This poster is based on the research on destractions and gait which was conducted during Kinesiology labs at Drake University in the Fall of 2010. It was presented at DUCURS in 2011.

1. Effects of Mental Math, Texting, and Talking on Gait Megan A. Lynch 1,  , Jackie D. Matsunaga 2,  , Elizabeth M. Pace 1,  , David S. Senchina 2 1 Health Sciences Program and 2 Biology Department, Drake University, Des Moines, Iowa 50311.  These authors are contributing equally to the presentation of the poster. ABSTRACT: BACKGROUND: Gait is normally an automatic process, however when distractions are added, automaticity may be compromised. Since laws have been made outlawing cell phone usage while driving, it can be concluded that distractions are potentially hazardous. PURPOSE: To study how gait is affected by simultaneously texting or talking on a cell phone or doing mental math. HYPOTHESIS: The various distractions will decrease step length and stride length and increase time and number of steps. METHODS: Time, number of steps, step length, stride length, and anthros were collected in twelve adults while walking and texting, talking, or doing mental math. These results were analyzed using univariate ANOVA. RESULTS: Texting, talking, and doing mental math did not significantly affect gait. However, walking undistracted elicited the longest step and stride lengths, least number of steps, and shortest length of time within the fixed distance; by contrast, texting had opposite effects. CONCLUSIONS: Although data values for each distraction clearly differed from normal gait, there were not enough subjects to conclude statistical significance. A 2003 study of dual-task productivity found that both young and old adults were able to maintain their walking rates while continuously talking (Kemper et al, 2003). The present study adds more distractions and measures more aspects of gait. A 2005 study found changes in gait and backward counting while dual-tasking. This proves that certain aspects of walking are attention demanding. A decrease in stride velocity, an increase in stride time variability, and no change in stride velocity were observed (Beauchet et al, 2005). The present study increases the level of difficulty of the mental math distraction. A 2008 study found that walking while performing an attention demanding task (enumerating animal names), resulted in a significant change in gait by decreasing stride velocity and increasing stride time, but no significant change was found in stride length (Dubost et al, 2008). The present study uses more relevant distractions. The purpose of this study was to determine how gait is affected by simultaneously texting or talking on a cell phone or doing mental math. This study builds on previous work by relating it to modern distractions experienced by younger generations, specifically college students. It was hypothesized that the various distractions would decrease step length and stride length, while increasing time and number of steps. INTRODUCTION & HYPOTHESIS: MATERIALS & METHODS: Procedures: Anthropometrics were collected. A moleskin pad was attached to the ball of each of the subjects’ shoes. The moleskin pads were colored with green and black dry erase markers. Each subject walked across three 7m sheets of paper signifying three trials. The moleskin pads left a trail of steps across the paper, which were circled and later measured. Normal walking was performed first, then repeated three additional times for the distractions of talking on the phone, texting, and mental math in randomized order. Data: Time, number of steps, step length, stride length, and anthros were collected and analyzed using univariate ANOVA. IRB approved:2009-100091 Subjects: Age: 23.42 ± 8.5 Gender: 6 females, 6 males Height: 174.0cm ± 10.6 Weight: 73.6 kg ± 16.0 Supplies: Kraft paper sheets (7 m length), painter’s tape, moleskin pads (approx. 2 cm 2 ), dry erase markers, physician’s scale, measuring tape, stopwatch, cell phone, meter stick, Microsoft Excel, SPSS Environment: Drake University Olin Hall, room 453 and west 4 th floor hallway Figure 3: Average time (seconds) taken to walk across the paper undistracted (5.7  0.8), doing mental math (7.3  0.9), texting (7.6  0.9), and talking (6.2  0.9). There was no difference in time taken between trials (p=0.48). Figure 4: Average number of steps taken to walk across the paper undistracted (9.6  0.3), doing mental math (10.0  0.3), texting (10.7  0.3), and talking (10.0  0.3). There was no difference in number of steps between trials (p=0.239). Figure 1: Average step length (cm) taken to walk across the paper undistracted (81.2  5.3), doing mental math (76.7  5.4), texting (70.8  5.4), and talking (74.4  5.8). There was no difference in step length across trials (p=0.738). Figure 2: Average stride length (cm) taken to walk across the paper undistracted (143.5  8.3), doing mental math (138.2  8.5), texting (129.3  8.5), and talking (135.8  9.2). There was no difference in stride length between trials (p=0.751). Walking undistracted was determined to produced the longest step land stride length (Figures 1 & 2), least number of steps (Figure 4), and shortest length of time (Figure 3). This is due to the automaticity of gait. Conversely, texting elicited the shortest step and stride length (Figures 1 & 2), most number of steps (Figure 4), and longest length of time (Figure 3) due to the mental complexity needed to perform this task. The relationships between measured parameters makes sense. Since step length is a component of stride length, it is expected both would increase or decrease together. When step length and stride length decrease, a greater number of steps is needed to cover the same distance. Since time is inversely related to step length and stride length, it is expected time would have an inverse relationship to the others. These results support all aspects of the initial hypothesis. Results of this study are important because they support the basis for recent legislature against usage of mobile devices while driving. They also could be used as evidence to support future laws against distractions while walking in potentially hazardous locations, such as construction sites. The benefits to society are that we have an improved understanding of how distractions influence gait parameters. Shortcomings of this study include small sample size, small length of Kraft paper, limited technology, placement of moleskin, and marking. Future studies could include the effect of different types of shoes on gait (high heels, flip flops, clogs, boots, barefoot, etc), or different weather conditions such as snow, rain, fog, wind, etc. REFERENCES: Beauchet, O., Dubost, V., Herrmann , F.R., & Kressig , R.W. (2005). Stride-to- stride variability while backward counting among healthy young adults. Journal of NeuroEngineering and Rehabilitation , 2 (26). Dubost, V., Annweiler, C., Aminian, K., Najafi, B., Herrmann, F., & Beauchet, O. (2008). Stride-to-stride variability while enumerating animal names among healthy young adults: result of stride velocity or effect of attention-demanding task? Gait & Posture , 27 , 138-143. Kemper, S, Herman, R,.E., Lian, C.H.T. (2003). The cost of doing two things at once for young and older adults: talking while walking, finger tapping, and ignoring speech or noise. Psychology and Aging , 18 (2), 181-192. As shown in Figure 1 the average step length was longest when undistracted (81.2  5.3 cm) and shortest when texting (70.8  5.4 cm); however, the variations by trial were not significantly different from each other (p=0.738). Figure 2 demonstrates the average stride length was longest when undistracted (143.5  8.3 cm), and shortest when texting (129.3  8.5 cm); however, comparisons were not significantly difference from each other (p=0.751). The average time taken to walk across the paper was shortest for undistracted (5.7  0.8 sec) and longest for texting (7.6  0.9 sec) are shown in Figure 3. A p- value of 0.48 indicated there was not a significant difference across conditons. Figure 4 displays the average number of steps taken to walk across the paper was least when undistracted (9.6  0.3) and most when texting (10.7  10.3); however, there was no difference statistically between trials (p=0.239). RESULTS: DISCUSSION & CONCLUSIONS: