Affective instability in those with and without mental disorders: A case control study

Abstract

Individuals with mental disorder demonstrate higher levels of affective lability and lower affect control than those without mental disorder. In contrast affective intensity may not be useful in demarcating abnormal affective experience. Independent of diagnosis, affective instability, as measured by affect lability, adversely impacts day-to-day functioning. It could be an important target for clinical intervention.

Affective lability across psychosis spectrum disorders

“…In nonaffective psychotic disorders, especially schizophrenia, knowledge concerning the prevalence, distribution, and clinical correlates of AL is scarce [25]. The few existing studies looking explicitly into AL suggest that it is common, and that it may mediate the link between childhood adversity and positive psychotic symptoms [4,10,25]. More broadly, features of affective dysregulation have been associated with both the emergence and persistence of paranoid delusions, auditory hallucinations and other psychotic experiences such as passivity phenomena and thought interference [26][27][28][29].…”

“…Furthermore, there is mounting evidence of considerable overlap between SCZ and BD when it comes to genetic susceptibility and clinical symptomatology [30,31]. A previous study suggests that the level of AL is the same in nonaffective psychotic disorders and BD [10]. To what extent AL is linked to the same sociodemographic factors and clinical symptoms across these diagnostic groups is, however, not known.…”

Explaining why childhood abuse is a risk factor for poorer clinical course in bipolar disorder: a path analysis of 923 people with bipolar I disorder

“…Affective instability is linked to changes in the amygdala and salience networks (Broome et al ., 2015 a ) and can be defined as rapid oscillations of intense affect with difficulties in regulating these or their behavioural consequences (Marwaha et al ., 2013 a , 2013 b ). Whilst affective instability is transdiagnostic (Broome et al ., 2015 b ; Marwaha et al ., 2018), it may be particularly important in bipolar disorder (Harrison et al ., 2017). It is linked to the poor functional outcome (Strejilevich et al ., 2013; Stange et al ., 2016) and worse clinical course (Etain et al ., 2013) in this condition.…”

Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?

“…Firstly, digital phenotyping may be used as a diagnostic predictive marker in BD, by identifying BD specific traits for a rapid and accurate diagnosis. Secondly, digital phenotyping may be considered as a tool to predict longitudinal outcomes, by considering how BD subjects may oscillate in mood, energy levels, and cognition within hours, days, and months [ 49 ]. In this context, digital phenotyping could significantly improve the early identification and intervention in potentially life-threatening conditions, including fluctuations in suicidal ideation and thoughts of death [ 50 ], the dimension of the affective instability comprising emotional intensity, emotional lability, and ability to control shifts in mood [ 8 , 49 ].…”

“…Secondly, digital phenotyping may be considered as a tool to predict longitudinal outcomes, by considering how BD subjects may oscillate in mood, energy levels, and cognition within hours, days, and months [ 49 ]. In this context, digital phenotyping could significantly improve the early identification and intervention in potentially life-threatening conditions, including fluctuations in suicidal ideation and thoughts of death [ 50 ], the dimension of the affective instability comprising emotional intensity, emotional lability, and ability to control shifts in mood [ 8 , 49 ]. Moreover, it may be a valid tool for clinical characterization, course of illness (i.e., detection of subgroups of BD patients), prediction of critical outcomes in illness course (i.e., relapse, recurrence, resilience), to early detecting, monitoring and predicting treatment response, non-response, remission, and treatment tolerance (i.e., identification of predictors of side effects) as well as a prediction tool for the identification of high-risk BD subjects [ 8 , 19 , 21 , 45 ].…”