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Learning from Evidence in a Complex World

Bibliographic Data

ID11023955
AuthorsJohn D Sterman (0000-0001-7476-6760, The author is with the MIT Sloan School of Management, Cambridge, Mass., corresponding author)
Year2006
Volume96
Issue3
Pages505-514
Publication date2006-03-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAmerican Journal of Public Health (JOURNAL)
Journal identifiersISSN: 0090-0036 • E-ISSN: 1541-0048
PublisherAmerican Public Health Association (PUBLISHER • US)
DOI10.2105/ajph.2005.066043
PMID16449579
PMCIDPMC1470513
OpenAlexW2157800154
LanguageEN
Citations received164
References cited42

Policies to promote public health and welfare often fail or worsen the problems they are intended to solve. Evidence-based learning should prevent such policy resistance, but learning in complex systems is often weak and slow. Complexity hinders our ability to discover the delayed and distal impacts of interventions, generating unintended “side effects.” Yet learning often fails even when strong evidence is available: common mental models lead to erroneous but self-confirming inferences, allowing harmful beliefs and behaviors to persist and undermining implementation of beneficial policies. Here I show how systems thinking and simulation modeling can help expand the boundaries of our mental models, enhance our ability to generate and learn from evidence, and catalyze effective change in public health and beyond

Cognitive psychology · Economic growth · Economics · Machine learning · Mental health · Policy learning · Political science · Psychiatry · Psychological intervention · Public economics · Public health · Public health interventions · Public policy · Resistance (ecology) · Risk analysis (engineering) · Unintended consequences · Welfare · Complex Systems and Decision Making · Computer Science · Health Policy Implementation Science · Medicine · Mental Health Research Topics · Psychology

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Unique citing works164
Citations per year8,2
Citation span2006 - 2026 (21)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 149

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