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PsyPost – Psychology News Daily Digest (Unofficial)

 

(https://www.psypost.org/new-study-finds-infidelity-fears-drive-both-affectionate-gestures-and-controlling-behaviors/) New study finds infidelity fears drive both affectionate gestures and controlling behaviors
Mar 12th 2025, 10:00

New research has confirmed that having participants imagine their partner cheating on them increases their jealousy. This, in turn, makes them more likely to use strategies intended to retain their partner by either inflicting costs (e.g., inducing jealousy, making threats) or providing benefits (e.g., giving gifts, showing affection). The research was published in (https://doi.org/10.1177/14747049241267226) Evolutionary Psychology.
Since the early days of human evolution, children have depended on both parents for care. This parental investment was facilitated by the tendency of humans to form monogamous, long-term romantic relationships. While such relationships are rare among sexually reproducing animal species, they are the norm in most human populations.
However, the formation of long-term romantic relationships and the reliance on them introduce unique challenges. One of the most significant challenges is infidelity—that is, a partner engaging in a romantic or intimate relationship with someone else and violating agreed-upon boundaries. To counteract this persistent threat, humans evolved jealousy, a negative emotion characterized by distress in response to a real or perceived threat to a valued relationship.
Study author Steven Arnocky and his colleagues sought to examine whether the perception that one’s partner might engage in infidelity would evoke feelings of jealousy. They also wanted to determine whether jealousy mediates the link between an experimentally induced threat of infidelity and mate retention behaviors. The researchers hypothesized that perceiving a threat of infidelity would lead participants to engage in mate retention behaviors that would persist over the following month.
The study involved 222 participants recruited via MTurk, including 97 women. The average participant age was 33 years, and 75% of participants identified as heterosexual. The researchers compensated them $1 for their time.
Participants were randomly assigned to one of two groups: the infidelity threat condition or the control condition. Those in the infidelity threat condition watched a one-minute TikTok video of a therapist discussing the prevalence of infidelity in committed relationships. After watching the video, they were asked to imagine that their romantic partner had become interested in someone else, was having sex with them, and was falling in love with that person. This exercise was designed to induce feelings of a perceived infidelity threat.
Participants in the control group watched a one-minute TikTok video featuring a negative food review. Afterward, they were asked to recall a time when they were excited about a meal but then found it disappointing.
Following these tasks, participants completed assessments of state jealousy (e.g., “At this moment, how jealous do you feel in your current romantic relationship?”) and mate retention behaviors using the 38-item Mate Retention Inventory Short Form.
The results showed that imagining a partner’s infidelity increased participants’ jealousy. In turn, participants who felt more jealous reported a higher likelihood of engaging in mate retention behaviors over the following month. These behaviors included both benefit-providing strategies (e.g., giving gifts, showing affection) and cost-inflicting strategies (e.g., inducing jealousy, making threats).
Benefit-providing mate retention behaviors enhance a partner’s satisfaction and commitment through actions such as giving gifts, expressing affection, or offering emotional support. In contrast, cost-inflicting mate retention behaviors aim to deter a partner from leaving by exerting control, inducing jealousy, or making threats—actions that can create emotional and physical distress.
“Participants exposed to an experimental infidelity threat condition reported higher state jealousy scores than those in the control condition. Jealousy, in turn, predicted more intended benefit-provisioning and cost-inflicting mate retention to be performed over the following month. These findings, which extend beyond extant cross-sectional tests of this model, support the perspective that jealousy plays a crucial role in responding to threats to mating relationships by motivating greater mate retention efforts,” the study authors concluded.
The study contributes to the scientific understanding of jealousy’s role in human behavior. However, its findings are limited by the use of MTurk participants, who may not be fully representative of the general population. Additionally, all measures were self-reported, leaving room for reporting bias to affect the results.
The paper, “(https://doi.org/10.1177/14747049241267226) An Experimental Test of Jealousy’s Evolved Function: Imagined Partner Infidelity Induces Jealousy, Which Predicts Positive Attitude Towards Mate Retention,” was authored by Steven Arnocky, Kayla Kubinec, Megan MacKinnon, and Dwight Mazmanian.

(https://www.psypost.org/artificial-intelligence-predicts-adolescent-mental-health-risk-before-symptoms-emerge/) Artificial intelligence predicts adolescent mental health risk before symptoms emerge
Mar 12th 2025, 08:00

A new study published in (https://www.nature.com/articles/s41591-025-03560-7) Nature Medicine demonstrates that artificial intelligence can identify adolescents at high risk for serious mental health problems before symptoms become severe. This innovative model goes beyond simply looking at current symptoms; it identifies underlying factors, such as disruptions in sleep patterns and conflicts within families, that contribute to these risks. This capability opens up the possibility of significantly improving access to mental health support, potentially making assessments and early interventions available through primary care doctors.
Rates of mental illness among young people have increased considerably, placing even greater pressure on already stretched mental health services. A major obstacle in improving mental health care is the difficulty in pinpointing which young people are most vulnerable and at the highest risk of developing psychiatric conditions. Being able to accurately predict which individuals in the general population will develop mental health problems would allow for a more efficient distribution of resources aimed at prevention.
“The United States is facing a youth mental health crisis. Almost 50% of teens will experience some form of mental illness, and of those, two-thirds will not get support from a mental
health professional,” explained study author (https://elliot-d-hill.github.io/) Elliot Hill ((https://bsky.app/profile/elliotdhill.bsky.social) @elliotdhill), an AI Health Fellow at Duke University School of Medicine.
“We wanted to test if AI could be used to help detect which children are most at risk of worsening mental health. If we can predict who is at risk, we can better allocate mental health resources to patients that need it the most to reduce the demand on over-burdened providers.”
The scientists used data from a large, ongoing study called the Adolescent Brain and Cognitive Development Study, which includes over 11,000 children across the United States. This study collects information about various aspects of these children’s lives, including their social environments, behaviors, and brain development, over several years. The researchers used this extensive data to train computer models known as neural networks. These models are designed to learn complex patterns from large amounts of data. The aim was to see if these models could predict a teenager’s future mental health risk based on information collected earlier.
The research team created two main types of prediction models. One type, called a symptom-driven model, was trained to predict future mental health risk based on the symptoms teenagers were already showing. This approach is similar to how risk is often assessed currently.
The other type, called a mechanism-driven model, was designed to predict risk based on potential underlying causes of mental health issues, such as problems with sleep, family difficulties, and stressful childhood experiences. This model did not rely on current symptoms. Both models used questionnaires completed by the teenagers and their parents. Some models also incorporated brain scans, obtained through a process called magnetic resonance imaging, to see if brain measurements could improve predictions.
To measure mental health risk, the researchers used a concept called the “p-factor.” The p-factor is a way of measuring general mental health difficulties across different types of problems, such as anxiety, depression, and behavioral issues. Instead of focusing on specific diagnoses, the p-factor provides a single score that reflects an individual’s overall level of psychological distress. The research team divided the teenagers into four groups based on their p-factor scores, ranging from no risk to high risk. The computer models were then trained to predict which risk group a teenager would fall into one year later.
The artificial intelligence model was able to predict which adolescents would develop serious mental health issues with high accuracy. The model trained on existing psychiatric symptoms achieved an accuracy score of 0.84, while the model trained solely on underlying causes reached a score of 0.75.
The findings indicate that “AI models trained on psychosocial and behavioral questionnaires can accurately predict future mental health risk while simultaneously suggesting potential targets for intervention,” Hill told PsyPost. “Our model highlighted the importance of sleep quality and prosocial behaviors for predicting future mental health risk.”
Among the various factors analyzed, sleep disturbances emerged as the strongest predictor of future psychiatric illness. The impact of sleep problems on mental health risk was greater than that of adverse childhood experiences or family mental health history. Adolescents with significant sleep disturbances were far more likely to transition into the highest-risk group within a year. Other influential factors included family conflict and low levels of parental monitoring.
“In the literature, adverse childhood experiences and family mental health history are often thought to be dominant predictors of future mental health,” Hill said. “While these factors were still strong predictors in our model, the influence of sleep quality on mental health predictions was even stronger. This is a hopeful finding because this factor is modifiable through evidence-based behavioral interventions.”
Interestingly, the inclusion of brain imaging data did not improve the model’s performance. This suggests that simple psychosocial questionnaires—rather than expensive and difficult-to-access neuroimaging measures—may be sufficient for identifying mental health risk. The findings indicate that artificial intelligence models could be used in routine healthcare settings, such as pediatric clinics or schools, to flag at-risk adolescents before they develop severe psychiatric conditions.
The researchers acknowledged some limitations to their study. The data came from a general population of teenagers, not specifically from young people already seeking mental health treatment. Therefore, it will be important to test these models in clinical settings to ensure they work effectively for those seeking help. Future research should also explore ways to make these prediction tools even more practical and accessible. This could involve identifying the smallest set of questionnaire questions needed to maintain accuracy, reducing the burden on individuals taking these assessments.
“Though the ABCD study was a general sample of the US population, it is possible that clinical populations are systematically different from the general population,” Hill explained. “Thus, it is vital to test our model in clinical settings before deploying it at large. Therefore, we are working on a grant to test this model in a clinical setting. We are targeting urban areas in North Carolina, as there is a critical shortage of mental health care providers in these areas.”
“This project was a diverse multidisciplinary collaboration between machine learning researchers, psychologists, psychiatrists, and neuroscientists. It would not have been possible without the help of my amazing co-authors.”
The study, “(https://doi.org/10.1038/s41591-025-03560-7) Prediction of mental health risk in adolescents,” was authored by Elliot D. Hill, Pratik Kashyap, Elizabeth Raffanello, Yun Wang, Terrie E. Moffitt, Avshalom Caspi, Matthew Engelhard and Jonathan Posner.

(https://www.psypost.org/hostile-tweets-linked-to-upbringing-and-legal-troubles-study-finds/) Hostile tweets linked to upbringing and legal troubles, study finds
Mar 12th 2025, 07:00

A new study published in the (https://www.pnas.org/doi/10.1073/pnas.2412277121) Proceedings of the National Academy of Sciences sheds light on why some people seem more aggressive on social media. By linking official government records to the online activity of Danish Twitter users, the researchers found that individuals with numerous criminal verdicts, more time spent in foster care, better performance in primary school, and higher childhood socioeconomic status tended to be more hostile in their social media interactions. A good portion of this behavior appears to be connected to the fact that these traits also predict whether a person actively discusses politics online, which itself is tied to higher levels of hostility.
The researchers undertook this investigation because aggression on social media has grown into a prominent concern. While early hopes for online platforms suggested they might create a friendlier, more connected world, many users have encountered the opposite. They see arguments, intimidation, and insults directed at strangers in ways that can create anxiety and discourage future online engagement. 
Past work has highlighted features of social media, such as relative anonymity or engagement-driven platform designs, that might inflame tensions. However, studies have also shown that the angriest interactions often come from a small fraction of users, hinting that stable, individual traits may be shaping who ends up launching hostile attacks online. The authors of the new study aimed to move beyond anecdotal observations or self-reported survey data by using broader, real-world administrative records and direct measurements of online behavior.
To carry out the study, the research team combined two kinds of data. First, they drew a large random sample of Danish adults, obtained their unique names, and gathered information from official national registries covering everything from criminal verdicts to childhood environments. Next, they searched for matching Twitter accounts by using each adult’s name to find a single, unique match on the platform. Only individuals who posted at least one tweet during the study period were included. 
In total, over 1.3 million Danish-language tweets from 4,931 users were analyzed. To gauge hostility, the researchers used a computer-based approach that rates each tweet by measuring how similar its wording is to common expressions of hatred. Experts had previously validated this method, confirming it could reliably capture the tone of the tweets. Finally, they created a separate measure of how often a user posted about politics by applying a similar technique keyed to political themes.
The investigators then connected people’s levels of online hostility with childhood and adult characteristics drawn from the official records. One of these attributes was the number of criminal verdicts a person had received. The researchers reasoned that repeated violations of the law might point to a long-standing inclination toward aggressive or antisocial behavior. They also looked at whether individuals experienced potential disruptions in childhood, including divorce in the family and multiple changes of address before the age of eighteen. 
Another factor was the amount of time, if any, spent in foster care. Since other research suggests that a harsher environment in early life can encourage aggression, the team used two indicators of background conditions: parents’ financial and occupational status, and how well participants performed in primary school. Finally, they examined the roles of age and sex, since past work has long noted that men and younger adults can show higher tendencies toward aggression.
Results revealed that people with more total criminal verdicts were more hostile on Twitter, and those who spent a greater portion of childhood in foster care tended to be more hostile as well. On the other hand, individuals with particularly strong childhood academic performance and higher socioeconomic family backgrounds also posted more hostile tweets. At first glance, one might assume that coming from a more resourceful family would reduce anger or aggression online. 
Yet the data suggest that those who grew up with better resources and skills were also more likely to talk about politics on Twitter, and political discussions were associated with more heated and confrontational posts. Men tended to show higher hostility compared to women, which is consistent with traditional findings in both psychological and criminological research. Younger people showed a slight tendency toward more hostile content, but this was less evident once political engagement was taken into account.
This study stands out for bringing together direct observations of online behavior and real-world, individual-level traits spanning decades. It points to a complex interplay between life history, personal dispositions, and the broader social media environment. One of the most interesting discoveries is that individuals with a greater inclination toward political debate appear more prone to writing hostile tweets, potentially because contentious topics encourage stronger language. 
And while factors such as criminal background align with higher aggression in digital settings, other traits often linked to social advantage—such as higher childhood socioeconomic status—also correlate with more hostile online behavior in large part due to increased political engagement. This challenges simple stereotypes of who is most likely to start heated exchanges.
“The key contribution of the findings is instead the demonstration that individual differences in the propensity to engage in online hostility is connected to broader offline dispositions including dispositions related to aggressiveness and, in particular, political engagement,” the researchers wrote.
The study does have limitations that are worth noting. The sample focuses on Danish Twitter users, raising questions about whether the same trends would appear in countries with different cultures or social structures. The measure of hostility relies on language patterns identified by a computer algorithm, which captures many shades of hateful or angry speech but may miss more subtle forms of rudeness, harassment, or intimidation. 
Also, while the connection to official data avoids some forms of bias that come with self-reported surveys, there are still other factors that likely shape hostile behavior that administrative data cannot capture, such as personality traits not flagged by criminal records or unique experiences that do not show up in government statistics. Future research might examine which features of social media platforms amplify the voices of aggressive users, as well as how everyday users perceive these confrontational individuals.
The study, “(https://doi.org/10.1073/pnas.2412277121) The offline roots of online hostility: Adult and childhood administrative records correlate with individual-level hostility on Twitter,” was authored by Stig Hebbelstrup Rye Rasmussen, Alexander Bor, and Michael Bang Petersen.

(https://www.psypost.org/the-surprising-age-when-cognitive-skills-actually-peak-and-how-to-keep-them-strong/) The surprising age when cognitive skills actually peak (and how to keep them strong)
Mar 12th 2025, 06:00

A new study published in (https://www.science.org/doi/10.1126/sciadv.ads1560) Science Advances challenges the widely held belief that cognitive skills begin to decline starting as early as age 30. Instead, researchers found that literacy and numeracy skills generally improve until at least age 40, after which they either stabilize or decline slightly. However, this decline is not inevitable. People who engage in frequent skill-related activities at work and in everyday life tend to maintain or even improve their cognitive abilities beyond their forties.
The researchers conducted this study to provide a more accurate picture of how cognitive skills change with age. Most previous research relied on cross-sectional data, which compares people of different ages at a single point in time. This approach can be misleading because it does not account for generational differences in education and skill development.
For example, an older person might score lower on a literacy test than a younger person, but this could reflect differences in their educational background rather than a true decline in ability over time. The researchers wanted to separate the effects of aging from these cohort differences by tracking the same individuals over time.
“Cognitive skills have a strong impact on an individual’s labor market earnings and on economic growth of countries. The aging of advanced societies around the world raises concerns about the pattern of skills with individual age. But the existing research had obvious limitations because it did not follow the skills of individuals but instead simply compared individuals of different ages,” explained study author (https://hanushek.stanford.edu/) Eric A. Hanushek, a senior fellow at the Hoover Institution of Stanford University.
For their new study, the researchers used data from the German longitudinal component of the Programme for the International Assessment of Adult Competencies (PIAAC-L). This project followed a large, representative sample of German adults who were tested on literacy and numeracy skills twice, with a gap of 3.5 years between assessments. This allowed the researchers to measure real changes in individual skills rather than relying on indirect comparisons between different age groups.
Skill usage was measured through a detailed questionnaire included in the initial PIAAC assessment. Participants reported how frequently they engaged in various reading and math-related activities both at work and in daily life. For reading, they indicated how often they read instructions, emails, articles, books, and reference materials. For numeracy, they reported activities such as calculating costs, using fractions or percentages, and interpreting graphs. Responses were recorded on a five-point scale, ranging from “never” to “every day.”
The research team used statistical methods to account for a common issue in repeated testing: measurement error. When people take tests, their scores are not perfectly accurate. There is always some degree of random fluctuation. This fluctuation can create a misleading impression of skill change over time, a phenomenon known as “reversion to the mean.”
Imagine someone scores very low on a test simply due to bad luck or random error. On a retest, their score is likely to be closer to their true skill level, making it seem like their skills have improved, even if they haven’t. The researchers employed statistical adjustments to minimize this bias and get a more accurate estimate of genuine skill changes with age.
After applying these adjustments, the researchers discovered a pattern quite different from what previous studies had suggested. On average, literacy and numeracy skills actually increased substantially into people’s forties. After this peak, literacy skills showed only a slight decline, while numeracy skills decreased more noticeably. However, these averages hid an important variation. When the researchers looked at skill changes in relation to how frequently people used their literacy and numeracy skills in their daily lives and at work, a striking difference emerged.
For individuals who reported using their skills more often than average, there was no sign of skill decline within the age range studied (up to age 65). In fact, their literacy and numeracy skills continued to improve into their fifties and then leveled off. In contrast, skill decline was primarily observed in individuals who reported below-average skill usage. This suggests that actively using cognitive skills throughout adulthood may be a key factor in maintaining or even improving them.
“Individual behavior dramatically affects the age pattern of cognitive skills,” Hanushek told PsyPost. “Those who use literacy or numeracy skills at home or work can lessen if not eliminate neurological patterns of skill decline.”
“The role of skill usage holds across a wide range of circumstances — across occupations, education levels, and life style differences such as quality of diet and exercise options. Within demographic and behavioral groups, those who use skills in normal activities tend to delay any aging effects on cognitive skills.”
The researchers also examined how these patterns differed across different groups of people. They found that individuals in white-collar jobs and those with higher levels of education, groups known to use their skills more frequently, showed increasing skill levels even beyond their forties, as long as they reported above-average skill usage. However, if people in these groups had below-average skill usage, this positive trend was not observed.
Another interesting finding was that women, on average, tended to experience larger skill losses at older ages, particularly in numeracy. This gender difference was not completely explained by differences in skill usage, suggesting other factors might be at play.
As with any study, there are some limitations to consider. The data only included adults up to age 65, so it cannot tell us about skill changes in older age groups. Also, the study was conducted in Germany, and it is uncertain whether these findings would be the same in other countries with different cultural and educational systems. Future research could investigate skill changes in older populations and in different countries to see how generalizable these results are.
In addition, the study focused only on literacy and numeracy. Future research could explore how other cognitive skills change with age and whether skill usage influences them in similar ways. While the study used robust statistical methods and longitudinal data, it remains observational, meaning it cannot establish cause and effect.
Despite these limitations, this research provides important insights into cognitive aging. It suggests that cognitive decline is not a uniform or inevitable process. Actively engaging our minds and regularly using our literacy and numeracy skills throughout adulthood may play a significant role in preserving and even enhancing these abilities as we age. This offers a more encouraging perspective on aging and highlights the potential for lifelong learning and cognitive engagement to support healthy cognitive function throughout life.
“This work is part of a long term research program into the determinants of cognitive skill differences and the economic and social impacts of any differences,” Hanushek explained. “We see more and more that skill differences have strong impacts on both individuals and nations.”
The study, “(https://www.science.org/doi/full/10.1126/sciadv.ads1560) Age and cognitive skills: Use it or lose it,” was authored by Eric A. Hanushek, Lavinia Kinne, Frauke Witthöft, and Ludger Woessmann.

(https://www.psypost.org/ai-reveals-why-people-really-exercise-and-how-they-stay-motivated/) AI reveals why people really exercise and how they stay motivated
Mar 11th 2025, 14:00

A recent study from Tel Aviv University has used artificial intelligence tools for the first time to uncover the key reasons people engage in physical activity and the most effective strategies for maintaining a fitness routine. By analyzing thousands of posts from the social media platform Reddit, researchers found that nearly one in four users (23.9%) exercise primarily to improve their physical appearance, while others cited maintaining physical health (18.9%) and mental health (16.9%) as their main motivations. The paper was published in the (https://doi.org/10.2196/54489) Journal of Medical Internet Research (JMIR).
Despite the well-known health benefits of exercise, a large portion of the population fails to engage in sufficient physical activity. Research has shown that more than 80% of adolescents and over a quarter of adults do not meet the minimum exercise guidelines recommended by the World Health Organization. Understanding what drives people to start and stick with an exercise routine is essential for designing interventions that encourage more consistent physical activity.
Traditionally, studies on exercise motivation have relied on surveys and structured interviews. While these methods provide useful information, they are prone to several biases. Participants may not represent the broader population, as individuals who volunteer for these studies tend to have specific characteristics that set them apart from non-volunteers. Additionally, people responding to surveys might modify their answers to align with what they believe the researchers want to hear. These issues can lead to an inaccurate picture of what truly motivates people to exercise.
To address these challenges, researchers at Tel Aviv University turned to social media as a data source. Platforms like Reddit provide a space where people share their thoughts and experiences freely, often with a level of honesty that is difficult to capture through traditional research methods. By analyzing thousands of real-world discussions, the researchers aimed to gain an unfiltered understanding of why people exercise and what helps them stay committed.
How the researchers conducted their study
The research team used artificial intelligence and machine learning techniques to scan Reddit posts related to exercise and motivation. They first identified popular subreddits where users frequently discussed physical activity, such as r/Fitness, r/bodyweightfitness, and r/crossfit, as well as broader discussion groups like r/askReddit, r/askMen, and r/askWomen. After filtering out irrelevant posts, they collected a final dataset of 1,850 unique comments spanning discussions from 2017 to 2021.
To categorize these comments, the researchers used advanced text analysis tools. They employed a machine learning model to cluster similar statements together and then worked with exercise science experts to verify and refine these clusters. Through this process, the study identified ten major themes, which were divided into two categories: reasons for starting an exercise routine (motivations) and strategies for maintaining one (adherence strategies).
The analysis revealed that the primary reason people exercise is to improve their physical appearance, with 23.9% of users mentioning this as their main motivation. Many participants described how they exercised to lose weight, build muscle, or achieve a particular body shape. This finding suggests that while people may outwardly claim they exercise for health reasons, aesthetic goals often play a more significant role in their decision to work out.
The second most common motivation, cited by 18.9% of users, was maintaining physical health. These individuals discussed the importance of exercise for preventing illness, managing chronic conditions, and enhancing overall well-being. Meanwhile, 16.9% of users exercised primarily for mental health benefits, describing how physical activity helped them manage stress, anxiety, and depression.
“Researchers in our field usually rely on cumbersome old-school questionnaires, containing inherent biases, to understand why people engage in sports and what strategies help them adhere to physical activity,” explained Yftach Gepner, one of the study’s authors. “It’s an astonishing phenomenon: science tells us that if we put just over two hours a week into physical activity, we can prevent 30% of diseases, improve our quality of life, and extend our lifespan; and yet, less than a quarter of the population actually does this. Why? What have we failed to see? While we all wish our loved one’s good health on their birthday, a wish of ‘good workouts’ is quite rare… But there is a way to be healthy – by exercising. That’s why it’s crucial to understand what really motivates people to engage in physical activity and what helps them stick with it.”
“Our findings are not based on self-reporting, a representative sample, a questionnaire, or a survey. This is, in plain terms, the real reason why people exercise. And the answer is that people mainly exercise to look good. In questionnaires, people claim they want to be healthy, but in reality, they want six-pack abs. These findings are important because they teach us how to address the public, how to persuade people to get off the couch, promote health, and prevent disease.”
Beyond motivation, the study also examined the strategies people use to stay committed to exercise. The most frequently mentioned approach, cited by 30% of users, was habit formation. Many users emphasized the importance of making exercise a routine part of daily life, rather than relying on fluctuating motivation. Other effective strategies included goal setting (13.9%), choosing enjoyable activities (12.1%), socializing (9.7%), and using digital tools such as fitness apps and online workout videos (8.9%).
“The results are quite significant,” Gepner said. “One strategy is more successful and therefore more recommended than others—creating exercise habits. If you want to be healthier, you need to develop healthy habits, period. Instead of a morning cigarette, drink two glasses of water and go out for a run. 30% is an empirical statistic that is hard to argue with, so as the Head of the Department of Health Promotion, I can confidently say to the public: develop habits and be healthy.”
Interestingly, the study also analyzed changes in exercise motivation during the COVID-19 pandemic. During this period, there was a noticeable increase in users citing physical health and mental health as primary motivators, while motivations related to appearance declined. This shift suggests that external factors, such as a global health crisis, can influence why people choose to stay active.
While this study provides valuable insights into exercise motivation, it also has certain limitations. The findings are based on self-reported discussions from a specific group of Reddit users, who may not represent the general population. Reddit tends to attract younger, more tech-savvy individuals, and the perspectives shared on the platform may not fully reflect those of older adults or people who do not engage with online fitness communities.
Additionally, because the study relied on publicly available posts, it could not gather demographic information about the users, such as their age, gender, or fitness levels. Future research could use more targeted data collection methods to examine how different groups of people experience exercise motivation differently.
Despite these limitations, the study offers a new approach to understanding fitness behaviors. By leveraging artificial intelligence and analyzing real-world conversations, researchers can gain deeper insights into how people think about exercise. This knowledge can help shape public health messaging, fitness programs, and digital tools designed to encourage long-term physical activity.
The study, “(https://www.jmir.org/2025/1/e54489) Analysis of Reddit Discussions on Motivational Factors for Physical Activity: Cross-Sectional Study,” was authored by Michal Shmueli-Scheuer, Yedidya Silverman, Israel Halperin, and Yftach Gepner.

(https://www.psypost.org/trigger-warnings-reduce-appreciation-of-visual-art-study-finds/) Trigger warnings reduce appreciation of visual art, study finds
Mar 11th 2025, 12:00

A study published in (https://psycnet.apa.org/record/2023-75193-001) Psychology of Aesthetics, Creativity, and the Arts suggests that content warnings on visual art can lower viewers’ aesthetic appreciation while increasing negative emotional responses. The research found that when participants were shown paintings accompanied by content warnings, they rated the artwork as less attractive and pleasant compared to when no warning was provided. The presence of warnings also heightened feelings of sadness, anger, and anxiety.
Content warnings, also known as trigger warnings, are alerts provided before content that may contain themes related to traumatic or distressing experiences. These warnings are intended to prepare viewers, readers, or listeners for potentially upsetting material, allowing them to either brace themselves emotionally or choose to avoid exposure. Originally used in online forums and academic settings, content warnings have since become common in various domains, including art galleries, museums, and social media.
Despite their widespread adoption, research on their effectiveness has produced mixed results. Prior studies suggest that content warnings increase anticipatory anxiety but have little to no effect on avoidance behavior or emotional responses to the content itself. However, most of this research has focused on literature, films, and academic material, leaving open the question of how content warnings influence aesthetic appreciation and emotional reactions to visual art.
The researchers conducted this study to investigate whether content warnings alter the way people experience and evaluate art. Art appreciation involves both cognitive interpretation and emotional engagement, meaning that a preemptive warning could shape how viewers process an artwork’s meaning and impact. While some theories suggest that content warnings might help people engage with challenging art in a more thoughtful way, others propose that they could bias viewers toward focusing on distressing elements, reducing their ability to appreciate the work as a whole.
“I’m a PTSD researcher. I became interested in trigger warnings when I read (https://www.nytimes.com/roomfordebate/2016/09/13/do-trigger-warnings-work/if-you-need-a-trigger-warning-you-need-ptsd-treatment) a New York Times article by my advisor, in which he argued that trigger warnings were countertherapeutic for PTSD because they encourage people to avoid their traumatic memories — the exact opposite of what we do in therapy. At that moment I had the epiphany that many debates about trigger warnings were perfectly suitable for being studied scientifically,” explained study author Payton Jones, an independent research psychologist who wrote (https://dash.harvard.edu/entities/publication/d486ca16-81e5-4d3e-863b-dfceba789381) his PhD dissertation about the “Neurotic Treadmill.”
To test this, the researchers conducted an experiment with 213 participants. Each person was shown six randomly assigned pieces of visual art, some of which were preceded by a content warning that described its potentially sensitive subject matter. For example, the 1861 painting Phryne before the Areopagus by Jean-Léon Gérôme was sometimes prefaced with the label: “content warning: sexual assault.” In other cases, no warning was given, and only the artist’s name and the year of creation were displayed.
Participants were asked to rate each piece on various aspects of aesthetic appreciation, such as attractiveness and interestingness, as well as to report their emotional responses. They were also given the option to skip viewing the artwork if they wished.
The study found that content warnings had a noticeable effect on how people engaged with the artwork. When a warning was included, participants rated the art as less aesthetically pleasing, particularly in terms of attractiveness and pleasantness. While some aspects of appreciation, such as how innovative or interesting a piece was, were less affected, there were no cases in which a content warning enhanced artistic appreciation.
In addition to lowering aesthetic ratings, content warnings significantly altered participants’ emotional reactions. Those who viewed art with warnings reported stronger negative emotions, including sadness, anger, and anxiety, while also experiencing less positive emotion, such as happiness or excitement. This suggests that warnings may prime viewers to focus on the distressing aspects of an artwork rather than appreciating it holistically.
“At this point there are many studies on trigger warnings, and almost all of them show that trigger warnings are inert, or that they have a very weak effect,” Jones told PsyPost. “So I was surprised that we found substantial effects in this study that made a tangible difference in how people view art. We can’t be completely sure why this study was different, but I’d speculate it has to do with how ambiguous art can be compared to materials used in other studies. Unlike, say, a scary movie clip, it’s relatively easy to shape how people feel about art based on the way it’s presented.”
Despite these emotional effects, no participants avoided viewing any of the artworks, even though they were explicitly given the option to do so. This aligns with previous research indicating that content warnings do not generally encourage avoidance behavior. People may feel compelled to engage with the material regardless of the warning, or they may not interpret the warning as a genuine invitation to opt out.
“I was also surprised that literally not a single participant avoided viewing any of the artwork in the study,” Jones said. “To see the artwork in our study, you had to actively click through the trigger warning. I knew from previous studies that avoidance was rare, even with a trigger warning — but with such a large sample size, I was surprised it was a literal zero.”
The findings highlight how “seemingly-kind actions often have unintended consequences,” he explained. “People who put trigger warnings on art never intend to take away from the art’s beauty — but that’s the result.”
But the study, like all research, has some limitations. For instance, while it showed that content warnings impact artistic appreciation and emotional response, it did not determine why this occurs. One possibility is that warnings direct viewers’ attention to the most distressing aspects of an artwork, shifting their focus away from other elements such as technique or symbolism.
Another factor could be the ambiguity of art itself—because art is open to interpretation, warnings might shape viewers’ perceptions in ways that would not occur with more straightforward content like news articles or film clips. Further studies could also explore alternative ways of contextualizing challenging artwork without diminishing its aesthetic impact.
“This is the first study to look at trigger warnings for artwork specifically,” Jones said. “So I’d give the same advice I give for all social science studies — you should absolutely wait for replications before you form a strong opinion.”
“That said, the research on trigger warnings more broadly (not just for artwork) is much larger, and so far has replicated quite well. So I feel somewhat more confident in, say, the general conclusion that trigger warnings lack substantial positive benefits.”
“When we published our first study on trigger warnings, there had already been several years of fierce political debate, but zero studies!” Jones added. “My hope is that for similar contentious topics in the future, scientists can act a little faster. I’m also proud that trigger warnings research has involved researchers with a wide variety of political viewpoints who have collaborated and approached the topic in a way that attempts to separate the empirical issues from the moral ones.”
“I think at the moment, the American public feels they cannot trust social science to deliver answers they can trust. Sadly, as a social scientist, I’m inclined to agree that my field is truly unworthy of trust. So while I’m proud of this line of research, I think we have a very long way to go. I’d love it if we could restore some of that trust, but it has to be earned.”
The study, “(https://psycnet.apa.org/doi/10.1037/aca0000586) Content Warnings Reduce Aesthetic Appreciation of Visual Art,” was authored by Payton J. Jones, Victoria M. E. Bridgland, and Benjamin W. Bellet.

Forwarded by:
Michael Reeder LCPC
Baltimore, MD

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