Stratified Random Sampling Strategy Research Articles

Racial Discrimination and Mental Health: Analyzing the Impact of Discrimination, Stress, Depressive Symptoms and Self-Esteem on Anxiety Experiences

ABSTRACT Background Existing research demonstrates that racial inequity influences mental health outcomes. However, few studies simultaneously analyze the multiple factors influencing racial disparities regarding these outcomes. Our study addresses this gap by analyzing the impact of discrimination, stress, self-esteem, racial identity, depressive symptoms, and demographic factors on anxiety symptoms. Methods Participants were adults recruited from a primary care clinic in the Southeastern region of the United States. We utilized a stratified random sampling strategy to select 383 participants. Participants completed a survey designed to assess levels of anxiety, depression, perceived stress, self-esteem, racial identity, experiences with discrimination, and demographic information. A hierarchical regression analyzed which factors most impact symptoms of anxiety. Results Of the 363 participants in our study, the majority were female (71.3%), 57% were White identifying, 43% were Black identifying, and the average age was 54.4 (SD = 12.3). Model 4 accounted for 58% of the variance of anxiety symptoms and included a combination of depressive symptoms, perceived stress, self-esteem, experiences of everyday discrimination, and interaction terms. Within this model, perceived stress (t = 3.81, p < .01), experiences of everyday discrimination, (t = 2.33, p < .01), and income (t = -1.96, p < .01) were significantly associated with increased anxiety. Conclusions and implications Multiple contextual factors influence the relationship between race and anxiety. In particular, anxiety increases with lower rates of self-esteem and income. Conversely, anxiety increases with higher rates of stress, discrimination, and depressive symptoms. Social workers should consider each of these factors when treating patients presenting with symptoms of anxiety.

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Abstract. Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery (Planet Team, 2017). Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World (Brown et al., 2022), based on Sentinel-2, and the NASA IMPACT model (Paul and Ganju, 2021), based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29 (Mukherjee et al., 2024).

The Effect of Mindfulness-Based SEL Programs on Reducing Stress and Improving Mental Health in Adolescents in Jordan

This study employed quantitative methodologies to investigate the impact of a 12-week mindfulness-based Social and Emotional Learning (SEL) program on lowering stress and improving mental well-being in a sample of 300 adolescents from Jordan. The study employed a stratified random sampling strategy to choose participants from diverse urban and rural populations. Data was collected utilizing the Perceived Stress Scale (PSS) and the Strengths and Difficulties Questionnaire (SDQ). The data evaluation involved the use of descriptive statistics, paired-sample t-tests, regression analysis, and an Analysis of Covariance (ANCOVA). The results indicate a significant decrease in stress levels and positive changes in mental health outcomes following the intervention. The regression analysis revealed that age was a likely predictor of changes in stress levels, indicating that older persons saw more significant declines. The analysis of covariance (ANCOVA) indicated significant gender-specific discrepancies in the impacts of the intervention. Independent samples t-tests revealed statistically significant variations in the average rankings across specific age groups and school environments. Proposed measures include implementing mindfulness-based social and emotional learning (SEL) programs in school systems, tailoring treatments to suit different demographic groups, examining gender-specific factors, and advocating for policy integration. Performing a longitudinal study is typically advised to assess the long-term sustainability of intervention results.

Efficient population mean estimation via stratified sampling with dual auxiliary information: A real estate perspective

Auxiliary information is an essential component in the field of survey sampling since it enables precise estimation of population parameters like mean, variance, distribution function, and so on, which in turn guarantees the best possible outcomes. In order to estimate the population mean of a study variable, this study makes use of auxiliary information in a two-fold approach. Through a stratified random sampling scheme, we introduce a novel class of estimators that utilize auxiliary information and their corresponding ranks. By conducting a thorough evaluation based on metrics such as mean square error and percentage relative efficiency, these proposed estimators have been shown to be effective in the estimation process. Empirical validation is conducted using a real dataset sourced from the domain of real estate. Exploring the relationship between Assessed Value (X) and Sale Amount (Y) during a five-year period extending from 2017 to 2021 is the primary emphasis of the empirical validation process, which is carried out with the assistance of a real dataset of real estate data. Furthermore, in order to demonstrate that our suggested estimator is superior to conventional unbiased estimators, as well as traditional regression estimators and other estimators that have been considered in the literature, a full simulation analysis is carried out. Our proposed estimator appears to be the most effective choice after being subjected to a comparison study against a variety of preexisting approaches. The findings of this study not only make a significant contribution to the development of the methodology of survey sampling but also offer vital insights for predictive modeling within the real estate sector.

A Comparative Study of Household Water, Sanitation and Hygiene (WASH) Covariates Across Socioeconomic Strata

Background: Water, sanitation, and hygiene (WASH) are essential for a healthy and productive life. High-quality access to these services reduces disease occurrence and spread in communities. Developing countries, including Pakistan, face significant challenges in providing these facilities. This study aims to highlight WASH-related service disparities in Pakistani households based on socioeconomic strata. Methodology: A stratified random sampling strategy was used, with a sample size of 1200 households based on the PDHS 2019 special survey. Descriptive analysis and chi-square tests were conducted to assess the association between wealth quintiles and WASH access. Results: The study found that 82.4% of households had access to improved sources of drinking water. Only 4.8% of households in the lowest quintile had access to improved drinking water sources. Water unavailability for at least one day per week was 13% higher among the lower quintiles. Forty-four percent of households using improved sanitation facilities belonged to the two highest strata, while poorer households predominantly used unimproved sanitation facilities. Conclusion: Lower-quality WASH access is more prevalent among lower wealth quintiles, increasing the risk of disease and infection. Further research is needed to inform policymakers and develop plans to reduce inequalities in access to WASH services.

Ratio-type estimator of the population mean in stratified sampling based on the calibration approach

An improved ratio-type calibrated estimator was developed using the logarithmic mean in the calibration constraint for the stratified random sampling scheme. The proposed estimator was extended in the case of stratified double sampling and compared with the estimators given by Tracy et al. (2003) together its ratio-type estimators, as well as Nidhi et al. (2017) and Khare et al. (2022). A simulation study was also carried out on both a real and artificial dataset in order to evaluate the performance of the proposed estimator compared to the existing estimators.

Anxiety and depression during post covid-19 lockdown period among medical students, and it's relation with stress and smartphone addiction in India.

Medical profession, a competitive and ever-updating field which requires great commitment, imposes a stressful environment for students. Our study aimed to find the prevalence and factors associated with psychological illness. A cross-sectional analytical study was done among medical students in Puducherry. A stratified random sampling strategy was incorporated to achieve a calculated sample size of 384. The presence of anxiety and depression, perceived stress and addiction to the phone were assessed using the Hospital Anxiety and Depression Scale, Perceived Stress Scale, and Smartphone Addiction Scale- short version. Prevalence of anxiety and depression was summarized as a proportion with a 95 % confidence interval (CI). The prevalence ratio (PR) for the factors associated was estimated using log-binomial regression. With the response from 383 students, the prevalence of anxiety and depression was 39.4 % (95 %CI: 34.5-44.3 %) and 26.6 % (22.2-31.1 %). Perceived stress was moderate in 68.2 % and high in 14 % of students. Higher age (aPR=1.49), female gender (aPR=1.22), tobacco or alcohol use (aPR=1.24), smartphone addiction (aPR=2.09) and high stress (aPR=1.93) were the predictors of anxiety among medical students in our study. Use of tobacco or alcohol (aPR=2.07), smartphone addiction (aPR=1.96) and high stress (aPR=1.72) were the predictors of depression. Anxiety was more prevalent than depression among the medical students. Use of tobacco or alcohol, smartphone addiction and stress increase the risk of psychological morbidity. Medical training should have a module on coping mechanisms to overcome psychological illness and have better mental well-being.

Exploring the Mediating Role of Organizational Commitment in the Relationship between Corporate Social Responsibility and Employee Performance: Evidence from Henan's Universities

Aims: This study aims to examine the mediating role of organizational commitment in the relationship between Corporate Social Responsibility (CSR) and employee performance within Henan's universities, highlighting the strategic importance of CSR in enhancing organizational effectiveness and employee outcomes. Study Design: This study utilized a cross-sectional survey methodology to explore the relationships among Corporate Social Responsibility (CSR), Organizational Commitment (OC), and Employee Performance (EP) within Henan's higher education sector. A stratified random sampling approach was employed to select faculty and administrative staff from universities engaged in CSR initiatives. The analysis, conducted through Structural Equation Modeling and mediation analysis, aimed to understand both direct and indirect effects of CSR on employee performance, with a particular focus on the mediating role of organizational commitment. Place and Duration of Study: Zhengzhou University, Henan University, Henan Normal University, Henan Agricultural University and Henan Polytechnic University, in December 2023. Methodology: The study adopted a quantitative research design using a cross-sectional survey method to explore CSR's impact on organizational commitment and employee performance in Henan's universities. A stratified random sampling strategy was utilized to select faculty and administrative staff from universities engaged in CSR, aiming for a sample size of 328 to ensure statistical significance. Validated scales measured CSR, organizational commitment, and employee performance, with data analysis conducted through Structural Equation Modeling and bootstrapping for mediation effects. Results: In this study, the impact of Corporate Social Responsibility (CSR) on Employee Performance (EP) and Organizational Commitment (OC) within Henan's universities was examined. Findings indicate that CSR positively influences EP both directly and via OC, serving as a mediator. Significant relationships were confirmed: CSR to EP (β=0.433), CSR to OC (β=0.825), and OC to EP (β=0.442), all highly statistically significant (p&lt;0.001). Mediation analysis showed CSR impacts EP through OC, accounting for about 45.73% of the effect. This underscores CSR's dual role in enhancing performance directly and by fostering organizational commitment. Conclusion: This study not only underscores the pivotal role of Corporate Social Responsibility (CSR) in enhancing employee performance within Henan's universities but also sheds light on the crucial mediating role of Organizational Commitment (OC). The dual pathway through which CSR influences employee performance underlines the significance of integrating CSR into the core strategic management practices of educational institutions. It signals to university administrators and policy-makers that CSR initiatives are not just external obligations but essential strategies for cultivating a committed and high-performing workforce. This realization opens up avenues for universities to re-evaluate and strengthen their CSR strategies, ensuring they are aligned with both organizational goals and employee values. Moreover, it encourages educational institutions to view CSR as a lever for organizational improvement and a bridge to deeper engagement with employees, ultimately contributing to the advancement of educational quality and societal contributions.

Comprehensive Insights Into E-Learning in Contemporary Education: Analyzing Trends, Challenges, and Best Practices

This study explores E-Learning in Modern Education at Afghanistan Universities, aiming to analyze trends, address challenges, and identify best practices. Employing a mixed-methods approach, it incorporates surveys and content analysis for both quantitative and qualitative data. A stratified random sampling strategy ensures representation from diverse faculties, resulting in 180 participants. Key findings emphasize widespread adoption of Learning Management Systems, multimedia content, mobile learning, and gamification for enhanced student engagement. Challenges include content management and resistance to change, highlighting complexities in E-Learning implementations. The study aligns with established theoretical frameworks like the Technology Acceptance Model and cognitive load theory, contributing to the theoretical understanding of E-Learning dynamics. Implications extend to educators, policymakers, and instructional designers, guiding strategic decision-making and interventions. Limitations, including potential response bias and context-specific considerations, underscore the need for cautious interpretation, paving the way for future research. In conclusion, this research provides a comprehensive examination of E-Learning trends and challenges, offering actionable insights for the ongoing discourse in digital education.

Monitoring and Organizational Performance in Private Higher Academic Institutions in Greater Bushenyi Districts in Western Uganda

The rational study assessed the effect of Monitoring on Organizational Performance in Private Higher Academic Institutions in Greater Bushenyi Districts in Western Uganda. The survey study engaged a correlational and descriptive research design with a quantitative standpoint. A sample of 380 contributors were carefully selected from 1053 persons using a table developed by Morgan &amp; Kreijcie (1970). Data was gathered by means of questionnaires to constitute an opinion survey. The researcher gathered evidence from the field using simple random sampling and stratified random sampling strategies. Data was evaluated using Descriptive statistics such as Means, Standard Deviation and Inferential Statistics such as Pearson linear correlation coefficient (PLCC) for quantitative data. The study results came up with a noteworthy relationship between monitoring and organizational Performance in Greater Bushenyi Districts in Western Uganda. The research venture concluded that Monitoring helps to identify implementation challenges that may be hindering the achievement of the intended outcomes. This information can be used to develop strategies to address these challenges and improve program or project implementation. From the research findings, the researchers recommended that private higher academic institutional managers should augment on the budget of Monitoring because it enhances accountability by ensuring that program or project implementation is transparent and that progress towards achieving goals and objectives can regularly be reported and reviewed. Academic private institutional managers should keep organizing periodically seminars and workshops to sensitize institutional stakeholders on the importance of monitoring in educational organizations. This can help provide relevant information for making informed decisions for development.

Prevalence of malnutrition and its associated factors among 18,503 Chinese children aged 3-14 years.

Child malnutrition places a major burden on global public health. We aimed to estimate the prevalence of child malnutrition and identify its potential factors among children aged 3-14 years from Beijing and Tangshan. We cross-sectionally recruited 18,503 children aged 3-14 years from September 2020 to January 2022, according to a stratified cluster random sampling strategy. Child malnutrition was defined according to the World Health Organization criteria. Data were analyzed by STATA software and R language. The prevalence of malnutrition among 18,503 children was 10.93%. After multivariable adjustment, seven factors significantly associated with child malnutrition were parental education (adjusted odds ratio, 95% confidence interval, p: 1.52, 1.40 to 1.67, <0.001), family income (1.23, 1.16 to 1.30, <0.001), fast food intake frequency (1.14, 1.06 to 1.21, <0.001), night meals intake frequency (1.09, 1.04 to 1.15, <0.001), eating speed (1.01, 1.01 to 1.02, <0.001), maternal obesity (0.97, 0.95 to 0.99, <0.001), and paternal obesity (0.97, 0.96 to 0.98, <0.001). The seven significant factors had better prediction performance (area under the receiver operating characteristic, 0.956) for child malnutrition. Approximately 10% of Chinese children aged 3-14 years were in malnutrition status, and seven factors were found to be significant predictors for child malnutrition.

Health-related quality of life and its changes of the Tibetan population in China: based on the 2013 and 2018 National Health Services Surveys

ObjectiveHealth-related quality of life (HRQoL) was an important health outcome measure for evaluating an individual’s overall health status. However, there was limited in the literature on HRQoL and its long-term...

Smoking cessation policy and treatments derived from the protective motivation of smokers: a study on graphic health warning labels.

Smoking is a leading public health risk. Many countries are reducing the demand for tobacco through graphic health warning labels (GHWLs). This study aims to explore smokers' perceptions of GHWLs and analyze the effect of GHWLs on their behavioral intentions to quit smoking. A theoretical model is designed by synthesizing protection motivation theory, an extension of the extended parallel process model, and the theory of planned behavior. We collected a cross-sectional sample of 547 anonymous smokers through a stratified random sampling strategy. GHWLs published in 2011 by the US Food and Drug Administration were used in the survey to assess smokers' responses to them, and then the hypotheses are validated through structural equation models. The results suggest that perceived severity, perceived vulnerability, response efficacy, and health anxiety have a significant impact on smokers' protection motivation. Furthermore, smokers' protection motivation directly impacts the behavioral intention to quit smoking and indirectly influences intention to quit through attitudes. These findings have practical implications for the implementation and improvement of GHWLs policies. Meanwhile, this study enriches the literature on public health protection measures (i.e., GHWLs) and smokers' behavioral intention to quit smoking.

Seroprevalence of SARS-CoV-2 in Niger State: Pilot Cross-Sectional Study.

The COVID-19 pandemic caused by SARS-CoV-2 is causing ongoing human and socioeconomic losses. To know how far the virus has spread in Niger State, Nigeria, a pilot study was carried out to determine the SARS-CoV-2 seroprevalence, patterns, dynamics, and risk factors in the state. A cross-sectional study design and clustered, stratified random sampling strategy were used to select 185 test participants across the state. SARS-CoV-2 IgG and IgM rapid test kits (colloidal gold immunochromatography lateral flow system) were used to determine the presence or absence of antibodies to the virus in the blood of sampled participants across Niger State from June 26 to 30, 2020. The test kits were validated using the blood samples of some of the Nigeria Center for Disease Control-confirmed positive and negative COVID-19 cases in the state. SARS-CoV-2 IgG and IgM test results were entered into the Epi Info questionnaire administered simultaneously with each test. Epi Info was then used to calculate the arithmetic mean and percentage, odds ratio, χ2 statistic, and regression at a 95% CI of the data generated. The seroprevalence of SARS-CoV-2 in Niger State was found to be 25.4% (47/185) and 2.2% (4/185) for the positive IgG and IgM results, respectively. Seroprevalence among age groups, genders, and occupations varied widely. The COVID-19 asymptomatic rate in the state was found to be 46.8% (22/47). The risk analyses showed that the chances of infection are almost the same for both urban and rural dwellers in the state. However, health care workers, those who experienced flulike symptoms, and those who had contact with a person who traveled out of Nigeria in the last 6 months (February to June 2020) were at double the risk of being infected with the virus. More than half (101/185, 54.6%) of the participants in this study did not practice social distancing at any time since the pandemic started. Participants' knowledge, attitudes, and practices regarding COVID-19 are also discussed. The observed Niger State SARS-CoV-2 seroprevalence and infection patterns meansuggest that the virus has widely spread, far more SARS-CoV-2 infections have occurred than the reported cases, and there is a high asymptomatic COVID-19 rate across the state.

Factors that led to Schools having different pass rates at Grade Seven Public Examinations level in Makoni District, Zimbabwe

The study sought to investigate factors that led to different trends in pass rates in Grade Seven National Examinations in Primary Schools in Makoni District during the period 2015 to 2019. The investigation employed mixed methods research design. The target population of the study comprised all school heads and Grade Seven teachers in Primary Schools in the District. The study was conducted in twenty primary schools randomly-selected from 182 primary schools in the district. A stratified random sampling strategy was used to select participants for the study. Twenty Grade Seven teachers and twenty School Heads were randomly-selected from their respective strata to participate in the study, bringing the total sample size to forty respondents. A structured questionnaire, and Focus Group Discussions were used for data-collection. The study findings revealed that the general Grade Seven Public Examination pass rates in Primary Schools in the District ranged from: low; high, and mixed. The factors that led to schools having different pass rates for the period 2015 to 2019 included the following factors: (1) Availability of text books and reading resources/library facilities; (2) Teacher's level of commitment to duty; (3) Regular and frequent administering of revision tests to learners; and (4) Teachers' length of experience. The study recommends that: (1) Government increases the non-remuneration component of the National Budget for school development, teaching and learning resources; and (2) School Development Committees establish a textbook levy to be paid by each learner, and approved by the Secretary for Primary and Secondary Education.

Pre-Start-Up Planning and Enhancement of Small and Medium Enterprises’ Operational Performance in The UAE

This rational research study assessed the association between Pre-start-up planning and Enhancement of Small and Medium Enterprises’ Operational Performance in the United Arab Emirates (UAE). The inquiry study engaged a descriptive and correlational research strategy with quantitative prototype. A sample of 104 participants were carefully chosen using a table prepared by Morgan &amp; Kreijcie (1970). Simple random sampling and stratified random sampling strategies were used to garner data for the research study. Details were assembled using questionnaires and evaluated utilizing frequencies, percentages, means, standard deviation and Pearson linear correlation coefficient (PLCC) were used for categorizing quantitative statistics. The study discoveries established a significant connection between Pre-start-up planning and Enhancement of Small and Medium Enterprises’ Operational Performance in the United Arab Emirates (UAE). The study concluded that Pre-start-up planning helps business people to strategically coordinate activities for businesses and avoid any regrets in terms of efficiency and effectiveness in SME’s. From the study consequences, the researchers recommended that the government of UAE should encourage its people to form groups so that government can provide financial assistance to such groups in order to foster their business performance. The government of UAE should also increase on the budget allocation to SME’s through the ministry of Economy so that SME’s can improve on their business, a scenario which may boost the economy of the country.

Police Stigma toward People with Opioid Use Disorder: A Study of Illinois Officers

Background Fatal opioid overdoses continue to break historical records. Stigma toward people with opioid use disorder (OUD) can negatively impact treatment access, retention, and recovery. Attitudes and beliefs of police officers can profoundly shape key discretionary decisions. Therefore, we examined police officer views indicating stigma toward those with OUD. Objectives We administered an online survey to select Illinois police departments using a stratified random sampling strategy with a final sample of 248 officers from 27 police departments. We asked officers questions measuring stigmatizing attitudes toward people with OUD including distrust, blame, shame, and fear. We found officers held somewhat stigmatizing views with a mean score of 4.0 on a scale of 1 (least stigmatic) to 6 (most stigmatic). Results Regression results showed certain officer characteristics were associated with more stigmatizing attitudes of blaming and distrust of those with OUD, including gender, education, race, years in policing, and department size. Conclusions/Importance Since most officers in the sample held at least some stigmatizing views toward people with OUD, this may impede the feasibility and acceptability of criminal justice interventions meant to improve behavioral health, such as police deflection programs that link people who use drugs to treatment in lieu of arrest. Departments should offer officer training and education on substance use disorders, treatment for addiction, and the potential for a person’s recovery. Training should allow officers to hear directly from, or learn about, personal experiences of people who use drugs and have been in recovery, as this type of interaction has been shown to reduce stigma.

Effectiveness of learning management system, teachers’ techno-pedagogical skills, and students’ learning engagement in Senior High School at the University Of Perpetual Help System-Jonelta Campuses

Information Communication Technology (ICT) changed the world orientation in general and education particularly in the teaching and learning process. A learning management system, or LMS, a software application that allows students to access course resources such as a syllabus, gradebook, discussion boards, and due dates (Center for Innovation in Teaching &amp; Learning, 2021) has been widely utilized in the educational system. Several educational institutions have been using certain LMS in planning, implementing, and evaluating learning processes (Brush, 2020), hence, researches were conducted to determine its effect to the teaching-learning process. However, there were many studies conducted about the effectivity of LMS, teachers’ techno-pedagogical skills, and students’ engagement which were mostly in international settings, but no study yet had been conducted particularly in the province of Laguna and among the senior high school students of UPHS-JONELTA Campuses. Thus, the researcher was inspired to measure the effectiveness of LMS, the teachers’ techno-pedagogical skills and students’ learning engagement and the relationship among variables. This is to further come up with programs that would help improve the utilization of LMS and the pedagogical competence of the teachers to ensure the maximum learning engagement of the learnersThis study utilized the descriptive-correlational research design which provides the most effective tool for determining the condition of relationship that exist (Bermudo et al., 2018). The respondents of the study consisted of 350 out of 3972 grade 12 students of University of Perpetual Help System JONELTA enrolled during the Academic Year 2022-2023. The sample size was computed using the Raosoft Size Calculator with the confidence level of 95 percent and a margin of error of 5 percent. The respondents were selected by utilizing stratified random sampling strategy. Proportional allocation was employed to calculate the number of the respondents selected from each campus. A total of 44 respondents came from Pangasinan Campus, 16 respondents from Pueblo de Panay Campus, 27 respondents from Isabela Campus, 54 respondents from GMA campus, 42 respondents from Manila campus and 167 respondents from Binan Campus for a total of 350 respondents in all.The research utilized modified standardized tests for the purpose of collecting the needed primary data. The first part covered the level of effectiveness of LMS in terms of system content, instruction, interaction, and technology quality. The second part covered the level of teachers’ pedagogical skills in terms of using technology in teaching; using technology in providing learning experiences; and using technology in preparation. Lastly, the third part of the questionnaire covered the level of students’ learning engagement in LMS. . Furthermore, a pilot test was also conducted and for the reliability of questionnaire using Cronbach Alpha, the results are as follow: for effectiveness of LMS: 0.963; for pedagogical skills: 0.934; and for students’ engagement: 0.950. After some modifications made, it was shown to the adviser for final approval.Based on the findings of the study, the study conclusions were drawn: The level of effectiveness of LMS in terms of system content, instruction, interaction, and technology quality is high. The level of the senior high school teachers’ techno-pedagogical skills alongside with using technology in teaching; using technology in providing learning experiences; and using technology in preparation is very high. The level of the senior high school students’ engagement in LMS is very high. Moreover, it was found out that the higher the level of effectiveness of LMS , the higher the teachers’ level of techno-pedagogical skills. Also, the higher the level of effectiveness of LMS, the higher the level of students’ engagement in LMS. Furthermore, the higher the level of teachers’ pedagogical skills, the higher the level of engagement of the students in LMS. Therefore, the better the skills of the teachers in utilizing technology in teaching, the more the students are engaged in LMS. Lastly, the independent variables; instruction and interaction under the effectiveness of LMS and the overall techno-pedagogical skills of the teachers are the drivers of the level of students’ engagement in LMS in the senior high school.

Fromforest floor to tree top: Partitioning of biomass and carbon stock in multiple strata of forest vegetation in Western Himalaya.

The foremost role of forest vegetation in storing biomass and carbon (C) stock constitutes one of the main nature-based solutions to mitigate climate change. In this study, we aimed to quantify biomass and C stock partitioning in multiple vegetation strata (tree, shrub, herb, and ground floor layers) of major forest types in Jammu and Kashmir,Western Himalaya, India. We used a stratified random cluster sampling strategy to collect field data in 96 forest stands of 12 forest types (altitudinal range: 350 to 3450m) in the study region. We evaluated the degree to which the carbon stock of the entire ecosystem was dependent on the multiple vegetation strata using the Pearson method. Across all the forest types, the average total ecosystem-level biomass was estimated to be 181.95 Mgha-1 (range: 60.64-528.98). Forest strata-wise, the maximum biomass of 172.92 Mgha-1 (range: 50.64-514.97) was found in the tree vegetation, followed by 5.58 Mgha-1 (range: 2.59-8.93) in understory vegetation (shrubs and herbaceous), and 3.44 Mgha-1 (range: 0.97 and 9.14) in the forest floor. The total ecosystem-level biomass showed a peak at mid-elevation coniferous forest types, whereas the lowest was observed in low-elevation broad leaved forest types. At the ecosystem-level, on average, the understory contributed 3% and the forest floor 2% to the total C stock across the forest types. The shrub layer contributed up to 80% of total understory C, with the herbaceous layer accounting for the remaining 20%. The ordination analysis clearly shows that anthropogenic and environmental variables significantly (p ≤ 0.002) influence the forest types' C stock in the region. Our findings have significant implications for conserving natural forest ecosystems and restoring degraded forest landscapes in this Himalayan region, which in turn can lead to better carbon sequestration and climate mitigation outcomes.

Measuring forest health at stand level: A multi-indicator evaluation for use in adaptive management and policy

Assessments of forest ecosystem health for use in adaptive management need an integrative multi-indicator examination at the stand scale. To assess forest health, we exained multiple forest indicators including diversity, age structure, regeneration, and edaphic factors of the dominant and associated tree species in their natural forest habitats. A stratified random cluster sampling strategy was used to gather vegetation samples from the five main forest types in the Zabarwan Mountain Range—Acacia forest (ACFT), Broad leaved forest (BLFT), Oak forest (OKFT), Pinus wallichiana forest (PWFT), and Scrub forest (SRFT). The Pearson method and canonical correspondence analysis (CCA) were used to investigate the relationship between tree species and edaphic factors. A total of 22 tree species were found, of which 13 were exotic and 9 were native. The proportion of exotic species was highest in OKFT (85%), followed by BLFT (75%), and the least (50%) SRFT. The BLFT forest type had the highest Shannon diversity while the lowest was the SRFT. ACFT and BLFT forest types have significantly higher Shannon diversity indexes than other forest types. Based on the density-girth class distribution, ACFT & SRFT forest types showed an Inverse-J distribution pattern, indicating a stable population structure. The dominant tree species, such as Populus alba in BLFT, demonstrated comparatively no regeneration, whereas Parrotiopsis jacquemontiana in SRFT, Pinus wallichiana in PWFT, Quercus robur in OKFT, and Robinia pseudoacacia demonstrated adequate regeneration performance. Overall exotic tree species such as Robinia pseudoacacia, Prunus cerasifera, Celtis australis, and Ailanthus altissima showed high/sufficient regeneration performance. The average seedling/tree value for all forest types in the area was 2.14, with the highest value at BLFT (3.61) and the lowest value at SRFT (0.71). In the CCA it showed that SRFT forests were greatly influenced by salinity and organic carbon, whereas ACFT and OKFT forests had comparable habitat preferences and were mutually influenced by electrical conductance and phosphorus availability. Prunus cerasifera was the only species positively associated with available calcium. By combining the data of numerous field-based indicators into a single integrated study, our research will give decision-makers an update on a forest's current and anticipated health.