Social network analysis to characterize women victims of violence

International Collaboration in Taiwan Emergency Department Publications: A Social Network Analysis

Background

Emergency medicine (EM) is a growing specialty both clinically and academically. Academic EM development can be measured by number of scientific publications. This study aimed to evaluate the academic international cooperation trend of Taiwan emergency departments (EDs) in the past two decades using social network analysis (SNA).

Methods

The study population were publications with first author affiliated with Taiwan EDs and the study duration was publication year before 2021. The enrolled publications were categorized into two groups: Group one, all authors were affiliated with Taiwan (domestic publications) and Group two, authors were affiliated with Taiwan and other countries (international publications). The primary outcome measurement was the degree centrality of Taiwan before 2021. The secondary outcome measurements included the trend in annual publication number of Group one and Group two, the trend in country number of each year in Group two, the top five countries that collaborate with Taiwan, the difference between the median of citation numbers in Group one and Group two, and the difference between the median of author numbers in Group one and Group two.

Results

A total 4,363 publications were enrolled, of which 4,046 publications were classified in Group one and 317 publications were in Group two. The annual publication number of both groups increased significantly. The annual country number of collaboration with Taiwan ED publications had also significantly increased. The median of citation number and author number in Group two were both significantly higher than Group one. The top five countries collaborating with Taiwan were the United States, China, Malaysia, Japan, and Australia.

Conclusions

Taiwan EDs' growing international collaboration in the past two decades indicated a capacity to conduct multi-country research. International collaboration publications obtained higher citations compared to domestic publications. Researchers should enhance international collaborations for academic advancement.

Clinical validation of the ineffective social support network nursing diagnosis in violence-victimized women

PURPOSE

To verify clinical validity evidence for the ineffective social support network nursing diagnosis.

METHOD

A quantitative, descriptive, cross-sectional study was performed with 98 violence-victimized women treated in two reference centers for violence in the city of Recife, Pernambuco, Brazil. The women were interviewed from August 2021 to June 2022.

FINDINGS

The clinical indicators that best predicted the nursing diagnosis were as follows: Frustration with unmet support expectations, negative social interaction, perceived neglect of support demands, feeling of abandonment, low reciprocity, and encouragement of negative behaviors. Etiological factors that showed greater association were excessive demand for support, limited social network, social isolation, the fragility of institutional service networked organizations, and inadequate appreciation of available social support.

CONCLUSIONS

The clinical validity evidence for the ineffective social support network nursing diagnosis has been verified. Thus, the validated clinical indicators and etiological factors can accurately diagnose and predict the emergence of this phenomenon in violence-victimized women.

IMPLICATIONS FOR NURSING PRACTICE

The results contribute to advancing scientific knowledge in nursing teaching, research, and practice and support the nursing process in violence-victimized women.

Global, regional, and national burdens of interpersonal violence in young women aged 10-24 years from 1990 to 2019: a trend analysis based on the global burden of disease study 2019

Background

Interpersonal violence (IPV) against young women, including physical and sexual violence, poses a major threat to public health. We analyzed global, regional and national trends in violence against females aged 10-24 years from 1990 to 2019.

Methods

We extracted age-standardized prevalence rates (ASPRs) of physical violence by firearm (PVF), physical violence by other means (PVOM), physical violence by sharp object (PVSO), and sexual violence (SV) from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Joinpoint regression analysis calculated annual and average annual percentage changes (AAPCs) in ASPRs.

Results

Globally, the ASPRs of the four measures of IPV decreased between 1990 and 2019, with the steepest declines between 2000 and 2009, except for SV, which increased slightly. However, the ASPRs of PVF and PVOM increased slightly between 2010 and 2019. Regionally, PVF prevalence declined most in East Asia (-0.9505, -1.0011 to -0.8975), South Asia (-0.277, -0.3089 to -0.244) and Latin America but PVOM prevalence increased in Oceania (0.6275, 0.6036 to 0.6498) and SV prevalence increased in Caribbean (0.4267, 0.4069 to 0.4495). Nationally, PVF prevalence decreased most in Thailand (-2.4031, -2.4634 to -2.3328) but increased most in Libya (6.8143, 6.6194 to 7.0113). SV prevalence increased most in Oman (0.4561, 0.4338 to 0.478) and the largest increase in Disability-adjusted life years (DALYs) from PVOM was observed in Botswana (6.2725, 6.0951 to 6.4082). DALYs showed similar trends.

Conclusion

While global declines over 30 years are encouraging, IPV against young women persists. Urgent, tailored approaches across sectors are critical to curb drivers of violence against young women, including poverty, inequality and sociocultural attitudes. High-quality data and in-depth analyses can inform locally-relevant solutions. Overall, intensified political will and resource investment are needed to overcome this pervasive human rights violation.

A Systematic Review of Systems Science Approaches to Understand and Address Domestic and Gender-Based Violence

Purpose

We aimed to synthesize insights from systems science approaches applied to domestic and gender-based violence.

Methods

We conducted a systematic review of systems science studies (systems thinking, group model-building, agent-based modeling [ABM], system dynamics [SD] modeling, social network analysis [SNA], and network analysis [NA]) applied to domestic or gender-based violence, including victimization, perpetration, prevention, and community responses. We used blinded review to identify papers meeting our inclusion criteria (i.e., peer-reviewed journal article or published book chapter that described a systems science approach to domestic or gender-based violence, broadly defined) and assessed the quality and transparency of each study.

Results

Our search yielded 1,841 studies, and 74 studies met our inclusion criteria (45 SNA, 12 NA, 8 ABM, and 3 SD). Although research aims varied across study types, the included studies highlighted social network influences on risks for domestic violence, clustering of risk factors and violence experiences, and potential targets for intervention. We assessed the quality of the included studies as moderate, though only a minority adhered to best practices in model development and dissemination, including stakeholder engagement and sharing of model code.

Conclusions

Systems science approaches for the study of domestic and gender-based violence have shed light on the complex processes that characterize domestic violence and its broader context. Future research in this area should include greater dialogue between different types of systems science approaches, consideration of peer and family influences in the same models, and expanded use of best practices, including continued engagement of community stakeholders.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10896-023-00578-8.

Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes: The 2019 Literature Year in Review

Data science continues to be recognized and used within healthcare due to the increased availability of large data sets and advanced analytics. It can be challenging for nurse leaders to remain apprised of this rapidly changing landscape. In this article, we describe our findings from a scoping literature review of papers published in 2019 that use data science to explore, explain, and/or predict 15 phenomena of interest to nurses. Fourteen of the 15 phenomena were associated with at least one paper published in 2019. We identified the use of many contemporary data science methods (eg, natural language processing, neural networks) for many of the outcomes. We found many studies exploring Readmissions and Pressure Injuries. The topics of Artificial Intelligence/Machine Learning Acceptance, Burnout, Patient Safety, and Unit Culture were poorly represented. We hope that the studies described in this article help readers: (1) understand the breadth and depth of data science's ability to improve clinical processes and patient outcomes that are relevant to nurses and (2) identify gaps in the literature that are in need of exploration.

Violence against women: An observational study in an Italian emergency department

Violence against women is a pervasive phenomenon affecting one in three women aged ≥15 in the world that are more likely to visit an emergency department (ED) for the serious physical and psychological consequences of the abuse. The aim of this observational single-centre study is to describe the socio-demographic and clinical variables associated with violence against women. We enrolled 425 female patients who attended an Italian ED for trauma on 2019 and the patients' information was collected and analyzed with descriptive statistics. The average age of the patients was 41.5 (standard deviation = 14.2) years. 74.6% of the women were Italians, and 86.6% were of metropolitan origin. The reasons for the ED visit included aggression (67.5%), accidental trauma (29.0%) and unknown reasons (3.5%). Multivariate analysis confirmed that three factors were independently associated with violence: nationality (odds ratio [OR] = 0.27; 95% confidence interval [CI], 0.09-0.77), head/face/neck injuries (OR = 7.32; 95% CI, 3.76-14.27) and multiple injuries (OR = 8.52; 95% CI, 1.03-70.47). Age over 25 was a protective factor. The study confirmed that being a foreigner and having head/face/neck injuries or multiple injuries are associated with violence against women.