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(https://www.psypost.org/your-eyes-could-reveal-the-first-signs-of-many-diseases/) Your eyes could reveal the first signs of many diseases
Dec 28th 2024, 08:00

Melissa, a 30-year-old educator, came to the emergency department with a sudden onset of double vision. She had not been in an accident or suffered any trauma and had never experienced this symptom before. However, she noted that a few months earlier, the vision in one of her eyes had become blurred and then returned to normal shortly after. She told herself it was a sign of fatigue after a period of intense work on a screen.
After some basic optometric tests, then more advanced tests of visual perception, the visual episodes were thought to be related to (https://pubmed.ncbi.nlm.nih.gov/25877966/) multiple sclerosis. Melissa was then referred to a neuro-ophthalmology specialist who confirmed the diagnosis, and she was quickly treated.
Is Melissa’s case unique? Over my 30 years working as an optometrist, I’ve seen many patients with different vision and eye health problems, the cause of which turned out to be an illness they didn’t know they had.
As a professor at the School of Optometry at the Université de Montréal, I teach students that certain ocular symptoms can be linked to general health problems. Optometrists are trained to identify the various diseases that can manifest themselves through the eyes and to work with other health professionals to manage them.
Diabetes
Because diabetes will affect almost (https://pubmed.ncbi.nlm.nih.gov/19896746/) 8 per cent of the population by 2030, screening is a crucial issue. However, it is estimated that diabetes is not generally diagnosed until (https://doi.org/10.2337/dc13-2101) six to 13 years after its onset. An eye health examination can shorten this delay since it is often possible to identify characteristic lesions of the disease at the back of the eye before other symptoms of diabetes appear.
Early diagnosis is crucial since within five years of diagnosis (i.e. 11 to 15 years after the onset of diabetes), 25 per cent of patients with Type 1 (juvenile diabetes) and 40 per cent of those with Type 2 (adult diabetes) who are treated with insulin will develop (https://www.consultant360.com/articles/ocular-manifestations-diabetes) eye lesions that can have a major effect on their vision. Early identification and rigorous monitoring of eye health (https://www.nei.nih.gov/learn-about-eye-health/eye-conditions-and-diseases/diabetic-retinopathy) significantly reduces the risk of blindness, which can happen when the disease is not treated.
Unmasking the silent killer
If diabetes affects a significant number of patients without them knowing it, what can be said about high blood pressure and high cholesterol? These two conditions significantly increase the (https://www.icm-mhi.org/en/prevention/adopt-healthy-lifestyle/risk-factors) risk of coronary heart disease or stroke in our societies.
The eye is the only place in the human body where blood vessels can be seen without having to make an incision or use invasive techniques.

High blood pressure (known as (https://www.fda.gov/drugs/special-features/high-blood-pressure-understanding-silent-killer) the silent killer) can be seen by (https://eyewiki.aao.org/Hypertensive_Retinopathy) crushing of vessels and very specific signs on the retina.
Hypercholesterolaemia creates (https://www.ncbi.nlm.nih.gov/books/NBK279327/) cholesterol deposits inside the vessels.
Atherosclerosis is associated with (https://www.ncbi.nlm.nih.gov/books/NBK470445/) Hollenhorst plaques, also visible inside the vessels.
Cholesterol can also be seen in the cornea (lipid arc) or in (https://www.medicalnewstoday.com/articles/321267) the adnexa (xanthelasma).

In all these cases, very often the symptoms experienced by the patient are so few, or progress so slowly, that he or she considers them almost normal.
Normotensive or open-angle glaucoma
The absence of symptoms is also the norm for glaucoma. This pathology of the optic nerve is usually associated with excessive production of (https://www.aao.org/eye-health/anatomy/aqueous-humor) aqueous humour in the eye or a deficit in its evacuation.
The pressure inside the eye then increases and through different mechanisms leads to the loss of nerve fibres in the nerve. The visual field narrows very slowly (and therefore can go unnoticed), so the person ends up with tunnel vision after several years.
By the time this loss of vision affects them, it is often late, so the damage to the optic nerve can be very extensive. This damage is mainly ocular, although it can also be induced by the effect of certain drugs (https://eyewiki.aao.org/Steroid-Induced_Glaucoma) (such as cortisone).
Normotensive glaucoma is of a completely different nature. In this case, the pressure inside the eye remains normal but the nerve is still damaged. The mechanisms at play are different from those in chronic open-angle glaucoma.
Normotensive glaucoma is often associated with (https://www.mayoclinic.org/diseases-conditions/glaucoma/symptoms-causes/syc-20372839) low blood pressure or conditions such as sleep apnea. If it is present, the patient must be referred to a family doctor for a thorough investigation.
The disease of the century
Because cancer is becoming so widespread and is expressed in so many ways, we call it the disease of the century. Cancers that affect the eye (retinoblastoma) can also cause (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5256122/) metastases to the lungs and liver.
Here again, the disease often develops without symptoms until it is too late. So early detection is crucial, because the patient’s very survival is at stake.
Other types of asymptomatic retinal pigment (shaped like a bear’s paw) may be associated with cancer of the colon, which has (https://webeye.ophth.uiowa.edu/eyeforum/atlas/pages/bear-tracks-CHRPE.htm#gsc.tab=0) a very negative prognosis if management is delayed.
A simple visual field measurement may reveal abnormalities that some patients are unaware of, or that they consider so benign they don’t bother to report them. However, many visual field abnormalities hide brain tumours, such as (https://www.brighamandwomens.org/neurology/neuro-ophthalmology/visual-problems-due-to-pituitary-tumors) pituitary adenoma, or (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6844511/) nerve fibres compressed by blood vessels.
Abnormal eye movements, asymmetric pupillary responses, sudden reading problems or the appearance of diplopia are all yellow flags that require further ocular and neurological investigation.
Rather than the mirror of the soul, the eyes become an open window on our overall health. That makes regular consultations with an optometrist more important than ever, even when there are no symptoms. Many disorders can be detected and treated to either minimize illnesses or prevent them altogether.
 
This article is republished from (https://theconversation.com) The Conversation under a Creative Commons license. Read the (https://theconversation.com/your-eyes-could-reveal-the-first-signs-of-many-diseases-238486) original article.

(https://www.psypost.org/ai-powered-study-reveals-brain-patterns-behind-small-animal-phobia/) AI-powered study reveals brain patterns behind small animal phobia
Dec 28th 2024, 06:00

A new study recently published in (https://doi.org/10.1111/psyp.14716) Psychophysiology has used machine learning to identify brain structures and networks associated with small animal phobia. The findings reveal distinct gray matter features and macro-networks that differentiate individuals with this phobia from those without it. These results not only highlight the brain’s role in phobic reactions but also suggest pathways for potential future interventions.
Small animal phobia, which involves an intense and irrational fear of creatures like insects, spiders, or rodents, affects about 10% of the population. Despite its prevalence, the neurological mechanisms underlying this condition remain poorly understood. Previous studies have identified various brain regions activated during exposure to phobic stimuli but often relied on limited sample sizes or focused on narrow brain areas. The current study aimed to address these gaps by employing a whole-brain approach and advanced machine learning techniques.
“At the (https://r.unitn.it/en/dipsco/clian) Clinical and Affective Neuroscience Lab, our focus is on developing neuro-predictive models of personality and normal and abnormal affective states,” said study author (http://www.alessandrogrecucci.it/profile/) Alessandro Grecucci, a professor of affective neuroscience and neurotechnology at the University of Trento.
“Small animal phobia is a particular type of anxiety disorder that has been poorly explored in neuroscientific research. Of note, the few studies conducted so far have suffered from some methodological limitations, such as the use of massive univariate analyses and small, unbalanced samples, resulting in inconsistent findings. Moreover, the possibility of predicting small animal phobia from brain features has not been assessed.”
For their study, the research team analyzed structural brain imaging data from 122 adult participants, 32 of whom were diagnosed with small animal phobia. The remaining 90 participants served as a control group. Participants with the phobia were identified using clinical diagnostic tools, ensuring that their condition was the primary psychological disorder. All participants underwent high-resolution magnetic resonance imaging (MRI) scans, which were then processed using advanced neuroimaging software.
To analyze the data, researchers employed a binary support vector machine, a machine learning algorithm designed to identify patterns in complex datasets. The model was trained to classify phobic and non-phobic individuals based on gray matter features. To enhance reliability, the team used cross-validation techniques and accounted for differences in imaging equipment.
The analysis revealed significant structural differences in the brains of individuals with small animal phobia compared to controls. At a whole-brain level, the machine learning model achieved an accuracy of approximately 80%, demonstrating its ability to differentiate phobic individuals based on their brain anatomy. Several key brain regions emerged as pivotal in the classification process:

Cerebellum: Traditionally associated with motor coordination, this region was implicated in emotional processing and fear-related responses in phobic individuals.
Amygdala: Known for its role in fear and threat detection, the amygdala showed structural differences that likely contribute to heightened emotional responses.
Temporal lobes and temporal pole: These regions, involved in memory and emotional processing, may enhance the recall and emotional salience of phobic stimuli.
Frontal cortex: The orbitofrontal cortex and other frontal areas, essential for emotional regulation and decision-making, appeared to play a role in controlling phobic responses.
Thalamus: This sensory relay center may heighten sensory processing in response to phobic stimuli.

“This study aimed at developing a neuro-predictive model to detect individuals with small animal phobia based on morphometric features (such as grey or white matter), utilizing a machine learning method known as binary support vector machine (SVM) approach,” Grecucci told PsyPost. “This model identified a set of brain regions associated with emotional perception and regulation, cognitive control, and sensory integration, including the amygdala, the cerebellum, the temporal pole, the temporal lobes, and the thalamus. These regions are highly predictive of having a small animal phobia. In other words, if you have morphometric alterations in these regions you probably have a small animal phobia.”
The analysis also explored specific brain networks to understand their collective contribution to small animal phobia. The default mode network emerged as the most predictive, outperforming the whole-brain analysis with an accuracy of over 80%. This network, typically associated with self-referential thinking, may reflect heightened internal focus and rumination linked to phobic fears. The affective network, comprising regions such as the amygdala, orbitofrontal cortex, and insula, also showed strong predictive power, highlighting its role in emotional regulation and reactivity.
“Our findings revealed that the default mode network was among the most predictive, reaffirming its significant role in psychopathology,” Grecucci said. “Furthermore, we examined a novel affective network, comprising cortical and subcortical regions previously linked to emotional processing, which demonstrated an excellent predictive power.”
Other networks, including the central executive network and the sensorimotor network, demonstrated significant but less precise contributions to classification. The central executive network, involved in attentional control, may reflect heightened vigilance toward threat-related stimuli. The sensorimotor network likely represents the physical manifestations of phobic responses, such as avoidance behaviors and heightened readiness for action.
While the study represents a significant advancement in understanding small animal phobia, it has limitations. The relatively small sample size, particularly of phobic individuals, may limit the generalizability of the findings. Future studies with larger and more diverse samples are needed to validate and expand upon these results.
Additionally, this study focused exclusively on gray matter features, excluding other potentially relevant aspects such as white matter or functional connectivity. Incorporating these factors in future research could provide a more comprehensive understanding of the brain mechanisms underlying phobias.
“We believe this line of research on neuro-predictive models of normal and abnormal affective states that rely on machine learning methods may provide valuable insights into the neural basis of psychological disorders, offering novel research directions and suggesting potential strategies for improved diagnostics and treatment,” Grecucci said.
The study, “(https://doi.org/10.1111/psyp.14716) The phobic brain: Morphometric features correctly classify individuals with small animal phobia,” was authored by Alessandro Scarano, Ascensión Fumero, Teresa Baggio, Francisco Rivero, Rosario J. Marrero, Teresa Olivares, Wenceslao Peñate, Yolanda Álvarez-Pérez, Juan Manuel Bethencourt, and Alessandro Grecucci.

(https://www.psypost.org/psilocybin-alters-how-rats-balance-risks-and-rewards-researchers-find/) Psilocybin alters how rats balance risks and rewards, researchers find
Dec 27th 2024, 14:00

New research published in (https://www.sciencedirect.com/science/article/abs/pii/S1074742724000650) Neurobiology of Learning and Memory sheds light on how psilocybin, a compound found in certain psychedelic mushrooms, affects behaviors involving the balance of reward and punishment. Conducted on male and female rats, researchers at Oregon Health & Science University found that psilocybin influenced how these animals learned and responded to situations involving potential risks.
Psilocybin is a naturally occurring psychedelic compound found in certain types of mushrooms. Once ingested, it is converted in the body into psilocin, which interacts with the brain by activating serotonin-2A receptors. These receptors play a key role in regulating mood, cognition, and perception.
Over the past decade, psilocybin has gained significant attention for its potential as a treatment for mental health conditions like depression and anxiety, particularly in cases where traditional therapies have been ineffective. Clinical studies have shown that even a single dose of psilocybin can lead to rapid and lasting improvements in mood, making it a promising option for conditions that are notoriously difficult to treat.
Despite its therapeutic potential, much about how psilocybin works remains unclear. Most research to date has focused on its effects in reducing fear and anxiety or enhancing emotional processing. However, real-life decision-making often involves balancing rewards and risks. For instance, individuals might need to decide whether pursuing a goal is worth the potential negative consequences—a process often disrupted in mental health disorders.
People with anxiety might avoid potentially rewarding situations out of fear, while those with addictive behaviors might take excessive risks despite knowing the possible harm. Understanding how psilocybin influences this type of conflict between reward and punishment is essential for uncovering its broader therapeutic mechanisms.
To better understand how psilocybin affects the learning and execution of behaviors that involve weighing risks against rewards, the researchers conducted a controlled experimental model with rats. Fifty-five adult Long-Evans rats, both male and female, were trained to perform tasks in specially designed operant chambers. These chambers included two illuminated “nose-poke” stations and a food dispenser.
Rats were tasked with earning food rewards (sucrose pellets) by completing a sequence of two actions: a “seek” action followed by a “take” action. The “seek” action carried a risk of a mild footshock, while the “take” action was always safe and resulted in a reward.
The study was divided into two phases. In the first phase, researchers investigated the effects of psilocybin during the initial learning of risk-punishment associations. Rats were randomly assigned to receive either psilocybin or a saline solution (control) before starting their tasks. The second phase examined the effects of psilocybin after the rats had already learned the associations. In this phase, rats were again given psilocybin or, for comparison, another psychedelic compound called ±DOI. Researchers measured several outcomes, including how many tasks the rats completed (indicating their willingness to take risks), how long they hesitated before acting, and whether these behaviors changed under varying levels of risk.
During the learning phase, psilocybin produced different effects depending on the rats’ sex. Female rats treated with psilocybin were more cautious, showing greater suppression of the risky “seek” action compared to males and saline-treated females. This heightened sensitivity to punishment persisted even when the task was safe, suggesting that psilocybin may have enhanced the females’ ability to associate risk with specific actions. In contrast, males treated with psilocybin displayed behaviors similar to the control group during this phase.
After the learning phase, the effects of psilocybin shifted. When given psilocybin after the rats had already learned the task, both males and females became less inhibited, completing more tasks despite the risk of punishment. This reduction in cautious behavior was not observed in rats treated with ±DOI, indicating that the effects might be specific to psilocybin.
Interestingly, the decrease in cautiousness did not appear to be due to reduced sensitivity to the footshocks, as psilocybin did not significantly alter the threshold at which the rats reacted to shocks. Instead, it appeared to change their willingness to act despite the risks.
In addition to task performance, researchers conducted supplementary tests to evaluate whether psilocybin affected the rats’ sensitivity to footshocks or their natural tendency to explore risky situations using an elevated plus maze. This maze included two open arms (perceived as riskier by rats) and two enclosed arms (perceived as safer). Time spent in the open arms was used as a measure of the rats’ willingness to engage in risky exploration.
In the elevated plus maze, psilocybin-treated rats spent less time in the open arms compared to controls, indicating an increase in cautious behavior in a novel, risky environment. However, this effect was accompanied by reduced overall movement, suggesting that the observed behavior might also reflect a general reduction in exploratory activity.
These findings suggest that psilocybin’s effects on behavior are dynamic and context-dependent. By increasing caution during the learning phase and reducing it afterward, psilocybin may help individuals adapt to challenging situations more flexibly. This dual role could have implications for its therapeutic use, particularly in conditions like anxiety, where individuals often overestimate risks, or in depression, where risk-taking may be impaired.
Future studies could explore the long-term effects of psilocybin on behavior and its potential to reshape learned associations over time. Understanding how psilocybin interacts with other factors, such as stress or environmental cues, could also provide deeper insights into its therapeutic potential.
The study, “(https://doi.org/10.1016/j.nlm.2024.107954) Effects of psilocybin on uncertain punishment learning,” was authored by David S. Jacobs, Alina P. Bogachuk, Chloé L. Le Moing, and Bita Moghaddam.

(https://www.psypost.org/study-finds-accelerated-biological-aging-linked-to-smaller-brain-volumes/) Study finds accelerated biological aging linked to smaller brain volumes
Dec 27th 2024, 12:00

Accelerated biological aging is strongly associated with reductions in brain volumes, according to a study published in the (https://doi.org/10.1016/j.jad.2024.08.078) Journal of Affective Disorders.
Chen Liu and colleagues conducted this study to explore how (https://www.psypost.org/epigenetic-age-acceleration-moderates-the-link-between-loneliness-and-chronic-health-conditions/) biological aging relates to brain structure. While chronological age has been a standard measure in aging research, it often fails to capture individual differences in aging processes.
Recent methods for calculating biological aging, such as the Klemera-Doubal Method (KDM) and PhenoAge, leverage biomarkers to provide a more detailed understanding of aging. Previous studies have shown that brain volume decreases with age, with significant loss occurring in regions like the gray matter, white matter, and hippocampus. However, the role of biological aging in these structural changes is less understood.
Leveraging advancements in neuroimaging and biomarkers, this study bridges biological and structural measures of aging to better understand neurodegenerative processes.
Liu and colleagues utilized data from the UK Biobank, a large-scale, population-based cohort consisting of over 500,000 participants. The researchers selected 14,725 individuals with complete data on relevant biomarkers and brain imaging. The sample had a mean age of ~ 55 years and approximately equal numbers of men and women. Brain volumes were measured using magnetic resonance imaging (MRI) and included gray matter, white matter, and specific brain structures such as the thalamus and hippocampus. These measurements were normalized and adjusted to account for inter-individual differences.
The study assessed biological aging using two advanced metrics, the KDM and PhenoAge, both derived from blood chemistry data. KDM incorporates biomarkers like albumin, creatinine, and C-reactive protein, while PhenoAge uses overlapping and additional biomarkers related to mortality risk. Both metrics provided a measure of biological aging acceleration by calculating the residual differences between biological aging and chronological age. These residuals, termed KDM-acceleration and PhenoAge-acceleration, reflected the extent to which an individual’s biological aging diverged from their chronological age.
Key demographic and lifestyle factors, such as sex, body mass index (BMI), smoking status, physical activity, and socioeconomic deprivation (measured by the Townsend Deprivation Index, TDI), were included as covariates to minimize confounding influences.
The study revealed a strong connection between accelerated biological aging and decreases in brain volume across several key regions. Individuals with higher levels of biological aging, as measured by two advanced biomarkers, tended to have less gray matter and white matter, as well as smaller hippocampus and thalamus structures. This relationship persisted even after accounting for factors like age, sex, body mass index, and socioeconomic status. This suggests that biological aging, beyond chronological age, plays a significant role in structural brain changes.
Interestingly, the effects of biological aging on brain volume were influenced by certain demographic and socioeconomic factors. Women showed more pronounced reductions in brain volume linked to biological aging compared to men. Similarly, younger adults (those under 55) experienced stronger associations between biological aging and brain structure changes, highlighting the potential for these effects to begin earlier in life.
Furthermore, individuals living in more socioeconomically deprived conditions had greater brain volume loss associated with biological aging, suggesting that environmental factors may amplify these biological effects.
The study’s cross-sectional design limits causal inferences. Additionally, the predominantly White UK Biobank sample limits the generalizability of findings.
Overall, these results underscore the significant role of biological aging in brain volume reductions, highlighting the importance of early interventions targeting aging-related biomarkers.
The study, “(https://doi.org/10.1016/j.jad.2024.08.078) Association of Accelerated Biological Aging with Brain Volumes: A Cross-Sectional Study,” was authored by Chen Liu, Qingqing Cai, Yifan Gou, Ye Liu, Meijuan Kang, Jingni Hui, Ruixue Zhou, Panxing Shi, Bingyi Wang, and Feng Zhang.

(https://www.psypost.org/specific-types-of-impulsivity-serve-as-risk-factors-for-problematic-pornography-use/) Specific types of impulsivity serve as risk factors for problematic pornography use
Dec 27th 2024, 10:00

A recent meta-analysis published in (https://academic.oup.com/jsm/article-abstract/21/10/922/7740891) The Journal of Sexual Medicine has found a significant link between impulsivity and both general pornography use and problematic pornography use. The study highlights that specific dimensions of impulsivity, such as attentional impulsivity, nonplanning impulsivity, and positive urgency, are particularly associated with problematic use patterns. These findings suggest that impulsivity traits may serve as risk factors for developing compulsive behaviors related to pornography consumption.
With the rise of internet accessibility, pornography has become a common form of entertainment for many people. While some individuals engage in pornography consumption recreationally, others develop compulsive patterns of use that lead to significant personal and social problems. Known as problematic pornography use, this behavior is characterized by excessive and uncontrollable consumption, often despite adverse consequences like relationship challenges, mental health issues, and financial difficulties.
Previous studies have suggested that impulsivity—a personality trait linked to acting on urges without considering the consequences—may play a role in these behaviors. However, the existing literature on this topic has produced mixed results. To clarify these findings, researchers at the University of Florence conducted a meta-analysis. Their aim was to assess the overall relationship between impulsivity and pornography use and to examine whether certain impulsivity dimensions were more strongly associated with problematic behaviors.
The meta-analysis synthesized data from 27 studies, encompassing thousands of participants worldwide. Studies were included if they assessed pornography use, problematic pornography use, and impulsivity or related traits. The researchers utilized major academic databases, including Medline, Scopus, and Web of Science, to identify relevant articles published up to September 2023.
Each study was evaluated for quality, and the researchers extracted information on participant demographics, impulsivity measures, and the relationships between impulsivity traits and pornography use. Specific dimensions of impulsivity—such as attentional impulsivity, nonplanning impulsivity, and urgency—were analyzed using statistical models to determine their associations with problematic pornography use.
To account for variability across studies, the researchers used random-effects models. They also conducted meta-regressions to explore how factors like age and gender influenced the relationship between impulsivity and problematic pornography use.
The researchers found that general impulsivity was moderately associated with both recreational and problematic pornography use. Individuals with higher impulsivity scores were more likely to engage in pornography consumption and to develop patterns of use that interfere with their personal and social lives. This relationship suggests that a broad tendency to act impulsively, without deliberation or long-term planning, increases vulnerability to problematic behaviors.
When examining specific traits of impulsivity, the study revealed nuanced findings. Attentional impulsivity, which reflects difficulty maintaining focus and susceptibility to distraction, was strongly linked to problematic pornography use. This suggests that individuals who struggle to maintain attention may be particularly prone to impulsive engagement with online pornography, as the medium’s accessibility and novelty appeal to their distracted tendencies.
Nonplanning impulsivity, or a focus on immediate rewards rather than long-term outcomes, was another significant predictor of problematic pornography use. People with this trait may prioritize the instant gratification provided by pornography without considering its potential negative consequences, such as relationship issues or emotional distress.
Positive urgency—the tendency to act impulsively during moments of heightened positive emotion—also emerged as a risk factor, albeit with a smaller effect size. This finding indicates that individuals experiencing intense positive emotions may turn to pornography as a way to enhance their immediate sense of pleasure.
Interestingly, the study found a divergence in the role of sensation seeking—a desire for novel and stimulating experiences. While sensation seeking was positively associated with general pornography use, it showed no significant relationship with problematic pornography use. This suggests that while individuals with high sensation-seeking tendencies may explore pornography for its novelty and variety, these traits alone are insufficient to explain the transition to problematic patterns.
The researchers also uncovered moderating effects of age and gender in the relationship between impulsivity and problematic pornography use. Men exhibited a stronger link between impulsivity and problematic use compared to women. This difference may be influenced by societal and cultural factors, as men generally report higher rates of pornography consumption.
Additionally, younger individuals showed a stronger association between impulsivity traits and problematic use. This may be attributed to developmental factors, such as a less mature prefrontal cortex, which governs inhibitory control and decision-making.
The results highlight the role of impulsivity in problematic pornography use, particularly highlighting the importance of attentional impulsivity, nonplanning impulsivity, and positive urgency. But as with all research, there are some limitations to consider.
First, many included studies relied on correlational designs, making it difficult to determine causality. Longitudinal research is needed to clarify whether impulsivity leads to problematic pornography use or whether the behaviors exacerbate impulsivity traits over time.
Second, the analysis predominantly included studies conducted in Western countries, limiting the generalizability of findings to non-Western populations. Future research should explore cultural differences in pornography consumption and impulsivity.
Third, while the study identified gender and age as moderating factors, it did not fully explore the underlying mechanisms driving these differences. Investigating the role of social, hormonal, and neurological factors could provide deeper insights.
Finally, the researchers noted that impulsivity is a complex, multifaceted construct. Experimental studies are needed to identify specific interventions that can target these traits effectively and reduce the risk of problematic pornography use.
The study, “(https://doi.org/10.1093/jsxmed/qdae101) Pornography use, problematic pornography use, impulsivity, and sensation seeking: a meta-analysis,” was authored by Sara Bocci Benucci, Cristian Di Gesto, Simon Ghinassi, Silvia Casale, and Giulia Fioravanti.

Forwarded by:
Michael Reeder LCPC
Baltimore, MD

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