Instrumentation & Measurement Magazine 24-6 - 35

The parameter estimates for the Number of sessions are almost
zero and not significant, suggesting that engagement
scores are not a function time. The parameter estimates for
the Game level are positive and significant, suggesting that as
the players' performance improved, their engagement also
improved. The linear coefficient for Affect is positive and significant,
suggesting that, as the participants experienced a
positive affect, they would be more engaged during gameplay.
The parameter estimates for the Disturbances are negative
and significant, indicating, not surprisingly, that disturbances
in the environment had a negative effect on engagement. The
linear coefficient for Prev Exp Comp Games is positive and
significant, suggesting that participants who had previous experience
playing mobile games before our study were more
likely to be highly engaged during gameplay. Despite a positive
correlation between Cognitive impairment and engagement
scores, which suggests that participants with cognitive impairment
were more engaged while playing computer games, this
estimate was not statistically significant. Finally, the type of
game played (i.e., the Type of game) was not significant for engagement
scores, although the descriptive statistics seemed
to show that Word-Search and Mahjong were more engaging.
Model A Equation:
Engagement β φ εti
ti   0i
Model B Equation:
Engagement β β NoSessions φ εti
1
ti
0i
Model C Equation:
 
 4
3
ti
 
ti
1 
ti 
0i
ti
Model D Equation:
 
ti
1
3
6
ti
4
i
7
2 
t i   (4)
Engagement β β NoSessions β GameLevel
β Affect β Disturb φ ε
ti
Engagement β β NoSessions β GameLevel
β Affect β Disturb β Prev_Exp
β CogImp β Type_Game φ ε
ti  
2
  
 
ti
5
i   0i
Model E Equation:
ti
 5

0i  ti
ti


0 1
i6 
i7
i
Engagement β β NoSessions β Affect
β Prev_Exp β CogImp β Type _Game
φ ε
ti  3

ti
i
(7)
Discussion
The purpose of this study was to determine what factors predict
engagement scores of older adults with and without
dementia while playing mobile games. To that end, we collected
repeated measures of our users' cognitive function,
affect and engagement after their gameplay sessions and fitted
the collected data with a multilevel linear mixed model. Our results
show that, regardless of the number of gameplay sessions
and game type, older adults' game level achieved, their previous
experience using computer games, and positive affect
were predictors of the engagement. In other words, our results
indicate that both objective and subjective measures matter in
predicting engagement. This model nicely corresponds to the
September 2021
Conclusion
ti
(5)
ti
(6)
Our findings with older adults indicated that game level
achieved, previous experience playing mobile games, and positive
affect experienced during gameplay mattered in keeping
the participants engaged while playing the mobile games.
However, the number of gameplay sessions and the type of the
game did not affect their engagement. A quiet environment
without disturbances (e.g., noise, bright light, comments from
and conversations with peers) was a strong predictor of increased
older adult engagement.
Acknowledgment
We thank study participants and our partners (Alzheimer
Society of Alberta and Northwest Territories, Revera) for contributing
their time and feedback. We also thank research
assistants and occupational therapy and computing science
students for their help in developing the Vibrant Minds games
as well as in collecting and analyzing the data. Finally, we
would like to thank Burn Evans and Ken Yu, two older adults
who contributed to the game designs and instructional videos.
References
[1] G. Livingston, A. Sommerlad, V. Orgeta, S. G. Costafreda, J.
Huntley, D. Ames, C. Ballard, S. Banerjee, A. Burns, J. CohenMansfield
and others, " Dementia prevention, intervention, and
care, " The Lancet, vol. 390, p. 2673-2734, 2017.
[2] L. Nguyen and K. Murphy, " Immediate and long-term efficacy
of executive functions cognitive training in older adults: a
systematic review and meta-analysis, " American Psychological
Association, pp. 698-733, 2019.
IEEE Instrumentation & Measurement Magazine
35
(3)
notion of the " state of flow, " where an individual is working
uninterrupted on an activity of interest that is challenging but
still manageable. Although not statistically significant, cognitive
impairment was a potential predictor of engagement, as
older adults with dementia reported higher levels of engagement.
Therefore, engagement in cognitive activities in the form
of mobile games has the potential to positively impact the cognitive
skills of older adults with dementia. We are aware that
some older adults may not have been able to articulate their
experiences. However, this does not mean that they were unable
to experience engagement while playing mobile games
or that they were unable to benefit from taking part in play activities.
Thus, our next steps will be to use machine learning
algorithms to classify engagement behaviors and then to adjust
the complexity of the games to keep older adults engaged
during mobile gameplay.
A visual analysis of Fig. 2b and Fig. 2c suggested exploring
whether some of the interactions between the covariates
had an effect on the engagement scores (e.g., Number of sessions*
Cognitive impairment). Although we ran some models
that aimed to explore these interactions, the computational algorithms
for the estimate of the covariance parameters did not
converge. We believe the small sample size was the main reason
this happened. Interactions between covariates should be
explored in larger datasets in further studies.

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