Effect of the Strategic Thinking, Problem Solving Skills, and Grit on the Disaster Triage Ability of Emergency Room Nurses

In this descriptive study, we aimed to identify factors related to emergency room nurses’ disaster triage ability. A total of 166 nurses who worked for emergency departments of general hospitals completed a structured questionnaire consisting of the Disaster Triage Ability Scale (DTAS), the Strategic Thinking Scale (STS), the Problem-Solving Inventory (PSI), and the Original Grit Scale (Grit-O). The data were analyzed using SPSS/WIN 25.0 by means of descriptive statistics, t-test, one-way ANOVA, the Scheffé post hoc test, Pearson’s correlation coefficients, and stepwise multiple regression. Participants’ DTAS averaged 14.03 ± 4.28 (Range 0–20) and showed a statistically significant difference according to their experience of triage education (t = 2.26, p = 0.022) as a disaster triage-related attribute. There were significant correlations among DTAS and confidence in the PSI (r = 0.30, p < 0.001), the approach-avoidance style in the PSI (r = −0.28, p < 0.001), and futurism in the STS (r = 0.19, p = 0.019). The strongest predictor was confidence in the PSI; in addition, 14.1% of the DTAS was explained by confidence in the PSI, approach-avoidance in the PSI, and futurism in the STS. Emergency room nurses who received triage education showed a higher level of the DTAS and their DTAS could be explained by problem-solving skills and strategic thinking. Therefore, it is necessary to develop and implement triage education programs integrated with stress management to improve the approach-avoidance style to ensure better problem-solving skills and to utilize various training methods to enhance confidence to improve problem-solving skills and futurism as part of strategic thinking.

Satisfaction Factors That Predict Loyalty in Ecotourism: A Study of Foreign Tourism in Costa Rica

Recently, foreign tourists have revealed a growing interest for natural environment enjoyment. This study aimed to: (a) identify the service satisfaction factors and (b) analyze the influence that satisfaction factors exert on the loyalty of ecotourists. The empirical analysis was carried out in Arenal National Park and Caño Negro Wildlife Refuge in Costa Rica, a country with international prominence in ecotourism due to the wealth of resources in its protected areas. A factorial analysis and the stepwise multiple regression method were performed for the data analysis of 246 surveys made in situ. Results show three satisfaction factors in ecotourism: “nature and culture”, “infrastructure”, and “service”, where “nature and culture” was the most influential predictor of tourists’ loyalty. The study also found a positive correlation between satisfaction and loyalty in ecotourism. This research will provide relevant insights to public institutions and private companies efficient planning and benefit the community and protected areas.

Large household reduces dementia mortality.

Background Large households/families create more positive psychological well-being which may offer a life course protection against dementia development and deliver more comprehensive healthcare to dementia patients. Methods Dementia specific mortality rates of the 183 member states of World Health Organization were calculated and matched with the respective country data on household size, Gross Domestic Product (GDP), urban and ageing. Scatter plots were produced to explore and visualize the correlations between household size and dementia mortality rates. Pearsons and nonparametric correlations were used to evaluate the strength and direction of the associations between household size and all other variables. Partial correlation of Pearsons moment-product approach was used to identify that household size protects against dementia regardless of the competing effects from ageing, GDP and urbanization. Multiple regression identified large household was a significant predictor of dementia mortality. Results Household size was in a negative and moderately strong correlation (r = -0.6034, p < 0.001) with dementia mortality. This relationship was confirmed in both Pearson r (r= - 0.524, p<0.001) and nonparametric (rho = -0.579, p < 0.001) analyses. Regardless of the contribution of ageing, SES and urban lifestyle to dementia mortality, large household was an independent predictor of dementia mortality (r = −0.331, p <0.001) in partial correlation analysis. Stepwise multiple regression analysis selected large household as the variable having the greatest contribution to dementia mortality with R2 = 0.263 while ageing was placed second increasing R2 to 0.259. GDP and urbanization were removed as having no statistically significant influence on dementia mortality. Conclusions Independent of ageing, urbanization and GDP, large household protects against dementia mortality. As part of dementia prevention, healthcare practitioners should encourage people to increase their positive interactions with persons from their neighbourhood or other fields where large household/family size is hard to achieve.

Estimating Forest Aboveground Biomass Using Gaofen-1 Images, Sentinel-1 Images, and Machine Learning Algorithms: A Case Study of the Dabie Mountain Region, China

Quantitatively mapping forest aboveground biomass (AGB) is of great significance for the study of terrestrial carbon storage and global carbon cycles, and remote sensing-based data are a valuable source of estimating forest AGB. In this study, we evaluated the potential of machine learning algorithms (MLAs) by integrating Gaofen-1 (GF1) images, Sentinel-1 (S1) images, and topographic data for AGB estimation in the Dabie Mountain region, China. Variables extracted from GF1 and S1 images and digital elevation model data from sample plots were used to explain the field AGB value variations. The prediction capability of stepwise multiple regression and three MLAs, i.e., support vector machine (SVM), random forest (RF), and backpropagation neural network were compared. The results showed that the RF model achieved the highest prediction accuracy (R2 = 0.70, RMSE = 16.26 t/ha), followed by the SVM model (R2 = 0.66, RMSE = 18.03 t/ha) for the testing datasets. Some variables extracted from the GF1 images (e.g., normalized differential vegetation index, band 1-blue, the mean texture feature of band 3-red with windows of 3 × 3), S1 images (e.g., vertical transmit-horizontal receive and vertical transmit-vertical receive backscatter coefficient), and altitude had strong correlations with field AGB values (p < 0.01). Among the explanatory variables in MLAs, variables extracted from GF1 made a greater contribution to estimating forest AGB than those derived from S1 images. These results indicate the potential of the RF model for evaluating forest AGB by combining GF1 and S1, and that it could provide a reference for biomass estimation using multi-source images.

Effect of Knowledge on COVID-19 and Hygiene Behavior on the Mental Health of Cosmetology Students

Purpose: This study aimed to confirm the knowledge on COVID-19 and hygiene behavior of cosmetology students and identify factors affecting mental health.Methods: In the analysis, SPSS/WIN program was used. Univariate analysis was used for knowledge COVID-19, preventive behavior, and mental health, and stepwise multiple regression was used for factors affecting mental health.Results: The factors affecting the mental health of cosmetology students were identified as knowledge related to COVID-19, subjective health perception, and part-time job.Conclusion: In this study, 34.9% and 36.2% of the borderline and severe groups of anxiety and depression respectively, which are subfactors of the mental health of cosmetology students, were identified. In future studies, it is considered necessary to expand sample and the influencing factors.

The Influence of Leadership Behaviour on Organizational Culture Among the Academic Deans of State Universities and Colleges (SUCs) in Panay Island, Philippines

This study aimed to determine the influence of leadership behaviour on organizational culture among the academic deans of state universities and colleges (SUCs) in Panay Island, Philippines. The 125 purposively selected academic deans who responded during the conduct of the study were the respondents of this investigation. Two (2) adapted research instruments were utilised to gather data, accompanied by an information sheet. Frequency counts, percentages, means, and standard deviations were used for descriptive analysis, while the Pearson Product Moment Correlation Coefficient and Stepwise Multiple Regression Analysis set at 0.05 alpha level were employed for inferential analysis. The results of the study showed that the respondents possessed very high levels of "pioneering/visionary", "team facilitation", and "encouraging/coaching" leadership behaviours, while also possessing high levels of leadership behaviours in being "strategic", "management/administrative", and "relational/social". The respondents had a very great extent of the practice of organizational culture in all the four organizational culture traits. According to the findings, there were positive, significant correlations between each type of leadership behaviour and organizational culture. Furthermore, "management/administrative" and "encouraging/coaching" leadership behaviours significantly impact organizational culture. In conclusion, academic deans should encourage "management/administrative" and "encouraging/coaching" behaviours in themselves as well as their constituents to strengthen and enhance the extent of the practice of organizational culture in the institution. These appear to be powerful mechanisms for the organization to rapidly adapt to changing institutional demands, remain competitive, and maintain high levels of performance and effectiveness.

Explaining Neighbourhood Variations in the Incidence of Dengue Fever in Jeddah City, Saudi Arabia

The rapid growth and development of cities is a contributing factor to the rise and persistence of dengue fever (DF) in many areas around the world. Many studies have examined how neighbourhood environmental conditions contribute to dengue fever and its spread, but have not paid enough attention to links between socio-economic conditions and other factors, including population composition, population density, the presence of migrant groups, and neighbourhood environmental conditions. This study examines DF and its distribution across 56 neighbourhoods of Jeddah City, Saudi Arabia, where the incidence of dengue remains high. Using stepwise multiple regression analysis it focuses on the key ecological correlates of DF from 2006-2009, the years of the initial outbreak. Neighbourhood variations in average case rates per 10,000 population (2006–2009) were largely predicted by the Saudi gender ratio and socio-economic status (SES), the respective beta coefficients being 0.56 and 0.32 (p < 0.001). Overall, 77.1% of cases occurred in the poorest neighbourhoods. SES effects, however, are complex and were partly mediated by neighbourhood population density and the presence of migrant groups. SES effects persisted after controls for both factors, suggesting the effect of other structural factors and reflecting a lack of DF awareness and the lack of vector control strategies in poorer neighbourhoods. Neighbourhood environmental conditions, as measured by the presence of surface water, were not significant. It is suggested that future research pay more attention to the different pathways that link neighbourhood social status to dengue and wider health outcomes.

STRUCTURAL FEATURE STUDY OF QUINOLINES DERIVATIVES WITH THERMODYNAMIC AND OTHER DESCRIPTORS: A QSAR APPROACH

Quantitative structure activity relationship analysis was performed on a series of thirty-three quinoline derivatives to establish the structural features required for angiotensin II receptor activity. QSAR models were derived by stepwise multiple regression analysis employing the method of least squares, using quantum chemical, thermodynamic, electronic and steric descriptors. Model showed best predictability of activity with cross validated value (q2 ) =0.7485, coeffi cient of determination (r2 ) =0.8734 and standard error of estimate (s) = 0.2690. These guidelines may be used to develop new antihypertensive agents based on the quinoline analogues scaffold.

Does Predicted Age At Peak Height Velocity Explain Physical Performance In U13-15 Basketball Female Players?

Background: The aims of the study were (i) to identify the physical fitness and basic anthropometric characteristics of Polish female basketball players aged 13 to 15 years, (ii) to show the effect of maturity timing on the performance in motor tests and basic body composition parameters, (iii) to identify the index that contributes most to the prediction of performance in the tests of speed, jumping ability, agility, and endurance. Methods: The sample included 925 female Polish players (U13-15). In part 1, maturity timing category distribution were examined within across age-groups. In part 2, the relationship between the anthropometric variables, physical fitness performance was assessed based on maturity timing categories (ANCOVA analysis). In part 3, backward stepwise multiple regression analyse quantified the relationship between maturity timing (group of PHV) and physical performance.Results: ANCOVA results (age, body height, and body mass as covariates) showed in the U13 female basketball players significantly higher sprinting (20m), jumping ability and endurance tests results of the PHV1 group.Better results was observed in U14 female players in PHV1 compared to PHV2 and PHV3 in 20m and jumping tests but opposite trend was observed for 5m sprint and endurance test (distance covered and VO2max). U15 basketball players from the PHV3 group were characterized by better results of jumping abilities, endurance, 10m and 20m sprint and agility (total, S4) tests. Maturity timing (10m), chronological age (5 m, 20 m, agility, SVJ, VJ, and VO2max tests), body height (10m), body mass (10m, 20m, VJ, VO2max), and the interaction between body mass and height (SVJ) were significant (adjusted R2 = 0.02-0.10; p < 0.001) predictors of motor skills. Conclusion: The results can help the coaches to personalize training programs and to adapt the training content to the biological age of the players.

Premenopausal Bilateral Oophorectomy Effects on Clinical and Real-World Physical Function Measures

Women with premenopausal bilateral oophorectomy (PBO) are at increased risk for physical function (PF) declines. This study investigated the relationships of field-based physical activity measures with clinical PF and strength parameters in post-menopausal women with and without PBO. Women with (n=21; age=64±4 years; BMI=32±8 kg.m-2) and without (n=15; age=67±6 years; BMI=28±6 kg.m-2) PBO performed PF and strength tests (walking speed, distance walked, short physical performance battery (SPBB), leg and chest strength), and wore ankle accelerometers for 7 days (daily step count and loading index [the cumulative sum of each step’s skeletal loading]). Age, BMI, step count and loading index were entered into stepwise multiple regression to identify significant predictors of PF and strength parameters. Step count was a predictor of SPBB score in both groups. In women without PBO, step count was a predictor of walking speed; loading index was a predictor of leg strength; step count and loading index were predictors of distance; and step count and age were predictors of chest strength. For PBO women, loading index and BMI were predictors of walking speed and distance; BMI was a predictor of leg strength; and there were no predictors of chest strength. These data suggest while field-based physical activity was strongly and positively associated with clinical PF and strength measures for women without PBO, BMI was a dominant negative factor for PF in women with PBO. Future work will include a larger sample size and additional confounders to further elucidate underlying factors of reduced PF and mobility after PBO.