Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1783660046943518720 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7930110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT maattanenilmari positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT henttonenpentti positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT valiahojulius positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT palomakijussi positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT thibaultmaisa positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT kalliojohanna positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT mantyjarvijani positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT harviainentatu positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires AT jokelamarkus positiveaffectstateisagoodpredictorofmovementandstresscombiningdatafromesmemamobilehrvmeasurementsandtraitquestionnaires |