Determinants of motivated behavior are linked to fatigue and its perturbation by SARS-CoV-2 vaccination
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Abstract
Background
Fatigue has an adaptive function and serves as a temporary signal to rest and save energy often in response to immune activation. It may, however, also persist in a pathological condition incurring significant burden. While subjective symptoms and scientific consensus indicate that both physical and mental determinants of motivated behavior are affected in fatigue, the underlying processes are rarely examined using objective, task-based indicators.
Methods
In three consecutive studies, including validation ( N = 48) and reliability assessments ( N = 27), we use an experimental task to jointly objectify reward learning and effort execution as two determinants of behavioral motivation. In addition, we tested how fatigue and its acute perturbation in response to immune activation after SARS-CoV-2 vaccination are linked to these task-based indicators of motivation in a longitudinal cross-over design ( N = 55).
Results
The validation study showed the utility of the experimental task for simultaneously assessing learning, effort exertion, and its regulation based on subjective confidence. The reliability assessment over a one-week period indicated that symptoms of fatigue and task behavior are highly reliable and that repetition effects have little impact on motivated behavior. Finally, in the vaccination trial, we found significant links between fatigue and task behavior. Baseline levels of fatigue predicted how effort is gauged in dependence of current confidence about reward outcomes, and state perturbations of fatigue in the context of the SARS-CoV-2 vaccination reduced confidence during learning. Importantly, task success was significantly lower in subjects who reported high fatigue at baseline and who additionally experienced stronger increase in fatigue in response to vaccination.
Discussion
Our results demonstrate that the experimental task allows to jointly assess determinants of motivated behavior, and to link its constituent processes to subjective fatigue. This suggests that our understanding of fatigue and its perturbation due to acute immune activation can benefit from objective, task-based indicators of the underlying motivational mechanisms. Future studies could build on these findings to further deepen the understanding of neurobehavioral mechanisms underlying fatigue in the context of immune activation.
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SciScore for 10.1101/2022.04.23.22274186: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: All subjects reported to have normal or corrected-to- normal vision, gave written informed consent prior to participation, and were financially reimbursed following study completion.
IRB: The study protocol was approved by the local ethics committee of the University of Lübeck (AZ 18-014; AZ 21-136).Sex as a biological variable In experiment 1, two out of 50 subjects were excluded, resulting in a final sample of 48 subjects (mean age=22.31, SD=2.75, 37 female, 11 male), all of whom were university students. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Software used for statistical analyses: Data … SciScore for 10.1101/2022.04.23.22274186: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: All subjects reported to have normal or corrected-to- normal vision, gave written informed consent prior to participation, and were financially reimbursed following study completion.
IRB: The study protocol was approved by the local ethics committee of the University of Lübeck (AZ 18-014; AZ 21-136).Sex as a biological variable In experiment 1, two out of 50 subjects were excluded, resulting in a final sample of 48 subjects (mean age=22.31, SD=2.75, 37 female, 11 male), all of whom were university students. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Software used for statistical analyses: Data were analyzed using MATLAB R2019b as well as jamovi Version 1.8.2.0 (The jamovi project, 2020) and R (R Core Team, 2018). MATLABsuggested: NoneFigures were created using the R package ggplot2 (Wickham, 2016), the Matlab toolbox gramm (Morel, 2018), as well as Inkscape (Inkscape, 2020). ggplot2suggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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