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  • Research Publications

    Prerequisites for the Formation of Sexual Perversions in Modern Youth: Research Results

    This post presents a theoretical and empirical study exploring the psychological and social prerequisites for the development of sexual perversions among modern youth. Conducted by researchers from Lviv State University of Internal Affairs and partner institutions, the study examines patterns of deviant sexual behavior, underlying personality traits, and social influences shaping youth sexuality in today’s environment.


    Authors:
    Anna Shydelko – Associate Professor, Department of Social and Behavioral, Humanities, and Economic Security, Institute of Management, Psychology and Security, Lviv State University of Internal Affairs, Lviv, Ukraine (UA)
    Tetiana Holovach – Ph.D. in Philology, Associate Professor, Lviv State University of Internal Affairs, Lviv, Ukraine (UA)
    Natalia Bamburak – Ph.D. in Psychology, Associate Professor, Lviv Regional Institute of Postgraduate Pedagogical Education, Lviv, Ukraine (UA)
    Halyna Barshatska – Ph.D. in Sociological Sciences, Associate Professor, National University “Zaporizhzhia Polytechnic”, Zaporizhzhia, Ukraine (UA)
    Serhii Shcherbyna – Ph.D. in Sociological Sciences, Associate Professor, National University “Zaporizhzhia Polytechnic”, Zaporizhzhia, Ukraine (UA)


    Research Focus and Purpose

    The study aims to identify psychological, social, and behavioral factors contributing to the emergence of deviant sexual behavior patterns in modern youth. Conducted between March and May 2022, the research involved 46 respondents aged 19–30, with 43.5% male and 56.5% female participants.

    By combining theoretical review with empirical testing, the authors sought to determine the relationship between personal traits, social influences, and sexual deviations, offering insights relevant for preventive education, social psychology, and behavioral counseling.

    Methodology

    The study used several standardized instruments to assess personality and behavioral tendencies:

    • O. Potemkina’s Sexual Profile Assessment Method – to evaluate patterns of sexual interest and orientation;
    • M. Horska’s Methodology for Determining the Tendency to Deviant Behavior – to identify broader behavioral risks;
    • A Questionnaire on Deviant Sexual Experience – to explore exposure to or engagement with non-normative sexual behaviors.

    Through these combined tools, researchers obtained both quantitative and qualitative data on youth perceptions, experiences, and predispositions regarding sexual conduct.

    Theoretical Background

    The article provides a comprehensive overview of the psychological and sociological literature addressing sexual perversions (or, more neutrally, deviant sexual behaviors). It explores the conceptual foundations of various forms of non-normative sexual expression and discusses how cultural, familial, and digital factors influence their formation.

    Among the examined categories are:
    autoeroticism, fetishism, exhibitionism, voyeurism (scopophilia), sadism, masochism, transvestism, and other phenomena traditionally defined in psychiatric and sociological discourse.

    The authors emphasize that modern youth are exposed to new forms of sexualized content and social communication, particularly through digital media and pornography, which can accelerate the desensitization of moral norms and alter perceptions of sexual boundaries.

    Key Findings

    • Certain psychological predispositions (e.g., impulsivity, emotional immaturity, and low self-control) were correlated with a higher tendency toward deviant sexual behavior.
    • Social environment and media exposure significantly shape youth attitudes toward sexuality, often normalizing previously taboo behaviors.
    • A lack of comprehensive sexual education and open discussion about healthy sexual behavior contributes to confusion, experimentation, and potential maladaptive patterns.
    • Both gender differences and individual personality factors play roles in how sexual deviations manifest or are expressed.

    Interpretation and Implications

    The study’s authors underscore that the findings should be interpreted within a psychological and educational framework, not a moralistic one. Understanding the prerequisites for deviant sexual behavior allows educators, psychologists, and policymakers to design more effective preventive programs, ethical education initiatives, and psychological support systems for young people.

    They also highlight the need for balanced sexual education, combining scientific understanding with value-based discussions about respect, empathy, and personal boundaries.

    Conclusion

    This research provides valuable insights into the complex interplay between psychological, social, and cultural factors influencing the formation of deviant sexual tendencies among youth. The authors advocate for a multidimensional approach — integrating psychological counseling, educational reform, and parental guidance — to foster healthier, more responsible sexual development in the modern age.


    Read the full article here: https://brain.edusoft.ro/index.php/brain/article/view/1356.

  • Research Publications

    Exploring AI and Computational Science in Predicting Outcomes of Conservative Treatment for Cervical Intraepithelial Neoplasia

    This post presents a preliminary research perspective on how artificial intelligence (AI) and computational methods can help identify predictive factors in the conservative management of cervical intraepithelial neoplasia (CIN), a precancerous condition strongly linked to HPV. The goal is to improve diagnosis, follow-up, and treatment decisions through smarter, data-driven tools.


    Authors:
    Maria Diana Focșa – Leonardo da Vinci University (CH)
    Radu Lefter – Romanian Academy (RO)
    Mihaela Tomaziu-Todosia – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)
    Bogdan Novac – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)
    Otilia Novac – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)
    Ecaterina Tomaziu-Todosia Anton – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)


    What Is This Study About?

    Cervical intraepithelial neoplasia (CIN) refers to precancerous changes in the cells of the cervix, most often caused by human papillomavirus (HPV). CIN is important to monitor because some lesions regress, while others can progress toward cervical cancer if not detected and managed in time.

    Current clinical practice relies on colposcopy-guided biopsy and imaging, but these methods depend a lot on the examiner’s experience. That’s where AI can make a difference.

    Why Use AI and Computational Science?

    The study, titled “A Preliminary View on Using AI and Computational Science for Observing Predictive Factors in Conservative Treatment of Cervical Intraepithelial Neoplasia,” explores how advanced algorithms can:

    • analyze colposcopy and cytology images automatically;
    • detect subtle patterns that indicate progression or regression;
    • help doctors decide which patients can safely continue conservative treatment;
    • support earlier prediction of cervical cancer risk.

    By integrating clinical data with AI-powered image analysis, healthcare providers could move toward more personalized, data-driven cervical cancer prevention.

    Key Benefits Highlighted

    • Higher diagnostic consistency – AI reduces subjectivity in image interpretation.
    • Better risk stratification – computational models can flag patients more likely to progress.
    • Support for conservative management – avoiding overtreatment while keeping high-risk patients under closer observation.
    • Foundation for future automated workflows in cervical screening.

    Conclusion

    This is an early, exploratory view, but it points clearly to the future: AI-assisted colposcopy and automated cervical cytology can significantly enhance how CIN is monitored and treated. As datasets grow and algorithms improve, such tools could become part of routine gynecological care, helping prevent cervical cancer more efficiently.

    Read the full text here: http://dx.doi.org/10.70594/brain/16.3/1.

  • News

    A Preliminary View on Using AI and Computational Science for Observing Predictive Factors in Conservative Treatment of Cervical Intraepithelial Neoplasia

    This study explores how artificial intelligence (AI) and computational science can enhance the detection, monitoring, and prediction of outcomes in the conservative treatment of Cervical Intraepithelial Neoplasia (CIN) — a range of precancerous lesions almost entirely caused by HPV infection.


    Maria Diana Focșa – Leonardo da Vinci University (CH)
    Radu Lefter – Romanian Academy (RO)
    Mihaela Tomaziu-Todosia – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)
    Bogdan Novac – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)
    Otilia Novac – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)
    Ecaterina Tomaziu-Todosia Anton – Grigore T. Popa University of Medicine and Pharmacy, Iași (RO)

    By integrating AI-assisted image analysis, mathematical modeling, and predictive algorithms, this research aims to support clinicians in automated cervical cytology, colposcopy examinations, and risk progression forecasting — offering new pathways toward precision medicine in gynecologic oncology.

    AI #MedicalResearch #ComputationalScience #CervicalCancer #HPV #PredictiveModeling #HealthcareInnovation #MachineLearning #WomenInScience

  • News

    New Research Insight: Neuroentropy and Consciousness

    In our upcoming issue (BRAIN, Vol. 16, Issue 4 – December 2025), we are pleased to feature the article:

    Díaz Palencia, J. L. (2025). Neuroentropy and consciousness: A meta-analytic review.

    This comprehensive meta-analysis explores neuroentropy—the complexity or diversity of brain activity—as a quantitative marker of consciousness. Drawing from EEG, MEG, fMRI, intracranial recordings, and perturbation-based methods (such as the Perturbational Complexity Index), the review synthesizes findings from 2013–2023.


    Key insights include:

    Higher entropy during wakefulness, REM sleep, and psychedelic states.

    Reduced entropy in anesthesia, deep sleep, and disorders of consciousness.

    Clinical applications of entropy measures in anesthesia monitoring and detecting covert awareness.

    The study highlights both the promise and the challenges of using brain complexity as an index for consciousness, making it a valuable contribution to the growing dialogue between neuroscience and artificial intelligence.

  • Research Publications

    The Social Media Addiction: What Have We Learned So Far? — A Review

    This post presents a comprehensive review of research on social media addiction, examining whether excessive use of social networks qualifies as a true behavioral disorder. The study, conducted by researchers from “Alexandru Ioan Cuza” University of Iași and the “Socola” Institute of Psychiatry, explores the psychological, demographic, and therapeutic dimensions of this modern phenomenon.


    Authors:
    Marius Dumitrescu – “Alexandru Ioan Cuza” University of Iași, Romania (RO)
    Nicoleta Dumitrescu – “Socola” Institute of Psychiatry, Iași, Romania (RO)
    Șerban Turliuc – “Socola” Institute of Psychiatry, Iași, Romania; Department of Psychiatry, “Grigore T. Popa” University of Medicine and Pharmacy, Iași, Romania (RO)


    Introduction: From Communication to Compulsion

    Over the last two decades, social media platforms like Facebook, Instagram, Twitter, and WeChat have revolutionized how people connect, share, and communicate. However, this digital expansion has also brought new psychological challenges.

    The concept of social media addiction (SMA) has emerged to describe patterns of compulsive and excessive engagement with online platforms — behaviors that mimic those seen in other forms of addiction.

    This review seeks to determine:

    • whether social media addiction can be considered a distinct behavioral disorder,
    • its demographic and psychological characteristics,
    • the health consequences it may cause,
    • and therapeutic interventions that can help individuals regain control.

    Is Social Media Use Really an Addiction?

    Currently, social media addiction is not formally recognized as a disorder in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Instead, it is classified by many scholars as a behavioral addiction or a subtype of Internet addiction.

    The authors discuss that, beyond neurobiological mechanisms, the roots of this dependency can be viewed through anthropological and philosophical perspectives — as a symptom of the human condition in a hyperconnected, performance-driven world where online identity often replaces authentic social interaction.


    Psychological and Health Consequences

    Excessive and compulsive use of social media can lead to a range of negative psychological and physical outcomes, including:

    • Reduced concentration and academic underperformance
    • Sleep disturbances (insomnia) due to late-night scrolling
    • Altered self-image and decreased self-esteem
    • Increased anxiety and depressive symptoms
    • Emotional instability and dependence on external validation

    The constant feedback loop of likes, comments, and notifications activates dopaminergic reward circuits, similar to those involved in substance use disorders, reinforcing repetitive checking and posting behavior.


    Demographic and Behavioral Factors

    Research suggests that younger users, particularly adolescents and young adults, are at higher risk of developing problematic social media habits.

    Key risk factors include:

    • High levels of boredom or loneliness;
    • Low self-esteem and social comparison tendencies;
    • Fear of missing out (FOMO);
    • Personality traits like neuroticism or impulsivity.

    The study emphasizes that these patterns are not limited by geography — SMA is a global behavioral trend shaped by digital accessibility and cultural attitudes toward technology.


    Prevention and Intervention

    Unlike substance addictions, where abstinence is the therapeutic goal, the objective in treating social media addiction is controlled, mindful use.

    The review highlights several effective therapeutic and preventive strategies:

    1. Cognitive-behavioral therapy (CBT) – helps individuals identify and reframe distorted thoughts related to social media use and replace compulsive behaviors with healthier routines.
    2. Digital detox programs – structured breaks from social media to restore focus and emotional balance.
    3. Self-monitoring tools – using screen-time trackers or app-limiters to create awareness of usage patterns.
    4. Psychoeducation and prevention campaigns – targeting young people to promote balanced digital habits.
    5. Family and school involvement – reinforcing real-world communication, emotional intelligence, and self-regulation.

    Conclusion

    Social media addiction reflects one of the paradoxes of the digital age: a technology designed to connect people has also fostered dependence, distraction, and emotional fragility.

    This review concludes that while SMA is not yet a recognized clinical disorder, its psychological impact and public health implications are undeniable. The focus should therefore shift toward awareness, education, and adaptive coping strategies, rather than strict prohibition.

    Controlled and conscious use — not abstinence — remains the key to preserving mental health and digital balance in a world increasingly defined by connectivity.


    Read the full article here: https://brain.edusoft.ro/index.php/brain/article/view/1361.

  • News

    BRAINews

    ✨ We’ve created this special section of the BRAIN. Broad Research in Artificial Intelligence and Neuroscience journal website to keep our readers, authors, and reviewers up to date with the latest news, updates, and developments.


    Stay connected with us as we continue to grow our academic community and share insights from the intersection of AI and neuroscience.