Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences

dc.contributor.authorChristie, Alec P.
dc.contributor.authorAbecasis, David
dc.contributor.authorAdjeroud, Mehdi
dc.contributor.authorAlonso, Juan Carlos
dc.contributor.authorAmano, Tatsuya
dc.contributor.authorAnton, Alvaro
dc.contributor.authorBaldigo, Barry Paul
dc.contributor.authorBarrientos, Rafael
dc.contributor.authorBicknell, Jake E.
dc.contributor.authorBuhl, Deborah A.
dc.contributor.authorCebrian, Just
dc.contributor.authorCeia, Ricardo Santos
dc.contributor.authorCibils-Martina, Luciana
dc.contributor.authorClarke, Sarah
dc.contributor.authorClaudet, Joachim
dc.contributor.authorCraig, Michael D.
dc.contributor.authorDavoult, Dominique
dc.contributor.authorde Backer, Annelies
dc.contributor.authorDonovan, Mary K.
dc.contributor.authorEddy, Tyler D.
dc.contributor.authorFrança, Filipe M.
dc.contributor.authorGardner, Jonathan
dc.contributor.authorHarris, Bradley P.
dc.contributor.authorHuusko, Ari
dc.contributor.authorJones, Ian L.
dc.contributor.authorKelaher, Brendan P.
dc.contributor.authorKotiaho, J. S.
dc.contributor.authorLópez-Baucells, Adrià
dc.contributor.authorMajor, Heather L.
dc.contributor.authorMäki-Petäys, Aki
dc.contributor.authorMartín, Beatriz
dc.contributor.authorMartín, Carlos A.
dc.contributor.authorMartin, Philip A.
dc.contributor.authorMateos-Molina, Daniel
dc.contributor.authorMcConnaughey, Robert A.
dc.contributor.authorMeroni, Michele
dc.contributor.authorMeyer, Christoph F.J.
dc.contributor.authorMills, Kade
dc.contributor.authorMontefalcone, Monica
dc.contributor.authorNoreika, Norbertas
dc.contributor.authorPalacín, Carlos
dc.contributor.authorPande, Anjali
dc.contributor.authorPitcher, C. Roland
dc.contributor.authorPonce, Carlos
dc.contributor.authorRinella, Matthew James
dc.contributor.authorRocha, Ricardo
dc.contributor.authorRuiz-Delgado, María C.
dc.contributor.authorSchmitter-Soto, Juan Jacobo
dc.contributor.authorShaffer, Jill A.
dc.contributor.authorSharma, Shailesh
dc.contributor.authorSher, Anna A.
dc.contributor.authorStagnol, Doriane
dc.contributor.authorStanley, Thomas R.
dc.contributor.authorStokesbury, Kevin D.E.
dc.contributor.authorTorres, Aurora
dc.contributor.authorTully, Oliver
dc.contributor.authorVehanen, Teppo
dc.contributor.authorWatts, Corinne H.
dc.contributor.authorZhao, Qingyuan
dc.contributor.authorSutherland, William J.
dc.date.accessioned2020-12-28T14:50:52Z
dc.date.available2020-12-28T14:50:52Z
dc.date.issued2020
dc.description.abstractBuilding trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs. © 2020, The Author(s).en
dc.identifier.doi10.1038/s41467-020-20142-y
dc.identifier.urihttps://repositorio.inpa.gov.br/handle/1/36942
dc.language.isoenpt_BR
dc.publisher.journalNature Communicationspt_BR
dc.relation.ispartofVolume 11, Número 1pt_BR
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Brazil*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/br/*
dc.subjectBiodiversityen
dc.subjectData Seten
dc.subjectDecision Makingen
dc.subjectNumerical Modelen
dc.subjectarticleen
dc.subjectConservation Biologyen
dc.subjectHumanen
dc.subjectintervention studyen
dc.subjectPrevalenceen
dc.subjectrandomized controlled trial (topic)en
dc.subjectSociologyen
dc.subjectSynthesisen
dc.titleQuantifying and addressing the prevalence and bias of study designs in the environmental and social sciencesen
dc.typeArtigopt_BR

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