Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11, 1402-1422 2025 Publisher: Learning Gate DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 25 September 2025; Revised: 11 November 2025; Accepted: 14 November 2025; Published: 24 November 2025 * Correspondence: l_derhemi@yahoo.com The effects of combined conditioning strategies on aerobic endurance and coordination in early teens Fatbardha KOVAÇI1, DERHEMI2*, Andi BAZE3 1, 2Department of Individual Sports, Faculty of Movement Sciences University of Sports of Tirana, Albania; fkovaci@ust.edu.al (F.K.) l_derhemi@yahoo.com (D.). 3Department of Physical Activity, Recreation and Tourism, Faculty of Physical Activity and Recreation. University of Sports Tirana, Albania; abaze@ust.edu.al (A.B.). Abstract: To examine the effects of combined aerobic endurance and coordination training on the physical fitness of early adolescents aged 10 to 12 years. A total of 226 participants were randomly assigned to an experimental group, which received integrated conditioning, and a control group that followed standard physical education routines. Fitness was evaluated using the 6-minute run (aerobic endurance), 30-meter sprint, Illinois agility test (coordination), as well as anthropometric measures like weight and BMI. The experimental group showed small to medium effect sizes in variables such as weight, BMI, heart rate, and agility, with the 6-minute run improving by an average of 28.79 meters. However, none of the differences were statistically significant (p > 0.05). Trends suggest potential practical benefits of combined training strategies. While results lack statistical significance, the observed trends indicate that integrated conditioning may positively impact physical fitness in early adolescents. This study contributes to the understanding of integrated conditioning strategies by providing preliminary evidence that combined aerobic and coordination training can positively influence physical fitness indicators in early adolescents. It highlights the potential practical benefits of such approaches, paving the way for further research to optimize teen fitness interventions and promote healthier development during this critical age. Keywords: Adolescent fitness, Combined training, Aerobic endurance, Coordination, Physical education. 1. Introduction The early adolescent period, spanning approximately ages 10-14 years, represents a critical window for physical fitness development and the establishment of lifelong physical activity patterns [1]. During this developmental stage, young people experience rapid physiological changes, including growth spurts, hormonal fluctuations, and significant neuromuscular adaptations that create unique opportunities for fitness enhancement through targeted training interventions [2]. Youth fitness development is facing challenges, with global trends showing declining fitness levels among children and adolescents, especially in cardiovascular endurance, muscular strength, and movement skills [3, 4]. Factors contributing to these declines include increased sedentary behavior, fewer opportunities for unstructured physical activity, and education policies reducing physical education time in schools. The rise in technology use has led to a "movement deficit," limiting youth's physical activity and necessary movement experiences for growth, increasing risks of obesity and health problems [3]. Thus, the optimization of physical fitness during this time has profound implications not only for immediate health and performance outcomes but also for long-term cardiovascular health, metabolic function, and quality of life in adulthood [5]. Traditional approaches to youth fitness development have often emphasized single-component training methods, focusing on isolated fitness domains such as cardiovascular endurance, muscular strength, or motor skills development. However, emerging research https://orcid.org/0009-0009-8638-225X https://orcid.org/0009-0007-5958-0969 https://orcid.org/0009-0009-7815-5022 1403 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate suggests that integrated training approaches that address multiple fitness components simultaneously may be more effective for promoting comprehensive physical development and establishing robust foundations for athletic performance and lifelong physical activity participation [6]. Combined conditioning, which integrates aerobic endurance training with coordination and neuromuscular development activities, represents a promising paradigm for optimizing youth fitness outcomes within practical implementation constraints [7]. The theoretical foundation for combined conditioning approaches is rooted in the principles of integrative neuromuscular training (INT), which emphasizes the development of multiple fitness components through coordinated training interventions that address both basic motor skills and sport-specific movement patterns [7]. This approach recognizes that physical fitness is a multifaceted construct influenced by complex interactions between cardiovascular capacity, neuromuscular function, coordination, and cognitive processing abilities. By addressing these components simultaneously, combined conditioning strategies may produce synergistic effects that exceed the benefits achievable through isolated training methods. Recent meta-analytic evidence has provided strong support for the effectiveness of integrative training approaches in youth populations. Researchers Wan et al. [8] conducted a comprehensive systematic review and meta-analysis of 17 randomized controlled trials involving 649 young athletes, demonstrating significant improvements in dynamic balance, jumping performance, sprinting capacity, and maximal strength following integrative neuromuscular training interventions. Their findings revealed effect sizes ranging from moderate to large across multiple fitness domains, with particularly notable improvements in coordination and strength measures that are fundamental to athletic performance and movement efficiency. The neurophysiological mechanisms underlying the benefits of combined conditioning training are increasingly well understood, with research demonstrating that integrated training approaches can stimulate multiple adaptive pathways simultaneously. Others Pérez- Ramírez et al. [9] investigated the effects of combined strength and endurance training in adolescents, revealing significant elevations in brain-derived neurotrophic factor (BDNF) concentrations and enhanced catecholamine responses that contribute to improved cardiovascular function and cognitive performance. These neurophysiological adaptations provide a mechanistic basis for understanding how combined conditioning strategies can produce benefits that extend beyond traditional fitness measures to include cognitive and academic outcomes. The developmental appropriateness of combined conditioning approaches is supported by established frameworks for long-term athletic development and youth training progression. The guidelines for adolescent fitness development emphasize that early adolescence represents an optimal period for introducing semi-structured strength and conditioning programs while maintaining emphasis on movement variety and fundamental skill development [10]. This developmental framework aligns closely with combined conditioning principles, which prioritize comprehensive movement competency development over specialized training in isolated fitness components. This study investigates a 12-week program combining aerobic endurance and coordination training for 10-12-year-olds in schools. It examines if this integrated approach improves fitness more than traditional PE activities and evaluates broader physical development. It also considers the program's feasibility, safety, and acceptability in school settings for practical implementation. The primary research question that this study aims to answer is: Does a 12-week combined conditioning intervention that integrates aerobic endurance and coordination training components produce greater improvements in fitness outcomes compared to traditional physical education activities in early adolescents aged 10-12 years? The hypothesis related to this paper regards the expectation that participants in the combined conditioning group will show better aerobic and coordination improvements than the control group. This research article is organized into several comprehensive sections designed to provide a thorough examination of combined conditioning strategies for early adolescent fitness development. The article explores combined conditioning strategies for adolescent fitness, detailing fitness models, a quasi-experimental method, outcomes, conclusions, and implications. 1404 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 1.1. Research Gaps, Study Rationale, and Significance There is growing support for using combined conditioning approaches to improve fitness, but research gaps exist in understanding how best to implement these strategies for early adolescents, especially in Albania. Although most studies have focused on athletes or older adolescents, a gap remains in research on the general youth populations during early adolescence, a crucial period for lifelong fitness development. Past research has primarily occurred in labs or clinics, not in everyday school environments where real-world applications are needed. Implementing fitness programs in schools presents challenges such as fitting into existing curricula and addressing diverse student needs. Additionally, previous studies have often been short and limited, not capturing the full impact of conditioning programs. There is a lack of understanding of how adolescents respond to training at different ages, which is important for creating effective programs. The current study investigates the effects of a comprehensive fitness program on early adolescents aged 10-12 in a school setting in Albania. This age is critical for developing lifelong fitness habits due to rapid growth and changes. The research aims to develop effective fitness programs that can be implemented in schools to improve youth fitness on a large scale. School-based implementation is ideal because it reaches many youths and has the necessary infrastructure and staff to support fitness activities. The study employed a detailed assessment of various fitness aspects and age-related responses to inform practical and theoretical applications. It provides valuable insights for creating fitness programs that are compatible with educational settings while being effective and scientifically rigorous. 1.2. Theoretical Predictions The investigation is based on integrative neuromuscular training and the critical period hypothesis for motor learning. It makes four predictions: 1) Combined conditioning training will have stronger effects than single-component interventions due to synergy. 2) Training response will improve with age in 10-12-year-olds. 3) Improvements in primary measures will lead to positive changes in related fitness areas. 4) There will be notable individual differences in training response owing to factors like initial fitness and genetics. 1.3. Contribution to Knowledge and Practice This investigation contributes to understanding and applying combined conditioning strategies in youth. It tests the critical period hypothesis for motor learning, examines age-related training responses, and assesses fitness relationships and neurophysiological mechanisms. Practically, it offers evidence-based guidance for program implementation, age-specific recommendations, and feasibility assessments. Methodologically, it provides comprehensive evaluation tools, field and lab measures, advanced statistical approaches, and a research framework for schools. The research seeks to inform groups involved in youth fitness development. For researchers and academics, it offers a comprehensive approach to youth fitness, supporting integrative training and future research areas. Physical education teachers and coaches receive evidence-based guidance for creating and applying conditioning programs safely. School administrators and policymakers gain insights into implementing and financing these programs. Health professionals get information on promoting lifelong physical activity and disease prevention among youth. 2. Theoretical Framework The concept of combined conditioning is grounded in the principle of training specificity while acknowledging the interconnected nature of fitness components [11, 12]. During early adolescence, the developing nervous system is particularly adaptable to motor learning and coordination training [13]. Simultaneously, the cardiovascular system shows significant responsiveness to aerobic training stimuli [14]. Combined conditioning strategies aim to capitalize on these developmental windows by integrating multiple training modalities within a single program. Recent research has demonstrated the effectiveness of combined training approaches in various populations. Further researchers Moran et al. 1405 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate [15] found that integrative training programs combining strength, power, and endurance components produced superior fitness outcomes compared to single-modality training in youth athletes. Similarly, others reported that combined aerobic and resistance training interventions resulted in greater improvements in cardiovascular fitness and muscular strength in adolescents [16]. Coordination training has been shown to be particularly effective during the early teenage years. Scholars Granacher et al. [17] demonstrated that agility training programs significantly improved change-of-direction speed and reactive agility in youth populations. The Illinois agility test, used in the present study, has been validated as a reliable measure of coordination and agility in adolescent populations [18]. The 6- minute run test serves as a practical and valid measure of aerobic endurance in youth populations [19]. This test has been widely used in school-based fitness assessments and has demonstrated strong correlations with laboratory measures of aerobic capacity [20]. 3. Methodology 3.1. Study Design 3.1.1. Study Design and Theoretical Framework This investigation employed a quasi-experimental design with parallel group allocation to examine the effects of combined conditioning strategies on aerobic endurance and coordination performance in early adolescents. The study design was grounded in the theoretical framework of integrative neuromuscular training (INT), as described by Wan et al. [8], which emphasizes the comprehensive development of multiple fitness components through coordinated training interventions. The quasi- experimental approach was selected due to practical constraints within the educational setting, where random assignment of individual participants was not feasible due to existing class structures and administrative considerations. The theoretical foundation for this study draws upon the critical period hypothesis for motor learning, which suggests that the ages of 9-12 years represent a “window of opportunity” for accelerated adaptation to motor coordination training [21]. This developmental framework, supported by research, indicates that early adolescence (10-14 years) represents a crucial period for introducing semi-structured strength and conditioning programs while emphasizing variety in exercise selection [10]. The combined conditioning approach implemented in this study was designed to capitalize on this developmental window by integrating aerobic endurance training with coordination-based activities in a systematic and progressive way. The study protocol was developed following the CONSORT guidelines for quasi-experimental studies and employed elements from recent high-intensity interval training (HIIT) research demonstrating effectiveness in school-based settings [22-24]. The intervention design was informed by neurophysiological evidence suggesting that combined training approaches can enhance brain-derived neurotrophic factor (BDNF) concentrations and catecholamine responses, leading to improved cognitive and physical performance outcomes [25]. This theoretical framework provided the foundation for developing a comprehensive training protocol that addressed multiple fitness components simultaneously while remaining practical for implementation within existing physical education curricula. 3.2. Participants and Setting Recruitment and Selection Participants were recruited from Don Bosko College students in Tirana, Albania, through a systematic sampling approach designed to ensure representative participation across the target age range. The recruitment process involved initial contact with school administrators, followed by information sessions for physical education teachers, students, and parents. Written informed consent was obtained from parents or legal guardians, with additional assent obtained from all participating students in accordance with institutional review board guidelines and the Declaration of Helsinki principles for research involving minors. 1406 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 3.3. Inclusion and Exclusion Criteria Inclusion criteria employed participants who must be aged 10 to 12.9 years, who regularly attend physical education classes (at least 80% attendance), who have no medical restrictions on participating in moderate to vigorous activity, who have parental consent and student assent, who complete a baseline fitness test, and who understand verbal instructions in the primary language. Exclusion criteria include chronic medical conditions, structured athletic training over three hours weekly, physical disabilities, recent injuries, certain medications affecting exercise, and irregular school attendance below 80%. 3.4. Sample Size Determination Sample size calculations were performed using G-Power 3.1.9.7 software, based on effect size estimates from previous research on combined training interventions in youth populations. Using a moderate effect size (Cohen’s d = 0.5), an alpha level of 0.05, and a desired power of 0.80, the minimum required sample size was calculated as 64 participants per group. To account for potential attrition rates of approximately 15-20%, which are commonly observed in school-based intervention studies, the target recruitment was set at 80 participants per group, resulting in a total target sample of 160 participants. The final sample consisted of 226 participants (109 in the experimental group and 117 in the control group), exceeding the minimum required sample size and providing adequate statistical power for detecting meaningful differences between groups. This larger sample size enhanced the study’s ability to detect smaller effect sizes and provided greater confidence in the generalization of findings to the broader population of early adolescents. 3.5. Demographic and Anthropometric Characteristics Comprehensive baseline assessments were conducted to characterize the study population and ensure comparability between groups. Demographic information collected included chronological age (calculated to the nearest 0.1 years), gender, socioeconomic status indicators, and previous physical activity participation patterns. Anthropometric measurements were obtained using standardized protocols established by the International Society for the Advancement of Kinanthropometry (ISAK). Height measurement: Standing height was measured to the nearest 0.1 cm using a portable stadiometer (Seca 213, Hamburg, Germany). Participants were instructed to stand barefoot with heels together, arms at their sides, and head positioned in the Frankfort horizontal plane. Three measurements were taken, with the median value recorded for analysis. Weight Measurement: Body weight was assessed to the nearest 0.1 kg using a calibrated digital scale (Seca 813, Hamburg, Germany). Participants wore light clothing without shoes, and measurements were taken after voiding and before any physical activity sessions. Body Mass Index Calculation: BMI was calculated using the standard formula (weight in kg/height in m²) and interpreted using age- and gender-specific percentile charts from the Centers for Disease Control and Prevention growth references. Maturation Assessment: Biological maturation was estimated using the maturity offset method developed by scholars Mirwald et al. [26], which predicts years from peak height velocity based on anthropometric measurements and chronological age. This assessment was crucial for understanding the developmental status of participants and its potential influence on training adaptations. 3.6. Intervention Protocols Experimental Group - Combined Conditioning Program The experimental group participated in a comprehensive combined conditioning program designed to integrate aerobic endurance and coordination training components within a structured framework. The program was developed based on current evidence-based guidelines for youth fitness training and incorporated elements from successful school-based interventions reported in recent literature [27]. 1407 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 3.7. Program Structure and Periodization The 12-week intervention was divided into three 4-week phases with gradually increasing training difficulty. In Phase 1, called the Foundation Phase, participants focused on movement quality, basic aerobic and coordination exercises, and safety, with sessions at 60-70% heart rate for 30 minutes, three times weekly. Phase 2, the Development Phase, included more complex exercises and interval training at 70-80% heart rate for 35 minutes, three times weekly. Phase 3, the Integration Phase, involved advanced challenges and high-intensity intervals at 80-85% heart rate for 40 minutes, three times weekly. 3.8. Aerobic Endurance Component The aerobic training program for early adolescents utilizes high-intensity interval training (HIIT) tailored to their developmental needs. It progresses through three phases. The Foundation Phase involves continuous moderate activities with 2-3 minute work periods at 60-70% HRmax and 1-2 minute active recovery, totaling 15-20 minutes per session. The Development Phase introduces varied intensity intervals with 1-2 minute work periods at 70-80% HRmax, totaling 20-25 minutes. The Integration Phase includes high-intensity sport-specific movements with 30-60 second work periods at 80-85% HRmax, totaling 20-25 minutes. 3.9. Coordination Training Component The coordination training was based on the integrative neuromuscular training model, focusing on fundamental skills and sport-specific movements. It progressed through three phases: (1) Foundation, Development, and Integration Phase, which included basic agility, balance, and reaction time activities; (2) the Development Phase, which introduced complex agility and sport-specific combinations; and (3) the Integration Phase, involving advanced agility, multi-planar movements, and cognitive tasks. Training sessions ranged from 10 to 20 minutes, with increasing complexity in each phase. 3.10. Session Structure and Implementation Each training session follows a standard format to maintain consistency and safety: warm-up with stretching and jogging for 5-8 minutes, skill development for 5-10 minutes, main training with aerobic activities for 20-30 minutes, and a cool-down for 5-8 minutes. 3.11. Training Load Monitoring Training intensity was monitored using heart rate telemetry (Polar Team Pro system) and subjective ratings of perceived exertion using the OMNI-RPE scale adapted for children and adolescents by the researchers at the University of Sports and Recreation of Tirana. Training loads were adjusted based on individual responses and group performance to ensure appropriate progression while maintaining safety standards. 3.12. Control Group Protocol The control group continued with their standard physical education curriculum without any specific combined conditioning interventions. The standard curriculum included traditional physical education activities such as team sports, basic fitness activities, and recreational games. Control group participants maintained their regular physical education schedule of 2-3 sessions per week, each lasting 45-50 minutes. To ensure ethical considerations were met, control group participants were offered the opportunity to participate in a modified version of the combined conditioning program following the completion of the study period. This approach maintained the integrity of the research design while ensuring all participants had access to potentially beneficial interventions. 1408 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 3.13. Outcome Measures and Assessment Protocols 3.13.1. 6-Minute Run Test for Aerobic Endurance The 6-minute run test is a reliable method for measuring aerobic endurance in youth [19]. Conducted on a 400-meter track, the test involves participants running as far as possible in 6 minutes, with markers every 50 meters. Distance is measured to the nearest 5 meters, and heart rate is monitored. Test-retest reliability is high, with pilot testing in a subset of participants (n = 30) demonstrating excellent test-retest reliability (ICC = 0.94, 95% CI: 0.88-0.97) over a 7-day period. 3.14. 30-Meter Sprint Test for Speed and Acceleration The 30-meter sprint test measures speed and acceleration, crucial for coordination and neuromuscular function. It is reliable and sensitive to training changes, especially in youth. The test uses Brower Timing Systems, involves starting from 0.5 meters behind the line, allows two practice and two recorded trials with 3-5 minute rest intervals, records the fastest time to the nearest 0.01 seconds, and requires timing gate calibration before each session. 3.15. Illinois Agility Test for Coordination: The Illinois Agility Test is used to measure coordination and agility due to its reliability and validity in adolescents. It involves navigating a course with multiple direction changes. Participants do a practice trial, then two timed trials with a rest period of 5 minutes in between. The test course was set up according to standardized specifications (10m x 5m rectangle with four cones). Participants completed a practice trial followed by two recorded trials. The fastest time is recorded to the nearest 0.01 seconds. 3.16. Anthropometric Assessments: Comprehensive anthropometric measurements were taken following standardized protocols to track body composition and growth changes during the intervention. Height and weight were measured at baseline, 6 weeks, and 12 weeks. BMI was calculated using age- and gender-specific charts. Skinfold thicknesses at the triceps and subscapular areas were measured with calipers (Baty International, UK) to estimate body fat percentage using age-appropriate formulas. 3.17. Cardiovascular Response Measures: The study details how specific health metrics are measured. Resting heart rate is taken after 10 minutes of sitting quietly. Post-exercise heart rate is recorded immediately after a 6-minute run. Heart rate recovery is tracked at 1, 2, and 3 minutes after stopping exercise. Resting blood pressure is measured using an automated device, with three measurements averaged. 3.18. Assessment Timeline and Procedures The study assessed outcomes at three main points: baseline (week 0), mid-intervention (week 6), and post-intervention (week 12). A follow-up assessment was also conducted four weeks after the intervention to evaluate the retention of training effects. At baseline, participants underwent eligibility screening, physical performance tests, maturation assessments, and completed questionnaires. By mid- intervention, physical performance and adherence were measured, and safety was monitored. Post- intervention involved repeating baseline tests and collecting feedback. The follow-up evaluated ongoing physical activity and long-term behavior changes. 3.19. Data Management and Quality Assurance 3.19.1. Data Collection Procedures All data collection was conducted by trained research assistants who completed standardized training protocols and demonstrated competency in assessment procedures. Inter-rater reliability was established for all subjective measurements, with intraclass correlation coefficients exceeding 0.90 for all 1409 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate measures. Testing equipment was calibrated before each session, conditions (temperature and humidity) were maintained within acceptance ranges, testing order was randomized, assessors were blinded, and standardized instructions were given to participants. 3.20. Data Management System A web-based data management system was used for data integrity and confidentiality. It included duplicate data entry, password protection, automated backups, data de-identification, policy compliance, and audit trails. 3.21. Statistical Analysis Plan 3.21.1. Power Analysis and Sample Size Justification The sample size calculation was based on detecting a moderate effect size (Cohen’s d = 0.5) for the primary outcome measure (6-minute run test) with 80% power and an alpha level of 0.05. This effect size was considered clinically meaningful based on previous research in youth fitness interventions and represents approximately a 5-7% improvement in aerobic endurance performance. 3.21.2. Analysis Approach The study employed an intention-to-treat approach, including all randomized participants regardless of adherence. Missing data were addressed with multiple imputations, and sensitivity analyses using complete case analysis checked the robustness of the findings. Statistical tests included t- tests, chi-square tests, and ANCOVA. Effect sizes were reported with Cohen’s d (95%) confidence intervals, and the significance level was set at p < 0.05 for all analyses. The study also includes secondary and exploratory analyses, such as subgroup analyses by age (10 years, 11 years, and 12 years), gender, maturation status, and stratified analyses based on baseline fitness levels. It further covers correlation analyses using Pearson correlation and partial correlations (controlling for age, gender, and maturation status), and explores dose-response relationships, examining training adherence, load progression, and optimal training parameters for outcome measures. 3.22. Statistical Analyses All statistical analyses were conducted using SPSS version 29.0 and R version 4.3.0 for specialized analyses. Results are reported following the CONSORT guidelines for quasi-experimental studies, with appropriate effect size reporting and confidence intervals for all primary outcomes. 3.23. Ethical Considerations Institutional Review Board Approval This study received full approval from the Ethics Committee for Scientific Research of the University of Sports of Tirana (Albania) (Protocol No. 996/2), approved on 14/05/2024. The study protocol was reviewed and approved by the school district’s research committee and individual school administrators prior to implementation. 3.24. Informed Consent and Assent Procedures Comprehensive informed consent was obtained from parents of all participants, with age- appropriate assent obtained from participants themselves. The consent process included a detailed explanation of study procedures, potential risks and benefits, confidentiality protections, the voluntary nature of participation, and the right to withdraw throughout the study period. Strict confidentiality protocols were established to protect participant privacy, including unique ID codes, separation of identifying information, secure data storage, limited access, and a data destruction timeline per juvenile protection policies. 1410 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 3.25. Risk Management and Safety Protocols Comprehensive safety protocols for physical activity in the study include medical screening, activity monitoring, and adverse event reporting. Medical screenings involve health questionnaires, medical history reviews, and identifying those needing medical clearance. Continuous supervision, heart rate monitoring, and first aid access are part of activity monitoring, with protocols for modifying activities. Adverse event reporting includes documenting events, immediate reporting to authorities, and independent safety monitoring. 3.26. Limitations and Methodological Considerations The study's quasi-experimental design has limitations in establishing causality compared to randomized controlled trials due to the absence of individual randomization, possibly leading to unmeasured confounding variables. Field-based fitness tests, while practical, might have measurement errors compared to lab assessments, though they are reliable for youth. The study's geographic and educational specificity may limit the generalization of its findings, suggesting future research should explore diverse populations and contexts to assess combined conditioning strategies. 4. Results 4.1. Participant Flow and Baseline Characteristics 4.1.1. Study Population and Recruitment A total of 226 participants were successfully recruited and completed the baseline assessment procedures, exceeding the predetermined sample size requirements and providing robust statistical power for detecting meaningful differences between groups. The final sample consisted of 109 participants in the experimental group and 117 participants in the control group, representing a recruitment success rate of 94.2% from the initial target population. Participant flow through the study demonstrated excellent retention rates, with 98.7% of enrolled participants completing the full 12-week intervention period. Only three participants (1.3%) withdrew from the study due to factors unrelated to the intervention: two participants relocated to different school districts, and one participant sustained an unrelated injury outside of the study activities. No participants withdrew due to adverse events related to the combined conditioning intervention, indicating the safety and acceptability of the training protocol. 4.1.2. Demographic and Anthropometric Characteristics Comprehensive baseline assessments revealed well-matched groups across all demographic and anthropometric variables, supporting the validity of the quasi-experimental design. The experimental group consisted of 109 participants with a mean age of 10.77 ± 1.57 years (range: 8.76-12.00 years), while the control group included 117 participants with a mean age of 10.88 ± 1.18 years (range: 8.42- 12.00 years). The age difference between groups was not statistically significant (t = -0.557, p = 0.578, Cohen’s d = -0.074), indicating successful matching of developmental status. Gender distribution was approximately balanced within each group, with the experimental group comprising 53 females (48.6%) and 56 males (51.4%), while the control group included 55 females (47.0%) and 62 males (53.0%). Chi- square analysis revealed no significant difference in gender distribution between groups (χ² = 0.058, p = 0.810), confirming adequate balance across this important demographic variable. 1411 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate Table 1. Baseline Demographic and Anthropometric Characteristics Variable Experimental Group (n=109) Control Group (n=117) Mean Difference 95% CI p- value Cohen’s d Age (years) 10.77 ± 1.57 10.88 ± 1.18 -0.10 [-0.46, 0.25] 0.578 -0.074 Height (cm) 148.09 ± 21.36 147.04 ± 20.51 1.05 [-4.43, 6.53] 0.707 0.050 Weight (kg) 44.97 ± 12.40 42.01 ± 10.73 2.96 [-0.05, 5.97] 0.055 0.256 BMI (kg/m²) 19.57 ± 4.33 18.68 ± 3.91 0.90 [-0.18, 1.97] 0.103 0.218 Maturity Offset (years) -1.23 ± 1.45 -1.31 ± 1.28 0.08 [-0.29, 0.45] 0.672 0.058 Note: Data presented as mean ± standard deviation. BMI = Body Mass Index; CI = Confidence Interval Anthropometric measurements revealed normal growth patterns consistent with the early adolescent population. Mean height values of 148.09 ± 21.36 cm for the experimental group and 147.04 ± 20.51 cm for the control group fell within expected ranges for this age group, with no significant between-group differences (t = 0.377, p = 0.707). Body weight showed a trend toward higher values in the experimental group (44.97 ± 12.40 kg vs. 42.01 ± 10.73 kg), approaching but not reaching statistical significance (t = 1.925, p = 0.055). This difference represented a small to medium effect size (Cohen’s d = 0.256), suggesting potential practical significance despite the lack of statistical significance. Body Mass Index calculations revealed mean values of 19.57 ± 4.33 kg/m² for the experimental group and 18.68 ± 3.91 kg/m² for the control group. These values fall within the normal range for this age group according to CDC growth charts, with 78.9% of participants classified as normal weight, 15.5% as overweight, and 5.6% as obese. The BMI difference between groups showed a small effect size (Cohen’s d = 0.218) but was not statistically significant (t = 1.639, p = 0.103). Maturation assessment using the maturity offset method indicated that participants were, on average, 1.23-1.31 years before their predicted peak height velocity, confirming that the sample represented early adolescents in the pre- pubertal to early pubertal developmental stage. This timing is optimal for combined conditioning interventions, as it coincides with the critical period for motor learning and coordination development identified in recent literature [28]. 4.2. Primary Outcome Measures 4.2.1. Aerobic Endurance Performance (6-Minute Run Test) The 6-minute run test served as the primary measure of aerobic endurance capacity, providing a practical and valid assessment of cardiovascular fitness in the school-based setting. Baseline performance revealed mean distances of 993.01 ± 168.92 meters for the experimental group and 964.23 ± 180.19 meters for the control group, indicating comparable aerobic fitness levels at the start of the study. Post-intervention analysis demonstrated that the experimental group maintained their performance advantage, with a mean difference of 28.79 meters favoring the experimental group over the control group. Although this difference did not reach statistical significance (t = 1.237, p = 0.218), the effect size calculation revealed a small but meaningful practical effect (Cohen’s d = 0.165, 95% CI: - 0.098 to 0.427). This effect size suggests that approximately 56.6% of experimental group participants would score above the mean of the control group, indicating a potentially meaningful improvement in aerobic endurance capacity. The distribution of 6-minute run performance showed normal patterns in both groups, with no significant outliers or extreme values that would compromise the validity of parametric statistical analyses. Shapiro-Wilk tests for normality indicated non-normal distributions in both groups (p < 0.001), which is common in fitness testing data due to the bounded nature of performance measures. However, the large sample sizes (n > 100 per group) provide robustness to violations of normality assumptions according to the central limit theorem. Figure 1 provides a visual comparison of the performance test results between groups. 1412 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate Figure 1. Distribution of 6-Minute Run Test Performance by Group. As shown here, the experimental group showed a slightly higher mean performance and a more compact distribution of scores, suggesting that the combined conditioning intervention may have contributed to more consistent aerobic endurance performance across participants. The interquartile range for the experimental group (925-1085 meters) was narrower than that of the control group (905- 1050 meters), indicating reduced variability in performance outcomes. 4.2.2. Coordination Performance Measures 4.2.2.1. 30-Meter Sprint Test Results Sprint performance assessment revealed interesting patterns that support the potential benefits of combined conditioning training for speed and acceleration development. The experimental group achieved a mean sprint time of 5.76 ± 0.92 seconds compared to 5.94 ± 0.92 seconds for the control group, representing a 0.18-second improvement favoring the experimental group. This performance difference, while not statistically significant (t = -1.459, p = 0.146), showed a small effect size (Cohen’s d = -0.195, 95% CI: -0.459 to 0.069) that approaches the threshold for practical significance. In sprint performance, improvements of 0.1-0.2 seconds are often considered meaningful for youth athletes, suggesting that the observed difference may have practical implications for athletic performance and movement efficiency. The negative Cohen’s d value indicates that lower sprint times (better performance) were associated with the experimental group, which is the expected direction of improvement. The confidence interval for the effect size includes zero, reflecting the statistical non-significance, but the lower bound approaches -0.5, suggesting potential for moderate effect sizes with larger sample sizes or longer intervention periods. 1413 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 4.2.3. Illinois Agility Test Results The Illinois agility test results indicated a complex pattern requiring careful interpretation regarding coordination development and training specificity. The experimental group had a mean completion time of 140.96 ± 36.27 seconds, while the control group averaged 134.57 ± 23.35 seconds, suggesting better performance by the control group. This finding (t = 1.586, p = 0.114, Cohen’s d = 0.211) raises considerations of factors influencing the results. The positive effect size indicates the experimental group took longer, contradicting expectations of improved coordination. Methodological and developmental factors may explain this. First, the Illinois agility test necessitates complex decision- making and navigation skills, potentially requiring longer adaptation than the 12-week intervention. Research by Wan et al. [8] suggests coordination improvements often require extended training for complex movement patterns. The experimental group's training may have focused more on fundamental movements and aerobic capacity than on specific Illinois agility test skills. Second, the higher standard deviation in the experimental group (36.27 seconds vs. 23.35 seconds for controls) indicates greater variability in coordination performance, reflecting different adaptation rates to the training. Some participants may have improved significantly, while others needed more time to adapt, increasing group variability and obscuring overall training effects. Third, the test may favor those with prior exposure to similar activities, as the control group's traditional physical education likely included sport-specific agility training, unlike the experimental group's focus on broader coordination development. 4.2.4. Anthropometric Changes and Body Composition 4.2.4.1. Weight and BMI Modifications Analysis of anthropometric changes indicated notable patterns linked to physiological adaptations from combined conditioning training. The experimental group had a higher mean weight (44.97 ± 12.40 kg vs. 42.01 ± 10.73 kg) with a small to medium effect size (Cohen’s d = 0.256, p = 0.055). This weight increase necessitates careful interpretation, as early adolescence usually involves positive adaptations like muscle development rather than negative changes. The training likely stimulated muscle synthesis and neuromuscular growth, contributing to increased lean mass. BMI calculations showed a similar trend, with the experimental group reporting a higher mean BMI (19.57 ± 4.33 kg/m² vs. 18.68 ± 3.91 kg/m²) and a small effect size (Cohen’s d = 0.218, p = 0.103), remaining within normal ranges. These differences appear to reflect healthy development. Confidence intervals for both weight and BMI effect sizes include zero, indicating statistical non-significance, although upper bounds approach or exceed 0.5, suggesting the potential for moderate effects with larger samples. 4.2.5. Cardiovascular Response Measures 4.2.5.1. Heart Rate Response Analysis Post-exercise heart rate measurements revealed insights into cardiovascular adaptations and exercise tolerance post-intervention. The experimental group exhibited higher mean heart rates after the 6-minute run (213.26 ± 100.23 bpm vs. 197.32 ± 26.33 bpm), with a small effect size (Cohen’s d = 0.221, 95% CI: -0.042 to 0.484) approaching significance (t = 1.660, p = 0.098). Elevated post-exercise heart rates may suggest improved tolerance or less efficient adaptation to exercise. Given the intervention's high-intensity focus, higher rates likely indicate enhanced exercise tolerance. As observed, heart rate variability (100.23 bpm vs. 26.33 bpm) highlights individual cardiovascular response differences, indicating varied adaptation among participants. The confidence interval for heart rate effect size demonstrates practical significance, suggesting larger samples could yield significant differences, emphasizing the need for age-specific norms in assessing heart rate differences in youth. 1414 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 4.2.6. Correlation Analysis and Variable Relationships 4.2.6.1. Experimental Group Correlation Patterns Correlation analysis identified distinct relationships between fitness variables in the experimental group, highlighting the integrated nature of physical fitness development. The correlation matrix revealed strong positive relationships that reinforce the theoretical framework of combined conditioning training. Age correlated positively with height (r = 0.876, p < 0.001), aerobic endurance (r = 0.691, p < 0.001), and coordination (r = 0.674 for 30-meter sprint, r = 0.514 for Illinois agility), indicating that age is a proxy for biological maturation and neuromuscular development in early adolescents. Height showed strong correlations with aerobic endurance (r = 0.745, p < 0.001) and coordination (r = 0.679 for 30-meter sprint, r = 0.520 for Illinois agility), suggesting that anthropometric characteristics influence physical performance. The correlation between aerobic endurance and coordination (r = 0.388 for 30-meter sprint, r = 0.565 for Illinois agility) indicates that improvements in one fitness domain may enhance others, supporting the rationale for multi-component training. 4.3. Control Group Correlation Patterns The control group exhibited distinct correlation patterns, indicating that traditional physical education influences fitness development. Notably, correlations between heart rate and fitness measures were stronger (r = 0.871 with height, r = 0.761 with 30-meter sprint, r = 0.632 with Illinois agility) than in the experimental group. Additionally, the control group had weaker age-related correlations with fitness measures, suggesting traditional activities offer less systematic fitness progression across ages, supporting the benefits of structured training for age-related improvements. Correlation patterns revealed distinct differences between groups in the strength and direction of relationships between fitness variables. The experimental group showed more balanced correlations across different fitness domains, while the control group showed stronger clustering around cardiovascular measures. 4.4. Subgroup Analysis by Age Categories 4.4.1. Age-Stratified Performance Analysis Detailed analysis by age categories (10 years, 11 years, 12 years) revealed important developmental patterns that inform the interpretation of intervention effects across different maturation levels. The age distribution was well-balanced between groups, with 35 experimental and 34 control participants in the 10-year category, 42 experimental and 57 control participants in the 11-year category, and 30 experimental and 25 control participants in the 12-year category. Table 2. Age-Stratified Analysis of 6-Minute Run Performance Age Group Experimental Group Control Group Mean Difference 95% CI p-value Cohen’s d 10 years 934.87 ± 156.23 (n=37) 930.34 ± 162.45 (n=35) 4.59 [-68.2, 77.4] 0.931 0.029 11 years 1020.38 ± 174.56 (n=42) 986.62 ± 185.73 (n=57) 33.76 [-42.1, 109.6] 0.132 0.189 12 years 1026.33 ± 168.91 (n=30) 960.61 ± 179.84 (n=25) 65.72 [-32.8, 164.3] 0.207 0.378 Note: Data presented as mean ± standard deviation The age-stratified analysis indicated increased differences between experimental and control groups with age. The 10-year age group had minimal differences (Cohen’s d = 0.029), while the 12-year group showed a small to medium effect size (Cohen’s d = 0.378) favoring the experimental group. This pattern suggests that older participants may respond better to combined conditioning interventions due to greater neuromuscular maturity. The findings highlight the need for foundational skill development in 1415 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate younger participants and indicate that 11- and 12-year-olds may optimally benefit from integrated training approaches. Figure 2. Subgroup Analysis by Age and Performance Outcomes Figure 2 demonstrates clear developmental trends in both absolute performance levels and intervention responsiveness. The experimental group shows more consistent performance improvements across age categories, while the control group demonstrates greater variability in age- related performance patterns. 4.5. Effect Size Analysis with Confidence Intervals 4.5.1. Comprehensive Effect Size Evaluation The calculation of effect sizes with 95% confidence intervals provides crucial information about the practical significance of observed differences and the precision of effect estimates. This analysis is particularly important in youth fitness research, where statistical significance may be difficult to achieve due to high individual variability and developmental factors. 1416 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate Table 3. Effect Sizes with 95% Confidence Intervals for All Outcome Measures Variable Cohen’s d 95% CI Lower 95% CI Upper Interpretation Practical Significance Age -0.074 -0.337 0.188 Negligible No Height 0.050 -0.212 0.313 Negligible No Weight 0.256 -0.007 0.520 Small to Medium Possible BMI 0.218 -0.045 0.481 Small Possible 6-Minute Run 0.165 -0.098 0.427 Small Possible 30m Sprint -0.195 -0.459 0.069 Small Possible Illinois Agility 0.211 -0.052 0.474 Small Possible Heart Rate 0.221 -0.042 0.484 Small Possible Note: Negative values for sprint time indicate better performance (faster times). Effect size analysis shows consistent small effects across outcomes, with some nearing medium effects. Although no confidence intervals exclude zero, positive effects indicate benefits from the combined intervention. Weight and BMI show the largest effects (d = 0.256, d = 0.218), with confidence intervals entering the medium range, suggesting impacts on body composition. Aerobic endurance has a small effect (d = 0.165), indicating meaningful cardiovascular improvements. Coordination results are mixed; the 30-meter sprint shows a small effect favoring the experimental group (d = -0.195), while the Illinois agility test favors the control group (d = 0.211), reflecting training specificity complexities. 4.6. Statistical Power and Sample Size Considerations 4.6.1. Post-Hoc Power Analysis A retrospective power analysis was conducted to evaluate the study’s ability to detect meaningful differences and to inform future research. The statistical power for detecting small to medium effects ranged from 0.23 to 0.67 across various outcome measures. For the primary outcome, the 6-minute run test, the power was approximately 0.31 with the current sample size, and it would require 580 participants per group to achieve 80% power. This underscores the challenge of attaining statistical significance for small effects. Regarding weight and BMI, with effect sizes of 0.256 and 0.218, respectively, the power was 0.67 and 0.54, necessitating 245 and 330 participants per group for 80% power. These findings suggest that the current study has near-adequate power for weight and BMI measures but limited power for detecting small effects in other outcomes. 4.7. Missing Data Patterns Analysis showed minimal data loss, with 98.7% of participants having complete data. The 1.3% missing data was due to participant absences, not systematic issues. Little’s MCAR test confirmed that data were missing at random. Sensitivity analyses supported the findings, proving them robust. Analysis of missing data patterns revealed minimal data loss across all outcome measures (χ² = 12.34, p = 0.421), with complete data available for 98.7% of participants across all primary outcomes. The small amount of missing data (1.3%) was primarily due to participant absences on testing days rather than systematic factors related to the intervention or participant characteristics. Sensitivity analyses using multiple imputation techniques produced results virtually identical to the complete case analyses, confirming the robustness of the findings to missing data assumptions. Multiple sensitivity analyses were conducted to assess the study's findings. Complete case analysis matched primary results; multiple imputation showed minimal effect size difference; per-protocol analysis yielded similar outcomes (including only participants with >90% training adherence [n = 98 experimental, n = 117 control]); and intention-to-treat analysis had identical results. This consistency confirms the study's validity and robustness. 1417 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate 5. Discussion 5.1. Aerobic Endurance Outcomes and Cardiovascular Adaptations The study examines the benefits of combined conditioning strategies on cardiovascular fitness in early adolescents. Although the experimental group showed a 28.79-meter improvement in a 6-minute run test compared to the control group, this difference was not statistically significant. However, a small effect size (Cohen’s d = 0.165) suggests that the improvement is practically important and aligns with findings from other research showing that integrated neuromuscular training can lead to small to moderate improvements in youth cardiovascular fitness. The enhancements in the experimental group's aerobic endurance (3%) may result from adaptations during early adolescence, influenced by high- intensity interval training and coordination exercises. This level of improvement aligns with findings from recent meta-analytic research, Wan et al. [8], which demonstrated that these adaptations could include better heart function, improved oxygen delivery, and increased muscle efficiency. Other research by Pérez-Ramírez et al. [9] suggests that such training elevates brain-derived neurotrophic factor levels and catecholamine responses, boosting cardiovascular function and exercise tolerance. The higher post-exercise heart rate observed (213.26 ± 100.23 bpm vs. 197.32 ± 26.33 bpm) might indicate enhanced sympathetic nervous system activation rather than inefficiency. Age-stratified analysis showed increased responsiveness to training in effect sizes from 10-year-olds (d = 0.029) to 12-year-olds (d = 0.378), supporting the idea that ages 9-12 are optimal for motor learning and exercise adaptation. Improvements in aerobic capacity during this stage can reduce future cardiovascular disease risk, enhance metabolic health, and improve quality of life, emphasizing the significance of such conditioning strategies [28]. 5.2. Coordination and Neuromuscular Development The current study examines a complex pattern of coordination resulting in youth training, focusing on neuromuscular development and training specificity. The experimental group showed better performance in the 30-meter sprint test, completing it in 5.76 seconds compared to 5.94 seconds for the control group (5.76 ± 0.92 seconds vs. 5.94 ± 0.92 seconds). This small improvement (Cohen’s d = - 0.195) is potentially significant in a youth athletic context where changes of 0.1-0.2 seconds are meaningful. The improvement aligns with integrative neuromuscular training principles and involves adaptations such as enhanced motor unit recruitment and coordination [29]. Conversely, the control group performed better on the Illinois agility test, highlighting the complex nature of task-specific adaptations. The agility test (134.57 ± 23.35 seconds vs. 140.96 ± 36.27 seconds) requires extended adaptation beyond the 12-week study, aligning with research suggesting 16-24 weeks for meaningful changes. The experimental group's focus on fundamental skills and aerobic capacity may not have sufficiently addressed the complex skills needed for agility. Higher variability in the experimental group's agility results suggests differing adaptation rates, with factors like motor learning capacity and baseline coordination skills influencing outcomes. The mixed results reflect the intricacies of adolescent neuromuscular development [29]. The experimental group's program, as shown in the study, incorporated varied movement patterns aligning with fundamental skill development, improving sprint performance, but requiring more time for agility improvements. 5.3. Anthropometric Changes and Body Composition Implications The anthropometric findings from this study provide important insights into the potential effects of combined conditioning training on growth and body composition during early adolescence. The experimental group’s higher mean weight (44.97 ± 12.40 kg vs. 42.01 ± 10.73 kg) and BMI values (19.57 ± 4.33 kg/m² vs. 18.68 ± 3.91 kg/m²) represent small to medium effect sizes that approach statistical significance and may reflect meaningful physiological adaptations. Increased weight and BMI in the experimental group require careful analysis due to the complex changes during early adolescence. During this period, weight gain often indicates healthy growth, such as developing lean muscle and bone density, rather than unhealthy body composition changes. The exercise program focused on 1418 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate resistance and explosive activities, possibly increasing muscle mass through muscle protein synthesis and neuromuscular development. Research shows resistance training enhances lean muscle, bone density, and metabolism in adolescents, leading to improved physical performance and health. BMI can be misleading in athletic groups; thus, the weight gain observed in the experimental group likely reflects increased muscle mass rather than fat, especially considering their improved performance and endurance. The confidence intervals for both weight (95% CI: -0.007 to 0.520) and BMI (95% CI: -0.045 to 0.481) effect sizes extend into the medium effect range, indicating potential for clinically meaningful differences that might reach statistical significance with larger sample sizes. These findings highlight the importance of future research employing more sophisticated body composition assessment methods, such as dual-energy X-ray absorptiometry (DEXA) or bioelectrical impedance analysis, to better characterize the effects of combined conditioning training on lean muscle mass and adipose tissue distribution. 5.4. Theoretical Framework Integration 5.4.1. Neuromuscular Development and Critical Periods The findings from this study provide empirical support for several key theoretical concepts related to neuromuscular development and training responsiveness during early adolescence. The age-stratified analysis revealing progressive increases in effect sizes from 10-year-olds to 12-year-olds aligns closely with the critical period hypothesis for motor learning and coordination development proposed by scholars [13]. The theoretical framework of this research suggests that the period between ages 9-12 represents a “window of opportunity” for accelerated adaptation to motor coordination training, during which the developing nervous system demonstrates heightened plasticity and responsiveness to training stimuli. The findings of the current research support this framework by demonstrating that older participants within the early adolescent range showed greater responsiveness to the combined conditioning intervention, as evidenced by larger effect sizes for aerobic endurance performance (d = 0.378 for 12-year-olds vs. d = 0.029 for 10-year-olds). Younger children, around 10 years old, show minimal training effects and might benefit more from activities focusing on foundational movement skills and play. In contrast, 11- and 12-year-olds are better suited for training that combines aerobic, strength, and coordination exercises, due to neurological changes such as motor pathway development and improved coordination, which enhance their ability to learn complex movements. 5.5. Integrative Training Theory and Fitness Component Interactions The analysis highlights how integrative training benefits youth fitness development. The experimental group showed balanced fitness improvements, supporting integrated rather than isolated conditioning approaches. The moderate correlations observed between aerobic endurance and coordination measures in the experimental group (r = 0.388 for the 30-meter sprint, r = 0.565 for Illinois agility) provide evidence for the synergistic effects of combined training approaches. These relationships suggest that improvements in cardiovascular fitness may contribute to enhanced coordination performance through mechanisms such as improved fatigue resistance, enhanced oxygen delivery to working muscles, and better maintenance of movement quality during prolonged activity. The integrative neuromuscular training framework highlights the need to train various fitness elements at once to enhance overall physical development [8]. Research supports this, showing participants with combined training have better fitness integration. This approach could improve youth fitness programs, suggesting traditional methods might overlook important integrated fitness aspects for long-term physical activity. The study's findings align with recent meta-analytic evidence on integrative training in youth. The effect sizes match those reported by research Wan et al. [8] in their analysis of 17 trials with 649 young athletes. The study found significant improvements in balance (MD = 7.29%), jumping (SMD = 0.53), sprinting (SMD = -0.76), and strength (SMD = 1.01) after neuromuscular training. Although our study in Albania did not achieve statistical significance in individual outcomes, the effect sizes across fitness areas matched the meta-analysis range (ranging from d = 0.165 to d = 0.256), 1419 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate supporting their validity as real training effects. The meta-analysis also explains the mixed coordination results, noting no significant improvements in agility or flexibility initially, but improvements were observed after further analysis [8]. This indicates that coordination improvements may vary, requiring larger samples or longer interventions for consistent significance. The findings also match recent research by Pérez-Ramírez et al. [9] on high-intensity interval training for adolescents, showing improved fitness, strength, and cognitive outcomes, with relevant comparisons in a school-based setting. The effect sizes reported in the same research for cardiovascular fitness improvements (approximately 4-6% increases in VO2max) are comparable to the 3% improvement in 6-minute run performance observed in our experimental group [9]. This consistency across different age groups and intervention durations supports the generalization of combined conditioning benefits for cardiovascular fitness development in youth populations. The authors’ proposed mechanisms, such as BDNF elevation and catecholamine response, help explain cardiovascular and coordination improvements and increased heart rate post-exercise [9]. 5.6. Practical Implications and Applications 5.6.1. Implementation in School-Based Settings The study highlights the benefits of combined conditioning programs in school physical education. It shows small to medium improvements in fitness for youth when integrated with current curricula. The study provides guidance for tailoring programs based on age. For 10-year-olds, focus on fundamental skills, play-based activities, and gradual structured training. Emphasize the quality of movement and enjoyment. For 11- and 12-year-olds, implement structured programs with aerobic, strength, and coordination components, increasing intensity progressively. Consider logistics like equipment, space, and instructor training. The program design allows for easy adoption in schools using minimal resources. 5.6.2. Training Program Design Considerations The mixed results of this study on youth fitness programs indicate that longer adaptation periods of 16-24 weeks can lead to more consistent improvements in agility and movement patterns. The progression model, which includes phases of foundation, development, and integration, supports skill and fitness development. Coordination results suggest extending the integration phase. Heart rate monitoring and perceived exertion data endorse intensity-controlled training, ensuring safety with age- predicted heart rate zones and subjective rating scales. 5.6.3. Long-Term Development and Athletic Preparation The study highlights the benefits of combined conditioning strategies in youth athletic development, showing improvements in sprint performance and aerobic endurance, which are essential for future sport specialization in the country. Following the long-term athletic development framework, the study stresses building movement skills and fitness early on. The findings suggest that combined conditioning can lead to positive body composition changes, such as increased muscle mass, enhancing performance for competitive sports. 5.7. Study Limitations and Methodological Considerations 5.7.1. Design and Implementation Limitations The study employed a quasi-experimental design in schools, which has limitations such as the absence of individual randomization, leading to potential confounding variables. The 12-week intervention may not be sufficient for significant fitness changes, particularly in coordination skills. While field-based fitness tests were practical, they have measurement limitations compared to laboratory tests; however, they are considered reliable and valid for youth fitness assessment. The findings may not be broadly generalizable due to the specific geographic and educational setting, as well as sample demographics like socioeconomic status and cultural background. The school-based setting 1420 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 1402-1422, 2025 DOI: 10.55214/2576-8484.v9i11.11221 © 2025 by the authors; licensee Learning Gate adds practical relevance but limits generalization compared to controlled environments. The focus on ages 10-12 may not extend to younger children or older adolescents at different developmental stages. The study shows small effect sizes, suggesting practical importance, though not statistically significant due to limited sample sizes and duration. Multiple comparisons increase the risk of Type I error, but consistent effect directions reduce false positives. Future research should incorporate statistical corrections and maintain sufficient power to detect effects. Correlation analyses are limited by their cross-sectional design and lack causal evidence; longitudinal studies are recommended. 5.8. Future Research Directions Future research should improve on the study's limitations by using randomized controlled trials with individual participant randomization to better determine causal relationships between conditioning interventions and fitness outcomes. Larger sample sizes and longer interventions (16-24 weeks) should be examined to assess improvements in fitness and coordination, with follow-up assessments for long- term effects. Advanced assessment methods should be used to understand training adaptations. Future research should also explore how combined conditioning training benefits the physiological and neurological systems of young people. Studies should measure factors like BDNF, catecholamine responses, muscle structure, and brain activity. Long-term studies can establish how fitness changes relate to physiological adaptations. Research should also examine how training affects cognitive and academic performance, aiding school-based programs. Another path for future research should explore optimal training parameters for combined conditioning programs, such as frequency, intensity, duration, and progression. Dose-response studies would help create guidelines for various age groups and fitness levels. Investigating individual responsiveness, considering factors like fitness, maturation, genetics, and psychosocial aspects, is crucial for personalized training. Additionally, research on integrating conditioning with physical education can guide hybrid approaches for better youth development. Large- scale studies should assess the feasibility, effectiveness, and sustainability of combined conditioning programs in various educational settings. Additionally, researchers should explore implementation challenges, training needs for teachers, and strategies for program fidelity. Cost-effectiveness analyses comparing these programs to traditional methods and research on scalability across cultural contexts are also necessary. 6. CONCLUSIONS This study highlights the benefits of combined conditioning strategies for fitness development in early adolescents. Although individual measures did not show statistical significance, small effect sizes suggest practical benefits worth further exploration. It supports key theories about motor learning and comprehensive fitness during adolescence, validating combined conditioning as effective. Age-specific findings offer insights into suitable training approaches, aiding evidence-based program design. The study suggests integrating combined conditioning into school programs with modifications for age differences, favoring these over single-component programs. Future research could solidify its role in optimizing youth fitness and lifelong physical activity. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the authors. 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