<table style="border:1px solid #adadad; background-color: #F3F1EC; color: #666666; padding:8px; -webkit-border-radius:4px; border-radius:4px; -moz-border-radius:4px; line-height:16px; margin-bottom:6px;" width="100%">
<tbody>
<tr>
<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">PsyPost – Psychology News</span></td>
</tr>
<tr>
<td> </td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/new-study-highlights-power-not-morality-as-key-motivator-behind-competitive-victimhood/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">New study highlights power—not morality—as key motivator behind competitive victimhood</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 21st 2025, 10:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A new study published in the <em><a href="https://doi.org/10.1111/jasp.13078" target="_blank">Journal of Applied Social Psychology</a></em> has reinforced previous findings that the desire for power—rather than a need to protect moral identity—is the strongest driver of competitive victimhood in groups experiencing intergroup conflict. By replicating a 2019 study in the unique context of the COVID-19 pandemic, researchers found that both Jewish and Arab citizens of Israel who felt a stronger need for group-based power were more likely to see their group as having suffered more than the other, a pattern known to hinder reconciliation.</p>
<p>Competitive victimhood, the belief that one’s own group has endured more suffering than an opposing group, is common in protracted conflicts and tends to worsen intergroup tensions. Past research has shown that it can justify hostility, reduce empathy, and block peace-building efforts. While some researchers have suggested that people engage in competitive victimhood to restore their group’s moral image, others argue that a desire to gain or maintain power is the more important driver.</p>
<p>To test which motivation is stronger, researchers aimed to replicate a prior study by <a href="https://doi.org/10.1111/bjso.12276" target="_blank">Kahalon and colleagues</a>, which found that <a href="https://www.psypost.org/study-finds-the-need-for-power-predicts-engaging-in-competitive-victimhood/" target="_blank">the need for power was a better predictor</a> of competitive victimhood than the need for morality. The new study was conducted in April 2020, shortly after Israel’s first wave of COVID-19 infections, during a national lockdown. The researchers wanted to see whether these earlier findings would still hold in the face of a shared external threat—one that might encourage solidarity or diminish competition between groups.</p>
<p>The study surveyed 357 participants living in Israel: 205 Jewish Israelis and 152 Arab Israelis. Participants were recruited via social media and completed an online questionnaire measuring various psychological factors. These included their identification with their ethnic group, views on the legitimacy and stability of group status relations, perceived commonality with other groups, and their needs for power and morality. They were also asked to rate how much they believed their group had suffered compared to the other—an indicator of competitive victimhood.</p>
<p>To ensure consistency, the survey used the same wording and structure as the original 2019 study. Measures included items such as “It is of highest priority for me that the group of Arabs/Jews in Israel become more powerful” (to assess need for power) and “I wish the Arabs/Jews would perceive us, Jews/Arabs, as moral” (to assess need for morality). Competitive victimhood was measured by agreement with statements like “People must know that those who suffer more from discrimination in Israel are the Jews/Arabs.”</p>
<p>The study confirmed the earlier finding that Arab participants, as members of a disadvantaged group, reported higher levels of competitive victimhood than Jewish participants. Arab participants also reported stronger needs for both power and morality compared to Jewish participants.</p>
<p>Importantly, both groups showed a correlation between greater needs for power and morality and stronger engagement in competitive victimhood. But when both motivations were analyzed together, only need for power remained a significant predictor. This was true for both Arabs and Jews. The need for morality did not predict competitive victimhood when controlling for the need for power.</p>
<p>For Arab participants, the strength of the relationship between power needs and competitive victimhood was even greater than in the original 2019 study, suggesting that the COVID-19 context may have amplified status concerns. Among Jewish participants, need for power also remained a robust predictor, while the need for morality had no significant effect.</p>
<p>An exploratory analysis examined whether the effect of morality might operate indirectly through power. In both groups, the researchers found that the relationship between moral motivation and competitive victimhood was indeed mediated by the desire for power. In other words, people who said they wanted to be seen as moral may have ultimately been motivated by a deeper wish for power and status.</p>
<p>Perceived commonality—feelings of “being in the same boat”—also played a role, though not uniformly. Among Jews, stronger feelings of commonality with other groups were associated with less competitive victimhood. Among Arabs, the opposite pattern emerged: stronger commonality was linked to more competitive victimhood, though this effect disappeared in more complex statistical models. This finding may reflect differing interpretations of shared experience between advantaged and disadvantaged groups.</p>
<p>The study was conducted during a unique period of global crisis, which could have influenced how participants viewed their relationships with other groups. Although the pandemic created shared risks and hardships, the specific impact of COVID-19 in Israel disproportionately affected Arab citizens, potentially reinforcing perceptions of inequality. The study did not directly measure perceived threat or the extent to which participants felt solidarity with the other group due to the pandemic.</p>
<p>Another limitation involves the measurement of motivation. The need for power was assessed using items that may overlap with other concepts such as social dominance, which involves a preference for hierarchical relations between groups. Future research could benefit from refining these measures to distinguish different types of power motives—such as empowerment versus control.</p>
<p>Future research might also explore how power and morality needs interact with broader factors like justice, group norms, or efforts to restore equality. For example, it is possible that some claims of victimhood are driven not by a desire to gain power over others, but to restore fairness and recognition. The motivations underlying competitive victimhood may vary depending on historical context, group status, and the perceived legitimacy of grievances.</p>
<p>The study, “<a href="https://doi.org/10.1111/jasp.13078" target="_blank">Replicating What Motivates Conflicting Groups to Engage in Competitive Victimhood: The Roles of Need for Power and Need for Morality</a>,” was authored by Samer Halabi, Noor Masi, and John F. Dovidio.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/attractiveness-shapes-beliefs-about-whether-faces-are-real-or-ai-generated-study-finds/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Attractiveness shapes beliefs about whether faces are real or AI-generated, study finds</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 21st 2025, 08:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A new study published in <em><a href="https://doi.org/10.1016/j.actpsy.2024.104670" target="_blank">Acta Psychologica</a></em> sheds light on how people decide whether a face is real or artificially generated—and the answer may have more to do with personality and perception than objective clues. Despite viewing only authentic photographs of real people, most participants in the study confidently labeled many faces as fake. Their judgments were strongly influenced by subjective impressions of attractiveness and trustworthiness, as well as personality traits like narcissism and honesty-humility.</p>
<p>As artificial intelligence becomes more capable of producing realistic images, especially of faces, the boundaries between what is real and what is synthetic are becoming harder to identify. In this rapidly changing landscape, understanding how people determine the authenticity of images is increasingly important. The researchers sought to explore which psychological factors drive these judgments, especially in the absence of clear visual markers.</p>
<p>“Witnessing the incredible acceleration of the technological ability to create artificial content (such as pictures of people) that are – or will soon become – indistinguishable from their ‘genuine’ counterparts, led us to two observations,” said study author <a href="https://profiles.sussex.ac.uk/p592424-dominique-makowski" target="_blank" rel="noopener">Dominique Makowski</a>, a lecturer in psychology at the University of Sussex and head of <a href="https://realitybending.github.io/" target="_blank" rel="noopener">the Reality Bending Lab</a>.</p>
<p>“The cyberspace (the digital environment created by social media, the internet, and virtually mediated communication) we navigate will soon become filled with content of ambiguous nature, for which the certainty of knowing if it is real and authentic is not guaranteed. At the same time, knowing that something is real or fake is epistemologically important and carries consequences for adaptive psychological processes such as the formation of trust, beliefs, memorization, and decision making.”</p>
<p>The research team recruited 150 participants to complete a multi-part study. First, participants filled out a series of personality questionnaires measuring traits such as narcissism, honesty-humility, paranoid ideation, and attitudes toward artificial intelligence. Then they were shown 109 images of real faces drawn from the American Multiracial Face Database. The images were carefully selected to feature individuals with neutral expressions, representing a diverse range of racial backgrounds.</p>
<p>Participants rated each face on four characteristics: attractiveness, beauty, trustworthiness, and familiarity. Later, they were told that about half of the images they had seen were AI-generated, though this was not true—all the images were real. The same faces were shown again in a randomized order, and this time, participants were asked to judge whether each face was real or fake, and how confident they were in their judgment.</p>
<p>Surprisingly, across all participants, about 44% of the images were judged to be fake—even though every face was a real person. The judgments varied not only between individuals but also within the same person across different faces. This variability suggests that judgments about authenticity are influenced by subjective impressions rather than objective features of the images.</p>
<p>One of the most important takeaways from the study is how easily people can be led to believe that real faces are fake. Simply telling participants that some of the images might be AI-generated was enough to drastically alter their beliefs. Despite having seen the faces already and rated them on other dimensions, participants changed their judgments when primed to expect fakes.</p>
<p>“People’s beliefs about what is real are surprisingly flexible,” Makowski told PsyPost. “People were easily led to the belief that ‘real’ images were AI-generated, and the decision as to which pictures were fake was highly variable from individual to individual, suggesting the role of subjective (idiosyncratic) processes.”</p>
<p>One of the most consistent findings was the role of facial attractiveness. For men, faces rated as more attractive or beautiful were more likely to be judged as real. For women, the relationship was more complex. Both highly attractive and highly unattractive faces were more likely to be judged as real, suggesting a U-shaped relationship. Confidence in these judgments also followed a similar pattern for women, with the highest confidence seen in responses to the most and least attractive faces.</p>
<p>“Judgments of facial attractiveness, which are made automatically and unconsciously, influence whether we believe that an image was AI-generated,” Makowski said. “This influence might be different for men and women.”</p>
<p>Trustworthiness also influenced judgments, particularly for female participants. Women were more confident in judging faces as real or fake when the faces were rated as highly trustworthy or untrustworthy. However, there was no strong evidence that trustworthiness directly affected whether a face was judged as real or fake for men.</p>
<p>Familiarity had weaker effects overall. However, among men, faces that seemed familiar were more likely to be judged as real, and participants felt more confident in these decisions. This finding supports past research showing that familiarity can enhance the feeling that something is genuine, although the effect here was modest.</p>
<p>Beyond face-related judgments, the researchers also examined how personality traits influenced reality beliefs. Narcissistic traits, particularly those related to seeking recognition and manipulating others, were associated with a higher likelihood of judging faces as real. These individuals were also more confident in their judgments. This fits with past research showing that narcissistic individuals often display greater self-assurance and are more likely to overestimate their abilities, including their skill in detecting authenticity.</p>
<p>In contrast, people scoring high in honesty-humility—a personality trait associated with sincerity and modesty—were less confident in their judgments. These individuals may have been more cautious in their responses, reflecting a general reluctance to make bold claims without certainty.</p>
<p>There was also a tentative link between paranoid ideation and a greater tendency to judge faces as real. The researchers speculated that heightened sensitivity to social cues, common in individuals with paranoid thinking, might increase the perceived emotional salience of the faces, leading to stronger impressions of authenticity.</p>
<p>Interestingly, general attitudes toward artificial intelligence had only limited effects. The only factor that mattered was participants’ enthusiasm about AI, which was linked to greater confidence in their judgments. However, beliefs about how realistic AI-generated content can be did not significantly influence decisions about whether faces were real or fake.</p>
<p>The researchers also found that the order in which images were shown had little effect on belief judgments, although participants were less confident in their decisions toward the end of the session. The delay between first viewing the face and making a real-fake judgment had no effect on the likelihood of calling a face real or fake, but it did affect confidence—participants were less confident when there was a longer delay.</p>
<p>There were some limitations to the research. All of the faces were shown twice, which could have introduced familiarity effects. The researchers also gave participants a false instruction that half of the images were fake, which may have created a bias toward identifying some faces as AI-generated. Although the instruction did not specify how many faces should be labeled real or fake, it may have led participants to second-guess their initial perceptions. Future research could use different designs to minimize these influences, such as showing new faces in the second phase or using a more implicit measure of authenticity judgment.</p>
<p>Another limitation was that the effects of facial ratings and personality traits, while statistically significant, were relatively small. This suggests that other factors—perhaps less conscious or more situational—also play a role in how people judge the authenticity of faces. The researchers recommend future studies explore additional cues, such as specific facial features or expressions, and examine how people consciously or unconsciously use these features to make reality judgments.</p>
<p>Looking ahead, Makowski said he plans to “confirm and expand these findings for other types of materials, such as art.” He added, “There will be more coming soon! Stay tuned by checking <a href="https://realitybending.github.io/" target="_blank" rel="noopener">the Reality Bending Lab’s website</a>.”</p>
<p>The study, “<a href="https://doi.org/10.1016/j.actpsy.2024.104670" target="_blank">Too beautiful to be fake: Attractive faces are less likely to be judged as artificially generated</a>,” was authored by Dominique Makowski, An Shu Te, Ana Neves, Stephanie Kirk, Ngoi Zi Liang, Panagiotis Mavros, and S.H. Annabel Chen.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/neuroforecasting-new-research-shows-brain-activity-can-predict-crowd-preferences/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Neuroforecasting: New research shows brain activity can predict crowd preferences</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 21st 2025, 06:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A new study published in <em><a href="https://doi.org/10.1093/pnasnexus/pgaf029" target="_blank">PNAS Nexus</a></em> provides evidence that brain activity can more accurately predict broader market behavior than self-reported preferences or observed choices—especially when research participants are not representative of the general population. The researchers found that neural responses tied to emotional reactions generalized across individuals and provided more consistent forecasts of what products or content would succeed in the market.</p>
<p>Most market predictions rely on behavioral data, assuming that what a sample of people chooses or reports will reflect the broader population. But this approach can fail if the sample is too small or not demographically matched to the public. In this new study, researchers explored whether signals from the brain—specifically those associated with emotional reactions—might be more reliable across different people. Their results showed that brain activity, especially in a region called the nucleus accumbens, consistently predicted market-level choices, even when traditional behavioral forecasts faltered.</p>
<p>The research builds on previous findings in a field known as neuroforecasting, which has shown that brain activity can sometimes outperform behavior and self-report in predicting real-world outcomes like music sales, advertising success, and even which news stories go viral. But these earlier studies mostly demonstrated that neuroforecasting could work—they didn’t explain why or under what conditions. This new research sought to uncover the underlying processes that make brain-based forecasting more generalizable than behavioral prediction, especially when sample demographics vary.</p>
<p>“Forecasting what people will choose at a large scale is critical in business and public policy. However, traditional tools like surveys or small-sample behavior often don’t predict real-world outcomes well. We wanted to know if brain activity can offer improved forecasts. And more importantly, when and why it might work better,” said study author <a href="https://www.rsm.nl/people/alex-genevsky/" target="_blank">Alexander Genevsky</a>, an associate professor of marketing and consumer neuroscience at Erasmus University.</p>
<p>The researchers grounded their approach in a decision-making model called the Affect Integration Motivation (AIM) framework. This model describes how people first respond to stimuli with quick emotional reactions, which are then processed more deliberately to arrive at a final decision. These early emotional responses are often shared across individuals and show up in specific areas of the brain. In contrast, the more reflective stages of decision-making—those that weigh personal memories or context—tend to be more individual and varied. The team hypothesized that these shared emotional components would offer more reliable signals for predicting broader market behavior.</p>
<p>To test their theory, the researchers conducted two experiments that combined neuroimaging and behavioral data with large-scale internet-based preference studies. In the first experiment, 32 participants viewed descriptions of crowdfunding projects while undergoing brain scans. In the second, 33 participants viewed short video clips. In both cases, the participants made real choices—whether to fund a project or continue watching a video. Their neural activity was measured while they made these decisions.</p>
<p>Separately, large internet samples of nearly 3,000 participants for the crowdfunding study and about 1,000 for the video-viewing study were asked to evaluate the same content. The researchers then used brain and behavioral data from the small laboratory samples to predict what the larger internet-based markets would prefer. They also divided the internet participants into groups that were more or less demographically similar to the lab samples to test how well forecasts generalized across different populations.</p>
<p>The key finding was that activity in the nucleus accumbens—a brain region associated with positive anticipation and emotional engagement—consistently predicted which projects or videos would be more popular in the broader samples. This predictive power held even when the lab sample was not demographically similar to the internet sample.</p>
<p>“There is information in the brain that reveals preferences, not just of the individual, but of larger groups,” Genevsky told PsyPost. “We found that certain patterns of brain activity, especially those linked to emotional reactions, can predict what large groups of people will choose, even when their background or demographics are quite different.”</p>
<p>In contrast, behavioral predictions based on participants’ choices or self-reports only worked well when the lab and internet samples were closely matched. Predictions based on another brain area, the medial prefrontal cortex—which is linked to more reflective and individualized thinking—did not consistently forecast market preferences.</p>
<p>The strength of the nucleus accumbens signal in predicting market choices was supported by further analyses. In both experiments, neural forecasts remained significant across all demographic quartiles of the internet sample, whereas behavioral forecasts declined as representativeness decreased. </p>
<p>Bootstrapped simulations showed that this pattern was robust in over 96% of analytic iterations. Moreover, the researchers found that brain activity in the nucleus accumbens was more consistent across individuals in the lab than activity in the medial prefrontal cortex, further supporting its role as a shared, generalizable signal.</p>
<p>Another key takeaway was that strong neural forecasts could be achieved with relatively small sample sizes. In both studies, brain activity from just 20 to 25 participants was enough to produce reliable predictions of market behavior. </p>
<p>In contrast, behavioral predictions remained inconsistent even as the sample size increased. This has practical implications, as neuroimaging studies are often considered too expensive or resource-intensive for widespread use. The study shows that relatively small and inexpensive neural datasets can still add significant forecasting value.</p>
<p>“We expected brain data to help, but we were surprised by how consistently it worked, even when our lab participants were quite different from the larger population,” Genevsky said. “In contrast, behavior and survey responses worked well only when our samples closely matched the broader market. It was striking that the brain signals held up across different groups.”</p>
<p>While these findings highlight the unique predictive power of neural signals, the study does have limitations. The two experiments focused on entertainment-related content—crowdfunding appeals and online videos—that likely evoke strong emotional responses. It is unclear whether the same brain-based forecasting methods would apply to different kinds of decisions, such as those involving financial risk or ethical trade-offs. The researchers note that future studies should test how different types of brain activity relate to various kinds of markets, such as those based on fear, long-term planning, or social influence.</p>
<p>“Brain imaging is still relatively expensive and time-consuming, and it’s not a silver bullet,” Genevsky noted. “Our findings are most relevant for decisions involving emotional reactions. Additional research is exploring if the same holds for more rational or complex choices. Also, we tested only two types of markets, so more research is needed to see how broadly these findings apply.”</p>
<p>Another open question is whether certain individuals consistently generate more predictive brain signals than others. If so, identifying these “neural superforecasters” could further reduce the cost and complexity of neuroforecasting.</p>
<p>“We want to better understand which types of brain signals matter for which kinds of decisions and how to make these tools more scalable,” Genevsky explained. “We’re also interested in partnering with organizations to apply these methods in new settings, like health messaging or sustainability campaigns.</p>
<p>“One encouraging takeaway is that you don’t need a massive neuroscience lab to apply these ideas. Our results suggest that even relatively small brain samples (i.e., under 40 people) can provide meaningful insight into what will appeal to a much larger audience.”</p>
<p>The study, “<a href="https://doi.org/10.1093/pnasnexus/pgaf029" target="_blank">Neuroforecasting reveals generalizable components of choice</a>,” was authored by Alexander Genevsky, Lester C. Tong, and Brian Knutson</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/what-brain-scans-reveal-about-the-neural-correlates-of-pornography-consumption/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">What brain scans reveal about the neural correlates of pornography consumption</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 20th 2025, 18:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>While pornography has been present throughout human history in various forms, such as ancient erotic art to more modernized motion pictures, research shows an <a href="https://doi.org/10.1007/s10508-021-02090-w">increase in use</a> over recent decades given the rise of technology and accessibility.</p>
<p>Pornography, meaning any <a href="https://doi.org/10.1007/s10508-013-0229-3">media intended to depict or describe sexual content</a> to heighten sexual arousal or pleasure, can <a href="https://psycnet.apa.org/doi/10.1037/adb0000603">serve many purposes</a>. Users may seek sexual pleasure, find it a fun way to fight boredom, or turn to it because they are down or stressed and perhaps want to escape their feelings.</p>
<p>Statistics show pornography to be commonplace: A 2018 study found that 91.5% of men and 60.2% of women had <a href="https://doi.org/10.1080/00224499.2018.1532488">consumed it in the past month</a>.</p>
<p>It’s important to ask: What does viewing explicit materials do to your brain and real-life sexual and romantic relationships, and specifically to the people who see it when they are <a href="https://www.commonsensemedia.org/research/teens-and-pornography">as young as 10 years old or even earlier</a>?</p>
<p>I am a <a href="https://som.cuanschutz.edu/Profiles/Faculty/Profile/29924">licensed marriage and family therapist</a> specializing in the treatment of a variety of mental health challenges. These include issues that are often seen in the context of relationships and larger systems such as media and pornography.</p>
<p>While neither problematic pornography use nor addiction to it <a href="https://doi.org/10.7759/cureus.33066">is listed in the handbook used for mental health diagnostics</a>, known as the DSM, it may still be detrimental for many people in terms of their behavior, their relationships and their mental and physical well-being. People with problematic porn use have trouble <a href="https://doi.org/10.3390/jcm8010091">reducing or controlling their pornography use</a> despite the harm it does to their life.</p>
<p>I will walk through some of these consequences below, starting with how the brain can be changed with pornography use.</p>
<h2>Brain changes behind pornography use</h2>
<p>While some of the most pertinent studies were done a decade ago or more, they remain highly relevant. Conducting research in this arena can be difficult due to the DSM’s exclusion of pornography “addiction” as a disorder as well as the sensitive nature of the topic. Controlled experiments on humans, particularly of this kind, are inherently unethical, therefore studies rely on surveys and reports.</p>
<p>A 2015 study − one of the first brain scan studies on male pornography users − found a correlation between <a href="https://doi.org/10.1001/jamapsychiatry.2014.93">pornography use and reduced gray matter</a> in part of the brain’s reward system involved in motivation and decision-making. The study also reported lower responsiveness to pornography and other sexual stimuli due to desensitization.</p>
<p>This pattern likely results from lower connectivity between the prefrontal cortex − the decision-making part of the brain − and the reward as more porn is consumed. This in turn leads to increased cravings and impulsivity in order to achieve the previous levels of reward in the brain.</p>
<p>Another study, published in 2016, found that 49% of subjects had experienced <a href="https://doi.org/10.1016/j.chb.2015.11.046">pursuing content that was previously not interesting to them</a> or that they considered disgusting. Because pornography can affect brain changes and subsequent pleasure responses, porn users may eventually feel the need to seek more extreme content.</p>
<p>This pursuit, in attempts to override the chemistry of the changing brain, may lend to disruption in the person’s life, often within relationships.</p>
<p>So what does this look like and how are relationships suffering as a result?</p>
<h2>How relationships can suffer</h2>
<p>While some research suggests that pornography use can <a href="https://doi.org/10.1007/s10508-010-9598-z">positively support sexuality exploration in couples</a>, including increased quality and frequency of sex with use of pornography, most studies highlight its negative impact on intimate relationships.</p>
<p>The use of pornography is often associated with <a href="https://doi.org/10.1080/00224499.2022.2148155">less relationship satisfaction and stability</a>. Higher rates of infidelity, lower levels of commitment, increased emotional detachment and loss of trust are also evident in <a href="https://doi.org/10.1080/0092623x.2019.1654579">relationships affected by problematic porn use</a>. The challenges related to unrealistic expectations, decreased sexual interest in a partner and increased partner insecurity influenced by pornography use have also been reported.</p>
<p>One 2011 survey found that women more often told researchers that they <a href="https://doi.org/10.1007/s10508-010-9598-z">had less sex</a> as a result of their partner’s pornography use, and men reported being less aroused by sex with their partner. A 2021 study looking at the correlation between pornography use and sexual dysfunction in young men ages 18-35 found that more than 20% of sexually active participants reported <a href="https://doi.org/10.2196/32542">some degree of erectile dysfunction</a> in the month prior to the questionaire. This contrasts to <a href="https://doi.org/10.1185/030079904125003467">8% in men 20-29 and 11% in the 30-39 age group</a>, based on a study of the general prevalence of erectile dysfunction across several countries.</p>
<p>Given the prevalence of pornography use as well as data that indicates that consuming porn can damage relationships between intimate partners, what can couples do about it?</p>
<h2>Finding a way forward</h2>
<p>Since pornography use is often associated with shame and secrecy, it’s important for affected couples experiencing problems because one of them is consuming too much porn to openly discuss it to move through these challenges and work together as a team.</p>
<p>Talking with loved ones and trusted support, such as close friends, about difficult issues is <a href="https://doi.org/10.1057/s41599-022-01227-z">known to reduce shame</a>, making taboo subject areas more approachable.</p>
<p>I highly recommend <a href="https://doi.org/10.1080/01926187.2012.685003">seeking support from licensed therapists</a>, especially those who specialize in the treatment of problematic pornography use, given the sensitive nature. In addition, <a href="https://doi.org/10.2147/sar.s81535">peer support groups</a> can be helpful in creating a sense of community and reducing isolation.</p>
<h2>Effects on young people</h2>
<p>It’s no surprise that pornography is getting into the hands of young people at earlier ages as accessibility via cellphones and internet use has been increasing.</p>
<p>One 2022 study from Common Sense Media, an organization dedicated to helping parents navigate suitable media content for their children, reported that 73% of study respondents <a href="https://www.commonsensemedia.org/press-releases/new-report-reveals-truths-about-how-teens-engage-with-pornography">between the ages of 13 and 17 have watched porn</a>. This differs from previous decades. For example, a study conducted <a href="https://doi.org/10.1542/peds.2006-1891">in 2005 found 42% of youth internet users had been exposed to pornographic content</a>.</p>
<p>The 2022 study found that 54% of these young people said they had been exposed to it before reaching the age of 13, and 15% at the age of 10 or younger. About 58% said they had accidentally encountered pornographic material.</p>
<p>Young people’s exposure to pornography can be disturbing to them and <a href="https://doi.org/10.1080/10720160902724228">may be linked to higher rates of personality and impulse disorders</a>.</p>
<p>Those who are exposed to pornography at earlier ages may also end up with <a href="https://doi.org/10.1080/10720162.2012.660431">unrealistic views of sexual behavior and beliefs</a>, as well as earlier sexual exploration in comparison to those who aren’t.</p>
<p>Pornography use could have even more profound effects on the developing brain. This is because adolescent brains are undergoing rapid development, and connections are being formed and reorganized at a high rate of speed during the teen years, a <a href="https://www.ncbi.nlm.nih.gov/books/NBK557811/">physiological concept called neuroplasticity</a>.</p>
<p>A 2021 study of almost 11,000 European adolescents between the ages of 14 and 17 found those exposed to pornography were more likely to <a href="https://doi.org/10.3390/children8100925">engage in rule-breaking and aggressive behaviors</a>.</p>
<p>These patterns drive home the great need for parental involvement in their children’s internet activity.<!-- Below is The Conversation's page counter tag. Please DO NOT REMOVE. --><img decoding="async" src="https://counter.theconversation.com/content/249725/count.gif?distributor=republish-lightbox-basic" alt="The Conversation" width="1" height="1"><!-- End of code. If you don't see any code above, please get new code from the Advanced tab after you click the republish button. The page counter does not collect any personal data. More info: https://theconversation.com/republishing-guidelines --></p>
<p> </p>
<p><em>This article is republished from <a href="https://theconversation.com">The Conversation</a> under a Creative Commons license. Read the <a href="https://theconversation.com/pornography-may-be-commonplace-but-a-growing-body-of-research-shows-it-causes-lasting-harm-to-the-brain-and-relationships-249725">original article</a>.</em></p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/ai-chatbots-often-misrepresent-scientific-studies-and-newer-models-may-be-worse/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">AI chatbots often misrepresent scientific studies — and newer models may be worse</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 20th 2025, 16:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>Artificial intelligence chatbots are becoming popular tools for summarizing scientific research, but a new study suggests these systems often misrepresent the findings they summarize. Published in <em><a href="https://royalsocietypublishing.org/doi/10.1098/rsos.241776" target="_blank">Royal Society Open Science</a></em>, the study found that the most widely used language models frequently overgeneralize the results of scientific studies—sometimes making broader or more confident claims than the original research supports. This tendency was more common in newer models and, paradoxically, was worsened when the chatbots were explicitly asked to be accurate.</p>
<p>The study was led by Uwe Peters of Utrecht University and Benjamin Chin-Yee of Western University and the University of Cambridge. The researchers were motivated by growing concerns about the use of large language models—such as ChatGPT, Claude, DeepSeek, and LLaMA—in science communication.</p>
<p>These tools are often praised for their ability to summarize complex material, but critics have warned that they may overlook important limitations or caveats, especially when converting technical findings into more readable language. Overgeneralizations can mislead readers, particularly when scientific results are treated as universally applicable or when uncertain findings are reframed as policy recommendations.</p>
<p>To test whether these concerns were justified, the researchers conducted a large-scale evaluation of 10 of the most prominent large language models. These included popular systems like GPT-4 Turbo, ChatGPT-4o, Claude 3.7 Sonnet, and DeepSeek. In total, they analyzed 4,900 chatbot-generated summaries of scientific texts.</p>
<p>The source material included 200 research abstracts from top science and medical journals such as <em>Nature</em>, <em>Science</em>, <em>The Lancet</em>, and <em>The New England Journal of Medicine</em>, as well as 100 full-length medical articles. For some of the full articles, the researchers also included expert-written summaries from <em>NEJM Journal Watch</em> to allow for comparisons between human- and AI-generated summaries.</p>
<p>Each summary was examined for signs of overgeneralization. The researchers focused on three specific features that broaden the scope of scientific claims: using generic statements instead of specific ones, changing past tense descriptions to present tense, and turning descriptive findings into action-oriented recommendations. For example, if a study stated that “participants in this trial experienced improvements,” a generalized version might say “this treatment improves outcomes,” which could falsely suggest a broader or more universal effect.</p>
<p>Most language models produced summaries that were significantly more likely to contain generalized conclusions than the original texts. In fact, summaries from newer models such as ChatGPT-4o and LLaMA 3.3 were up to 73% more likely to include overgeneralizations. By contrast, earlier models such as GPT-3.5 and the Claude family were less likely to introduce these problems.</p>
<p>The researchers also found that prompting the models to be more accurate didn’t help—if anything, it made things worse. When models were instructed to “avoid inaccuracies,” they were nearly twice as likely to produce generalized statements compared to when they were simply asked to summarize the text. One explanation for this counterintuitive result may relate to how the models interpret prompts. Much like the human tendency to fixate on a thought when told not to think about it, the models may respond to reminders about accuracy by producing more authoritative-sounding—but misleading—summaries.</p>
<p>In addition to comparing chatbot summaries to the original research, the study also looked at how the models performed compared to human science writers. Specifically, the researchers compared model-generated summaries of medical research to expert-written summaries published in <em>NEJM Journal Watch</em>. They found that the human-authored summaries were much less likely to contain overgeneralizations. In fact, the chatbot-generated summaries were nearly five times more likely to broaden the scope of scientific conclusions beyond what the original studies supported.</p>
<p>Another interesting finding was the role of model settings. When researchers used an “API” to generate summaries with the temperature setting at 0—a value that makes the model more deterministic and less creative—the likelihood of overgeneralization dropped significantly. This suggests that controlling certain technical parameters can help reduce errors, though this option may not be available to everyday users accessing chatbots through standard web interfaces.</p>
<p>The researchers point out that not all generalizations are inherently bad. Sometimes, simplifying complex findings can make science more accessible, especially for non-experts. But when these generalizations go beyond the evidence, they can mislead readers and even pose risks. This is particularly concerning in high-stakes fields like medicine, where overstated claims could affect clinical decisions.</p>
<p>While the study focused on overgeneralizations, the researchers acknowledged that undergeneralizations can also occur. A model might turn a broadly supported finding into a narrowly worded summary, potentially downplaying important results. However, these instances were far less common than the overgeneralizations, which were the main focus of the research.</p>
<p>This study stands out not only for its scale and thoroughness but also for offering a clear framework to evaluate how well language models preserve the scope of scientific conclusions. The researchers suggest that developers and users of language models adopt several strategies to reduce the risk of misleading summaries. These include using models with more conservative settings, avoiding prompts that explicitly demand accuracy, and choosing systems like Claude that have shown greater fidelity to the original texts.</p>
<p>But the study has some limitations. It only tested a few prompt types, and it focused largely on medical research, which may not generalize to all scientific fields. The human-written summaries used for comparison were produced by expert audiences and may not reflect the kinds of summaries written for the general public. Future studies might explore how different prompting strategies or model configurations influence performance across a wider range of scientific disciplines.</p>
<p>The study, “<a href="https://doi.org/10.1098/rsos.241776" target="_blank">Generalization bias in large language model summarization of scientific research</a>,” was authored by Uwe Peters and Benjamin Chin-Yee.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/is-gender-affirming-care-helping-or-harming-mental-health/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Is gender-affirming care helping or harming mental health?</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 20th 2025, 14:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>Two new studies offer contrasting insights into the mental health impacts of gender-affirming medical care, highlighting the complexity of transgender healthcare outcomes. A large-scale analysis of medical records published in <em><a href="https://academic.oup.com/jsm/article-abstract/22/4/645/8042063" target="_blank">The Journal of Sexual Medicine</a></em> found that transgender individuals who underwent gender-affirming surgery were more likely to be diagnosed with depression, anxiety, and other mental health conditions compared to those who did not have surgery. In contrast, a longitudinal study published in <em><a href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2831643" target="_blank">JAMA Network Open</a></em> found that transgender and nonbinary adults who received gender-affirming hormone therapy were significantly less likely to report symptoms of moderate-to-severe depression over time.</p>
<p>The research was conducted to address ongoing questions about the mental health outcomes associated with gender-affirming care. Transgender individuals—those whose gender identity does not align with the sex assigned at birth—often face a heightened risk of psychological distress. These difficulties can stem from factors such as societal stigma, discrimination, and the internal conflict of gender dysphoria.</p>
<p>Many seek gender-affirming treatments, including hormone therapy and surgical procedures, to alleviate this distress. While earlier studies have indicated psychological benefits from these interventions, the long-term mental health impact of surgery remains unclear, especially due to the limitations of small sample sizes and reliance on self-reported data.</p>
<h3>The first study: Gender-affirming surgery linked to higher post-surgical mental health risks</h3>
<p>To improve upon previous research, the authors of the study published in <em>The Journal of Sexual Medicine</em> used a large-scale dataset drawn from the TriNetX database, which compiles de-identified electronic medical records from more than 64 healthcare organizations in the United States. The analysis focused on patients aged 18 and older who had been diagnosed with gender dysphoria, using diagnostic codes from the International Classification of Diseases.</p>
<p>Among more than 107,000 individuals identified with gender dysphoria between 2014 and 2024, researchers formed several matched cohorts, comparing patients who had undergone gender-affirming surgery to those who had not. To ensure more accurate comparisons, they matched participants on age, race, and ethnicity using a statistical technique called propensity score matching.</p>
<p>Mental health outcomes were measured using clinical diagnoses documented in the medical records, rather than relying on self-reported surveys. Researchers focused on several conditions commonly observed in transgender populations: depression, anxiety, suicidal ideation, substance use disorder, and body dysmorphic disorder. They then examined how frequently these diagnoses appeared in patients’ records following surgery and compared the results across gender groups.</p>
<p>The findings revealed consistent patterns. Among individuals recorded as male in the medical records and diagnosed with gender dysphoria, those who had surgery had more than double the rate of depression compared to those who had not (25.4% vs. 11.5%) and nearly five times the rate of anxiety (12.8% vs. 2.6%). Suicidal ideation and substance use disorders were also more common in the surgical group. A similar trend appeared among patients recorded as female: those who underwent surgery were more likely to be diagnosed with depression (22.9% vs. 14.6%), anxiety (10.5% vs. 7.1%), suicidal ideation (19.8% vs. 8.4%), and substance use disorders (19.3% vs. 7.1%).</p>
<p>To explore whether these risks differed by type of gender transition, the researchers also examined individuals who had undergone masculinizing or feminizing surgeries but did not have a documented diagnosis of gender dysphoria. Even in this broader group, transgender men faced higher rates of mental health diagnoses compared to transgender women. For instance, the relative risk of depression was nearly 80% higher for transgender men. Rates of anxiety and substance use were also elevated.</p>
<p>Interestingly, across all comparisons, rates of body dysmorphic disorder—a condition involving distress over perceived flaws in physical appearance—did not differ between surgical and non-surgical groups. This suggests that dissatisfaction with surgical outcomes or body image was not the primary driver of the mental health disparities observed.</p>
<p>The study’s authors stress that the results should not be interpreted to mean that gender-affirming surgery causes poor mental health. Instead, they suggest that the observed associations may reflect a complex mix of social, emotional, and medical factors that persist even after surgery. Transgender individuals who choose to pursue surgery may already be experiencing greater psychological distress. At the same time, the stress of undergoing a major medical procedure, coupled with ongoing experiences of social stigma and limited access to mental health resources, may contribute to the emergence or worsening of mental health conditions.</p>
<p>One possible explanation raised by the authors involves the way psychiatric diagnoses are assigned. Before surgery, symptoms of depression or anxiety may be interpreted by clinicians as part of the gender dysphoria diagnosis. After surgery, however, these symptoms may be identified as independent conditions, leading to an apparent increase in diagnoses. This shift in diagnostic framing could influence how mental health outcomes are recorded and understood.</p>
<h3>The second study: Gender-affirming hormone therapy linked to lower depression rates</h3>
<p>On the other hand, the study published in <em>JAMA Network Open</em> found evidence that gender-affirming hormone therapy is associated with lower rates of moderate-to-severe depressive symptoms among transgender, nonbinary, and gender-diverse adults receiving care in community health centers. Over a four-year period, patients who were prescribed gender-affirming hormones experienced a 15% lower risk of clinically significant depression symptoms compared to those not receiving hormone therapy.</p>
<p>The research was part of the LEGACY project, a longitudinal study conducted at two federally qualified community health centers with extensive experience in providing care to transgender and nonbinary patients—Fenway Health in Boston and Callen-Lorde in New York City. The study followed 3,592 adult patients who had visited these clinics between 2016 and 2019. All participants were at least 18 years old, had a gender identity different from the sex assigned at birth, and had completed at least two depression screenings using a standardized questionnaire.</p>
<p>The researchers assessed depression symptoms using versions of the Patient Health Questionnaire, a widely used mental health screening tool. Moderate-to-severe depression was defined by standard clinical cutoffs. Patients were classified based on whether they had been prescribed hormone therapy during each year of follow-up. The researchers also collected extensive background information, including participants’ age, race and ethnicity, gender identity, income level, insurance status, HIV status, and other relevant health and demographic characteristics.</p>
<p>Overall, the sample was diverse. The median age was 28, and nearly one in five participants identified as nonbinary. Just over half lived below the federal poverty line. About 12% were Black, 16% were Hispanic, and 5% were living with HIV. At the start of the study, 84.5% of participants were already prescribed gender-affirming hormone therapy. At that same time, 15.3% of participants met criteria for moderate-to-severe depression.</p>
<p>Using statistical models that accounted for demographic differences and potential confounding factors, the researchers found that patients who received hormone therapy had a lower risk of experiencing moderate-to-severe depression symptoms over time. The adjusted risk ratio was 0.85, meaning there was a 15% reduction in the likelihood of clinically significant depression symptoms for those on hormone therapy compared to those who were not.</p>
<p>The study also identified other factors that were associated with a higher risk of depression. Younger participants, transgender women, nonbinary individuals assigned female at birth, those with public insurance, and individuals living in poverty were more likely to report depression symptoms. Patients who were HIV-negative but prescribed pre-exposure prophylaxis (PrEP) also had elevated rates of depression, possibly reflecting greater awareness of or anxiety about HIV risk. In contrast, Asian and Black participants, as well as older adults and patients from the New York clinic, had lower rates of depression symptoms.</p>
<h3>What might explain the different outcomes observed?</h3>
<p>The contrasting outcomes between the two studies may be explained by differences in study design, timing, and clinical context. The surgery study used cross-sectional data and clinical diagnoses, likely capturing patients during a stressful post-operative period when mental health issues are more likely to surface or be formally diagnosed. In contrast, the hormone therapy study used longitudinal, self-reported data and tracked patients over time, revealing gradual improvements in depression symptoms.</p>
<p>Other factors, such as differences in patient populations, levels of healthcare access, the role of social support, and the biological effects of hormones, may also contribute to the observed patterns. Diagnostic practices may shift after surgery, leading to more recorded mental health conditions that do not necessarily reflect worsening well-being.</p>
<p>As with all research, both studies have limitations to consider.</p>
<p>Although the study published in <em>The Journal of Sexual Medicine</em> used clinical data, which enhances its reliability, the data were collected from a broad network of health systems, which may introduce inconsistencies in how diagnoses are recorded. There are also concerns about misclassification. For example, individuals categorized as not having surgery may have had procedures done outside the database’s network. And because the study excluded patients with any prior mental health diagnosis, some pre-existing conditions may have been missed if they were never formally documented. In addition, because the study was cross-sectional, it could not track individual patients over time or establish causality.</p>
<p>The <em>JAMA Network Open</em> study, in contrast, used longitudinal data, allowing the researchers to better assess the direction of the relationship. However, the data were still observational, meaning they cannot prove that gender-affirming hormone therapy directly causes improvements in depression symptoms. Because participants were not randomly assigned to receive or not receive hormone therapy, other factors might have influenced the results. For example, patients who sought out hormone therapy may have had greater access to healthcare, more social support, or better mental health to begin with—factors that could independently contribute to lower rates of depression. The study also did not assess how long participants had been on hormone therapy or whether they underwent gender-affirming surgeries, both of which could influence mental health outcomes.</p>
<p>The study, “<a href="https://doi.org/10.1093/jsxmed/qdaf026" target="_blank">Examining gender-specific mental health risks after gender-affirming surgery: a national database study</a>,” was authored by Joshua E. Lewis, Amani R. Patterson, Maame A. Effirim, Manav M. Patel, Shawn E. Lim, Victoria A. Cuello, Marc H. Phan, and Wei-Chen Lee.</p>
<p>The study, “<a href="https://doi.org/10.1001/jamanetworkopen.2025.0955" target="_blank">Gender-Affirming Hormone Therapy and Depressive Symptoms Among Transgender Adults</a>,” was authored by Sari L. Reisner, David R. Pletta, Alex S. Keuroghlian, Kenneth H. Mayer, Madeline B. Deutsch, Jennifer Potter, Jaclyn M. W. Hughto, Alexander Harris, and Asa E. Radix</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<table style="font:13px Helvetica, sans-serif; border-radius:4px; -moz-border-radius:4px; -webkit-border-radius:4px; background-color:#fff; padding:8px; margin-bottom:6px; border:1px solid #adadad;" width="100%">
<tbody>
<tr>
<td><a href="https://www.psypost.org/study-finds-zombie-neurons-in-the-peripheral-nervous-system-contribute-to-chronic-pain/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Study finds “zombie” neurons in the peripheral nervous system contribute to chronic pain</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 20th 2025, 12:00</div>
<div style="font-family:Helvetica, sans-serif; color:#494949;text-align:justify;font-size:13px;">
<p><p>A new study published in <em><a href="https://www.nature.com/articles/s41593-025-01954-x" target="_blank">Nature Neuroscience</a></em> provides evidence that aging and injury lead to the buildup of senescent neurons—commonly referred to as “zombie” cells—in the peripheral nervous system. These neurons, which have stopped dividing but refuse to die, secrete inflammatory signals that increase pain sensitivity. The researchers found that removing these senescent cells with a targeted drug not only reduced markers of inflammation but also improved pain-related behavior in aged mice.</p>
<p>The study was driven by the need to better understand why older adults are more susceptible to chronic pain and why many existing treatments are either ineffective or come with serious side effects. While research has long shown that the central nervous system is affected by aging, much less was known about how aging influences the peripheral nervous system, which includes sensory neurons in the dorsal root ganglia that transmit pain signals. Since these neurons can be damaged by surgery, trauma, or disease, the researchers aimed to investigate whether they too exhibit signs of cellular senescence—and whether these changes contribute to long-term pain.</p>
<p>“Very little is known about underlying causes of pain experienced during aging. The prevalence of chronic pain in aging populations and the lack of effective and non-addictive treatments motivated this exploration into neuronal senescence as a potential mechanism,” said <a href="https://www.linkedin.com/in/lauren-j-donovan-phd-166626103/" target="_blank">Lauren Donovan</a>, a research scientist at Stanford University.</p>
<p>“There is nothing worse than sitting in front of a patient who is suffering from chronic pain and telling them you have nothing to offer,” added <a href="https://www.linkedin.com/in/vivianne-tawfik-md-phd-50278488/" target="_blank">Vivianne Tawfik</a>, an associate professor at <a href="https://tawfiklab.stanford.edu/" target="_blank">Stanford University</a> and board-certified anesthesiologist and pain medicine physician. “That’s why I run a research lab focused on pain mechanisms—so that in the future, there will be better options for my patients.”</p>
<p>For their study, the researchers used both young and aged mice to examine how peripheral nerve injury and age influence the development of cellular senescence in sensory neurons. The team studied the dorsal root ganglia, a cluster of nerve cells that relay sensory signals from the body to the spinal cord. They used molecular and genetic tools to identify markers of senescence—specifically p16 and p21, two proteins commonly found in senescent cells—as well as IL-6, a pro-inflammatory molecule frequently secreted by these cells. By comparing young and old animals, both with and without nerve injury, they assessed how senescence evolves with time and damage.</p>
<p>The researchers began by measuring senescence in aged mice and found a significant increase in dorsal root ganglia neurons expressing p16, p21, and IL-6, compared to young animals. These neurons also displayed activity of β-galactosidase, a commonly used indicator of cellular senescence. Importantly, many of the senescent neurons belonged to a class of small-diameter cells known as nociceptors, which detect painful stimuli. These cells also expressed Trpv1, a receptor associated with the detection of heat and inflammation-related pain.</p>
<p>Injury further amplified the presence of senescent neurons. When the researchers performed a standard nerve injury in young mice, they observed a rapid increase in neurons expressing p21 and IL-6 within the first week, with p16 expression building more gradually over time. The pattern was even more pronounced in aged animals, where senescence markers were elevated earlier and to a greater extent. Interestingly, not only injured neurons showed signs of senescence. Neighboring uninjured neurons also began to express p21 and p16, suggesting a “bystander” effect where inflammatory signals from injured cells may induce senescence in surrounding tissue.</p>
<p>To understand the functional implications of these changes, the team used electrophysiological techniques to study how senescent neurons behave. They discovered that many of these neurons fired more readily and frequently than others, indicating that they were more excitable. When exposed to IL-6, the senescent neurons became even more active. These findings support the idea that senescent neurons are not simply inactive bystanders but actively contribute to heightened sensitivity and pain.</p>
<p>Crucially, the researchers tested whether eliminating senescent cells could improve outcomes. They treated mice with a drug called ABT263, a senolytic compound that targets and destroys senescent cells. Mice received the treatment several weeks after nerve injury, at a time when senescence had already taken hold. In aged mice, the drug significantly improved mechanical pain thresholds and restored more balanced weight-bearing behavior in their limbs. In younger mice, the treatment had more modest effects, reinforcing the idea that age-related senescence plays a larger role in chronic pain.</p>
<p>To validate the relevance of their findings in humans, the researchers analyzed postmortem tissue samples from human donors aged 32 to 65. Similar to mice, human sensory neurons showed increased expression of p16, p21, and IL-6 with age. Many of these senescent cells were also positive for TRPV1, the same nociceptor marker seen in the mouse experiments. Reanalysis of publicly available human gene expression data further confirmed the association between pain-related symptoms and senescence-related gene activity.</p>
<p>These results highlight a previously underappreciated mechanism of age-related pain: the accumulation of senescent neurons that secrete inflammatory molecules and amplify the nervous system’s sensitivity to pain. Unlike traditional pain treatments that often mask symptoms or carry high risk of dependency, targeting the senescence pathway offers a promising strategy to reduce pain at its source.</p>
<p>“The key takeaway for the average person is that as we age, some of our sensory neurons undergo a process called senescence, which may contribute to chronic pain,” Donovan told PsyPost. “In addition, we found that injury can exacerbate senescence in neurons, leading to an additive effect of aging and injury that may enhance pain. This research identifies a new potential target for treating chronic pain, especially in older individuals. It suggests that addressing cellular senescence in the nervous system can lead to new ways of managing pain and sensory dysfunction. </p>
<p>But the study has limitations. The experimental models involved rodents and postmortem human tissue, which cannot fully replicate the complex experience of chronic pain in living humans. The number of human samples analyzed was small, and most came from donors without known chronic pain conditions. While the researchers used multiple rigorous methods to confirm their findings, future studies will need to explore how senescence affects different types of chronic pain, including conditions like arthritis or diabetic neuropathy. There is also a need to determine the long-term safety of using senolytic drugs in humans, as they may also affect beneficial immune responses or other essential cellular functions.</p>
<p>This research opens the door for new approaches to pain management, particularly for older adults who face limited treatment options. As Donovan noted, “The team will continue investigating how to best target senescent neurons to relieve chronic pain, with their work still at the pre-clinical phase, there is a lot of groundwork to do. The ultimate goal is to create treatments that can help manage pain while preserving healthy nerve function.”</p>
<p>The study, “<a href="https://doi.org/10.1038/s41593-025-01954-x" target="_blank">Aging and injury drive neuronal senescence in the dorsal root ganglia</a>,” was authored by Lauren J. Donovan, Chelsie L. Brewer, Sabrina F. Bond, Aleishai Pena Lopez, Linus H. Hansen, Claire E. Jordan, Oscar C. González, Luis de Lecea, Julie A. Kauer, and Vivianne L. Tawfik.</p></p>
</div>
<div style="font-family:Helvetica, sans-serif; font-size:13px; text-align: center; color: #666666; padding:4px; margin-bottom:2px;"></div>
</td>
</tr>
</tbody>
</table>
<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
<p><strong>This information is taken from free public RSS feeds published by each organization for the purpose of public distribution. Readers are linked back to the article content on each organization's website. This email is an unaffiliated unofficial redistribution of this freely provided content from the publishers. </strong></p>
<p> </p>
<p><s><small><a href="#" style="color:#ffffff;"><a href='https://blogtrottr.com/unsubscribe/565/DY9DKf'>unsubscribe from this feed</a></a></small></s></p>