PDF(Pubmed)
Abstract：
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.
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.
摘要：
背景：许多有有害成瘾行为的人可能不符合疾病的正式诊断阈值。一种维度的方法，相比之下,包括临床和社区样本，可能是早期发现的关键，预防,和干预。重要的是,而神经认知功能障碍是成瘾行为的基础，神经认知评估的既定评估工具是冗长而无吸引力的，难以大规模管理，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，旨在全面评估支持成瘾行为的主要共识驱动结构。
目的：这项研究的目的是在心理上验证一系列基于共识的神经认知任务的游戏化对标准实验室范式的影响，确定测试-重测可靠性，并确定他们对成瘾行为的敏感性(例如，酒精使用)和其他危险因素(例如，特质冲动)。
方法：选择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]，延迟贴现任务[DDT]，值调制注意力捕获[VMAC]任务，和顺序决策任务[SDT])，得到一个国际成瘾专家小组的认可；即反应选择和抑制，奖励估价，动作选择,奖励学习，期望和奖励预测误差，习惯,和强迫性。与游戏开发者合作，通过MechanicalTurk使用横截面设计，在3个连续队列（总共N=600）和一个单独的测试-重测队列（N=50）中开发并验证了BrainPAC任务。
结果：在大多数指标上，BrainPAC任务与原始实验室范例显着相关（r=0.18-0.63，P<0.05）。除DDTk函数和VMAC总分外，5个任务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证明了足够的重测可靠性（组内相关系数0.72-0.91，P<.001；SDT除外）。游戏化指标与行为清单上的成瘾行为显着相关，尽管在很大程度上独立于已知的预测成瘾风险的基于特征的量表。
结论：一组专门构建的数字游戏化任务对于对支持成瘾行为的关键神经认知过程的可扩展评估是足够有效的。这一验证提供了一种新方法的证据，据称是为了增强任务参与度，在评估与成瘾相关的神经认知方面是可行的，并且在经验上是合理的。这些发现对于风险检测和下一代评估工具的成功部署具有重要意义，用于药物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。BrainPAC工具的未来开发和验证应考虑进一步加强与既定措施的融合，并收集人口代表性数据以在临床上用作规范比较。
目的：这项研究的目的是在心理上验证一系列基于共识的神经认知任务的游戏化对标准实验室范式的影响，确定测试-重测可靠性，并确定他们对成瘾行为的敏感性(例如，酒精使用)和其他危险因素(例如，特质冲动)。
方法：选择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]，延迟贴现任务[DDT]，值调制注意力捕获[VMAC]任务，和顺序决策任务[SDT])，得到一个国际成瘾专家小组的认可；即反应选择和抑制，奖励估价，动作选择,奖励学习，期望和奖励预测误差，习惯,和强迫性。与游戏开发者合作，通过MechanicalTurk使用横截面设计，在3个连续队列（总共N=600）和一个单独的测试-重测队列（N=50）中开发并验证了BrainPAC任务。
结果：在大多数指标上，BrainPAC任务与原始实验室范例显着相关（r=0.18-0.63，P<0.05）。除DDTk函数和VMAC总分外，5个任务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证明了足够的重测可靠性（组内相关系数0.72-0.91，P<.001；SDT除外）。游戏化指标与行为清单上的成瘾行为显着相关，尽管在很大程度上独立于已知的预测成瘾风险的基于特征的量表。
结论：一组专门构建的数字游戏化任务对于对支持成瘾行为的关键神经认知过程的可扩展评估是足够有效的。这一验证提供了一种新方法的证据，据称是为了增强任务参与度，在评估与成瘾相关的神经认知方面是可行的，并且在经验上是合理的。这些发现对于风险检测和下一代评估工具的成功部署具有重要意义，用于药物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。BrainPAC工具的未来开发和验证应考虑进一步加强与既定措施的融合，并收集人口代表性数据以在临床上用作规范比较。
