Centerstone

As the number of persons living with dementia (PLWD) grows, there is a pressing need for person-centered long-term care solutions that prioritize their experiences. Adult day centers (ADCs) play a critical role in supporting PLWD, yet most research focuses on outcomes relevant to caregivers and payors rather than the voices of those receiving care. This study explores PLWD’s firsthand perspectives on their ADC experiences, using Kitwood’s (1997) person-centered dementia care framework which identifies five key psychological needs: inclusion, attachment, comfort, occupation, and identity. Six focus groups were conducted with PLWD (n = 51) and their caregivers (n = 6) at four ADCs across the U.S. ADCs were purposively selected to represent a diverse range of racial/ethnic backgrounds, geographic locations, and urban and rural settings. Qualitative directed content analysis was guided by Kitwood’s framework to categorize the aspects of ADC care that participants found most meaningful. Findings revealed that PLWD were most impacted by inclusion, as participants consistently described ADCs as family-like environments where they built strong social bonds with both peers and staff which alleviated feelings of isolation. Attachment was also a key theme, with many PLWD referring to ADCs as a “second home,”—a place where they felt safe, secure, and supported. Participants expressed comfort with ADC staff, who provided consistent, personalized care and treated them with dignity. The need for occupation was fulfilled by the opportunity to leave home, engage in structured activities, and maintain a sense of purpose and routine. Lastly, ADCs helped PLWD maintain their identity by respecting their individual preferences, cultural backgrounds, and autonomy. Some participants described newfound confidence and self-worth as a result of their participation, highlighting the importance of person-centered care. This study amplifies the voices of PLWD, highlighting ADCs as environments that foster person-centered outcomes by addressing fundamental psychological needs. Findings emphasize the necessity of centering PLWD’s lived experiences in ADC programming, policy development, and outcome measurement to ensure alignment with what truly matters to them. Future research should focus on translating these insights into scalable person-centered care practices in ADCs and other long-term care settings.

Immersive virtual reality (VR) environments are increasingly utilized to support training in safety-critical fields such as construction, transportation, healthcare, and emergency response. However, the reliability of these simulations depends not only on visual fidelity but also on how well user perception and behavior in virtual environments correspond with real-world expectations. This paper presents the VR Training Readiness Evaluation Model (VTREM), a cross-domain model for assessing the perceptual and behavioral credibility of scenario-based VR training systems. VTREM comprises three integrated components: a Spatial Realism Test to evaluate distance and size perception; an Action Credibility Test to examine whether motor responses align with real-world behaviors; and a Response Variability Analysis to measure behavioral consistency across users and simulation conditions. The model is based on an experimental study of egocentric distance estimation and demonstrates applicability across various industry contexts, including fire services, process plants, aviation, and healthcare. By positioning immersive environments as behaviorally expressive systems, VTREM contributes novel insights to the field of information visualization, broadening the concept of data interpretation to encompass embodied spatial decision-making. The model enables simulation designers and educators to systematically validate training environments, thereby enhancing both instructional integrity and operational preparedness.

Abstract This study evaluated stages of change and treatment outcomes among 146 adults who participated in a reentry and recovery program for substance use disorders post-incarceration, an understudied population regarding treatment outcomes. Data were collected at three time points. Bivariate analyses and logistic regression were used to analyze the data. Using the constructs Readiness-to-Change (RTC) and Committed Action (CA), results indicated that baseline CA scores were significantly and positively associated with treatment outcomes. Individuals who scored higher in baseline RTC stages and who completed supervision had greater odds of program success. These findings can inform future interventions with correctional populations, such that individuals with lower RTC and CA at baseline might need additional support.

Detailed underwater inspection or sampling tasks are often performed by human divers, often in difficult or dangerous conditions. Highly maneuverable, intelligent autonomous underwater vehicles have the potential to enhance or replace the most monotonous and difficult portions of this work to improve outcomes and reduce risks to divers. In this paper, we describe autonomous exploration, mapping, return-to-target, sediment sampling, and diver assistant capabilities developed for the small, hover-capable SUNFISH® AUV to enable marine archaeological investigation in unstructured, 3-D, overhead environments. SUNFISH is a compact, easily transportable vehicle, with full 6-DOF control. It is able to navigate in and build fully 3-D maps of complex underwater geometries such as cliffs, caves, and tunnels. The primary sensing is via a side-look multibeam sonar which can be used for survey and detailed 3- <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$D$</tex> mapping. Additional sensors and actuators enable photogrammetry, precision inspection, and underwater intervention in these environments. SUNFISH employs a real-time sonar SLAM system and an exploration behavior to expand the mapped volume and safely find paths through 3- <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$D$</tex> environments. Here we report on augmented vehicle capabilities enabling return to targets in the mapped volume, and intervention in the form of sediment sampling at a location specified in the 3- <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$D$</tex> map. In May-June 2023, we demonstrated these capabilities in a field deployment as part of the Our Submerged Past project. This project aims to uncover evidence of prehistoric human habitation on the continental shelf west of Prince of Wales Island in Southeast Alaska by exploring, mapping, and sampling currently submerged caves and rock shelters that would have been exposed at times in the last 17,000 years. In this project, the SUNFISH AUV demonstrated the ability to autonomously survey an area, return to targets identified in its high-precision 3-D map, take sediment samples, and assist human divers in archaeological tasks. Lessons learned in applying a cutting-edge AUV to investigate and document archaeological sites in this project can serve to enable new types of investigations, and streamline and reduce costs of archaeological and other assessments in the future.

The ‘me too’ movement originated to help survivors of sexual violence by providing resources and building a community of advocates to exemplify the magnitude of sexual violence victimization. This movement gained momentum via Twitter due to the viral hashtag—#metoo. YouTube is often used as a means of expression in younger generations, thus sexual violence survivors began using the platform as a way to disseminate ‘me too’ narratives. Therefore, this study aimed to examine how sexual violence narratives resulting from the ‘me too’ movement are being told on YouTube and understand the components of the narratives related to self-blaming mindsets. Based on predetermined search criteria, researchers identified and screened YouTube videos of people sharing ‘me too’ narratives, and developed themes and codes (e.g., type of violence, perpetrator characteristics). Descriptive statistics and a logistic regression were conducted using demographic, experience, and attitudinal data to predict self-blaming mindsets. Sixty-two YouTube videos were included, consisting of 96 individual ‘me too’ stories. The sample was mostly female, and perpetrators were predominately strangers. The model explained 19.3% of the variance in self-blaming attitudes. Odds of self-blaming rose 4.589 times for those who experienced sexual harassment, and 6.109 times for those who experienced rape. If the perpetrator was not mentioned in the video, odds of self-blaming dropped by 89.4%. This study suggests self-blaming beliefs are prominent among victims, even when they have the space to share their story. Overall, our findings support the continued need for further education and support for victims.

ABSTRACT Housing first models have become increasingly common for supporting persons experiencing homelessness. However, successful implementation of the housing first model can vary from program to program. To better understand what factors, influence whether a person experiencing homelessness can secure housing in a housing first model, we constructed a logistic Bayesian model. With data from 69 clients enrolled in a housing first program in Indiana, we tested demographic factors, depression, drug use, health status, hospital and acute care and outpatient visits, probation/parole status, and number of crimes committed as prospective predictors of securing housing six months later. We found that older participants, those who had recently utilized acute care services, and those with lower depression scores were more likely to secure housing after six months.

With the Educational Childhood Longitudinal Kindergarten Cohort class of 2011 (ECLSK-2011) database, I used propensity score matching and a longitudinal multilevel model to evaluate how 4970 kindergarteners in public (assigned public, charter, or magnet) and private (religious, non-religious private) schools, who were matched on a host of covariates, differed on a psychometrically sound self-control construct from fall 2010 to spring 2012. I found no statistically significant difference in self-control scores between private and public-school children. I discuss possible more effective and equitable mechanisms for improving student self-control, as well as suggesting guidance for future research on this topic.

The present paper examines if developmental pathways for students at risk for academic failure can be improved through social and emotional learning (SEL). Specifically, we test this hypothesis by accounting for shifts in student engagement, a highly studied and malleable construct often inclusive of SEL interventions, as the pathway by which to impact student achievement outcomes. Using longitudinal data from a randomized control trial, we identified students at risk for school failure (n = 318) within a larger sample of fifth graders (N = 1,352). Multigroup path model revealed that participation in RULER significantly impacted the relationship between student engagement and conduct behaviors for at risk students: students who experienced RULER demonstrated increased engagement a year later (at sixth grade) and improved conduct the following year (in seventh grade). The potential for and limitations of SEL programs on developmental trajectories for students at risk for school failure are discussed.