Review articleAssociations between Facets and Aspects of Big Five Personality and Affective Disorders:A Systematic Review and Best Evidence Synthesis
Introduction
Affective disorders are among the most common mental illnesses, with anxiety disorders being the most prevalent mental illnesses, followed by mood disorders (Stansfeld et al, 2016; Steel et al, 2014; Wittchen et al, 2011). For instance, a review of mental health population studies across thirty European countries found that anxiety disorders have a 12-month prevalence rate of 14%, whereas mood disorders have a 12-month prevalence rate of 7.8% (Wittchen et al, 2011). Affective disorders also have high economic costs. For example, mental illnesses are the third most common cause of sick leave in the UK, accounting for between £70- and £100 billion per year, much of which is accounted for by affective disorders (Mental Health Foundation, 2016). Due to their high prevalence and health cost, it is important to assess possible risk factors of affective disorders.
Within the diathesis-stress model, personality constructs can be conceptualized as diathesis, or vulnerability, factors in the development of affective disorders (Ormel et al, 2013; Watson et al, 2006). Associations between personality constructs and affective disorders may be mediated by behavioural and neurocognitive correlates of personality, such as stressful life events (Kendler et al, 2004), attentional biases (Elliott et al, 2011; Amin et al, 2004) and emotion regulation strategies (Connor-Smith & Flachsbart, 2007). Personality constructs have also been conceptualized as endophenotypes of mental illnesses (Bearden & Friemer, 2006), as they are moderately heritable (Vukasović & Bratko, 2015), and causally predict the development of affective disorders (Spinhoven et al, 2013; Struijs et al, 2018). Overall, investigating personality constructs associated with affective disorders can help to identify possible endophenotypes for affective disorders. Furthermore, affective disorders can also causally affect personality traits, such as scar effects, in which anxiety and depression increase trait neuroticism (Ormel et al, 2013; Watson et al, 2006).
Studies of personality using factor analysis have converged on five personality traits (Davis & Panksepp, 2018; Goldberg et al, 1990). A dominant model of personality is the Big Five (DeYoung et al, 2007; Allen and DeYoung, 2017), which proposes that personality can be described across five broad personality traits: neuroticism (referring to stress-reactivity and avoidance), extroversion (referring to sociability and positive emotion), conscientiousness (referring to delayed gratification and organisation), agreeableness (referring to politeness and compassion) and openness (referring to creativity and aesthetic appreciation; Costa & McCrea, 1992; Goldberg et al, 1990). A meta-analysis of 175 correlational studies of personality traits and common mental illnesses found that neuroticism positively correlates with affective disorders such as generalised anxiety disorder, MDD and panic disorder, whereas extroversion and conscientiousness negatively correlate with these affective disorders (Kotov et al, 2010). For this reason, the personality configuration of high neuroticism, low extroversion and low consciousness has been referred to as the “vulnerable personality” (Wardenaar et al, 2014) and the “misery triad” (Miller, 1991).
Big Five personality constructs exist within a personality hierarchy, from broad traits to narrow facets (DeYoung et al, 2016), allowing personality to be considered at different level of specificity (DeYoung et al, 2016). Various measures of lower-order personality constructs have been developed. In the Big Five Aspect Scale (BFAS), each trait is split into its two most statistically robust components (DeYoung et al, 2007); for example, trait agreeableness is split into the aspects compassion and politeness. The Big Five Inventory – 2 (BFI-2) splits each trait into three facets; for example, trait conscientiousness is split into order, productiveness and responsibility (Soto & John, 2017). The NEO-PI-R separates each trait into six narrow facets: for instance, extroversion is separated into the facets warmth, gregariousness, assertiveness, activity, excitement-seeking and positive emotion (Costa & McCrea, 1992).
Studying these lower-order personality constructs can provide more specific information about which components of a personality trait best explain its predictive power. For example, trait agreeableness has a non-significant relationship with MDD (Kotov et al, 2010), whereas the agreeableness facet trust moderately negatively correlates with MDD (r=-0.30, Quilty et al, 2013), indicating a specific role of this facet within the trait. Conversely, trait conscientiousness significantly negatively correlates with various affective disorders, whereas the conscientiousness facet deliberation does not (Friesen, 2008), indicating that this facet does not play an important role in this relationship.
Investigating lower-order personality constructs can therefore help to understand how personality constructs and affective disorders impact each other and can help to identify narrower endophenotypes for affective disorders. It may also help us to better understand the mechanisms underlying these associations. For instance, trait extroversion negatively correlates with various affective disorders (Kotov et al, 2010). However, extroversion includes conceptually distinct personality facets that could relate to separate mediating mechanisms: If the effect of extroversion is explained by facet positive emotion, extroversion may protect from affective disorders via positive attentional and memory biases (Amin et al, 2004; Canli et al, 2004) and goal-directed behaviour (Carver et al, 2013; Wilt et al., 2017). However, if the effect of extroversion is explained by facet sociability, the mediating mechanism may relate to social factors, such as social support. If the effect of extroversion is explained by facet assertiveness, one mediating mechanism may be negotiating skills to attain competitive goals. Therefore, investigating associations between facets and affective disorders can help to understand how personality risk factors influence the development of affective disorders.
The aim of the current study is therefore to systematically review the literature investigating associations between lower-order personality constructs and affective disorder.
Section snippets
Methodology
The systematic review protocol was pre-registered on Prospero (ID: CRD42019126874).
Results
Eleven studies used a sample of current or recovering psychiatric patients; four studies used a sample of undergraduate students. The sample size ranged from fourteen (Rees et al., 2006) to 1,079 (Friesen, 2008), with a mean sample size of 303.60 (SD = 281.03). Across the fifteen studies, the total sample comprised 4,554 participants. Four studies were rated as being of “good” quality; eight of “fair” quality; and three studies of "poor" quality (Table 1).
Several studies did not provide details
Discussion
The aim of this systematic review was to determine which personality facets were significantly associated with affective disorders. Fifteen studies were identified across fourteen publications, most of which focused on MDD or social anxiety. Fifteen studies investigated personality facets, and two investigated correlations between personality aspects and MDD. There was strong evidence that aspect withdrawal in neuroticism, and most facets of neuroticism, positively associated with various
Conclusion
This systematic review reveals that a range of affective disorders are associated with high trait neuroticism, low positive emotion in extroversion, and low competence and self-discipline in conscientiousness. Furthermore, anxiety disorders are associated with low trust and low openness to actions, along with high openness to fantasy. Investigating these personality facets may help to improve our understanding of the development of affective disorders. Future research is needed to investigate
Declaration of Competing Interest
The authors report no conflict of interest.
Acknowledgements and author contributions
All authors were involved in study conceptualisation and report writing. Kieran Lyon and Kerry Ware were involved in data collection and quality assessment. Kieran Lyon performed the best evidence syntheses. Gabriella Juhasz was supported by the Hungarian Brain Research Program, the Hungarian Academy of Sciences, Hungarian National Development Agency, and Semmelweis University (Grants: 2017-1.2.1-NKP-2017-00002; and KTIA_NAP_13-2- 2015-0001, MTA-SE-NAP B Genetic Brain Imaging Migraine Research
Role of the Funding source
This study was conducted as part of a self-funded Ph.D., administered by the Student Loans Company, UK. No funding organisation was involved in the conceptualizing, planning, analysis or writing of this study.
References (* included in the systematic review) (77)
- et al.
Attentional bias for valenced stimuli as a function of personality in the dot-probe task
Journal of Research in Personality
(2004) - et al.
Endophenotypes for psychiatric disorders: ready for primetime?
Trends in genetics
(2006) - et al.
Dimensions of hypochondriasis and the five-factor model of personality
Personality and individual differences
(2000) The effects of locus of control on daily exposure, coping and reactivity to work interpersonal stressors: a diary study
Personality and Individual Differences
(2000)- et al.
Association of five-factor model personality domains and facets with presence, onset, and treatment outcomes of major depression in older adults
The American Journal of Geriatric Psychiatry
(2013) - et al.
Relationships between personality traits and depression in the light of the “Big Five” and their different facets
L'Évolution Psychiatrique
(2017) - et al.
The state effect of depressive and anxiety disorders on big five personality traits
Journal of psychiatric research
(2012) - et al.
Neuroticism and perfectionism as predictors of social anxiety
Personality and Individual Differences
(2017) - et al.
Neuroticism and common mental disorders: meaning and utility of a complex relationship
Clinical psychology review
(2013) - et al.
Hierarchical personality traits and the distinction between unipolar and bipolar disorders
Journal of affective disorders
(2013)