Exploring Possibilities: Virtual Reality in Nursing Research

This paper describes the use of virtual reality (VR) as a method of measurement in nursing research. VR refers to the use of computerized displays to display a life-like environment in which the user interacts. Although many disciplines are beginning to use VR environments in research, nursing has yet to embrace this technology. Nursing, as a profession which values the interaction between the environment, individual, and health, can benefit from the use of VR in research. Establishing reliability and validity of the VR tool selected for research is important and requires special consideration. VR testing can produce side effects, such as vertigo and discomfort, which must be anticipated in the research protocol

Search Strategies Used by Older Adults in a Virtual Reality Place Learning Task

Purpose of the study: Older adults often have problems finding their way in novel environments such as senior living residences and hospitals. The purpose of this study was to examine the types of self-reported search strategies and cues that older adults use to find their way in a virtual maze Design and Methods: Healthy, independently living older adults (n = 129) aged 55–96 were tested in a virtual maze task over a period of 3 days in which they had to repeatedly find their way to a specified goal. They were interviewed about their strategies on days 1 and 3. Content analysis was used to identify the strategies and cues described by the participants in order to find their way. Strategies and cues used were compared among groups. Results: The participants reported the use of multiple spatial and non-spatial strategies, and some of the strategies differed among age groups and over time. The oldest age group was less likely to use strategies such as triangulation and distance strategies. All participants used visual landmarks to find their way, but the use of geometric cues (corners) was used less by the older participants. Implications: These findings add to the theoretical understanding of how older adults find their way in complex environments. The understanding of how wayfinding changes with age is essential in order to design more supportive environments

Driving in Early-Stage Alzheimer’s Disease: An Integrative Review of the Literature

One of the most difficult decisions for individuals with Alzheimer’s disease (AD) is when to stop driving. Because driving is a fundamental activity linked to socialization, independent functioning, and wellbeing, making the decision to stop driving is not easy. Cognitive decline in older adults can lead to getting lost while driving, difficulty detecting and avoiding hazards, as well as increased errors while driving due to compromised judgment and difficulty in making decisions. The purpose of the current literature review was to synthesize evidence regarding how individuals with early-stage AD, their families, and providers make determinations about driving safety, interventions to increase driving safety, and methods to assist cessation and coping for individuals with early-stage AD. The evidence shows that changes in driving ability start early and progress throughout the trajectory of AD. Some individuals with mild cognitive impairment or early-stage AD may be safe to drive for a period of time. Support groups aimed at helping with the transition have been shown to be helpful for individuals who stop driving. Research and practice must support interventions to help individuals maintain safety while driving, as well as cope with driving cessation

‘A double-edged sword. This is powerful but it could be used destructively’: Perspectives of early career education researchers on learning analytics

Learning analytics has been increasingly outlined as a powerful tool for measuring, analysing, and predicting learning experiences and behaviours. The rising use of learning analytics means that many educational researchers now require new ranges of technical analytical skills to contribute to an increasingly data-heavy field. However, it has been argued that educational data scientists are a ‘scarce breed’ (Buckingham Shum et al., 2013) and that more resources are needed to support the next generation of early career researchers in the education field. At the same time, little is known about how early career education researchers feel towards learning analytics and whether it is important to their current and future research practices. Using a thematic analysis of a participatory learning analytics workshop discussions with 25 early career education researchers, we outline in this article their ambitions, challenges and anxieties towards learning analytics. In doing so, we have provided a roadmap for how the learning analytics field might evolve and practical implications for supporting early career researchers’ development

Changes in initial COPD treatment choice over time and factors influencing prescribing decisions in UK primary care : a real-world study

Acknowledgements Samantha Holmes (CircleScience, an Ashfield Company, part of UDG Healthcare plc) and Paul Hutchin (contracted to CircleScience, an Ashfield Company, part of UDG Healthcare plc) provided medical writing assistance. Funding The study was funded by Novartis Pharma AG (Basel, Switzerland).Peer reviewedPublisher PD

Social inclusion for children with hearing loss in listening and spoken Language early intervention: an exploratory study

Background: Social inclusion is a common focus of listening and spoken language (LSL) early intervention for children with hearing loss. This exploratory study compared the social inclusion of young children with hearing loss educated using a listening and spoken language approach with population data. Methods: A framework for understanding the scope of social inclusion is presented in the Background. This framework guided the use of a shortened, modified version of the Longitudinal Study of Australian Children (LSAC) to measure two of the five facets of social inclusion ('education' and 'interacting with society and fulfilling social goals'). The survey was completed by parents of children with hearing loss aged 4-5 years who were educated using a LSL approach (n = 78; 37% who responded). These responses were compared to those obtained for typical hearing children in the LSAC dataset (n = 3265). Results: Analyses revealed that most children with hearing loss had comparable outcomes to those with typical hearing on the 'education' and 'interacting with society and fulfilling social roles' facets of social inclusion. Conclusions: These exploratory findings are positive and warrant further investigation across all five facets of the framework to identify which factors influence social inclusion

Comparison of Four Commercially Available Group B Streptococcus Molecular Assays Using Remnant Rectal-Vaginal Enrichment Broths

The incidence of neonatal Group B streptococcal (GBS) disease has significantly declined since the widespread implementation of prenatal screening of expectant mothers for urogenital and gastrointestinal tract GBS colonization. Screening methods have evolved from exclusively culture-based approaches to more rapid and highly sensitive molecular methods. We chose to evaluate the performance of four commercially available GBS molecular tests for detection of GBS colonization using 299 antepartum rectal-vaginal specimens submitted to our laboratory for routine GBS screening. In 97% of instances, there was agreement between all three systems. When testing 1, 6, and 12 samples simultaneously, all methods performed comparably, but the ARIES® GBS assay required the least total hands-on time and the illumigene® Group B Streptococcus assay required the most hands-on time

Using Prior Knowledge and Student Engagement to Understand Student Performance in an Undergraduate Learning-to-Learn Course

This study examined prior knowledge and student engagement in student performance. Log data were used to explore the distribution of final grades (i.e., weak, good, excellent final grades) occurring in an elective under-graduate course. Previous research has established behavioral and agentic engagement factors contribute to academic achievement (Reeve, 2013). Hierarchical logistic regression using both prior knowledge and log data from the course revealed: (a) the weak-grades group demonstrated less behavioral engagement than the good-grades group, (b) the good-grades group demonstrated less agentic engagement than the excellent-grades group, and (c) models composed of both prior knowledge and engagement measures were more accurate than models composed of only engagement measures. Findings demonstrate students performing at different grade-levels may experience different challenges in their course engagement. This study informs our own instructional strategies and interventions to increase student success in the course and provides recommendations for other instructors to support student success

Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI

As the importance of high-throughput screening (HTS) continues to grow due to its value in early stage drug discovery and data generation for training machine learning models, there is a growing need for robust methods for pre-screening compounds to identify and prevent false-positive hits. Small, colloidally aggregating molecules are one of the primary sources of false-positive hits in high-throughput screens, making them an ideal candidate to target for removal from libraries using predictive pre-screening tools. However, a lack of understanding of the causes of molecular aggregation introduces difficulty in the development of predictive tools for detecting aggregating molecules. Herein, we present an examination of the molecular features differentiating datasets of aggregating and non-aggregating molecules, as well as a machine learning approach to predicting molecular aggregation. Our method uses explainable graph neural networks and counterfactuals to reliably predict and explain aggregation, giving additional insights and design rules for future screening. The integration of this method in HTS approaches will help combat false positives, providing better lead molecules more rapidly and thus accelerating drug discovery cycles.Comment: 17 pages, plus S