An official website of the United States government
Background People’s health-related knowledge influences health outcomes, as this knowledge may influence whether individuals follow advice from their doctors or public health agencies. Yet, little attention has been paid to where people obtain health information and how these information sources relate to the quality of knowledge. Objective We aim to discover what information sources people use to learn about health conditions, how these sources relate to the quality of their health knowledge, and how both the number of information sources and health knowledge change over time. Methods We surveyed 200 different individuals at 12 time points from March through September 2020. At each time point, we elicited participants’ knowledge about causes, risk factors, and preventative interventions for 8 viral (Ebola, common cold, COVID-19, Zika) and nonviral (food allergies, amyotrophic lateral sclerosis [ALS], strep throat, stroke) illnesses. Participants were further asked how they learned about each illness and to rate how much they trust various sources of health information. Results We found that participants used different information sources to obtain health information about common illnesses (food allergies, strep throat, stroke) compared to emerging illnesses (Ebola, common cold, COVID-19, Zika). Participants relied mainly on news media, government agencies, and social media for information about emerging illnesses, while learning about common illnesses from family, friends, and medical professionals. Participants relied on social media for information about COVID-19, with their knowledge accuracy of COVID-19 declining over the course of the pandemic. The number of information sources participants used was positively correlated with health knowledge quality, though there was no relationship with the specific source types consulted. Conclusions Building on prior work on health information seeking and factors affecting health knowledge, we now find that people systematically consult different types of information sources by illness type and that the number of information sources people use affects the quality of individuals’ health knowledge. Interventions to disseminate health information may need to be targeted to where individuals are likely to seek out information, and these information sources differ systematically by illness type.
more »
« less
When and Why People Conceal Infectious Disease
People sick with infectious illnesses face negative social outcomes, like exclusion, and may take steps to conceal their illnesses from others. In 10 studies of past, current, and projected illness, we examined the prevalence and predictors of infection concealment in adult samples of U.S. university students, health-care employees, and online crowdsourced workers (total N = 4,110). About 75% reported concealing illness in interpersonal interactions, possibly placing others in harm’s way. Concealment motives were largely social (e.g., wanting to attend events like parties) and achievement oriented (e.g., completing work objectives). Disease characteristics, including potential harm and illness immediacy, also influenced concealment decisions. People imagining harmful (vs. mild) infections concealed illness less frequently, whereas participants who were actually sick concealed frequently regardless of illness harm, suggesting state-specific biases underlying concealment decisions. Disease concealment appears to be a widely prevalent behavior by which concealers trade off risks to others in favor of their own goals, creating potentially important public-health consequences.
more »
« less
- Award ID(s):
- 2134796
- PAR ID:
- 10487921
- Publisher / Repository:
- Association for Psychological Science
- Date Published:
- Journal Name:
- Psychological Science
- ISSN:
- 0956-7976
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract People believe they should consider how their behavior might negatively impact other people, Yet their behavior often increases others’ health risks. This creates challenges for managing public health crises like the COVID-19 pandemic. We examined a procedure wherein people reflect on their personal criteria regarding how their behavior impacts others’ health risks. We expected structured reflection to increase people's intentions and decisions to reduce others’ health risks. Structured reflection increases attention to others’ health risks and the correspondence between people's personal criteria and behavioral intentions. In four experiments during COVID-19, people (N = 12,995) reported their personal criteria about how much specific attributes, including the impact on others’ health risks, should influence their behavior. Compared with control conditions, people who engaged in structured reflection reported greater intentions to reduce business capacity (experiment 1) and avoid large social gatherings (experiments 2 and 3). They also donated more to provide vaccines to refugees (experiment 4). These effects emerged across seven countries that varied in collectivism and COVID-19 case rates (experiments 1 and 2). Structured reflection was distinct from instructions to carefully deliberate (experiment 3). Structured reflection increased the correlation between personal criteria and behavioral intentions (experiments 1 and 3). And structured reflection increased donations more among people who scored lower in cognitive reflection compared with those who scored higher in cognitive reflection (experiment 4). These findings suggest that structured reflection can effectively increase behaviors to reduce public health risks.more » « less
-
Previous studies, both in psychology and linguistics, have shown that individuals with mental illnesses show deviations from normal language use, that these differences can be used to make predictions, and used as a diagnostic tool. Recent studies have shown that machine learning can be used to predict people with mental illnesses based on their writing. However, little attention is paid to the interpretability of the machine learning models. In this talk we will describe our analysis of the machine learning models, the different language patterns that distinguish individuals having mental illnesses from a control group, and the associated privacy concerns. We use a dataset of Tweets that are collected from users who reported a diagnosis of a mental illnesses on Twitter. Given the self-reported nature of the dataset, it is possible that some of these individuals are actively talking about their mental illness on social media. We investigated if the machine learning models are detecting the active mentions of the mental illness or if they are detecting more complex language patterns. We then conducted a feature analysis by creating feature vectors using word unigrams, part of speech tags and word clusters and used feature importance measures and statistical methods to identify important features. This analysis serves two purposes: to understand the machine learning model, and to discover language patterns that would help in identifying people with mental illnesses. Finally, we conducted a qualitative analysis of the misclassifications to understand the potential causes for the misclassifications.more » « less
-
Abstract This study examined the development of children's avoidance and recognition of sickness using face photos from people with natural, acute, contagious illness. In a U.S. sample of fifty-seven 4- to 5-year-olds (46% male, 70% White), fifty-two 8- to 9-year-olds (26% male, 62% White), and 51 adults (59% male, 61% White), children and adults avoided and recognized sick faces (ds ranged from 0.38 to 2.26). Both avoidance and recognition improved with age. Interestingly, 4- to 5-year-olds' avoidance of sick faces positively correlated with their recognition, suggesting stable individual differences in these emerging skills. Together, these findings are consistent with a hypothesized immature but functioning and flexible behavioral immune system emerging early in development. Characterizing children's sickness perception may help design interventions to improve health.more » « less
-
Framing public-health behaviors as benefiting others, rather than the self, can increase behavior uptake in adults. However, there are mixed results on the effects of such messaging in a vaccination context, and it is unclear how children reason about the social and moral implications of vaccination. In this study, we present school-aged children ( N = 60) with hypothetical vaccine-like behaviors and manipulate whether they benefit the self or others, and whether they prevent low or high severity harm. We find that children readily endorse these behaviors when they prevent high severity harm, and that the beneficiary of the behavior does not impact children’s endorsement. Younger children thought vaccine-like behaviors were morally important regardless of who they protected; However, as children get older, they thought about the vaccine-like behaviors in moral terms when they protected others. We discuss potential implications for how communications about vaccination may impact children’s reasoning about others.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1177/09567976231221990
