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|Title: ||Measuring Emotional Responses to Interaction: Evaluation of Sliders and Physiological Reactions|
|Authors: ||Lottridge, Danielle|
|Advisor: ||Chignell, Mark|
|Department: ||Mechanical and Industrial Engineering|
|Issue Date: ||18-Feb-2011|
|Abstract: ||Recent work has proposed sliders as a useful way to measure self-reported emotion continuously. My dissertation extends this work to ask: what are relevant properties of affective self-report on sliders and variations? How reliable are affective self-reports? How do they relate to physiological data? What are individual and cultural differences? How can this method be applied to ehealth?
Three emotion self-report tools (one-slider, two-slider, a touchscreen) were developed and evaluated in four experiments. The first experiment was within-subjects. Participants viewed short videos, with four self-report conditions (including no reporting) and physiological capture (heart rate variability and skin conductance). In a re-rating task, the sliders models were found to be more reliable than the touchscreen (Lottridge & Chignell, 2009a).
The second and third experiments were between-subjects, and examined individual and cultural differences. Canadian and Japanese participants watched a nature video, while rating emotions and answering questions. Analyses were carried out within and across the datasets. Larger operation span displayed a minor benefit. Valence and arousal ratings were not strongly related to skin conductance. The Japanese performed on par with Canadians but reported worse performance.
Based on the results, the recommendation was made that a single slider be used to rate valence, that arousal be estimated with skin conductance, and that slider psychometrics be used to assess cognitive load over time.
In the fourth experiment, diabetic participants watched Diabetes-related videos. They clustered into usage patterns: some moved the slider very little during videos and more afterward, some hardly moved the slider, and some used it as expected.
Two novel metrics facilitated these analyses: Emotional Bandwidth, an application of information entropy that characterizes the granularity of the self reports (Lottridge & Chignell, 2009b) and Emotional Majority Agreement, the amount of agreement relative to a sample’s self-reports (Lottridge & Chignell, 2009c).
In summary, this dissertation contributes a method of measuring emotion through sliders and skin conductance that has been evaluated in a number of experimental studies. It contributes the empirical results, design recommendations, and two novel metrics of emotional response. Limitations and implications for future research and practice are also discussed.|
|Appears in Collections:||Doctoral|
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