数据科学
行为科学
数据收集
众包
心理学
计算机科学
社会学
万维网
社会科学
心理治疗师
作者
Dwight J. Kravitz,Stephen R. Mitroff,Chloe Callahan-Flintoft,Kelvin S. Oie
标识
DOI:10.1177/23727322241274745
摘要
The behavioral sciences have had great success in their study of the mechanisms that drive behavior. However, they have had less impact on applied settings or policy. This gap results from the very adaptability that makes human behavior useful. Adaptability implies that behavior will be highly specific to the context in which it occurs. Thus, building a bridge between the lab and application requires testing in the specific applied setting, which runs afoul of the high cost of data collection. This cost has also led to a focus on simple paradigms that poorly match applied settings. However, crowdsourcing enables data collection at vastly reduced budgets and schedules. This new cost regime also enables paradigms better suited to applied settings. Behavioral science should now be used throughout applied- and policy-focused projects.
科研通智能强力驱动
Strongly Powered by AbleSci AI