Degree Of Association Research Articles

A novel recommender framework with chatbot to stratify heart attack risk

Cardiovascular diseases are a major cause of mortality and morbidity. Fast detection of life-threatening emergency events and an earlier start of the therapy would save many lives and reduce successive disabilities. Understanding the specific risk factors associated with heart attack and the degree of association is crucial in the clinical diagnosis. Considering the potential benefits of intelligent models in healthcare, many researchers have developed a variety of machine learning (ML)-based models to identify patients at risk of a heart attack. However, the common problem of previous works that used ML concepts was the lack of transparency in black-box models, which makes it difficult to understand how the model made the prediction. In this study, an automated smart recommender system (Explainable Artificial Intelligence) for heart attack prediction and risk stratification was developed. For the purpose, the CatBoost classifier was applied as the initial step. Then, the SHAP (SHapley Additive exPlanation) explainable algorithm was employed to determine reasons behind high or low risk classification. The recommender system can provide insights into the reasoning behind the predictions, including group-based and patient-specific explanations. In the final step, we integrated a Large Language Model (LLM) called BioMistral for chatting functionally to talk to users based on the model output as a digital doctor for consultation. Our smart recommender system achieved high accuracy in predicting a patient risk level with an average AUC of 0.88 and can explain the results transparently. Moreover, a Django-based online application that uses patient data to update medical information about an individual’s heart attack risk was created. The LLM chatbot component would answer user questions about heart attacks and serve as a virtual companion on the route to heart health, our system also can locate nearby hospitals by applying Google Maps API and alert the users. The recommender system could improve patient management and lower heart attack risk while timely therapy aids in avoiding subsequent disabilities.

Can all roads lead to competency? School levels effects in Licensing examinations scores.

At the foundation of research concerned with professional training is the idea of an assumed causal chain between the policies and practices of education and the eventual behaviours of those that graduate these programs. In medicine, given the social accountability to ensure that teaching and learning gives way to a health human resource that is willing and able to provide the healthcare that patients and communities need, it is of critical importance to generate evidence regarding this causal relationship. One question that medical education scholars ask regularly is the degree to which the unique features of training programs and learning environments impact trainee achievement of the intended learning outcomes. To date, this evidence has been difficult to generate because data pertaining to learners is only rarely systematically brought together across institutions or periods of training. We describe new research which leverages an inter-institutional data-driven approach to investigate the influence of school-level factors on the licensing outcomes of medical students. Specifically, we bring together sociodemographic, admissions, and in-training assessment variables pertaining to medical trainee graduates at each of the six medical schools in Ontario, Canada into multilevel stepwise regression models that determine the degree of association between these variables and graduate performances on the Medical Council of Canada Qualifying Examinations (Part 1, n = 1097 observations; Part 2, n = 616 observations), established predictors of downstream physician performance. As part of this analysis, we include an anonymized school-level (School 1, School 2) independent variable in each of these models. Our results demonstrate that the largest variable associated with performance on both the first and second parts of the licensing examinations is prior academic achievement, notably clerkship performance. Ratings of biomedical knowledge were also significantly associated with the first examination, while clerkship OSCE scores and enrollment in a family medicine residency were significantly associated with the Part 2. Small significant school effects were realized in both models accounting for 4% and 2% of the variance realized in the first and second examinations, respectively. These findings highlight that school enrollment plays a minor role relative to individual student performance in influencing examination outcomes.

Reducing direct physical disturbance also mitigates hidden drivers of decline in a threatened seagrass meadow

Physical disturbances typically cause ecological impacts within areas of direct contact (primary disturbances) but can also impact surrounding areas through other mechanisms (secondary disturbances). Secondary disturbances are often overlooked, especially in marine ecosystems where sufficiently detailed observation can be difficult to obtain. For example, boat moorings create circular clearings in seagrass meadows by physically scouring the seabed, but visible impacts extend beyond this into surrounding areas due to disturbances such as increased sediment transport, edge effects, and shading from boats. Previous studies on impacts of moorings have not distinguished between primary and secondary disturbances, and secondary disturbances are rarely accounted for in environmental management. We used spatial modelling to examine the primary and secondary disturbances associated with moorings in a meadow of the threatened seagrass Posidonia australis. We compared the disturbance from traditional ‘swing’ moorings with ‘environmentally friendly’ moorings (EFM) designed to reduce scour. Within the scour zone (0-5 m from moorings), we compared seagrass cover around swing moorings with cover around EFM. Further from moorings (5-25 m), we tested the degree of association between seagrass cover and secondary disturbances that may accumulate with mooring density and be influenced by mooring design. We found that mooring design affected the degree of direct disturbance, with cover of P. australis in the scour zone of standard moorings ~49% lower than that of EFMs (p < 0.01). Mooring density had cumulative negative effects on P. australis cover in the surrounding meadow, but the influence of mooring density was reduced when most moorings were EFMs. This suggests that secondary effects contingent on direct physical disturbance (e.g. sediment transport, fragmentation, edge effects) may be stronger than the general influence of moored boats (shading). We use the findings to simulate two broad policy scenarios for mooring designs in P. australis meadows: installing only EFM, or only traditional moorings. The simulations suggest that using only EFM would lead to a 14.2% increase (~164 m2), whereas installing only traditional moorings would lead to a 16% (~187 m2) loss of P. australis cover in this already highly disturbed meadow. Synthesis and applications: We demonstrate a nondestructive approach to assessing primary and secondary disturbances driving the distribution of a threatened seagrass and simulate a range of potential management scenarios that could assist in conserving the species.

Respectful Maternity Care During Facility-Based Childbirth and Its Predictors in Public Health Facilities in Central Ethiopia: A Multidimensional Communication as a Proximal Predictor: A Cross-Sectional Study.

The provision of compassionate, respectful, and caring healthcare is an essential component of health workforces because it builds deep relationships between healthcare practitioners and mothers. However, respectful maternity care has received less attention in practice, and existing research is inconclusive as well. Therefore, this study is aimed to assess respectful maternity care and its predictors during childbirth in Siltie Zone, Ethiopia. We conducted a cross-sectional study on 374 mothers from May 1 to 30, 2021. A systematic random sampling technique was used to select the study participants. A structured questionnaire was used to collect the data. The data was entered into Epi Data 3.1, and the analysis was done using SPSS 24.0. Binary logistic regression was employed to identify candidate variables for multivariable logistic regression. In the multivariable analysis, variables having a p-value of less than 0.05 were taken as measures of the degree of association between independent variables and the outcome variable. The result of the study revealed that the overall prevalence of respectful maternal care is 41.0%. Rapport built through communication during antenatal care (AOR = 6.32, 95% CI: 2.81, 16.67), pre-communication of husband and wife (AOR = 2.45, 95% CI: 2.01, 13.69), clearly known communication of family with mother (AOR = 0.35, 95% CI: 0.11, 0.69), caring culturally and appropriately (AOR = 7.45, 95% CI: 2.88, 19.28), perceived length of the stay during labor (AOR = 1.36, 95% CI: 0.230, 0.551), number of ANC received (AOR = 1.98, 95% CI: 0.037, 0.260), and number of deliveries (AOR = 1.36, 95% CI: 0.230, 0.551) were independent predictors of the outcome variable. The study revealed that respectful maternity care was provided very low. Multidimensional communication with the mother was identified as a significant proximal predictor of respectful maternity care. The study suggests that stakeholders should improve respectful maternity care through the provision of professional health training and create guidelines to identify and address challenges to its practice.

FINANCIAL TURBULENCE AND RECOVERY IN STOCK MARKETS AMONG INDIA AND ITS MAJOR ASIA-PACIFIC COUNTERPARTS: AN ANALYTICAL STUDY DURING THE GLOBAL FINANCIAL CRISIS PERIOD AND POST-FINANCIAL CRISIS PERIOD

Understanding stock market correlations is essential for gauging financial integration, identifying risk diversification potential, and supporting investment management especially during economic downturns in a globally connected landscape. This paper presents a comprehensive correlation analysis among India (S&P BSE SENSEX) and ten prominent Asia-Pacific countries— China (SSE Composite), Israel (TA-125), Japan (Nikkei), Hong Kong (Hang Seng), Taiwan (TSEC), Indonesia (Jakarta Composite), South Korea (KOSPI), Australia (S&P/ASX 00), Singapore (FTSE), and Russia (MOEX Russia)—across two pivotal phases: the global financial crisis period, spanning from August 7, 2007, to April 16, 2009 and post-financial crisis period, from April 20, 2009, to December 30, 2019. Using a combination of descriptive statistics and correlation analysis on the calculated returns from daily adjusted market closing series of these indices, the study assesses the degree of association among the indices of India and the ten economies, with normality diagnostics guiding the selection of the appropriate correlation methodology. The normality tests indicate that none of the return series follow normal distribution and validate the use of the non-parametric Spearman Rank Correlation method. Results reveal persistently weak correlations among the S&P BSE SENSEX and other indices, suggesting scope for minimal co-movement across the indices in both periods. Although correlation among returns from Indian and ten Asia-Pacific indices grew from the crisis to the post-crisis period, no strong association emerged, showing only modest inter-market linkages in both intervals.

Nursing faculty perceptions of entry to nursing practice competencies expected at day one of hire: A statewide study

BackgroundNo universal nursing education framework exists aligning competency expectations of new-to-practice nurses graduating from the varying prelicensure academic degree programs. PurposeThis study aimed to identify a set of core competencies expected of all prelicensure nursing programs in Maryland, including associate degree (ADN), entry-level bachelor of science nursing degree (BSN), and master of science entry into nursing (MSN Entry) programs. MethodA mixed-method approach was used to identify necessary competencies, including a survey consisting of 109 outcome statements and a series of focus groups with faculty representatives from the prelicensure degree programs. FindingsUnexpected findings showed few differences between ADN, BSN, and MSN Entry nursing program faculty perceptions regarding their program graduates' ability to meet the expected competencies. Faculty were not surprised that few differences emerged. Barriers like overloaded curricula, the necessity of prioritizing teaching specific components of nursing content for NCLEX, and competing priorities were faculty concerns. ConclusionsA comprehensive examination of all BSN and MSN entry knowledge not included in the NCLEX-RN is suggested for students, nurse residents, and professional nurses, delineating entry-level and ongoing minimal core competencies expected of a competent professional nurse. Results support the development of a competency-based education framework to clearly communicate learning and performance expectations among the varying degree programs.

Effectiveness of Web-supported Videos on Students’ Academic Achievement, Critical Thinking Skills and Three-dimensional Learning

While traditional teaching methods such as face-to-face lectures, training, and mentoring have been utilised in the educational process, the importance of web-supported materials was better underscored with the advent of the pandemic. Documentary videos, prepared with scientific data, serve as significant web-supported materials. The aim of this research was to find out the effectiveness of web-supported videos on associate degree school students' academic achievement, critical thinking skills, and three-dimensional learning in science. The study employed a pre-post-test design, a type of quasi-experimental research, involving 42 associate degree school students enrolled in a child development programme. Data were collected using academic achievement tests, critical thinking skill tests, and three-dimensional learning scales, and analysed using non-parametric techniques. The two-month training revealed that web-supported videos contributed to the academic achievement and three-dimensional learning skills of students in understanding the concepts of the moon, sun, earth, and planets, though they did not have a significant effect on students' critical thinking skills.

A Model for Enhancing Workforce and Health System Resilience Against Natural and Human Crises

Background: Human resources are the most crucial asset of any organization, and by maintaining and strengthening them, organizational goals can be achieved. In the context of health systems, human resource resilience is primarily focused on the theoretical development of this concept and its various dimensions. Objectives: This study aimed to develop a model to enhance the resilience of human resources within the health system. Methods: This study used a mixed-methods approach, conducted in two stages. In the first stage, a scoping review of relevant literature was carried out across multiple databases (Scopus, ScienceDirect, PubMed, and Google Scholar) to identify dimensions and preliminary indicators for the model. A total of 20 studies that met the inclusion criteria were analyzed. Studies were included if they met two criteria: (a) the term "resilience" was used in the title, abstract, or keywords, and (b) the main analytical focus was on health systems. In the second stage, the initial model was designed using the fuzzy Delphi technique. The degree of association of each component and factor in the final model was assessed using the fuzzy DEMATEL method for the primary components and the interpretive structural modeling (ISM) technique for secondary components. Finally, the relationships between the indicators were determined based on the effectiveness and influence of the components. Results: Three key dimensions were identified in this study: (1) behavioral dimension (work experience, creativity, work commitment, and job design), (2) motivational dimension (in-service training, lifestyle changes, self-esteem, empathy, interaction with the surrounding environment, and continuous performance evaluation), and (3) empowerment dimension (employee welfare, rewards, job promotion, damage compensation, timely handling of complaints, and job security). Conclusions: To foster and sustain resilience in human resources, it is essential to address behavioral, empowerment, and motivational dimensions within the health sector. Managers should consider the dimensions and indicators proposed in this model to improve workforce resilience.

University Technological Entrepreneurship Projects: Factors of Success

The paper presents the results of an empirical analysis of the success factors in university technological entrepreneurial projects, based on a unique empirical dataset created with the support of the project office and the office for promoting the federal project «University Technological Entrepreneurship Platform». The dataset includes a ranking of over 1,000 university projects from 2023, each of which contains information on approximately 35 characteristics, both financial and non-financial. The success indicators selected for analysis are the «final ranking position» and «investment attractiveness of the project». Statistical methods, implemented through Python libraries, were used to examine the relationships between different forms of project support and the aforementioned characteristics. The results highlight the critical role of the university environment in supporting entrepreneurial projects, while also revealing that specific support measures can exhibit varying degrees of association with project success. Two key findings are noteworthy. First, there is no positive correlation between the project’s strong embeddedness in the university environment (e.g., a team assembled within the university or a project initially started as an academic exercise) and the project’s success. Second, among the support measures implemented within the current federal project «University Technological Entrepreneurship Platform», the strongest association with the success of entrepreneurial initiatives is found in participation in startup studios. Considering contemporary discussions on the need to seek new solutions to enhance the educational and life experiences of modern students, bringing them closer to the realities of a dynamically changing labor market, the university startup studio model may serve as a source for developing new models of university organization.

Depression and anxiety in primary care patients with hemodialysis

Depression and anxiety affect with persistent sadness, low mood, fear and loss of interest in daily activities. Therefore, it is important to consider hemodialysis patients with psychological disorders in primary care. To analyze the presence of depression and anxiety with the Beck inventory in patients with hemodialysis in the Family Medicine Unit No. 1. A cross-sectional, analytical study was carried out with a type of convenience sampling. based on the inclusion criteria all patients on hemodialysis morning-afternoon shift and excluding all who do not wish to participate or intellectual disability, sample of 53 patients. Beck's anxiety and depression inventory instrument was applied, and the Pearson correlation coefficient was used to assess the degree of association. The sex with the greatest presence was male (57%) and the age range is 40-46 years with 22.6%, the relationship of patients with end-stage renal disease (ESRD) presented mild anxiety/depression, while patients with moderate anxiety presented intermittent depression, the level of anxiety was positively correlated with depression and anxiety (p = 0.877). ESRD decreases functional capacity, generating psychological disorders such as depression and anxiety, which is why joint management with psychology or psychiatry must be carried out.

Chemosensory vocabulary in wine, perfume and food product reviews: Insights from language modeling

Chemosensory sensations are often hard to describe and quantify. Language models may facilitate a systematic understanding of sensory descriptions. We accessed consumer and expert reviews of wine, perfume, and food products (English language; about 68 million words in total) and analyzed their sensory descriptions. Using a novel data-driven method based on natural language data, we compared the three chemosensory vocabularies (wine, perfume, food) with respect to their vocabulary overlap and semantic properties, and explored their semantic spaces. The three vocabularies primarily differ with respect to domain specificity, concreteness, descriptor type preference and degree of gustatory vs. olfactory association. Wine vocabulary primarily distinguishes between white wine and red wine flavors and qualities. Food vocabulary separates drinkable and edible food products and ingredients, on the one hand, and savory and non-savory products, on the other. A salient distinction in all three vocabularies is between concrete and abstract/evaluative terms. Valence also plays a role in the semantic spaces of all three vocabularies, but valence is less prominent here than ingeneral olfactory vocabulary. Our method allows a systematic comparison of sensory descriptors in the three product domains and provides a data-driven approach to derive sensory lexicons that can be applied by sensory scientists.

Automatic Experimental Numerosity Generation and Numerical Training for Rodents.

Non-symbolic stimuli representing numerosities are invariably associated with continuous magnitudes, complicating the interpretation of experimental studies on numerosity perception. Although various algorithms for experimental numerosity generation have been proposed, they do not consider the quantifiable distribution of values of continuous magnitudes and the degree of numerosity-magnitudes association. Consequently, they cannot thoroughly exclude the possibility of magnitudes integration or strategy switch between different magnitudes in numerical stimulus perception. Here, we introduce a protocol for numerosity generation, animal training, and behavior outcomes analysis that takes the aforementioned issues into consideration. This protocol has been applied to rodents and is applicable to other animals in numerosity studies. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Algorithm for generating non-symbolic numerical stimuli Alternate Protocol: General algorithm for generating non-symbolic numerical stimuli Basic Protocol 2: Numerical training and testing for rodents.

Overview of the education system for dental technicians in Taiwan

Background/purposeCurrently, the education and examination system for dental technicians in Taiwan is gradually maturing. This study primarily explored the overview of the Taiwan's dental technology education system and the student numbers from 2017 to 2023. Materials and methodsThis study employed the literature and secondary data analysis to investigate the development of the Taiwan's dental technology education system from 2017 to 2023 and the changes in the number of dental technology students. ResultsCurrently, Taiwan had five dental technology schools offering the associate, bachelor's, and master's degrees in the dental technology. The enrollment quotas for the dental technology students determined by the Ministry of Education was reduced from 400 students in 2017 to 387 students in 2023. The number of dental technology students with the official enrollment decreased from 2196 in 2017 to 1720 in 2023 with a reduction rate of 21.68 %. Comparing the distribution of the officially enrolled dental technology students in 2023 by the gender, school location, and academic program showed significant differences (P < 0.001). Overall, the 46 dental technology-related programs had produced a total of 3330 dental technology graduates (1354 male graduates and 1488 female graduates) over the past seven years. ConclusionThe dental technicians, who are primarily responsible for the fabrication and maintenance of the dental prostheses, play an indispensable role in the dental healthcare. However, the number of dental technology students decrease year by year. Therefore, attracting more students to join the dental technology education is a great challenge in Taiwan.

Women’s Empowerment and Son Preference: The Case of India

The purpose of this article is to explore the changing patterns of women’s empowerment and son preference at the Indian sub-national level. We have measured the state-level degree of women’s empowerment and son preference for two different periods, that is, 2015–2016 and 2019–2020 using the fourth and fifth rounds state-level National Family Health Survey data. The sample of the study consists of women who can potentially have son preference. The study has examined whether the mean level of women’s empowerment and son preference has changed significantly between the two concerned time periods. The categorisation and cluster analysis of the states is done based on the degree of women’s empowerment and son preference. To explore the degree of association between son preference and women’s empowerment and its indicators, a correlation matrix is formed. No significant increase in the mean level of son preference is found whereas the average value of the degree of women’s empowerment increased significantly in 2019–2020 compared to 2015–2016. Further, the states categorised as having comparatively strong women’s empowerment do not necessarily have a comparatively low level of son preference. No significant association between women’s empowerment and son preference is explored through the correlation matrix as well. Thus, the study leads to the conclusion that son preference in India has no significant association with women’s empowerment.

An Enhanced Affective Computing Technology for Fostering an Emotionally Healthy Workplace

The mental health of workers is of paramount importance in today’s fast-paced and demanding workplaces. This research establishes a strong connection between affective decision-making and mental health, presenting a novel method to improve affective computing technologies for developing emotionally healthy workplaces. We use Multinomial Naive Bayes Integrated Gated Recurrent Units (MNB-GRU) for classification and prediction to reach our goals. This dataset includes many measures of mental health, working climate, and individual variables. Data Exploration is performed to learn more about the properties of the dataset, and Preprocessing Grouping is used to get the data ready for analysis. Relationships between emotional decisionmaking and mental health markers are shown using data visualization approaches to give intuitive insights. To evaluate the reliability of the connection, a correlation analysis is used in Model Assessment. Understanding how people are feeling emotionally at work can be gained via this assessment, which examines the degree of association between affective decision-making and mental health. As a result of using categorization methods to divide the workforce into several categories based on their emotional well-being, we can better assist businesses in meeting the varying demands of their staff members. This method guarantees that efforts to improve mental health are focused and productive. By creating a solid connection between effective decisionmaking and mental health, businesses can take preventative measures to aid their workers' emotional well-being and create a more upbeat and productive workplace.

Scale of self-perceived listening, empathy, and presence (LEP) abilities in associate degree nursing students for aging care

This cross-sectional study involved 341 fifth-year associate degree nursing students who completed an online questionnaire survey from May 1 to July 31, 2020. Out of these, 196 effective responses were received, with participants' ages ranging from 19 to 29 years. Most were female, the eldest in their families, and had experience living with grandparents. They had also completed long-term care or elderly nursing courses, and had experience in practicing, volunteering, and caring for elders. The average scores for all listening and empathy items were above 4.0. The LEP self-perception abilities scale demonstrated expert content validity with a score of .94 and an internal consistency Cronbach's α of .96. Construct validity was confirmed with factor loadings ranging from .73 to .92, explaining 67.03% of the variance, indicating strong construct validity.

Development of Targeted Safety Hazard Management Plans Utilizing Multidimensional Association Rule Mining

Investigating hidden hazards and implementing closed-loop management are essential strategies for accident prevention in the mining industry. This study tackles a key challenge in applying association rule mining to the development of hazard management plans for underground mines. The current approach mainly focuses on hazard description data, often underutilizing critical information such as hazard time and location. To address this, we integrate topic mining with association rule mining to uncover intrinsic association patterns among various attributes of mine safety hazards. Through a systematic analysis of standardized mining hazard attributes, five key analytical dimensions were identified: Hazard Type, Level, Time, Location, and Responsible Units. A topic mining model, utilizing the Biterm Topic Model, was constructed to reduce dimensionality and aggregate hazard description data. Evaluation indicators such as Standard Lift and Difference Degree were proposed, resulting in a multidimensional association rule mining model for mining safety hazards. In this research, 1,387 valid rules were extracted based on hazard inspection data from an underground gold mine in China. The analysis revealed relatively strong associations between hazard location and hazard type, responsible unit, as well as hazard level, with association degrees of 1.934, 1.412, and 1.240, respectively. Additionally, 15 rules with a high degree of differentiation were identified to explore interesting correlations among different attributes. Based on this, corresponding control measures and improvement plans were developed for 19 locations. The results demonstrate that a multidimensional partition-based association rule mining approach for mining safety hazards can significantly enhance the specificity of safety training and improve the efficiency of safety hazard investigation.

INTERCULTURAL COMMUNICATION COMPETENCE OF HEALTHCARE PROFESSIONALS CARING FOR PATIENTS FROM DIVERSE CULTURES

This research aims to examine the intercultural communication competence of healthcare professionals providing care and treatment to patients from different cultures. It evaluates the impact of intercultural communication on the quality and effectiveness of healthcare services. Method: The research was conducted with the participation of 280 healthcare professionals working at Alanya Alaaddin Keykubat University Hospital. Data were collected using the Intercultural Sensitivity, Intercultural Effectiveness, and Intercultural Awareness scales. Data analysis was performed using SPSS 25.0, and non-parametric tests were used for data that did not follow a normal distribution. Findings: Of the participants, 67.8% were female, 74.7% were under 25 years old, and 81.6% were single. In terms of education, 36.8% had an associate degree, and 44.8% had a bachelor's degree. The effects of demographic variables such as gender, marital status, and work department on intercultural competence were examined. Women scored higher than men in the Identity Protection sub-dimension, while married individuals scored lower than singles in the Cultural Communication Awareness sub-dimension. Paramedics had higher intercultural effectiveness scores compared to nurses. Discussion: The duration of experience significantly affected the Comfort in Communication sub-dimension. Higher education levels were associated with increased intercultural sensitivity and effectiveness scores. Those who received intercultural patient care training had higher scores, and those willing to work with patients from different cultures had higher intercultural sensitivity and effectiveness scores. Conclusion: These findings emphasize the importance of intercultural training and development programs to improve the quality of healthcare services. Enhancing healthcare professionals' intercultural communication skills is crucial for increasing patient satisfaction and the effectiveness of healthcare services.

THE EFFECT OF HEALTHY LIFE STYLE BEHAVIOR ON PSYCHOLOGICAL RESILIENCE OF ASSOCIATE DEGREE STUDENTS RECEIVING HEALTH EDUCATION AFTER EARTHQUAKE

It was aimed to examine the effect of healthy lifestyle behavior on psychological resilience of associate degree students receiving health education after the earthquake. In line with the aim of the study, 428 people, who were determined by convenience sampling method among the students continuing their education and training at the university, constitute the sample of the study and the data were collected by applying an online questionnaire. In the study, "Personal Information Form", "Healthy Lifestyle Behavior Scale II" and "Brief Psychological Resilience Scale" were used. The data were analyzed with SPSS program. In addition, Pearson correlation and regression analyses were applied upon the determination that the data were normally distributed as an analysis method. As a result of the study, it was determined that there was a positive and significant relationship between healthy lifestyle behavior and its sub-dimensions and psychological resilience. In addition, it was determined that healthy lifestyle behavior has a positive and significant effect on psychological resilience. It is predicted that increasing the healthy lifestyle behavior of students after the earthquake will increase their psychological resilience against the disaster in a positive way.

Empowering Community College Students’ Geospatial Education Through Virtual Practical Training

Practical training is important for community college students to gain high-impact real-world experience. This study aims to evaluate the impact of practical training of remote internships of community college and two-year associate degree students on spatiotemporal GIS learning during the pandemic. Anonymous pre- and post-internship surveys and in-person focus groups were conducted, ensuring the collection of quantitative and qualitative data. Outcomes reveal discernible enhancements across all skill domains, encompassing technical proficiencies and soft skills such as research, presentation, and time management. Findings provide valuable insights for refining the efficacy of similar internship programs.