Aging Suit and Motor Performance in Young Adults: Effects Depend on Why the Suit is Worn!

Abstract

By 2030, one in six people worldwide will be at least 60 years old, with associated sensorimotor changes that complicate daily activities. Aging suits simulate these conditions for younger individuals to enhance their empathy and understanding of older adults’ challenges. Research on aging suits has recently increased, withevidence that these suits impair younger adults' motor performance; but, for a greater understanding of the motorchanges induced by aging suits, and, to identify any factors that may modify them, more research is needed. In this research, we explored how the presentation of the suit and the wearer’s physical activity level affected motor performance. We divided 95 younger adults into two groups: (a) one informed about the suit’s aging properties (aging suit group); and (b) one in which participants were told that it was a posture training suit (posture training group). Each group was further divided into low and high physical activity levels by a median-split method. Participants completed two fine motor tasks (i.e., placing and building bricks) and two gross motor tasks (i.e., heel-to-toe walking and figure-of-eight walking/running) with and without the suit. The aging suit significantly affected motor performance on all tasks, but participants aware that it was an aging suit performed worse on the figure-of-eight walking/running task than participants who thought it was a posture training suit. In addition, for the same motor task, the groups engaged in low physical activity were more affected by wearing the suit than those engaged in high physical activity. Thus, how aging suits are presented and the general activity level of wearers significantly influenced the aging suits’ effects on motor performance. The findings from this study can guide future researchers in validating the use of these suits in larger studies.

Keywords

aging suit motor performance aging representation aging simulation motor skills physical activity

Introduction

According to the World Health Organization (2022), one person in six will be at least 60 years old in 2030. Older adults experience cognitive, affective and sensorimotor changes. At the sensorimotor level, older adults undergo visual changes pathological ones (e.g., presbyopia, cataract), auditory changes (e.g., presbycusis and tinnitus), and especially general physical changes (e.g., sarcopenia, joint stiffness, difficulty and slowness in the execution of certain movements, decrease in coordination). Since, these sensorimotor changes can complicate daily activities, it is important to understand them to best support older adults in maintaining independence. Aging suits were created to allow younger adults to put themselves in the shoes of older people and better understand various environmental challenges faced by older individuals (e.g., automated driving; Frison et al., 2018; Scherf, 2014; home living; Taşoz & Afacan, 2022; use of mobile apps; Gaggioli et al., 2018; wayfinding in a hospital; Zijlstra et al., 2016; or shopping in a store; Lavallière et al., 2017) and the empathy and care they require from others, particularly medical staff (e.g., Bowden et al., 2020; Cheng et al., 2020; Eymard et al., 2010; Hsu et al., 2016; Jeong & Kwon, 2021; Lee & Teh, 2020; Ono et al., 2017; Sari et al., 2020; Schmidt et al., 2022; for a systematic review of studies published before 2010, see Tullo et al., 2010).

Aging suits generally comprise four modules or body regions, to best reproduce all the sensorimotor changes related to aging and create a whole-body experience (Groza et al., 2017): (a) head (sight, hearing, and neck motor skills); (b) torso (spinal movements); (c) arms (touch, joint movements, and fine motor skills); and (d) legs (walking and gross motor skills). Although most of these modules refer to motor difficulties encountered by older people, there has been limited research regarding the effects of aging suits on motor performance, with only eight studies in our awareness, including three focusing on walking (Gaggioli et al., 2018; Lauenroth et al., 2017; Laurentius et al., 2022; Lavallière et al., 2017; Schaefer et al., 2022; Vieweg & Schaefer, 2020; Watkins et al., 2021; Zijlstra et al., 2016).

In Lavallière et al. (2017), younger adults performed four gross motor tasks with and without an aging suit (Age Gain Now Empathy System, MIT AgeLab, Cambridge, USA; AgeLab, n.d.): (a) postural balance (in seconds, two conditions: eyes open and eyes closed); (b) shoulder and neck range of motion (four measure in degrees: shoulder abduction, cervical extension, lateral neck flexion and neck rotation); (c) lower back and hamstring flexibility (in centimeters on a sit-and-reach task); (d) gait (step frequency, velocity in meters/seconds, and number of steps per 10 m). Results revealed poorer performance by suit wearers on all four motor tasks. To go further, Gaggioli et al. (2018) compared older adults and younger adults without an aging suit, to three groups of younger adults wearing a GERonTologic simulator (GERT) aging suit (Produkt + Projekt Wolfgang Moll, Niederstotzingen, Germany; Moll, n.d.) with (a) visual disturbances only, (b) motor disturbances affecting the upper body only, and (c) visuomotor disturbances. For the two fine motor tasks (performed over the phone), the younger adults without the suit performed best, and the younger adults wearing the suit that induced visuomotor changes performed worst. More precisely, on a finger coordination task, older adults made significantly more errors than all other groups, but their response times did not differ from those of the younger group who had experienced visuomotor changes. For a speed response task involving visual search, older adults hit fewer targets and were slower than all other groups. Although this study made an interesting first contribution by comparing performances of younger adults wearing the aging suit with those of older adults, the motor tasks only involved the upper body (and phone using), while actual aging affects the whole body.

Another recent study compared the fine and gross motor performances of younger adults wearing the GERT aging suit with published normative data for older adults (Vieweg & Schaefer, 2020). Results indicated that when younger adults (M_age = 22 years) wore the aging suit, they lost 12%–26% of their gross motor skills as measured by the four motor dimensions on the Functional Fitness Test (Rikli & Jones, 1999): (a) chair stands and bicep curls holding a weight in 30 seconds for strength, (b) chair sit-and-reach task for flexibility, (c) step test for aerobic endurance and (d) 8-feet timed-up-and-go task for balance/agility). The younger adults’ performance was close to the norm for 60-year-olds (no statistical analysis reported). On fine motor skills measured with a shirt-buttoning task and the Purdue Pegboard™ Test (Tiffin & Asher, 1948) designed by Lafayette Instrument (2015), there was a reduction of 20–30%, and the motor performance of younger adults wearing the aging suit approached the norms of adults aged 80 and over (no statistical analysis reported). Declines in motor performance were also replicated in a more recent study by the same research team (Schaefer et al., 2022) that focused on the choice of appropriate strategies for two different motor tasks that varied in difficulty (i.e., risk of falling). However, members of this research team reported the limitation that physical activity level was not considered in these prior studies (Schaefer et al., 2022; Vieweg & Schaefer, 2020), as they only interviewed sports students, despite the impact of aging on older adults’ motor performance, particularly when they were experiencing physical changes (Buchman et al., 2007).

Negative stereotypes about aging can also affect the motor performance of older adults (Barber et al., 2020). The stereotypical ideas about aging may have been internalized in childhood and present in younger adults (Vauclair et al., 2018). Interestingly, in some studies, younger adults have been placed in fictional aging situations with the aid of virtual reality technology. Results in these studies have shown that when young adult participants embodied an older rather than a younger avatar, they exhibited poorer motor performance (walking time; Reinhard et al., 2020; Yoo et al., 2015) and motor imagery (mental movement; Beaudoin et al., 2020), especially when they held negative beliefs about older adults’ motor abilities (as measured by a questionnaire assessing participants’ beliefs about the physical characteristics of people aged between 20 and 90 in terms of strength, balance, walking speed and flexibility) (Beaudoin et al., 2020). This suggests that mental representations of aging may be associated with fictional perceptions of aging effects on motor performance. In the same way that embodying an older adult avatar in virtual reality modifies the motor performance of younger adults, the wearer’s knowledge that wearing the suit has an aging effect may influence motor performance. However, in contrast to virtual reality scenarios, it is possible to modify the way the aging suit is presented to participants to conceal its aging properties. By comparing the motor performances of younger adults wearing aging suits that were presented to them in different ways, we can study the impact of knowledge about aging on motor performance.

Importantly, researchers have also begun to investigate the effects of the aging suit on younger adults’ cognitive performance, compared with older adults’ actual cognitive performance (Schaefer et al., 2022; Vieweg et al., 2023; Vieweg & Schaefer, 2020). Moutoussamy et al. (2023) recently suggested using this method for research on cognitive aging from an embodied and situated perspective. This perception of cognition suggests that cognition originates in the body and in the interactions between the body and the environment. Thus, the cognitive changes observed in older adults may be linked to their sensorimotor decline. To study this with the help of an aging suit, researchers must ensure that the suit reproduces the motor changes observed in advancing age. In addition, given the important relationships between the environment, the body, and cognition suggested by the embodied and situated approach, it would be interesting to manipulate the environment of younger adults wearing the suit. These possible relationships between body and environment could then inform future studies of cognition.

In the current study, we had three objectives. First, we sought to replicate and extend earlier findings by Vieweg and Schaefer (2020). We expected to observe an increase in the time required to perform the motor tasks when participants wore the suit. Second, our main objective was to explore how changes in the presentation of the aging suit might influence its effects on wearers’ motor performances. We expected that more time would be required to perform the motor tasks when the suit was worn if the instructions given to participants mentioned aging than if the suit was worn when it was presented without mentioning aging. Finally, we sought to examine the influence of the wearers’ physical activity levels on the effects on motor tasks of wearing the aging suit. This factor was not considered in prior studies but had been mentioned as a research limitation by some (Schaefer et al., 2022; Vieweg & Schaefer, 2020). We assumed that higher physical activity level would lessen the effects of the aging suit on motor skills.

Method

Ethical Considerations

The entire study was approved in advance by the Institutional Review Board of Tours University (no. 2021-09-01). All participants provided their informed consent.

Participants

A total of 98 students from Tours University (France) voluntarily engaged in the present study over a two-month experimental period. Participants were randomly divided into two groups: (i) one that received no information that the suit was related to aging, but that were told instead that it was a posture training suit (n = 49); and (ii) a group for whom aging properties of the suit were highlighted (aging suit; n = 49). [Of note, no participants in the posture training suit group indicated any familiarity with the aging suit at the end of the study, verifying that this group was unaware that the suit was being used to simulate the effects of aging on motor performance.] Both groups were further divided, using a median split, into high and low physical activity subgroups, based on their physical activity levels. The median physical activity level for the posture training suit group was 1320; the median physical activity level for the aging suit group was 1455. Participants below the median were classified as having low physical activity, and those above the median were classified as having high physical activity. Participants exactly at the median were excluded from these analyses (n = 2). Participants whose motor response times for any of the four tasks described below differed by more than 2.5 standard deviations (SDs) from the mean were also excluded from the statistical analyses (n = 3). Thus, four groups were compared: the posture training suit group with low physical activity level (n = 22) and high physical activity level (n = 23), and the aging suit group with low physical activity level (n = 24) and high physical activity level (n = 24). All participants reported being in good health: none of them had neurological problems, needed walking aids (e.g., cane, wheelchair), reported motor difficulties related to chronic or acute pain, or experienced dizziness or limb numbness during the experiment.

Materials

Aging Suit

The GERT aging suit (Produkt + Projekt Wolfgang Moll, Niederstotzingen, Germany) was used to reproduce the experience of physical aging for participants who wore the suit. At the sensory level, the GERT suit featured: (a) yellow-tinted glasses to reduce the visual field and induce altered perceptions of colors and contrast difficulties, (b) headphones to limit hearing, and (c) gloves to reduce tactile sensations. At the motoric level, it featured: (a) a cervical collar to reduce head motor skills, (b) elbow and knee pads to restrict mobility and reproduce joint stiffness, (c) wrist weights (1.5 kg per wrist) and ankle weights (2.3 kg per ankle) for loss of strength, impaired coordination and uncertain gait, (d) gloves to restrict hand mobility and decrease agility, (e) overshoes to simulate hesitant gait and loss of balance when walking, and (f) a 10-kg vest to induce spinal curvature, mobility restriction, loss of strength, and impaired sense of balance. To achieve a vest weight representing 10% of each participant’s weight, 250-g weights can be removed if needed. Thus, for the first time in such studies, we modulated age-related challenges in an inter-individual way.

Motor Tasks

We used the Test of Motor Competence (Sigmundsson et al., 2016) to measure participants’ level of motor skill proficiency. This test battery is composed of four tasks (summarized in Figure 1) for which completion times are recorded for two measures of fine motor skills, and two measures of gross motor skills. Each task started with a training session.

Figure 1.

Four Measures of Motor Skills Included in the Test of Motor Competence (as adapted from Sigmundsson et al., 2016).

Concerning fine motor skills, the two tasks included measures of the speed and sureness of the movement, hand-to-hand coordination, and hand-to-eye coordination. The first fine motor task (i.e., placing bricks or PB, Figure 1(A)) required participants to place 18 square Duplo^TM bricks on a board (for 3 × 6 bricks; Lego Group, Billund, Denmark) as quickly as possible. This task was performed with the right hand first, then the left hand. We used the group’s mean completion time (in seconds) for the two hands our measure of interest. The second fine motor task (i.e., building bricks or BB, Figure 1(B)) involved stacking 12 Duplo^TM bricks (Lego Group, Billund, Denmark) on top of each other as quickly as possible. During this task, participants were not allowed to place either hand on the table, and they had to constantly raise the bricks. We recorded the time (in seconds) required to build the tower. The first task assessed the speed and sureness of the hand movements, while the second task focused on the coordination between the two hands to perform a single action. Both tasks also measured hand-to-eye coordination.

Concerning gross motor skills, the two tasks considered dynamic balance skills, mobility and walking maneuvers, speed and safety of movement, and agility. In the first task (i.e., heel-to-toe walking, HTW, Figure 1(C)), participants walked along a straight line (4.5-m long) as fast as possible. They had to walk in tandem gait (i.e., the heel was placed against the toes of the other foot at each step). We recorded the time (in seconds) taken to walk the 4.5-m line. For the second task (i.e., figure-of-eight walking/running or W/R, Figure 1(D)), they had to perform a figure eight walk around two 1-m lines as fast as possible. The first line was one m from the starting point, and the second line was 5.5-m from the starting point. We recorded the time (in seconds) required to complete the figure eight. The first task assessed gait, balance and coordination during a precision task, while the second assessed the ability to accelerate and decelerate in a rapid movement that included changes of direction. Both tasks assessed dynamic balance and agility during controlled movements.

Physical Activity Questionnaire

We used the Historical Leisure Activity Questionnaire (Kriska et al., 1988) to assess participants’ prior physical activity over a typical week. Responses to this self-report questionnaire allowed us to calculate a cumulative index representing: (a) mean energy expenditure in metabolic equivalents (METs) per minute per week (Ainsworth et al., 2000); (b) perceived intensity (light, moderate, vigorous); and (c) duration, and frequency of physical activity. We used the following formula for this calculation:

\sum [M E T s x s e s s i o n d u r a t i o n (i n \min) x f r e q u e n c y d u r i n g t h e w e e k]

Procedure

First, participants completed the inclusion criteria and prior physical activity questionnaires. They then performed the motor tasks twice: once without the aging suit and once with it. Before each motor task, participants performed a training session for which no times were recorded, to ensure that they correctly understood the instructions. They indicated when they were physically ready to perform each task. The conditions were counterbalanced, with half the volunteers starting with the suit, and half starting without it. The aging suit was presented in two different ways, depending on whether the aging aspect was evoked, for the two different participant groups. For the aging suit group, the instruction was as follows: “We are going to fit you with an aging suit, and you will be in the skin of an older adult.” For the posture training suit group, the purpose of the suit was hidden: “We are going to fit you with a suit that trains your posture.”

Statistical Analyses

For purposes of describing our data, we presented means (and standard deviations). We tested data distributions to assure that they met assumptions of normality using a Shapiro-Wilk test, and homogeneity of variance, using Levene’s test. We performed repeated measures analyses of variance (ANOVAs) on each of the four motor measures independently, with Condition (with vs. without suit) as a within-participants factor, and with Group (posture training vs. aging suit) and Physical Activity Level (low vs. high) as between-participants factors. For each statistical analysis, the criterion of statistical significance was set at an alpha of 0.05. Effect sizes for significant effects and interactions were calculated using partial eta squared (η_p²) (Richardson, 2011). Post-hoc analyses were conducted to better understand the nature of any significant interactions. In post-hoc comparisons, we adjusted the alpha level for each post-hoc result using Bonferroni’s corrections (adjusted for comparing a family of 6 estimates), separately for each ANOVA. All analyses were conducted using Jeffreys’s Amazing Statistics Program (JASP, version 0.13.0).

Results

Table 1 shows the participants’ demographic characteristics. Also evident in Table 1 are our findings of not significant differences between participant groups with regard to age, education level, height, and weight. A chi square test (7.62) revealed no significant differences between males and females (p = .06) on these characteristics. The means and standard deviations for each motor task measure, are shown in Table 2.

Table 1.

Participants’ Means (and Standard Deviation) on Demographic Characteristics and Tests of Group Differences on These Variables.

	Posture training group (n = 47)		Aging suit group (n = 48)		F (1,89)
	Low physical activity (n = 22)	High physical activity (n = 23)	Low physical activity (n = 24)	High physical activity (n = 24)	Group(^ns)	Physical activity	Interaction group x physical activity(^ns)
Age in years	20.77 (2.00)	21.61 (2.37)	21.83 (3.19)	21.25 (2.54)	0.43	0.06^ns	1.77
Physical activity	523.52 (409.24)	3769.71 (1761.91)	713.96 (509.16)	3267.29 (363.87)	0.33	115.19^***	1.64
Education level in years	13.14 (1.61)	13.35 (1.82)	13.54 (1.93)	13.21 (1.79)	0.13	0.03^ns	0.53
Height in cm	168.41 (9.18)	170.52 (10.16)	167.83 (6.16)	165.79 (8.29)	2.24	0.00^ns	1.37
Weight in kg	63.41 (11.40)	63.57 (13.48)	62.25 (10.10)	60.25 (9.58)	0.93	0.16^ns	0.22
Number of women	17	10	18	17

Note. ns: non-significant; ***: p < .001.

Table 2.

Participants’ Mean (and Standard Deviation) Scores on Motor Tasks by Group (Posture Training vs. Aging Suit), Physical Activity Level (Low vs. High) and Condition (Without vs. With Suit).

	Posture training group (n = 47)				Aging suit group (n = 48)
	Low physical activity (n = 22)		High physical activity (n = 23)		Low physical activity (n = 24)		High physical activity (n = 24)
	Without suit	With suit	Without suit	With suit	Without suit	With suit	Without suit	With suit
Placing bricks (mean for both hands in seconds)	20.94 (1.67)	26.44 (3.46)	19.52 (2.04)	25.01 (3.62)	21.49 (2.57)	26.92 (3.03)	20.81 (2.18)	26.75 (4.40)
Building bricks (in seconds)	11.18 (1.40)	15.01 (3.03)	10.54 (1.43)	13.36 (2.63)	12.17 (2.25)	15.25 (2.47)	11.45 (1.84)	15.19 (3.17)
Heel-to-toe walking (in seconds)	9.86 (2.29)	12.47 (3.20)	8.96 (2.88)	11.05 (3.55)	10.09 (2.73)	13.64 (4.32)	10.00 (2.24)	13.05 (2.99)
Figure-of-eight walking/running (in seconds)	5.70 (0.92)	7.42 (0.99)	5.43 (0.59)	6.91 (0.99)	6.52 (1.76)	9.15 (2.46)	6.12 (1.68)	7.80 (1.79)

Motor Tasks

For the PB task, the analysis indicated a significant effect of Condition, F (1, 90) = 284.87, p < .001, η²_p = .76, confirming that brick placement time increased when the suit was worn. A trend toward significance was found for the main effect of Group, F (1, 90) = 3.76, p = .06, η²_p = .04, indicating that the brick placement time in the posture training suit group approached significance as a shorter time than that of the aging suit group. However, the interaction effect between Condition and Group was not significant, F (1, 90) = 0.09, p = .77. The effect of condition on motor performance was no greater in the aging suit group than in the posture training suit group. Moreover, prior physical activity did not have a significant beneficial effect on motor performance, F (1, 90) = 2.98, p = .09, regardless of the wearing of the suit, F (1, 90) = 0.15, p = .70.

Concerning the BB task, we observed a significant main effect of Condition, F (1, 90) = 174.05, p < .001, η²_p = .66, with a longer block building time when the suit was worn than when it was not worn. Building time also differed significantly according to Group, F (1, 90) = 5.56, p = .02, η²_p = .06, with a shorter time for the posture training suit group than the aging suit group. The interaction effect of condition and group was not significant, F (1, 90) = 0.04, p = .85. Thus, the effect of condition on motor performance was comparable across the aging suit and posture training suit groups. For this task, there were no differences between Physical Activity Levels on building time, F (1, 90) = 3.22, p = .08, and there was no significant interaction effect between Condition and Physical Activity Level, F (1, 90) = 0.09, p = .77, indicating that the benefit of prior Physical Activity Level did not interact with whether the participant wore the suit or not.

Regarding the HTW task, we observed a main effect of Condition, F (1, 90) = 105.14, p < .001, η²_p = .54, with longer walking time when participants wore the aging suit than when they did not wear it. A trend toward significance was observed for Group, F (1, 90) = 3.71, p = .06, η²_p = .04, with a marginally shorter walking time for the posture training suit group than for the aging suit group. The Condition x Group interaction was not significant, F (1, 90) = 3.02, p = .09. Finally, Physical Activity Level did not have a beneficial main effect on participants’ motor performance on this task, F (1, 90) = 1.61, p = .21, and there was no significant interaction effect between Condition and Physical Activity Level, F (1, 90) = 0.84, p = .36.

Finally, for W/R task, there was a significant main effect of Condition, F (1, 90) = 364.74, p < .001, η²_p = .80, with poorer performance when the suit was worn than when not worn. There was also a significant main effect of Group, F (1, 90) = 11.71, p < .001, η²_p = .12, with significantly longer walking/running times for the aging suit group than for the posture training suit group. The Condition x Group interaction was also significant, F (1, 90) = 7.81, p = .006, η²_p = .08 and, interestingly, the post-hoc comparisons indicated that within both groups (posture training and aging suit), wearing the suit significantly reduced motor performance, t(89) = −11.35, p _Bonferroni = < .001; t(89) = −15.74, p _Bonferroni = < .001 respectively. Therefore, while response times between groups were equivalent without the suit, t(89) = 2.38, p _Bonferroni = .11, there was a significant difference when wearing the suit, t(89) = 4.12, p _Bonferroni = < .001. Also, participants in the low physical activity group showed slower walking/running times compared to those in the high physical activity group, F (1, 90) = 4.52, p = .04, η²_p = .05. This beneficial effect from physical activity was different when the suit was worn, as a significant Physical Activity Level x Condition interaction appeared, F (1, 90) = 9.62, p = .003, η²_p = .10. Specifically, both high and low physical activity groups exhibited an increase in motor response times when the suit was worn, t(89) = −11.38, p _Bonferroni = < .001; t(89) = −15.61, p _Bonferroni = < .001 respectively. However, without the suit, both physical activity groups demonstrated equivalent performance, t(89) = 1.06, p _Bonferroni = 1.00. Once participants wore the suit, the response times of the low physical activity group were higher, reflecting poorer performance, t(89) = 2.98, p _Bonferroni = .02.

Discussion

In the present study, we confirmed that wearing an aging suit effectively reduced the motor skills of younger adults, as reflected in their performance on both fine and gross motor tasks, consistent with other prior studies (Gaggioli et al., 2018; Lavallière et al., 2017; Schaefer et al., 2022; Vieweg & Schaefer, 2020). Additionally, we demonstrated that these effects varied according to the way the suit was presented and participants’ levels of prior physical activity – new results that have never been shown before.

The gross motor performance of younger adults wearing the suit varied according to Group (posture training suit vs. aging suit), particularly on the W/R task. More specifically, for this task, the reduction in motor performance associated with wearing the suit was greater when the presentation of the suit referred to aging rather than posture training. By contrast, the reduction in motor performance was the same, regardless of suit instruction, for fine motor tasks (PB and BB). The embodied and situated approach assumes that motor skills and environment (social, cultural, physical) are related factors in determining performance. This means that the effects of the aging suit on motor performance could depend on the environmental information provided. Two main complementary assumptions have emerged from prior literature to explain the effect of the aging suit on motor performance: (a) the suit experience modifies the social environment (as a function of how the suit is presented), and the suit experience modifies the physical environment (as a function of type of motor task).

First, we modified the social environment by highlighting or concealing the aging properties of the suit during its presentation to participants. The Group x Condition interaction observed in the W/R task could be explained by the activation of knowledge about aging, which mostly negative implications for motor skills performance. The negative effects of stereotypes on motor performance have been demonstrated, not only in older adults (Barber et al., 2020; Chiviacowsky et al., 2018; Swift et al., 2012), but also in younger adults placed in a fictional aging situation using virtual reality (Reinhard et al., 2020; Yoo et al., 2015). The impact of the aging suit on motor performance could therefore be associated with internalized negative stereotypes. Future investigators might take this idea further by exploring the effects of negative stereotypes on physical abilities within an aging suit group. We would expect participants with highly negative stereotypes to have poorer motor performance than participants with less negative stereotypes, but only if the suit is presented as an aging tool. Second, we influenced the physical environment with task difficulty of the motor task, such that the Group x Condition interaction was only observed on the W/R task, which can present a risk for balance and falls. Younger adults wearing the aging suit may therefore have adopted conservative strategies (underestimating their performance) to create a margin of safety with regard to balance and the risk of falling (Schaefer et al., 2022). Conversely, the presentation of the suit as being for posture training purposes may have led participants to adopt less conservative strategies. This hypothesis merits further investigation to confirm that the way the aging suit is presented modifies the type of strategy used. For example, Schaefer et al., (2022) proposed using the term challenge suit, which we eschewed in favor of a more neutral one. The challenge label could also lead to changes in strategies, by increasing participants’ motivation to surpass their motor abilities in the task (i.e., as a challenge). Future studies are needed to elucidate this issue, by assessing the relationship between strategies and motor performance on more or less complex tasks performed by groups of volunteers presented with different labels (aging suit for a negative view, posture training suit for a neutral view, and challenge suit for a positive view).

The embodied and situated approach considers not only the links between motor skills and the environment (social, cultural, physical), but also posits that these two domains are closely and bidirectionally related to cognition. In this sense, this approach provides an important theoretical framework for interpreting how aging simulators affect motor performance. It allows us to consider not only the physical and motor effects of simulation but also the cognitive aspects associated with motor tasks, as well as the complex interaction between the individual and their environment. This is especially relevant for the W/R task, as it involves complex motor tasks that also incorporate cognitive components such as planning and navigation abilities (Hess et al., 2010). Specifically, aging suits alter both sensory perception (e.g., proprioception and tactile sensitivity) and motor skills (e.g., coordination and balance). Considering that cognition is not confined solely to the brain but is closely linked to our sensory and motor experiences, these sensory-motor alterations directly influenced how participants perceived and executed motor tasks and may influence cognitive tasks as well. How the aging suit is presented created a specific context wherein participants were or were not aware of simulated aging, and this awareness altered their task perception and problem-solving strategies for motor performance and might alter if for cognitive engagement. Future studies should further explore the relationship between cognition, environment, and motor skills to better understand their interrelated significance.

Regarding our hypotheses for motor skills we assessed, our results supported our prediction that prior physical activity levels of participants would have a beneficial effect on motor performance, but this was only evident for the W/R task, particularly when the aging combination was worn. In fact, the literature shows that physical activity makes it possible to maintain good motor performance despite the physical changes associated with advancing age. Older adults who engage in more physical activity do not have such a steep decline in their motor skills (Buchman et al., 2007). These effects could be particularly pronounced on tasks requiring higher level physical ability, such as the W/R task. Thus, regarding the effects of physical activity on motor performance, depending on whether the aging suit was worn, we suggested two main hypotheses.

First, we predicted that the effect of physical activity level would not differ according to whether participants were wearing the aging suit. During the aging process, physical activity had a beneficial and protective effect on gradually declining motor functions (Buchman et al., 2007), thus limiting the effects of age. The suit, by contrast, diminishes motor performance at a given point in time, and therefore represents the physical aging of the people wearing it according to their current motor skills and in relation to their current physical activity. The effects of the suit are therefore sudden, not gradual. Thus, the beneficial effects of physical activity on motor skills cannot be translated into an interaction, owing to the short timeframe. In the present study, where younger adults were placed in a fictional aging situation through the wearing of a suit for just 15 minutes, there was no interaction between condition and physical activity for three of the four tasks: both fine motor tasks and one of the gross motor tasks (HTW).

Our second hypothesis, however, did not exclude the possibility of prior physical activity level moderating the effects of the suit. First, we can assume that this moderation only occurred for tasks requiring more physical training, such as the W/R task. The latter can be likened to a race, and therefore involves the physical abilities enhanced by most physical activities (e.g., cardiovascular capacity, speed, but also motivational aspects). Furthermore, as previously mentioned, physical activity has a protective role over time for older adults; so, although the aging suit may not be able to reproduce this effect in the short term, it might be able to do so with a longer wearing time. More specifically, the suit wearing modification of motor performance in younger adults might depend on their prior physical activity practice if the suit was worn for a longer period, as this would allow participants to adapt to it. The most active younger adults would presumably be less affected by the aging suit over the long term because of their prior physical activity levels.

Limitations and Directions for Further Research

Although this was not one of the objectives of the present study, it would be interesting to compare the performance we observed in younger adults with those of older adults, to quantify the extent of the suit wearing effect more accurately. One crucial unexamined aspect of suit-wearing, in contrast to the aging process, is that older adults gradually adapt to aging, whereas younger adults wearing suits experience abrupt changes that can significantly disrupt their motor performance. Indeed, we aimed to demonstrate that the suit wearing effects could vary with the combination of personal characteristics (e.g., physical activity level), the suit presentation (posture training vs. aging suit), and task differences, as have been highlighted in various studies (e.g., Schaefer et al., 2022). Knowledge gained from this study about the effects of the suit may inform future investigators’ efforts to validate the use of these suits in a larger study. However, future studies will need to remain vigilant about how well the suit accounts for the individualized variability of aging. For instance, aging does not necessarily affect the entire body, and some suit wears did not experience these changes to the same extent as the simulator might suggest. Similarly, to address this variability, future researchers should focus on understanding how each component of the simulator contributes to the overall effect and how these components can be adjusted to reflect a more personalized aging experience. Furthermore, it will be important for future investigators to study how the impact of different components of the suit may vary from individual to individual and influence the specific contributions of each aspect of the suit on the motor performance of younger adults. Then, although the variety of motor tasks we used was particularly useful for capturing the dynamic aspects of everyday motor skills, norms for these tasks are still underdeveloped and rarely applied in studies of older adults. It might be useful, therefore, to assess the motor changes induced by the aging suit by using classic motor tasks as applied in research on physical aging. Future motor measures might also include more precise assessments of motor abilities by considering accuracy and/or mistakes made to enrich the findings and provide a more nuanced evaluation of the effects of aging on task performance. Lastly, our results indicated near statistical significance, raising the question of whether our sample size was sufficient to detect small effect size differences. This initial study can serve as a foundation for future researchers to estimate the necessary sample size for their investigations.

Conclusion

We affirmed that an aging suit reduced the motor performance of younger adults, and we found that this reduced performance accentuated by the way the suit was presented, with greater declines when aging was explicitly referenced in that presentation. This first finding highlights the importance of knowledge of aging and adaptation of strategy in managing tasks with varying difficulty. In addition, we found that prior physical activity level was an important mediating factor in the effects of suit wearing by younger adults. This finding, particularly, warrants further investigation regarding its precise influence on motor performance during tasks of varying complexity while wearing the suit. This perspective opens several interesting avenues for future research.

Footnotes

Acknowledgments

We sincerely thank Sylvester Bergeron and Antoine Souilijaert for their help in collecting the data.

Author Contributions

Ilona Moutoussamy: conceptualization, methodology, writing - original draft

Kristell Pothier: conceptualization, writing - review and editing

Lucette Toussaint: conceptualization, writing - review and editing

Shaïma Kerroum: methodology, investigation, writing - review and editing

Laurence Taconnat: conceptualization, writing - review and editing.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

ORCID iD

Ilona Moutoussamy

Author Biographies

Ilona Moutoussamy has a PhD in Psychology.

Kristell Pothier is Associate Professor in Psychology.

Lucette Toussaint is a Professor in Sports Science.

Shaïma Kerroum is a student in biology, specializing in neuroscience.

Laurence Taconnat is a Professor in Psychology.

References

AgeLab . (nd). Age gain Now empathy System. [Apparatus and software]. https://agelab.mit.edu/methods/agnes-age-gain-now-empathy-system

Ainsworth

B. E.

Haskell

W. L.

Whitt

M. C.

Irwin

M. L.

Swartz

A. M.

Strath

S. J.

O’Brien

W. L.

Bassett

D. R.

Schmitz

K. H.

Emplaincourt

P. O.

Jacobs

D. R.

Leon

A. S.

(2000). Compendium of physical activities: An update of activity codes and MET intensities. Medicine & Science in Sports & Exercise, 32(9 Suppl), S498–S504. https://doi.org/10.1097/00005768-200009001-00009

Barber

S. J.

Hamel

Ketcham

Lui

Taylor-Ketcham

(2020). The effects of stereotype threat on older adults’ walking performance as a function of task difficulty and resource evaluations. Psychology and Aging, 35(2), 250–266. https://doi.org/10.1037/pag0000440

Beaudoin

Barra

Dupraz

Mollier-Sabet

Guerraz

(2020). The impact of embodying an “elderly” body avatar on motor imagery. Experimental Brain Research, 238(6), 1467–1478. https://doi.org/10.1007/s00221-020-05828-5

Bowden

Wilson

Traynor

Chang

(2020). Exploring the use of ageing simulation to enable nurses to gain insight into what it is like to be an older person. Journal of Clinical Nursing, 29(23-24), 4561–4572. https://doi.org/10.1111/jocn.15484

Buchman

Boyle

Wilson

Bienias

J. L.

Bennett

(2007). Physical activity and motor decline in older persons. Muscle & Nerve, 35(3), 354–362. https://doi.org/10.1002/mus.20702

Cheng

W. L.-S.

P. K.

Lam

Y. Y.

K. C.

Ling

T. K.

Yau

W. H.

Chui

Y. W.

Tsui

H. M.

P. P.

(2020). Effects of senior simulation suit programme on nursing students' attitudes towards older adults: A randomized controlled trial. Nurse Education Today, 88, Article 104330. https://doi.org/10.1016/j.nedt.2020.104330

Chiviacowsky

Cardozo

P. L.

Chalabaev

(2018). Age stereotypes’ effects on motor learning in older adults: The impact may not be immediate, but instead delayed. Psychology of Sport and Exercise, 36, 209–212. https://doi.org/10.1016/j.psychsport.2018.02.012

Eymard

A. S.

Crawford

B. D.

Keller

T. M.

(2010). “Take a walk in my Shoes”: Nursing students take a walk in older adults’ shoes to increase knowledge and empathy. Geriatric Nursing, 31(2), 137–141. https://doi.org/10.1016/j.gerinurse.2010.02.008

10.

Frison

A.-K.

Aigner

Wintersberger

Riener

(2018). Who is generation A? Investigating the experience of automated driving for different age groups. In Proceedings of the 10th International Conference on Automotive user Interfaces and interactive Vehicular Applications, Toronto (Canada), Sept. 25, 2018 (pp. 94–104). https://doi.org/10.1145/3239060.3239087

11.

Gaggioli

Settimi

Cipresso

Pedroli

Stramba-Badiale

Riva

(2018). Using an aging simulator suit for modeling visuo-motor limitations of elderly users interacting with a mobile application: Feasibility study. In Cipresso

Serino

Ostrovsky

Baker

J. T.

(Eds.), Pervasive computing paradigms for mental health (253, pp. 24–33). Springer International Publishing. https://doi.org/10.1007/978-3-030-01093-5_4

12.

Groza

H. L.

Sebesi

S. B.

Mandru

D. S.

(2017). Age simulation suits for training, research and development. International Conference on Advancements of Medicine and Health Care through Technology, 12–15 October 2016, Cluj-Napoca, Romania (59, pp. 77–80). Springer International Publishing. https://doi.org/10.1007/978-3-319-52875-5_17

13.

Hess

R. J.

Brach

J. S.

Piva

S. R.

VanSwearingen

J. M.

(2010). Walking skill can be assessed in older adults: Validity of the Figure-of-8 Walk Test. Physical Therapy, 90(1), 89–99. https://doi.org/10.2522/ptj.20080121

14.

Hsu

H.-C.

Lee

C. Y.

Lee

C. H.

(2016). Effects of aging simulation program on nurses’ attitudes and willingness toward elder care. Taiwan Geriatrics & Gerontology, 11(2), 105–115.

15.

Jeong

Kwon

(2021). Long-term effects of an aging suit experience on nursing college students. Nurse Education in Practice, 50, Article 102923. https://doi.org/10.1016/j.nepr.2020.102923

16.

Kriska

A. M.

Sandler

R. B.

Cauley

J. A.

Laporte

R. E.

Hom

D. L.

Pambianco

(1988). The assessment of historical physical activity and its relation to adult bone parameters. American Journal of Epidemiology, 127(5), 1053–1063. https://doi.org/10.1093/oxfordjournals.aje.a114881

17.

Lafayette Instrument . (2015). Purdue pegboard model 32020A. [Apparatus and software]. https://www.lafayetteinstrument.com/

18.

Lauenroth

Schulze

Ioannidis

Simm

Schwesig

(2017). Effect of an age simulation suit on younger adults’ gait performance compared to older adults’ normal gait. Research in Gerontological Nursing, 10(5), 227–233. https://doi.org/10.3928/19404921-20170831-04

19.

Laurentius

Quandel

Bollheimer

L. C.

Leonhardt

Ngo

Lüken

(2022). Spatiotemporal gait parameters in young individuals wearing an age simulation suit compared to healthy older individuals. European Review of Aging and Physical Activity, 19(1), 29. https://doi.org/10.1186/s11556-022-00298-w

20.

Lavallière

D’Ambrosio

Gennis

Burstein

Godfrey

K. M.

Waerstad

Puleo

R. M.

Lauenroth

Coughlin

J. F.

(2017). Walking a mile in another’s shoes: The impact of wearing an age suit. Gerontology & Geriatrics Education, 38(2), 171–187. https://doi.org/10.1080/02701960.2015.1079706

21.

Lee

S. W. H.

Teh

P.-L.

(2020). “Suiting up” to enhance empathy toward aging: A randomized controlled study. Frontiers in Public Health, 8, 376. https://doi.org/10.3389/fpubh.2020.00376

22.

Lego . (nd). Duplo bricks and 3 × 6 bricks board. [Apparatus and software]. https://www.lego.com/

23.

Moll . (nd). GERonTologic simulator. [Apparatus and software]. https://www.age-simulation-suit.com/geriatric-simulator.html

24.

Moutoussamy

Taconnat

Villatte

Toussaint

Pothier

(2023). Étudier le vieillissement mnésique d’un point de vue incarné: réflexions sur l’apport des simulateurs de vieillissement. [Studying memory aging from an embodied point of view: Reflections on the contribution of aging suits]. L’Année psychologique [Topics in Cognitive Psychology], 123(4), 641–671. https://doi.org/10.3917/anpsy1.234.0641

25.

Ono

Iwayama

Tanaka

Ashida

Komasa

(2017). Learning effects of aging simulationbased training Analysis using text mining. Journal of Osaka Dental University, 51(2), 5. https://doi.org/10.18905/jodu.51.2_131

26.

Reinhard

Shah

K. G.

Faust-Christmann

C. A.

Lachmann

(2020). Acting your avatar’s age: Effects of virtual reality avatar embodiment on real life walking speed. Media Psychology, 23(2), 293–315. https://doi.org/10.1080/15213269.2019.1598435

27.

Richardson

J. T. E.

(2011). Eta squared and partial eta squared as measures of effect size in educational research. Educational Research Review, 6(2), 135–147. https://doi.org/10.1016/j.edurev.2010.12.001

28.

Rikli

Jones

(1999). Development and validation of a functional fitness test for community-residing older adults. Journal of Aging and Physical Activity, 7(2), 129–161. https://doi.org/10.1123/japa.7.2.129

29.

Sari

Taskiran

Baysal

Acar

Cevik Akyil

(2020). Effect of an aged simulation suit on nursing students’ attitudes and empathy. European Geriatric Medicine, 11(4), 667–675. https://doi.org/10.1007/s41999-020-00316-z

30.

Schaefer

Bill

Hoor

Vieweg

(2022). The influence of age and age simulation on task-difficulty choices in motor tasks. Neuropsychology and Cognition, 30(3), 429–454. https://doi.org/10.1080/13825585.2022.2043232

31.

Scherf

(2014). Entwicklung, Herstellung und Evaluation des Modularen Alterssimulationsanzugs eXtra (MAX). Universitätsverlag Chemnitz.

32.

Schmidt

L. I.

Schlomann

Gerhardy

Wahl

H.-W.

(2022). Aging means to me… that I feel lonely more often”? An experimental study on the effects of age simulation regarding views on aging. Frontiers in Psychology, 13, Article 806233. https://doi.org/10.3389/fpsyg.2022.806233

33.

Sigmundsson

Lorås

Haga

(2016). Assessment of motor competence across the life span: Aspects of reliability and validity of a new test battery. Sage Open, 6(1), Article 215824401663327. https://doi.org/10.1177/2158244016633273

34.

Swift

H. J.

Lamont

R. A.

Abrams

(2012). Are they half as strong as they used to be? An experiment testing whether age-related social comparisons impair older people’s hand grip strength and persistence. BMJ Open, 2(3), Article e001064. https://doi.org/10.1136/bmjopen-2012-001064

35.

Taşoz

Ş. M.

Afacan

(2022). Simulated physical ageing: A prioritized persona-based model for accessible interiors in senior housing environments. Indoor and Built Environment, 31(8), 2115–2133. https://doi.org/10.1177/1420326X20952817

36.

Tiffin

Asher

E. J.

(1948). The Purdue pegboard; norms and studies of reliability and validity. Journal of Applied Psychology, 32(3), 234–247. https://doi.org/10.1037/h0061266

37.

Tullo

E. S. C.

Spencer

Allan

(2010). Systematic review: Helping the young to understand the old. Teaching interventions in geriatrics to improve the knowledge, skills, and attitudes of undergraduate medical students. Journal of the American Geriatrics Society, 58(10), 1987–1993. https://doi.org/10.1111/j.1532-5415.2010.03072.x

38.

Vauclair

C.-M.

Borges Rodrigues

Marques

Esteves

C. S.

Cunha

Gerardo

(2018). Doddering but dear … even in the eyes of young children? Age stereotyping and prejudice in childhood and adolescence. International Journal of Psychology, 53(Suppl 1), 63–70. https://doi.org/10.1002/ijop.12430

39.

Vieweg

Panzer

Schaefer

(2023). Effects of age simulation and age on motor sequence learning: Interaction of age-related cognitive and motor decline. Human Movement Science, 87, Article 103025. https://doi.org/10.1016/j.humov.2022.103025

40.

Vieweg

Schaefer

(2020). How an age simulation suit affects motor and cognitive performance and self-perception in younger adults. Experimental Aging Research, 46(4), 273–290. https://doi.org/10.1080/0361073X.2020.1766299

41.

Watkins

C. A.

Higham

Gilfoyle

Townley

Hunter

(2021). Age suit simulation replicates in healthy young adults the functional challenges to balance experienced by older adults: An observational study. BMJ Simulation and Technology Enhanced Learning, 7(6), 581–585. https://doi.org/10.1136/bmjstel-2021-000867

42.

World Health Organization . (2022). Ageing and health. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health

43.

Yoo

S.-C.

Peña

J. F.

Drumwright

M. E.

(2015). Virtual shopping and unconscious persuasion: The priming effects of avatar age and consumers’ age discrimination on purchasing and prosocial behaviors. Computers in Human Behavior, 48, 62–71. https://doi.org/10.1016/j.chb.2015.01.042

44.

Zijlstra

Hagedoorn

Krijnen

W. P.

van der Schans

C. P.

Mobach

M. P.

(2016). Route complexity and simulated physical ageing negatively influence wayfinding. Applied Ergonomics, 56, 62–67. https://doi.org/10.1016/j.apergo.2016.03.009