Setting Physical Activity Goals with a Virtual Coach: Data and Analysis Code

doi:10.4121/21806868.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21806868
Datacite citation style:
Albers, Nele; Beyza Hizli; Bouke L. Scheltinga; Eline Meijer; Brinkman, Willem-Paul (2023): Setting Physical Activity Goals with a Virtual Coach: Data and Analysis Code. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21806868.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This is the data and analysis code underlying the paper "Setting Physical Activity Goals with a Virtual Coach: Vicarious Experiences, Personalization and Acceptance" by Nele Albers, Beyza Hizli, Bouke L. Scheltinga, Eline Meijer, and Willem-Paul Brinkman. The paper examines the use of personalized vicarious experiences in a goal-setting dialog for physical activity with a virtual coach.


Study

The paper is based on the study conducted in March 2022 for the publicly available Master's thesis by Beyza Hizli (http://resolver.tudelft.nl/uuid:b7225a91-6ae8-4a32-8441-38fb7ff74b4c). In this study, 39 fluently English-speaking adults set a running or walking goal with the text-based virtual coach Jody.  Participants thereby received either two of the three overall most motivating vicarious experiences (i.e., "generic" experiences) or "personalized" vicarious experiences chosen based on a linear regression model. During the dialog, participants wrote what they could take away from the examples from other people that they saw. After the dialog, participants further provided information regarding their self-efficacy for the type of goal they set (i.e., running or walking), ratings of examples on perceived motivational impact, and a free-text response about what they found motivating about the examples they saw.


The study was pre-registered in the Open Science Framework (OSF): https://osf.io/4duwh. 


Links to further resources:

  • The implementation of the virtual coach Jody is available here: https://doi.org/10.5281/zenodo.6647381.
  • The 72 examples from other people used in the study can be found in the dataset accompanying the Master's thesis by Beyza Hizli: https://doi.org/10.4121/20047328.v1.
  • A video of part of the dialog with the virtual coach is available here: https://youtu.be/7WJy7-H3QEQ.

Data

We collected data in three separate studies:

  1. Study to collect the vicarious experiences (part A). We gathered the vicarious experiences together with data on individual characteristics of the participants (e.g., age, stage of change for becoming physically active). We collected vicarious experiences from 72 people.
  2. Study to rate the vicarious experiences on perceived motivational impact and similarity (part B). We asked 36 individuals to each rate 18 vicarious experiences on perceived motivational impact and similarity to the person in the experience. We further collected data on individual characteristics of these 36 participants.
  3. Study to evaluate the goal-setting dialog and the vicarious experiences therein (part C). 39 participants interacted with the text-based virtual coach Jody to set a running or walking goal. Participants saw either personalized or generic examples from other people. We also collected data on individual characteristics of these 39 participants.

Please refer to the OSF pre-registration for more information on the data we collected. In addition, we describe our measures in detail in a separate sheet in each data file in the "Data"-folder. Note that we do not provide all data here: we describe in our README-files which data needs to be downloaded from the repository accompanying the Master's thesis by Beyza Hizli to reproduce some of our analyses (https://doi.org/10.4121/20047328.v1).


If you have any questions, please contact Nele Albers (n.albers@tudelft.nl).


history
  • 2023-01-04 first online, published, posted
publisher
4TU.ResearchData
format
.zip .pdf .Rmd .md .bib .tar.gz .csv .xlsx .ipynb .PNG .py .txt
funding
  • This work is part of the multidisciplinary research project Perfect Fit, which is supported by several funders organized by the Netherlands Organization for Scientific Research (NWO), program Commit2Data - Big Data & Health (project number 628.011.211). Besides NWO, the funders include the Netherlands Organisation for Health Research and Development (ZonMw), Hartstichting, the Ministry of Health, Welfare and Sport (VWS), Health Holland, and the Netherlands eScience Center.
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science

DATA

files (1)