Emotional intelligence in acquired brain injury

© 2018 Dr. Sarah Elizabeth HallSocio-emotional difficulties are among the most clinically striking and psychosocially disabling consequences of moderate to severe acquired brain injury (ABI). However, formal assessment and characterisation of these difficulties has proven challenging. Although emotion processing is theoretically understood to represent a complex and multifaceted set of skills that contribute to adaptive interpersonal functioning, including the ability to experience, identify, use, understand and regulate emotions, existing assessment approaches in ABI tend to be idiosyncratic. Furthermore, many available emotion processing tools lack adequate psychometric properties. A multi-dimensional, theoretically-driven approach would help to elucidate the nature of emotion processing deficits after ABI in a systematic way. Such an approach may offer a means of predicting vulnerability to psychosocial dysfunction after ABI by identifying domains of emotion processing that are most pertinent for functional outcomes. This may prove particularly useful for understanding why a subset of patients experience marked psychosocial dysfunction in the community despite intact performances on traditional neuropsychological tests. The aim of this thesis was to investigate the utility of a multi-dimensional model of emotional intelligence (EI) for conceptualising and assessing emotion processing difficulties after moderate to severe ABI. This aim was investigated over a series of three studies employing a cross-sectional sample of 82 community-dwelling adults with moderate to severe ABI. Participants completed a standardised, normed ability-based test of EI, the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT V2.0), and measures of cognitive, psychological, and community functioning. Study 1 provided initial evidence of the sensitivity of the MSCEIT V2.0 to emotion processing impairments in this sample. This study demonstrated evidence of reliability and validity of the test within this population, with support for a three- rather than four-factor model of EI due to the statistical redundancy of the Using Emotions subscale. In Study 2, two specific EI domains were found to be relevant for community participation outcomes after ABI: the ability to understand emotions was predictive of return to work, and the ability to manage emotions was predictive of community integration. In Study 3, EI assessment was used to identify distinct emotion processing profiles in ABI, including a group that appear particularly vulnerable to poor psychosocial functioning despite broadly intact performance on traditional neuropsychological tests. In combination, these findings provide initial support for the utility of a tripartite model of EI for conceptualising emotion processing deficits after moderate to severe ABI. In addition to offering a means of reconciling the existing literature, this framework may prove useful for guiding approaches to clinical assessment and intervention in ABI. Findings from the series of studies presented here suggest that assessment of EI can help to predict participation outcomes and identify vulnerability to psychosocial dysfunction among patients who appear otherwise largely cognitively intact. In particular, strategic EI skills appear to represent an important target for clinical assessment and intervention given their relevance to psychosocial functioning. The findings of this thesis add to a growing body of evidence supporting the inclusion of socio-emotional skills tests in routine clinical assessment for individuals with brain injury