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	<title>prevention programs &#8211; Science</title>
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	<title>prevention programs &#8211; Science</title>
	<link>https://scienmag.com</link>
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		<title>Meta-analysis estimates 6.2% infant HIV prevalence in Ethiopia</title>
		<link>https://scienmag.com/meta-analysis-estimates-6-2-infant-hiv-prevalence-in-ethiopia/</link>
		
		<dc:creator><![CDATA[Harold Sullivan]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 04:40:44 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[antiretroviral therapy]]></category>
		<category><![CDATA[early infant diagnosis]]></category>
		<category><![CDATA[Ethiopia]]></category>
		<category><![CDATA[heterogeneity in HIV studies]]></category>
		<category><![CDATA[HIV prevalence in infants Ethiopia]]></category>
		<category><![CDATA[HIV prevention in Ethiopia]]></category>
		<category><![CDATA[infant HIV]]></category>
		<category><![CDATA[Joanna Briggs Institute quality assessment]]></category>
		<category><![CDATA[maternal HIV and vertical transmission]]></category>
		<category><![CDATA[meta-analysis]]></category>
		<category><![CDATA[meta-analysis of infant HIV rates]]></category>
		<category><![CDATA[mother-to-child transmission]]></category>
		<category><![CDATA[Pooled]]></category>
		<category><![CDATA[pooled HIV prevalence estimates]]></category>
		<category><![CDATA[pooled prevalence]]></category>
		<category><![CDATA[prevalence]]></category>
		<category><![CDATA[prevention programs]]></category>
		<category><![CDATA[PRISMA Guidelines for Systematic Reviews]]></category>
		<category><![CDATA[publication period and HIV prevalence]]></category>
		<category><![CDATA[regional variation]]></category>
		<category><![CDATA[statistical methods in HIV research]]></category>
		<category><![CDATA[systematic review]]></category>
		<category><![CDATA[systematic review of HIV transmission]]></category>
		<category><![CDATA[temporal trends in infant HIV rates]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=327102</guid>

					<description><![CDATA[A meta-analysis of 31 studies involving 15,251 infants estimated HIV prevalence of 6.2% among Ethiopian infants born to HIV-positive mothers, with lower estimates in more recent study groups and substantial statistical and regional variation.]]></description>
										<content:encoded><![CDATA[<p>A systematic review and meta-analysis estimated that 6.2% of infants born to HIV-positive mothers in Ethiopia had HIV, based on 31 studies encompassing 15,251 infants. The pooled estimate had a 95% confidence interval of 4.7% to 7.9%, but variation among studies was substantial: heterogeneity reached 93.7% with a p-value below 0.001. The analysis was published in BMC Infectious Diseases as an accepted article on October 20, 2026.</p>
<p>Researchers searched Scopus, PubMed, Web of Science, ScienceDirect, Embase and Google Scholar between June and September 2025 for studies published from October 2011 onward that reported HIV prevalence among infants born to HIV-positive mothers in Ethiopia. Eligible studies were included under PRISMA guidelines, and data were extracted using a standardized form. Study quality was assessed with the Joanna Briggs Institute critical appraisal tool. Prevalence was pooled in Stata version 17 using a random-effects model with the DerSimonian and Laird estimator, while heterogeneity was evaluated with Higgins’ I² statistic.</p>
<p>When studies were grouped by publication period, pooled prevalence estimates were lower in the more recent groups. The estimate was 9.6% for studies published from 2011 to 2015, 6.4% for those published from 2016 to 2020 and 4.6% for those published from 2021 to 2024. This sequence describes differences among the included evidence groups rather than a direct longitudinal measurement in a single population. The high between-study heterogeneity and the grouping of studies by publication period limit how confidently the pattern can be interpreted as change over time.</p>
<p>Regional pooled estimates also varied, ranging from 2.3% in the combined Tigray and Gambella estimate to 7.6% in Oromia. Individual study estimates varied substantially within regions. The researchers performed subgroup and sensitivity analyses to explore sources of heterogeneity and evaluated possible small-study effects with funnel plots, Egger’s test and nonparametric trim-and-fill analysis. The applied tests found no statistically significant evidence of a small-study effect after trim-and-fill analysis, with reported p-values above 0.05. That finding did not resolve the high heterogeneity across the underlying studies.</p>
<p>The authors said the variation may indicate possible differences in the implementation and coverage of measures that prevent mother-to-child HIV transmission and in access to maternal and infant HIV services. They identified continued strengthening of antenatal HIV care, skilled institutional delivery, maternal antiretroviral therapy adherence, timely infant prophylaxis, early infant diagnosis and postnatal follow-up as measures that may contribute to further reductions. The review itself was designed to estimate prevalence and describe temporal and regional variation, rather than evaluate the efficacy of any single intervention.</p>
<p><strong>Subject of Research:</strong> Pooled HIV prevalence among Ethiopian infants born to HIV-positive mothers</p>
<p><strong>Article Title:</strong> Pooled prevalence and temporal variations of infant HIV infection in Ethiopia: a systematic review and meta-analysis</p>
<p><strong>Article References:</strong> Gizachew, M., &amp; Deress, T. (2026). Pooled prevalence and temporal variations of infant HIV infection in Ethiopia: a systematic review and meta-analysis. <em>BMC Infectious Diseases</em>. <a href="https://doi.org/10.1186/s12879-026-14673-w" rel="noopener noreferrer">https://doi.org/10.1186/s12879-026-14673-w</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12879-026-14673-w" rel="noopener noreferrer">10.1186/s12879-026-14673-w</a></p>
<p><strong>Keywords:</strong> infant HIV, Ethiopia, mother-to-child transmission, systematic review, meta-analysis, pooled prevalence, regional variation, antiretroviral therapy, early infant diagnosis, prevention programs, Pooled, prevalence</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">327102</post-id>	</item>
		<item>
		<title>Cyberbullying Follows School Violence Into the Digital World, Study of 4,200 Teens Finds</title>
		<link>https://scienmag.com/cyberbullying-follows-school-violence-into-the-digital-world-study-of-4200-teens-finds/</link>
		
		<dc:creator><![CDATA[Courtney Benton]]></dc:creator>
		<pubDate>Sat, 10 Oct 2026 04:03:20 +0000</pubDate>
				<category><![CDATA[Social Science]]></category>
		<category><![CDATA[Adolescent Mental Health]]></category>
		<category><![CDATA[adolescents]]></category>
		<category><![CDATA[Brazil]]></category>
		<category><![CDATA[bullying]]></category>
		<category><![CDATA[cyberbullying]]></category>
		<category><![CDATA[FAPESP]]></category>
		<category><![CDATA[latent class analysis]]></category>
		<category><![CDATA[latent class analysis in bullying research]]></category>
		<category><![CDATA[Mental health]]></category>
		<category><![CDATA[online and offline bullying]]></category>
		<category><![CDATA[overlap of physical and digital aggression]]></category>
		<category><![CDATA[prevention programs]]></category>
		<category><![CDATA[psychological distress in adolescents]]></category>
		<category><![CDATA[school violence]]></category>
		<category><![CDATA[school violence and aggression]]></category>
		<category><![CDATA[school violence prevention strategies]]></category>
		<category><![CDATA[sociodemographic factors in teen violence]]></category>
		<category><![CDATA[substance use]]></category>
		<category><![CDATA[substance use among teens]]></category>
		<category><![CDATA[teenage social behavior and violence]]></category>
		<category><![CDATA[Unifesp]]></category>
		<category><![CDATA[victim-perpetrators]]></category>
		<category><![CDATA[youth victimization patterns]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=257330</guid>

					<description><![CDATA[A Brazilian study of 4,200 adolescents found that cyberbullying typically extends in-person school violence, with victim-perpetrators in multiple contexts showing an elevenfold higher likelihood of clinically significant psychological distress and elevated substance use.]]></description>
										<content:encoded><![CDATA[<p>Cyberbullying among adolescents rarely exists as a separate, purely online phenomenon. Instead, according to a large new study from Brazil, it almost always functions as an extension of physical and verbal aggression already circulating in the school environment. The research, conducted at the Federal University of São Paulo (Unifesp) and published in the journal Psychiatry Research, followed 4,200 students ranging from the seventh grade of elementary school through the third grade of high school, and mapped in unprecedented detail how patterns of victimization, aggression, psychological distress, and substance use overlap in young people&#8217;s lives.</p>
<p>The study&#8217;s central methodological innovation was its use of latent class analysis, a statistical technique that identifies probabilistic clusters within a population rather than forcing adolescents into isolated, predefined categories such as &#8220;online victim&#8221; or &#8220;physical aggressor.&#8221; Most previous research on bullying has examined these categories separately, using distinct data sets and analytical frames. By contrast, the Unifesp team analyzed associations between violent involvement, psychological symptoms, drug use, and sociodemographic factors simultaneously, allowing the data to reveal how different forms of violence tend to co-occur in the same young person.</p>
<p>The analysis identified three distinct profiles. The largest group, comprising 48 percent of the sample, showed no significant association with any type of violence. The second group, representing 46 percent, consisted of adolescents who are frequently bullied at school and sometimes engage in bullying themselves, but who rarely participate in cyberbullying. The third and smallest group, just 6 percent of the sample, proved to be the most complex and the most vulnerable: so-called victim-perpetrators who both experience and perpetrate aggression across multiple contexts, moving frequently between physical school environments and online spaces.</p>
<p>Although this third group is numerically small, its members carry a disproportionate burden of harm. More than half of the adolescents classified as victim-perpetrators in multiple contexts — 52.4 percent — exhibited psychological symptoms at a clinically significant level, compared with 12.5 percent of those not involved in bullying at all. That difference translates into an elevenfold higher likelihood of psychological distress. The pattern extended to substance use as well: seven out of ten members of this group had consumed alcohol at some point in their lives, and their rate of cigarette use was nearly three times higher than that of peers uninvolved in bullying incidents.</p>
<p>&#8220;The research shows that violence against the same young person occurs both at school and online, indicating that cyberbullying is often an extension of in-person conflict,&#8221; says Professor Zila Sanchez, head of the Department of Preventive Medicine at Unifesp and coordinator of the study. &#8220;We have to look very closely at these young people involved in multiple contexts. It isn&#8217;t just bullying. It includes mental health issues and the use of alcohol and other drugs. There&#8217;s no way to separate them.&#8221; Sanchez argues that the findings reinforce a growing body of evidence that fragmented interventions — one program for mental health, another for drug prevention, a third against bullying — fail to address the interconnected reality of adolescent risk in Brazil.</p>
<p>The demographic breakdown of the high-risk group adds a further layer of concern. Girls were more likely to be victims of bullying, while boys predominated in the multiple-context victim-perpetrator group. Younger adolescents and Black and Brown students were also more likely to fall into the highest-risk category, a finding the researchers say underscores the importance of building social and racial inequalities into the design of prevention strategies rather than treating bullying as a uniformly distributed phenomenon.</p>
<p>One of the study&#8217;s most counterintuitive findings concerned screen time. Despite widespread public anxiety about how many hours teenagers spend online, the researchers found that screen time did not distinguish between the risk groups, even though most students in the sample spent four or more hours online each day. &#8220;We were unable to distinguish, based on the number of hours, any differences in impact between those exposed to cyberbullying and those not exposed to any type of violence,&#8221; Sanchez explains. &#8220;It has much more to do with the group they interact with on WhatsApp, for example, which is generally the same as their school group. Parents often think that keeping their children away from screens protects them. Protection isn&#8217;t just about limiting screen time; it&#8217;s also about what teenagers are doing, who they&#8217;re interacting with, and what&#8217;s happening.&#8221;</p>
<p>For parents and educators seeking warning signs, Sanchez draws a distinction between ordinary adolescent turbulence and genuine cause for alarm. Typical behavioral changes tend to be temporary, but isolation, aggression, irritability, or disruptive behavior become red flags when they are frequent and begin to interfere with a young person&#8217;s studies, social life, or other domains. She also stresses that bullying extends far beyond physical violence, which accounts for only a minority of cases and is the form schools most readily intervene against. Bullying can involve social exclusion, humiliation, hiding belongings, or repeated comments about physical appearance. &#8220;Cases range from frequently excluding a student from games or conversations to the point where they would rather stay in the classroom during recess to insults about their appearance, weight, and other characteristics,&#8221; she says. &#8220;That often goes undiagnosed by the school.&#8221;</p>
<p>The study arrives amid a shifting legal and statistical landscape in Brazil. Since 2024, bullying and cyberbullying have been classified as crimes under Law No. 14.811, defined as &#8220;systematic intimidation&#8221; and &#8220;systematic virtual intimidation&#8221; involving intentional, repetitive physical or psychological violence, with penalties on conviction ranging from a fine to up to four years of imprisonment. The 20th Brazilian Yearbook of Public Safety, produced by the Brazilian Forum on Public Safety, recorded 4,549 police reports of bullying against children and adolescents in 2025, a 68.2 percent increase over the previous year, alongside 677 reports of cyberbullying, up 61.4 percent. Experts caution that these figures largely reflect the most serious cases that extend beyond school walls, and that the sharp rise stems primarily from the new law&#8217;s implementation rather than a sudden surge in violence. Meanwhile, the National School Health Survey (PeNSE 2024), conducted by the Brazilian Institute of Geography and Statistics, shows the percentage of students reporting being bullied rising from 23 percent in 2019 to 27 percent in 2024, meaning four in ten students aged 13 to 17 now report having been victims of bullying at school.</p>
<p>The research is already shaping public policy. It forms part of Prev.Action, a thematic project funded by the São Paulo Research Foundation (FAPESP) that evaluates strategies for preventing alcohol use among adolescents in four municipalities in the interior of São Paulo state, and its findings contributed directly to the creation of Prisma, a program launched in 2026 for eighth- and ninth-grade elementary students. Prisma is currently being tested in 36 state schools across six cities, with nearly 5,000 adolescents participating. Teachers receive training, materials, and implementation support, while students complete twelve lessons covering drug prevention, bullying, cyberbullying, and emotional education, with initial results expected after an end-of-year follow-up. &#8220;The seed is being planted with this FAPESP-funded study so that we can develop a program in partnership with the state,&#8221; says Sanchez, who is also coordinating the program. &#8220;The research made it possible to test a public policy in the field. The study identified gaps, guided the refinement of interventions, and translated its findings into school-based practice.&#8221; The study&#8217;s first author is biomedical researcher Augusto Henrique Roiz Druziani, supported by a FAPESP doctoral scholarship, with postdoctoral fellow Luís Eduardo Soares dos Santos among the co-authors. Taken together, the findings deliver a clear message to schools, families, and policymakers: the digital and physical worlds of adolescent violence are one continuous ecosystem, and effective prevention must treat it that way.</p>
<p><strong>Subject of Research:</strong> Patterns of bullying and cyberbullying involvement and their links to mental health and substance use among Brazilian adolescents</p>
<p><strong>Article Title:</strong> Cyberbullying rarely occurs in isolation; it functions as an extension of school violence</p>
<p><strong>Article References:</strong> Cyberbullying rarely occurs in isolation; it functions as an extension of school violence. (n.d.). <a href="https://www.eurekalert.org/news-releases/1147127" rel="noopener noreferrer">Original publication</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> Not provided</p>
<p><strong>Keywords:</strong> cyberbullying, bullying, adolescents, school violence, mental health, substance use, latent class analysis, Brazil, victim-perpetrators, prevention programs, Unifesp, FAPESP</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">257330</post-id>	</item>
		<item>
		<title>Empathy, Not Dominance, Predicts Sexual Aggression Risk in Landmark Model Test</title>
		<link>https://scienmag.com/empathy-not-dominance-predicts-sexual-aggression-risk-in-landmark-model-test/</link>
		
		<dc:creator><![CDATA[Courtney Benton]]></dc:creator>
		<pubDate>Sat, 12 Sep 2026 15:32:36 +0000</pubDate>
				<category><![CDATA[Social Science]]></category>
		<category><![CDATA[Bem Sex-Role Inventory]]></category>
		<category><![CDATA[confluence model]]></category>
		<category><![CDATA[confluence model of sexual violence]]></category>
		<category><![CDATA[Critical]]></category>
		<category><![CDATA[dominance/nurturance]]></category>
		<category><![CDATA[empathy]]></category>
		<category><![CDATA[empathy versus dominance in men]]></category>
		<category><![CDATA[empirical validation of empathy's role]]></category>
		<category><![CDATA[gender attitudes and aggressive behavior]]></category>
		<category><![CDATA[gender-based violence research]]></category>
		<category><![CDATA[hostile masculinity]]></category>
		<category><![CDATA[hostile masculinity and impersonal sexuality]]></category>
		<category><![CDATA[impersonal sexuality]]></category>
		<category><![CDATA[influence of nurturance on aggression]]></category>
		<category><![CDATA[long-term studies on sexual aggression predictors]]></category>
		<category><![CDATA[negative binomial regression]]></category>
		<category><![CDATA[personality traits linked to sexual aggression]]></category>
		<category><![CDATA[prevention programs]]></category>
		<category><![CDATA[psychological predictors of sexual assault]]></category>
		<category><![CDATA[response surface analysis]]></category>
		<category><![CDATA[role]]></category>
		<category><![CDATA[role of empathy in sexual violence]]></category>
		<category><![CDATA[sexual aggression]]></category>
		<category><![CDATA[sexual aggression risk prediction]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=195943</guid>

					<description><![CDATA[A new study of 300 men finds that empathy, rather than the dominance/nurturance dimension, predicts and buffers sexual aggression risk within the confluence model.]]></description>
										<content:encoded><![CDATA[<p>For nearly four decades, psychologists attempting to understand why some men commit sexual aggression have relied on a framework known as the confluence model, developed by Neil Malamuth. The model identifies two core risk factors: hostile masculinity, a constellation of hostility, distrust and adversarial attitudes toward women, and impersonal sexuality, a preference for casual, uncommitted sexual encounters. A third element has long lingered at the model&#8217;s edges, the personality dimension of dominance versus nurturance. New research published in Archives of Sexual Behavior now delivers a striking verdict on that element: it may have been standing in for something else all along, and that something is empathy.</p>
<p>The study, led by Philipp Yorck Herzberg of Helmut-Schmidt-University in Hamburg together with colleagues at the European Distance University Hamburg and the University of Bern, set out to answer a question posed nearly thirty years earlier by Dean and Malamuth. Those researchers had found in 1997 that the interaction between hostile masculinity and impersonal sexuality robustly predicted sexual aggression only among men high in dominance and low in nurturance, a pattern they interpreted as possibly driven by empathy. Nurturant individuals, after all, tend to be warm, gentle and sensitive to others&#8217; needs, traits closely linked to empathic capacity. But the question remained whether empathy itself was the critical protective ingredient, or merely one facet of the broader dominance-nurturance dimension.</p>
<p>To disentangle the two, the researchers recruited 300 heterosexual men aged 18 to 65 through online advertisements on social networks and internet forums, without disclosing that the survey concerned sexual aggression. Participants completed the German version of the Sexual Experience Survey, a ten-item count of sexually coercive behaviors ranging from verbal manipulation to physical force or incapacitation through alcohol or drugs. Hostile masculinity was measured with the Hostile Sexism Scale of the Ambivalent Sexism Inventory, impersonal sexuality with the revised Sociosexual Orientation Inventory, and dominance and nurturance with the revised Bem Sex-Role Inventory. Crucially, empathy was assessed with the German adaptation of Davis&#8217;s Interpersonal Reactivity Index, which captures perspective taking, fantasy, empathic concern and personal distress.</p>
<p>Statistically, the team faced a technical challenge. Sexual aggression scores are count variables, skewed toward zero, with roughly sixty percent of participants reporting no aggressive acts at all. Ordinary linear regression would violate the distributional assumptions of such data. The researchers therefore employed latent negative binomial regression models within a structural equation modeling framework, comparing three nested models: one in which empathy&#8217;s effect was constrained to zero, one in which dominance/nurturance&#8217;s effect was constrained to zero, and one in which both were freely estimated. Latent modeling also sidestepped the notorious unreliability of difference scores, which the dominance-nurturance variable required.</p>
<p>The results were unambiguous. Across all three models, hostile masculinity and impersonal sexuality emerged as significant positive predictors of sexual aggression, confirming their status as the model&#8217;s core risk factors. Empathy, by contrast, acted as a significant negative predictor: men higher in empathy reported lower rates of sexually aggressive behavior. In the model combining all predictors, each unit increase in empathy reduced the expected rate of sexual aggression by roughly a third, while each unit increase in hostile masculinity multiplied the expected rate by about 1.46 and impersonal sexuality by 1.25. The dominance/nurturance difference score, however, contributed nothing, neither directly nor in interaction with the two risk factors.</p>
<p>Model fit statistics told the same story. The model containing empathy but excluding dominance/nurturance achieved the best fit according to the Akaike information criterion, the Bayesian information criterion and sample-size-adjusted variants. Because dominance/nurturance showed no effect to begin with, there was no effect for empathy to replace or explain away, despite a substantial negative correlation of minus 0.52 between empathy and the dominance/nurturance score. The authors conclude that whatever predictive value the dominance-nurturance dimension once appeared to hold was likely attributable to its overlap with empathy, and that future confluence model research should replace it with direct empathy measures.</p>
<p>One finding added an unexpected layer of nuance. Although the hostile masculinity by impersonal sexuality interaction failed to reach significance in the count regression models, complementary response surface analysis confirmed a synergistic effect. Using a shifted and rotated squared difference model, the analysis revealed that risk climbs steeply and nonlinearly when hostile masculinity is high, even when impersonal sexuality is only moderate. The interaction, in other words, is asymmetric and driven primarily by hostile masculinity. The authors caution that previous studies reporting interaction effects with ordinary linear regression may have overestimated them, and that appropriate count regression techniques may simply make interactions harder to detect, making the response surface approach a valuable complement.</p>
<p>Why does empathy matter so much? The authors suggest that when a man can take the perspective of a potential victim and imagine how coercive behavior would feel from her side, the behavior becomes less likely to be carried out, independently of his hostility toward women or his preference for uncommitted sex. The prevalence figures underline how rare protective combinations are. The high-risk profile of high hostile masculinity, high impersonal sexuality and low empathy appeared in only 5.7 percent of the sample, whereas the opposite profile combining all three risk traits with high empathy occurred in fewer than one percent of participants, a scarcity that may also explain why the three-way interaction just failed to reach statistical significance.</p>
<p>The practical implications reach into prevention. Interventions that merely attack hostile attitudes have often proven ineffective over time because the underlying traits are stable, and some programs may even provoke reactance and boomerang effects in high-risk men. Earlier work by Schewe and O&#8217;Donohue showed that programs targeting victim empathy can partially succeed in increasing empathic concern and reducing risk factors such as acceptance of interpersonal violence. The present findings strengthen the case for empathy-enhancing components in prevention programs aimed at high-risk men. At the same time, the open question of whether empathy operates as a moderator or as an independent protective factor has direct practical weight: if both pathways exist, different groups of aggressive men may require different interventions.</p>
<p>The study carries limitations that its authors freely acknowledge. The cross-sectional design rules out causal claims, and longitudinal work is needed to establish temporal ordering among the constructs. The sample, though spanning a broad adult age range, was restricted to heterosexual men and relatively small, and hostile masculinity was operationalized solely as hostility toward women rather than the full heterogeneous construct including sexual dominance. Replication in more diverse populations and with broader measures is essential. Nevertheless, the message is clear and consequential. Within the confluence model, hostile masculinity and impersonal sexuality remain the drivers of risk, dominance/nurturance should step aside, and empathy emerges as a measurable, modifiable protective factor that may be the most promising lever for reducing sexual aggression.</p>
<p><strong>Subject of Research:</strong> The roles of empathy and dominance/nurturance in predicting male sexual aggression within the confluence model</p>
<p><strong>Article Title:</strong> The Critical Role of Empathy Over Dominance/Nurturance in Predicting Sexual Aggression in the Confluence Model</p>
<p><strong>Article References:</strong> Herzberg, P. Y., Brunner, H., Wildfang, S., &amp; Troche, S. J. (2026). The Critical Role of Empathy Over Dominance/Nurturance in Predicting Sexual Aggression in the Confluence Model. <em>Archives of Sexual Behavior, 55</em>(6), 2627-2641. <a href="https://doi.org/10.1007/s10508-026-03510-5" rel="noopener noreferrer">https://doi.org/10.1007/s10508-026-03510-5</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s10508-026-03510-5" rel="noopener noreferrer">10.1007/s10508-026-03510-5</a></p>
<p><strong>Keywords:</strong> confluence model, sexual aggression, empathy, hostile masculinity, impersonal sexuality, dominance/nurturance, Bem Sex-Role Inventory, negative binomial regression, response surface analysis, prevention programs, Critical, Role</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">195943</post-id>	</item>
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