New Hick's law based reaction test App reveals “information processing speed” better identifies high falls risk older people than “simple reaction time”
Introduction
The world is facing a major challenge on population aging and falls present a substantial health problem among the older population (Kim and Robinson, 2005, Yu et al., 2013; Choi et al., 2016, Dueñas et al., 2016). Many studies have been conducted to identify at-risk individuals and to diagnose underlying risk factors of falls for proactive fall prevention (Rodriguez et al., 1995, Lajoie and Gallagher, 2004, Chippendale and Boltz, 2015, Davis et al., 2015; Qiu and Xiong, 2015; Rantz et al., 2015, Dueñas et al., 2016, Kim and Xiong, 2016).
To maintain human balance and prevent falls, central nervous system (CNS) integrates the inputs from sensory systems (vision, vestibular and somatosensory systems) and responds as adjusting muscles and joints to achieve balance (Winter, 1995, Horak, 2006). Slow or inappropriate reactions of CNS could induce poor central integrative mechanisms responsible for the reconfiguration of the postural set and delay the responses of muscles and joints, and result in falls, especially for the critical situations of sudden motion of base of support (BOS) such as slips, trips and missteps (Horak et al. 1997). Prior studies have widely used reaction time measures to assess human cognitive abilities such as information processing and executive functions (Camicioli et al., 1997, Lord and Fitzpatrick, 2001). Increased simple reaction time (SRT), choice reaction time (CRT), and choice stepping reaction time (CSRT) were reported as significant risk factors for falls of older people (Lord and Clark, 1996, Lord and Fitzpatrick, 2001, Tijsma et al., 2016). However, some researchers (Jensen and Munro, 1979, Mahurin and Pirozzolo, 1993, Lord and Fitzpatrick, 2001) argued that reaction time may fail to measure the information processing efficiently since it contains not only the time of perception and information processing but also motor planning time. Most tests involved motor functions to respond to the stimulus, such as SRT task using the hand to press a switch as the response to a light stimulus (Lord and Clark 1996), and original CSRT task involving the balance of the whole body to step on the illuminated panel as the response. As a result, longer reaction time may result from worse motor functions due to weak muscular strengths or other motor deficits. Therefore, reaction time alone in these tasks could be inadequate to assess human performance of information processing. In some latter versions of CSRT tasks, total stepping time was divided into foot lift-off response time and transfer time (St George et al. 2007). Both foot lift-off response time and transfer time were found to be significantly different between high-risk and low-risk of falls in older people. Ejupi et al. (2016) recently developed Kinect-based choice reaching and stepping reaction time tests for assessment of fall risk in older people. Algorithms were used to extract features for reaction, movement and the total time from Microsoft Kinect skeleton data, therefore, the total choice reaching and stepping time can be further separated into reaction time and movement time.
Taking into account limitations of the direct use of reaction time, Mahurin and Pirozzolo (1993) applied Hick's law to examine the age-related neurological cognitive dysfunction in people with Alzheimer and Parkinson diseases. Hick's law, which is also referred to as the Hick-Hyman law, describes the relationship between reaction time and task complexity (Hick, 1952, Hyman, 1953). The law states that human reaction time increases linearly with the logarithm of the number of equi-probable alternatives. In the study of Mahurin and Pirozzolo (1993), they used a timed card-sorting task and derived information processing speeds from the linear function based on Hick's law. They reported that Parkinson and Alzheimer patients showed significantly slower information processing speeds compared with healthy controls. However, to the best of our knowledge, no study has been conducted on applying Hick's law to measure information processing speed for assessing the risk of falls in older people. In addition, some recent studies showed that new methods which are easy-to-administer, cost-effective and can enable the older individuals to perform regular fall risk self-assessments at home are needed (Howcroft et al., 2013, Ejupi et al., 2016).
The present study attempts to develop a reaction test App based on Hick's law for assessing cognitive function related fall risks in older people. The effectiveness of the developed App on age related differences and classifying older people with and without a history of falls were investigated through an experimental study on a sample of one hundred Korean women. The developed reaction test App is expected to have good potential for elderly fall risk assessment in clinical settings and regular self-assessments at home, which can significantly lower barriers to reassessment.
The rest of the article is organized as follows. After an introduction of the development of a reaction test App in section 2, section 3 describes a preliminary experiment that was undertaken to check the convergent validity of outcome measures from the developed App. Section 4 presents a main experiment on investigating the effectiveness of the developed App for assessing cognitive function related fall risks, which is followed by an overall discussion and conclusion in section 5 and section 6 respectively.
Section snippets
Design and working mechanism of App
We have developed an App for iPad Mini using an iOS Apple language-Swift (Apple Inc.) that allows a user to perform the following four different reaction tests (Fig. 1) in the Hick paradigm. Those four reaction tests are in line with the traditional card-sorting tasks (Mahurin and Pirozzolo 1993).
- (1)
One-choice reaction test: At the beginning of the test, the card is facing down by showing the back side of the card with a brick pattern in card display box (upper section of the screen). During the
Aim
The major purpose of this preliminary experiment is to examine the convergent validity of two outcome measures (simple reaction time and information processing speed) from the newly developed reaction test App. The developed App can't be used for our main experiment on fall risk assessment (Experiment 2 in section 4) until it has been verified.
Methodology
An experiment was conducted with 27 college students (Age:) to validate the developed App against two commonly used reaction time tests: simple
4.1 Aim
The aim of this main experiment is to investigate the effectiveness of the developed App on age related differences and classifying older people with and without a history of falls.
4.2.1 Participants
One hundred Korean women consisting of twenty young controls, forty community-dwelling older nonfallers and forty matched older fallers (Table 1), participated in the experiment. The young controls were college students recruited from Ulsan National Institute of Science and Technology, a public university in the city
Overall discussion
In this study, a Hick's law based reaction test App was developed for the purpose of assessing cognitive function related fall risks in older people. The convergent validity and the effectiveness of two outcome measures (simple reaction time and information processing speed) from App were examined through experimental studies. To the best of our knowledge, this is the first study that utilizes a developed reaction test App to empirically measure simple reaction time and information processing
6. Conclusion
We have designed and developed the software for a reaction test based on Hick's law. The test tasks are simple and quick to administer within a few minutes. The test can be run as an App and its effectiveness on assessing age related differences and fall risks in the older population has been demonstrated through an experimental study with a sample of one hundred Korean women. Experimental results showed that the reaction test App is not only sensitive to age related differences, but also fall
Conflict-of-interest statement
The authors declared no conflict of interest.
Acknowledgements
This study was funded by Basic Science Research Program through the National Research Foundation of Korea (NRF 2011-0022185; NRF 2014R1A1A2056193). The authors would like to thank Taekyoung Kim, Woojoo Kim and Xiaoqun Yu for his assistance with experimental data acquisition. The strong support from Ulsan Elderly Welfare Center on this study is also appreciated.
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