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Profiling Emotion Regulation: Exploring patterns of regulation in classroom behaviour


Type

Thesis

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Authors

Sinclaire-Harding, Lysandra 

Abstract

Emotion Regulation describes the ability to influence the experience and expression of affect. Adaptive emotion regulation contributes to healthy development, social competence and academic success (Kochanska, Murray & Harlan, 2000). This study investigated the behavioural strategies for emotion regulation, emotion expression, regulatory styles and classroom behaviour in middle childhood. One hundred and twenty-eight children were recruited from five UK public and private primary schools. From within their school setting, participant sensitivity to emotion-eliciting events was recorded using ambulatory skin conductance technology whilst age-group paired children performed two LEGO construction tasks. Observed behaviours were video-recorded and coded to establish frequencies of distinct regulatory behaviours. These were compared to self-reports of emotion regulation strategies and teacher-reports of classroom behaviour. Iterative partitioning cluster analysis methods were used to identify four regulatory profiles: 1) the ‘Adaptive’ cluster: employed high levels of positive problem solving and reappraisal strategies and frequently expressed both positive and negative emotions; 2) the ‘Maladaptive’ cluster: used more negative regulation (avoidant or obstructive strategies), expressed more negative emotion and had more social and behavioural problems in class; 3) the ‘Reactive’ cluster showed high levels of electrodermal activity, expressed little emotion and were reported as inattentive/hyperactive in class; and 4) the ‘Distracted’ cluster demonstrated high levels of behavioural and cognitive distraction. These results indicate four meaningful profiles that could support the identification of vulnerable individuals for positive school-based intervention and support.

Description

Date

2018-02-05

Advisors

Whitebread, David

Keywords

emotion regulation, skin conductance, cluster analysis, attentional deployment

Qualification

Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge