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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Nov 18, 2022
Open Peer Review Period: Nov 18, 2022 - Nov 25, 2022
Date Accepted: Jul 22, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

A Novel, Expert-Endorsed, Neurocognitive Digital Assessment Tool for Addictive Disorders: Development and Validation Study

Lee RSC, Albertella L, Christensen E, Suo C, Segrave RA, Brydevall M, Kirkham R, Liu C, Fontenelle LF, Chamberlain SR, Rotaru K, Yücel M

A Novel, Expert-Endorsed, Neurocognitive Digital Assessment Tool for Addictive Disorders: Development and Validation Study

J Med Internet Res 2023;25:e44414

DOI: 10.2196/44414

PMID: 37624635

PMCID: 7615064

A Novel, Expert-Endorsed, Neurocognitive Digital Assessment Tool for Addictive Disorders: Development and Validation Study

  • Rico S. C. Lee; 
  • Lucy Albertella; 
  • Erynn Christensen; 
  • Chao Suo; 
  • Rebecca A. Segrave; 
  • Maja Brydevall; 
  • Rebecca Kirkham; 
  • Chang Liu; 
  • Leonardo F. Fontenelle; 
  • Samuel R. Chamberlain; 
  • Kristian Rotaru; 
  • Murat Yücel

ABSTRACT

Background:

Many people with harmful addictive behaviours do not meet formal diagnostic thresholds for a disorder. A dimensional approach, by contrast, including clinical and community samples is therefore key to early detection, prevention, and intervention. Importantly, while neurocognitive dysfunction underpins addictive behaviours, established assessment tools for neurocognitive assessment are lengthy and unengaging, difficult to administer at scale, and not suited to clinical or community needs. The 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.

Objective:

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 and other risk factors (eg, trait impulsivity).

Methods:

Gold standard laboratory paradigms were selected to measure key neurocognitive constructs endorsed by an international panel of addiction experts; namely, response selection/inhibition, reward valuation, action selection, reward learning, expectancy/reward prediction error, habit, and compulsivity. Working with game developers, BrainPAC tasks were developed and validated in three successive cohorts (total N = 600) and a separate test-retest cohort (N = 50) via Mechanical Turk using a cross-sectional design.

Results:

BrainPAC tasks were significantly correlated with the original laboratory paradigms (p’s < 0.05), with all except two metrics differing between gamified and non-gamified tasks (p’s > 0.05). Four out of five tasks demonstrated good test-retest reliability (r’s ≥ 0.6). Gamified metrics were significantly associated with addictive behaviours on behavioural inventories, though largely independent of trait-based scales known to predict addiction risk.

Conclusions:

A purpose-built battery of digital gamified tasks is a valid approach for the scalable assessment of key neurocognitive processes underpinning addictive behaviours. This validation provides evidence that a novel approach, purported to enhance task engagement, in the assessment of addiction-related neurocognition is valid, reliable and feasible. These findings have significant implications for risk detection and the successful deployment of next-generation assessment tools for substance (mis)use and other mental disorders characterised by neurocognitive anomalies related to motivation and self-regulation.


 Citation

Please cite as:

Lee RSC, Albertella L, Christensen E, Suo C, Segrave RA, Brydevall M, Kirkham R, Liu C, Fontenelle LF, Chamberlain SR, Rotaru K, Yücel M

A Novel, Expert-Endorsed, Neurocognitive Digital Assessment Tool for Addictive Disorders: Development and Validation Study

J Med Internet Res 2023;25:e44414

DOI: 10.2196/44414

PMID: 37624635

PMCID: 7615064

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.