Digital game-based interventions for cognitive training in healthy adults and adults with cognitive impairment: Protocol for a two-part systematic review and meta-analysis

Abstract

IntroductionDigital game-based training interventions are scalable solutions that may improve cognitive function for many populations with varying abilities. This two-part review aims to synthesise the effectiveness and key features of digital game-based interventions for cognitive training in: 1) healthy adults across the life span; and 2) adults with cognitive impairment, to update current knowledge and impact the development of future interventions for different adult subpopulations.Methods and analysisThis systematic review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines. A systematic search was performed in PubMed, Embase.com, CINAHL, Cochrane Library, Web of Science, PsycINFO and IEEE Explore on July 31st, 2022 for relevant literature published in the previous five years. Experimental, observational, exploratory, correlational, qualitative and mixed-methods studies will be eligible if they report at least one cognitive function outcome and include a digital game-based intervention intended to improve cognitive function. Reviews will be excluded but retained to search their reference lists for other relevant studies. All screening will be done by at least two independent reviewers. The appropriate Joanna Briggs Institute Critical Appraisal Tool, according to the study design, will be applied to perform the risk of bias assessment. Outcomes related to cognitive function and digital game-based intervention features will be extracted. Results will be categorised by adult life span stages in the healthy adult population for Part 1 and by neurological disorder in Part 2. Extracted data will be analysed quantitatively and qualitatively, according to study type. If a group of sufficiently comparable studies is identified, we will perform a meta-analysis applying the random effects model with consideration of the I2statistic.

N-of-1 medicine

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