BrainPark, Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia.
Melbourne School of Psychological Sciences, University of Melbourne, Parkville, Australia.
J Med Internet Res. 2023 Aug 25;25:e44414. doi: 10.2196/44414.
Many people with harmful addictive behaviors may not meet formal diagnostic thresholds for a disorder. A dimensional approach, by contrast, including clinical and community samples, is potentially key to early detection, prevention, and intervention. Importantly, while neurocognitive dysfunction underpins addictive behaviors, established assessment tools for neurocognitive assessment are lengthy and unengaging, difficult to administer at scale, and not suited to clinical or community needs. The BrainPark Assessment of Cognition (BrainPAC) Project sought to develop and validate an engaging and user-friendly digital assessment tool purpose-built to comprehensively assess the main consensus-driven constructs underpinning addictive behaviors.
The purpose of this study was to psychometrically validate a gamified battery of consensus-based neurocognitive tasks against standard laboratory paradigms, ascertain test-retest reliability, and determine their sensitivity to addictive behaviors (eg, alcohol use) and other risk factors (eg, trait impulsivity).
Gold standard laboratory paradigms were selected to measure key neurocognitive constructs (Balloon Analogue Risk Task [BART], Stop Signal Task [SST], Delay Discounting Task [DDT], Value-Modulated Attentional Capture [VMAC] Task, and Sequential Decision-Making Task [SDT]), as endorsed by an international panel of addiction experts; namely, response selection and inhibition, reward valuation, action selection, reward learning, expectancy and reward prediction error, habit, and compulsivity. Working with game developers, BrainPAC tasks were developed and validated in 3 successive cohorts (total N=600) and a separate test-retest cohort (N=50) via Mechanical Turk using a cross-sectional design.
BrainPAC tasks were significantly correlated with the original laboratory paradigms on most metrics (r=0.18-0.63, P<.05). With the exception of the DDT k function and VMAC total points, all other task metrics across the 5 tasks did not differ between the gamified and nongamified versions (P>.05). Out of 5 tasks, 4 demonstrated adequate to excellent test-retest reliability (intraclass correlation coefficient 0.72-0.91, P<.001; except SDT). Gamified metrics were significantly associated with addictive behaviors on behavioral inventories, though largely independent of trait-based scales known to predict addiction risk.
A purpose-built battery of digitally gamified tasks is sufficiently valid for the scalable assessment of key neurocognitive processes underpinning addictive behaviors. This validation provides evidence that a novel approach, purported to enhance task engagement, in the assessment of addiction-related neurocognition is feasible and empirically defensible. These findings have significant implications for risk detection and the successful deployment of next-generation assessment tools for substance use or misuse and other mental disorders characterized by neurocognitive anomalies related to motivation and self-regulation. Future development and validation of the BrainPAC tool should consider further enhancing convergence with established measures as well as collecting population-representative data to use clinically as normative comparisons.
许多存在有害成瘾行为的人可能不符合障碍的正式诊断标准。相比之下,采用维度方法,包括临床和社区样本,对于早期检测、预防和干预可能是关键。重要的是,尽管神经认知功能是成瘾行为的基础,但现有的神经认知评估工具冗长且不吸引人,难以大规模实施,并且不适合临床或社区需求。BrainPark 认知评估(BrainPAC)项目旨在开发和验证一种引人入胜且用户友好的数字评估工具,专门用于全面评估支持成瘾行为的主要共识驱动结构。
本研究的目的是通过与标准实验室范式相比,对基于共识的神经认知任务的游戏化电池进行心理测量学验证,确定其测试-重测信度,并确定其对成瘾行为(例如酒精使用)和其他风险因素(例如特质冲动)的敏感性。
选择黄金标准实验室范式来测量关键的神经认知结构(气球模拟风险任务[BART]、停止信号任务[SST]、延迟折扣任务[DDT]、价值调制注意捕获任务[VMAC]和顺序决策任务[SDT]),这是由一个国际成瘾专家小组认可的;即反应选择和抑制、奖励评估、动作选择、奖励学习、期望和奖励预测误差、习惯和强迫。与游戏开发者合作,通过 Mechanical Turk 使用横断面设计,在 3 个连续队列(共 600 名参与者)和一个单独的测试-重测队列(50 名参与者)中开发和验证了 BrainPAC 任务。
BrainPAC 任务在大多数指标上与原始实验室范式显著相关(r=0.18-0.63,P<.05)。除了 DDT k 函数和 VMAC 总分数外,五个任务中的所有其他任务指标在游戏化和非游戏化版本之间没有差异(P>.05)。在 5 个任务中,4 个任务的测试-重测信度达到了足够好到优秀的水平(组内相关系数 0.72-0.91,P<.001;除了 SDT)。游戏化指标与行为量表上的成瘾行为显著相关,尽管与预测成瘾风险的特质量表有很大的独立性。
专门设计的数字化游戏化任务电池足以用于可扩展的成瘾行为相关神经认知过程的评估。该验证提供了证据,表明在评估与成瘾相关的神经认知时,一种据称可以增强任务参与度的新方法是可行且具有经验依据的。这些发现对风险检测以及下一代用于物质使用或滥用以及其他以与动机和自我调节相关的神经认知异常为特征的精神障碍的评估工具的成功部署具有重要意义。未来应进一步考虑增强与既定测量方法的一致性,并收集具有代表性的人群数据,以便在临床上用作标准比较,从而对 BrainPAC 工具进行开发和验证。