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Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires

Personality describes the average behaviour and responses of individuals across situations; but personality traits are often poor predictors of behaviour in specific situations. This is known as the “personality paradox”. We evaluated the interrelations between various trait and state variables in p...

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Autores principales: Määttänen, Ilmari, Henttonen, Pentti, Väliaho, Julius, Palomäki, Jussi, Thibault, Maisa, Kallio, Johanna, Mäntyjärvi, Jani, Harviainen, Tatu, Jokela, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930110/
https://www.ncbi.nlm.nih.gov/pubmed/33681494
http://dx.doi.org/10.1016/j.heliyon.2021.e06243
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author Määttänen, Ilmari
Henttonen, Pentti
Väliaho, Julius
Palomäki, Jussi
Thibault, Maisa
Kallio, Johanna
Mäntyjärvi, Jani
Harviainen, Tatu
Jokela, Markus
author_facet Määttänen, Ilmari
Henttonen, Pentti
Väliaho, Julius
Palomäki, Jussi
Thibault, Maisa
Kallio, Johanna
Mäntyjärvi, Jani
Harviainen, Tatu
Jokela, Markus
author_sort Määttänen, Ilmari
collection PubMed
description Personality describes the average behaviour and responses of individuals across situations; but personality traits are often poor predictors of behaviour in specific situations. This is known as the “personality paradox”. We evaluated the interrelations between various trait and state variables in participants’ everyday lives. As state measures, we used 1) experience sampling methodology (ESM/EMA) to measure perceived affect, stress, and presence of social company; and 2) heart rate variability and 3) real-time movement (accelerometer data) to indicate physiological stress and physical movement. These data were linked with self-report measures of personality and personality-like traits. Trait variables predicted affect states and multiple associations were found: traits neuroticism and rumination decreased positive affect state and increased negative affect state. Positive affect state, in turn, was the strongest predictor of observed movement. Positive affect was also associated with heart rate and heart rate variability (HRV). Negative affect, in turn, was not associated with neither movement, HR or HRV. The study provides evidence on the influence of personality-like traits and social context to affect states, and, in turn, their influence to movement and stress variables.
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spelling pubmed-79301102021-03-05 Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires Määttänen, Ilmari Henttonen, Pentti Väliaho, Julius Palomäki, Jussi Thibault, Maisa Kallio, Johanna Mäntyjärvi, Jani Harviainen, Tatu Jokela, Markus Heliyon Research Article Personality describes the average behaviour and responses of individuals across situations; but personality traits are often poor predictors of behaviour in specific situations. This is known as the “personality paradox”. We evaluated the interrelations between various trait and state variables in participants’ everyday lives. As state measures, we used 1) experience sampling methodology (ESM/EMA) to measure perceived affect, stress, and presence of social company; and 2) heart rate variability and 3) real-time movement (accelerometer data) to indicate physiological stress and physical movement. These data were linked with self-report measures of personality and personality-like traits. Trait variables predicted affect states and multiple associations were found: traits neuroticism and rumination decreased positive affect state and increased negative affect state. Positive affect state, in turn, was the strongest predictor of observed movement. Positive affect was also associated with heart rate and heart rate variability (HRV). Negative affect, in turn, was not associated with neither movement, HR or HRV. The study provides evidence on the influence of personality-like traits and social context to affect states, and, in turn, their influence to movement and stress variables. Elsevier 2021-02-25 /pmc/articles/PMC7930110/ /pubmed/33681494 http://dx.doi.org/10.1016/j.heliyon.2021.e06243 Text en © 2021 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Määttänen, Ilmari
Henttonen, Pentti
Väliaho, Julius
Palomäki, Jussi
Thibault, Maisa
Kallio, Johanna
Mäntyjärvi, Jani
Harviainen, Tatu
Jokela, Markus
Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires
title Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires
title_full Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires
title_fullStr Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires
title_full_unstemmed Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires
title_short Positive affect state is a good predictor of movement and stress: combining data from ESM/EMA, mobile HRV measurements and trait questionnaires
title_sort positive affect state is a good predictor of movement and stress: combining data from esm/ema, mobile hrv measurements and trait questionnaires
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930110/
https://www.ncbi.nlm.nih.gov/pubmed/33681494
http://dx.doi.org/10.1016/j.heliyon.2021.e06243
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