Wearable ESM
© 2016 ACM. The Experience Sampling Method is widely used for collecting self-report responses from people in natural settings. While most traditional approaches rely on using a phone to trigger prompts and record information, wearable devices now offer new opportunities that may improve this method...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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ACM
2021
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| Online Access: | https://hdl.handle.net/1721.1/137012 |
| _version_ | 1811089205728641024 |
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| author | Hernandez, Javier McDuff, Daniel Infante, Christian Maes, Pattie Quigley, Karen Picard, Rosalind W. |
| author2 | Massachusetts Institute of Technology. Media Laboratory |
| author_facet | Massachusetts Institute of Technology. Media Laboratory Hernandez, Javier McDuff, Daniel Infante, Christian Maes, Pattie Quigley, Karen Picard, Rosalind W. |
| author_sort | Hernandez, Javier |
| collection | MIT |
| description | © 2016 ACM. The Experience Sampling Method is widely used for collecting self-report responses from people in natural settings. While most traditional approaches rely on using a phone to trigger prompts and record information, wearable devices now offer new opportunities that may improve this method. This research quantitatively and qualitatively studies the experience sampling process on head-worn and wrist-worn wearable devices, and compares them to the traditional "smartphone in the pocket." To enable this work, we designed and implemented a custom application to provide similar prompts across the three types of devices and evaluated it with 15 individuals for five days (75 days total), in the context of real-life stress measurement. We found significant differences in response times across devices, and captured tradeoffs in interaction types, screen size, and device familiarity that can affect both users' experience and the reports made by users. |
| first_indexed | 2024-09-23T14:15:31Z |
| format | Article |
| id | mit-1721.1/137012 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T14:15:31Z |
| publishDate | 2021 |
| publisher | ACM |
| record_format | dspace |
| spelling | mit-1721.1/1370122024-08-09T21:36:46Z Wearable ESM differences in the experience sampling method across wearable devices Hernandez, Javier McDuff, Daniel Infante, Christian Maes, Pattie Quigley, Karen Picard, Rosalind W. Massachusetts Institute of Technology. Media Laboratory © 2016 ACM. The Experience Sampling Method is widely used for collecting self-report responses from people in natural settings. While most traditional approaches rely on using a phone to trigger prompts and record information, wearable devices now offer new opportunities that may improve this method. This research quantitatively and qualitatively studies the experience sampling process on head-worn and wrist-worn wearable devices, and compares them to the traditional "smartphone in the pocket." To enable this work, we designed and implemented a custom application to provide similar prompts across the three types of devices and evaluated it with 15 individuals for five days (75 days total), in the context of real-life stress measurement. We found significant differences in response times across devices, and captured tradeoffs in interaction types, screen size, and device familiarity that can affect both users' experience and the reports made by users. 2021-11-01T17:55:50Z 2021-11-01T17:55:50Z 2016-09-06 2019-07-24T14:49:48Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137012 Hernandez, Javier, McDuff, Daniel, Infante, Christian, Maes, Pattie, Quigley, Karen et al. 2016. "Wearable ESM." en 10.1145/2935334.2935340 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf ACM MIT web domain |
| spellingShingle | Hernandez, Javier McDuff, Daniel Infante, Christian Maes, Pattie Quigley, Karen Picard, Rosalind W. Wearable ESM |
| title | Wearable ESM |
| title_full | Wearable ESM |
| title_fullStr | Wearable ESM |
| title_full_unstemmed | Wearable ESM |
| title_short | Wearable ESM |
| title_sort | wearable esm |
| url | https://hdl.handle.net/1721.1/137012 |
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