Elsevier

Journal of Affective Disorders

Volume 294, 1 November 2021, Pages 939-948
Journal of Affective Disorders

Research paper
A longitudinal trait-state model of attentional control: Implications for repetitive negative thinking

https://doi.org/10.1016/j.jad.2021.07.105Get rights and content

Highlights

  • A latent variable model was applied to attentional control.

  • Time-invariant factor variance was greater than time-varying factor variance.

  • Effects of time-varying factor variance were small to moderate in magnitude.

  • Time-invariant factor of attentional control most strongly linked with repetitive thinking.

Abstract

Background

Attentional control refers to the ability to direct, focus, and shift attention voluntarily, and poor attentional control may confer risk for various affective disorders by increasing repetitive negative thinking. Although attentional control has been described as a trait, it is unclear if it is a time-varying (TV) or state-like factor versus a time-invariant (TI) or trait-like personality characteristic.

Methods

In a 6-wave, 5-month longitudinal study, community participants (n = 1,251) completed the Attentional Control Scale (Derryberry & Reed, 2002), the most commonly used measure of attentional control that includes two components: Focusing and Shifting. A latent variable (trait-state-occasion) model was applied to the two components.

Results

The results showed that although estimates of TI factor variance and TV factor variance were both significant for Focusing and Shifting, the proportion of TI factor variance (0.81, 0.77) was significantly greater than the amount of TV factor variance (0.18, 0.22). Furthermore, although TV factor stability was statistically significant for Focusing and Shifting, the size of the coefficients was small to moderate in magnitude. In predicting latent repetitive negative thinking at each of the six time points, regression weights for the attentional control TI factor were significant and larger than those for the TV factor (which were generally not significant).

Limitations

Relatively short timeframe of 5 months and exclusive reliance on self-report measures.

Conclusions

These findings suggest that self-reported attentional control is largely TI and that it is this TI component that predicts repetitive negative thinking.

Section snippets

Participants

A total of 1279 participants completed at least one survey as part of the present study. Participants were excluded from analyses if they scored more than two standard deviations above the sample mean on the Lie Scale (see Measures), leaving 1251 participants (87% female, 13% male, 0.2% declined to respond) with complete, valid data from at least one wave of the study. The mean age of the participants was 42.6 years (SD = 13.6 years), ranging from 18 to 71 years. The ethnicity composition was

Descriptive statistics and correlations

Means, standard deviations, and cross-wave correlations for the ACS Focusing and Shifting subscales, as well as measures of repetitive negative thinking, appear in Table 1. As expected, correlations between waves generally decreased as the lag between waves increased from one month to five months. Median over-time correlations for ACS Focusing were 0.83 for lag 1, 0.81 for lag 2, 0.79 for lag 3, 0.79 for lag 4, and 0.76 for lag 5. For ACS Shifting, median over-time correlations were 0.73 for

Discussion

Attentional control has been described as a trait that may have its effects on affective disorders by facilitating negative repetitive thinking (De Jong et al., 2019). Although preliminary evidence suggests that attentional control is stable over time (Booth et al., 2019), very little research has examined its longitudinal structure. In the current study, the trait-state model was applied to longitudinal data from an adult community sample that completed the ACS, the most commonly used measure

Authors contributions

Bunmi Olatunji was the coordinating investigator on the study. All authors contributed to the concept and design of the study. Bunmi Olatunji and Kelly Knowles contributed to data collection. Kelly Knowles and David Cole undertook the data analysis. All authors contributed to the critical interpretation of the data, drafting and revising the manuscript, and approved the final article for submission.

Declaration of competing interest

The authors have no conflict of interest to declare.

Role of funding source

None.

Acknowledgments

None.

References (65)

  • T.J. Meyer et al.

    Development and validation of the Penn state worry questionnaire

    Behav. Res. Ther.

    (1990)
  • A.C. Mills et al.

    Trait attentional control as a moderator between repetitive negative thinking and psychopathology symptoms

    Psychiatry Res.

    (2016)
  • P. Muris et al.

    Attentional control and psychopathological symptoms in children

    Pers. Individ. Dif.

    (2008)
  • R.P. Ólafsson et al.

    Self-reported attentional control with the Attentional Control Scale: factor structure and relationship with symptoms of anxiety and depression

    J. Anxiety Disord.

    (2011)
  • B.A. Sari et al.

    Training working memory to improve attentional control in anxiety: a proof-of-principle study using behavioral and electrophysiological measures

    Biol. Psychol.

    (2016)
  • R. Shi et al.

    A meta-analysis of the relationship between anxiety and attentional control

    Clin. Psychol. Rev.

    (2019)
  • I. Abasi et al.

    The psychometric properties of Attentional Control Scale and its relationship with symptoms of anxiety and depression: a study on Iranian population

    Iran J. Psychiatry

    (2017)
  • Y. Bar-Haim et al.

    Threat-related attentional bias in anxious and nonanxious individuals: a meta-analytic study

    Psychol. Bull.

    (2007)
  • C. Booth et al.

    The CogBIAS longitudinal study of adolescence: cohort profile and stability and change in measures across three waves

    BMC Psychol.

    (2019)
  • R.B. Cattell

    Patterns of change: measurement in relation to state-dimension, trait change, lability, and process concepts

    Handbook of Multivariate Experimental Psychology

    (1966)
  • D.A. Cole et al.

    Empirical and conceptual problems with longitudinal trait–state models: support for a trait–state–occasion model

    Psychol. Methods

    (2005)
  • R. De Raedt et al.

    Attentional control in depression: a translational affective neuroscience approach

    Cognit. Affect. Behav. Neurosci.

    (2010)
  • D. Derryberry et al.

    Anxiety-related attentional biases and their regulation by attentional control

    J. Abnorm. Psychol.

    (2002)
  • D. Derryberry et al.

    Arousal, affect, and attention as components of temperament

    J. Pers. Soc. Psychol.

    (1988)
  • H.J. Eysenck

    Cicero and the state-trait theory of anxiety: another case of delayed recognition

    Am. Psychol.

    (1983)
  • M.W. Eysenck et al.

    Anxiety and cognitive performance: attentional control theory

    Emotion

    (2007)
  • J. Fan et al.

    Assessing the heritability of attentional networks

    BMC Neurosci.

    (2001)
  • E. Fox et al.

    Attentional control and suppressing negative thought intrusions in pathological worry

    Clin. Psychol. Sci.

    (2015)
  • B. Gaertner et al.

    Attention in toddlers: measurement, stability, and relations to negative emotion and parenting

    Infant. Child. Dev.

    (2008)
  • J.R. Gagne et al.

    The shared etiology of attentional control and anxiety: an adolescent twin study

    J. Res. Adolescence

    (2017)
  • E.G. Helzer et al.

    Traits, states, and attentional gates: temperament and threat relevance as predictors of attentional bias to social threat

    Anxiety Stress Coping: An Int. J.

    (2009)
  • C. Hertzog et al.

    Beyond autoregressive models: some implications of the trait-state distinction for the structural modeling of developmental change

    Child. Dev.

    (1987)
  • Cited by (2)

    View full text