Sue & Bill Gross School of Nursing

There is an urgent need for improved school-based mental health services to address students increasing mental health needs. School nurses are often at the frontlines of youth mental health, but report feeling unprepared to manage student needs due to limited training. We conducted a rapid review to identify evidence-based mental health educational interventions for school nurses and evaluate program characteristics. Eleven studies met the inclusion criteria. While the literature evaluating mental health training programs for school nurses is limited, it suggests that training may improve school nurse knowledge, confidence, and preparedness to address student mental health needs and improve the management of student mental health. Additionally, it highlighted the importance of support, resources, and policies that foster mental health promotion. Future research should focus on obtaining a current assessment of school nurse mental health education needs, evaluating existing interventions, and developing more evidence-based mental health training programs for school nurses.

BACKGROUND AND OBJECTIVES: Culturally diverse informal caregivers of community-dwelling persons with dementia face challenges in accessing dementia care resources due to language barriers and cultural stigmas surrounding dementia. This study presents the perceived intervention experiences of a home-based approach which considers the cultural and linguistic needs of diverse family caregivers in dementia care. The intervention model includes home visits by trained bilingual, non-licensed community health workers (CHWs) whose cultural histories and understandings reflect that of the caregivers. The purpose of the present study was to understand family caregivers experience in caregiving and their feedback on the intervention, which includes caregiver support through education and skill development. METHODS: The present study thematically analyzed qualitative data from exit interviews with caregivers who participated in a CHW-led, 12-week home visit-based intervention program. RESULTS: Among 57 caregivers (mean age = 63.5, SD = 14.3) who participated in the 3-month home-visit intervention and completed the exit interviews, 33% were Korean Americans, 28% Vietnamese Americans, 21% non-Hispanic Whites, and 17.5% Latino/Hispanic. The majority were females (81%) and spouses (51%). Main themes include, (a) Individual Level: Improvements in Caregiving Self-efficacy and Self-care Awareness, (b) Relational Level: Enhanced Communications and Relationships with Persons with Dementia, and (c) Community Level: Connection and Access to Community Resources and Support. CONCLUSION: Interview data show that the culturally and linguistically tailored program supported diverse caregivers by increasing self-care awareness, improving knowledge about dementia and dementia care, strengthening communication skills, and facilitating access to community resources. Strong rapport between CHWs and caregivers enhanced the effectiveness of the intervention. Future approaches can focus on supporting caregivers with especially limited resources.

As a practicing clinical nurse, a phenomenon I experienced at times was the sudden acute sense that something was going wrong with a person in care at the sub-critical unit in the hospital where I worked. In fact, many hospital nurses have their story of somethings not right in relation to a person they were caring for/with, in that the day started with them on a coherent path to healing and then suddenly the nurse feels something is going very wrong, and yet there is nothing observable that would justify such a feeling. This feeling would be called intuition by many nurses, a concept most notably theorized in nursing by Patricia Benner in her extensive program of scholarship. Benner defines intuition as understanding without rationale. Benner opposes embodied intuition and rational abstract reasoning and creates criteria for the use of each by nursing depending on whether the clinical situation is familiar or novel. The philosophical idea is that the new must be reasoned with a different mode of thought than the familiar. Charles Sanders Peirce was a philosopher of reasoning. He defined logic as the theory of reasoning, which by the end of his career he was declaring was only another name for semiotic. Peirce argued that all reasoning/semiosis is done through signs, or more accurately sign-activity. Semiotic is the philosophical schema providing the concepts and methods by which semiosis - reasoning - happens. Importantly, semiotic does not oppose different modes of thought, and conceptualizes reasoning as a process that functions in familiar as well as novel situations. In this paper I describe Peirces philosophy of semiotic. I then provide an example relevant to nursing by conducting a semiosis of the nursing scenario above to show how nursing works chance, or novelty, in a way that doesnt need to resort to rational abstract reasoning and yet is different than Benners notion of intuition.

INTRODUCTION: We used an implementation science framework to investigate perceived health inequities in preventive health care initiatives in rural communities in the Philippines. We also identified health equity-focused quality improvement strategies. METHODS: Three health care providers and 12 barangay clinic patients were interviewed. RESULTS: Patient interviews showed that social determinants of health, respect, and attitudes toward health care providers affected patient empowerment to engage in self-management for noncommunicable diseases (NCDs). Health care providers identified six challenges in managing NCDs: (a) inefficient work processes; (b) staffing shortages; (c) insufficient access to low-cost medications; (d) inadequate primary preventive health education from the schools; (e) health care not considered a priority; and (f) lack of local government support. DISCUSSION: Inadequate preventive health care and education intensify health access and resource inequities in rural communities in the Philippines. A multi-sectoral plan may improve rural health infrastructure and education toward improving health care access and decreasing care disparities.

Chronic hepatitis B remains a substantial global health challenge, impacting approximately 254 million people worldwide. A cure for this condition is yet to be discovered. Early identification and effective treatments coupled with vigilant monitoring can help alleviate associated morbidity and mortality due to potential complications such as liver cirrhosis and hepatocellular carcinoma.

PURPOSE: The aim of the study was to develop a prediction model using deep learning approach to identify breast cancer patients at high risk for chronic pain. DESIGN: This study was a retrospective, observational study. METHODS: We used demographic, diagnosis, and social survey data from the NIH All of Us program and used a deep learning approach, specifically a Transformer-based time-series classifier, to develop and evaluate our prediction model. RESULTS: The final dataset included 1131 patients. We evaluated the deep learning prediction model, which achieved an accuracy of 72.8% and an area under the receiver operating characteristic curve of 82.0%, demonstrating high performance. CONCLUSION: Our research represents a significant advancement in predicting chronic pain among breast cancer patients, leveraging deep learning model. Our unique approach integrates both time-series and static data for a more comprehensive understanding of patient outcomes. CLINICAL RELEVANCE: Our study could enhance early identification and personalized management of chronic pain in breast cancer patients using a deep learning-based prediction model, reducing pain burden and improving outcomes.

Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the provision of various services, including diagnosis, personalized lifestyle recommendations, dynamic scheduling of follow-ups, and mental health support, the objective is to substantially augment patient health outcomes, all the while mitigating the workload burden on healthcare providers. The life-critical nature of healthcare applications necessitates establishing a unified and comprehensive set of evaluation metrics for conversational models. Existing evaluation metrics proposed for various generic large language models (LLMs) demonstrate a lack of comprehension regarding medical and health concepts and their significance in promoting patients’ well-being. Moreover, these metrics neglect pivotal user-centered aspects, including trust-building, ethics, personalization, empathy, user comprehension, and emotional support. The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare. Subsequently, we present a comprehensive set of evaluation metrics designed to thoroughly assess the performance of healthcare chatbots from an end-user perspective. These metrics encompass an evaluation of language processing abilities, impact on real-world clinical tasks, and effectiveness in user-interactive conversations. Finally, we engage in a discussion concerning the challenges associated with defining and implementing these metrics, with particular emphasis on confounding factors such as the target audience, evaluation methods, and prompt techniques involved in the evaluation process.

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School nurses are pivotal to the safety of school-aged children, particularly those who receive medications in the school setting. The purpose of this study was to explore factors associated with medication administration errors in North Carolina school districts between 2012/2013 and 2017/2018. A longitudinal study using repeated measures analysis of school health services data collected in the North Carolina Annual School Health Services and Programs Survey was conducted. Over time, the number of medication errors (p = .001) and number of medication corrective action plans (p < .0001) trended upwards. There was also an increase in medication errors when the number of schools in a district was higher (p < .0001). Conversely, there was a decrease in corrective action plans when school nurses were directly employed by the school district (p = .0471). We implore school disticts to consider the important role of school nurses to keep kids safe, healthy, and ready to learn.

A significant proportion of frontline nurses developed post-traumatic stress disorder (PTSD) symptoms as a result of working during the COVID-19 pandemic. This study aimed to determine the efficacy of a mindfulness- and acceptance-based smartphone app intervention among nurses traumatized by the COVID-19 pandemic. This was a two-arm, randomized controlled trial. We randomly assigned 60 frontline nurses working in various clinical settings in the United States during the pandemic to either the intervention group (i.e. participants used the mindfulness app for 6 wk) or the wait-list control group. We assessed the apps efficacy through outcome measures of PTSD symptom severity, experiential avoidance, rumination, mindfulness, and resilience, measured at pre-, mid-, and post-intervention periods and a 1-month follow-up. Intervention satisfaction and perceived usability of the app were assessed within the intervention group. There was strong evidence of within-between interaction for PTSD, experiential avoidance, and rumination, implying significant improvement of these outcomes for the intervention group as compared to the control group. We only found a within-group interaction effect for mindfulness, indicating significant improvement of mindfulness within the intervention group only. Participants in the intervention group reported high satisfaction levels and perceived usability with the app. Findings highlight that mindfulness- and acceptance-based smartphone apps can improve PTSD symptoms of nurses traumatized by the pandemic. Healthcare organizations should provide nurses with accessible interventions (e.g. mindfulness apps) to treat and prevent secondary behavioral consequences of the pandemic, such as PTSD.