INTRODUCTION

1. The Effects of Frustration and Novelty during Internet Use • on Heart Rate and Heart Rate Variability Michelle A. Patriquin, Michael M. Knepp, B.S., Anthony O. Wells, M.S.., Angela Scarpa,PhD, Bruce H. Friedman, PhD INTRODUCTION RESULTS METHODOLOGY • The U.S. Census Bureau (2005) found that college-aged adults (18-24 years) were the most likely of any age group to use computers (75%) and the internet (71%). • Research has shown a positive relationship between the expectation of immediate information and higher frustration/stress levels in human-computer interaction (Timmel, et al., 2003; Scheirer, 2002; Ramsay, et al. 1998). • The current study assessed whether higher internet use would increase expectations for immediate information and subsequent frustration levels when expectations were not met. • Primary Hypothesis: • As download time increased, heart rate (HR) would also increase and heart rate variability (HRV) would decrease, as a reflection of autonomic state. • These HR and HRV relationships would be most pronounced in students who reported high levels of internet use. • Compared the difference in means (derived from the entire baseline and task periods) between baseline and task for HR and HRV within each group, using paired t-tests. • A paired t-test found that HR increased from baseline to task for all groups except for the low internet use, slow download condition. All results are as follows: • High/Fast t(12)=-2.319 p<.04 • High/Slow t(17)=-3.775 p<.005 • Low/Fast t(10)=-4.343 p<.005 • Low/Slow t(12)=-1.398 p=.187 • A paired t-test found a significant decrease in HRV from baseline to task for the high/slow condition and a trend for the low/fast condition. All the results are as follows: • High/Fast t(12)=.492 p=.632 • High/Slow t(17)=3.153 p<.006 • Low/Fast t(10)=1.952 p<.08 • Low/Slow t(12)=1.568 p=.143 • After being placed in high and low internet use groups, students were randomly assigned to fast and slow download conditions. This created four groups: • Webpage download times determined by the researcher are listed below. • Duplicated from a similar computer task used by Ramsay et al. (1998), websites were delayed by a Firefox extension, used with Mozilla Firefox version 1.5.0.6. • Subjects had to participate in an online scavenger hunt searching for specified items on the following websites: vt.edu, weather.com, facebook.com, cheaptickets.com, google.com, and youtube.com. • Baseline HR and HRV was recorded during the video Powaqqatsi: Life in Transformation by Godfrey Reggio validated by Vella and Friedman, (in press). • HR and HRV were measured using the ambulatory monitoring system and the Polar S810i Heart Rate Monitor. • HR and HRV were assed using mean HR and HRV for the entire baseline and task periods. SUBJECTS • Phase I: 397 undergraduates participated in an online survey. • The selection tool used was the Internet Use Questionnaire (Campbell, 2006). From this high and low internet use groups were determined. • Phase II: 55 participants (male=17, female=38) aged 18-23 (M= 19.38, SD= 1.31), were selected from the screening. • A power analysis was conducted for this study, finding that groups must include between 12 to 15 subjects or between 48 to 60 total subjects for adequate power to detect a medium effect. CONCLUSIONS • The unexpected significant increase in HR for the low internet use/fast download condition could be an indicator of novelty for this group who did not posses the confidence, knowledge, or skills to keep up with the fast webpage download condition. • The significant increase in HR and decrease in HRV for the high internet use/slow download condition could be an indicator of this group becoming frustrated with the slow download times. Virginia Tech Psychology Department Presented at the 2007 GSA Research Symposium