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Gum disease during pregnancy is not just a dental issue but a significant public health concern with potential implications for maternal and child health. This study aims to estimate the national prevalence of gum disease among pregnant women and examine the association of maternal gum disease during pregnancy and pregnancy outcomes. A retrospective case-control study used the PRAMS (phase 8, 2016-2020) dataset. Propensity score matching was employed to match cases in a 1:3 ratio. Logistic regression was used to test the associations between maternal gum disease, low birth weight, and small gestational age. The study revealed a prevalence rate of 207 cases per 100,000 pregnant women. Notable differences were observed, with higher prevalence rates among younger women (20-24 yrs), racial minorities (Black women), and those with lower educational attainment (9-12 grade, no diploma). Maternal gum disease was associated with an increased risk of small for gestational age (SGA) and falls below the 10th percentile (OR = 2.43, 95% CI: 1.56-3.75, p < 0.001), having babies with birthweight below 2500g are 3.51 times higher (OR = 3.51, 95% CI: 2.39-5.16, p < 0.001) compared to those who do not have gum disease. The complex relationship between maternal oral health and adverse pregnancy outcomes necessitates immediate and comprehensive research to understand and address this issue, highlighting the immediate need for action to prevent potential health risks.

Physical inactivity is a growing societal concern with significant impact on public health. Identifying barriers to engaging in physical activity (PA) is a critical step to recognize populations who disproportionately experience these barriers. Understanding barriers to PA holds significant importance within patient-facing healthcare professions like nursing. While determinants of PA have been widely studied, connecting individual and social factors to barriers to PA remains an understudied area among nurses. The objectives of this study are to categorize and model factors related to barriers to PA using the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework. The study population includes nursing students at the study institution (N = 163). Methods include a scoring system to quantify the barriers to PA, and regularized regression models that predict this score. Key findings identify intrinsic motivation, social and emotional support, education, and the use of health technologies for tracking and decision-making purposes as significant predictors. Results can help identify future nursing workforce populations at risk of experiencing barriers to PA. Encouraging the development and employment of health-informatics solutions for monitoring, data sharing, and communication is critical to prevent barriers to PA before they become a powerful hindrance to engaging in PA.

This secondary analysis used data collected for the Korean Longitudinal Study of Aging from 2006 to 2018 to examine changes in life satisfaction among middle-aged adults living alone in South Korea. Individuals who were over 45 years of age, lived alone at the time of the first data collection wave, and responded at least twice to the survey over the 12-year study period were included in the final linear mixed model ( N = 124). Life satisfaction increased for those who had increased assets, were widowed, and had more frequent contact with acquaintances (i.e., once a month and once a week compared with once a year). Life satisfaction decreased as the number of chronic illnesses increased for underweight individuals compared with normal weight or overweight individuals and for depressed versus non-depressed individuals. This study’s findings indicate that increased social support is beneficial for middle-aged marginalized individuals, including those who are economically disadvantaged, have few social interactions, are underweight, and have chronic illnesses.

This study explored the experiences, challenges, and social dynamics of middle-aged individuals living alone in South Korea, compared with English-speaking individuals. From a public health perspective, this study examined cultural and generational factors influencing wellbeing. This cross-sectional descriptive study used topic modeling with natural language processing to analyze YouTube video comments related to single-person households collected from 30 Korean and 88 English-language channels. Distinct cultural and generational differences emerged. Korean participants, particularly women, frequently expressed concerns about social stigma surrounding marriage and singlehood. English-speaking participants emphasized careers and personal independence. Themes included employment, financial security, travel, and food. Younger Koreans showed interest in leisure activities (mukbang, solo drinking). Older Koreans expressed concerns about economic stability and societal expectations. Understanding the cultural and generational context of living alone is essential for developing public health strategies addressing social isolation, mental health, and health equity. Digital platforms function as alternative social spaces, offering insights into socially isolated individuals' needs. Public health interventions should consider online engagement to support wellbeing and reduce health disparities in this population.

Background Measurements of nursing workload often fail to reflect the complexity of nursing work. Nurses’ perceived workload is shaped by many factors, including patient characteristics, personal, social, organizational, and environmental factors. There is a demonstrated interest in developing more comprehensive nurse workload measurement strategies, but little research has employed qualitative methods to investigate the beliefs and experiences of frontline staff. The purpose of this study was to explore inpatient nurses’ perceptions of their workload and the factors that impact their percieved workload levels. Methods This was qualitative study using focus groups. Participants were recruited from the cardiac floors of an urban, academic medical center. A total of 17 nurses participated, including nurses from bedside, charge, educator, and nurse manager roles. Focus group transcripts were analyzed by a team of qualitative investigators using conventional content analysis. Results Inpatient nurses’ perceived workload is shaped by their work volume, work attributes, and their ability to complete required tasks while providing meaningful, impactful care. The volume of nursing work is comprised of patient-focused, unit-focused, and institutional-focused tasks. Important work attributes include its perceived urgency, difficulty, alignment to the nurse and unit, interference, unpredictability, and individual nursing burden. Overall, participants expressed deep concern over high workloads that compromise holistic nursing care. Conclusion Strategies to more comprehensively measure nurses’ perceived workload should account for the breadth and complexity of nursing work. Nurses should advocate for workload measurement systems that more closely reflect their subjective work experiences. Clinical trial registration number Not applicable.

There has been a growing emphasis on data across various health-related fields, not just in nursing research, due to the increasing volume of unstructured data in electronic health records (EHRs). Natural Language Processing (NLP) provides a solution by transforming this unstructured data into structured formats, thereby facilitating valuable insights. This methodology paper explores the application of NLP in nursing, using an exemplar case study that analyzes YouTube data to investigate social phenomena among adults living alone. The methodology involves five steps: accessing data through YouTube’s API, data cleaning, preprocessing (tokenization, sentence segmentation, linguistic normalization), sentiment analysis using Python, and topic modeling. This study serves as a comprehensive guide for integrating NLP into nursing research, supplemented with digital content demonstrating each step. For successful implementation, nursing researchers must grasp the fundamental concepts and processes of NLP. The potential of NLP in nursing is significant, particularly in utilizing unstructured textual data from nursing documentation and social media. Its benefits include streamlining nursing documentation, enhancing patient communication, and improving data analysis.

Marijuana is the most common illicit substance globally. The rate of marijuana use is increasing in young adults in the US. The current environment of legalizing marijuana use is further contributing to an increase of users. The purpose of this study was to explore the characteristics of adults who abuse marijuana (20–49 years old) and analyze behavior and social relation variables related to depression and suicide risk using machine-learning algorithms. A total of 698 participants were identified from the 2019 National Survey on Drug Use and Health survey as marijuana dependent in the previous year. Principal Component Analysis and Chi-square were used to select features (variables) and mean imputation method was applied for missing data. Logistic regression, Random Forest, and K-Nearest Neighbor machine-learning algorithms were used to build depression and suicide risk prediction models. The results showed unique characteristics of the group and well-performing prediction models with influential risk variables. Identified risk variables were aligned with previous studies and suggested the development of marijuana abuse prevention programs targeting 20–29 year olds with a regular depression and suicide screening. Further study is suggested for identifying specific barriers to receiving timely treatment for depression and suicide risk.

An educational support group, The Lighten Your Life Program, was developed for adult patients who self-reported depressive symptoms and had one or more comorbid chronic pain condition. Using a mixed methods, pilot design, the purpose of the current study was to test the feasibility of The Lighten Your Life Program, which combined depression education with in-person group support every 2 weeks. The Lighten Your Life Program also encouraged the use of Pacifica, a mobile application (app), as a self-management tool. Another aim was to explore what effect The Lighten Your Life Program had on decreasing depression severity. Statistically significant differences in Patient Health Questionnaire-9 scores were noted over time. Educational support group programs and the use of mobile apps, such as Pacifica, could be beneficial in helping individuals self-manage their depressive symptoms and chronic pain condition. [ Journal of Psychosocial Nursing and Mental Health Services, 57 (7), 39–47.]

An exam wrapper is a structured debriefing questionnaire designed to help students understand examination performance and develop improvement strategies. This mixed-methods pilot study sought to examine its impact on students' metacognitive skills in a fundamentals nursing class and to assess student perceptions of its usefulness. Metacognition was assessed using the Metacognitive Inventory for Nursing Students. Quantitative data were analyzed using the nonparametric Friedman test. Qualitative data were taken from four focus groups. Students who used the exam wrapper throughout the semester demonstrated significant improvement in metacognition over time (p = .014). Focus group data revealed that students did not find the exam wrapper to be helpful. The analysis revealed three themes: Reliance on Faculty, Overlap With Established Self-Regulated Learning Strategies, and Difficulty in Answering Exam Wrapper Questions. Although students may not perceive this tool as useful, those who repeatedly used it over time had increased metacognition. [J Nurs Educ. 2019;58(7):417-421.].

This secondary analysis used data collected for the Korean Longitudinal Study of Aging from 2006 to 2018 to examine changes in life satisfaction among middle-aged adults living alone in South Korea. Individuals who were over 45 years of age, lived alone at the time of the first data collection wave, and responded at least twice to the survey over the 12-year study period were included in the final linear mixed model (N = 124). Life satisfaction increased for those who had increased assets, were widowed, and had more frequent contact with acquaintances (i.e., once a month and once a week compared with once a year). Life satisfaction decreased as the number of chronic illnesses increased for underweight individuals compared with normal weight or overweight individuals and for depressed versus non-depressed individuals. This study's findings indicate that increased social support is beneficial for middle-aged marginalized individuals, including those who are economically disadvantaged, have few social interactions, are underweight, and have chronic illnesses.