Search and Match Task: Development of a Taskified Match-3 Puzzle Game to Assess and Practice Visual Search

Alvin Chesham; Stephan Moreno Gerber; Narayan Schütz; Hugo Saner; Klemens Gutbrod; René Martin Müri; Tobias Nef; Prabitha Urwyler

doi:10.2196/13620

Search and Match Task: Development of a Taskified Match-3 Puzzle Game to Assess and Practice Visual Search

JMIR Serious Games. 2019 May 9;7(2):e13620. doi: 10.2196/13620.

Authors

Alvin Chesham¹, Stephan Moreno Gerber¹, Narayan Schütz¹, Hugo Saner^{1

2}, Klemens Gutbrod³, René Martin Müri^{1

3}, Tobias Nef^{1

4}, Prabitha Urwyler^{1

4}

Affiliations

¹ Gerontechnology & Rehabilitation, University of Bern, Bern, Switzerland.
² Department of Cardiology, University Hospital (Inselspital), Bern, Switzerland.
³ Department of Neurology, University Neurorehabilitation, University Hospital Bern (Inselspital), University of Bern, Bern, Switzerland.
⁴ Artificial Organ Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.

PMID: 31094325
PMCID: PMC6532342
DOI: 10.2196/13620

Abstract

Background: Visual search declines with aging, dementia, and brain injury and is linked to limitations in everyday activities. Recent studies suggest that visual search can be improved with practice using computerized visual search tasks and puzzle video games. For practical use, it is important that visual search ability can be assessed and practiced in a controlled and adaptive way. However, commercial puzzle video games make it hard to control task difficulty, and there are little means to collect performance data.

Objective: The aim of this study was to develop and initially validate the search and match task (SMT) that combines an enjoyable tile-matching match-3 puzzle video game with features of the visual search paradigm (taskified game). The SMT was designed as a single-target visual search task that allows control over task difficulty variables and collection of performance data.

Methods: The SMT is played on a grid-based (width × height) puzzle board, filled with different types of colored polygons. A wide range of difficulty levels was generated by combinations of 3 task variables over a range from 4 to 8 including height and width of the puzzle board (set size) and the numbers of tile types (distractor heterogeneity). For each difficulty level, large numbers of playable trials were pregenerated using Python. Each trial consists of 4 consecutive puzzle boards, where the goal of the task is to find a target tile configuration (search) on the puzzle board and swap 2 adjacent tiles to create a line of 3 identical tiles (match). For each puzzle board, there is exactly 1 possible match (single target search). In a user study with 28 young adults (aged 18 to 31 years), 13 older (aged 64 to 79 years) and 11 oldest (aged 86 to 98 years) adults played the long (young and older adults) or short version (oldest adults) of the difficulty levels of the SMT. Participants rated their perception and the usability of the task and completed neuropsychological tests that measure cognitive domains engaged by the puzzle game.

Results: Results from the user study indicate that the target search time is associated with set size, distractor heterogeneity, and age. Results further indicate that search performance is associated with general cognitive ability, selective and divided attention, visual search, and visuospatial and pattern recognition ability.

Conclusions: Overall, this study shows that an everyday puzzle game-based task can be experimentally controlled, is enjoyable and user-friendly, and permits data collection to assess visual search and cognitive abilities. Further research is needed to evaluate the potential of the SMT game to assess and practice visual search ability in an enjoyable and adaptive way. A PsychoPy version of the SMT is freely available for researchers.

Keywords: aging; attention; match-three puzzle games; neuropsychological tests; pattern recognition, visual; task difficulty; video games.

©Alvin Chesham, Stephan Moreno Gerber, Narayan Schütz, Hugo Saner, Klemens Gutbrod, René Martin Müri, Tobias Nef, Prabitha Urwyler. Originally published in JMIR Serious Games (http://games.jmir.org), 09.05.2019.