Feasibility of generating structured motivational messages for tailored physical activity coaching: Data and analysis code

doi:10.4121/33888406-2d4e-4365-bf6e-0a45616842ef.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: 10.4121/33888406-2d4e-4365-bf6e-0a45616842ef
Datacite citation style:
Ghantasala, Ramya; Albers, Nele; Kristell M. Penfornis; van Vliet, Milon; Brinkman, Willem-Paul (2023): Feasibility of generating structured motivational messages for tailored physical activity coaching: Data and analysis code. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/33888406-2d4e-4365-bf6e-0a45616842ef.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This is the data and analysis code underlying the paper "Feasibility of generating structured motivational messages for tailored physical activity coaching" by Ramya P. Ghantasala, Nele Albers, Kristell M. Penfornis, Milon van Vliet, and Willem-Paul Brinkman. In this paper, experts wrote structured motivational messages for physical activity coaching tailored to a person's mood, self-efficacy, and progress and evaluated the perceived motivational impact of these messages in an online study with 60 participants. We further conducted a thematic analysis of participants' free-text responses about what they find motivating and demotivating in motivational messages.


Study

The study was conducted on the online crowdsourcing platform Prolific between December 2021 and January 2022. The Human Research Ethics Committee of Delft University of Technology granted ethical approval for the research (Letter of Approval number: 1814). 60 participants each rated the perceived motivational impact of 6 generic and 6 tailored messages based on scenarios. This repository contains both the generic and tailored motivational messages and the scenarios.


Data

We provide data on:

  1. participant characteristics (e.g., age, gender, stage of change for becoming physically active),
  2. the perceived motivational impact ratings,
  3. the free-text responses about what people found motivating and demotivating in motivational messages.


The file "data/Columns explanation.xlsx" explains in detail how each variable was measured.


Analysis

We provide code to reproduce our analysis with Docker. For more information on this, please refer to the README-file in this repository.


In the case of questions, please contact Nele Albers (n.albers@tudelft.nl) or Willem-Paul Brinkman (w.p.brinkman@tudelft.nl).


history
  • 2023-08-31 first online, published, posted
publisher
4TU.ResearchData
format
.zip, .pdf, .md, .bib, .Rmd, .csv, .xlsx, .ipynb, .r
derived from
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, Department of Intelligent Systems, Interactive Intelligence

DATA

files (1)