"Letter to my future self" as a device for assessing health education effectiveness.

Objective: To examine whether a "letter to my future self" analyzed using structural topic modeling (STM) represents a useful technique in revealing how participants integrate educational content into planned future behaviors.

Methods: 453 club-sports athletes in a concussion-education randomized control study wrote two-paragraph letters describing what they hoped to remember after viewing one of three randomly assigned educational interventions.

Results: A six-topic solution revealed three topics related to the content of the education and three topics related to the participant behavioral takeaways.

How Visual Aesthetics and Calorie Density Predict Food Image Popularity on Instagram: A Computer Vision Analysis.

Social media have become an important source where people are exposed to visual representations of foods. This study aims to understand what content factors contribute to the popularity of food images on Instagram. We collected 53,894 images from 90 popular food influencer accounts on Instagram over two years.

The role of ideological dimensions in shaping acceptance of facial recognition technology and reactions to algorithm bias.

Facial recognition technology has been introduced into various aspects of social life, yet it has raised concerns over its infringement of civil liberties and biases against minorities. This study investigates how three ideological dimensions-social dominance orientation, right-wing authoritarianism, and libertarianism-shape facial recognition acceptance. First, two surveys of crowdsourced workers ( = 891 and 587) demonstrated that the acceptance of facial recognition applications is positively associated with right-wing authoritarianism and negatively with libertarianism, whereas social dominance orientation shows little influence.

Politics of COVID-19 vaccine mandates: Left/right-wing authoritarianism, social dominance orientation, and libertarianism.

Mandatory and punitive vaccination policies, such as requiring vaccination certificates for public activities and firing employees who refuse vaccination, have raised considerable objections. With a sample of U.S.

Give me liberty or give me COVID-19: How social dominance orientation, right-wing authoritarianism, and libertarianism explain Americans' reactions to COVID-19.

While previous research has revealed an ideological divide in Americans' perceptions of COVID-19, specific ideological components can additionally explain public reactions to the pandemic. With two surveys-one sample of crowdsourced workers (N = 482) and a nationally representative sample of American adults (N = 7449)-this research investigates how multiple ideological facets simultaneously predict individuals' reactions to COVID-19. Results demonstrate that social dominance orientation and libertarianism are two important ideological sources that predict more dismissal of COVID-19 and less support for government measures.

Fitspiration on Instagram: Identifying Topic Clusters in User Comments to Posts with Objectification Features.

This study aimed to examine features of objectified images in popular fitspiration accounts on social media, identify the most prevalent user discussion topics about these images, and investigate the linkages between specific objectification cues and discussion topics. We employed content analysis to identify gender-specific objectification elements in fitspiration images ( = 2,000) on Instagram and unsupervised topic modeling to uncover topics in user comments ( = 35,263). Multilevel regressions were conducted to examine how gender and objectification features associate with the topics.

The ideological divide in public perceptions of self-driving cars.

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars.

The influence of weight-of-evidence strategies on audience perceptions of (un)certainty when media cover contested science.

Controversy in science news accounts attracts audiences and draws attention to important science issues. But sometimes covering multiple sides of a science issue does the audience a disservice. Counterbalancing a truth claim backed by strong scientific support with a poorly backed argument can unnecessarily heighten audience perceptions of uncertainty.