Positive affect and heart rate variability: a dynamic analysis
Abstract Traditional survey methods can provide noisy data arising from recall, memory and other biases. Technological advances (particularly in neuroscience) are opening new ways of monitoring physiological processes through non-intrusive means. Such dense continuous data provide new and fruitful a...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-57279-5 |
| _version_ | 1797233546799087616 |
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| author | Tony Beatton Ho Fai Chan Uwe Dulleck Andrea Ristl Markus Schaffner Benno Torgler |
| author_facet | Tony Beatton Ho Fai Chan Uwe Dulleck Andrea Ristl Markus Schaffner Benno Torgler |
| author_sort | Tony Beatton |
| collection | DOAJ |
| description | Abstract Traditional survey methods can provide noisy data arising from recall, memory and other biases. Technological advances (particularly in neuroscience) are opening new ways of monitoring physiological processes through non-intrusive means. Such dense continuous data provide new and fruitful avenues for complementing self-reported data with a better understanding of human dynamics and human interactions. In this study, we use a survey to collect positive affect (feelings) data from more than 300 individuals over a period of 24 h, and at the same time, map their core activities (5000 recorded activities in total) with measurements of their heart rate variability (HRV). Our results indicate a robust correlation between the HRV measurements and self-reported affect. By drawing on the neuroscience and wellbeing literature we show that dynamic HRV results are what we expect for positive affect, particularly when performing activities like sleep, travel, work, exercise and eating. This research provides new insights into how to collect HRV data, model and interpret it. |
| first_indexed | 2024-04-24T16:17:54Z |
| format | Article |
| id | doaj.art-ab1496c145cf4c329954b248c4b69bd4 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T16:17:54Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-ab1496c145cf4c329954b248c4b69bd42024-03-31T11:21:34ZengNature PortfolioScientific Reports2045-23222024-03-0114111110.1038/s41598-024-57279-5Positive affect and heart rate variability: a dynamic analysisTony Beatton0Ho Fai Chan1Uwe Dulleck2Andrea Ristl3Markus Schaffner4Benno Torgler5School of Economics and Finance, Queensland University of TechnologySchool of Economics and Finance, Queensland University of TechnologySchool of Economics and Finance, Queensland University of TechnologyHeart2Business GmbHCentre for Behavioural Economics, Society and Technology (BEST)School of Economics and Finance, Queensland University of TechnologyAbstract Traditional survey methods can provide noisy data arising from recall, memory and other biases. Technological advances (particularly in neuroscience) are opening new ways of monitoring physiological processes through non-intrusive means. Such dense continuous data provide new and fruitful avenues for complementing self-reported data with a better understanding of human dynamics and human interactions. In this study, we use a survey to collect positive affect (feelings) data from more than 300 individuals over a period of 24 h, and at the same time, map their core activities (5000 recorded activities in total) with measurements of their heart rate variability (HRV). Our results indicate a robust correlation between the HRV measurements and self-reported affect. By drawing on the neuroscience and wellbeing literature we show that dynamic HRV results are what we expect for positive affect, particularly when performing activities like sleep, travel, work, exercise and eating. This research provides new insights into how to collect HRV data, model and interpret it.https://doi.org/10.1038/s41598-024-57279-5Positive affectHeart rate variabilityData collectionAnalytical modelsInterpretation |
| spellingShingle | Tony Beatton Ho Fai Chan Uwe Dulleck Andrea Ristl Markus Schaffner Benno Torgler Positive affect and heart rate variability: a dynamic analysis Scientific Reports Positive affect Heart rate variability Data collection Analytical models Interpretation |
| title | Positive affect and heart rate variability: a dynamic analysis |
| title_full | Positive affect and heart rate variability: a dynamic analysis |
| title_fullStr | Positive affect and heart rate variability: a dynamic analysis |
| title_full_unstemmed | Positive affect and heart rate variability: a dynamic analysis |
| title_short | Positive affect and heart rate variability: a dynamic analysis |
| title_sort | positive affect and heart rate variability a dynamic analysis |
| topic | Positive affect Heart rate variability Data collection Analytical models Interpretation |
| url | https://doi.org/10.1038/s41598-024-57279-5 |
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