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Video game training to improve selective visual attention in older adults

BELCHIOR, Patrícia, et al.

Abstract

The current study investigated the effect of video game training on older adult's useful field of view performance (the UFOV® test). Fifty-eight older adult participants were randomized to receive practice with the target action game (Medal of Honor), a placebo control arcade game (Tetris), a clinically validated UFOV training program, or into a no contact control group.

Examining pretest–posttest change in selective visual attention, the UFOV improved significantly more than the game groups; all three intervention groups improved significantly more than no-contact controls. There was a lack of difference between the two game conditions, differing from findings with younger adults. Discussion considers whether games posing less challenge might still be effective interventions for elders, and whether optimal training dosages should be higher.

BELCHIOR, Patrícia, et al . Video game training to improve selective visual attention in older adults. Computers in Human Behavior , 2013, vol. 29, no. 4, p. 1318-1324

DOI : 10.1016/j.chb.2013.01.034

Available at:

http://archive-ouverte.unige.ch/unige:91881

Disclaimer: layout of this document may differ from the published version.

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Video game training to improve selective visual attention in older adults

Patrícia Belchior

a,

, Michael Marsiske

b,

, Shannon M. Sisco

b

, Anna Yam

b

, Daphne Bavelier

c

, Karlene Ball

d

, William C. Mann

e

aSchool of Physical and Occupational Therapy, McGill University, Canada

bDepartment of Clinical and Health Psychology, University of Florida, United States

cDepartment of Brain and Cognitive Sciences, University of Rochester, United States

dDepartment of Psychology, University of Alabama-Birmingham, United States

eDepartment of Occupational Therapy, University of Florida, United States

a r t i c l e i n f o

Article history:

Available online 1 March 2013

Keywords:

Aging Visual attention Training Videogames Older adults

a b s t r a c t

The current study investigated the effect of video game training on older adult’s useful field of view per- formance (the UFOV Òtest). Fifty-eight older adult participants were randomized to receive practice with the target action game (Medal of Honor ), a placebo control arcade game (Tetris), a clinically validated UFOV training program, or into a no contact control group. Examining pretest–posttest change in selec- tive visual attention, the UFOV improved significantly more than the game groups; all three intervention groups improved significantly more than no-contact controls. There was a lack of difference between the two game conditions, differing from findings with younger adults. Discussion considers whether games posing less challenge might still be effective interventions for elders, and whether optimal training dos- ages should be higher.

Ó2013 Elsevier Ltd. All rights reserved.

1. Introduction

The focus of the current study was to examine whether off-the- shelf video games, particular ly so-called first person action video games, could boost useful field of view (UFOV, a widely studied measure of speed of processing and visual attention) in older adults. UFOV yields an estimate of the size of the visual area within which targets can capture attention during a brief inspection per- iod, and has been shown to be negatively related to age (Ball, Beard, Roenker, Miller, & Griggs, 1988; Sekuler, Bennett, & Mamel- ak, 2000 ). The deteriorati on of the UFOV is characterized by a de- crease in the efficiency with which individua ls can extract information from a cluttered scene, rather than by a shrinking of the field of view per se. Furthermore, the decrease in efficiency is increased when conditions require the division of attention be- tween central and peripheral tasks (Sekuler et al., 2000 ). When there is training, the primary goal of the UFOV is to improve pro-

cessing speed/efficiency by which central and peripheral targets can be identified (Ball, Edwards, & Ross, 2007 ).

UFOV performance appears to have practical implication s:

Better UFOV has been associated with better driving (De Raedt

& Ponjaert-Kristoffe rsen, 2000; Roenker, Cissell, Ball, Wadley, &

Edwards, 2003 ) and everyday task performance (Ball et al., 2007), and UFOV testing has been integrated into some elder driving assessment contexts (Clay et al., 2005; Myers, Ball, Kali- na, Roth, & Goode, 2000 ). It follows that UFOV improvements are expected to be related to maintained mobility and everyday functioning .

The UFOV test is comprised of three subtasks: speed of process- ing, divided attention and selective attention , which build on top of each other in complexity. Several training studies have found that UFOV can be improved with fairly brief computer-base d instruc- tion on the criterion task (Edwards et al., 2005 ). Training is usually adaptive , beginning at the lowest level of skill in which the partic- ipant shows performanc e below a defined criterion. Training goals are to increase speed of processing as well as the peripheral eccen- tricity of detected targets. In ACTIVE, a multi-site clinical trial of adults aged 65 years and older, initial UFOV intervention effects were maintained up to 5 years post-inter vention (Ball et al., 2002; Willis et al., 2006 ).

The rationale for examining video games as an alternative ap- proach to training UFOV-relate d visual attention stems from prior research with younger adults and from practical considerations . Studies by Green and Bavelier (2003, 2006a) and colleagues 0747-5632/$ - see front matter Ó2013 Elsevier Ltd. All rights reserved.

http://dx.doi.org/10.1016/j.chb.2013.01.034

Corresponding authors. Addresses: School of Physical and Occupational Ther- apy, McGill University, Hosmer House, 3654 Promenade Sir William Osler, Montreal (QC), Canada H3G 1Y5. Tel.: +1 514 398 4400x00675; fax: +1 514 398 8193 (P.

Belchior), Department of Clinical and Health Psychology, University of Florida, PO Box 100165, Gainesville, FL 32610-0165, United States. Tel.: +1 352 273 5097; fax:

+1 352 720 5897 (M. Marsiske).

E-mail addresses:Patricia.belchior@mcgill.ca (P. Belchior),marsiske@phhp.u- fl.edu(M. Marsiske),ssisco@phhp.ufl.edu(S.M. Sisco),ayam@phhp.ufl.edu(A. Yam), daphne@bcs.rochester.edu(D. Bavelier),kball@uab.edu(K. Ball),wmann@phhp.u- fl.edu(W.C. Mann).

Contents lists available atSciVerse ScienceDi rect

Com puters in Human Behavior

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h

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research. When interventions require travel to centralized facilities during defined office hours, only more persistent or committed participants are likely to remain compliant. Furthermor e, ‘‘busi- ness’’ hours limit the exposure time to the training program. In addition,Park, Gutchess, Meade, and Stine-Mor row (2007)have ar- gued that active leisure (‘‘productive engagement’’) which encour- ages the formation of new schema will be more likely than

‘‘receptive engagement’’ (e.g., reading, listening to music) to lead to the developmen t of improved cognition. Furthermore, recent work employin g strategy-based video games with older adults, has documented improvements in executive skills such as the abil- ity to switch between task sets (Basak, Boot, Voss, & Kramer, 2008 ).

The mechanisms by which action video games impact visual and cognitive skills are still unknown. It has been posited that ac- tion video game play facilitates a general speed of processin g improvement, presumably by (a) the game demands for fast and frequent decisions (Green, Pouget, & Bavelier, 2010 ), (b) the use of a dynamic display and a rich environment to explore, (c) the need for divided attention at all times, and (d) the rapid pace requiring non-stop decision making (Achtman et al., 2008 ). In addi- tion,Clark, Fleck, and Mitroff (2011)found that video game players (VGPs) and non-vide o game players (NVGPs) use different search patterns when exploring a visual scene. VGP are more likely to search the visual scene broadly while NVGP are more likely to per- severe in a given region. Furthermor e, VGP require fewer expo- sures to the change stimulus to detect its presence . It can be the case that VGP are able to capitalize on their visual processing abil- ities and explore larger areas of the image or alternativel y they might use a different strategy to employ a broad search strategy.

Another study found that video game playing can alter funda- mental characteristics of the visual system such as the spatial res- olution of visual processin g across the visual field (Green &

Bavelier, 2007 ). The spatial resolution of visual attention was mea- sured by the smallest distance a distracter could be from a target without compromising target identification. Results showed that, compared with a non-video game player, an action video game player could tolerate smaller target-dis tracter distances.

Prior work employin g video game interventions also suggests that video games, due to their multimodal engagement of re- sources, might facilitate enhancem ent of processin g components with more widespre ad conseque nces, which as Hertzog et al.

(2008) argue, might be particularly appropriate for individuals with better-preserved latent cognitive potential.

The current study sought to augment the video game literature by (a) extending a previously employed video game training ap- proach to older adults (i.e. Medal of Honor , Green & Bavelier, 2003), (b) including a no-conta ct control group, and (c) including a clinically validated training condition (UFOV training), which has been shown to effectively enhance UFOV skills in prior studies (Ball et al., 2002 ). This clinically validated group could serve as a benchmark for gauging video game training effect sizes. This study was also intended as a feasibilit y/pilot study to investigate the use of video games to train visual attention in a group of older adults.

As such, beyond the goal of finding statistically significant training group differences (as reported in this paper), we also sought to

Federal Entity Identification Number: 1596002052A 1) of the Uni- versity of Florida. Informed consent was obtained for all partici- pants, and the investigatio n was conducte d according to the principles expressed in the Declaration of Helsinki.

2.2. Sample

As is typical for almost all studies in this field of research, the sample was a community -solicited volunteer group from the com- munity surrounding University of Florida. Participants ’ characteris- tics were reflective of the local community. Fifty-eight non-gamers complete d the entire study; they were generally young-old (mean age = 74.5 years, SD = 6.7, range = 65–91), college-educated (mean education = 16 years, SD = 2.4, high school to doctorate), and all were White. There were 30 women and 28 men. Participants were recruited by phone calls, by mail, and through flyers that were dis- tributed in the communi ty.

Three randomized participants (one from each intervention group – MOH, UFOV, Tetris) dropped out prior to the onset of train- ing and were not included in the analysis. No participant dropped out after the training had initiated. Given the small sample size, it is not surprising that there were no differences between dropout and completing participants in age, years of education, gender, MMSE, or visual acuity (p> .05).

As described in greater detail below, participants were random- ized into four groups (Medal of Honor n= 14; Useful Field of View n= 16; Tetris n= 15; Control n= 13). With an average group size of 14.5, this design was powered to detect an omnibus effect size Co- hen’sfor 0.45 at power = 0.80. This corresponds to an eta-squared of 0.17.

2.3. Inclusion and exclusion criteria

Included participants were (a) 65 years or older, (b) had very lit- tle or preferably no video game usage in the past 6 months (same criteria used byGreen & Bavelier, 2003 ), (c) scored 24 or higher on the Mini Mental State Examina tion (MMSE), (d) were willing to participa te in 6 training sessions, and (e) had visual acuity of 20/

70. Visual acuity tests were used because eye sensory function plays an important role in UFOV test performanc e and training ef- fects could be compromise d by a lack of visual acuity. Participants with composite scores of 200 (combined scores from speed, di- vided and selective attention tasks) or lower on the UFOV were ex- cluded from the study because of limited room for improvement (i.e., their baseline performanc e already exceeded the established criterion for training). With regard to participants ’ status as novice gamers, no participants reported playing any of console games prior to this study. The only game that a subset of participants re- ported playing was solitaire on a computer; those participa nts were not excluded, since there was no clear association between that game and the demands of the console game. It should be fur- ther noted that fewer than five of 58 participants reported playing even these simple computer games.

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2.4. Measures

Three subtasks from the UFOV Òtest were included as depen- dent measure s (same as inBall et al., 2002 ). Each subtask pre- sented stimuli at speeds ranging from 16 to 500 ms. For each subtask, a double staircase method determined an individual’s threshold of 75% correct performanc e. This value, assessed in mil- liseconds, was the individual’s score on the task. UFOV training fo- cus on increasing speed of processing and speed of responding is not important. The subtasks (see Fig. 1), in order of incremen tal difficulty, were:

2.4.1. Speed

This subtask required accurate identification of a centrally-pre- sented object (two-dimensional line drawing of a car or truck).

2.4.2. Divided attention

This subtask required both accurate object identification and simultaneou s accurate localization of a peripher ally-presented car.

2.4.3. Selective attention

This subtask was similar to Divided Attention, but added visual clutter (multiple equilateral triangles that filled most of the blank areas of the screen), requiring rapid visual search to localize the peripheral target.

The analysis was conducted using each subscore as a separate within-pers on level of a task factor. The score for each subtask could range from 16 ms (the minimum frame rate the computer could detect) to 500 ms (a maximum time-out criterion). Lower scores indicated better speed of processing skills. Specifically, the score assigned to each subtask reflected the presentation time needed to achieve at least 75% accuracy on the central task (for Speed) and on the peripheral task as well (for Divided and Selective Attention).

To permit comparis ons with the ACTIVE study (Ball et al., 2002 ), we used the identical UFOV presentation platform as the ACTIVE study, which was a DOS based platform, with no chin rest. The training procedure was identical to that reported in Ball et al.

The UFOV testing and training were conducted in a darkened room, following standardized instructions associated with that training program.

2.5. Design and procedure

Participants were randomized to one of four groups: (1)Medal of Honor training (MOH; target intervention for this study, n= 14); (2) clinically validated UFOV training (Ball et al., 2002 , n= 16); (3) Tetris (placebo control) training (Green & Bavelier,

2003,n= 15); or (4) no-contact control (pre- and posttest only, n= 13). Pre- and post assessments were complete d within 1 week of interventi ons.

The two video game training conditions (MOHandTetris) em- ployed a Sony PlayStation 2 (PS2), console model 97060 and a dual shock 2 analog controlle r, model 97026. The games were presente d on a 1900 TV monitor. The UFOV training was administere d via a desktop computer. A CPU was connected to a 2100ELO touch screen.

For the three training conditions, training consisted of six 90- min sessions administered over 2–3 weeks. Training was sched- uled according to participa nts’ preferred time of day. For consis- tency, to control time-of-day effects within subject, participants were trained at the same time of day for all subsequent sessions.

Trainers were undergraduate student assistants who had extensive self-repo rted experience with action video games. All trainers re- ceived instruction in the impleme ntation of the training protocol, which was manualized. Manuals with step by step instructions on game play were developed for both video game conditions.

For the UFOV condition, a training manual previously used in the ACTIVE (Ball et al., 2002 ) study was used. Trainings were provided individua lly or in groups of 2. Training is summarized below, and full copies of the training manual are available from the authors upon request.

For both video game conditions (Medal of Honor, Tetris), the trainer played the game for about 10 min in order to model game play and the requisite skills. Next, the trainer demonstrated use of the controller to the participants.

2.5.1. Medal of Honor training

In this training, participants played the ‘‘first person shooter’’

video game Medal of Honor – Rising Sun , first with guidance from a student trainer and then more independen tly. The MoH training was conducted in a lighted room with normal office (fluorescent) lighting, using low-glare television screens.

The MOH game is quite challenging for novice elders, so diffi- culty level was made manageable by use of step by step instruc- tions on how to play the game, which were presented by an experienced trainer/coach, using a Microsoft Power Point presenta - tion on a computer that was placed next to the participants. Train- ing broke the game into missions, and manualized all the steps needed to successfully solve a mission. The experienced coach/

interventi onist first modeled successfu l game play, talking aloud as they progressed through the mission. The coach then had partic- ipants execute all the manualiz ed steps themselves, starting and stopping as much as needed, until they had successfu lly complete d a mission. Finally, participants played through the mission from beginning to end, and continued to play until they had successfu lly complete d the mission. This shaping by steps ensured that all

Fig. 1.Useful field of view subtasks.

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which is a classic 1980s arcade game, seven randomly rendered tetrominoes – shapes composed of four blocks each – fall down the playing field. The object of the game is to manipulate these tetrominoes to create a horizontal line of blocks without gaps.

When such a line is created, it disappears, and the blocks above (if any) fall. As the game progresses, the tetrominoes fall faster, and the game ends when the stack of tetrominoes reaches the top of the playing field. Unlike MOH, the Tetrisgame scenario did not change over the course of the following sessions. The partici- pants had to repeat the same task over and over again; however as game play improved, the speed of tetramino dropping increased.

It should also be noted that participa nts had to visually process the tetramino at the top of the screen, while simultaneou sly determin- ing the optimal position for its placement at the bottom of the screen. Thus,Tetrisrequired continual visual scanning and spatial manipulation, although tetramin os were usually presented more in the central and less in the peripher al fixation region.

2.5.3. Useful field of view (UFOV) training

For this training, a manual previousl y employed in ACTIVE (Ball et al., 2002 ) was used. In the initial assessme nt, participa nts re- ceived a preliminary score on the each of the three UFOV subtasks.

Participants were considered not in need of further training on a subtask if they were scoring 30 ms or better on Speed, 40 ms or better on Divided Attention, or 80 ms or better on Selective Atten- tion. Training began at participants’ current skill level, starting at the most challenging level (speed followed by Divided Attention followed by selective attention) at which the participa nt was per- forming worse than the pre-specified training criterion. Within a given task, training started at roughly the presentation time at which they performed with high accuracy (75%) on the screening

An analysis of variance was conducted to determine whether there were differences between the four intervention groups in demogra phic status, age, years of education, gender, race, cognitive status (MMSE), and visual acuity. The omnibus test revealed that there were no significant differences between the four groups, sug- gesting that randomizat ion had distribut ed participant characteris- tics similarly across the groups.Table 1shows the characteri stics of the sample on the variables assessed, both for the total group and by intervention subgroup.P-values shown reflect the absence of a significant overall differenc e between groups.

3.2. Training effect on visual attention

In UFOV training, goal performance on the Speed subtask is 630 ms and on the Divided Attention subtask 640 ms. Preliminary analyses revealed that the majority of participants were perform- ing at or better than this criterion on the Speed (93%) and Divided Attention (53% at 640 ms) subtasks at baseline. In contrast only one participant (1.7%) was at or below the 680 ms training goal for Selective Attention. This applied to all groups, and meant re- duced sensitivit y to change for these first two outcome s.

A 324 ANOVA was conducte d with two within-pers ons factors (UFOVÒTask: Speed, Divided Attention, Selective Attention and Test: Pretest, Posttest) and one between-pe rson factor (Train- ing Group:Medal of Honor , UFOV,Tetris, no-contact). A significant main effect was revealed for Test (prepost), F(1, 54) = 23.49, p< .001,

g

2= .30, Cohen’s f= 0.65 and UFOV Ò task, F(2, 108) = 178.36,p< .001,

g

2= .77, Cohen’s f= 1.83 but no signifi- cant main effect was found for Group, F(3, 54) = 1.27, p= .294,

g

2= .07, Cohen’s f= 0.27. A significant two-way interaction effect

Table 1

Sample characteri stics both for the total group and by intervention subgroup.

Total sample (N= 58) MOH group (N= 14) UFOV group (N= 16) Tetris group (N= 15) Non contact (N= 13) p-Values

Age .81

M 74.7 74.8 73.7 75.8 73.7

(SD) (6.4) (6.3) (6.2) (8.5) (5.3)

Education .72

M 16.0 15.8 15.6 16.5 16.3

(SD) (2.4) (2.5) (2.6) (2.6) (1.7)

Sex .33

Male

N 28 9 5 7 7

(%) (48.3) (64.3) (31.2) (46.6) (53.8)

Female

N 30 5 11 8 6

(%) (51.7) (35.7) (68.8) (53.4) (46.2)

MMSE .42

M 29.8 29.2 29.2 29.4 29.0

(SD) (5.2) (.97) (1.5) (.91) (1.2)

Vision .26

M 85.2 87.2 86.8 86.3 79.6

(SD) (11.5) (5.9) (3.9) (5.1) (22.3)

Snellen equivalent

20/18 20/17 20/17 20/17 20/20

Note: MOH = Medal of Honor; UFOV = useful field of view; MMSE = Mini Mental State Examination.

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was revealed for Test UFOVÒ task, F(2, 108) = 11.44, p< .001

g

2=.18, Cohen’s f= 0.47, but no significant interaction effects were revealed for UFOV ÒtaskGroup,F(6, 108) = .945,p= .467,

g

2=.05, Cohen’sf= 0.23 or Test Group, F(3, 54) = 2.37,p= .081,

g

2= .12 Cohen’sf= 0.37. All lower order effects were qualified by a signif- icant three-way interactio n: Test UFOVÒ taskGroup effect, F(6, 108) = 3.40,p< .004,

g

2=.16, Cohen’s f= 0.44.

Followup univariate ANOVAs were conducted for each UFOV Ò task (Speed, Divided Attention, Selective Attention). Main effects and interactio n of Test (2: pretest, posttest) and Group (4: Medal of Honor, UFOV, Tetris, no-contact) were examined, as summarized inTable 2. AsTable 2and the means/standar d deviations inTable 3 show, for Divided Attention and Selective Attention, faster posttest performanc e for all groups produced the Test main effect.

To decompose the Test- -Group interaction for the Selective Attention task, a simple effects post-hoc analysis compared pre- post change by group; results showed greater improvem ent for (1) UFOV-tra ined participants than controls,t(54) = 3.51,p= .001,

g

2=.19, Cohen’s f= 0.48, Cohen’s d= .99, (2) Medal of Honor - trained participants than controls, t(54) = 2.13, p= .038,

g

2= .08, Cohen’sf= 0.29, Cohen’s d= 0.59 and (3)Tetris-trained participants than controls,t(54) = 2.81, p= .007,

g

2=.13, Cohen’s f= 0.39, Co- hen’sd= 0.77. None of the three intervention groups differed from one another (allps > .05).Table 3demonst rates that UFOV-trained participants gained about 90.34 ms in Selective Attention, while Medal of Honor andTetrisgained about 53.00 and 71.60 ms respec- tively. Control participants , on the other hand, performed about 9.15 ms slower at posttest than at pretest. If Bonferroni corrections had been used to keep family-wise error rates below .05, only tests withp-values of .008 and lower would be judged significant, mean-

ing that the Medal of Honor effect would not be judged significantly greater than controls.

4. Conclusion

The current study findings are promising but should be inter- preted with caution due to low sample size, minimal training dos- age and the lack of racial/ethni c diversity in the sample. Clearly, generaliz ability of the current findings to a larger and more diverse population of elders is a necessary goal for future research. This study, which employed action video games to train older adults’ vi- sual attention skills, partially replicated previous findings with younger adults (Green & Bavelier, 2003 ), in that playing a first-per- son shooter game was associated with significant improvement in selective visual attention relative to no contact controls. Unlike in the younger adults from the Green and Bavelier (2003)study,Tetris play (an arcade puzzle game utilized as a placebo control condi- tion) also improved selective attention in our older adult sample.

All participa nts were novice players; thus, no participant reported playing any of console games prior to this study.

The UFOV training program produced marginall y (but not sig- nificantly) greater improvement than the video games, which was expected given high isomorph y between the training condi- tions and the tests used to evaluate change. Unfortunate ly, the low sample size in this study compromise d the power to detect dif- ferences among the training conditions. The biggest surprise in this study was the apparent effect ofTetris play on selective visual attention , which was not observed in the Green and Bavelier (2003)study with younger adults. Speculatively, given that Tetris appears to demand whole-scree n scanning and mental rotation which, for non-gamer older adults, may have been sufficiently Table 2

ANOVA summary tables for three visual attention outcomes.

Source df Speed Divided Attention Selective Attention

F g2/f1 F g2/f F g2/f

Between-subjects

Group (G) 3 0.75 0.04 /0.20 1.77 0.09 /0.31 0.94 0.05/0.23

Error 54 198.84 7020.19 21436.67

Within subjects

Test (T) 1 2.74 0.05 /0.23 5.93 * 0.10 /0.33 26.49 *** .33/0.70

Group Test 3 1.45 0.08 /0.29 1.05 0.06 /0.25 4.49 ** .20/0.50

Error 54 183.64 2255.33 2881.05

Note: values enclosed in parentheses represent mean square errors.g2= partial eta squared,f= Cohen’s f, estimate of effect size.

*p< .05.

**p< .01.

***p< .001.

Table 3

Change of useful field of view performance by group from pretest to posttest.

Measure Training group

UFOV (n= 16) Medal of Honor (n= 14) Tetris(n= 15) No-contact (n= 13)

Pretest Posttest Pretest Posttest Pretest Posttest Pretest Posttest

UFOV speed

M 19.88 16.94 18.29 19.43 20.13 18.53 30.15 16.85

SD 5.48 2.11 3.27 4.22 8.92 3.62 39.17 2.15

UFOV divided

M 41.69 24.56 85.36 43.43 95.73 66.67 61.92 63.92

SD 20.52 11.55 86.24 37.96 100.61 70.68 72.98 92.01

UFOV selected

M 209.00 118.63 225.64 172.64 256.93 185.33 209.54 218.69

SD 54.44 72.71 114.76 108.39 131.91 119.85 114.22 148.38

Note: Lower scores represent faster (better) performance. M = mean, SD = standard deviation, UFOV = useful field of view.

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more appealing to an older adult population than a first person shooter game.

A special question emerging from the current investigation is why the Tetris condition might have produced UFOV improvem ent in older adults, when it did not in younger adults (Green & Bavelier, 2003)? The answer likely includes the idea that our participants were older and were gaming novices. For novice older adults (who play Tetris against a backdrop of declining speed and percep- tual abilities), Tetris likely offered a much higher level of percep- tual, cognitive and motor challenge than it would for younger adults. The perceptual and motor demands of making relatively fast responses to falling blocks (novel stimuli requiring mental rotation), the need to divide attention between the falling object and the receptor site (located at different vertical ends of the game), the need to predict where the falling object would best fit, and the game-deliver ed feedback of decisions (‘‘clearing a row’’ or failing to do so) likely all contributed to making Tetris much more of an ‘‘action’’ video game for older adults than it would have been for younger participa nts.

As a preliminary study with relatively few participants, the current investigatio n can offer relatively little insight into the mechanism s or mediators of our video game training effects on UFOV. The growing literature in this area, however, suggests sev- eral speculative reasons regarding why video games might be effective. These include: (1) improvem ent in basic speed of pro- cessing (video games demand rapid and accurate response to transient objects with fast velocity; as participants increase speed in game play, this may generalize to speed in other tasks (Edwards et al., 2005; Roenker et al., 2003 &Dye, Green, & Bave- lier, 2009a ); (2) improvement in executive control (video games require balancing among a large number of concurrent demands, including fast response, high cognitive/percep tual/motor loads, peripheral and central visual field processing, predictin g what may happen next, maintaining items in short-term memory, ra- pid task switching, and reasonin g); practice with coordinatio n may then generalize to the coordina tive demands of UFOV (Green et al., 2010; Scalf et al., 2007 &Anderson-Han ley et al., 2012); in general, ‘‘gamification’’ increases the need to engage high-level planning and spatial working memory (Green & Bave- lier, 2012 ). (3) improvem ents in attentional control, including improvements in both the spatial and temporal operation of attention (Donohue, Woldorff, & Mitroff, 2010; Dye, Green, &

Bavelier, 2009b; Green & Bavelier, 2006b; Hubert-Wal lander, Green, & Bavelier, 2011 ); (4) improvements in the ability to quickly perceive the relations between multiple objects and events, since video games require differential response to differ- ent virtual objects; this may generalize to the simultaneou s per- ceptual identification and object localization demands of the UFOV selective attention task (Green et al., 2006a; Basak et al., 2008); (5) an fMRI study suggests that UFOV practice may in- creases activation in the right inferior frontal gyrus and right precentral gyrus; this raises the question of whether video game play might also increase activation in brain regions associated with the ability to recruit and re-orient stimulus-drive n atten- tion to novel and unpredictab le target locations outside the cur-

Mann, 2012 ) throughout the period of training, something that was not true for traditional UFOV training; might this suggest that high levels of engagement and effort mean that games encourag e older players to ‘stick with it’ and ‘try harder’, and that these factors contribute to the training potential of games?

This motivational interpretation is consistent with recent work byAnderson-Han ley et al. (2012), who showed that video-game based exercycling was more effective than traditional cycling in boosting executive function in older adults. The authors argued that the enjoyment and motivational value of games, including visual stimulation and personal challenge to beat previous per- formance levels, may make them particular ly potent intervention tools. If the games maximize engagement, individuals may exert maximal effort.

While the present study used a randomized experime ntal design with more control conditions than previous research (i.e.,Tetrisas control game, gold-standard training condition, and no-contact con- trols), given our sample of healthy, educated, White older adults, many of whom were performi ng quite well at baseline, the general- izability of findings is limited. Other studies using participants with slower baseline processing have found much larger training effects (Edwards et al., 2005 ). The modal intervention dosage of 6–9 h was brief, especially for the MOH condition, in which necessary

‘‘game learning’’ reduced time spent actively playing the game.

Future research can expand on the current findings in several key ways: (a) recruitment of a more ability-di verse sample with fewer high performer s at baseline; (b) increase of exposure dosage or additional dose-respon se studies to determine optimal amount of game play needed to produce larger and broader visual attention training effects; and (c) expansion of the outcome battery to exam- ine possible transfer effects and game differenc es in transfer to other measure s of visual attention , spatial cognition, and everyday function. In addition, more work aimed at identifying the processes by which games improve visual attention and other cognitive skills are necessar y. The present study contributes to the growing body of intervention work, termed ‘‘third generation’’ byHertzog et al.

(2009), aimed at capitalizing on neural plasticity and boosting underlyin g cognitive-beha vioral processes that might generalize to novel environments . Findings suggest that ‘‘off-the-shelf’’ video- games may be one accessible vehicle for achieving cognitive per- formance improvements in older adults.

Funding

This research was supported by the National Institute on Dis- ability and Rehabilitation Research Grant H133E01 0106 awarded to W.C.M. Patricia Belchior’s work on the manuscript was also sup- ported by a Supplement to Enhance Diversity Grant U01-AG- 014276-S1 to M.M. Anna Yam was supported, in part, by Robert Wood Johnson Foundati on Grant 64441 to P.B. Additional study support in the form of discounted software licenses was provided by Systems Technology Inc. (http://www.stisimdrive.com/ ) of Hawthor ne, CA. The funding sources had no involvement in re- search design, data collection or data analysis.

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Acknowled gments

We acknowledge the support of undergraduate colleagues at the Universit y of Florida who assisted with data collection and training activities. These include Jason Bendezu, Eric Gonzalez - Mule, Brian Huei, Matt Mustard, Sean Weisbrot, Emily Ricketts, and Claudia Ramirez. We also thank Jason Rogers for technical and IT-related support with this Project.

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