Search results for: marital adjustments

Authors: Carolina Busco, Daniela Osses

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The development of digital literacy has become a fundamental element that allows for citizen inclusion, access to quality jobs, and a labor market capable of responding to the digital economy. There are no methodological instruments available in Chile to measure the workforce’s digital literacy and improve national policies on this matter. Thus, the objective of this research is to develop a survey to measure digital literacy in a sample of 200 Chilean workers. Dimensions considered in the instrument are sociodemographics, access to infrastructure, digital education, digital skills, and the ability to use e-government services. To achieve the research objective of developing a digital literacy model of indicators and a research instrument for this purpose, along with an exploratory analysis of data using factor analysis, we used an empirical, quantitative-qualitative, exploratory, non-probabilistic, and cross-sectional research design. The research instrument is a survey created to measure variables that make up the conceptual map prepared from the bibliographic review. Before applying the survey, a pilot test was implemented, resulting in several adjustments to the phrasing of some items. A validation test was also applied using six experts, including their observations on the final instrument. The survey contained 49 items that were further divided into three sets of questions: sociodemographic data; a Likert scale of four values ranked according to the level of agreement; iii) multiple choice questions complementing the dimensions. Data collection occurred between January and March 2022. For the factor analysis, we used the answers to 12 items with the Likert scale. KMO showed a value of 0.626, indicating a medium level of correlation, whereas Bartlett’s test yielded a significance value of less than 0.05 and a Cronbach’s Alpha of 0.618. Taking all factor selection criteria into account, we decided to include and analyze four factors that together explain 53.48% of the accumulated variance. We identified the following factors: i) access to infrastructure and opportunities to develop digital skills at the workplace or educational establishment (15.57%), ii) ability to solve everyday problems using digital tools (14.89%), iii) online tools used to stay connected with others (11.94%), and iv) residential Internet access and speed (11%). Quantitative results were discussed within six focus groups using heterogenic selection criteria related to the most relevant variables identified in the statistical analysis: upper-class school students; middle-class university students; Ph.D. professors; low-income working women, elderly individuals, and a group of rural workers. The digital divide and its social and economic correlations are evident in the results of this research. In Chile, the items that explain the acquisition of digital tools focus on access to infrastructure, which ultimately puts the first filter on the development of digital skills. Therefore, as expressed in the literature review, the advance of these skills is radically different when sociodemographic variables are considered. This increases socioeconomic distances and exclusion criteria, putting those who do not have these skills at a disadvantage and forcing them to seek the assistance of others.

Keywords: digital literacy, digital society, workforce digitalization, digital skills

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Authors: Rose Branch-Allen, John Jayachandran

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Background and purpose: Canada is a pluralistic, multicultural society with an ethno-cultural composition that has been shaped over time by immigrants and their descendants. Although Canada welcomes these immigrants, many will endure hardship and assimilation difficulties. Despite these life hurdles, surveys consistently disclose high life satisfaction for all Canadians. Most research studies on Life Satisfaction/ Subjective Wellbeing (SWB) have focused on one main determinant and a variety of social demographic variables to delineate the determinants of life satisfaction. However, very few research studies examine life satisfaction from a holistic approach. In addition, we need to understand the causal pathways leading to life satisfaction, and develop theories that explain why certain variables differentially influence the different components of SWB. The aim this study was to utilize a holistic approach to construct a causal model and identify major determinants of life satisfaction. Data and measures: This study utilized data from the General Social Survey, with a sample size of 19, 597. The exogenous concepts included age, gender, marital status, household size, socioeconomic status, ethnicity, location, immigration status, religiosity, and neighborhood. The intervening concepts included health, social contact, leisure, enjoyment, work-family balance, quality time, domestic labor, and sense of belonging. The endogenous concept life satisfaction was measured by multiple indicators (Cronbach’s alpha = .83). Analysis: Several multiple regression models were run sequentially to estimate path coefficients for the causal model. Results: Overall, above average satisfaction with life was reported for respondents with specific socio-economic, demographic and lifestyle characteristics. With regard to exogenous factors, respondents who were female, younger, married, from high socioeconomic status background, born in Canada, very religious, and demonstrated high level of neighborhood interaction had greater satisfaction with life. Similarly, intervening concepts suggested respondents had greater life satisfaction if they had better health, more social contact, less time on passive leisure activities and more time on active leisure activities, more time with family and friends, more enjoyment with volunteer activities, less time on domestic labor and a greater sense of belonging to the community. Conclusions and Implications: Our results suggest that a holistic approach is necessary for establishing determinants of life satisfaction, and that life satisfaction is not merely comprised of positive or negative affect rather understanding the causal process of life satisfaction. Even though, most of our findings are consistent with previous studies, a significant number of causal connections contradict some of the findings in literature today. We have provided possible explanation for these anomalies researchers encounter in studying life satisfaction and policy implications.

Keywords: causal model, holistic approach, life satisfaction, socio-demographic variables, subjective well-being

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Authors: Mariam Anwaar, Kiran B. Ahmad

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Borderline Personality Disorder (BPD) is an invasive presence of affect instability, disturbance in self-concept and attachment in relationships. The profound indicator is the dichotomous approach of the world in which the ego categorizes individuals, especially their significant others, into secure or threatful beings, leaving little room for a complex combination of characteristics in one person. This defense mechanism of splitting their world has been described through the explanatory model of unconscious conflict theorized by Sigmund Freud’s Electra Complex in the Phallic Stage. The central role is of the father with whom the daughter experiences penis envy, thus identifying with the mother’s characteristics to receive the father’s attention. However, Margret Mahler, an object relation theorist, elucidates the central role of the mother and that the split occurs during the pre-Electra complex stage. Amid the 14 and 24 months of the infant, it acknowledges the world away from the mother as they have developed milestones such as crawling. In such novelty, the infant crawls away from the mother creating a sense of independence (individuation). On the other hand, being distant causes anxiety, making them return to their original object of security (separation). In BPD, the separation-individuation stage is disrupted, due to contradictory actions of the caregiver, which results in splitting the object into negative and positive aspects, repressing the former and adhering to the latter for survival. Thus, with time, the ego distorts the reality into dichotomous categories, using the splitting defenses, and the mental representation of the self is distorted due to the internalization of the negative objects. The explanatory model was recognized in the case study of Fizza, at 21-year-old Pakistani female, residing in Karachi. Her marital status is single with an occupation being a dental student. Fizza lives in a nuclear family but is surrounded by her extended family as they all are in close vicinity. She came with the complaints of depressive symptoms for two-years along with self-harm due to severe family conflicts. Through the intervention of Dialectical Behavior Therapy (DBT), the self-harming actions were reduced, however, this libidinal energy transformed into claustrophobic symptoms and, along with this, Fizza has always experienced vivid dreams. A retrospective method of Jungian dream-analysis was applied to locate the origins of the splitting in the unconscious. The result was the revelation of a sexual harassment trauma at the age of six-years which was displaced in the form of self-harm. In addition to this, the presence of a conflict at the separation-individuation stage was detected during the dream-analysis, and it was the underlying explanation of the claustrophobic symptoms. This qualitative case study implicates the use of a patient’s subjective experiences, such as dreams, to journey through the spiral of the unconscious in order to not only detect repressed memories but to use them in psychotherapy as a means of healing the patient.

Keywords: borderline personality disorder, dream-analysis, Electra complex, separation-individuation, splitting, unconscious

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Authors: Dominik Kowitzke

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Housing constructions have direct and indirect environmental impacts especially caused by soil sealing and gray energy consumption related to the use of construction materials. Accordingly, the German government introduced regulations limiting additional annual soil sealing. At the same time, in many regions like metropolitan areas the demand for further housing is high and of current concern in the media and politics. It is argued that meeting this demand by making better use of the existing housing supply is more sustainable than the construction of new housing units. In this context, targeting the phenomenon of so-called over the housing of empty nest households seems worthwhile to investigate for its potential to free living space and thus, reduce the need for new housing constructions and related environmental harm. Over housing occurs if no space adjustment takes place in household lifecycle stages when children move out from home and the space formerly created for the offspring is from then on under-utilized. Although in some cases the housing space consumption might actually meet households’ equilibrium preferences, frequently space-wise adjustments to the living situation doesn’t take place due to transaction or information costs, habit formation, or government intervention leading to increasing costs of relocations like real estate transfer taxes or tenant protection laws keeping tenure rents below the market price. Moreover, many detached houses are not long-term designed in a way that freed up space could be rent out. Findings of this research based on socio-economic survey data, indeed, show a significant difference between the living space of empty nest and a comparison group of households which never had children. The approach used to estimate the average difference in living space is a linear regression model regressing the response variable living space on a two-dimensional categorical variable distinguishing the two groups of household types and further controls. This difference is assumed to be the under-utilized space and is extrapolated to the total amount of empty nests in the population. Supporting this result, it is found that households that move, despite market frictions impairing the relocation, after children left their home tend to decrease the living space. In the next step, only for areas with tight housing markets in Germany and high construction activity, the total under-utilized space in empty nests is estimated. Under the assumption of full substitutability of housing space in empty nests and space in new dwellings in these locations, it is argued that in a perfect market with empty nest households consuming their equilibrium demand quantity of housing space, dwelling constructions in the amount of the excess consumption of living space could be saved. This, on the other hand, would prevent environmental harm quantified in carbon dioxide equivalence units related to average constructions of detached or multi-family houses. This study would thus provide information on the amount of under-utilized space inside dwellings which is missing in public data and further estimates the external effect of over housing in environmental terms.

Keywords: empty nests, environment, Germany, households, over housing

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Authors: Charlotte Bach, Albrecht Jahn, Mahnaz Motamedi, Maryam Karimi-Ghahfarokhi

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Background: Maternal and infant deaths are most prevalent in the first month after birth, emphasizing the critical need for quality healthcare services during this period. Immigrant women, who are more susceptible to adverse pregnancy outcomes, often face neglect in accessing proper healthcare. The lack of adequate postpartum care significantly contributes to mortality rates. Therefore, utilizing maternal health care services and implementing postpartum care is crucial in reducing maternal and child mortality. Aims: This study aims to evaluate the assessment of pre- and postnatal care among women with and without migration background. In addition, the study explores the impact of COVID-19 procedures on women's experiences during pregnancy, birth, and the postpartum period. Methods: This research employs a cross-sectional Mixed-Method design. Data collection was facilitated through structured questionnaires administered to participants, alongside the utilization of patient bases, including Maternity and child medical records. Following the assumption that the investigator aimed to gain comprehensive insights, qualitative sampling focused on individuals with substantial experiences related to COVID-19, regarded as rich cases. Results: our study highlighted the influence of educational level, marital status, and consensual partnerships on the likelihood of Cesarean deliveries. Regarding breastfeeding practices, migrant women exhibited higher rates of breastfeeding initiation and continuation. Contraception utilization revealed interesting patterns, with non-migrants displaying higher odds of contraceptive use. The qualitative component of our research adds depth to the exploration of women's experiences during the COVID-19 pandemic, revealing nuanced challenges related to anxiety, hospital restrictions, breastfeeding support, and postnatal ward routines. Conclusion: Dissimilarity among studies toward cesarean rate between migrants and non-migrants underscores the importance of targeted interventions considering the diverse needs of distinct population groups. It also acknowledges potential cultural, contextual, and healthcare system influences on the association between mode of delivery and infant feeding practices. Studies acknowledge the influence of contextual variables on contraceptive preferences among migrants and non-migrants, emphasizing the need for tailored healthcare policies. The findings contribute to existing research, highlighting the need for a nuanced understanding of the impact of birth preparation courses on maternal and infant outcomes. Furthermore, they emphasize the universality of certain maternity care experiences, regardless of pandemic contexts, reinforcing the importance of patient-centred approaches in healthcare delivery.

Keywords: migration background, pregnancy outcome, covid-19, postpartum

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Authors: Paola Montenegro, Maria de los Angeles Balaguera Villa

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In February 2022 Colombia achieved a historic milestone in ensuring universal access to abortion rights with ruling C-055 of 2022 decriminalising abortion up to 24 weeks of gestation. In the context of this triumph and the expansion of telemedicine services in the wake of the COVID-19 pandemic, this research studied the acceptability of self-care abortion in young people (13 - 28 years) through a telemedicine service and also explored the primary needs that should be the focus of such care. The results shine light on a more comprehensive understanding of opportunities and challenges of teleabortion practices in a context that combines overall higher access to technology and low access to reliable information of safe abortion, stigma, and scarcity especially felt by transnational migrants, racialised people, trans men and non-binary people. Through a mixed methods approach, this study collected 5.736 responses to a virtual survey disseminated nationwide in Colombia and 47 in-person interviews (24 of them with people who were assigned female at birth and 21 with local key stakeholders in the abortion ecosystem). Quantitative data was analyzed using Stata SE Version 16.0 and qualitative analysis was completed through NVivo using thematic analysis. Key findings of the research suggest that self-care abortion is practice with growing acceptability among young people, but important adjustments must be made to meet quality of care expectations of users. Elements like quick responses from providers, lower costs, and accessible information were defined by users as decisive factors to choose over the abortion service provider. In general, the narratives in participants about quality care were centred on the promotion of autonomy and the provision of accompaniment and care practices, also perceived as transformative and currently absent of most health care services. The most staggering findings from the investigation are related to current barriers faced by young people in abortion contexts even when the legal barriers have: high rates of scepticism and distrust associated with pitfalls of telehealth and structural challenges associated with lacking communications infrastructure, among a few of them. Other important barriers to safe self-care abortion identified by participants surfaced like lack of privacy and confidentiality (especially in rural areas of the country), difficulties accessing reliable information, high costs of procedures and expenses related to travel costs or having to cease economic activities, waiting times, and stigma are among the primary barriers to abortion identified by participants. Especially in a scenario marked by unprecedented social, political and economic disruptions due to the COVID-19 pandemic, the commitment to design better care services that can be adapted to the identities, experiences, social contexts and possibilities of the user population is more necessary than ever. In this sense, the possibility of expanding access to services through telemedicine brings us closer to the opportunity to rethink the role of health care models in transforming the role of individuals and communities to make autonomous, safe and informed decisions about their own health and well-being.

Keywords: contraception, family planning, premarital fertility, unplanned pregnancy

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Authors: Magda Milleyde de Sousa Lima, Letícia Lima Aguiar, Marina Guerra Martins, Erika Veríssimo Dias Sousa, Lizandra Sampaio de Oliveira, Lívia Moreira Barros, Joselany Áfio Caetano

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Patients with chronic kidney disease are vulnerable to episodes which make the safety of their health vulnerable, mainly due to the treatment process that exposes them to high rates of interventions during hemodialysis sessions. Some factors associated with health care contribute to the risk of death and complications. However, there are a small number of scientific studies evaluating the level of safety of hemodialysis clinics, and the sociodemographic characteristics of patients and professionals associated with this safety. Therefore, the present study aims to examine the level of patient safety in hemodialysis clinics in the Brazilian capital, to identify the sociodemographic and clinical factors of patients and nursing staff associated with the level of safety. This is an observational, descriptive and quantitative research conducted in three hemodialysis clinics placed in the city of Fortaleza-CE, Brazil, from September to November 2019. The sample was formed after a sample calculation for finite inhabitants of correlation with 200 chronic renal patients, 30 nursing technicians and seven nurses. Conventional sampling was used based on the inclusion criteria: being present at the hemodialysis session on the day the researcher performed the data collection and being 18 years of age or older. Participants who presented communication difficulties to listen to and/or answer the sociodemographic and clinical questionnaire were excluded. Two instruments were applied: sociodemographic and clinical characterization form and Chronic Renal Patient Safety Assessment Scale on Hemodialysis (EASPRCH). The data were analyzed using the Kruskal Walls Test for categorical variables and Spearman correlation coefficient for non-categorical variables, using the Statistical Package SPSS version 20.0. The present study respected the ethical and legal principles determined by resolution 466/2012 of the National Health Council, under the approval of the Ethics and Research Committee with an opinion number: 3,255,635. The results showed that a hemodialysis clinic presented unsafe care practices of 32 points in the EASPRCH (p=0.001). A statistical association was identified between the level of safety and the variables of the patients: level of education (p=0.018), family income (p=0.049), type of employment (p=0.012), venous access site (p=0.009), use of medication during the session (p=0.008) and time of hemodialysis (p=0.002). When evaluating the profile of nurses, a statistical association was evidenced between the level of safety with the variables: marital status (p=0.000), race (p=0.017), schooling (p= 0.000), income (p=0.013), age (p=0.000), clinic workload (p=0.000), time working with hemodialysis (p=0.000), time working in the clinic (p= 0.007) and clinic sizing (p=0.000). In order, the sociodemographic factors of nursing technicians associated with the level of patient safety were: race (p= 0.001) and weekly workload at (p=0.010). Therefore, it is concluded that there is a non-conformity in the level of patient safety in one of the clinics studied and, that sociodemographic and clinical factors of patients and health professionals corroborate the level of safety of the health unit.

Keywords: hemodialysis, nursing, patient safety, quality improvement

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Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Sıdıka Kaya, Gülay Sain Güven, Seda Karsavuran, Onur Toka

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This study is part of an ongoing research project supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 114K404, and participation to this conference was supported by Hacettepe University Scientific Research Coordination Unit under Project Number 10243. Evaluation of hospital readmissions is gaining importance in terms of quality and cost, and is becoming the target of national policies. In Turkey, the topic of hospital readmission is relatively new on agenda and very few studies have been conducted on this topic. The aim of this study was to determine 30-day readmission rates and risk factors for readmission. Whether readmission was planned, related to the prior admission and avoidable or not was also assessed. The study was designed as a ‘prospective cohort study.’ 472 patients hospitalized in internal medicine departments of a university hospital in Turkey between February 1, 2015 and April 30, 2015 were followed up. Analyses were conducted using IBM SPSS Statistics version 22.0 and SPSS Modeler 16.0. Average age of the patients was 56 and 56% of the patients were female. Among these patients 95 were readmitted. Overall readmission rate was calculated as 20% (95/472). However, only 31 readmissions were unplanned. Unplanned readmission rate was 6.5% (31/472). Out of 31 unplanned readmission, 24 was related to the prior admission. Only 6 related readmission was avoidable. To determine risk factors for readmission we constructed Chi-square automatic interaction detector (CHAID) decision tree algorithm. CHAID decision trees are nonparametric procedures that make no assumptions of the underlying data. This algorithm determines how independent variables best combine to predict a binary outcome based on ‘if-then’ logic by portioning each independent variable into mutually exclusive subsets based on homogeneity of the data. Independent variables we included in the analysis were: clinic of the department, occupied beds/total number of beds in the clinic at the time of discharge, age, gender, marital status, educational level, distance to residence (km), number of people living with the patient, any person to help his/her care at home after discharge (yes/no), regular source (physician) of care (yes/no), day of discharge, length of stay, ICU utilization (yes/no), total comorbidity score, means for each 3 dimensions of Readiness for Hospital Discharge Scale (patient’s personal status, patient’s knowledge, and patient’s coping ability) and number of daycare admissions within 30 days of discharge. In the analysis, we included all 95 readmitted patients (46.12%), but only 111 (53.88%) non-readmitted patients, although we had 377 non-readmitted patients, to balance data. The risk factors for readmission were found as total comorbidity score, gender, patient’s coping ability, and patient’s knowledge. The strongest identifying factor for readmission was comorbidity score. If patients’ comorbidity score was higher than 1, the risk for readmission increased. The results of this study needs to be validated by other data–sets with more patients. However, we believe that this study will guide further studies of readmission and CHAID is a useful tool for identifying risk factors for readmission.

Keywords: decision tree, hospital, internal medicine, readmission

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Authors: Mary Wangari Kamau, Agatha Christine Atieno, Louise Wanjiku Ngugi

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Diabetes Mellitus Type 2 is a prevalent disease in Kenya, with complications often resulting from poor adherence to dietary guidelines. This study aims to identify and understand the factors influencing adherence to diet guidelines among patients with Diabetes Mellitus Type 2 at a specific clinic in Kenya. The findings will contribute to the improvement of nutrition care for diabetic patients. Research Aim: The main objective of this study was to determine the factors that influence adherence to dietary guidelines among patients with Diabetes Mellitus Type 2. Specifically, the study described the level of diet adherence, identified factors influencing adherence using the ecological approach, and determined the relationships among these factors. Methodology: A cross-sectional study design was utilized at the Cancer and Chronic Diseases Center at Moi Teaching and Referral Hospital in Kenya. The sample size consisted of 241 respondents from a target population of 412. Data was collected using food frequency questionnaires, three-day food records, and key informant interviews. Descriptive statistics were used to assess diet adherence, and chi-square and odds ratio tests were applied to identify factors at various levels of the ecological model. Multiple linear regression was employed to determine the relationship between diet adherence and ecological factors. Findings: The mean level of adherence to recommended dietary guidelines for Diabetes Mellitus Type 2 patients was 48.6%. Individual level factors, such as marital status, monthly income, duration of Diabetes Mellitus, frequency of monitoring blood sugar levels, treatment for Diabetes Mellitus, and BMI, were found to significantly influence diet adherence. However, cognitive and psychological factors at the individual level were not significantly associated with adherence. No significant associations were found between adherence and factors at small group, organizational or health care system, community, and policy levels. However, when considering all levels collectively, 43% of the variance in diet adherence could be explained. Theoretical Importance: This study highlights that while individual factors play a significant role in adherence to dietary guidelines, environmental factors also have an influence. The findings support the need for health professionals and policymakers to consider factors at multiple levels when improving adherence to dietary guidelines for diabetic patients. Data Collection and Analysis Procedures: Data was collected through questionnaires and interviews, including food frequency questionnaires and three-day food records. Descriptive statistics, chi-square tests, odds ratio tests, and multiple linear regression were used to analyze the data. Questions Addressed: The study addresses the following questions: 1. What is the level of adherence to dietary guidelines among patients with Diabetes Mellitus Type 2? 2. Which factors at individual, small group, organizational or health care system, community, and policy levels influence diet adherence? 3. What is the relationship between these factors and diet adherence? Conclusion: The study findings emphasize the need to consider both individual and environmental factors when promoting adherence to dietary guidelines among patients with Diabetes Mellitus Type 2. Health professionals and policymakers should incorporate factors at multiple levels to improve the nutrition care process for diabetic patients.

Keywords: adherence, dietary guidelines, ecological factors, type 2 diabetes mellitus

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Authors: Parth Gupta, Ujjawal Singh, Shashank Kumar, Mansi Chandra, Arnab Sarkar

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Microfluidic devices have emerged as indispensable tools across various scientific disciplines, offering precise control and manipulation of fluids at the microscale. Their efficacy in flow-based research, spanning engineering, chemistry, and biology, relies heavily on the geometric design of microfluidic channels. This work introduces a novel approach to optimise these channels through Response Surface Methodology (RSM), departing from the conventional practice of addressing one parameter at a time. Traditionally, optimising microfluidic channels involved isolated adjustments to individual parameters, limiting the comprehensive understanding of their combined effects. In contrast, our approach considers the simultaneous impact of multiple parameters, employing RSM to efficiently explore the complex design space. The outcome is an innovative microfluidic channel that consumes an optimal sample volume and minimises flow time, enhancing overall efficiency. The relevance of geometric parameter optimization in microfluidic channels extends significantly in biomedical engineering. The flow characteristics of porous materials within these channels depend on many factors, including fluid viscosity, environmental conditions (such as temperature and humidity), and specific design parameters like sample volume, channel width, channel length, and substrate porosity. This intricate interplay directly influences the performance and efficacy of microfluidic devices, which, if not optimized, can lead to increased costs and errors in disease testing and analysis. In the context of biomedical applications, the proposed approach addresses the critical need for precision in fluid flow. it mitigate manufacturing costs associated with trial-and-error methodologies by optimising multiple geometric parameters concurrently. The resulting microfluidic channels offer enhanced performance and contribute to a streamlined, cost-effective process for testing and analyzing diseases. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing.

Keywords: microfluidic device, minitab, statistical optimization, response surface methodology

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Mayantoinette F. Watson

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During such an unprecedented time of the largest public health crisis, the COVID-19 pandemic, nursing students are of the utmost concern regarding their psychological and physical well-being. Questions are emerging and circulating about what will happen to the nursing students and the long-term effects of the pandemic, especially now that hospitals are being overwhelmed with a significant need for nursing staff. Expectations, demands, change, and the fear of the unknown during this unprecedented time can only contribute to the many stressors that accompany nursing students through laborious clinical and didactic courses in nursing programs. The risk of psychological distress is at a maximum, and its effects can negatively impact not only nursing students but also nursing education and academia. The high exposures to interpersonal, economic, and academic demands contribute to the major health concerns, which include a potential risk for psychological distress. Achievement of educational success among nursing students is directly affected by the high exposure to anxiety and depression from experiences within the program. Working relationships and achieving academic success is imperative to positive student outcomes within the nursing program. The purpose of this study is to identify and establish influences and associations within multilevel factors, including the effects of the COVID-19 pandemic on psychological distress in nursing students. Neuman’s Systems Model Theory was used to determine nursing students’ responses to internal and external stressors. The research in this study utilized a mixed-methods, convergent study design. The study population included undergraduate nursing students from Southeastern U.S. The research surveyed a convenience sample of undergraduate nursing students. The quantitative survey was completed by 202 participants, and 11 participants participated in the qualitative follow-up interview surveys. Participants completed the Kessler Psychological Distress Scale (K6), the Perceived Stress Scale (PSS4), and the Dundee Readiness Educational Environment Scale (DREEM12) to measure psychological distress, perceived stress, and perceived educational environment. Participants also answered open-ended questions regarding their experience during the COVID-19 pandemic. Statistical tests, including bivariate analyses, multiple linear regression analyses, and binary logistics regression analyses were performed in effort to identify and highlight the effects of independent variables on the dependent variable, psychological distress. Coding and qualitative content analysis were performed to identify overarching themes within participants’ interviews. Quantitative data were sufficient in identifying correlations between psychological distress and multilevel factors of coping, marital status, COVID-19 stress, perceived stress, educational environment, and social support in nursing students. Qualitative data were sufficient in identifying common themes of students’ perceptions during COVID-19 and included online learning, workload, finances, experience, breaks, time, unknown, support, encouragement, unchanged, communication, and transmission. The findings are significant, specifically regarding contributing factors to nursing students’ psychological distress, which will help to improve learning in the academic environment.

Keywords: nursing education, nursing students, pandemic, psychological distress

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Authors: Wondale Getinet Alemu, Lillian Mwanri, Clemence Due, Telake Azale, Anna Ziersch

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Background: Mental illness is one of the most severe, chronic, and disabling public health problems that affect patients' Quality of life (QoL). Improving the QoL for people with mental illness is one of the most critical steps in stopping disease progression and avoiding complications of mental illness. Therefore, we aimed to assess the QoL and its determinants in patients with mental illness in outpatient clinics in Northwest Ethiopia in 2023. Methods: A facility-based cross-sectional study was conducted among people with mental illness in an outpatient clinic in Ethiopia. The sampling interval was decided by dividing the total number of study participants who had a follow-up appointment during the data collection period (2400) by the total sample size of 638, with the starting point selected by lottery method. The interviewer-administered WHOQOL BREF-26 tool was used to measure the QoL of people with mental illness. The domains and Health-Related Quality of Life (HRQoL) were identified. The indirect and direct effects of variables were calculated using structural equation modeling with SPSS-28 and Amos-28 software. A p-value of < 0.05 and a 95% CI were used to evaluate statistical significance. Results: A total of 636 (99.7%) participants responded and completed the WHOQOL-BREF questionnaire. The mean score of overall HRQoL of people with mental illness in the outpatient clinic was (49.6 ± 10 Sd). The highest QoL was found in the physical health domain (50.67 ±9.5 Sd), and the lowest mean QoL was found in the psychological health domain (48.41±10 Sd). Rural residents, drug nonadherence, suicidal ideation, not getting counseling, moderate or severe subjective severity, the family does not participate in patient care, and a family history of mental illness had an indirect negative effect on HRQoL. Alcohol use and psychological health domain had a direct positive effect on QoL. Furthermore, objective severity of illness, having low self-esteem, and having a history of mental illness in the family had both direct and indirect effects on QoL. Furthermore, sociodemographic factors (residence, educational status, marital status), social support-related factors (self-esteem, family not participating in patient care), substance use factors (alcohol use, tobacco use,) and clinical factors (objective and subjective severity of illness, not getting counseling, suicidal ideation, number of episodes, comorbid illness, family history of mental illness, poor drug adherence) directly and indirectly affected QoL. Conclusions: In this study, the QoL of people with mental illness was poor, with the psychological health domain being the most affected. Sociodemographic factors, social support-related factors, drug use factors, and clinical factors directly and indirectly, affect QoL through the mediator variables of physical health domains, psychological health domains, social relation health domains, and environmental health domains. In order to improve the QoL of people with mental illnesses, we recommend that emphasis be given to addressing the scourge of mental health, including the development of policy and practice drivers that address the above-identified factors.

Keywords: quality of life, mental wellbeing, mental illness, mental disorder, Ethiopia

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Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

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Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

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The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

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Authors: Tristance Kee

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With the unprecedented increase in elderly population globally, it is critical to search for new sustainable housing and urban development alternatives to traditional housing options. This research examines concepts of elderly migration pattern in the context of a high density city in Hong Kong to Mainland China. The research objectives are to: 1) explore the relationships between soon-to-be-old elderly and their intentions to move to Mainland upon retirement and their demographic characteristics; and 2) What are the desired amenities, locational factors and activities that are expected in the soon-to-be-old generation’s retirement housing environment? Primary data was collected through questionnaire survey conducted using random sampling method with respondents aged between 45-64 years old. The face-to-face survey was completed by 500 respondents. The survey was divided into four sections. The first section focused on respondent’s demographic information such as gender, age, education attainment, monthly income, housing tenure type and their visits to Mainland China. The second section focused on their retirement plans in terms of intended retirement age, prospective retirement funding and retirement housing options. The third section focused on the respondent’s attitudes toward retiring in Mainland for housing. It asked about their intentions to migrate retire into Mainland and incentives to retire in Hong Kong. The fourth section focused on respondent’s ideal housing environment including preferred housing amenities, desired living environment and retirement activities. The dependent variable in this study was ‘respondent’s consideration to move to Mainland China upon retirement’. Eight primary independent variables were integrated into the study to identify the correlations between them and retirement migration plan. The independent variables include: gender, age, marital status, monthly income, present housing tenure type, property ownership in Hong Kong, relationship with Mainland and the frequency of visiting Mainland China. In addition to the above independent variables, respondents were asked to indicate their retirement plans (retirement age, funding sources and retirement housing options), incentives to migrate to retire (choices included: property ownership, family relations, cost of living, living environment, medical facilities, government welfare benefits, etc.), perceived ideal retirement life qualities including desired amenities (sports, medical and leisure facilities etc.), desired locational qualities (green open space, convenient transport options and accessibility to urban settings etc.) and desired retirement activities (home-based leisure, elderly friendly sports, cultural activities, child care, social activities, etc.). The finding shows correlations between the used independent variables and consideration to migrate for housing options. The two independent variables indicated a possible correlation were gender and the frequency of visiting Mainland at present. When considering the increasing property prices across the border and strong social relationships, potential retirement migration is a very subjective decision that could vary from person to person. This research adds knowledge to housing research and migration study. Although the research is based in Mainland, most of the characteristics identified including better medical services, government welfare and sound urban amenities are shared qualities for all sustainable urban development and housing strategies.

Keywords: elderly migration, housing alternative, soon-to-be-old, sustainable environment

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Authors: Giuliana Murfet, Heidi Behrens

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Chronic disease is Australia’s biggest health concern and obesity the leading risk factor for many. Obesity and chronic disease have a higher representation in rural Tasmania, where levels of socio-disadvantage are also higher. People living outside major cities have less access to health services and poorer health outcomes. To help primary healthcare professionals manage obesity, the Australian NHMRC evidence-based clinical practice guidelines for management of overweight and obesity in adults were developed. They include recommendations for practice and models for obesity management. To our knowledge there has been no research conducted that investigates translation of these guidelines into practice in rural-regional areas; where implementation can be complicated by limited financial and staffing resources. Also, the systematic review that informed the guidelines revealed a lack of evidence for chronic disease models of obesity care. The aim was to establish and evaluate a multidisciplinary model for obesity management in a group of adult people with type 2 diabetes in a dispersed rural population in Australia. Extensive stakeholder engagement was undertaken to both garner support for an obesity clinic and develop a sustainable model of care. A comprehensive nurse practitioner-led outpatient model for obesity care was designed. Multidisciplinary obesity clinics for adults with type 2 diabetes including a dietitian, psychologist, physiotherapist and nurse practitioner were set up in the north-west of Tasmania at two geographically-rural towns. Implementation was underpinned by the NHMRC guidelines and recommendations focused on: assessment approaches; promotion of health benefits of weight loss; identification of relevant programs for individualising care; medication and bariatric surgery options for obesity management; and, the importance of long-term weight management. A clinical pathway for adult weight management is delivered by the multidisciplinary team with recognition of the impact of and adjustments needed for other comorbidities. The model allowed for intensification of intervention such as bariatric surgery according to recommendations, patient desires and suitability. A randomised controlled trial is ongoing, with the aim to evaluate standard care (diabetes-focused management) compared with an obesity-related approach with additional dietetic, physiotherapy, psychology and lifestyle advice. Key barriers and enablers to guideline implementation were identified that fall under the following themes: 1) health care delivery changes and the project framework development; 2) capacity and team-building; 3) stakeholder engagement; and, 4) the research project and partnerships. Engagement of not only local hospital but also state-wide health executives and surgical services committee were paramount to the success of the project. Staff training and collective development of the framework allowed for shared understanding. Staff capacity was increased with most taking on other activities (e.g., surgery coordination). Barriers were often related to differences of opinions in focus of the project; a desire to remain evidenced based (e.g., exercise prescription) without adjusting the model to allow for consideration of comorbidities. While barriers did exist and challenges overcome; the development of critical partnerships did enable the capacity for a potential model of obesity care for rural regional areas. Importantly, the findings contribute to the evidence base for models of diabetes and obesity care that coordinate limited resources.

Keywords: diabetes, interdisciplinary, model of care, obesity, rural regional

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Authors: Annis Lai Chu Fung

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While aggression had high stability throughout developmental stages and across generations, it should be the top priority of researchers and frontline helping professionals to develop prevention and intervention programme for aggressive children and children at risk of developing aggressive behaviours. Although there is a substantial amount of anti-bullying programmes, they gave disappointingly small effect sizes. The neglectful practical significance could be attributed to the overly simplistic categorisation of individuals involved as bullies or victims. In the past three decades, the distinction between reactive and proactive aggression has been well-proved. As children displaying reactively aggressive behaviours have distinct social-information processing pattern with those showing proactively aggressive behaviours, it is critical to identify the unique needs of the two subtypes accordingly when designing an intervention. The onset of reactive aggression and proactive aggression was observed at earliest in 4.4 and 6.8 years old respectively. Such findings called for a differential early intervention targeting these high-risk children. However, to the best of the author’s knowledge, the author was the first to establish an evidence-based intervention programme against reactive and proactive aggression. With the largest samples in the world, the author, in the past 10 years, explored three different approaches and their effectiveness against aggression quantitatively and qualitatively with longitudinal design. The three approaches presented are (a) cognitive-behavioral approach, (b) moral education, with Chinese marital arts and ethics as the medium, and (c) bioneurological measures (omega-3 supplementation). The studies adopted a multi-informant approach with repeated measures before and after the intervention, and follow-up assessment. Participants were recruited from primary and secondary schools in Hong Kong. In the cognitive-behavioral approach, 66 reactive aggressors and 63 proactive aggressors, aged from 11 to 17, were identified from 10,096 secondary-school children with questionnaire and subsequent structured interview. Participants underwent 10 group sessions specifically designed for each subtype of aggressor. Results revealed significant declines in aggression levels from the baseline to the follow-up assessment after 1 year. In moral education through the Chinese martial arts, 315 high-risk aggressive children, aged 6 to 12 years, were selected from 3,511 primary-school children and randomly assigned into four types of 10-session intervention group, namely martial-skills-only, martial-ethics-only, both martial-skills-and-ethics, and physical fitness (placebo). Results showed only the martial-skills-and-ethics group had a significant reduction in aggression after treatment and 6 months after treatment comparing with the placebo group. In the bioneurological approach, 218 children, aged from 8 to 17, were randomly assigned to the omega-3 supplement group and the placebo group. Results revealed that compared with the placebo group, the omega-3 supplement group had significant declines in aggression levels at the 6-month follow-up assessment. All three approaches were effective in reducing proactive and reactive aggression. Traditionally, intervention programmes against aggressive behaviour often adapted the cognitive and/or behavioural approach. However, cognitive-behavioural approach for children was recently challenged by its demanding requirement of cognitive ability. Traditional cognitive interventions may not be as beneficial to an older population as in young children. The present study offered an insightful perspective in aggression reduction measures.

Keywords: intervention, outcome effectiveness, proactive aggression, reactive aggression

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Authors: Kristina F. Wolff

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Background: In the Federal Republic of Germany, violence against women is deeply embedded in society. Germany is, as of March 2020, the most populous member state of the European Union with 83.2 million inhabitants and, although more than half of its inhabitants are women, gender equality was not certified in the Basic Law until 1957. Women have only been allowed to enter paid employment without their husband's consent since 1977 and have marital rape prosecuted only since 1997. While the lack of equality between men and women is named in the preamble of the Istanbul Convention as the cause of gender-specific, structural, traditional violence against women, Germany continues to sink on the latest Gender Equality Index. According to Police Crime Statistics (PCS), women are significantly more often victims of lethal violence, emanating from men than vice versa. The PCS, which, since 2015, also collects gender-specific data on violent crimes, is kept by the Federal Criminal Police Office, but without taking into account the relevant criteria for targeted prevention, such as the history of violence of the perpetrator/killer, weapon, motivation, etc.. Institutions such as EIGE or the World Health Organization have been asking Germany for years in vain for comparable data on violence against women in order to gain an overview or to develop cross-border synergies. The PCS are the only official data collection on violence against women. All players involved are depend on this data set, which is published only in November of the following year and is thus already completely outdated at the time of publication. In order to combat German femicides causally, purposefully and efficiently, evidence-based data was urgently needed. Methodology: Beginning in January 2019, a database was set up that now tracks more than 600 German femicides, broken down by more than 100 crime-related individual criteria, which in turn go far beyond the official PCS. These data are evaluated on the one hand by daily media research, and on the other hand by case-specific inquiries at the respective public prosecutor's offices and courts nationwide. This quantitative long-term study covers domestic violence as well as a variety of different types of gender-specific, lethal violence, including, for example, femicides committed by German citizens abroad. Additionallyalcohol/ narcotic and/or drug abuse, infanticides and the gender aspect in the judiciary are also considered. Results: Since November 2020, evidence-based data from a scientific survey have been available for the first time in Germany, supplementing the rudimentary picture of reality provided by PCS with a number of relevant parameters. The most important goal of the study is to identify "red flags" that enable general preventive awareness, that serve increasingly precise hazard assessment in acute hazard situations, and from which concrete instructions for action can be identified. Already at a very early stage of the study it could be proven that in more than half of all femicides with a sexual perpetrator/victim constellation there was an age difference of five years or more. Summary: Without reliable data and an understanding of the nature and extent, cause and effect, it is impossible to sustainably curb violence against girls and women, which increasingly often culminates in femicide. In Germany, valid data from a scientific survey has been available for the first time since November 2020, supplementing the rudimentary reality picture of the official and, to date, sole crime statistics with several relevant parameters. The basic research provides insights into geo-concentration, monthly peaks and the modus operandi of male violent excesses. A significant increase of child homicides in the course of femicides and/or child homicides as an instrument of violence against the mother could be proven as well as a danger of affected persons due to an age difference of five years and more. In view of the steadily increasing wave of violence against women, these study results are an eminent contribution to the preventive containment of German femicides.

Keywords: femicide, violence against women, gender specific data, rule Of law, Istanbul convention, gender equality, gender based violence

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