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| Type | Conference Presentation |
| Scope | Discipline-based scholarship |
| Title | Indivi: Personalizing feedback for study participants at scale |
| Organization Unit | |
| Authors |
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| Presentation Type | other |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | The 6th biennial conference of Society for Ambulatory Assessment (SAA) 2019 |
| Event Type | conference |
| Event Location | Syracuse, New York, USA |
| Event Start Date | June 19 - 2019 |
| Event End Date | June 22 - 2019 |
| Abstract Text | Ambulatory assessment often includes a significant burden to the participant, particularly if it includes self-reports. One way of compensating this effort and allow the study participant to take part in the interpretational discourse, is to provide personalized feedback of own data. With increasingly large number of study participants, manually personalizing feedback becomes infeasible. In this poster, we present “Indivi”, an open-source web application that aids researchers to personalize feedback at scale. Indivi is an interdisciplinary collaboration between experts in ambulatory assessment and HumanComputer Interaction. We started with Contextual Inquiry interviews with ambulatory assessment experts, resulting in work models showing (1) an iterative process of analyzing and formulating personalized feedback, (2) a taxonomy of variables and the associated method to visualize and contextualize the feedback. Based on these findings, we iteratively designed and tested the Indivi tool. To use Indivi, the researchers import a comma-separated file of study data. Indivi supports data from many types of study designs, including longitudinal data and dyadic data, within- and between-subjects. Then, they specify sets of variables. For each of these sets, in the second step, Indivi automatically choose an appropriate chart type and classifies participants in three categories depending on their individual values. The researchers assign textual explanation individually for the high, medium, and low values. These are used to personalize the feedback. We believe that Indivi will provide researchers within an ambulatory assessment framework a scalable way to use personalized feedback to foster the participatory moment in their studies and motivate study participants. |
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