Impact of socio-demographic variables of students on environmental Awareness, Behavior, and Practices: A case study of Gujarat

Impact of socio-demographic variables of students on environmental Awareness, Behavior, and Practices: A case study of Gujarat | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of socio-demographic variables of students on environmental Awareness, Behavior, and Practices: A case study of Gujarat Astha Garg, Dr. Urvashi Mishra This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7941844/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract a) Objectives: This study investigates the influence of socio-demographic variables- age, gender, grade level, and area of the school on environmental awareness, behavior, and practices (ABP) among middle-stage students (6 th – 8 th grade) in Halol taluka, Gujarat. b) Methods: A descriptive research design was used, and data were collected through a validated 128-item questionnaire, with responses analyzed via IBM SPSS Statistics version 20. c) Result: Results revealed significant urban-rural disparities, with urban students demonstrating higher awareness (Cohen's d = 1.30), reflecting 38% awareness gap and better waste management practices (odds ratio = 6.22, p < 0.001) than rural counterparts. Grade level strongly predicted awareness (β = 0.230, p < 0.001), while behavior was minimally influenced by area (R 2 = 0.024). Gender showed females exhibiting more positive behaviors (Cohen's d = 0.33), and age consistently influenced awareness and behavior but not practices. d) Conclusion: The findings highlight the need for targeted environmental education interventions, particularly in rural areas, to bridge awareness-practice gaps and foster sustainable behaviors. Environmental awareness behavior sustainability socio-demographic variables middle-stage students waste management urban-rural disparities Figures Figure 1 Figure 2 Figure 3 Introduction India's ranking as the world's third-largest waste producer, following the United States and China, underscores the magnitude of this challenge (Hoornweg et al., 2013). The country generates approximately 62 million tonnes of solid waste annually from urban areas, equivalent to 160,000 tonnes daily. What makes this scenario particularly alarming is the projected growth trajectory; waste production is expected to increase by 2.7 times by 2030 and sevenfold by 2050, with peak waste generation estimated to occur a century into the future (Madrascourier, 2018). The school-age period represents a particularly influential stage for environmental education interventions. During this developmental phase, students form fundamental beliefs, attitudes, and behavioral patterns that will guide their actions (Nath et al., 2021). Educational interventions during this period can establish lasting foundations for environmental stewardship and sustainable living practices. Environmental ABP (Awareness, Behavior, and Practices) The Awareness-Behavior-Practice (ABP) model serves as a foundational framework for understanding the development of environmental behavior, demonstrating that environmental awareness leads to behavioral attitude formation, which subsequently influences actual practices (Launiala, 2009). However, research has consistently documented gaps between these domains, particularly the awareness-practice disconnect, where increased environmental awareness does not automatically translate to sustainable actions (Kollmuss & Agyeman, 2002b). Ajzen's (1991) Theory of Planned Behavior further explains this complexity by identifying perceived behavioral control and subjective norms as critical mediators between behavioral attitudes and actual practice implementation. In the context of environmental education, the relationships among theoretical concepts are further complicated by demographic factors. Research suggests that age, gender, socioeconomic status, and geographic location significantly influence the strength of the associations between attitudes, beliefs, and practices (ABP) (Bamberg & Möser, 2006a ). It is essential to understand how these demographic variables affect these theoretical pathways to develop effective environmental education interventions, especially in diverse educational settings where students may have varying access to environmental information and opportunities for practical application. Research demonstrates age-related patterns in environmental learning. Mathew (2021) found that age correlated with knowledge of biomedical waste among students. This developmental pattern is supported by Deksne et al. (2022), who found that children aged 6-7 begin to form their food waste behavior, suggesting early formation of environmental behaviors. Nagy (2024) confirmed this pattern, showing that age and the number of children are positively associated with pro-environmental behavior, with older individuals engaging more in environmentally friendly actions. Gender shows as a consistent predictor across environmental contexts. Deksne et al. (2022) found that food consumption was affected by gender. Reddy and Chandrasekarayya (2025) and Ali et al. (2022) both found that female students exhibited more positive environmental attitudes, which may be attributed to greater parental encouragement, emotional maturity, and social expectations. Family background significantly influences environmental behaviors. Objectives To examine the impact of selected socio-demographic variables of the middle-stage (6 th – 8 th ) grade school students on environmental awareness, behavior, and practices. Methodology This study employed a descriptive research design to investigate the impact of socio-demographic variables of the students on environmental awareness, behavior, and practices. The research was conducted in Halol Taluka, Gujarat. Six schools were purposively selected from Halol Taluka, and a total of 720 students from grades 6, 7, and 8 were randomly selected using a systematic sampling technique from these schools. 720 structured questionnaires were distributed, 678 were fully completed, resulting in a response rate of 94.2%. Data were collected using a structured questionnaire designed to measure three domains of the environment. The questionnaire consisted of 128 items, divided into three sections. Dichotomous scoring was used for awareness, where 1 was for correct, and 0 was for incorrect or I don't know. A 3-point Likert scale for behavior was used, where 3 for agree, 2 for neutral, and 1 for disagree. 5-point Likert scale for practice, where 5 is the best and 1 is the least practised. To establish the questionnaire's validity, the Delphi method was employed, with a panel of 13 experts in environmental education and statisticians. The process, detailed in Fig. 2 , is given. Construct validity was further assessed using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's Test of Sphericity. Results indicated adequate factorability (KMO = 0.723; Bartlett’s χ² = 28,444.083, df = 8,128, p < 0.001). Reliability was evaluated using Cronbach's alpha and McDonald's omega for the overall questionnaire. The overall reliability was high (Cronbach's α = 0.861, McDonald's ω = 0.859). Prior to full-scale administration, the questionnaire underwent pilot testing with 90 students from a separate school in Halol Taluka, excluded from the final sample. The pilot testing revealed no amendments were required. The final content-validated ABP questionnaire, consisting of 128 items, was suitable for measuring awareness, behavior, and practices. Quantitative data were analysed using IBM SPSS Statistics version 20. Results Socio-demographic profile of the students The study sample comprised 678 students, with the area of the school located equally distributed, with 50% urban students (n=339) and 50% rural students. Grade-level distribution was also balanced across the academic levels: 35.25% students belonged to 8 th grade, followed by 32.25% from 7 th grade, and 32.15% from 6 th grade. 56.34% were males, and 43.65% were females. Age distribution reflected the grade level composition, with the majority of the students, 68.14% being from the 12-13 years age group, followed by 19.46% of the students aged 10-11 years, and 12.24% of the students from 14-15 years, as shown in Figure 3. Influence of Age on Environmental ABP Table 01 revealed progressive improvement in awareness and behavior scores across age groups, but inconsistent patterns in practice scores. Awareness scores demonstrated progression, with mean scores increasing from 29.95 in the 10-11 years group to 32.01 in the 12-13 years group, and reaching 34.24 in the 14-15 years group. The effect size for age differences in awareness was small but significant (η² = 0.011). Behavior scores showed a similar upward trend, progression from 52.43 in the youngest group to 54.36 in the oldest group, with a small effect size (η² = 0.013). However, practice scores displayed an inconsistent pattern, initially increasing, then declining with effect size (η² = 0.015). Table 01: Age-wise descriptive statistics of ABP scores Age in years Groups N Range Mean SD η² Variance Statistics SE Awareness 10-11 132 52 29.95 0.90 10.39 0.011 108.09 12-13 462 62 32.01 0.54 11.68 136.64 14-15 83 48 34.24 1.30 11.91 141.94 Behavior 10-11 132 24 52.43 0.37 04.28 0.013 18.37 12-13 462 26 52.94 0.22 04.84 23.49 14-15 83 16 54.36 0.48 04.40 19.40 Practice 10-11 132 46 42.02 0.70 08.07 0.015 65.16 12-13 462 58 45.15 0.47 10.12 102.56 14-15 83 46 44.26 1.01 09.27 86.00 Influence of Gender on Environmental ABP Gender-based analysis revealed differential patterns across ABP. Male students demonstrated slightly higher Awareness scores, 32.59, compared to females, 30.97, with a small effect size (Cohen's d = 0.20). Conversely, female students exhibited more positive behaviors 53.75 than males 52.43, representing a moderated effect size (Cohen's d = 0.33). Practice scores showed minimal gender differences, with females scoring slightly higher, 44.91, than males, 44.04, but with a negligible effect size (Cohen's d = 0.10). The variance pattern indicated greater individual differences within genders than between genders, particularly evident in awareness scores, where females showed higher variability (Variance = 155.50) compared to males (Variance = 114.06), as shown in Table 02 . Table 02: Gender-wise descriptive statistics of ABP scores Gender Groups N Range Mean SD Cohen's d Variance Statistics SE Awareness Male 382 57 32.59 0.54 10.68 0.20 114.06 Female 296 54 30.97 0.72 12.47 155.50 Behavior Male 382 24 52.43 0.21 04.23 0.33 17.95 Female 296 27 53.75 0.30 05.18 26.89 Practice Male 382 47 44.04 0.50 09.93 0.10 98.64 Female 296 58 44.91 0.58 09.43 88.96 Influence of Grade on Environmental ABP Table 03 revealed the most consistent educational progression patterns. Awareness scores demonstrated substantial improvement across grade levels, increasing from 28.57 in 6 th grade to 36.10 in the 8 th grade. This progression represented a medium-sized effect (η² = 0.075), indicating that grade level accounts for 7.5% of the variance in awareness scores. Behavior scores showed modest but consistent improvement across grades. Practice scores also demonstrated progressive improvement from 6 th grade to 8 th grade, with a small effect size (η² = 0.005). Table 03: Grade-wise descriptive statistics of ABP scores Grade Groups N Range Mean SD η² Variance Statistics SE Awareness 6 th Grade 221 52 28.57 0.70 10.54 0.075 111.13 7 th Grade 218 57 30.64 0.72 10.68 114.22 8 th Grade 239 54 36.10 0.76 11.86 140.84 Behavior 6 th Grade 221 24 51.37 0.27 04.02 0.003 16.22 7 th Grade 218 24 52.92 0.34 05.10 26.07 8 th Grade 239 25 54.61 0.28 04.40 19.43 Practice 6 th Grade 221 49 42.32 0.55 08.29 0.005 68.77 7 th Grade 218 46 44.73 0.61 09.13 83.53 8 th Grade 239 54 46.07 0.71 11.04 122.07 Influence of Area on Environmental ABP Area-based analysis revealed that the most substantial differences were among all demographic variables. Urban students significantly outperformed rural students in awareness scores, with urban students achieving a mean of 37.25 compared to rural students' mean of 26.89. This represents a large effect size (Cohen's d = 1.30) and a substantial 38% performance gap between urban and rural students. Behavior scores showed minimal area-related differences, with urban students scoring 53.98 and rural students scoring 52.03, resulting in a negligible effect size (Cohen's d = 0.04). Practice scores demonstrated that urban students scored 47.60 compared to rural students' 41.60, representing a moderate effect size (Cohen's d = 0.30). Table 04: Area-wise descriptive statistics of ABP scores based Area Groups N Range Mean SD Cohen's d Variance Statistics SE Awareness Urban 339 54 37.25 0.41 11.76 1.30 138.52 Rural 339 37 26.89 0.63 7.72 59.62 Behavior Urban 339 29 53.98 0.27 5.15 0.04 26.55 Rural 339 20 52.03 0.21 4.01 16.10 Practice Urban 339 58 47.60 0.61 11.27 0.30 127.11 Rural 339 45 41.60 0.35 6.46 41.81 Multiple Regression Analysis: Impact of socio-demographic variables Awareness Score Predictors The overall model significantly predicted awareness scores [F (4,673) = 69.134, p < 0.001, R² = 0.291]. The model accounted for 29.1% of the variance in awareness scores, indicating a moderate predictive capability. Area emerged as the strongest predictor (β = 0.465, p < 0.001), followed by grade level (β = 0.230, p < 0.001). Gender showed a significant negative relationship (β = -0.144, p < 0.001), while age contributed modestly (β = 0.065, p = 0.046) as shown in Table 05. Table 05: Multiple Regression Analysis Predicting Students' Awareness Score Based on Age, Gender, Grade, and Area Predicator B SE β t p Tolerance VIF Constant 11.929 2.041 - 5.845 < 0.001 Age (in years) 1.327 0.663 0.065 2.001 0.046 0.987 1.013 Gender -3.284 0.750 -0.144 -4.377 < 0.001 0.977 1.023 Grade 3.165 0.451 0.230 7.020 < 0.001 0.982 1.018 Area 10.541 0.746 0.465 14.136 < 0.001 0.974 1.027 Note: R 2 = 0.291, Adjusted R 2 = 0.287, F (4, 673) = 69.134, p < 0.001 Behavior Score Predictors The multiple regression model Table 06 revealed that the combination of demographic predictors significantly explained behavior score variance, [F(4, 673) = 4.162, p = 0.002]. However, the model accounted for only 2.4% of the variance in Behavior scores (R² = 0.024, Adjusted R² = 0.018), indicating a weak predictive capability and suggesting that these demographic variables have minimal influence on behavior regarding waste management. Only age (β = 0.100, p = 0.010) and gender (β = 0.106, p = 0.006) were significant predictors. Table 06: Multiple Regression Analysis Predicting Students' behavior Score Based on Age, Gender, Grade, and Area Predicator B SE β t p Tolerance VIF Constant 49.472 0.996 - 49.691 .000 - - Age (in years) 0.841 0.323 0.100 2.601 0.010 0.987 1.013 Gender 1.004 0.366 0.106 2.742 0.006 0.977 1.023 Grade 0.233 0.220 0.041 1.058 0.291 0.982 1.018 Area 0.02 0.364 0.000 0.006 0.995 0.974 1.027 Note: R 2 = 0.024, Adjusted R 2 = 0.018, F (4, 673) = 4.162, p = 0.002 Practice Score Predictors The multiple regression model Table 07 revealed that the combination of demographic predictors significantly explained practice score variance, F (4, 673) = 24.260, p < 0.001. The model accounted for 12.6% of the variance in practice scores (R² = 0.126, Adjusted R² = 0.121), indicating a moderate predictive capability. Area dominated as the strongest predictor (β = 0.319, p < 0.001), with grade level as secondary (β = 0.135, p < 0.001). Table 07: Multiple Regression Analysis Predicting Students' Practice Score Based on Age, Gender, Grade, and Area Predicator B SE β t p Tolerance VIF Constant 31.691 1.942 - 16.320 0.00 - - Age (in years) 0.219 0.631 0.013 0.348 0.728 0.987 1.013 Gender -0.158 0.714 -0.008 -0.221 0.825 0.977 1.023 Grade 1.598 0.429 0.135 3.726 0.000 0.982 1.018 Area 6.197 0.709 0.319 8.735 0.000 0.974 1.027 Note: R 2 = 0.126, Adjusted R 2 = 0.121, F (4, 673) = 24.260, p < 0.001 Binary Logistic Regression: Likelihood of High Performance High Awareness Achievement The binary logistic regression model Table 08 was statistically significant, χ²(6) = 145.40, p < 0.001, indicating that the combination of predictors significantly distinguished students with high and low awareness levels. The model explained 26.0% of the variance in awareness outcomes (Nagelkerke R² = 0.260) and correctly classified 69.2% of cases. The Hosmer-Lemeshow test indicated excellent model fit (χ² = 0.06, p > 0.05), demonstrating strong predictive capability. Urban students were 4.56 times more likely to achieve high awareness levels than rural students (OR = 4.56, 95% CI: 3.14-6.61, p < 0.001). Grade advancement increased odds by 77.2% per level (OR = 1.772, p < 0.001). Table 08: Binary Logistic Regression Predicting the Likelihood of High Levels of Awareness from Demographic and ABP Scores Predictor B S.E. Wald df p Exp(B) 95% CI for Exp(B) Age (in years) 0.109 0.155 0.488 1 0.485 1.115 0.822-1.511 Gender -0.914 0.184 24.566 1 0.00** 0.401 0.279-0.576 Grade 0.572 0.108 27.969 1 0.00** 1.772 1.433-2.190 Area 1.516 0.190 63.771 1 0.00** 4.556 3.140-6.610 Practice Score 0.024 0.011 5.200 1 0.023* 1.025 1.003-1.046 Behavior Score 0.029 0.019 2.309 1 0.129 1.029 0.992-1.068 Constant -4.521 1.132 15.958 1 0.00** 0.011 - Note: N = 678, Dependent variable = Awareness (0 = Low, 1 = High). Model X 2 (6) = 145.4029, p < 0.001, Nagelkerke R 2 = 0.260, Hosmer & Lemeshow X 2 (8) = 0.06, p = 0.000, Overall classification = 69.2%. Positive Behavior Achievement The binary logistic regression model Table 09 was statistically significant, χ²(6) = 24.60, p < 0.001, indicating that the combination of predictors significantly distinguished students with positive and negative behaviors toward waste management. However, the model explained only 4.8% of the variance in behavior outcomes (Nagelkerke R² = 0.048) and correctly classified 58.6% of cases, suggesting weak predictive capability. Age (OR = 1.507, p = 0.004) and gender (OR = 1.583 for females, p = 0.005) significantly predicted positive behaviors. Table 09: Binary Logistic Regression Predicting the Likelihood of Positive Behavior on Solid Waste Management from Demographic and ABP Scores Predictor B S.E. Wald df p Exp(B) 95% CI for Exp(B) Age 0.410 0.144 8.146 1 0.004** 1.507 1.141-1.99 Gender 0.459 0.162 8.026 1 0.005** 1.583 1.150-2.180 Grade 0.109 0.100 1.179 1 0.277 1.115 0.920-1.351 Area -.021 0.187 0.013 1 0.909 0.979 0.681-1.408 Awareness Score 0.013 0.008 2.618 1 0.106 1.013 0.998-1.029 Practice Score -.016 0.009 3.328 1 0.068* 0.984 0.966-1.002 Constant -1.499 0.526 8.116 1 0.004** 0.223 0.080-0.621 Note: N = 678, Dependent variable = Behavior (0 = Low, 1 = High). CI = Confidence Interval; SE = Standard Error; Exp(B) = Odds Ratio. p < .10, p < .05**, p < .01**. Model X 2 (6) = 24.60, p < 0.001, Nagelkerke R 2 = 0.048, Overall classification = 58.6%. Good Practice Achievement The binary logistic regression model Table 10 was statistically significant, χ²(6) = 133.29, p < 0.001, indicating that the combination of predictors significantly distinguished between students with good and poor waste management practices. The model explained 24.7% of the variance in practice outcomes (Nagelkerke R² = 0.247) and correctly classified 72.1% of cases. The Hosmer-Lemeshow test indicated good model fit (χ² = 6.81, p = 0.557). Area was the only significant predictor of good practices (OR = 6.22, p < 0.001), with urban students over 6 times more likely to demonstrate good waste management practices. Table 10: Binary Logistic Regression Predicting the Likelihood of Good Practices on Solid Waste Management from Demographic and ABP Scores Predictor B S.E. Wald df p Exp(B) 95% CI for Exp(B) Gender 0.21 0.18 1.24 1 0.27 1.23 0.86-1.76 Grade 0.09 0.12 0.55 1 0.46 1.09 0.87-1.37 Area 1.83 0.21 74.49 1 < 0.0010 6.22 4.11-9.43 Age -0.02 0.17 0.02 1 0.89 0.98 0.70-1.35 Awareness Score 0.01 0.01 1.91 1 0.17 1.01 0.99-1.03 Behavior Score -0.01 0.02 0.42 1 0.52 0.99 0.95-1.03 Constant -3.71 1.08 11.73 1 0.001 0.02 _ Note: N = 678, Dependent variable = Practice (0 = Poor, 1 = Good). Model X 2 (6) = 133.29, p < 0.001, Nagelkerke R 2 = 0.247, Hosmer & Lemeshow X 2 (8) = 6.81, p = 0.557, Overall classification = 72.1%. Interpretation and Discussions Urban-Rural Disparities The most notable finding of this study is the substantial area disparity in environmental awareness and practice among students. Urban students demonstrated significantly higher awareness scores than rural area students (Cohen's d = 1.30, p < 0.001), representing a 38% performance gap that constitutes a large practical effect. This disparity was further reinforced in multiple regression analysis, where area emerged as the strongest predictor of awareness scores (β = 0.465, p < 0.001), and binary logistic regression revealed that urban students had 4.556 times higher odds of achieving high awareness levels (95% CI: 3.140-6.610, p < 0.001). The urban-rural gap extended to practice scores, with urban students demonstrating significantly better waste management practices (Cohen's d = 0.30, p < 0.001). Urban students were 6.22 times more likely to exhibit good waste management practices than rural students (95% CI: 4.11-9.43, p < 0.001). These findings align with Dolipas et al. (2018) and Yadav and Medhavi (2024), who similarly documented urban area respondents showed more environmental engagement and responsible waste disposal behaviors. However, a critical finding was that the area showed no influence on environmental behaviors (p = 0.575, Cohen's d = 0.04), suggesting that while urban students possess greater factual awareness and demonstrate better practices, both groups maintain similar attitude and evaluative responses toward environmental issues. This dissociation between awareness-practice and behaviors across geographic areas suggests that environmental values may be more uniformly distributed than environmental awareness, possibly reflecting common cultural values regardless of area. Grade-Level Impacts Grade level emerged as the second most influential factor, particularly for awareness. The analysis revealed highly significant differences in awareness scores across grades (F = 27.49, p < 0.001, η² = 0.075), with 8th-grade students significantly outperforming both 6th-grade (mean difference = 7.214, p < 0.001) and 7th-grade students (mean difference = 5.458, p < 0.001). Multiple regression confirmed grade as a strong predictor (β = 0.230, p < 0.001), while binary logistic regression showed that higher-grade students had 1.772 times higher odds of achieving high awareness levels. Grade level showed differential effects across awareness, behavior, and practices . While awareness demonstrated clear educational progression, behavior showed no significant grade-related differences (F = 1.092, p = 0.336, η² = 0.003). This finding suggests that while formal education effectively increases factual awareness about waste management, it may not significantly influence students' attitude and evaluative responses toward environmental issues. Practice scores showed an intermediate pattern, with significant differences across grades (χ² = 26.53, p < 0.001) and grade serving as a significant predictor in regression analysis (β = 0.135, p < 0.001). This pattern aligns with Dolipas et al. (2018) and Ali et al. (2022), suggesting that practices improve with educational progression, possibly due to increased opportunities for hands-on environmental activities and greater autonomy in decision-making among older students. These findings align with Liu et al. (2024), and Ali et al. (2024), who reported that educational qualification influences students' KAP scores. The progressive increase in awareness across grades likely reflects the impact of educational exposure and cognitive development, consistent with formal educational progression in environmental issues. Gender Influences Gender demonstrated complex relationships that varied significantly, revealing important insights about how males and females engage differently with environmental issues. Initial univariate analysis suggested no significant gender difference in awareness scores (p = 0.093, Cohen's d = 0.20), indicating minimal practical significance when examined in isolation. However, multiple regression analysis revealed gender as a significant predictor (B = -3.284, β = -0.144, p < 0.001), with males showing higher awareness when controlling for other demographic variables. Binary logistic regression further supported this pattern, showing males had significantly higher odds of achieving high awareness levels (OR = 2.49, p < 0.001). The high variability observed within both groups (SD = 10.68 for males, SD = 12.47 for females) suggests that individual differences within each gender far outweigh differences between genders. These findings align with Yadav and Medhavi (2024), and Mathew et al. (2021), who found similar patterns of gender influence on environmental awareness. A statistically significant difference was found in behavior scores (t = -2.77, p = 0.006, Cohen's d = 0.33), with females demonstrating more positive behavior toward waste management than males by 1.03 points. This moderate effect size suggests a meaningful practical difference between genders. Multiple regression analysis confirmed gender as a significant predictor of behavior scores (β = 0.106, p = 0.006), and binary logistic regression showed that females had 1.583 times higher odds of having positive behaviors toward waste management (95% CI: 1.150-2.18, p = 0.005). These results align with research by Yadav and Medhavi (2024) and Marin et al. (2024), who found that females showed more positive behaviors toward environmental issues. Age Effects Age revealed a consistent but modest influence on awareness and behaviors, but demonstrated no relationship with practices, revealing important insights about developmental patterns in environmental engagement. Multiple regression confirmed age as a significant predictor for both awareness (β = 0.065, p = 0.046) and behaviors (β = 0.100, p = 0.010). Binary logistic regression showed that older students had 1.507 times higher odds of having positive behaviors (95% CI: 1.141-1.99, p = 0.004). These results support the findings of Mathew (2021), Yadav and Medhavi (2024), Badrum et al. (2020), and Lliopoulou (2019), who highlighted the significance of age-related cognitive development in environmental awareness. The progressive improvement in awareness and behaviors with age may reflect increased exposure to environmental issues and enhanced capacity for abstract thinking about long-term consequences. Surprisingly, in practice scores across age groups, Multiple regression confirmed that age was not a significant predictor of practice scores (p = 0.728), and binary logistic regression showed similar non-significant patterns. This shows the disassociation among awareness-behavior-practice and aligns with findings by Ahmad et al. (2015), who documented weak correlations between awareness and practice (r = 0.217). This gap highlights the complexity of translating environmental awareness into actual practice. Despite improvements in awareness and behaviors with age. Comparative Analysis The differential influence patterns of demographic variables of students across awareness, behavior, and practices reveal important insights about the complexity of environmental learning. Awareness: Influenced by Educational Level and Environmental Access Awareness scores were most strongly predicted by area (β = 0.465), followed by grade level (β = 0.230), with modest contributions from gender (β = -0.144) and age (β = 0.065). This pattern suggests that awareness is primarily determined by access to educational resources and environmental information, which are more readily available in urban settings and through formal educational progression. Behaviors: Influenced by Personal and Developmental Factors Behavior scores showed a different pattern, with only age (β = 0.100) and gender (β = 0.106) as significant predictors, while area and grade showed no significant influence. The minimal variance explained (R² = 0.024) suggests that Behaviors are primarily influenced by individual differences rather than demographic factors, possibly reflecting personal values and family influences. Practices: Contextual Factors Dominate Practice scores were most strongly predicted by area (β = 0.319) and grade level (β = 0.135), while age and gender showed no significant relationships. This pattern suggests that behavioral implementation depends heavily on contextual factors such as infrastructure availability and educational opportunities for hands-on practice. Conclusion The study concluded that area disparity is the major highlight for environmental awareness, and practices to remove it, educational intervention programs for rural area students with the required infrastructure and facilities are necessary. Early age of the students is crucial for the students to learn environmental behavior and practices in their habits. Implications for Environmental Education Policy and Practice These findings have significant implications for environmental education policy and practice. The substantial urban-rural disparities in both awareness and practice indicate a critical need for targeted interventions to address educational equity in environmental learning. Rural students require enhanced access to environmental resources, infrastructure and practical opportunities to develop waste management skills. The influential patterns of socio-demographic variables across dimensions suggest that effective environmental education programs must address all aspects rather than focusing solely on awareness transfer. The finding that behaviors are least predicted by demographic variables suggests the importance of addressing culture and values of individual and family-level factors in environmental education. The awareness-behavior-practice gaps, particularly the age-related disconnect in practices, highlight the need for educational approaches that emphasize practical skill development and behavioral implementation, not just awareness and behavior formation. Limitations and Recommendations The study was limited to the 678 middle-stage (6th – 8th ) grade students of Halol, taluka, Gujarat. The findings may not be generalizable to other geographic regions, cultural contexts, or educational systems due to the specific socio-economic and environmental characteristics of this area. The study only assessed three constructs of environment, namely awareness, behavior, and practices. Future research would benefit from longitudinal designs to track developmental changes over time. A standardized tool could be used to assess environmental behavior to enhance comparability across studies and contexts. External factors, culture, and values should be included in future research related to environmental learning and attitude s to provide a more comprehensive understanding of factors influencing student environmental outcomes. Declarations Human Ethics and Consent to Participate: The study was approved by the Institutional Ethics Committee for Human Research (IECHR), Faculty of Family and Community Sciences, The Maharaja Sayajirao University of Baroda, India (Approval No. IECHR/FCSc/P.hd/10/2023/03). Informed consent was obtained from all participants before their inclusion in the study. For participants under 18 years, consent was obtained from their parents/guardians and school administrators. The study was conducted per the institutional research committee's ethical standards and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. References Ahmad, J., Noor, S. M., & Ismail, N. (2015c). Investigating students’ environmental knowledge, attitude, practice and communication. Asian Social Science , 11 (16). https://doi.org/10.5539/ass.v11n16p284 Ajzen, I. (1991b). The theory of planned behavior. Organizational Behavior and Human Decision Processes , 50 (2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-t Ali, S. A., Bekela, N., & Mengistu, M. (2022). Attitude, awareness, concern, and practice (AACP) towards solid waste management among university students: A case study in Kotebe Education University, Addis Ababa. International Journal of Waste Resources , 12 (2), 461. https://doi.org/10.35248/2252-5211.22.12.461 Badrum, S. Y., & Mapa, M. T. (2020). Village-level knowledge, attitude, and practice (KAP) on solid waste management in Penampang, Sabah. Proceedings of Political and Social Science , 1 (1), 148-160. https://doi.org/10.31098/pss.v1i1.191 Bamberg, S., & Möser, G. (2006b). Twenty years after Hines, Hungerford, and Tomera: A new meta-analysis of psycho-social determinants of pro-environmental behaviour. Journal of Environmental Psychology , 27 (1), 14–25. https://doi.org/10.1016/j.jenvp.2006.12.002 Deksne, J., Litavniece, L., Zvaigzne, A., Lonska, J., & Kodors, S. (2022). Analysis of factors affecting zero-waste food consumption in schools. Research for Rural Development/Research for Rural Development (Online) , 37 , 150–157. https://doi.org/10.22616/rrd.28.2022.022 Dolipas, B., Ramos, J. L., Alimondo, M., & Madinno, C. (2018). Waste handling practices and values of university student. Athens Journal of Health , 5 (3), 213–232. https://doi.org/10.30958/ajh.5-3-3 Hoornweg, D., Bhada-Tata, P., & Kennedy, C. (2013). Environment: Waste production must peak this century. Nature , 502(7473), 615-617. Iliopoulou, I. (2019). Students’ Ability to Pose a Problem: The Case of Waste. Pedagogical Research, 4(2), em0033. https://doi.org/10.29333/pr/5783 Kollmuss, A., & Agyeman, J. (2002b). Mind the Gap: Why do people act environmentally and what are the barriers to pro-environmental behavior? Environmental Education Research , 8 (3), 239–260. https://doi.org/10.1080/13504620220145401 Launiala, A. (1970). How much can a KAP survey tell us about people’s knowledge, attitudes and practices? Some observations from medical anthropology research on malaria in pregnancy in Malawi. Anthropology Matters , 11 (1). https://doi.org/10.22582/am.v11i1.31 Liu S, Liu X, Li Y, Yang D, Li F and Yang J (2024) College students’ knowledge, attitudes, and practices of garbage sorting and their associations: a cross-sectional study of several universities in Beijing, China. Front. Public Health 12:1328583. doi: 10.3389/fpubh.2024.1328583 Madrascourier. (2018). The unsustainable urban waste economy. Retrieved from https://madrascourier.com/policy/the-unsustainable-urban-waste-economy/ Mathew, B. (2021). A study to assess the knowledge on biomedical waste management among GNM students at selected school of nursing, Vrindavan, Mathura, U.P. International Journal for Research in Applied Science & Engineering Technology, 9 (11), 1797–1801. https://doi.org/10.22214/ijraset.2021.39118 Nagy, S. (2024). The impact of Socio-Demographic variables on Pro-Environmental behaviour. Periodica Polytechnica Social and Management Sciences .https://doi.org/10.3311/ppso.23128 Nath, R., Kumar, A., & Sharma, P. (2021). Global warming awareness and sustainable behaviors among school students. International Journal of Environmental Education , 15(3), 45-62. Reddy, O., & Chandrasekarayya, T. (2025b). Socio-Demographic Aspects Influences on Attitudes towards Study: A Cross-Sectional Study among High School Students. International Journal of Research Publication and Reviews, 6(7), 6764–6769. https://doi.org/10.55248/gengpi.6.0725.2739 Yadav, U., & Medhavi, S. (2024). Exploring the Knowledge, Attitude, and Practice (KAP) among youth towards circular Economy practices in Lucknow. South India Journal of Social Sciences, 22(4), 217–230. https://doi.org/10.62656/sijss.v22i4.1350 Additional Declarations The authors declare no competing interests. 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2","display":"","copyAsset":false,"role":"figure","size":132452,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eContent Validity of the questionnaire\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7941844/v1/2b8eb62839dc78e86d7799d8.png"},{"id":94671986,"identity":"f7c8a755-495a-4bd0-83a6-fb5e086d4c3a","added_by":"auto","created_at":"2025-10-29 13:31:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112029,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7941844/v1/02750d37087ea011636b6eaa.png"},{"id":94730630,"identity":"23948d75-0bb6-4ebb-acc5-b926ecb9fb72","added_by":"auto","created_at":"2025-10-30 07:06:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2900780,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7941844/v1/42c8c239-9415-43b6-a093-8aae51b3a760.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eImpact of socio-demographic variables of students on environmental Awareness, Behavior, and Practices: A case study of Gujarat\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIndia\u0026apos;s ranking as the world\u0026apos;s third-largest waste producer, following the United States and China, underscores the magnitude of this challenge \u003cstrong\u003e(Hoornweg et al., 2013).\u003c/strong\u003e The country generates approximately 62 million tonnes of solid waste annually from urban areas, equivalent to 160,000 tonnes daily. What makes this scenario particularly alarming is the projected growth trajectory; waste production is expected to increase by 2.7 times by 2030 and sevenfold by 2050, with peak waste generation estimated to occur a century into the future \u003cstrong\u003e(Madrascourier, 2018).\u0026nbsp;\u003c/strong\u003eThe school-age period represents a particularly influential stage for environmental education interventions. During this developmental phase, students form fundamental beliefs, attitudes, and behavioral patterns that will guide their actions \u003cstrong\u003e(Nath et al., 2021).\u003c/strong\u003e Educational interventions during this period can establish lasting foundations for environmental stewardship and sustainable living practices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironmental ABP (Awareness, Behavior, and Practices)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Awareness-Behavior-Practice (ABP) model serves as a foundational framework for understanding the development of environmental behavior, demonstrating that environmental awareness leads to behavioral attitude formation, which subsequently influences actual practices \u003cstrong\u003e(Launiala, 2009).\u003c/strong\u003e However, research has consistently documented gaps between these domains, particularly the awareness-practice disconnect, where increased environmental awareness does not automatically translate to sustainable actions \u003cstrong\u003e(Kollmuss \u0026amp; Agyeman, 2002b).\u003c/strong\u003e \u003cstrong\u003eAjzen\u0026apos;s (1991)\u003c/strong\u003e Theory of Planned Behavior further explains this complexity by identifying perceived behavioral control and subjective norms as critical mediators between behavioral attitudes and actual practice implementation. In the context of environmental education, the relationships among theoretical concepts are further complicated by demographic factors. Research suggests that age, gender, socioeconomic status, and geographic location significantly influence the strength of the associations between attitudes, beliefs, and practices (ABP) \u003cstrong\u003e(Bamberg \u0026amp; M\u0026ouml;ser, 2006a\u003c/strong\u003e). It is essential to understand how these demographic variables affect these theoretical pathways to develop effective environmental education interventions, especially in diverse educational settings where students may have varying access to environmental information and opportunities for practical application.\u003c/p\u003e\n\u003cp\u003eResearch demonstrates age-related patterns in environmental learning. \u003cstrong\u003eMathew (2021)\u003c/strong\u003e found that age correlated with knowledge of biomedical waste among students. This developmental pattern is supported by \u003cstrong\u003eDeksne et al. (2022),\u003c/strong\u003e who found that children aged 6-7 begin to form their food waste behavior, suggesting early formation of environmental behaviors. \u003cstrong\u003eNagy (2024)\u003c/strong\u003e confirmed this pattern, showing that age and the number of children are positively associated with pro-environmental behavior, with older individuals engaging more in environmentally friendly actions. Gender shows as a consistent predictor across environmental contexts. \u003cstrong\u003eDeksne et al. (2022)\u003c/strong\u003e found that food consumption was affected by gender. \u003cstrong\u003eReddy and Chandrasekarayya (2025)\u003c/strong\u003e and \u003cstrong\u003eAli et al. (2022)\u003c/strong\u003e both found that female students exhibited more positive environmental attitudes, which may be attributed to greater parental encouragement, emotional maturity, and social expectations. Family background significantly influences environmental behaviors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo examine the impact of selected socio-demographic variables of the middle-stage (6\u003csup\u003eth\u003c/sup\u003e \u0026ndash; 8\u003csup\u003eth\u003c/sup\u003e) grade school students on environmental awareness, behavior, and practices.\u0026nbsp;\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThis study employed a descriptive research design to investigate the impact of socio-demographic variables of the students on environmental awareness, behavior, and practices. The research was conducted in Halol Taluka, Gujarat. Six schools were purposively selected from Halol Taluka, and a total of 720 students from grades 6, 7, and 8 were randomly selected using a systematic sampling technique from these schools. 720 structured questionnaires were distributed, 678 were fully completed, resulting in a response rate of 94.2%.\u003c/p\u003e\u003cp\u003eData were collected using a structured questionnaire designed to measure three domains of the environment. The questionnaire consisted of 128 items, divided into three sections. Dichotomous scoring was used for awareness, where 1 was for correct, and 0 was for incorrect or I don't know. A 3-point Likert scale for behavior was used, where 3 for agree, 2 for neutral, and 1 for disagree. 5-point Likert scale for practice, where 5 is the best and 1 is the least practised. To establish the questionnaire's validity, the Delphi method was employed, with a panel of 13 experts in environmental education and statisticians. The process, detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, is given. Construct validity was further assessed using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's Test of Sphericity. Results indicated adequate factorability (KMO\u0026thinsp;=\u0026thinsp;0.723; Bartlett\u0026rsquo;s χ\u0026sup2; = 28,444.083, df\u0026thinsp;=\u0026thinsp;8,128, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Reliability was evaluated using Cronbach's alpha and McDonald's omega for the overall questionnaire. The overall reliability was high (Cronbach's α\u0026thinsp;=\u0026thinsp;0.861, McDonald's ω\u0026thinsp;=\u0026thinsp;0.859). Prior to full-scale administration, the questionnaire underwent pilot testing with 90 students from a separate school in Halol Taluka, excluded from the final sample. The pilot testing revealed no amendments were required. The final content-validated ABP questionnaire, consisting of 128 items, was suitable for measuring awareness, behavior, and practices. Quantitative data were analysed using IBM SPSS Statistics version 20.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSocio-demographic profile of the students\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study sample comprised 678 students, with the area of the school located equally distributed, with 50% urban students (n=339) and 50% rural students. Grade-level distribution was also balanced across the academic levels: 35.25% students belonged to 8\u003csup\u003eth\u003c/sup\u003e grade, followed by 32.25% from 7\u003csup\u003eth\u003c/sup\u003e grade, and 32.15% from 6\u003csup\u003eth\u003c/sup\u003e grade. 56.34% were males, and 43.65% were females. Age distribution reflected the grade level composition, with the majority of the students, 68.14% being from the 12-13 years age group, followed by 19.46% of the students aged 10-11 years, and 12.24% of the students from 14-15 years, as shown in \u003cstrong\u003eFigure 3.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInfluence of Age on Environmental ABP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 01\u003c/strong\u003e revealed progressive improvement in awareness and behavior scores across age groups, but inconsistent patterns in practice scores. Awareness scores demonstrated progression, with mean scores increasing from 29.95 in the 10-11 years group to 32.01 in the 12-13 years group, and reaching 34.24 in the 14-15 years group. The effect size for age differences in awareness was small but significant (\u0026eta;\u0026sup2; = 0.011). Behavior scores showed a similar upward trend, progression from 52.43 in the youngest group to 54.36 in the oldest group, with a small effect size (\u0026eta;\u0026sup2; = 0.013). However, practice scores displayed an inconsistent pattern, initially increasing, then declining with effect size (\u0026eta;\u0026sup2; = 0.015).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 01: Age-wise descriptive statistics of ABP scores\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge in years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026eta;\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwareness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e10-11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e29.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e10.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e108.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e12-13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e32.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e11.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e136.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14-15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e34.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e11.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e141.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBehavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e10-11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e52.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e04.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e12-13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e52.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e04.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e23.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14-15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e54.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e04.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e19.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractice\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e10-11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e42.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e08.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e65.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e12-13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e45.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e10.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e102.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14-15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e44.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e09.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e86.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eInfluence of Gender on Environmental ABP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGender-based analysis revealed differential patterns across ABP. Male students demonstrated slightly higher Awareness scores, 32.59, compared to females, 30.97, with a small effect size (Cohen\u0026apos;s d = 0.20). Conversely, female students exhibited more positive behaviors 53.75 than males 52.43, representing a moderated effect size (Cohen\u0026apos;s d = 0.33). Practice scores showed minimal gender differences, with females scoring slightly higher, 44.91, than males, 44.04, but with a negligible effect size (Cohen\u0026apos;s d = 0.10). The variance pattern indicated greater individual differences within genders than between genders, particularly evident in awareness scores, where females showed higher variability (Variance = 155.50) compared to males (Variance = 114.06), as shown in \u003cstrong\u003eTable 02\u003c/strong\u003e. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 02: Gender-wise descriptive statistics of ABP scores \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026apos;s d\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwareness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e32.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e10.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e114.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e30.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e12.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e155.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBehavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e52.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e04.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e17.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e53.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e05.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e26.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractice\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e44.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e09.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e98.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e44.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e09.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e88.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eInfluence of Grade on Environmental ABP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 03 revealed the most consistent educational progression patterns. Awareness scores demonstrated substantial improvement across grade levels, increasing from 28.57 in 6\u003csup\u003eth\u003c/sup\u003e grade to 36.10 in the 8\u003csup\u003eth\u003c/sup\u003e grade. This progression represented a medium-sized effect (\u0026eta;\u0026sup2; = 0.075), indicating that grade level accounts for 7.5% of the variance in awareness scores. Behavior scores showed modest but consistent improvement across grades. Practice scores also demonstrated progressive improvement from 6\u003csup\u003eth\u003c/sup\u003e grade to 8\u003csup\u003eth\u003c/sup\u003e grade, with a small effect size (\u0026eta;\u0026sup2; = 0.005).\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 03: Grade-wise descriptive statistics of ABP scores \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026eta;\u0026sup2;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwareness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e28.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e10.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e111.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e30.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e10.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e114.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e36.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e11.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e140.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBehavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e51.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e04.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e52.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e05.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e26.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e54.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e04.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e19.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractice\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e42.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e08.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e68.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e44.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e09.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e83.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e46.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e11.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e122.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eInfluence of Area on Environmental ABP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eArea-based analysis revealed that the most substantial differences were among all demographic variables. Urban students significantly outperformed rural students in awareness scores, with urban students achieving a mean of 37.25 compared to rural students\u0026apos; mean of 26.89. This represents a large effect size (Cohen\u0026apos;s d = 1.30) and a substantial 38% performance gap between urban and rural students. Behavior scores showed minimal area-related differences, with urban students scoring 53.98 and rural students scoring 52.03, resulting in a negligible effect size (Cohen\u0026apos;s d = 0.04). Practice scores demonstrated that urban students scored 47.60 compared to rural students\u0026apos; 41.60, representing a moderate effect size (Cohen\u0026apos;s d = 0.30).\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 614px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 04: Area-wise descriptive statistics of ABP scores based\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 614px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026apos;s d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwareness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e37.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e138.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e26.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e7.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e59.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBehavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e53.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e5.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e26.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e52.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractice\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e47.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e127.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e41.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e6.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e41.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple Regression Analysis: Impact of socio-demographic variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAwareness Score Predictors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall model significantly predicted awareness scores [F (4,673) = 69.134, p \u0026lt; 0.001, R\u0026sup2; = 0.291]. The model accounted for 29.1% of the variance in awareness scores, indicating a moderate predictive capability. Area emerged as the strongest predictor (\u0026beta; = 0.465, p \u0026lt; 0.001), followed by grade level (\u0026beta; = 0.230, p \u0026lt; 0.001). Gender showed a significant negative relationship (\u0026beta; = -0.144, p \u0026lt; 0.001), while age contributed modestly (\u0026beta; = 0.065, p = 0.046) as shown in \u003cstrong\u003eTable 05.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 05: Multiple Regression Analysis Predicting Students\u0026apos; Awareness Score Based on Age, Gender, Grade, and Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredicator\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTolerance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e11.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e2.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e5.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e2.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-3.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-4.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e3.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e7.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e10.541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/strong\u003e \u003cstrong\u003eR\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e0.291, \u003cstrong\u003eAdjusted R\u003csup\u003e2\u003c/sup\u003e =\u0026nbsp;\u003c/strong\u003e0.287, F (4, 673) = 69.134, p \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBehavior Score Predictors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe multiple regression model \u003cstrong\u003eTable 06\u003c/strong\u003e revealed that the combination of demographic predictors significantly explained behavior score variance, [F(4, 673) = 4.162, p = 0.002]. However, the model accounted for only 2.4% of the variance in Behavior scores (R\u0026sup2; = 0.024, Adjusted R\u0026sup2; = 0.018), indicating a weak predictive capability and suggesting that these demographic variables have minimal influence on behavior regarding waste management. Only age (\u0026beta; = 0.100, p = 0.010) and gender (\u0026beta; = 0.106, p = 0.006) were significant predictors.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 06: Multiple Regression Analysis Predicting Students\u0026apos; behavior Score Based on Age, Gender, Grade, and Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredicator\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTolerance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e49.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e49.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e2.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e2.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/strong\u003e \u003cstrong\u003eR\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e0.024, \u003cstrong\u003eAdjusted R\u003csup\u003e2\u003c/sup\u003e =\u0026nbsp;\u003c/strong\u003e0.018, F (4, 673) = 4.162, p = 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003ePractice Score Predictors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe multiple regression model \u003cstrong\u003eTable 07\u003c/strong\u003e revealed that the combination of demographic predictors significantly explained practice score variance, F (4, 673) = 24.260, p \u0026lt; 0.001. The model accounted for 12.6% of the variance in practice scores (R\u0026sup2; = 0.126, Adjusted R\u0026sup2; = 0.121), indicating a moderate predictive capability. Area dominated as the strongest predictor (\u0026beta; = 0.319, p \u0026lt; 0.001), with grade level as secondary (\u0026beta; = 0.135, p \u0026lt; 0.001).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 07: Multiple Regression Analysis Predicting Students\u0026apos; Practice Score Based on Age, Gender, Grade, and Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredicator\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTolerance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e31.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e1.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e16.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e3.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e6.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e8.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/strong\u003e \u003cstrong\u003eR\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e0.126, \u003cstrong\u003eAdjusted R\u003csup\u003e2\u003c/sup\u003e =\u0026nbsp;\u003c/strong\u003e0.121, F (4, 673) = 24.260, p \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBinary Logistic Regression: Likelihood of High Performance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHigh Awareness Achievement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe binary logistic regression model \u003cstrong\u003eTable 08\u003c/strong\u003e was statistically significant, \u0026chi;\u0026sup2;(6) = 145.40, p \u0026lt; 0.001, indicating that the combination of predictors significantly distinguished students with high and low awareness levels. The model explained 26.0% of the variance in awareness outcomes (Nagelkerke R\u0026sup2; = 0.260) and correctly classified 69.2% of cases. The Hosmer-Lemeshow test indicated excellent model fit (\u0026chi;\u0026sup2; = 0.06, p \u0026gt; 0.05), demonstrating strong predictive capability. Urban students were 4.56 times more likely to achieve high awareness levels than rural students (OR = 4.56, 95% CI: 3.14-6.61, p \u0026lt; 0.001). Grade advancement increased odds by 77.2% per level (OR = 1.772, p \u0026lt; 0.001).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 08: Binary Logistic Regression Predicting the Likelihood of High Levels of Awareness from Demographic and ABP Scores\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.E.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWald\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp(B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for Exp(B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.822-1.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e24.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.00**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.279-0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e27.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.00**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.433-2.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e63.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.00**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e4.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.140-6.610\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractice Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e5.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.003-1.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBehavior Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e2.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.992-1.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-4.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e15.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.00**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote: N\u003c/em\u003e = 678, Dependent variable = Awareness (0 = Low, 1 = High). Model X\u003csup\u003e2\u003c/sup\u003e(6) = 145.4029, p \u0026lt; 0.001, Nagelkerke R\u003csup\u003e2\u003c/sup\u003e = 0.260, Hosmer \u0026amp; Lemeshow X\u003csup\u003e2\u003c/sup\u003e(8) = 0.06, p = 0.000, Overall classification = 69.2%.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003ePositive Behavior Achievement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe binary logistic regression model \u003cstrong\u003eTable 09\u003c/strong\u003e was statistically significant, \u0026chi;\u0026sup2;(6) = 24.60, p \u0026lt; 0.001, indicating that the combination of predictors significantly distinguished students with positive and negative behaviors toward waste management. However, the model explained only 4.8% of the variance in behavior outcomes (Nagelkerke R\u0026sup2; = 0.048) and correctly classified 58.6% of cases, suggesting weak predictive capability. Age (OR = 1.507, p = 0.004) and gender (OR = 1.583 for females, p = 0.005) significantly predicted positive behaviors.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"616\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 616px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 09: Binary Logistic Regression Predicting the Likelihood of Positive Behavior on Solid Waste Management from Demographic and ABP Scores\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.E.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWald\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp(B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for Exp(B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e8.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.004**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.141-1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e8.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.005**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.150-2.180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.920-1.351\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e-.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.681-1.408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwareness Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e2.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.998-1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractice\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e-.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e3.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.068*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.966-1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e-1.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e8.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.004**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.080-0.621\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 616px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote: N\u003c/em\u003e = 678, Dependent variable = Behavior (0 = Low, 1 = High). CI = Confidence Interval; SE = Standard Error; Exp(B) = Odds Ratio.\u003cem\u003ep\u003c/em\u003e \u0026lt; .10, \u003cem\u003ep\u003c/em\u003e \u0026lt; .05**, \u003cem\u003ep\u003c/em\u003e \u0026lt; .01**. Model X\u003csup\u003e2\u003c/sup\u003e(6) = 24.60, p \u0026lt; 0.001, Nagelkerke R\u003csup\u003e2\u003c/sup\u003e = 0.048, Overall classification = 58.6%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eGood Practice Achievement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe binary logistic regression model \u003cstrong\u003eTable 10\u003c/strong\u003e was statistically significant, \u0026chi;\u0026sup2;(6) = 133.29, p \u0026lt; 0.001, indicating that the combination of predictors significantly distinguished between students with good and poor waste management practices. The model explained 24.7% of the variance in practice outcomes (Nagelkerke R\u0026sup2; = 0.247) and correctly classified 72.1% of cases. The Hosmer-Lemeshow test indicated good model fit (\u0026chi;\u0026sup2; = 6.81, p = 0.557). Area was the only significant predictor of good practices (OR = 6.22, p \u0026lt; 0.001), with urban students over 6 times more likely to demonstrate good waste management practices.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 602px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 10: Binary Logistic Regression Predicting the Likelihood of Good Practices on Solid Waste Management from Demographic and ABP Scores\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.E.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWald\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp(B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI for Exp(B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.86-1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.87-1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e74.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026lt; 0.0010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.11-9.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.70-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwareness Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.99-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBehavior Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.95-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e11.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e_\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 602px;\"\u003e\n \u003cp\u003e\u003cem\u003eNote: N\u003c/em\u003e = 678, Dependent variable = Practice (0 = Poor, 1 = Good). Model X\u003csup\u003e2\u003c/sup\u003e(6) = 133.29, p \u0026lt; 0.001, Nagelkerke R\u003csup\u003e2\u003c/sup\u003e = 0.247, Hosmer \u0026amp; Lemeshow X\u003csup\u003e2\u003c/sup\u003e(8) = 6.81, p = 0.557, Overall classification = 72.1%.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eInterpretation and Discussions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUrban-Rural Disparities\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most notable finding of this study is the substantial area disparity in environmental awareness and practice among students. Urban students demonstrated significantly higher awareness scores than rural area students (Cohen\u0026apos;s d = 1.30, p \u0026lt; 0.001), representing a 38% performance gap that constitutes a large practical effect. This disparity was further reinforced in multiple regression analysis, where area emerged as the strongest predictor of awareness scores (\u0026beta; = 0.465, p \u0026lt; 0.001), and binary logistic regression revealed that urban students had 4.556 times higher odds of achieving high awareness levels (95% CI: 3.140-6.610, p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eThe urban-rural gap extended to practice scores, with urban students demonstrating significantly better waste management practices (Cohen\u0026apos;s d = 0.30, p \u0026lt; 0.001). Urban students were 6.22 times more likely to exhibit good waste management practices than rural students (95% CI: 4.11-9.43, p \u0026lt; 0.001). These findings align with \u003cstrong\u003eDolipas et al. (2018) and Yadav and Medhavi (2024),\u003c/strong\u003e who similarly documented urban area respondents showed more environmental engagement and responsible waste disposal behaviors.\u003c/p\u003e\n\u003cp\u003eHowever, a critical finding was that the area showed no influence on environmental behaviors (p = 0.575, Cohen\u0026apos;s d = 0.04), suggesting that while urban students possess greater factual awareness and demonstrate better practices, both groups maintain similar attitude and evaluative responses toward environmental issues. This dissociation between awareness-practice and behaviors across geographic areas suggests that environmental values may be more uniformly distributed than environmental awareness, possibly reflecting common cultural values regardless of area.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrade-Level Impacts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGrade level emerged as the second most influential factor, particularly for awareness. The analysis revealed highly significant differences in awareness scores across grades (F = 27.49, p \u0026lt; 0.001, \u0026eta;\u0026sup2; = 0.075), with 8th-grade students significantly outperforming both 6th-grade (mean difference = 7.214, p \u0026lt; 0.001) and 7th-grade students (mean difference = 5.458, p \u0026lt; 0.001). Multiple regression confirmed grade as a strong predictor (\u0026beta; = 0.230, p \u0026lt; 0.001), while binary logistic regression showed that higher-grade students had 1.772 times higher odds of achieving high awareness levels.\u003c/p\u003e\n\u003cp\u003eGrade level showed differential effects across awareness, behavior, and practices\u003cstrong\u003e.\u003c/strong\u003e While awareness demonstrated clear educational progression, behavior showed no significant grade-related differences (F = 1.092, p = 0.336, \u0026eta;\u0026sup2; = 0.003). This finding suggests that while formal education effectively increases factual awareness about waste management, it may not significantly influence students\u0026apos; attitude and evaluative responses toward environmental issues.\u003c/p\u003e\n\u003cp\u003ePractice scores showed an intermediate pattern, with significant differences across grades (\u0026chi;\u0026sup2; = 26.53, p \u0026lt; 0.001) and grade serving as a significant predictor in regression analysis (\u0026beta; = 0.135, p \u0026lt; 0.001). This pattern aligns with \u003cstrong\u003eDolipas et al. (2018) and Ali et al. (2022),\u003c/strong\u003e suggesting that practices improve with educational progression, possibly due to increased opportunities for hands-on environmental activities and greater autonomy in decision-making among older students. These findings align with \u003cstrong\u003eLiu et al. (2024), and Ali et al. (2024),\u003c/strong\u003e who reported that educational qualification influences students\u0026apos; KAP scores. The progressive increase in awareness across grades likely reflects the impact of educational exposure and cognitive development, consistent with formal educational progression in environmental issues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGender Influences\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGender demonstrated complex relationships that varied significantly, revealing important insights about how males and females engage differently with environmental issues. Initial univariate analysis suggested no significant gender difference in awareness scores (p = 0.093, Cohen\u0026apos;s d = 0.20), indicating minimal practical significance when examined in isolation. However, multiple regression analysis revealed gender as a significant predictor (B = -3.284, \u0026beta; = -0.144, p \u0026lt; 0.001), with males showing higher awareness when controlling for other demographic variables. Binary logistic regression further supported this pattern, showing males had significantly higher odds of achieving high awareness levels (OR = 2.49, p \u0026lt; 0.001). The high variability observed within both groups (SD = 10.68 for males, SD = 12.47 for females) suggests that individual differences within each gender far outweigh differences between genders. These findings align with \u003cstrong\u003eYadav and Medhavi (2024), and Mathew et al. (2021),\u003c/strong\u003e who found similar patterns of gender influence on environmental awareness.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA statistically significant difference was found in behavior scores (t = -2.77, p = 0.006, Cohen\u0026apos;s d = 0.33), with females demonstrating more positive behavior toward waste management than males by 1.03 points. This moderate effect size suggests a meaningful practical difference between genders. Multiple regression analysis confirmed gender as a significant predictor of behavior scores (\u0026beta; = 0.106, p = 0.006), and binary logistic regression showed that females had 1.583 times higher odds of having positive behaviors toward waste management (95% CI: 1.150-2.18, p = 0.005). These results align with research by \u003cstrong\u003eYadav and Medhavi (2024) and Marin et al. (2024),\u0026nbsp;\u003c/strong\u003ewho found that females showed more positive behaviors toward environmental issues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge Effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAge revealed a consistent but modest influence on awareness and behaviors, but demonstrated no relationship with practices, revealing important insights about developmental patterns in environmental engagement. Multiple regression confirmed age as a significant predictor for both awareness (\u0026beta; = 0.065, p = 0.046) and behaviors (\u0026beta; = 0.100, p = 0.010). Binary logistic regression showed that older students had 1.507 times higher odds of having positive behaviors (95% CI: 1.141-1.99, p = 0.004). These results support the findings of \u003cstrong\u003eMathew (2021), Yadav and Medhavi (2024), Badrum et al. (2020), and Lliopoulou (2019),\u003c/strong\u003e who highlighted the significance of age-related cognitive development in environmental awareness. The progressive improvement in awareness and behaviors with age may reflect increased exposure to environmental issues and enhanced capacity for abstract thinking about long-term consequences.\u003c/p\u003e\n\u003cp\u003eSurprisingly, in practice scores across age groups, Multiple regression confirmed that age was not a significant predictor of practice scores (p = 0.728), and binary logistic regression showed similar non-significant patterns. This shows the disassociation among awareness-behavior-practice and aligns with findings by \u003cstrong\u003eAhmad et al. (2015),\u003c/strong\u003e who documented weak correlations between awareness and practice (r = 0.217). This gap highlights the complexity of translating environmental awareness into actual practice. Despite improvements in awareness and behaviors with age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparative Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe differential influence patterns of demographic variables of students across awareness, behavior, and practices reveal important insights about the complexity of environmental learning.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAwareness: \u0026nbsp;Influenced by Educational Level and Environmental Access\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAwareness scores were most strongly predicted by area (\u0026beta; = 0.465), followed by grade level (\u0026beta; = 0.230), with modest contributions from gender (\u0026beta; = -0.144) and age (\u0026beta; = 0.065). This pattern suggests that awareness is primarily determined by access to educational resources and environmental information, which are more readily available in urban settings and through formal educational progression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBehaviors: Influenced by Personal and Developmental Factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBehavior scores showed a different pattern, with only age (\u0026beta; = 0.100) and gender (\u0026beta; = 0.106) as significant predictors, while area and grade showed no significant influence. The minimal variance explained (R\u0026sup2; = 0.024) suggests that Behaviors are primarily influenced by individual differences rather than demographic factors, possibly reflecting personal values and family influences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePractices: Contextual Factors Dominate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePractice scores were most strongly predicted by area (\u0026beta; = 0.319) and grade level (\u0026beta; = 0.135), while age and gender showed no significant relationships. This pattern suggests that behavioral implementation depends heavily on contextual factors such as infrastructure availability and educational opportunities for hands-on practice.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study concluded that area disparity is the major highlight for environmental awareness, and practices to remove it, educational intervention programs for rural area students with the required infrastructure and facilities are necessary. Early age of the students is crucial for the students to learn environmental behavior and practices in their habits.\u003c/p\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003eImplications for Environmental Education Policy and Practice\u003c/h2\u003e\u003cp\u003eThese findings have significant implications for environmental education policy and practice. The substantial urban-rural disparities in both awareness and practice indicate a critical need for targeted interventions to address educational equity in environmental learning. Rural students require enhanced access to environmental resources, infrastructure and practical opportunities to develop waste management skills. The influential patterns of socio-demographic variables across dimensions suggest that effective environmental education programs must address all aspects rather than focusing solely on awareness transfer. The finding that behaviors are least predicted by demographic variables suggests the importance of addressing culture and values of individual and family-level factors in environmental education.\u003c/p\u003e\u003cp\u003eThe awareness-behavior-practice gaps, particularly the age-related disconnect in practices, highlight the need for educational approaches that emphasize practical skill development and behavioral implementation, not just awareness and behavior formation.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLimitations and Recommendations\u003c/h3\u003e\n\u003cp\u003eThe study was limited to the 678 middle-stage (6th \u0026ndash; 8th ) grade students of Halol, taluka, Gujarat. The findings may not be generalizable to other geographic regions, cultural contexts, or educational systems due to the specific socio-economic and environmental characteristics of this area. The study only assessed three constructs of environment, namely awareness, behavior, and practices. Future research would benefit from longitudinal designs to track developmental changes over time. A standardized tool could be used to assess environmental behavior to enhance comparability across studies and contexts. External factors, culture, and values should be included in future research related to environmental learning and attitude\u003cb\u003es\u003c/b\u003e to provide a more comprehensive understanding of factors influencing student environmental outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cspan\u003eHuman Ethics and Consent to Participate: The study was approved by the Institutional Ethics Committee for Human Research (IECHR), Faculty of Family and Community Sciences, The Maharaja Sayajirao University of Baroda, India (Approval No. IECHR/FCSc/P.hd/10/2023/03). Informed consent was obtained from all participants before their inclusion in the study. For participants under 18 years, consent was obtained from their parents/guardians and school administrators. The study was conducted per the institutional research committee\u0026apos;s ethical standards and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad, J., Noor, S. M., \u0026amp; Ismail, N. (2015c). Investigating students\u0026rsquo; environmental knowledge, attitude, practice and communication. \u003cem\u003eAsian Social Science\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(16). https://doi.org/10.5539/ass.v11n16p284\u003c/li\u003e\n\u003cli\u003eAjzen, I. (1991b). 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South India Journal of Social Sciences, 22(4), 217\u0026ndash;230. https://doi.org/10.62656/sijss.v22i4.1350\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Environmental awareness, behavior, sustainability, socio-demographic variables, middle-stage students, waste management, urban-rural disparities","lastPublishedDoi":"10.21203/rs.3.rs-7941844/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7941844/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ea)\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Objectives: \u003c/strong\u003eThis study investigates the influence of socio-demographic variables- age, gender, grade level, and area of the school on environmental awareness, behavior, and practices (ABP) among middle-stage students (6\u003csup\u003eth\u003c/sup\u003e – 8\u003csup\u003eth\u003c/sup\u003e grade) in Halol taluka, Gujarat.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb)\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Methods: \u003c/strong\u003eA descriptive research design was used, and data were collected through a validated 128-item questionnaire, with responses analyzed via IBM SPSS Statistics version 20.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec)\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Result: \u003c/strong\u003eResults revealed significant urban-rural disparities, with urban students demonstrating higher awareness (Cohen's d = 1.30), reflecting 38% awareness gap and better waste management practices (odds ratio = 6.22, p \u0026lt; 0.001) than rural counterparts. Grade level strongly predicted awareness (β = 0.230, p \u0026lt; 0.001), while behavior was minimally influenced by area (R\u003csup\u003e2 \u003c/sup\u003e\u003cstrong\u003e= \u003c/strong\u003e0.024). Gender showed females exhibiting more positive behaviors (Cohen's d = 0.33), and age consistently influenced awareness and behavior but not practices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed)\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Conclusion: \u003c/strong\u003eThe findings highlight the need for targeted environmental education interventions, particularly in rural areas, to bridge awareness-practice gaps and foster sustainable behaviors.\u003c/p\u003e","manuscriptTitle":"Impact of socio-demographic variables of students on environmental Awareness, Behavior, and Practices: A case study of Gujarat","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 07:36:31","doi":"10.21203/rs.3.rs-7941844/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ce3c0a9a-3211-4572-82a3-2d6e2dfe70d3","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-29T07:36:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 07:36:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7941844","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7941844","identity":"rs-7941844","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}