Looks interesting: Attention allocation in depression when using a news website - An eye tracking study

J Affect Disord. 2022 May 1:304:113-121. doi: 10.1016/j.jad.2022.02.058. Epub 2022 Feb 24.

Abstract

Background: Eye-tracking-based attention research has shown attentional biases toward dysphoric and away from positive stimuli in depression. However, most research used prototypical stimuli (co-presented contrasting emotional faces/pictures), less reflective of real-life situations. The current study addressed this limitation by examining participants' attentional allocation patterns while freely viewing a news website containing dysphoric and positive news articles.

Methods: Participants with high levels of depression (HD; n = 30) and with minimal levels of depression (MD; n = 30) freely viewed a fictitious news website for 3.5 min, containing six articles (picture + text) with dysphoric content and six with positive content. Gaze patterns on corresponding areas of interest (AOIs) were compared. Following the task, participants rated each article's valence, authenticity, and interest.

Results: Compared to MD participants, HD participants spent more time dwelling on dysphoric articles and less time dwelling on positive articles. Within group analyses showed that while HD participants spent more time dwelling on dysphoric compared to positive articles, MD participants showed no preference, allocating their attention equally to both article types. Echoing within-group gaze patterns, HD participants rated the dysphoric articles as being more interesting than the positive articles, while MD participants rated both types of articles as being equally interesting.

Conclusion: Attentional biases in depression were also evident when using a more ecologically valid task such as viewing a news website, manifesting as increase attention allocation to dysphoric over positive content. This attention pattern may be related to corresponding differences in the level of interest participants found in each article type.

Keywords: Attention allocation; Attention bias; Depression; Eye tracking; News websites.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Attention
  • Attentional Bias*
  • Depression / psychology
  • Emotions
  • Eye-Tracking Technology*
  • Humans