Datasets for What emotions to encourage? International Journal of Applied Positive Psychology, 2023

DOI

Growing evidence shows that positive psychology interventions (PPIs) are able to enhance positive emotions. However, less is known about the specific role of high and low arousal positive emotions within such interventions. The goal of the current study is to examine the effect of different types of PPIs on high and low arousal emotions and to explore whether high and low arousal positive emotions serve as mediators for the intervention effects on mental well-being. Post-hoc tests of three formerly published randomized controlled trials were conducted in comparison with waitlist control: (1) a multicomponent PPI (N = 275), (2) a comprehensive gratitude intervention (N = 144), and (3) an acts of kindness intervention (N = 216). Findings showed that the multicomponent PPI improved low arousal emotions, while the gratitude intervention marginally improved high arousal positive emotions. The acts of kindness intervention was not more effective in improving positive emotions compared to waitlist control. Similar conclusions could be drawn from the mediation analyses, yielding most pronounced results for low arousal positive emotions mediating the effect of the multicomponent PPI on mental well-being. The current study provides first evidence that the upward spiral of positive emotions might depend on the type of PPI and its impact on high and in particular low arousal positive emotions.

Date Submitted: 2023-11-06

Identifier
DOI https://doi.org/10.17026/dans-z5b-x8pm
Metadata Access https://ssh.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-z5b-x8pm
Provenance
Creator M Schotanus-Dijkstra
Publisher DANS Data Station Social Sciences and Humanities
Contributor Marijke Schotanus-Dijkstra
Publication Year 2023
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact Marijke Schotanus-Dijkstra
Representation
Resource Type Dataset
Format application/zip; text/x-fixed-field; text/tab-separated-values; application/x-spss-syntax
Size 16369; 206784; 87713; 14432; 311040; 143469; 14431
Version 2.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Psychology; Social Sciences; Social and Behavioural Sciences; Soil Sciences