The cognitive load of poverty: From attention mechanisms to the role of income inequality
Résumé
Poverty is a phenomenon that tends to persist and reproduce itself (i.e., the ”vicious circle of poverty”). Whereas
social sciences have focused on the structural and political dynamics subtending the vicious circle of poverty,
behavioral sciences have rather focused on individuals’ behaviors that further perpetuate poverty. In that vein,
Mani, Mullainathan, Shafir and Zhao (2013) have proposed that low-income individuals would behave in
inappropriate ways because poverty imposes a cognitive load (via intrusive thoughts and worries), which
impedes cognitive functioning and subsequent behavior. In series of studies, they found that financial concerns
decreased low-income individuals performance on fluid intelligence and cognitive control tasks. The present
research (3 studies) first aims at identifying the attention mechanisms involved the cognitive load of poverty
(studies 1-2). Intrusive thoughts and worries may indeed highjack attention resources from any other ongoing
activity, thereby leading to performance decrements. Study 1 (online; N = 103 all comers adults) tested whether
low-income individuals’ attention is exhausted by concurrent financial concerns. Participants were randomly
assigned to one of the two conditions involving an experimental induction of either low or high financial
concerns. While thinking about how to solve these problems, participants performed a visual search game (20
Where’s Waldo puzzles) of various difficulty levels. Participants’ household income was finally collected. As
predicted, in the high-financial concerns condition, the lower the participants’ income the longer it took them to
perform the difficult visual task puzzles, thereby suggesting a shortfall of selective attention resources. Study 2
(lab experiment; N = 179 undergraduate students) further investigated the attention processes potentially
impacted by the cognitive load of poverty by using the Attentional Network Test allowing to assess three
attentional components: alerting, orienting and executive components. Given that suppressing interfering
thoughts solicits executive control, we hypothesized that low-income students specifically experience executive
attention impairments when high-financial concerns are experimentally induced. However and contrary to Study
1 (and to most studies in the literature), participants in Study 2 were undergraduate students whose current
financial situation was hard to assess given the diversity of social situations among students. As a consequence
our main IV (income) was not usable. Based on the literature, maternal level of education was then chosen as a
proxy for poverty. Results thus only provided a partial support for our prediction by showing that not income
but maternal education positively predicted students’ executive attention performance in the high-financial
concerns condition. As it happens, studying the psychological impact of poverty requires going beyond the mere
indicator of income. Study 3 (online; N = 776 US adults) therefore aimed at investigating how income
inequalities may further fuel the cognitive load of poverty. Based on the same design as Study 1, results
suggested that for participants living in areas heavily marked by income inequality (as measured by the GINI
coefficient), the lower their income and the lower their performance on the visual search task. Limits of and
perspectives on the cognitive load of poverty hypothesis are further discussed.