Search Results (9)

There is no doubt that leadership is one of the most researched and disseminated topics in recent years, and over time, some distinguished models have developed a solid foundation and a reputable structure. From this perspective, this study analyzes the evidence of validity and reliability of a scale that assesses leadership styles in non-profit institutions. The study had an instrumental design. The sample consisted of 272 workers from nine Latin American countries, aged between 19 and 68 years (M = 34.08 and SD = 8.61), recruited through non-probabilistic sampling. A validity and reliability analysis of the scale confirmed the nine items and three original factors (servant, empowering and shared leadership). The KMO test reached a high level (0.898 > 0.70), and the Bartlett test reached a highly significant level (Sig. = 0.000). The scale also showed good internal consistency (α = 0.918 to 0.956; CR = 0.918 to 0.957; AVE = 0.755 to 0.880). Likewise, for the Confirmatory Factor Analysis, a measurement adjustment was performed, obtaining excellent and acceptable fit indices for Model 2 (CMIN/DF = 1.794; CFI = 0.993; SRMR = 0.023; RMSEA = 0.054; Pclose = 0.369). This study provides a brief and useful tool to measure leadership styles in Latin America, as a scale used specifically for this context would allow for a more accurate and valid assessment. This is crucial for generating effective organizational interventions, fostering the development of authentic leaders, and improving the competitiveness of non-profit institutions. Full article

Due to the current and predicted increase in the global demand for water–energy–food (WEF) resources, as well as the inevitable linkages between the WEF sectors and sustainable development, the WEF nexus is rapidly being recognized as a method to effectively manage sustainable development. Many African countries still face challenges in terms of the demand for and accessibility of WEF resources. For this reason, a comparative study of two sites (Narok County and Vhembe District Municipality), which exhibit similar socio-economic, environmental, and technological circumstances, was undertaken. In the present study, we considered 218 questionnaire responses, which we analyzed using partial least squares structural equation modeling (SEM) based on the WEF nexus constructs. This study is anchored on the null hypothesis (H0), whereby no interdependencies exist between the state of the climate and WEF resources, as constrained by sustainable development options. The results show that the proposed hypothesis does not hold, but rather, an alternative hypothesis (Ha)—there exist linkages between climate change and WEF resources—holds. This is demonstrated by the descriptive statistics indicating p values < 0.05 for both the t-test and the Bartlett test. Furthermore, analysis from the multi-regression, particularly for the model where we combined the sites, showed p values < 0.05 and higher adjusted r-squared values, which denoted a better fit. The communities in both study sites agree that the regions have experienced a scarcity of WEF resources due to climate change. The results show that climate change is an intrinsic part of the developmental options for the sustainable livelihood of both study sites, which aligns with the 2030 UN agenda on sustainable development goals targets. Moreover, the sustainable management of natural resources that are people- and planet-centric is crucial to climate change adaptation and mitigation, social justice, equity, and inclusion. The SEM results showed with significant confidence that the water, energy, and food sectors are closely interconnected; however, their impact on climate and sustainability is significantly different. Food has a direct positive impact on climate and sustainability, while both water and energy have an indirect negative impact. Moreover, the climate construct indicated a significant direct link to sustainability for all the relationships explored. This is particularly true because, in most underdeveloped countries, sustainable development and societal wellbeing heavily rely on goods and services derived from natural resources and the environment. This study contributes to the nexus modeling research field by introducing SEM as an innovative methodology over a single equation modeling framework in analyzing variables that have complex interrelationships, facilitating advanced WEF nexus resource governance. Full article

Unmanned aerial vehicles (UAVs) are now widely preferred systems that are capable of rapid mapping and generating topographic models with relatively high positional accuracy. Since the integrated GNSS receivers of UAVs do not allow for sufficiently accurate outcomes either horizontally or vertically, a conventional method is to use ground control points (GCPs) to perform bundle block adjustment (BBA) of the outcomes. Since the number of GCPs to be installed limits the process in UAV operations, there is an important research question whether the precise point positioning (PPP) method can be an alternative when the real-time kinematic (RTK), network RTK, and post-process kinematic (PPK) techniques cannot be used to measure GCPs. This study introduces a novel approach using precise point positioning with ambiguity resolution (PPP-AR) for ground control point (GCP) positioning in UAV photogrammetry. For this purpose, the results are evaluated by comparing the horizontal and vertical coordinates obtained from the 24 h GNSS sessions of six calibration pillars in the field and the horizontal length differences obtained by electronic distance measurement (EDM). Bartlett’s test is applied to statistically determine the accuracy of the results. The results indicate that the coordinates obtained from a two-hour PPP-AR session show no significant difference from those acquired in a 30 min session, demonstrating PPP-AR to be a viable alternative for GCP positioning. Therefore, the PPP technique can be used for the BBA of GCPs to be established for UAVs in large-scale map generation. However, the number of GCPs to be selected should be four or more, which should be homogeneously distributed over the study area. Full article

Background and Objectives: The Foot Function Index (FFI) is a widely recognized patient-reported outcome measure (PROM) for assessing foot functionality and its impact on quality of life in individuals with rheumatoid arthritis (RA). This study aimed to observe the behavior of the tool in the Spanish population with RA, optimize the tool, and check its functionality. Materials and Methods: A total of 549 RA patients, with a predominant female participation (75.6%). This study involved a comprehensive statistical analysis, leading to a refined version of the FFI for a Spanish-speaking population. Results: The original 23-item FFI was revised, resulting in a 15-item version by excluding items that caused confusion or were considered redundant. This modified version maintained the original’s subscales of pain, disability, and activity limitation, but with an adjusted item distribution. The construct validity was confirmed through exploratory factor analysis, demonstrating excellent fit indices (Kaiser–Meyer–Olkin test = 0.926, Bartlett’s test of sphericity = 4123.48, p < 0.001). The revised FFI demonstrated good internal consistency (Cronbach’s alpha = 0.96) and test–retest reliability (ICC = 0.89). Conclusions: This study highlights the applicability of the FFI in Spanish-speaking RA populations, offering a valid and reliable tool for clinicians and researchers. The modifications enhance the FFI’s relevance for RA patients, facilitating better assessment and management of foot-related functional impairments. Full article

Research on employee experience is a topic that has been growing in recent decades. This study analyzes the validity and reliability of an employee experience scale in Peruvian teachers. The study had an instrumental design. The sample was comprised of 760 Peruvian teachers between 20 and 71 years old (M = 40.91; SD = 10.05), where men (36.1%) and women (63.9%) participated, recruited through non-probabilistic sampling. A validity and reliability analysis of the employee experience scale confirmed the three original factors (sensory experience, intellectual experience, and emotional experience). The KMO test reaches a high level (0.950 > 0.70), and the Bartlett test reaches a highly significant level (Sig. = 0.000). The scale also showed good internal consistency (α = 0.948 to 0.980; CR = 0.950 to 0.981; AVE = 0.864 to 0.878). Similarly, for the confirmatory factor analysis, a measurement adjustment was performed, obtaining excellent and acceptable fit indices for Model 2 for three factors (CMIN/DF = 4.764; CFI = 0.984; SRMR = 0.024; RMSEA = 0.070). This study provides a useful tool to measure the employee experience in a friendly way, using simple language to be applied to the Peruvian context. This study is considered an important contribution to organizational behavior and human talent management in educational circles. Full article

This paper studies the relationship between leadership as an activity of business process management (BPM) and company performance. Business process data about leadership and business processes in SMEs were collected via questionnaires on the population of 3007 SMEs in Slovenia. Aspects of leadership such as the involvement of employees, middle management, customers and suppliers were studied. The financial data of the SMEs of the sample were obtained from publicly available financial statements to assess relative residual income profitability ROE_r and ROE_a. Data analysis was performed using Bartlett’s, Kaiser–Maier–Olkin and nonparametric Mann–Whitney U tests. We confirmed a positive relationship between employee involvement in leadership as an activity of BPM and company profitability. It was proved that companies that involve employees and middle management in improving core business processes to a greater degree are more profitable. Intense involvement of employees in changes in core business processes results in higher company profitability, which has been detected by the higher risk-adjusted profitability measure ROE_a. Companies that involve middle management to a greater degree by leading employees based on their interests are more profitable. The results are important for managers as decision-makers and other company stakeholders, especially those responsible for business process improvements. Theoretical and practical implications and further research possibilities are discussed. Full article

Most breast cancer patients are middle-aged women actively involved in establishing a family, developing a career, or raising children. With the exception of the Newly Diagnosed Breast Cancer Stress Scale (NDBCSS), few stress scales have been designed for women with breast cancer. This study checked the dimensionality of the NDBCSS by confirmatory factor analysis (CFA) and the results showed a poor fit, indicating an urgent need for improvement. Exploratory factor analysis (EFA) using the varimax rotation method was performed to improve the model, the revised NDBCSS (NDBCSS-R), which showed a good Kaiser-Meyer-Olkin value, Bartlett’s test of sphericity, and internal consistency reliability. The NDBCSS-R showed improved indices compared with NDBCSS, including: chi-square fit statistics/degree of freedom (CMIN/DF), goodness-of-fit index (GFI), adjusted goodness of fit index (AGFI), normed fix index (NFI), relative fit index (RFI), incremental fix index (IFI), Tucker–Lewis index (TLI), comparative fix index (CFI), root mean square error of approximation (RMSEA), root mean square residual (RMR), parsimonious goodness-fit-index (PGFI), and parsimonious normed fit index (PNFI). In conclusion, the improved NDBCSS-R can provide health professionals with an early understanding of the stress levels of women with breast cancer so that they can provide immediate medical intervention to prevent vicious cycles in a timely manner. Full article

Forest-canopy height is an important parameter for the estimation of forest biomass and terrestrial carbon flux and climate-change research at regional and global scales. Currently, various methods combining Light Detection and Ranging (LiDAR) data with various auxiliary data, particularly satellite remotely sensed reflectances, have been widely used to produce spatially continuous canopy-height products. However, current methods in use for remote sensing reflectances mainly focus on the nadir view direction, while anisotropic reflectances, which are theoretically more sensitive to the forest canopy height in the multiangle remote sensing field, have rarely been explored. Here, we attempted to examine the potential of using modeled multiangle reflectances at three typical viewing angles (i.e., from the hotspot, darkspot, and nadir directions) to estimate forest-canopy height as auxiliary data sources. First, the sensitivities of the typical angular reflectances as a function of forest canopy height were fully examined using the Extended Fourier Amplitude Sensitivity Test (EFAST) method based on the 4-scale Bidirectional Reflectance Distribution Function (BRDF) model simulations. This indicated that reflectances in the off-nadir viewing directions are generally sensitive to canopy-height variations. Then, the canopy heights were extracted from airborne Laser Vegetation Imaging Sensor (LVIS) data, which were further divided into training and validation data. Moderate Resolution Imaging Spectroradiometer (MODIS) multiangle reflectances at typical viewing angles were calculated from the MODIS BRDF parameter product (MCD43A1, version 6) as partial training-input data, based on a hotspot-adjusted, kernel-driven linear BRDF model. Subsequently, the Random Forest (RF) machine learning model was trained to acquire the relationship between the extracted canopy heights and the corresponding MODIS typical viewing reflectances. The trained model was further applied to estimate the canopy height metrics in the study areas of Howland Forest, Harvard Forest, and Bartlett Forest. Finally, the estimated canopy heights were independently validated by canopy heights extracted from the LVIS data. The results indicate that the canopy heights modeled through this method exhibit generally high accordance with the LVIS-derived canopy heights (R = 0.65−0.67; RMSE = 3.63−5.78). The results suggest that the MODIS multiangle reflectance data at typical observation angles contain important information regarding forest canopy height and can, therefore, be used to estimate forest canopy height for various ecological applications. Full article

The mixed-effects model for repeated measures (MMRM) approach has been widely applied for longitudinal clinical trials. Many of the standard inference methods of MMRM could possibly lead to the inflation of type I error rates for the tests of treatment effect, when the longitudinal dataset is small and involves missing measurements. We propose two improved inference methods for the MMRM analyses, (1) the Bartlett correction with the adjustment term approximated by bootstrap, and (2) the Monte Carlo test using an estimated null distribution by bootstrap. These methods can be implemented regardless of model complexity and missing patterns via a unified computational framework. Through simulation studies, the proposed methods maintain the type I error rate properly, even for small and incomplete longitudinal clinical trial settings. Applications to a postnatal depression clinical trial are also presented. Full article