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. 2014 Jul;44(9):1793-808.
doi: 10.1017/S0033291713002407. Epub 2013 Sep 27.

How is affective instability defined and measured? A systematic review

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How is affective instability defined and measured? A systematic review

S Marwaha et al. Psychol Med. 2014 Jul.

Abstract

Background: Affective instability (AI) is poorly defined but considered clinically important. The aim of this study was to examine definitions and measures of AI employed in clinical populations.

Method: This study was a systematic review using the PRISMA guidelines. MEDLINE, Embase, PsycINFO, PsycArticles and Web of Science databases were searched. Also five journals were hand searched. Primary empirical studies involving randomized controlled trials (RCTs), non-RCTs, controlled before and after, and observational investigations were included. Studies were selected, data extracted and quality appraised. A narrative synthesis was completed.

Results: A total of 11 443 abstracts were screened and 37 studies selected for final analysis on the basis that they provided a definition and measure of AI. Numbers of definitions for each of the terms employed in included studies were: AI (n = 7), affective lability (n = 6), affective dysregulation (n = 1), emotional dysregulation (n = 4), emotion regulation (n = 2), emotional lability (n = 1), mood instability (n = 2), mood lability (n = 1) and mood swings (n = 1); however, these concepts showed considerable overlap in features. A total of 24 distinct measures were identified that could be categorized as primarily measuring one of four facets of AI (oscillation, intensity, ability to regulate and affect change triggered by environment) or as measuring general emotional regulation.

Conclusions: A clearer definition of AI is required. We propose AI be defined as 'rapid oscillations of intense affect, with a difficulty in regulating these oscillations or their behavioural consequences'. No single measure comprehensively assesses AI and a combination of current measures is required for assessment. A new short measure of AI that is reliable and validated against external criteria is needed.

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