdsourcinga i karakteristike crowd radnika.
Metode MEDLINE, EMBASE i ClinicalTrials.gov su pretražene za dostupne izvještaje od početka do 30. marta 2016., bez ograničenja na jezik ili status publikacije.
Rezultati Identificirali smo 202 relevantne studije koje su koristile crowdsourcing, uključujući 9 randomiziranih kontroliranih studija, od kojih je samo jedna objavila rezultate na ClinicalTrials.gov. Crowdsourcing je korišten u promociji zdravlja (91/202, 45,0%), istraživanju (73/202, 36,1%) i skrbi (38/202, 18,8%). Četiri najčešća područja primjene bile su javno zdravstvo (67/202, 33,2%), psihijatrija (32/202, 15,8%), hirurgija (22/202, 10,9%) i onkologija (14/202, 6,9%). Polovina izvještaja (99/202, 49,0%) odnosila se na obradu podataka, 34,6% (70/202) na anketiranje, 10,4% (21/202) na nadzor ili praćenje, a 5,9% (12/202) na rješavanje problema. Platforme tržišta rada (npr. Amazon Mechanical Turk) korištene su u većini studija (190/202, 94%). Karakteristike masovnih radnika bile su loše prijavljene, a logistika crowdsourcinga je nedostajala u dvije trećine izvještaja. Kada je objavljeno, srednja veličina gomile je bila 424 (prvi i treći kvartil: 167-802); Srednja starost radnika mase bila je 34 godine (32-36). Grupni radnici su uglavnom regrutovani na nacionalnom nivou, posebno u Sjedinjenim Državama. Za mnoge studije (58,9%, 119/202) bilo je potrebno prethodno iskustvo u crowdsourcingu, a polaganje kvalifikacionog testa ili obuka rijetko je bilo potrebno (11,9% studija; 24/202). Za polovinu studija spomenuti su novčani poticaji, s uglavnom manje od 1 USD za obavljanje zadatka. Vrijeme potrebno za izvođenje zadatka uglavnom je bilo manje od 10 minuta (58,9% studija; 119/202). Provjera kvaliteta podataka korištena je u 54/202 studije (26,7%), uglavnom pitanjima za provjeru pažnje ili repliciranjem zadatka s nekoliko radnika iz mase.
Zaključci Upotreba crowdsourcinga, koji omogućava pristup velikom broju učesnika, kao i uštedu vremena u prikupljanju podataka, smanjenje troškova i ubrzavanje inovacija, sve je više u promociji zdravlja, istraživanju i njezi. Međutim, opis logistike crowdsourcinga i karakteristika masovnih radnika često nedostaje u izvještajima o studijama i potrebno ga je precizno izvijestiti kako bi se rezultati studije bolje interpretirali i replicirali.
Prikaži originalni naslov i sažetak na engleskom
Mapping of Crowdsourcing in Health: Systematic Review.
Background Crowdsourcing involves obtaining ideas, needed services, or content by soliciting Web-based contributions from a crowd. The 4 types of crowdsourced tasks (problem solving, data processing, surveillance or monitoring, and surveying) can be applied in the 3 categories of health (promotion, research, and care).
Objective This study aimed to map the different applications of crowdsourcing in health to assess the fields of health that are using crowdsourcing and the crowdsourced tasks used. We also describe the logistics of crowdsourcing and the characteristics of crowd workers.
Methods MEDLINE, EMBASE, and ClinicalTrials.gov were searched for available reports from inception to March 30, 2016, with no restriction on language or publication status.
Results We identified 202 relevant studies that used crowdsourcing, including 9 randomized controlled trials, of which only one had posted results at ClinicalTrials.gov. Crowdsourcing was used in health promotion (91/202, 45.0%), research (73/202, 36.1%), and care (38/202, 18.8%). The 4 most frequent areas of application were public health (67/202, 33.2%), psychiatry (32/202, 15.8%), surgery (22/202, 10.9%), and oncology (14/202, 6.9%). Half of the reports (99/202, 49.0%) referred to data processing, 34.6% (70/202) referred to surveying, 10.4% (21/202) referred to surveillance or monitoring, and 5.9% (12/202) referred to problem-solving. Labor market platforms (eg, Amazon Mechanical Turk) were used in most studies (190/202, 94%). The crowd workers' characteristics were poorly reported, and crowdsourcing logistics were missing from two-thirds of the reports. When reported, the median size of the crowd was 424 (first and third quartiles: 167-802); crowd workers' median age was 34 years (32-36). Crowd workers were mainly recruited nationally, particularly in the United States. For many studies (58.9%, 119/202), previous experience in crowdsourcing was required, and passing a qualification test or training was seldom needed (11.9% of studies; 24/202). For half of the studies, monetary incentives were mentioned, with mainly less than US $1 to perform the task. The time needed to perform the task was mostly less than 10 min (58.9% of studies; 119/202). Data quality validation was used in 54/202 studies (26.7%), mainly by attention check questions or by replicating the task with several crowd workers.
Conclusions The use of crowdsourcing, which allows access to a large pool of participants as well as saving time in data collection, lowering costs, and speeding up innovations, is increasing in health promotion, research, and care. However, the description of crowdsourcing logistics and crowd workers' characteristics is frequently missing in study reports and needs to be precisely reported to better interpret the study findings and replicate them.
Izvorni podaci
- DOI
- 10.2196/jmir.9330
- PMID
- 29764795
- PMCID
- PMC5974463
- Provjereno
- 2026-07-26
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