Hanson Jamie L, Kahhalé Isabella, Sen Sriparna
Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
Learning Research & Development Center, University of Pittsburgh, Pittsburgh, PA, USA.
Dev Psychopathol. 2024 Dec;36(5):2165-2172. doi: 10.1017/S0954579424001056. Epub 2024 May 21.
This commentary discusses opportunities for advancing the field of developmental psychopathology through the integration of data science and neuroscience approaches. We first review elements of our research program investigating how early life adversity shapes neurodevelopment and may convey risk for psychopathology. We then illustrate three ways that data science techniques (e.g., machine learning) can support developmental psychopathology research, such as by distinguishing between common and diverse developmental outcomes after stress exposure. Finally, we discuss logistical and conceptual refinements that may aid the field moving forward. Throughout the piece, we underscore the profound impact of Dr Dante Cicchetti, reflecting on how his work influenced our own, and gave rise to the field of developmental psychopathology.
本评论探讨了通过整合数据科学和神经科学方法来推进发展性精神病理学领域的机会。我们首先回顾了我们的研究项目的要素，该项目调查早期生活逆境如何塑造神经发育并可能传递精神病理学风险。然后，我们举例说明了数据科学技术（如机器学习）可以支持发展性精神病理学研究的三种方式，例如通过区分压力暴露后常见和不同的发展结果。最后，我们讨论了可能有助于该领域向前发展的后勤和概念改进。在整篇文章中，我们强调了但丁·西契迪博士的深远影响，反思了他的工作如何影响了我们自己的工作，并催生了发展性精神病理学领域。
