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College student’s perceptions of acceptability of an AI-powered mental wellness chatbot for college student mental health
No full textBackground: College counseling centers have begun to turn to digital mental health interventions (DMHIs) to increase the availability and accessibility of treatment for students. Artificial intelligence (AI)-based chatbots are a new type of DMHI. However, more information is needed to better understand college student’s attitudes toward AI chatbots and their role in helping to fill the gap in treatment. Thus, this study aims to assess college student’s perceptions of using Wayhaven, an AI chatbot for mental health wellness. Methods: Data was drawn from a cross-sectional study examining the preliminary effectiveness of Wayhaven, a DMHI, in improving anxiety and depression among college students. Participants were 50 ethnoracially diverse college students. Students used Wayhaven across one week and completed two open-ended questions asking them to: 1) provide feedback about how engaging and helpful they found Wayhaven and 2) give suggestions for changes or improvements t Wayhaven. Thematic analysis was used to code these two items. Results: Overall, results revealed that most students found Wayhaven to be engaging, citing that the human-like conversations and user-centered experience prompted them to continue conversations with the AI chatbot. However, some participants noted receiving robotic and unsympathetic responses, which may suggest the need to add more validating and supportive replies into Wayhaven. Conclusions: Students generally found Wayhaven to be engaging and helpful in reducing their depression and anxiety symptoms, and reported being satisfied with their experience using tool
A cross-disciplinary approach to supporting mathematically
No full textMany freshmen intending to earn a degree in a science, technology, engineering, and mathematics (STEM) field begin their studies with inadequate mathematical preparation (American College Testing Association, 2019). However, this underpreparation is not the only challenge these students are navigating as they transition to college life; STEM majors are at a high risk of developing mental health issues due to the stress-inducing nature of their coursework (Kalkbrenner et al., 2022; Madhuri et al., 2021). In addition, STEM majors are less likely than their non-STEM counterparts to avail themselves of available counseling services (Kalkbrenner et al., 2022), and fully one-third of these students who abandon their majors report having struggled “with depression, high levels of stress, chronic anxiety, overwhelm, feelings of guilt, regret, shame, and self-blame for ‘failing’” (Holland et al., 2019, p. 330). To help address these rising concerns, the Mathematics and Counseling departments at Montclair State University (MSU) have undertaken a cross-disciplinary effort to design an introductory mathematics course called Transitions to College Mathematics (TCM) with integrated counseling services. This poster aims to share our program design, solicit feedback on this design, and generate conversations about how educators can support freshman STEM majors experiencing high levels of anxiety and stress in math
I almost broke”: Examining the mental health impact of gendered racism among black millennial women
No full textBlack feminist scholars have long emphasized the unique marginalization resulting from the intersecting injustices of sexism and racism ( Collins, 2000; Crenshaw, 1986; hooks, 2015; Lewis et al., 2017; Lewis, 2023; Settles, 2006). Essed (1991) coined the term gendered racism to describe how these forms of oppression converge and disproportionately impact minority women, especially Black women. Research demonstrates that gendered racism contributes to adverse mental health outcomes, including depression, anxiety, and suicidal ideation ( Jones et al., 2021; TaeHyuk Keum & Wong, 2022; Vance et al., 2023; Williams et al., 2025). However, emerging research has suggested that the experience of gendered racism’s impact on mental health and functioning may vary among Black Americans based on socio-political locations, generational cohorts, life stages, and contexts (Settles,2006; Williams et al.,2025). This study, part of a broader qualitative research project, explores the impact of gendered racism experienced in adulthood on the mental health of five Black millennial women in the United States. Preliminary findings reveal that participants often experience anxiety through persistent rumination on distressing events and heightened hypervigilance regarding negative stereotypes and perceptions of Black women. The initial findings provide valuable insights for the fields of family science and counseling by contributing to a nuanced understanding of mental health outcomes among Black millennial women facing gendered racism and supporting the development of healing-centered approaches
An exploratory investigation of the convergent validity of measures implicit and explicit bias, the CPI, and the MMPI-3 among police officers
No full textThere have been calls and directives for increased attention to the assessment of bias and intolerance among police officer candidates. However, there remains very little research that has examined implicit and explicit biases within the specific context of police personnel selection. Participants (N = 77) were candidates for police officer positions undergoing a pre-employment psychological evaluation who completed an online survey of demographics questions, two explicit bias measures (self-report measures of attitudes toward African Americans and toward racial and ethnic diversity in the United States), and an implicit bias measure (the Race Implicit Association Test). Survey data were combined with scale scores from two personality tests administered as part of participants’ pre-employment evaluations. Correlational analyses were used to explore convergent validity among measures. Interim results indicated that the two explicit bias measures were strongly related, whereas the implicit bias measure did not relate to these measures. Conceptually, this may be due to their differential methods (i.e., self-report vs. performance-based). One of the explicit bias measures exhibited minimal convergent validity with the two personality measures whereas the other related to a wide range of scales on one of the personality measures. The implicit bias measure, in turn, exhibited several relationships with the two personality measures. Data collection for the current study is ongoing toward increased power and precision for effects. The preliminary findings are promising in terms of personality test usage as convergent evidence for potential bias and prejudice in prospective police officers, though more research is clearly needed
Nutley\u27s invasive plant problem
No full textInvasive species pose a significant threat to biodiversity and this study will examine the impact of invasive plant species on native plant diversity and soil quality in local parks and green spaces in Nutley, New Jersey. By conducting field surveys, I will document the presence of invasive species and assess their effect on native plant communities. To determine the amount of biodiversity loss, I will compare species richness and diversity indices in invaded and non-invaded areas. The findings of this study will provide insight into the consequences of biological invasions at a local scale. With the understanding of how invasive species affect plant communities and soil health, it can help inform conservation efforts and park management strategies
Magnetic separation and characterization of ferrospheres in contaminated soil
No full textFerrospheres are spherical particles primarily composed of iron oxides. They are commonly associated with pollution from industrial activities and can be indicative of metal contamination in soil. This study aimed to investigate the relationship between ferrospheres and metal concentration by comparing their accumulation at different depths (0–2 cm vs. 8–10 cm), and analyzing their elemental abundance at these depths. Magnetic separation was performed to divide the magnetic and non-magnetic fractions and compare their prevalence in ferrospheres. 25R soil samples were collected from a brownfield site at Liberty State Park, Jersey City, NJ, two from the surface (0–2 cm) and two from the deeper layer (8–10 cm). Each sample was separated into magnetic and non-magnetic fractions, then analyzed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). Ten random locations from each fraction were analyzed at magnifications of 60x and 120x. Preliminary results indicated that magnetic samples from the surface layer contained higher numbers of ferrospheres (8 ferrospheres per sample) compared to non-magnetic samples (5 ferrospheres per sample) and no significant difference in count between the top and bottom magnetic samples. Ferrospheres in deeper layers appeared more irregularly shaped which could be due to the lower abundance of metals (Al, Fe, Mn) revealed through EDS analysis. These findings highlight the association of ferrosphere accumulation with metal contamination at the surface, and the potential implications for understanding metal mobility in soils. This study provides valuable insights into the role of ferrospheres in environmental contamination and their potential to act as indicators of pollution
A bi-directional emotion interaction interface for friendly collaborative robots
No full textHuman-robot collaboration has become an important topic in the field of robotics over the years, especially in the manufacturing scene. Unfortunately, current collaborative robots usually have very stiff and mechanic behaviors of many collaborative robots make their interactions with humans dull and uninteresting, especially for an extended period of time. One’s willingness to work alongside collaborative robots can be deterred by these behaviors, negatively impacting user acceptance and the potential wider application of collaborative robots. To solve this issue and be inspired by the human-human communication, a multimodal information-based bidirectional emotion interface (MI-BEI) was developed and added into the collaboration process aims to enable collaborative robots’ social-emotional competence. This developed interface allows the robot to recognize a human’s emotions through their facial expressions and vocal tones, while enabling it to respond using artificial emotion feedback via 3D simulation technology. Our work can be summarized into parts. First, the development of a 3D human interface that can monitor a human’s facial expressions and vocal tones while providing artificial emotional feedback. Second, the integration of the developed interface enables a collaborative manufacturing robot to express emotions in real-time while being able to perform actions during co-assembly tasks. Third, the validation experiments and analysis to evaluate the performance and effectiveness of the enhanced collaborative robot through real-world assembly tasks. The results and analysis from the experiment demonstrate the current system’s advantages and effectiveness, as well as guide the future development of collaborative robots and enhancing a more friendly and empathetic human-robot interaction
Progressive robot assisted gait therapy post-stroke with Kessler Institute
No full textPost-stroke, patients often experience hemi-paralysis, aphasia, cognitive impairments, and motor control issues, which require extensive rehabilitation. While standard of care gait training is commonly used to improve motor control, this study examines the effects of robotic assisted gait training. Acting as a clinical trial for the Ekso ™ robotic exoskeleton, the study hypothesizes that robotic gait training may lead to faster and more effective recovery. To assess the robotic exoskeleton’s impact we measure the mobility, muscle function, and brain activity in each stroke patient. Participants are divided into two groups: one undergoing traditional gait rehabilitation and the other receiving robotic exoskeleton assisted therapy. The study employs magnetic resonance imaging, transcranial magnetic stimulation, electromyography, and electroencephalography to evaluate brain activity and muscle responses before and after intervention. 75 participants (50 stroke patients and 25 healthy controls) were evaluated with stroke patients recruited from Kessler’s inpatient hospital. Participants undergo 10 weeks of rehabilitation, then follow up assessments at the end of training and six months post stroke. Outcome measures include walking ability, balance, and neurophysiological changes using walking evaluation, a 10 meter walk test, the Berg Balance Assessment, and a balance platform assessment using Movendo ™ at the beginning and end of the study. While data collection is ongoing, findings from this study may contribute to the development of more effective rehabilitation strategies for post-stroke gait recovery, providing insights into how robotic assistance influences motor function and neuroplasticity
The presence of young children\u27s voices in early years research
No full textThis presentation describes a series of projects that have been undertaken by our research team, Supervised by Dr. Elizabeth Erwin. Over the past three years, this team has conducted several projects in the field of education focusing on the presence of young children’s voices in early years research. Our work was designed around frameworks of wellness, and inspired by the Reggio Emilia approach (Burke, 2010) to early childhood education. More specifically, the research team conducted a qualitative meta-synthesis (Brown & Englehardt, 2016), which reviewed empirical research (n=8) including childrens’ first-person perspectives about their in-school experiences with mindfulness and mindfulness-related practices (i.e. yoga, breathing techniques). Through our analysis, many themes were identified which resulted in the development of two unique manuscripts currently under review. Our research found many studies conducted outside of the United States, where children connected mindfulness practices with their own well-being and belonging in early childhood settings. Additionally, we found that some children’s voices are missing from the literature, including students of color, students who are multilingual learners, and students with disabilities. Many of the recent articles we have reviewed around the Mosaic approach (Clark, 2005) have discussed a powerful connection between young children\u27s voices and their well-being. As a next step, Dr. Erwin and the rest of the team have submitted an IRB application to explore these topics first-hand through the use of qualitative methods such as interview and photography to explore young children’s perspectives on belonging in the spaces and places where they learn and play
Cross-task and sequential transfer learning for euphemism detection
No full textEuphemism detection is a challenging task for language models due to its subtle, context-dependent, and pragmatically rich nature. We investigate how related classification tasks, such as sentiment, politeness, and sensitivity, interact with euphemism detection through cross-task and sequential fine-tuning. We show that while models fine-tuned on related tasks rarely outperform single-task euphemism baselines, the degree of forgetting or transfer in sequential setups depends on task alignment and label semantics. Training on polite or sensitive data before euphemism detection yields more robust performance than the reverse order, suggesting asymmetry in representational overlap. These findings highlight when and how pragmatic features support effective transfer learning for euphemism detection