Abstract
When interpreting other people's movements or actions, observers may not only rely on the visual cues available in the observed movement, but they may also be able to “put themselves in the other person's shoes” by engaging brain systems involved in both “mentalizing” and motor simulation. The ageing process brings changes in both perceptual and motor abilities, yet little is known about how these changes may affect the ability to accurately interpret other people's actions. Here we investigated the effect of ageing on the ability to discriminate the weight of objects based on the movements of actors lifting these objects. Stimuli consisted of videos of an actor lifting a small box weighing 0.05–0.9 kg or a large box weighting 3–18 kg. In a four-alternative forced-choice task, younger and older participants reported the perceived weight of the box in each video. Overall, older participants were less sensitive than younger participants in discriminating the perceived weight of lifted boxes, an effect that was especially pronounced in the small box condition. Weight discrimination performance was better for the large box compared to the small box in both groups, due to greater saliency of the visual cues in this condition. These results suggest that older adults may require more salient visual cues to interpret the actions of others accurately. We discuss the potential contribution of age-related changes in visual and motor function on the observed effects and suggest that older adults' decline in the sensitivity to subtle visual cues may lead to greater reliance on visual analysis of the observed scene and its semantic context.
Introduction
Imagine being in a coffee shop and looking at a cup placed on a counter. The cup is completely opaque and you do not know whether it is full or empty. Now imagine your friend reaching for and lifting the cup to move it to another table. By observing the strength of their grip and the speed of their movement, you can immediately deduce that the cup is full, even though you still cannot see what is inside it. What's more, you can also deduce whether they knew that the cup was full or incorrectly expected it to be empty. As such, observing the actions of others involves a form of experience sharing (Brown and Brüne, ; Limanowski and Blankenburg, ), from which we can derive meaningful information about the agent's intentions and expectations as well as the characteristics of the object acted upon. This information can in turn inform our own interactions with the environment.
Our ability to understand the actions of others (action understanding or action interpretation) is likely mediated by multiple levels of analysis (Grafton and Hamilton, ; Thioux et al., ), including deducing how an action is performed (e.g., with the hand or with the full body), what the action is (e.g., lifting a cup) and why it is occurring (e.g., to refill the cup because it is empty) (Thioux et al., ). The ageing process is accompanied by perceptual and physical changes that may impact the ability to interpret others' actions at these multiple levels of analysis. However, to date, the relationship between ageing, action perception, and judgment of object properties remains relatively unexplored. In younger adults, it has been suggested that the spatiotemporal information derived from action observation engages internal motor simulation of the observed action (Gallese et al., ; Knoblich and Sebanz, ) and that action understanding and action execution have a shared coding system (Gallese et al., ; Knoblich and Sebanz, ), as they have been shown to involve overlapping brain regions (Gallese et al., ; Rizzolatti et al., ). These shared systems may afford our understanding of actions toward objects (Buccino et al., ; Hamilton et al., ; Ramsey and Hamilton, ), as well as intransitive actions such as walking or dancing (Buccino et al., ; Calvo-Merino et al., ). Although such mechanisms may inform our understanding of how and what actions are performed, it has been suggested that when people infer the unobservable aspects of the action, such as why the action is being performed, they engage an extended network beyond the sensorimotor system to support such “mentalizing” or “theory of mind” processing (Spunt et al., ). Other studies have suggested a role for the motor system in conjunction with other brain networks typically involved in theory of mind processing for action interpretation (De Lange et al., ; Ramsey and Hamilton, ; see also Keysers and Gazzola, ).
Motor engagement in action observation is largely modulated by the motor repertoire of the observer (Calvo-Merino et al., ). Evidence from healthy and patient populations suggests that spatial awareness of our own and others' body positions (Marzoli et al., , ) and sensations arising from our body contribute to interpreting the actions of others (Hamilton et al., ; Bosbach et al., ; Ní Choisdealbha et al., ). For example, when Hamilton et al. () asked participants to judge the weight of a box lifted by an agent while concurrently lifting a box themselves, they noted that the weight of the physically lifted box directly affected perceptual weight judgments. Participants judged the box being lifted by the agent to be heavier when they were physically lifting a light box, and vice versa. In a follow-up study, Hamilton et al. () showed that the magnitude of the bias induced by the motor system on perceptual weight judgments was associated with activation of a specific cluster of visual and motor regions in the brain, leading the authors to suggest that the perceptual and motor systems are not distinct, but interact and influence each other at various levels.
The ageing process is accompanied by declines in motor abilities across a range of tasks. For example, older adults demonstrate differential velocity profiles, decreased fluidity, and increased variability in simple action execution (Cooke et al., ; Seidler et al., , for review, see Seidler et al., ). The ability to imitate and replicate more complex movement sequences is also negatively affected by ageing (Maryott and Sekuler, ; Caçola et al., ). Older adults also show declines in the ability to judge the position of their body in space and appear to rely on additional sensory information, largely vision, to compensate for their decline in proprioception (Seidler-Dobrin and Stelmach, ; Romero et al., ; Barrett et al., ). Moreover, Diersch et al. () demonstrated that when online visual information is interrupted, older adults show deficits in predicting the correct time course of action sequences. This indicates that the ability to mentally represent and predict action sequences declines with ageing (see also Saimpont et al., ; Gabbard et al., ; Diersch et al., ). Thus, declines in motor ability with ageing, together with changes in internal forward models of action representation (Diersch et al., ), may lead older adults to become more reliant on visual analysis of observed action sequences for action interpretation and inference on object properties. Interestingly, Poliakoff et al. () observed that patients with Parkinson's disease can still perform perceptual weight judgments, however, they may rely more on visual analysis due to declines in the motor system (Poliakoff et al., ; Poliakoff, ). Thus, while embodied simulation may in part underlie action perception, when we cannot put ourselves “in other people's shoes” through simulation, or when this is not useful to action perception, visual analysis may support action understanding (Brady et al., ). Yet, little is known as to how motor changes in non-pathological ageing may affect the interpretation of other people's actions and whether a similar visual strategy may be engaged with advancing age.
Although action execution and action interpretation appear to interact, it is also important to note that they may not bear a direct correspondence. For example, Hamilton et al. () demonstrated that the most reliable physical cues as to the weight of a lifted item do not correspond to the perceptual cues that individuals use when making a weight judgment. Auvray et al. () observed similar discrepancies and suggest that individuals do not engage an “exact copy” of action execution when making perceptual judgments, but rather exploit the most diagnostic visual cues, such as acceleration. Indeed, motion cues such as velocity and acceleration can be used to determine the weight of lifted objects even when visual information is only provided by moving point light displays (Shim and Carlton, ). Moreover, the embodied nature of forward models has been questioned, as it has been suggested that motor activation may relate less to “mirroring” or directly matching the actions of others, but rather to anticipating future compatible actions (Csibra, ). It has also been suggested that action understanding may be achieved through visual analysis alone without the need for direct embodied simulation (for review, see Giese and Poggio, ). This is largely related to our direct visual experience of naturally occurring sequences. The changes that we encounter in action sequences in a natural environment are gradual and are governed by natural laws. Through our constant exposure to naturally occurring sequences, our perceptual system can learn to predict the continuation and outcomes of observed actions (Giese and Poggio, ; Perrett et al., ). Indeed the spatial and temporal constraints observed in naturally occurring sequences can have a direct effect on our ability to encode (Wallis, ; Wallis and Bülthoff, ) and, in turn, anticipate the sequence outcome (Perrett et al., ). Such visual analysis abilities may be compromised in older adults.
Ageing is associated with deterioration in visual motion perception. For example, older adults are less accurate than younger adults at processing information in biological motion displays (Billino et al., ; Pilz et al., ; Insch et al., ; Legault et al., ), suggesting that their ability to process motion cues relevant to action may be impaired. However, age-related declines in motion perception are not limited to biological motion, as other forms of motion perception are also vulnerable to the ageing process (Billino et al., ). Older adults are less sensitive at detecting and discriminating the direction of motion in random-dot patterns, a class of stimuli commonly used to address the mechanisms underpinning motion perception (Snowden and Kavanagh, ; Bennett et al., ; Roudaia et al., ; Hutchinson et al., ). Older adults are also less sensitive to changes in the speed of moving stimuli (Scialfa et al., ; Snowden and Kavanagh, ). Thus, age-related declines in visual motion perception may limit older adults' ability to perform visual analysis of observed actions and therefore potentially negatively affect action perception in older adults.
In sum, healthy ageing is accompanied by declines in the ability to perform fine motor movements and declines in visual motion perception, both of which may compromise older adults' ability to interpret other people's actions accurately, either through a reduced ability to extract relevant cues from visual observation and/or through reduced internal simulation of observed actions. In the present study, we examined whether ageing may impact on action understanding by examining the ability of younger and older adults to derive information about the weight of an object, based on the movements of an actor lifting the object. This task is likely to engage aspects of action understanding pertaining to how the action is performed (e.g., lifting the box with the hand or with full body motion; the grip and speed of the movements), and what the action is (e.g., lifting a small or a large box). It is a naturalistic task with which both younger and older adults have direct experience in everyday life and it is known to provide a reliable measure of sensitivity to interpret the actions of others (Hamilton et al., ). Furthermore, the task has been shown to engage both the perceptual and motor systems of the observer (Hamilton et al., , ; Poliakoff et al., ). Stimuli consisted of a series of videos showing lifting actions of a small box with light weights and a large box with heavy weights. Small box lifts displayed upper limb motion that engaged the forearm and hand and large box lifts displayed the full body motion of the actor lifting the box from the floor. An additional set of videos contained motions that showed the lifting actions of an actor who was told incorrect information about the weight they were about to lift. This deceptive information altered the actors' movement profile, resulting in exaggerated motion that may provide greater visual cues to support weight judgment. The manipulations of box weight category and the actors' movement profile allows for exploration of the relative contribution of visual cues and motor engagement in perceptual weight judgment performance in ageing. For example, although the weights lifted in the large box condition can challenge the ageing motor system via simulation, the perceptual cues pertaining to the weight lifted may be more salient in this condition than in the small box condition (Bosbach et al., ). We also collected self-report measures of motor ability (Potter et al., ) in the older adult group to assess how perceived motor ability may be related to their capacity to interpret lifting actions.
Materials and methods
Participants
Seventeen younger adults (all female) aged 21-28 years (mean age = 24.6 years; SD = 1.9 years) and 19 community-dwelling older adults, recruited through an active choral society (18 female) took part in this study. Participation was voluntary and individuals did not receive monetary compensation for their time. Data from two older participants were excluded from the analysis reported below: data from one male participant was removed to maintain consistently with the all-female sample in the younger group and data from one female participant were removed because the participant did not understand the task. The remaining 17 older adults were aged 68-84 years (mean age = 74 years; SD = 4.4 years). All younger and older participants reported to be right hand dominant and all reported normal or corrected to normal vision. All participants wore their usual corrective lenses, if needed, at the time of testing. All participants were not suffering from psychiatric or neurological illness by self-report and all provided written informed consent. Our younger and older samples were not strictly matched for years of education, however, older adults had secondary level education or higher and younger adults were college students. The experiments reported here were approved by the St. James Hospital Ethics Committee and conformed to the Declaration of Helsinki.
Stimuli and apparatus
Video stimuli
Stimuli were made available by the authors of Bosbach et al. (). Stimuli consisted of 8 videos of a male actor lifting a small box and 8 videos of a female actor lifting a large box. The small box videos displayed the right arm and hand of the actor lifting the small box from a table and putting it on a small shelf. The large box videos displayed the full body of the actor lifting a large box from the floor. In all videos, the external features of the box remained constant, but the weight of the box varied (see Figure 1). The small box weighed 50, 300, 600, or 900 g. and the large box weighted 3, 6, 12, or 18 kg. For both the small and large boxes, four non-deceptive videos showed the actor lifting the box after being told correct information about the weight of the box and four deceptive videos showed the actor lifting the box after being told incorrect information about the weight of the box (e.g., lighter than the true weight of the box). All videos showed the actor and the box from the side-view. Each video was approximately 4 s in length and was displayed at a rate of 25 frames per second. Participants viewed the videos at a distance of 60 cm and the images in the videos subtended a visual angle of approximately 14° horizontally and 11° vertically. The experiment was driven by Presentation® software and was presented on a Sony Vaio PC laptop with a 14 inch LCD screen.
Figure 1
Perceived motor-efficacy scale for older adults
All older adult participants completed a subset of 19 items taken from the Perceived Motor-Efficacy Scale for Older Adults (Potter et al.,
Procedure
For the computer-based experiment, participants were seated at a distance of approximately 60 cm from the screen. They were instructed that they would view a number of videos of a person lifting either a small or a large box and that following each video presentation they would be asked to estimate the weight of the box the actor lifted by choosing one of four weight options shown onscreen (50, 300, 600, 900 g. for small boxes and 3, 6, 12, 18 kg. for large boxes). Participants were told that one option was always correct. Participants were offered the choice to view weight options in ounces and pounds and a number of the older adult sample opted for this option. On each trial, the video was presented for 4 s, which was then followed immediately by the response screen. Older participants responded verbally and the experimenter entered their responses by pressing the corresponding button on the keyboard. Younger adults responded by pressing the appropriate button themselves. In all cases, the button press immediately initiated the beginning of the next video. The experiment was presented in four blocks: two blocks contained only non-deceptive videos and two blocks contained both non-deceptive and deceptive videos. The blocks containing only non-deceptive videos were always shown first, however, the order of the small and large box blocks was counterbalanced across participants. In the non-deceptive blocks, each of the four weights was repeated 3 times in random order. In the deceptive blocks, each weight was repeated once in the deceptive and once in the non-deceptive form. Each block was preceded by two practice trials to familiarize the participants with the task. Excluding practice trials, the computer task comprised of 40 trials in total, 24 trials in the non-deceptive blocks and 16 trials in the deceptive block and was approximately 10 min in duration. Following the computer based task, older adult participants completed the questionnaire comprised of the 19 selected items from the Perceived Motor Efficacy Scale for Older Adults (Potter et al.,
Analysis
Data for non-deceptive videos were analyzed using the mean weight estimates, as well as signal-detection measures of sensitivity (d′) and response bias (c) (Macmillian and Creelman,
d′ scores for discriminating between each pair of adjacent weights were calculated for each participant according to the standard procedure for one-dimensional classification experiments (Macmillian and Creelman,
Due to the limited number of deceptive trials, it was impossible to calculate d′ and c measures for this condition, therefore, data were analyzed by obtaining the slope and intercept of the best-fit line to the weight estimates for the small and large box condition separately.
Whereas the mean weight estimates, and the fitted regression lines, are contaminated with participants' response bias, the d′ measure represents an unbiased estimate of the participant's sensitivity for discriminating the weights (Macmillian and Creelman,
Slope and intercept values of the linear regression fits, and d′ scores were analyzed using separate 2 × 2 mixed-design analyses of variance (ANOVA) with Age (older and younger) as the between-subjects factor and Box Type (small or large) as the within-subjects factor. c scores across Age and Box Type were tested against zero using one sample t-tests.
Results
Non-deceptive trials
Figure 2 shows the group average mean weight estimates of younger and older participants for non-deceptive videos in the small and large box conditions, as well as individual subjects' regression line fits. The 2 (Age) × 2 (Box Type) ANOVA on slope values revealed a significant main effect of Age [F(1, 32) =8.56, p = 0.006], as slopes were shallower in the older group (mean = 0.36) compared to the younger group (mean = 0.57). There was also a significant main effect of Box Type [F(1, 32) = 6.43, p = 0.02], with shallower slopes in the small box (mean = 0.39) compared to the large box (mean = 0.53) conditions (see Figure 3). There was no significant Age x Box Type interaction [F(1, 32) < 1]. The 2 (Age) × 2 (Box Type) ANOVA on intercept values revealed significant main effects of Age [F(1, 32) = 5.32, p = 0.03], with higher intercepts in the older group compared to the younger group. The main effect of Box Type was also significant [F(1, 32) = 71.33, p < 0.001], as intercepts in the large box were higher than in the small box. The Age × Box Type interaction was also significant [F(1, 32) = 4.4, p = 0.04]. Tests of simple main effects revealed a significant effect of Age for the small box [F(1, 32) = 4.47, p = 0.04; mean younger = 0.13, mean older = 0.25] and the large box [F(1, 32) = 4.86, p = 0.03; mean younger = 3.78, mean older = 6.31] conditions (see Figure 3). Thus, older participants showed overall shallower slopes and higher intercepts for both small and large box conditions.
Figure 2

Linear regression fits to the group average (bold line) and individual (dashed line) perceptual weight estimates for younger (black) and older (red) participants in the small box (upper panel) and large box (lower panel) conditions.
Figure 3

Mean slopes (left) and intercepts (right) of fitted regression lines for younger (gray) and older (red) participants in the small box (top) and large box (bottom) conditions. Error bars represent the standard error of the mean.
Sensitivity d′ analysis
Figure 4 (left) shows the mean sensitivity(d′) scores for younger and older participants in the small and large box conditions. Higher d′ scores represent better discrimination ability. As can be seen in the figure, older participants showed overall poorer sensitivity for discriminating weights than younger participants, especially in the small box condition. A 2 (Age) × 2 (Box Type) ANOVA on d′ scores revealed a significant main effect of Age [F(1, 32) = 18.61, p < 0.001], with younger participants showing overall higher d′ scores than older participants. The main effect of Box Type was also significant [F(1, 32) = 5.61, p < 0.001], with overall higher d′ scores in the large box compared to the small box condition. The Age × Box Type interaction was also significant [F(1, 32) = 4.55, p = 0.04], indicating that the effect of Age depended on the type of box. To decompose the interaction, simple main effects of Age were analyzed for the small and large box separately. Analyses revealed that older participants showed significantly lower d′ scores in the small box condition [F(1, 32) = 18, p < 0.001; younger mean = 2.92, older mean = 0.7], but there was no significant difference between d′ scores in the two groups in the large box condition [F(1, 32) = 2.5, p = 0.12] (see Figure 4). Thus, older participants showed poorer sensitivity than younger participants for discriminating weights in the small box condition, but showed similar performance to younger participants in the large box condition.
Figure 4

Mean d′ (left) and bias (right) measures for perceptual weight discrimination performance in younger (gray) and older (red) participants across the small and large box conditions. Error bars represent the standard error of the mean.
Bias analysis
Figure 4 (right) shows the mean response bias (c) scores for younger and older participants in the small and large box conditions. Positive c scores indicate participants' bias for using the upper end of the weight scale (higher weight estimations), negative c scores indicate participants' bias to respond at the lower end of the scale (lower weight estimations), and c scores near zero indicate no response bias for either end of the scale. To test for the presence of response bias, c scores were compared against zero across the small and the large box condition in the younger and older adult groups. In the small box condition, younger participants showed a significant negative bias, with c scores being significantly different from zero [t(16) = −3.46, p = 0.003], however, older participants showed no significant bias, as c scores did not differ from zero [t(16) = −1.55, p = 0.14]. In the large box condition, the pattern was reversed, such that older participants showed a significant positive bias [t(16) = 2.46, p = 0.03], while younger participants showed no response bias, as their c scores did not differ from zero [t(16) = −0.02, p = 0.1]. Thus, younger participants preferred to use the lower end of the weight scale in the small box condition only, while older participants preferred to use the upper end of the weight scale in the large box condition only (see Figure 4).
Deceptive trials
Linear regression was performed on each individual participant data set for the deceptive trials in order to calculate a slope and an intercept value for the small and the large box condition. Slope and intercept values were analyzed separately using a 2 × 2 mixed design analysis of variance (ANOVA), with Age (younger or older) as the between subjects factor and Box Type (small or large) as the within subjects factor. For the slope analysis, no significant main effects of Age [F(1, 32) = 2.05, p = 0.17]; or Box Type [F(1, 32) < 1] were observed. There was no significant interaction between Age and Box Type [F(1, 32) < 1]. For the intercept analysis there was no significant effect of Age [F(1, 32) = 2.78, p = 0.1]. There was a significant main effect of Box Type [F(1, 32) = 96.9, p < 0.001], with lower intercept values for the small box condition. However, there was no evidence for a significant interaction between Age and Box Type [F(1, 32) = 2.44, p = 0.13].
Perceived motor-efficacy scale for older adults scores
Table 1 shows the average scores from the Perceived Motor-Efficacy Scale broken down into five subscales validated by Potter and colleagues (Potter et al.,
Table 1
| N17 (Older adults) | ||
|---|---|---|
| Potter subscales | Item numbers | Mean score (SD) |
| Perceived motor ability in the face of ageing | 7; 16; 27; 3; 4 | 6.11 (2.28) |
| Perceived ability to perform precise movements | 9; 14; 19; 32; 11 | 7.51 (2.58) |
| Perceived motor ability in demanding contexts | 37; 15; 23; 24; 33 | 5.49 (2.52) |
| Perceived manual ability culturally specific | 10; 38 | 9.26 (0.87) |
| Confidence indicator | 12; 21 | 3.38 (2.25) |
Mean scores (standard deviations) for each Perceived Motor-Efficacy subscale administered.
Discussion and conclusion
Older age brings a number of physical and perceptual changes that can potentially impact older adults' ability to understand other people's actions and the characteristics of the objects acted upon. However, little is known about the effects of ageing on action perception. The present study aimed to fill this gap by using a previously-established paradigm involving weight judgment of objects lifted by an actor (Shim and Carlton,
One previous study of perceptual weight judgment in Parkinson's disease (PD) patients found that only PD patients showed evidence of poor performance, while younger controls and healthy age-matched controls did not show a significant difference in weight estimation performance (Poliakoff et al.,
Visual cues in action perception
As noted earlier, perceptual weight judgments involve visual analysis of the observed scene and changes in the velocity of movements provide strong diagnostic criteria for accurately deducing the weight of a lifted object (Shim and Carlton,
Consistent with previous studies, perceptual weight sensitivity was greater in the large box compared to the small box condition (Bosbach et al.,
In light of a decline in motor ability, it is possible that older adults may become more dependent on visual analysis of the observed action sequence. Indeed, previous findings suggest that individuals with proprioceptive (Bosbach et al.,
In line with our study, previous research involving action perception in older adults has reported a decline in the ability to mentally represent or simulate actions. Older adults show a decline in the ability to accurately predict the timing of perceived actions, possibly due to a difficulty in building internal forward models, especially when visual cues are not always available (Diersch et al.,
Motor simulation in action perception
Although older adults' performance may be modulated to a greater extent than younger adults by the saliency of the visual cues, age-related changes in motor ability may also underlie task performance. Specifically, older adults' difficulty in discriminating between the weights of lifted objects in the small box condition parallels behavioral evidence of marked changes in simple motor behavior (e.g., Romero et al.,
We also observed a systematic bias in weight estimation, which may be reflective of the motor system of the observer. Specifically, older adults tended to report that all weights were toward the upper end of the weight scale in the large box condition, but not the small box condition, while younger adults showed a bias to report lighter weights in the small box condition and showed no bias in the large box condition. We can speculate that some form of motor simulation was recruited, as older participants would be expected to experience more difficulty lifting heavier weights, whereas younger participants should be more confident in their abilities with all weights. Interestingly we also observed that older adults' subjective judgment about their action-related skills was reflected in task performance. Specifically, accuracy performance (slope) in the deceptive small box condition correlated positively with older adults' perceived manual ability to use small tools and perform actions related to the use of the hands. Weight estimation in the large box condition was also related to older adults' perceived confidence in movement. Specifically, those who reported being more cautious in carrying out movements, i.e., perceived their own movements to be slower than usual and monitored them more, tended to have better performance in the large box condition than those with higher confidence indicator scores, a score that has been linked previously to physical motor performance (Potter et al.,
Conclusion and future directions
The current findings advance our understanding of how action perception is affected by the ageing process. Our results strongly suggest that we become increasingly reliant on robust visual cues to interpret the actions of others with advancing age. One possible consequence of this change is that older adults may be compromised in detecting subtle differences between motion profiles in action sequences, which may carry information about the intention of the actor. For example, a recent study showed that older adults were less sensitive to differences in the timing of interactions between two human characters (Roudaia et al.,
Although the role of visual cues appears to be a plausible account for the present findings, similar to younger adult studies (e.g., Hamilton et al.,
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Statements
Acknowledgments
We would like to thank Simone Schütz-Bosbach for providing us with the videos used in the present work. Support funding was provided by The Irish Longitudinal Study on Ageing (TILDA).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Appendix
Subset of items taken from the Perceived Motor-Efficacy Scale. Underlined items are reverse scored.
3. I usually do not attempt complex movements because I find it difficult to perform them well
4. I rarely avoid certain movements in case I fall
7. I do not feel more anxious than I used to when carrying out certain movements
9. I am not very good at activities involving precise manual movements
10. I am likely to have some difficulty using a knife and fork
11. I feel confident at adjusting movements to improve their accuracy or efficiency
12. I do not have to monitor, or keep an eye on my movements, more than I used to
14. I feel I am good at activities involving hand-to-eye coordination, such as catching a ball
15. I believe I would have no problems running for a bus if I had to
16. I rarely worry about climbing up or down stairs
19. I expect to be able to shift smoothly from one movement to another
21. I feel that my movements are slower than they used to be
23. If I were to trip-up, I am confident that I could prevent myself from falling to the ground
24. I am likely to have difficulty walking to the top of a large flight of stairs
27. I expect to be able to learn new movements within a short time
32. I consider myself to be good at activities requiring the precise timing of actions
33. I am confident in my ability to walk a long distance without any difficulties
37. I am not likely to have difficulties getting about outside in the wind
38. I believe I can easily perform the actions required when using kitchen or bathroom taps
Summary
Keywords
action perception, motion perception, visuomotor, sensorimotor, embodied cognition, motor simulation, weight judgment, aging
Citation
Maguinness C, Setti A, Roudaia E and Kenny RA (2013) Does that look heavy to you? Perceived weight judgment in lifting actions in younger and older adults. Front. Hum. Neurosci. 7:795. doi: 10.3389/fnhum.2013.00795
Received
12 July 2013
Accepted
31 October 2013
Published
25 November 2013
Volume
7 - 2013
Edited by
Antonia Hamilton, University of Nottingham, UK
Reviewed by
Simone Schütz-Bosbach, Max Planck Institute for Human Cognitive and Brain Sciences, Germany; Richard Ramsey, Bangor University, UK
Copyright
© 2013 Maguinness, Setti, Roudaia and Kenny.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Annalisa Setti, The Irish Longitudinal Study on Ageing, School of Psychology, Lincoln Gate, Trinity College Dublin, Dublin 2, Ireland e-mail: asetti@tcd.ie
This article was submitted to the journal Frontiers in Human Neuroscience.
Disclaimer
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