Department of Psychiatry, The University of Oxford, Oxford, United Kingdom.
Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, GA, United States of America.
PLoS One. 2020 Nov 30;15(11):e0242936. doi: 10.1371/journal.pone.0242936. eCollection 2020.
Measuring executive function (EF) among adults is important, as the cognitive processes involved in EF are critical to academic achievement, job success and mental health. Current evidence on measurement and structure of EF largely come from Western, Educated, Industrialized, Rich and Democratic (WEIRD) countries. However, measuring EF in low-and-middle-income countries (LMICs) is challenging, because of the dearth of EF measures validated across LMICs, particularly measures that do not require extensive training, expensive equipment, or professional administration. This paper uses data from three LMIC cohorts to test the feasibility, validity and reliability of EF assessment in adults using three sub-tests (representing key components of EF) of the NIH Toolbox Cognitive battery. For each cohort, all three EF measures (inhibition, flexibility and working memory) loaded well onto a unidimensional latent factor of EF. Factor scores related well to measures of fluid intelligence, processing speed and schooling. All measures showed good test-retest reliability across countries. This study provides evidence for a set of sound measures of EF that could be used across different cultural, language and socio-economic backgrounds in future LMIC research. Furthermore, our findings extend conclusions on the structure of EF beyond those drawn from WEIRD countries.
衡量成年人的执行功能(EF)很重要,因为 EF 所涉及的认知过程对学业成绩、工作成功和心理健康都至关重要。目前关于 EF 的测量和结构的证据主要来自西方、受过教育、工业化、富有和民主(WEIRD)国家。然而,在中低收入国家(LMICs)衡量 EF 具有挑战性,因为缺乏在 LMICs 中得到验证的 EF 测量方法,特别是那些不需要广泛培训、昂贵设备或专业管理的测量方法。本文使用来自三个 LMIC 队列的数据,测试 NIH 工具包认知电池的三个子测试(代表 EF 的关键组成部分)在成年人中进行 EF 评估的可行性、有效性和可靠性。对于每个队列,所有三个 EF 测量(抑制、灵活性和工作记忆)都很好地加载到 EF 的单维潜在因素上。因子分数与流体智力、加工速度和受教育程度的测量密切相关。所有测量在不同国家的重测信度都很好。这项研究为一系列健全的 EF 测量方法提供了证据,这些方法可在未来的 LMIC 研究中应用于不同的文化、语言和社会经济背景。此外,我们的发现扩展了对 EF 结构的结论,超越了 WEIRD 国家得出的结论。