Poster Session II (Afternoon)

Dental professionals are regularly exposed to high levels of noise from work-related equipment which can contribute to Noise Induced Hearing Loss (NIHL). Overall, fostering awareness and education about the risks of NIHL and the benefits of using ear/hearing protection devices (EPDs/HPDs) are fundamental steps in promoting a culture of hearing protection among dental professionals. This approach not only enhances individual health and well-being but also contributes to a safer and more sustainable work environment in dental practices.

Quantum theory allows quantum systems to possess unique properties, such as being in a superposition of two possible physical states and/or correlations that are not possible to have between two classical systems, like entanglement. These properties are key ingredients that set quantum systems apart from classical ones and they constitute foundation of next generation quantum technologies, such as quantum computing. However, quantum systems inevitably interact with their environment, which results in the loss of genuine quantum properties. Despite, it is possible to find physically relevant open system settings that hinders the relaxation of the quantum system to the state of the environment. Such non-stationary states sustain emergent time periodic oscillations in their observable quantities. Our goal is to address the problem of determining the conditions under which this behavior emerges and their stability in interacting one-dimensional spin-1/2 systems that are dissipatively coupled an environment.

Containing thousands of galaxies embedded in Megaparsec-scale dark matter halos, galaxy clusters are the largest gravitationally bound structures in the Universe. The majority of the baryonic matter in these giant systems exists as a hot (T ~ 100 million Kelvin) diffuse intracluster medium (ICM) of ionized hydrogen and helium through which the galaxies orbit. Observable characteristics of the ICM (temperature, density, pressure, spatial distribution, etc.) are directly linked to cluster mass and, when resolved on the kiloparsec scale, reveal the role that AGN heating, radiative cooling, and cluster-cluster mergers play in the life of a galaxy cluster. To investigate the impact that glancing cluster mergers (off-axis collisions) have on ICM core evolution, we performed an analysis of the X-ray properties of a statistically representative, mass-limited sample of galaxy clusters observed with the Chandra X-ray Observatory out to a distance corresponding to 4 billion years of cosmic history.

This poster presentation examines the connection between Adverse Childhood Experiences (ACEs), children and youth in care, and the risk of sex trafficking. Youth with high ACEs—particularly those living in foster care, group homes, or residential treatment centers—face increased vulnerability, due to unstable placements and the targeting strategies of traffickers. Runaway youth are especially at risk. The presentation recommends comprehensive strategies for prevention and intervention at micro, mezzo, and macro levels of practice. Child welfare agencies should play a key role in identifying, supporting, and helping youth affected or at risk of sex trafficking. Inter-professional collaboration among child welfare workers and their organizations is crucial. Systemic barriers such as gender discrimination, racism, and poverty demand coordinated, multi-level responses. It is vital to strengthen legislation to protect trafficked youth from criminalization and to collect reliable data linking ACEs, care experiences, and trafficking risk to document and support effective services.

"Traditional medical practitioners (TMPs) such as herbalists, spiritual healers, and faith healers play a vital role in health care across Ghana, where they are often the first point of contact for people experiencing mental health challenges. Their knowledge is trusted, culturally embedded, and accessible in communities where formal services may be limited.

This project reports on a structured dialogue between TMPs and neuroscientists in Accra, Ghana. Nineteen practitioners participated in surveys and group discussions. Thematic analysis identified three central themes shaping collaboration: trust, communication, and training. TMPs expressed strong interest in joint research but also raised concerns about exploitation, intellectual property, and limited transparency. 

These findings highlight both the challenges and opportunities of building equitable TMP-scientist partnerships. Such collaborations can strengthen Ghana's mental health system and provide models for integrating traditional and scientific knowledge in other countries."

The State University of New York DSP Program, in partnership with New York State’s Office for People with Developmental Disabilities and the National Alliance for Direct Support Professionals (NADSP), provides direct support professionals with training that leads to national certification in the skills and competency areas unique to the field of direct support. Seventy-one students enrolled in level one of the Direct Support Professionals Microcredential Program offered through Farmingdale State College across the Spring 2024 (n=32), Summer 2024 (n=14), and Fall 2024 (n=31) semesters. Initial data indicate that the DSP Microcredential Program offered at Farmingdale State College was successful in fostering student success. Overall, 62.5% of the Spring 2024, 76.92% of the Summer 2024, and 83.90% of the Fall 2024 cohorts successfully completed all program requirements. These data are a crucial first step in providing empirically based best practices for successfully supporting adult learners in micro credential programs.

This presentation will describe my summer scholarship work drafting two book chapters for my monograph project currently titled Invisible Work, Visible Scars: Life with Hidradenitis Suppurativa, a Chronic Dermatological Condition. I will describe patient and provider of experience and how race, gender and class shape them. The book proposal was completed in Summer 2024 with Summer Scholarship Support and the 2025 support was to complete sample chapters for manuscript submission to NYU Press in Spring 2026.

This research draws on data from Reddit threads within Muslim, Protestant Christian, and
Jewish communities. Using Voyant for text analysis and sentiment analysis tools, we examined
the frequency of keywords, the overall sentiment of discussions, and recurring themes. The
analysis focused on the roles, challenges, and financial struggles of religious leaders, as well
as the ways in which these issues are discussed within each community.

Compound process models are widely used in applications such as modeling the sum of claims against an insurance portfolio or the total withdrawals from a bank. The classic compound Poisson–Exponential model is often used and the standard approach is to estimate unknown parameters based on historical data using maximum likelihood estimation.  Unfortunately, this method can lead to significant underestimation of risk.  We utilize a Bayesian approach to compute a predictive distribution for the cumulative loss as well as the probability of ruin (i.e., bankruptcy).  We examine the performance of these methods and show, under a wide range of sample sizes, our method outperforms the traditional approaches and that there is strong statistical evidence that our method achieves zero coverage error.

Online Safety for kids may be at the forefront of parental objectives in the Digital Age. An array of resources and knowledge-based tools exist to help parents control and protect their children from predatory activity online. Utilizing my background as a Private Investigator and Research Scientist, I conducted an analysis of current technologies, tools and techniques accessible and geared to parents when directed efforts focus on procuring their children’s safety when using digital devices.

Athletic directors (ADs) at the intercollegiate level face a variety of issues related to participation of student-athletes. To explore these issues further, the current study sought to gather perspectives of practicing athletic directors through semi-structured interviews. Approval was granted by the principal investigator’s Institutional Review Board. Ten ADs across one Division II conference in the midwest United States and one Division III conference in the northeast United States participated in the study. All interviews were conducted via Microsoft Teams, ranging from 42-54 minutes. The researchers asked a series of questions regarding the most important participation issues facing athletic directors. A thematic analysis was performed to identify common themes. Four themes were detected by the researchers: Mental health stigma, Physical health, Recruiting strategies, and Student-athlete involvement/transparency. Results from these interviews could assist intercollegiate ADs in developing policies and strategies to enhance the participation experiences of their student-athletes.

Quantum computing (QC) was introduced for the quantum Turing machine as a method to circumvent the challenging quantum mechanics simulations by classical computers. Recently, QC devices (> 50 qubits) have been announced by IBM, Google, and Riggeti based on circuit or gate models. As a constrain, the quantum devices are limited by poor error tolerance and decoherence. Also, this noise limits the number of quantum gates. In addition, quantum annealing (QA), encodes the solution to a computational problem in the ground state of a quantum Hamiltonian. The QA device is implemented in D-Wave systems (>2,000 qubits). However, QA can solve only a classical combinatorial optimization problem (i.e. Ising or QUBO model). We formulate QUBO to solve elliptic problems with Dirichlet and Neumann boundary conditions using the finite element method. Based on QUBO, we introduce an algorithm to solve the elliptic problems and discuss the validation of the modeling on the D-Wave quantum annealing system.

Autistic individuals often experience loneliness and social isolation, negatively affecting quality of life (Grace et al., 2022). Research suggests that group-based social skills interventions reduce these feelings (Gantman et al., 2012), yet limited work has explored this in community settings. This project examined the effectiveness of structured intervention groups in promoting belonging and reducing loneliness among autistic youth. Participants (n=8), ages 8–16 with ASD, were recruited through a community mental health organization and completed an eight-week Socio-Dramatic Affective Relational Intervention (SDARI; Lerner & Mikami, 2012). Measures included the UCLA Loneliness Scale (Version 3; Russell, 1996), General Belonging Scale (GBS; Malone et al., 2012), Psy-Flex (Gloster et al., 2021), and Social Responsiveness Scale-2 (SRS-2; Constantino & Gruber, 2012), administered pre- and post-intervention. Paired sample t-tests revealed significant improvements on all measures, supporting SDARI as a promising community-based approach to reduce loneliness and foster belonging in autistic youth.

This article examines the cinematic representation of the coca leaf in five Peruvian and Bolivian films set in the Andean-Amazonian region: Bala perdida (2001), Coca Mama (2004), El misterio del Kharisiri (2004), ¿Quién mató a la llamita blanca? (2006), and Wiñay (2018). While mainstream media typically focuses on international cartels, this corpus addresses territories where the coca plant is native and central to Indigenous health, rituals, and economic practices. By linking each film's production and circulation system to its representation of coca-related economies, the analysis reveals two dominant trends: the overshadowing of the coca leaf by urban cocaine consumption, and its representation as a timeless artifact of rural Andean communities for tourism. At the same time, some films break with this dichotomy by presenting the coca plant as a nonhuman agent participating in complex environmental and socioeconomic networks connecting the Andes and the Amazon.

During Summer 2025, two caterpillar decoy studies were implemented. In the first project, Farmingdale State College campus animal biodiversity was explored through an experiment utilizing clay caterpillar decoys, which is used to identify the types and abundance of predators on caterpillars in a geographic area. Two urban sites were compared – a parking lot (high car traffic, low foot traffic) and a campus walking path (high foot traffic, low car traffic). Results suggest that the walking path site posed a greater predation risk to caterpillars than the parking lot. For Project 2, because the actual predators of these caterpillar decoys are rarely seen, in-lab validation studies, focused on invertebrates, were conducted to confirm the presence of predator types such as ants, earwigs, harvestman, crickets, among others. This work was accomplished through the extensive collaboration with and efforts of seven Farmingdale State College interns from a variety of majors.

ACK1 has been characterized for its anti-apoptotic function, leading to cell proliferation and differentiation in cells, and its role in lung, prostate, pancreatic and breast cancer (Mahajan and Mahajan 2015). ACK1 has also been reported to have high expression levels in the brain, particularly in the hippocampus, neocortex and cerebellum (Torre et al 2006). However, the function of ACK1 in the brain has not yet been characterized. In this experiment, a Drosophila model is used to research the role of DAck in learning and memory.

With the discovery that the wastewater bacterium Serratia marcescens causes White Pox disease in corals came the startling awareness that sewage pollution can directly drive ocean epidemics. Fortunately, White Pox disease was limited to a few species of Caribbean corals. However, no further research has been done to determine whether other wastewater associated microbes can infect corals, representing a huge knowledge gap. My lab has preliminary evidence that the wastewater bacterium, Enterococcus faecalis, can also cause infect coral, suggesting that there is such potential for a greater variety of human waste-associated microbes to impact coral health. Thus, I am submitting an NSF CAREER Grant with a proposal to leverage in-class student research to conduct a sweeping investigation wastewater associated microbes’ potential virulence against corals and to understand how interactions between potential pathogens and the hosts’ microbiome may play a role in disease development.

CoIn2 undergoes a Peierls-like distortion at temperature T1 = 194(1) K.  We previously reported that the Peierls state is separated from a higher symmetry state by a structurally modulated phase that extends to T2 = 206(2) K, only the second such observation in a metallic system.  High resolution single crystal x-ray diffraction measurements carried out with synchrotron radiation, however, reveal the existence of not one but two competing modulated phases within this narrow temperature range.  Here we discuss the interplay of these phases and provide context for the potential existence of competing modulated phases across a broader class of materials.

BRCA2 breast cancer suppressor in human is a component of a prominent DNA repair pathway. Its activity is to govern Rad51, a catalytic factor promoting DNA rearrangements. Interaction between these proteins is mediated through the BRC structural element in BRCA2, a small protrusion of about 35 amino acids that penetrates into Rad51 to lock the proteins together. My lab uses a microbe with conserved Rad51 and BRCA2 (termed Brh2 in the microbe) homologs to study mechanistic aspects of this interplay. In previous genetic studies I isolated mutant variants with specific changes in the BRC motif and characterized these biologically for effects on DNA repair proficiency. Mutant cells deleted of the Brh2 gene are sensitive to DNA damaging agents. One of the mutants that I isolated has the perplexing property of being more sensitive to DNA damage than cells without the gene suggesting it is somehow a “poison.”

This project was conducted with Discover Life in America (DLIA), a non-profit devoted to cataloguing and protecting biodiversity in Great Smoky Mountains National Park. The team consisted of a Farmingdale faculty member (Dr. Carly Tribull) and a Bioscience senior intern (James Marrin) and was carried out during Summer 2025. In this project, we received unidentified wasps that had been collected by DLIA, provided identification services, and conducted COI barcoding analyses through the Canadian Centre for DNA Barcoding. COI Barcoding allows us to link together sexually dimorphic wasps as the same species - despite males and females being incredibly different looking, they are more genetically similar to each other than wasps in other species. We provide new taxonomic records for the park and test the viability of COI barcoding for conspecific delimitation.

Research on cultural essentialism, the belief that different cultural groups have unchangeable characteristics, have not fully examined the nomological net of the construct.  Most notably, within countries there are demonstrated sub-group variances in cultural dimensions and personality traits across different ethnic groups.  It would be reasonable that such differences may be found in cultural essentialism, however currently there is insufficient empirical evidence to make such a determination.  There may also exist a relationship between multicultural exposure and ideology and cultural essentialism that have not been examined in detail.  This is topical given the current socio-political climate surrounding ethnic group relations around the world.  In this study we propose a more detailed examination of cultural essentialism and its relationship with various variables.

As artificial intelligence (AI) becomes increasingly embedded in corporate operations, firms are under growing pressure to disclose the use of AI in their business practices. While prior research has largely examined how firms use AI, limited attention has been given to how firms publicly disclose their use of AI. Although AI disclosure is essential for building customer trust, such disclosure is not mandatory in most countries. in this project, we plan to examine the relationship between civic engagement on firms’ AI disclosures. We propose that firms in countries with higher levels of civic engagement are more likely to face demands for transparency, leading to more detailed disclosures of AI practices. To investigate this proposition, we utilize the civic engagement related scores of countries from the Freedom in the World index and conduct content analyses of publicly available firm reports (such as annual reports, CSR reports, etc.).

Artificial Intelligence (AI) tools have become increasingly integrated into higher education, prompting both optimism and concern regarding their impact on student learning. While prior research has largely focused on AI perception and general usage, there remains limited empirical understanding of how AI literacy, comprising technical, cognitive, and social-emotional dimensions, affects learning outcomes. This mixed-methods study examines the relationships between AI literacy and both academic performance and perceived learning gains. Qualitative data were gathered from 10 structured interviews to explore student experiences, challenges, and ethical considerations. Quantitative data are collected through a survey among college students, measuring AI literacy, AI-assisted learning behaviors, and learning outcomes. Findings are expected to advance theoretical understanding of AI literacy’s role in academic contexts and offer practical guidance for integrating AI into higher education curricula.

Congestion, fluctuating demand, and resource constraints in supply chain transport corridors
lead to inefficiencies such as delays, increased costs, and suboptimal pricing strategies. These challenges are exacerbated by stochastic factors like demand variability, fuel price fluctuations, and geopolitical events. To address this, we propose an integrated approach combining actor critic algorithm and stochastic differential game theory. The actor-critic algorithm, a type of reinforcement learning algorithm, dynamically optimizes the Volume Weighted Average Price (VWAP) by adjusting commodity pricing and resource allocation in real time. This method effectively balances supply and demand, thereby maximizing stakeholder revenue. Concurrently, the game-theoretic framework models stakeholder interactions to identify a unique Nash Equilibrium, ensuring fair and stable resource allocation and pricing strategies. This combined solution reduces congestion, enhances profitability, and improves system resilience to uncertainty created by geopolitical tensions. Applied to a congested port corridor, the approach dynamically allocates container slots and adjusts pricing, minimizing bottlenecks and maximizing throughput.

A 2023 report from the Financial Health Network suggests that immigrants are, on average, just as financially healthy as U.S. natives. Surprisingly, foreign-born individuals often outperform natives in terms of short-term savings and credit scores, indicating a degree of financial resilience that challenges conventional assumptions about immigrant economic vulnerability. This paper, first, seeks to uncover the gap between immigrants and natives in terms of financial health status, shedding light on the disparities and potential strengths within immigrant communities. Second, it aims to provide a deeper understanding of how immigrants' backgrounds, such as generational, national, cultural, and socioeconomic factor, shape their financial well-being. It offers valuable insights that can inform policy efforts to foster greater financial inclusion and stability for all individuals in the United States.

This project will investigate how Generative AI (GAI) can be intentionally integrated into active learning to foster AI literacy and prompt literacy in business education. Guided by the Active Learning-Informed Generative AI Integration (ALGAI) framework, the study examines 110 undergraduate students enrolled in an Organizational Behavior course. GAI tools such as ChatGPT were embedded into course activities that emphasized iterative prompt design, critical evaluation of AI-generated content, collaborative problem-solving, and ethical reflection. Rather than relying on passive AI use, students engaged interactively with AI to analyze Organizational Behavior concepts and address applied business challenges. Using an explanatory mixed-methods design, quantitative results revealed significant pre- to post-intervention improvements across AI literacy (knowledge, application, and ethics) and prompt literacy (knowledge and skills). Paired-sample t-tests demonstrated large effect sizes (AI literacy d = 0.72–0.94; prompt literacy d = 0.85–1.14). Qualitative reflections highlighted heightened confidence, conceptual depth, and ethical awareness. The study offers practical, scalable insights for embedding GAI into active learning to prepare students for ethical and strategic AI adoption.

This project incorporates ‘quality’ into the theoretical analysis of individual time allocation and consumption decisions. A growing body of literature has explored alternative approaches to incorporate quality into the analysis of consumers’ behavior, but the qualities of alternative goods still play a minor role in economic theory as its focus remains centered on the quantities of homogeneous goods. The analysis exploits a simple but overlooked dependence between quality and time. Quality can affect welfare "while" the individual is using or enjoying a good; consumption and enjoyment require time. Quality can also allow to save time that the individual can use to increase leisure or income (by increasing labor). All possible qualitative attributes of a good are here grouped into three categories: durability, effectiveness and enjoyability. These three categories are shown to affect time and income allocations through three different channels, and to have distinctive effects on high- and low-income individuals.

Although Environmental, Social, and Governance (ESG) investing has been broadly applied to guide responsible investment decisions as companies that perform well on ESG metrics are often perceived as more socially responsible and better positioned for long-term success, challenges and issues surrounding ESG investing remain. This paper examines the potential drawbacks of ESG investing, primarily from the perspective of a dynamic game between companies and investors. An ESG-noncompliant risk premium is defined, which is positively related to the net financial costs associated with ESG compliance and negatively related to the relative proportion of investors to companies regarding ESG practices in market equilibrium. Moreover, our model suggests that the higher the net financial costs of implementing ESG practices, the less likely companies are to adopt them; conversely, the greater the proportion of investors aware of ESG and the higher the ESG-noncompliant risk premium, the more likely companies are to implement ESG measures. Additionally, once global competition is considered, ESG investing may become less appealing for a country unable to reduce the net financial costs of implementing ESG practices.

As artificial intelligence (AI) becomes increasingly embedded in corporate operations, firms are under growing pressure to disclose the use of AI in their business practices as a part of their Corporate Social Responsibility. Although AI disclosure is essential for building customer trust and gain legitimacy, limited attention has been given to how firms publicly disclose their use of AI. To address this gap, we examine the influence of civic engagement on firms’ AI disclosures. We looked up foreign companies by Market Cap to get a list of biggest foreign companies operating in the U.S. so they would have a 20-K report. We associated each company with the regions according to the Civil Liberty scores. We took the top 2 companies from each region (except for Americas) according to market cap from each region. We examined the AI disclosures of these companies in their annual reports.

The rapid development of self-driving technology and artificial intelligence in recent years has enabled innovations such as autonomous delivery robots (ADRs), attracting considerable interest from both academia and industry. However, how human delivery workers perceive ADRs remains to be explored and investigated. This research examines the potential factors influencing delivery workers’ willingness to adopt and collaborate with ADRs, and focuses on the mediating role of procedural fairness. Field and online surveys show that perceived usefulness, ease of use, anthropomorphism, and social influence enhance ADRs acceptance, while insecurity inhibits it. By extending the Technology Acceptance Model (TAM) with social and relational dimensions from the Social Relational Attachment Model (sRAM), this research highlights the significant aspects of ADRs in influencing employees’ willingness to collaborate with this new technology.

A novel pneumatic mono-disperse spray was fabricated and multiple droplets of highly viscous 87 wt% aqueous glycerin solution was deposited onto a flat, transparent, plexiglass substrate. The uniformly sized droplets (2.5 mm in diameter) impacted, spread, and
 coalesced on the substrate which led to the creation of a liquid sheet. Using a high-speed camera placed underneath the transparent substrate, droplet impact and resultant area coverage were recorded. When impinging droplets overlapped those already on the surface, surface tension forces pulled impacting droplets towards them, agglomerating the liquid, in a phenomenon known as drawback. The area covered by the liquid was measured from photographs using image analysis software. The measurements from image analysis were compared with traditional (stochastic and probabilistic) models as well as AI predictive tools.

This project presents a novel framework to enhance the safety and reliability of collaborative robots (cobots) using digital twins and Generative AI. The system leverages Generative AI to interpret natural language job descriptions, generate task-specific commands, and simulate cobot actions within the Unity engine. Advanced algorithms—deep reinforcement learning, multi-objective optimization, and physics-informed neural networks—are employed to optimize motion planning, energy efficiency, and adaptability in virtual scenarios. Explainable AI (XAI) tools are included to ensure transparency in decision-making. A physical UR3e cobot is used, and plans are underway to integrate a RealSense depth camera and Jetson Orin Nano to enable real-time monitoring and IoT connectivity. This integration will enrich the digital twin with real-world data, ultimately improving system responsiveness and safety. While integration is ongoing, the current framework already provides a strong foundation for safe cobot deployment in dynamic manufacturing environments.

Artificial intelligence (AI) is transforming dentistry, particularly in dental radiology and oral pathology, by enhancing diagnostic accuracy, efficiency, and patient outcomes. Through machine learning and deep learning algorithms, AI supports clinicians in detecting caries, periodontal disease, and oral lesions earlier and more precisely. Integration with 2D and 3D imaging, such as cone beam computed tomography (CBCT), enables improved treatment planning and risk assessment. In oral pathology, AI aids in identifying premalignant and malignant tissues with high accuracy, complementing traditional biopsy methods. While AI offers significant advantages, such as increased precision, workflow efficiency, and personalized care, it also presents limitations related to cost, training, and ethical oversight. Dental hygienists play a key role in leveraging AI for early detection, patient education, and preventive care while maintaining, not replacing, essential human judgment.

This study examined the experiences of abuse, suicide ideation and mental health among homeless LGBTQ+ youth. The research used a retrospective approach utilizing data that was previously collected through the years 2019-2024 to gain a comprehensive understanding of the mental health challenges faced by this population.  Of the participants 61.5% (n=1010) reported being diagnosed with a mental health condition and 86.1% (n=1580) reported experiencing a form of abuse and 35% (n=575) were experiencing suicide ideation.  Depression did not vary significantly by whether the participant was a sexual orientation minority (p=0.340) but was significant for gender minority (p<0.001).  Physical and sexual abuse were significant predictors of suicidal ideation (p < .001). Verbal abuse was not a significant predictor. It was found that the odds of having suicidal thoughts increased by 74% (95% CI [1.345, 2.261]) for participants who experienced physical abuse over those who experienced no physical abuse.

Oral cancer is a significant public health concern affecting thousands of Americans each year. 
Comprehensive head and neck examinations involve a systematic assessment of the structures and tissues in the head and neck region, and are significant for early detection of abnormalities, cancers, and detecting lumps and lymph node involvement. Dental hygiene students are educated to conduct a comprehensive head and neck examination on each patient.  This study seeks to investigate if dental hygienists continue to perform the comprehensive head and neck examination while working in private clinical practice. Preliminary literature review suggests this procedure is not thoroughly provided on a routine basis.

This narrative review examines the relationship between diet and the development of the neuropathological hallmarks of AD in cognitively normal adults. Additionally, it explores limitations in the current evidence base and identifies areas for future research. Inclusion/exclusion criteria were set, and a PubMed search was conducted in March 2025. Out of 264 results, 13 articles passed the inclusion/exclusion criteria and were included in this review. Most studies were cross-sectional (n = 8), followed by cohort (n = 3), with one study including both cross-sectional and longitudinal analyses (n = 1). Only one intervention study was published. Various dietary exposures were tested, with most studies (n = 5) supporting a protective relationship between the Mediterranean diet and prevention of the neuropathological hallmarks of AD. However, the evidence base varies in methodology. Future research would benefit from greater consensus in methodology and should prioritize prospective cohort and randomized trial designs.

Excessive screen usage is a public health concern due to its correlation with mindless eating, sedentariness, and ensuing weight gain. Exposure to emotionally laden screen content and its correlation to feelings of anxiety and depression, as well as emotional eating, are additional factors related to weight gain. We investigated whether emotionally charged screen content correlated with changes in emotion and subsequent food selection among Generation Z college students.