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As people get older they are slow to react to things because there is a difference in how much their perception and motor skills hinder their ability to process or respond. However, expertise and mastery contribute to maintaining manual skills into older age. In this aspect, the mastery of a task can play a more important role in reaction time than age. An example of this would be reaction time in a computer-simulated test might be slower in a younger individual who is less computer savvy than an older computer engineer. A study was conducted testing the hypothesis that students 33 years of age and older have a slower reaction time than students that are younger than 33 years of age when given a reaction time simulation task. The grounds for this hypothesis was based on several studies showing behavioral slowing in older adults has been demonstrated in a number of different reaction time tasks but the causes of age-related reaction time are not clearly defined.

Literature Review

Becic, E., Kramer, A. F., & Boot, W. R. (2007). Age-related differences in visual search in dynamic displays. Psychology and aging, 22(1), 67–74. doi:10.1037/0882- 7974.22.1.67

The first study deals with “Age-related differences in visual search in dynamic displays” (Becic, & Boot, 2007) the experiment tracked and compared eye movement between adults and children and concluded that these tests are one way to determine how one person filters visual information compared to another. The differences in age performance were separated into categories of the type of eye movements (e.g. ‘active scanners’).Their goal was to present a stimulus that was not to make it more reflective of real world stimuli. Older and younger adults viewed displays containing numerous moving objects and were asked to respond when a new object was added to the display. Accuracy, response times, and eye movements were recorded. In relation to the younger and older participants, the number of eye movements accounted for a large proportion of variance in transient detection performance. Participants who actively searched for the change performed significantly worse than did participants who employed a passive or covert scan strategy, indicating that passive scanning may be a beneficial strategy in certain dynamic environments. The results of this study support that the decision making or “searching” aspect of the reaction time played a factor as well as age. The hypothesis that the younger group will react faster is not based on age alone but a combination of all of these principles.

Dykiert, D., Der, G., Starr, J. M., & Deary, I. J. (2012). Age differences in intra-individual variability in simple and choice reaction time: systematic review and meta-analysis. PloS one, 7(10), e45759. doi:10.1371/journal.pone.0045759

The second study was titled “Age differences in intra-individual variability in simple and choice reaction time: systematic review and meta-analysis” (Dykiert, Der, Starr, & Deary 2012). Older adults (60+ years) had greater reaction time than younger (20–39) and middle-aged (40–59) adults. Age effects were larger in choice reaction time tasks than in simple ones. Effect sizes were larger for the comparisons between older and younger adults than between older and middle-aged adults, indicating that the age-related increases in reaction time are not limited to old age. The difference between old and young groups was larger than that between old and middle-aged groups, suggesting that increase in reaction time is not limited to old age, but occurs already in mid-adulthood. However, the fact that age gradually plays a factor in reaction time at a steady rate is enough evidence to base a hypothesis that that younger group will have a faster reaction time in our study.

Fujiyama, H., Tandonnet, C., & Summers, J. J. (2011). Age-related differences in corticospinal excitability during a Go/NoGo task. Psychophysiology, 48(10), 1448– 55. doi:10.1111/j.1469-8986.2011.01201.x

On researching the third source titled “Age-related differences in cortico-spinal excitability” (Fujiyama, Tandonnet, & Summers, 2011) it was helpful in showing that the type of processing of stimuli is the same with both age groups, and the effect of having instruction and preparation before a task has on response time. This goes into the expertise and mastery factor that was also the basis for our hypothesis. Younger adults had shorter reaction times and a larger increase in cortico-spinal excitability at response generation period than older adults. Although behavioral slowing in older adults has been demonstrated in a number of different reaction time tasks the particular mechanisms underlying age-related reaction time delays are poorly understood (pg.1448) Younger adults were significantly faster in responding than older adults. The age-related effect on reaction time was predominantly evident in central premotor time rather than in peripheral neuromuscular processes motor time.

Jennings, J. R., Mendelson, D. N., Redfern, M. S., & Nebes, R. D. (2011). Detecting age differences in resistance to perceptual and motor interference. Experimental aging research, 37(2), 179–97. doi:10.1080/0361073X.2011.554512

In the study “Detecting age differences in resistance to perceptual and motor interference” (Jennings, et al, 2011) it was concluded that there is a definite distinction in change of response times with different age groups focusing on the relationship between perceptual inhibition and motor inhibition. As people get older we are slower to react to things because there is a difference in how much our perception and motor skills hinder our ability to process or respond. Ninety-eight individuals participating in studies of balance and attention were separated into younger (mean age 25 years) and older (mean age 73) participants. Older participants showed less perceptual and motor inhibition compared to younger participants, with moderation of this effect by gender, that is, motor inhibition appeared to decline more sharply with age in women than in men. This study also gives basis for our hypothesis and brings another factor of gender combined with age being a factor as well.

Ratcliff, R. (2008). Modeling aging effects on two-choice tasks: response signal and response time data. Psychology and aging, 23(4), 900–16. doi:10.1037/a0013930

The study “Modeling aging effects on two-choice tasks: response signal and response time data” (Ratcliff, 2008) provides an additional model for experimenting with motor responses, both in terms of time accuracy and signal efficacy. This study provided results from different age groups. In the response signal task, the primary reason for a slower rise in the response signal functions for older participants was variability in the non-decision component of processing. Variations in criterion settings can also interact with task difficulty, with some participants showing large reaction time differences across levels of difficulty and other participants showing smaller differences. This factor also justifies the expertise and mastery aspect for the basis of the hypothesis. The understanding of the simulated test given to our students may have had a different degree of difficulty for video game players than book readers. However, video gaming may be more a quality of less than 33 years compared to those aged 33 and above, which is the reason for the assumed faster reaction time of the younger group.

Taware, G. B., Bhutkar, M. V, Bhutkar, P. M., Doijad, V. P., & Surdi, A. D. (2012). Effect of Age on Audio-Visual and Whole Body Reaction Time. The American Journal of Medical Sciences, 5(1), 90–94.

In the study “Effect of Age on Audio-Visual and Whole Body Reaction Time” (Taware, et al, 2012), involving an audio component the conclusion was that response times for older people were longer. It was found that audiovisual reaction time, whole body reaction time increases as the age advances and delayed average audio-visual, and whole body reaction time is significantly different among different age groups. Effect of ageing on the myelination of neurons may be the possible cause for this observation.

Group Age (yrs.) Sample size were as follows:

Group I – 20-29 30; Group II – 30-39 30; Group III – 40-49 30; Group IV – 50-59 30

In younger age groups (Group I and II) there was rapid initiation and quick completion of action, effectively the whole body reaction time was less in younger age groups as compared to the older age groups. (pg. 92) the average audio-visual reaction time increases as the age advances. This studied gives raw proof that reaction time slows with age also supporting our hypothesis.

Wiegand, I., Finke, K., Müller, H. J., & Töllner, T. (2013). Event-related potentials dissociate perceptual from response-related age effects in visual search. Neurobiology of aging, 34(3), 973–85. doi:10.1016/j.neurobiolaging.2012.08.002

A further study entitled “Event-related potentials dissociate perceptual from response-related age effects in visual search” (Wiegand, et al, 2013). Shows that attention decline plays a major role in cognitive changes with aging. This study combined response time measures with lateralized event-related potentials of younger and older adults performing a compound-search task, in which the target-defining dimension of a pop-out target (color/shape) and the response-critical target feature (vertical/horizontal stripes) varied independently across trials. Slower responses in older participants were associated with age differences in all analyzed event-related potentials from perception to response, indicating that behavioral slowing originates from multiple stages within the information-processing stream. This studied concludes that with age comes slower reaction time due to physiological stages also supporting our hypothesis.

Vieluf, S., Mahmoodi, J., Godde, B., Reuter, E.-M., & Voelcker-Rehage, C. (2012). The influence of age and work-related expertise on fine motor control. GeroPsych: The Journal of Gerontopsychology and Geriatric Psychiatry, 25(4), 199–206. doi:10.1024/1662-9647/a000071

In the final study entitled “The influence of age and work-related expertise on fine motor control” (Vieluf, et al, 2012), forty-eight right-handed novices and experts (35 to 65 years) performed submaximal precision grip force modulation tasks with index or middle finger opposing the thumb, either with the right hand or the left hand. Novices revealed expected age-related differences in all performance measures whereas experts outperformed novices in all outcome measures. Expertise seems to contribute to maintaining manual skills into older age, as indicated by the age and expertise interaction for the force initialization. Generally, it is proposed that extensive and deliberate practice helps develop a specific expertise over time, leading to stable and outstanding performance. This study could place the most balancing or misbalancing factor on reaction time decreasing with age. Expertise, practice, athleticism, etc. can and has a role in reaction time. Therefore, in considering our hypothesis of the younger group being faster we considered other factors as well. The under 33 group is not predicted as faster purely on age alone.

Conclusion

In similar studies, results were larger for the comparisons between older and younger adults than between older and middle-aged adults, indicating that the age-related increases in reaction time are not limited to old age. The average audio-visual reaction time increases as the age advances and attention decline plays a major role in cognitive changes with aging. The studies in the literature show there is a definite distinction in change of response times with different age groups. In one study, the younger age groups were found to have rapid initiation and quick completion of action showing that younger groups may tend to act more impulsively than the older age groups. However, which specific aspects of attention contribute to this decline is yet to be understood.

The questions remaining are what specific features have the highest level of influence on age and reaction time Is this a statistically predictable theory or does underlying factors such as expertise or decision making play more major roles. In conclusion, the specific aspects of age contribute to decline in reaction time is little understood. The questions remaining are what specific features have the highest level of influence on age and reaction time. Many people question whether age alone a statistically predictable theory or underlying factors such as expertise or decision making play more major roles. As we get older individuals are slower to react to things because of perception and motor skills slowing their ability to process or respond. However, more research is needed involving what aspects of age causes this deterioration in reaction time. Research is needed to compare the significance of expertise, preparation, and thought processing to the variable of age as all these factors may vary according to individual.

References

Becic, E., Kramer, A. F., & Boot, W. R. (2007). Age-related differences in visual search in dynamic displays. Psychology and aging, 22(1), 67–74. doi:10.1037/0882-7974.22.1.67

Ratcliff, R. (2008). Modeling aging effects on two-choice tasks: response signal and response time data. Psychology and aging, 23(4), 900–16. doi:10.1037/a0013930

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