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John Maltby
John
Maltby
Liz Day
Liz
Day
Magdalena Zemojtel-Piotrowska
Magdalena
Zemojtel-Piotrowska
Jarosław Piotrowski
Jarosław
Piotrowski
Hidefumi Hitokoto
Hidefumi
Hitokoto
Tomasz Baran
Tomasz
Baran
Ceri Jones
Ceri
Jones
Anjalee Chakravarty-Agbo
Anjalee
Chakravarty-Agbo
Heather Flowe
Heather
Flowe
An ecological systems model of trait resilience: Cross-cultural and clinical relevance
Loughborough University
2016
Resilience
Adaptation
Recovery
Depression
Anxiety
Psychometrics
Medical and Health Sciences not elsewhere classified
2016-06-09 11:06:57
Journal contribution
https://repository.lboro.ac.uk/articles/journal_contribution/An_ecological_systems_model_of_trait_resilience_Cross-cultural_and_clinical_relevance/9624857
© 2016. The study explored how scores on the three dimensions of the Engineering, Ecological, and Adaptive Capacity (EEA) trait resilience scale, derived from Holling's ecological systems theory of resilience, demonstrate fit within higher-order bifactor models of measurement, cultural invariance, and associations with clinical caseness of affect. Three samples (295 US adults, and 179 Japanese and 251 Polish university students) completed the EEA trait resilience scale. In addition, a subsample of US adults were administered the Ten-Item Personality Inventory and the Hospital Anxiety and Depression Scale). Across all samples, a higher-order bifactor model provided the best fit of the data, with salience of loadings on the three group factors. A multi-group comparison found configural invariance, but neither metric nor scalar invariance, for EEA resilience scores across the three samples. Among the US sample, engineering and adaptive trait resilience scores predicted clinical caseness of depression, and adaptive trait resilience scores predicted clinical caseness of anxiety, after controlling for sex, age, income, education, employment, and personality. The findings suggest the cross-cultural replicability of the structure (but not the meaning) of the three-factor EEA measure of trait resilience, and its relevance for predicting clinical caseness of affect among a US sample.