Tag: statistics

Brain Res. 2024 Apr 9:148931. doi: 10.1016/j.brainres.2024.148931. Online ahead of print.

ABSTRACT

This study aims to explore the therapeutic effect and possible mechanisms of icariin in schizophrenia. SD rats were divided into five groups, a control group, a MK801-induced schizophrenia model group, and three icariin treatment groups, with twelve rats in each group. Morris water maze and open field were used to observe the spatial learning and memory ability of rats. Compared with the control group, rats in the MK801-induced model group showed an increase in stereotypic behavior score, distance of spontaneous activities, escape latency, malondialdehyde (MDA) content, and IL-6, IL-1β, TNF-α expression, but a decrease in platform crossing times and superoxide dismutase (SOD) activity (P < 0.05). Furthermore, all the above changes of the model group were reversed after icariin treatment in a dose-dependent manner (P < 0.05). Network pharmacology found that icariin can exert anti-schizophrenic effects through some signaling pathways, such as relaxin, estrogen, and TNF signaling pathways. MAPK1, MAPK3, FOS, RELA, TNF, and JUN were the key targets of icariin on schizophrenia, and their expression was detected in animal models, which was consistent with the predicted results of network pharmacology. Icariin treatment may improve the spatial learning and memory ability of schizophrenic rats through TNF signaling pathway.

PMID:38604555 | DOI:10.1016/j.brainres.2024.148931

Front Neuroendocrinol. 2024 Apr 9:101133. doi: 10.1016/j.yfrne.2024.101133. Online ahead of print.

ABSTRACT

The incorporation of sex and gender (S/G) related factors is commonly acknowledged as a necessary step to advance towards more personalized diagnoses and treatments for somatic, psychiatric, and neurological diseases. Until now, most attempts to integrate S/G-related factors have been reduced to identifying average differences between females and males in behavioral/ biological variables. The present commentary questions this traditional approach by highlighting three main sets of limitations: 1) Issues stemming from the use of classic parametric methods to compare means; 2) challenges related to the ability of means to accurately represent the data within groups and differences between groups; 3) mean comparisons impose a results’ binarization and a binary theoretical framework that precludes advancing towards precision medicine. Alternative methods free of these limitations are also discussed. We hope these arguments will contribute to reflecting on how research on S/G factors is conducted and could be improved.

PMID:38604552 | DOI:10.1016/j.yfrne.2024.101133

Nurse Educ Today. 2024 Apr 1;138:106189. doi: 10.1016/j.nedt.2024.106189. Online ahead of print.

ABSTRACT

AIM: The purpose of this study was to analyze the effectiveness of virtual reality technology in nursing education.

BACKGROUND: Virtual reality technology is regarded as one of the advanced and significant instructional tools in contemporary education. However, its effectiveness in nursing education remains a subject of debate, and there is currently limited comprehensive research discussing the impact of varying degrees of virtual technology on the educational effectiveness of nursing students.

DESIGN: Systematic review and meta-analysis.

METHODS: The present systematic review and meta-analysis were applied according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. The PubMed, Embase, CINAHL, ProQuest, Cochrane Library, Web of Science, and Scopus were searched for relevant articles in the English language. The methodologies of the studies evaluated were assessed using Cochrane Risk of Bias2 (ROB 2) tool and Joanna Briggs Institute (JBI) assessment tool. We took the learning satisfaction, knowledge, and skill performance of nursing students as the primary outcomes, and nursing students’ self-efficacy, learning motivation, cognitive load, clinical reasoning, and communication ability were assessment as secondary outcomes. The meta-analysis was performed using R 4.3.2 software according to PRISMA guidelines. Heterogeneity was assessed by I² and P statistics. Standardized mean difference (SMD) and 95 % confidence intervals (CIs) were used as effective indicators.

RESULTS: Twenty-six studies were reviewed, which involved 1815 nursing students. The results showed that virtual reality teaching, especially immersive virtual reality, was effective in improving nursing students’ learning satisfaction (SMD: 0.82, 95%CI: 0.53-1.11, P < 0.001), knowledge (SMD: 0.56, 95%CI: 0.34-0.77, P < 0.001), skill performance (SMD: 1.13, 95 % CI: 0.68-1.57, P < 0.001), and self-efficacy (SMD: 0.64, 95%CI: 0.21,1.07, P < 0.001) compared to traditional teaching methods. However, the effects of virtual reality technology on nursing students’ motivation, cognitive load, clinical reasoning, and communication ability were not significant and require further research.

CONCLUSIONS: The results of this study show that virtual reality technology has a positive impact on nursing students. Nonetheless, it is crucial not to underestimate the effectiveness of traditional education methods, and future research could analyze the impact of different populations on nursing education while improving virtual reality technology, to more comprehensively explore how to improve the quality of nursing education. Moreover, it is imperative to emphasize the integration of virtual education interventions with real-world experiences promptly. This integration is essential for bridging the gap between the virtual learning environment and real-life scenarios effectively.

REGISTRATION NUMBER: CRD42023420497 (https://www.crd.york.ac.uk/PROSPERO/#recordDetails).

PMID:38603830 | DOI:10.1016/j.nedt.2024.106189

Nurse Educ Today. 2024 Mar 24;138:106155. doi: 10.1016/j.nedt.2024.106155. Online ahead of print.

ABSTRACT

BACKGROUND: Good nursing leadership management positively correlates with patient care quality and an organization’s performance. Plans to nurture top-notch talents and strengthen management functions are essential to retain key talents and achieve sustainability. The leadership training for nursing staff should begin early to cope with complex clinical situations.

OBJECTIVES: To compare the impact of leadership training on high-performing young nurses’ (young nursing elite) management functions and team behavior.

SETTING: A public teaching hospital in Taipei, Taiwan.

METHODS: This research implemented a longitudinal quasi-experimental study with a fixed time series design; the target subjects were youth nursing elites who received training, along with their direct managers and peers, for a total of 102 participants. The training course intervention included the classroom teaching of leadership management functions, arranging internships in the hospital’s internal administrative units and professional nursing institutions, and the direct managers sharing their experiences during teaching. We measured the outcome indicators before the course intervention, at the end of the course intervention, and three months after using the management function and team behavior scales.

RESULTS: The mean score of the direct managers’ assessments regarding the youth nursing elite’s pre-test team behavior was 4.18. This improved by 0.68 points (p < .001) after the program intervention and improved by 0.65 points (p < .001) three months after the program compared to the pre-test. There was no statistically significant difference between the two groups as analyzed using GEE. The mean score of the pre-test self-assessment management function of the young nursing elite was 3.27. This improved by 1.06 points (p < .001) after the program intervention and by 1.14 points (p < .001) three months after the program compared to the pre-test. There was no statistically significant difference between the three groups using GEE analysis.

CONCLUSIONS: Leadership training enhances young nursing professionals’ leadership function and team behavior.

PMID:38603829 | DOI:10.1016/j.nedt.2024.106155

Nurse Educ Today. 2024 Apr 6;138:106196. doi: 10.1016/j.nedt.2024.106196. Online ahead of print.

ABSTRACT

BACKGROUND: One in four newly graduated registered nurses leave their employment positions within the first year. To reduce this attrition, nursing stakeholders could focus on the final year of nursing education because students at this stage make professional career plans, including their practice destination for the graduate year and their commitment to the profession. Previous studies provide evidence of nursing students’ career preferences and specialty choices. However, there is a dearth of data that focuses on the students’ career decision-making process.

AIM: This study examined the self-efficacy or confidence of final-year nursing students in making career decisions and the factors that influence their career decision-making process.

SETTING AND PARTICIPANTS: Final year pre-registration nursing students (N = 222) at two public universities in Western Australia.

METHODS: An online survey was used to collect cross-sectional data. The Career Decision Self-Efficacy Scale – Short Form was used to investigate nursing students’ confidence in making career decisions. Career decision-making self-efficacy refers to the confidence to successfully complete career decision-making tasks. Descriptive statistics were used to describe the participants’ characteristics. The chi-square test was used to assess the significance of the difference between categorical data, and binary logistic regression was used to determine the odds of the factors that predict career decision self-efficacy.

RESULTS: Forty-seven percent of participants who answered all Career Decision Self-Efficacy Scale – Short Form questions had good confidence in making career decisions. Factors such as the setting of the final clinical placement, the intention to be employed in the specialisation or organisation of their final placement and the students’ assessment of their clinical experience were associated with career decision-making confidence.

CONCLUSIONS: Most participants had low confidence in making career decisions. This study provides ideas for nursing stakeholders to implement measures to improve students’ confidence to make informed career decisions.

PMID:38603828 | DOI:10.1016/j.nedt.2024.106196

Environ Int. 2024 Apr 1;186:108619. doi: 10.1016/j.envint.2024.108619. Online ahead of print.

ABSTRACT

INTRODUCTION: Ambient air temperature may affect birth outcomes adversely, but little is known about their impact on foetal growth throughout pregnancy. We evaluated the association between temperature exposure during pregnancy and foetal size and growth in three European birth cohorts.

METHODS: We studied 23,408 pregnant women from the English Born in Bradford cohort, Dutch Generation R Study, and Spanish INMA Project. Using the UrbClim^TM model, weekly ambient air temperature exposure at 100x100m resolution at the mothers’ residences during pregnancy was calculated. Estimated foetal weight, head circumference, and femur length at mid and late pregnancy and weight, head circumference, and length at birth were converted into standard deviation scores (SDS). Foetal growth from mid to late pregnancy was calculated (grams or centimetres/week). Cohort/region-specific distributed lag non-linear models were combined using a random-effects meta-analysis and results presented in reference to the median percentile of temperature (14 °C).

RESULTS: Weekly temperatures ranged from -5.6 (Bradford) to 30.3 °C (INMA-Sabadell). Cold and heat exposure during weeks 1-28 were associated with a smaller and larger head circumference in late pregnancy, respectively (e.g., for 9.5 °C: -1.6 SDS [95 %CI -2.0; -0.4] and for 20.0 °C: 1.8 SDS [0.7; 2.9]). A susceptibility period from weeks 1-7 was identified for cold exposure and a smaller head circumference at late pregnancy. Cold exposure was associated with a slower head circumference growth from mid to late pregnancy (for 5.5 °C: -0.1 cm/week [-0.2; -0.04]), with a susceptibility period from weeks 4-12. No associations that survived multiple testing correction were found for other foetal or any birth outcomes.

CONCLUSIONS: Cumulative exposure to cold and heat during pregnancy was associated with changes in foetal head circumference throughout gestation, with susceptibility periods for cold during the first pregnancy trimester. No associations were found at birth, suggesting potential recovery. Future research should replicate this study across different climatic regions including varying temperature profiles.

PMID:38603813 | DOI:10.1016/j.envint.2024.108619

JMIR Form Res. 2024 Apr 11;8:e50968. doi: 10.2196/50968.

ABSTRACT

BACKGROUND: Cybersecurity is a growing challenge for health systems worldwide as the rapid adoption of digital technologies has led to increased cyber vulnerabilities with implications for patients and health providers. It is critical to develop workforce awareness and training as part of a safety culture and continuous improvement within health care organizations. However, there are limited open-access, health care-specific resources to help organizations at different levels of maturity develop their cybersecurity practices.

OBJECTIVE: This study aims to assess the usability and feasibility of the Essentials of Cybersecurity in Health Care Organizations (ECHO) framework resource and evaluate the strengths, weaknesses, opportunities, and threats associated with implementing the resource at the organizational level.

METHODS: A mixed methods, cross-sectional study of the acceptability and usability of the ECHO framework resource was undertaken. The research model was developed based on the technology acceptance model. Members of the Imperial College Leading Health Systems Network and other health care organizations identified through the research teams’ networks were invited to participate. Study data were collected through web-based surveys 1 month and 3 months from the date the ECHO framework resource was received by the participants. Quantitative data were analyzed using R software (version 4.2.1). Descriptive statistics were calculated using the mean and 95% CIs. To determine significant differences between the distribution of answers by comparing results from the 2 survey time points, 2-tailed t tests were used. Qualitative data were analyzed using Microsoft Excel. Thematic analysis used deductive and inductive approaches to capture themes and concepts.

RESULTS: A total of 16 health care organizations participated in the study. The ECHO framework resource was well accepted and useful for health care organizations, improving their understanding of cybersecurity as a priority area, reducing threats, and enabling organizational planning. Although not all participants were able to implement the resource as part of information computing technology (ICT) cybersecurity activities, those who did were positive about the process of change. Learnings from the implementation process included the usefulness of the resource for raising awareness and ease of use based on familiarity with other standards, guidelines, and tools. Participants noted that several sections of the framework were difficult to operationalize due to costs or budget constraints, human resource limitations, leadership support, stakeholder engagement, and limited time.

CONCLUSIONS: The research identified the acceptability and usability of the ECHO framework resource as a health-focused cybersecurity resource for health care organizations. As cybersecurity in health care organizations is everyone’s responsibility, there is potential for the framework resource to be used by staff with varied job roles. Future research needs to explore how it can be updated for ICT staff and implemented in practice and how educational materials on different aspects of the framework could be developed.

PMID:38603777 | DOI:10.2196/50968

J Chem Theory Comput. 2024 Apr 11. doi: 10.1021/acs.jctc.4c00014. Online ahead of print.

ABSTRACT

On the one hand, much of computational chemistry is concerned with “bottom-up” calculations which elucidate observable behavior starting from exact or approximated physical laws, a paradigm exemplified by typical quantum mechanical calculations and molecular dynamics simulations. On the other hand, “top down” computations aiming to formulate mathematical models consistent with observed data, e.g., parametrizing force fields, binding or kinetic models, have been of interest for decades but recently have grown in sophistication with the use of Bayesian inference (BI). Standard BI provides an estimation of parameter values, uncertainties, and correlations among parameters. Used for “model selection,” BI can also distinguish between model structures such as the presence or absence of individual states and transitions. Fortunately for physical scientists, BI can be formulated within a statistical mechanics framework, and indeed, BI has led to a resurgence of interest in Monte Carlo (MC) algorithms, many of which have been directly adapted from or inspired by physical strategies. Certain MC algorithms─notably procedures using an “infinite temperature” reference state─can be successful in a 5-20 parameter BI context which would be unworkable in molecular spaces of 10³ coordinates and more. This Review provides a pedagogical introduction to BI and reviews key aspects of BI through a physical lens, setting the computations in terms of energy landscapes and free energy calculations and describing promising sampling algorithms. Statistical mechanics and basic probability theory also provide a reference for understanding intrinsic limitations of Bayesian inference with regard to model selection and the choice of priors.

PMID:38603773 | DOI:10.1021/acs.jctc.4c00014

PLoS One. 2024 Apr 11;19(4):e0300175. doi: 10.1371/journal.pone.0300175. eCollection 2024.

ABSTRACT

Timely case notifications following the introduction of an uncommon pathogen, such as mpox, are critical for understanding disease transmission and for developing and implementing effective mitigation strategies. When Massachusetts public health officials notified the Centers for Disease Control and Prevention (CDC) about a confirmed orthopoxvirus case on May 17, 2023, which was later confirmed as mpox at CDC, mpox was not a nationally notifiable disease. Because existing processes for new data collections through the National Notifiable Disease Surveillance System were not well suited for implementation during emergency responses at the time of the mpox outbreak, several interim notification approaches were established to capture case data. These interim approaches were successful in generating daily case counts, monitoring disease transmission, and identifying high-risk populations. However, the approaches also required several data collection approvals by the federal government and the Council for State and Territorial Epidemiologists, the use of four different case report forms, and the establishment of complex data management and validation processes involving data element mapping and record-level de-duplication steps. We summarize lessons learned from these interim approaches to inform and improve case notifications during future outbreaks. These lessons reinforce CDC’s Data Modernization Initiative to work in close collaboration with state, territorial, and local public health departments to strengthen case-based surveillance prior to the next public health emergency.

PMID:38603766 | DOI:10.1371/journal.pone.0300175

PLoS One. 2024 Apr 11;19(4):e0301602. doi: 10.1371/journal.pone.0301602. eCollection 2024.

ABSTRACT

BACKGROUND: Stillbirth is a silent tragedy that shatters the lives of women, families, and nations. Though affecting over 2 million infants globally in 2019, it remains overlooked, with no specific targets dedicated to its reduction in the sustainable development goals. Insufficient knowledge regarding the primary risk factors contributing to stillbirths hinders efforts to reduce its occurrence. Driven by this urgency, this study focused on identifying the determinants of stillbirth among women giving birth in hospitals across North Wollo Zone, Northeast Ethiopia.

METHODOLOGY: This study employed an institution-based unmatched case-control design, involving a randomly selected sample of 412 women (103 cases and 309 controls) who gave birth in hospitals of North Wollo Zone. Data were collected using a structured data extraction checklist. Data entry was conducted using Epi-data version 3.1, and analysis was performed using SPSS version 25.0. Employing a multivariable logistic regression model, we identified independent predictors of stillbirth. The level of statistical significance was declared at a p-value < 0.05.

RESULTS: Our analysis revealed several critical factors associated with an increased risk of stillbirth. Women who experienced premature rupture of membranes (AOR = 5.53, 95% CI: 2.33-9.94), induced labor (AOR = 2.24, 95% CI: 1.24-4.07), prolonged labor exceeding 24 hours (AOR = 3.80, 95% CI: 1.94-7.45), absence of partograph monitoring during labor (AOR = 2.45, 95% CI: 1.41-4.26) were all significantly associated with increased risk of stillbirth. Preterm birth (AOR = 3.46, 95% CI: 1.87-6.39), post-term birth (AOR = 3.47, 95% CI: 1.35-8.91), and carrying a female fetus (AOR = 1.81, 95% CI: 1.02-3.22) were at a higher risk of stillbirth.

CONCLUSION: These findings highlight the importance of early intervention and close monitoring for women experiencing premature rupture of membranes, prolonged labor, or induced labor. Additionally, consistent partograph use and enhanced prenatal care for pregnancies at risk of preterm or post-term birth could potentially contribute to reducing stillbirth rates and improving maternal and neonatal outcomes. Further research is needed to investigate the underlying mechanisms behind the observed association between fetal sex and stillbirth risk.

PMID:38603732 | DOI:10.1371/journal.pone.0301602