Mapping children's and adolescents' judgment rules for assessing the risk of disease transmission from sick friends

Abstract

Knowing the way children and adolescents assess the risk of disease transmission is important because this kind of knowledge may allow health caregivers to better communicate with them. We had 587 students in Spain and France aged 7–16 judge the risk of disease transmission in 28 scenarios of students visiting a sick friend. The scenarios were composed according to a three within‐subject orthogonal design: type of contact (from no contact to prolonged close contact), type of disease (contagious vs. noncontagious), and number of contacts. Cluster analysis revealed six main clusters, labeled “Contagion can never been ruled out,” “Depends on type of physical contact,” “Depends on type of disease,” “Depends simultaneously on contact and disease,” “Depends conjunctively on contact and disease,” and “Categorical thinking.” The composition of these clusters depended strongly on age level. From a practical perspective, even 7‐year‐olds seem to be fully aware of the issue of contagion, although they overgeneralize the risk. As a result, progress in understanding might be best achieved through a process of unlearning rather than learning. Highlights We examined the way children and adolescents judge the risk of contagion. Five hundred eighty‐seven students aged 7–16 judged the risk of disease transmission in 28 scenarios of students visiting a sick friend that were composed according to a three within‐subject design: type of contact × type of disease × number of contacts. Six judgment rules were found. They were labeled “Contagion can never been ruled out,” “Depends on type of contact,” “Depends on type of disease,” “Depends simultaneously on contact and disease,” “Depends conjunctively on contact and disease,” and “Categorical thinking.” Even 7‐year‐olds seemed to be fully aware of the issue of contagion, although they overgeneralize the risk. As a result, progress in understanding might be best achieved through a process of unlearning rather than learning.

Young children’s ability to make predictions about novel illnesses

“…By 7 years of age, children use information about the type of disease (contagious vs. not contagious), type of contact (varying levels of physical contact), and frequency of contact to make predictions about the risk of contagion from a sick person (Muñoz Marco et al, 2017).…”

“…When provided with competing explanations about why someone got sick, they are more likely to select biological explanations for illness (e.g., explanations that invoke germs or bodily fluids) than explanations that rely on desires or punishment for bad behavior (Hatano & Inagaki, 2013; Kalish, 1997; Siegal, 1988; Slaughter & Lyons, 2003; Springer & Ruckel, 1992). By 7 years of age, children use information about the type of disease (contagious vs. not contagious), type of contact (varying levels of physical contact), and frequency of contact to make predictions about the risk of contagion from a sick person (Muñoz Marco et al, 2017). Perhaps, children can derive a simple strategy from these early conceptual foundations to inform their predictions about illness, which would not require a detailed understanding of germs, invisible particles, or causality.…”

Mapping Risk Judgment and Risk Taking in Mountain Hiking: An Information Integration Approach

“…All five elements had a significant impact on judgments of well-being, and two well-being judgment positions were identified, with each characterized by different cognitive processes (an additive rule in the moderate well-being position and a disjunctive rule in the high well-being position), and with both associated with the participants' age. Muñoz Marco et al (2017) mapped how children and adolescents judged the risk of catching a disease from sick friends. They estimated this risk transmission in scenarios that were constituted from information about type of contact, type of disease, and number of contacts, and they identified six risk judgment positions.…”

“…The information integration approach has also been used to map different judgment and decision positions in sport (e.g., Fruchart & Rulence-Pâques, 2020) and different views of risk in the health domain (e.g., Muñoz Marco et al, 2017). Fruchart and Rulence-Pâques (2020) mapped how adolescents, young adults, and middle-aged adults cognitively combined five elements when estimating the level of well-being in sport.…”

“…By means of cluster analysis, this approach can describe potential radically different positions within raw data (in contrast to the use of an individual design) and reveal individual differences in information integration processes. Recent applications of this technique can be found in sport psychology (e.g., Fruchart & Rulence-Pâques, 2020) and health (e.g., Muñoz Marco et al, 2017). Fruchart and Rulence-Pâques (2020) mapped how adolescents, young adults, and middle-aged adults cognitively combined five elements when estimating their level of well-being in sport.…”