Uncovering the structure of self-regulation through data-driven ontology discovery
Uncovering the structure of self-regulation through data-driven ontology discovery
复制标题
DOI：
10.1038/s41467-019-10301-1
复制
发表时间：
2019-05-24
影响因子：
16.6
通讯作者：
Poldrack, Russell A.
中科院分区：
文献类型：
--
作者：
Eisenberg, Ian W.;Bissett, Patrick G.;Poldrack, Russell A.
心理科学已经确定了大量的认知过程和行为现象，但努力产生累积的知识。孤立的科学传统和对解释的关注超过了预测，这两个问题对自我调节等多方面结构的研究特别有害。在这里，我们从一个广泛的行为任务，自我报告的调查，自我报告的现实世界的结果与自我调节的个体差异的研究中得出一个心理本体。虽然任务和调查都可以测量自我调节，但它们几乎没有显示出经验关系。然而，在任务和调查中，本体识别可靠的个人特征，并揭示理论综合的机会。然后，我们评估了心理测量的预测能力，发现虽然调查适度和异质性预测现实世界的结果，任务在很大程度上没有。我们的结论是，自我调节缺乏连贯性作为一个结构，数据驱动的本体论奠定了基础的累积心理科学。
Psychological sciences have identified a wealth of cognitive processes and behavioral phenomena, yet struggle to produce cumulative knowledge. Progress is hamstrung by siloed scientific traditions and a focus on explanation over prediction, two issues that are particularly damaging for the study of multifaceted constructs like self-regulation. Here, we derive a psychological ontology from a study of individual differences across a broad range of behavioral tasks, self-report surveys, and self-reported real-world outcomes associated with self-regulation. Though both tasks and surveys putatively measure self-regulation, they show little empirical relationship. Within tasks and surveys, however, the ontology identifies reliable individual traits and reveals opportunities for theoretic synthesis. We then evaluate predictive power of the psychological measurements and find that while surveys modestly and heterogeneously predict real-world outcomes, tasks largely do not. We conclude that self-regulation lacks coherence as a construct, and that data-driven ontologies lay the groundwork for a cumulative psychological science.