Numerous theories posit different core features to borderline personality disorder (BPD). Recent advances in network analysis provide a method of examining the relative centrality of BPD symptoms, as well as examine the replicability of findings across samples. Additionally, despite the increase in research supporting the validity of BPD in adolescents, clinicians are reluctant to diagnose BPD in adolescents. Establishing the replicability of the syndrome across adolescents and adults informs clinical practice and research. This study examined the stability of BPD symptom networks and centrality of symptoms across samples varying in age and clinical characteristics.

Cross-sectional analyses of BPD symptoms from semi-structured diagnostic interviews from the Collaborative Longitudinal Study of Personality Disorders (CLPS), the Methods to Improve Diagnostic Assessment and Service (MIDAS) study, and an adolescent clinical sample. Network attributes, including edge (partial association) strength and node (symptom) expected influence, were compared.

The three networks were largely similar and strongly correlated. Affective instability and identity disturbance emerged as relatively central symptoms across the three samples, and relationship difficulties across adult networks. Differences in network attributes were more evident between networks varying both in age and in BPD symptom severity level.

Findings highlight the relative importance of affective, identity, and relationship symptoms, consistent with several leading theories of BPD. The network structure of BPD symptoms appears generally replicable across multiple large samples including adolescents and adults, providing further support for the validity of the diagnosis across these developmental phases.

Childhood abuse is a risk factor for poorer illness course in bipolar disorder, but the reasons why are unclear. Trait-like features such as affective instability and impulsivity could be part of the explanation. We aimed to examine whether childhood abuse was associated with clinical features of bipolar disorder, and whether associations were mediated by affective instability or impulsivity.

We analysed data from 923 people with bipolar I disorder recruited by the Bipolar Disorder Research Network. Adjusted associations between childhood abuse, affective instability and impulsivity and eight clinical variables were analysed. A path analysis examined the direct and indirect links between childhood abuse and clinical features with affective instability and impulsivity as mediators.

Affective instability significantly mediated the association between childhood abuse and earlier age of onset [effect estimate (θ)/standard error (SE): 2.49], number of depressive (θ/SE: 2.08) and manic episodes/illness year (θ/SE: 1.32), anxiety disorders (θ/SE: 1.98) and rapid cycling (θ/SE: 2.25). Impulsivity significantly mediated the association between childhood abuse and manic episodes/illness year (θ/SE: 1.79), anxiety disorders (θ/SE: 1.59), rapid cycling (θ/SE: 1.809), suicidal behaviour (θ/SE: 2.12) and substance misuse (θ/SE: 3.09). Measures of path analysis fit indicated an excellent fit to the data.

Affective instability and impulsivity are likely part of the mechanism of why childhood abuse increases risk of poorer clinical course in bipolar disorder, with each showing some selectivity in pathways. They are potential novel targets for intervention to improve outcome in bipolar disorder.

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.

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.

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.

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.