Pain Monitoring Task

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This continuous pain rating task assesses pain intensity using the open-source software PsychoPy [1] hosted on Pavlovia [2]. At the start, participants are provided with detailed instructions and asked to complete a short practice run to ensure they understood how the application worked. Once this is completed, participants continuously rated their pain for approximately five minutes on a vertical scale ranging from "Least Pain" to "Most Pain."

The interface of the application and the experiment timeline are depicted in Figure 1:

Figure 1: Experimental Task Design.

🏃‍♂️Running the Task

1. Create an account on pavlovia.org
2. Click on '+' sign on top navigation bar and select 'New project' option.
3. Select 'Import project' and then click on the 'Repo by URL' button
4. Paste our current GitHub URL under the 'Git repository URL' textbox. On the pavlovia page, you can rename the default 'Project name' to suit your project's requirements.
5. Voilà! The task is instantly ready to use for your experiment. Remember, the participant data (.csv and .log files) will be stored under data directory

🎯Application

This task helped us collect pain ratings and highlight the importance of short-term variability in chronic musculoskeletal pain and its potential as a predictor of clinical outcomes. Please read our paper as cited below for more details.

📑Citation

Pain monitoring Task citation:

Zheng, X., Rajwal, S., Ho, S. Y. S., Ashworth, C., Seymour, B., Shenker, N., & Mancini, F. (2024). Psychopy based Continuous Pain Monitoring Task (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.13754802

Preprint paper citation:

@article {Zheng2025.01.12.25320413,
author = {Zheng, Xuanci and Rajwal, Swati and Ho, Sharon Yuen Shan and Ashworth, Carl and Seymour, Ben and Shenker, Nicholas and Mancini, Flavia},
title = {Short-term variability of chronic musculoskeletal pain},
elocation-id = {2025.01.12.25320413},
year = {2025},
doi = {10.1101/2025.01.12.25320413},
publisher = {Cold Spring Harbor Laboratory Press},
URL = {https://www.medrxiv.org/content/early/2025/01/13/2025.01.12.25320413},
eprint = {https://www.medrxiv.org/content/early/2025/01/13/2025.01.12.25320413.full.pdf},
journal = {medRxiv}
}

Citation will be updated as soon as the preprint is published

📚References

1. Peirce, J., Gray, J.R., Simpson, S. et al. PsychoPy2: Experiments in behavior made easy. Behav Res 51, 195–203 (2019). https://doi.org/10.3758/s13428-018-01193-y
2. Pavlovia. Pavlovia, https://pavlovia.org/. Accessed 11^th September 2024.

⚖️License

Generously distributed under the MIT