Disentangling vulnerabilities from outcomes: Distinctions between trait affect and depressive symptoms in adolescent and adult samples

Abstract

Background Trait negative affect and trait positive affect are affective vulnerabilities to depressive symptoms in adolescence and adulthood. While trait affect and the state affect characteristic of depressive symptoms are proposed to be theoretically distinct, no studies have established that these constructs are statistically distinct. Therefore, the purpose of the current study was to determine whether the trait affect (e.g. temperament dimensions) that predicts depressive symptoms and the state affect characteristic of depressive symptoms are statistically distinct among early adolescents and adults. We hypothesized that trait negative affect, trait positive affect, and depressive symptoms would represent largely distinct factors in both samples. Method Participants were 268 early adolescents (53.73% female) and 321 young adults (70.09% female) who completed self-report measures of demographic information, trait affect, and depressive symptoms. Results Principal axis factoring with oblique rotation for both samples indicated distinct adolescent factor loadings and overlapping adult factor loadings. Confirmatory factor analyses in both samples supported distinct but related relationships between trait NA, trait PA, and depressive symptoms. Limitations Study limitations include our cross-sectional design that prevented examination of self-reported fluctuations in trait affect and depressive symptoms and the unknown potential effects of self-report biases among adolescents and adults. Conclusions Findings support existing theoretical distinctions between adolescent constructs but highlight a need to revise or remove items to distinguish measurements of adult trait affect and depressive symptoms. Adolescent trait affect and depressive symptoms are statistically distinct, but adult trait affect and depressive symptoms statistically overlap and warrant further consideration.

Longitudinal Trajectories of Depression Symptoms in Adolescence: Psychosocial Risk Factors and Outcomes

“…It is plausible that current depression influences responses to other questionnaire measures to some degree, leading to exaggerated temperament scores during periods of depression. However, a recent study by Harding et al [68] investigated this issue and reported a clear statistical distinction between trait positive and negative affectivity, as measured by the EATQ-R, and depressive symptoms. They suggested that the EATQ-R ensured distinct construct measurement by separating items referencing depression, sadness, happiness, and pleasure as a distinct scale labelled Depressed Mood, which does not load onto the subscales used as measures of temperament in this study.…”

Trait Affect, Emotion Regulation, and the Generation of Negative and Positive Interpersonal Events

“…Further, identifying the potential role of trait negative affect in stress generation among relatively healthy samples of late adolescents may highlight a target for intervention. Given that negative affect is a prospective risk factor for depression and anxiety (Watson, Clark, & Carey, 1988), yet distinct from depression itself (Harding, Willey, Ashles, & Mezulis, 2016), identifying whether negative affect contributes to stress generation may elucidate a potential transdiagnostic mechanism contributing to mood and anxiety disorders. In particular, stress generation may be a process through which individuals with higher levels of trait negative affect are doubly at risk- both due to their tendency towards negative affective states and generation of negative interpersonal stressors.…”

“…Although negative and positive affects are closely related, positive affect is uniquely associated with psychopathology (Carl, Soskin Kerns, & Barlow, 2013; Gilbert, 2012; Harding et al, 2016). Individuals with low trait positive affect often experience less positive emotions and energy, which is characteristic of anhedonia- a hallmark of depression (e.g., Pizzagalli, 2013), and predicts greater depressive symptoms (Watson et al, 1988; Hudson, Harding, & Mezulis, 2015).…”