Expressed emotion in parents’ spontaneous speech as a window to parental burnout.
Year: 2025
Type: article
Study design: Observational Study
Abstract: Parental burnout arises from persistent and severe parenting stress and is mainly characterized by profound exhaustion in the parental role. Whereas much of the research on this condition relies on questionnaires, developmental studies advocate for the use of spontaneous speech samples to capture naturalistic parenting experiences. The coded "expressed emotion" (EE) within these speech samples has proven to be a valid indicator of the emotional climate of the parent-child relationship and meaningfully maps onto measures of parental well-being. This study used EE as a lens to examine parental burnout by first comparing EE between parents applying for parental burnout treatment and a control group and, second, by exploring associations between parents' EE and their parental burnout scores. A total of 106 Belgian parents (94.3% mothers, mostly aged 30-39 years), including 55 parents applying for parental burnout treatment and 51 parents in a control group, completed the Parental Burnout Assessment and were prompted to talk for 5 min about how they feel as a parent. These speech samples were coded based on EE, with coders being blind to participants' parental burnout scores and group memberships. Most parents applying for treatment (90.9%) showed high EE and demonstrated more criticism, higher emotional overinvolvement, and lower warmth compared to the control group, with substantial effect sizes. Criticism showed the strongest association with parents' parental burnout scores. This study highlights the promising benefits of listening to naturally provided cues in parents' spontaneous speech about parenthood, thereby pointing toward crucial pathways for the detection of parental burnout. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Source: Journal of Family Psychology
DOI: 10.1037/fam0001392
Institutions: Ghent University, UCLouvain, University of Liège
Language: English
Subfield: Demography
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4415246972
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