Introduction

Epidemiological evidence increasingly indicates that declining physical fitness contributes to a growing health burden in China1. Physical fitness, defined as a set of attributes that determine the ability to perform physical activity, encompasses two primary domains: health-related and skill-related fitness2. Health-related fitness includes cardiorespiratory fitness, musculoskeletal fitness (including muscular strength and endurance), body composition, and flexibility, all of which are directly associated with overall health3,4. Skill-related fitness, reflecting abilities relevant for sports or occupational performance, is associated with motor skills and includes components such as speed, power, coordination, agility, and balance5,6. Physical fitness in childhood is integral to a broad spectrum of health benefits, including cardiovascular, metabolic, skeletal, and psychological well-being7,8,9.

Abnormal physical posture, defined as a significant deviation from optimal body segment alignment, has become a major public health issue among children10,11. Evidence suggests a high prevalence of this condition, with some studies reporting that up to 68% of children exhibit at least one postural abnormality, such as forward head posture (FHP) or uneven shoulders12,13,14. Notably, cross-sectional studies have reported abnormal physical posture rates of 30–50% in primary school children in some countries12,15. Abnormal physical posture, often indicative of underlying sensorimotor dysfunction, can lead to negative outcomes including musculoskeletal pain, reduced cardiorespiratory function, and decreased physical endurance16,17.

Muscle-strengthening exercise (MSE) is fundamental for developing musculoskeletal fitness and addressing neuromuscular deficits underlying abnormal posture18,19,20,21. Functional training, an MSE variant emphasizing multi-joint, movement-pattern-based exercises, offers a theoretically promising approach for simultaneously improving physical fitness and postural health by enhancing core stability and movement efficiency22,23,24. Distinct from traditional resistance training, which isolates single muscle groups along fixed trajectories25, this approach closely replicates actual sports movements. Furthermore, it has been proven to offer unique advantages for improving athletic performance22,26,27,28. These characteristics position functional training as a viable and promising approach for improving overall physical fitness and postural health in school-aged children.

Although evidence suggests that MSE can improve physical fitness and postural health, the quality of this evidence is limited by small sample sizes26,29,30, reliance on specialized athletic training programs rather than integrated curricular approaches26,29,31,32, and a predominance of studies involving clinical populations or adolescents rather than children25,33,34,35,36. To our knowledge, no MSE intervention has yet developed exercise protocols that simultaneously target physical fitness and postural health using functional training among primary-school children.

Given the limited high-quality evidence and uncertainties regarding the effectiveness of functional training in school-based children, this study evaluated the impact of integrating functional training into school physical education (PE) on both physical fitness and postural health. It was hypothesized that functional training would simultaneously enhance these outcomes due to their biomechanical interdependence. These findings may inform the development of scalable, evidence-based public health policies to address the dual burden of declining physical fitness and postural health among school-aged children.

Methods

Study design and participants

This intervention study was conducted among fifth-grade students (aged 9–11 years) from two demographically matched primary schools in Beijing, who were assigned to either the intervention or the control group (1:1 allocation). Inclusion criteria were: (1) age 9–11 years and enrolled in the 5th grade of elementary school, and (2) ability to complete baseline health assessment and questionnaires. Exclusion criteria included: (1) physical disabilities preventing participation in school PE, (2) planning to transfer schools within a year, and (3) severe mental health conditions impairing compliance with study procedures. Participants were recruited between April and June 2024, with the intervention implemented in September 2024 and the first follow-up conducted in December 2024, resulting in a total intervention duration of 16 weeks (see Fig. 1). This 16-week duration, corresponding to one academic semester, was selected based on previous school-based interventions demonstrating its sufficiency for inducing meaningful changes in children’s physical health outcomes25,37,38. The intervention was delivered by four in-service PE teachers, all of whom held a bachelor’s degree in physical education and were initially employed by the participating schools. Each teacher was responsible for teaching four to five classes of fifth-grade students. Due to the nature of the behavioral intervention, the PE teachers were aware of group allocation, while participants, their families, and the outcome assessors and statisticians remained blinded.

Sample size determination

The sample size was calculated to detect a clinically meaningful difference of 0.1 standard deviations in Physical Fitness Indicators (PFI) scores with 95% power at a two-sided alpha of 0.05. The initial sample size (n₁) for an individually randomized trial was estimated using G*Power. This initial estimate was then multiplied by the design effect (DE = 1 + (m − 1) * ICC), where m = 30 (average cluster size) and ICC = 0.02, to account for school-level clustering39. The resulting sample size was then increased by 20% to compensate for an anticipated attrition rate, which was assumed due to potential survey non-participation during the final exam week at the end of the semester, especially for the questionnaire investigation. This adjustment yielded a final target of 520 participants per group. Oversampling was used, yielding 601 participants in the intervention group and 685 in the control group. This approach provided sufficient power to detect the predefined clinically meaningful difference in physical fitness scores between the groups.

Fig. 1
figure 1

Flow diagram of study participants.

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Intervention

The intervention protocol, detailed in Fig. 2 and the Appendix, was developed in January 2024 by a multidisciplinary expert panel, including specialists in sports science and child and adolescent health. The intervention was designed using the SAAFE (Supportive, Active, Autonomous, Fair, Enjoyable) framework40 to address students’ basic psychological needs and self-determination41 (the application of the SAAFE framework was presented in Appendix Table 2). The panel designed four exercise modules tailored to integrate seamlessly with regular school PE frameworks. Pilot tests were conducted between May and July 2024 at the same intervention schools that participated in this study. The PE teachers who subsequently delivered the intervention participated in the pilot testing, and their feedback was incorporated to refine the protocol and enhance feasibility and implementation quality. Before implementation, the PE teachers in the intervention group underwent standardized training to ensure fidelity to the protocol. This training was delivered by professors and experts specializing in functional training for children and physical education. The professors first taught the teachers the standard techniques for each exercise, and then trained them in the class procedures and key considerations according to the SAAFE framework. The control group continued their usual PE classes, which were matched in duration (3 × 40 min per week) to the intervention group.

Fig. 2
figure 2

Diagram of intervention design and implementation.

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Measurement and outcomes

All outcome assessments were conducted on-site at the participating schools. Physical fitness assessments and physical examinations were performed in the schools’ sports halls. To ensure consistency across groups and measurement time points, questionnaires were administered under standardized protocols in standard computer rooms, where students completed them collectively under supervision. Assessments were conducted at baseline (pre-test) and 16 weeks of follow-up (post-treatment), including:

Physical examinations: height, weight, body mass index, and postural health

Height, weight, and postural health were measured by trained staff using a standardized procedure. Height and weight were measured while students wore light clothing and stood barefoot, with height recorded to the nearest 0.1 cm and weight to the nearest 0.1 kg. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared (kg/m2). The BMI status was classified as thinness, normal weight, or overweight/obesity (OWOB) according to age- and sex-specific Chinese BMI percentiles42.

Postural health was one of the primary outcomes assessed using two indicators: FHP and uneven shoulders. The degree of FHP was measured with participants in a lateral standing position. The landmarks of the seventh cervical vertebra (C7) and the tragus were identified. A horizontal line was drawn parallel to the ground from C7, and the craniovertebral angle (CVA) was measured. The CVA ≥ 50° was considered normal, while < 50° was classified as FHP43. For uneven shoulders, grid paper was affixed to the wall, and participants stood barefoot with their backs to the paper in their habitual standing position. The bilateral acromion points were marked, and a height difference of > 1 cm between shoulders was defined as uneven shoulders44. Additionally, a postural health multimorbidity index (normal, only FHP, only uneven shoulders, FHP & uneven shoulders) was constructed to analyze the intervention’s effectiveness on postural changes over time.

Physical fitness tests

The assessment of PFI was one of the primary outcomes. Physical fitness was measured by standardized tests organized by the education department at the end of each semester, comprising the following components1:

Cardiorespiratory fitness: Forced vital capacity (ml). Children’s forced vital capacity was assessed via spirometry in a quiet setting. Forced vital capacity is defined as the maximum volume of air (measured in milliliters) a child can expel from his or her lungs after a maximum inhalation. The test was repeated three times on each child, and their best performance from the three tests was recorded.

Muscular strength: Sit-ups (reps/min). Children were instructed to perform a 1-minute sit-up test. The protocol required that children lie in a supine position, with their knees bent and feet flat on a floor mat (secured by the test examiner), and their hands placed on the back of the head, fingers crossed. During the performance, children were also instructed to elevate their trunks until their elbows contacted their thighs and then return to the starting position by lowering their shoulder blades to the mat. Children were asked to perform as many sit-ups as possible during the 1-minute test period. The test examiner counted and recorded the number of sit-ups.

Flexibility: Sit-and-reach (cm). Children were seated with both knees fully extended and feet firmly against a vertical support. Children were asked to reach forward with their hands, along a measuring line, as far as possible. Two trials were given to each child, with the score recorded (measured to the nearest 0.1 cm) on the farthest distance reached in the 2 trials.

Speed: 50-m dash (seconds). To assess the 50-m dash, children were instructed to run in a straight line on a flat, clear surface as fast as possible for 50 m. This test was performed once (as a single maximum sprint) for each child, and the time to the finish line was recorded to the nearest 0.1 s.

Coordination: Rope-skipping (counts/min). Children were instructed to perform a rope-skipping task requiring them to take off and land on both feet. After determining the appropriate rope length for each child, the child was asked to jump continuously for 1 min, with the total number of jumps recorded.

Z-scores were calculated for each component by standardizing individual values against the study population’s age- and sex-specific means and standard deviations, using the formula: Z = (X − µ)/σ, where X is the raw value, µ is the mean, and σ is the standard deviation for each parameter within the participant’s age (1-year intervals) and sex stratum. All Z-scores were normalized to a distribution with mean = 0 and SD = 1 before PFI computation. The PFI was calculated using the following formula45: PFI = Z-score of forced vital capacity + Z-score of sit-and-reach + Z-score of sit-ups − Z-score of 50-m dash + Z-score of rope-skipping.

Physical activity: questionnaires

Physical activity was assessed using the Chinese Physical Activity Questionnaire for Children46, which has been specifically validated for use in Chinese children, showing good test-retest reliability (ICC ranging from 0.63 to 0.93) and significant validity for total physical activity and sedentary behavior (Spearman’s rho = 0.32, P < 0.001) against accelerometer measurements. Participants self-reported the frequency (days per week) and duration (minutes per day) of moderate-intensity and vigorous-intensity physical activity. From these responses, the following indicators were derived: moderate-intensity physical activity (MPA; minutes per day), vigorous-intensity physical activity (VPA; minutes per day), moderate-to-vigorous-intensity physical activity (MVPA; minutes per day), and meeting the MVPA recommendation (≥ 60 min per day).

Adherence to programs

Trained members of the research team conducted weekly, unannounced, in-person observations of the sessions using a standardized fidelity checklist. This checklist assessed key components, including adherence to the session structure and the quality of exercise technique coaching.

Adverse events

Adverse events (AEs) were monitored throughout the study and were defined as any issue persisting for more than 2 days or prompting the participant to seek additional treatment. All AEs were systematically recorded and monitored, and the investigator was notified within 24 h of any serious adverse events. Weekly unannounced audits and standardized checklists were used to ensure accurate documentation of AEs, and supplemental teacher training sessions were provided as needed to address any safety concerns. In this study, no AEs were reported.

Blinding

The PE teachers were aware of the group assignments. However, participants, their families, and outcome assessors and statisticians remained blinded to minimize bias.

Statistical analysis

In accordance with the prespecified protocol, the primary outcome analysis was performed in children with available baseline data on both PFI and posture health. All analyses adhered to the intention-to-treat (ITT) principle. The Kolmogorov-Smirnov test was used to verify the normality of the data. Descriptive statistics were reported as mean ± SD and percentages (%) for continuous and dichotomous variables, respectively. Baseline differences between groups were examined using independent-samples t-tests or chi-square tests (χ2) for continuous and dichotomous variables, respectively. Missing data, primarily related to PA surveys, were handled via multiple imputation by chained equations (MICE) under the missing-at-random (MAR) assumption. Missing values for days of MPA, VPA, and daily activity duration were imputed using predictive mean matching (PMM). For continuous outcomes, linear mixed-effects models with a difference-in-differences (DID) framework were fitted. Effect sizes were expressed as Cohen’s d with 95% CI, which was calculated as the difference in treatment effects divided by the pooled SD estimated from the mixed model for repeated measures, where values of Cohen’s d < 0.2, 0.2–0.5, and > 0.5 were interpreted as small, medium, and large, respectively47. For the 50-m dash, a negative Cohen’s d value indicates a decrease in sprint time, which corresponds to an improvement in performance. For binary outcomes, generalized linear mixed models (GLMMs) with a Poisson distribution were fitted, and risk ratios (RRs) with 95% CIs were reported. All models were adjusted for sex, age, parental educational attainment, and extracurricular sports participation to account for potential confounding factors. Subgroup analyses (by sex and BMI status) were conducted after confirming the statistical significance (P < 0.05) of these variables as effect modifiers using these models with interaction terms. Sensitivity analyses included a Per-Protocol (PP) analysis (excluding participants with missing data; results were shown in Appendix Tables 6, 7 and 8). Two-sided P values < 0.05 were considered statistically significant. Analyses were performed using R 4.4.2.

Results

Of 1,286 participants (intervention: n = 601; control: n = 685), their baseline characteristics were well-balanced (Table 1), with age (mean ± SD 10.43 ± 0.31 vs. 10.43 ± 0.34 years; P = 0.713), sex (53.1% vs. 53.3% boys; P = 0.940), BMI (mean ± SD 19.28 ± 3.99 vs. 19.51 ± 4.32; P = 0.285), parental educational attainment (≥ 83% bachelor’s degree; P = 0.502 mothers, P = 0.097 fathers), and extracurricular sports participation (74.4% vs. 77.2%; P = 0.230).

Table 1 Baseline characteristics of participants.
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Table 2 summarized the within- and between-group changes in primary outcome indicators over 16 weeks. The functional training intervention significantly improved PFI scores compared to regular PE. These effect sizes indicate clinically meaningful differences (mean difference 0.77 [95% CI: 0.48–1.05], Cohen’s d = 0.28, P < 0.001). The improvement effects varied slightly across different measurement items. A significant intervention effect was observed in sit-ups (mean difference 3.89 [95% CI: 2.88–4.91], Cohen’s d = 0.43, P < 0.001), followed by sit-and-reach (mean difference 1.78 [95% CI: 1.25–2.31], Cohen’s d = 0.33, P < 0.001), rope-skipping (mean difference 4.63 [95% CI: 1.23–8.03], Cohen’s d = 0.17, P < 0.001) and BMI (mean difference − 0.30 [95% CI: -0.44–-0.17], Cohen’s d = -0.07, P < 0.001). However, no significant improvement in forced vital capacity was observed (P = 0.725). At the same time, the control group demonstrated better performance in the 50-m dash compared to the intervention group (mean difference 0.15 [95% CI: 0.03–0.28], Cohen’s d = 0.18, P < 0.001) (Table 2; Fig. 3). Subgroup analyses revealed greater improvements in PFI among girls (mean difference 1.43 [95% CI: 1.01–1.84], Cohen’s d = 0.53, P < 0.001) and normal weight group (mean difference 1.31 [95% CI: 0.92–1.70], Cohen’s d = 0.46, P < 0.001), and no significantly improvement was observed in boys (mean difference − 0.19 [95% CI: -0.20–0.57], Cohen’s d = 0.17, P = 0.348), thinness group (mean difference 0.72 [95% CI: -0.60–2.04], Cohen’s d = 0.49, P = 0.287) and OWOB group (mean difference 0.09 [95% CI: -0.36–0.54], Cohen’s d = 0.12, P = 0.703) (Figs. 3, 4 and 5; Appendix Tables 3 and 5).

Postural assessments demonstrated parallel improvements to those in PFI, with the intervention group showing significantly greater reductions in FHP (difference in proportion: -12.6%, P < 0.001; RR = 0.65, 95% CI: 0.54–0.78, P < 0.001) and prevented the worsening of uneven shoulders observed in controls (difference in proportion: -23.3%, P < 0.001; RR = 0.51, 95% CI: 0.42–0.65, P < 0.001). Subgroup analyses revealed significant reductions in FHP among girls (RR = 0.55; 95% CI: 0.39–0.78; P < 0.001) and the normal weight group (RR = 0.50; 95% CI: 0.35–0.70; P < 0.001) compared with controls. Similarly, girls (RR = 0.41; 95% CI: 0.28–0.61; P < 0.001) and the OWOB group (RR = 0.40; 95% CI: 0.26–0.61; P < 0.001) showed greater improvement in uneven shoulders. In contrast, no statistically significant reduction in both FHP and uneven shoulders was observed in the thinness group (Uneven shoulders: RR = 0.49; 95% CI: 0.18–1.30; P = 0.154; FHP: RR = 0.16; 95% CI: 0.02–1.13; P = 0.067) (Fig. 6 & Appendix Tables 4 and 5).

Multimorbidity of FHP and uneven shoulders showed that, compared to the control group, the intervention group increased the prevalence of normal posture from 40.8% to 57.2% (difference in proportion: +24.4%), whereas the control group showed a decrease. The prevalence of combined abnormalities (FHP and uneven shoulders) decreased significantly in the intervention group from 11.7% to 5.7% (difference proportion: 11.6%), whereas it decreased less in the control group. Within the intervention group, FHP demonstrated a larger reduction (difference in proportion: -10.0%), exceeding improvements observed in FHP with multimorbidity and uneven shoulders (within-group difference in proportion: -6.0%) and in isolated uneven shoulders (within-group difference in proportion: -0.5%) (Fig. 6).

The intervention group demonstrated significantly greater improvements in MVPA (mean difference 34.62 [95% CI: 22.04–47.20], P < 0.001; Cohen’s d = 0.47, P < 0.001), with similar patterns for MPA (mean difference 17.25 [95% CI: 10.79–23.72], Cohen’s d = 0.43, P < 0.05) and VPA (mean difference 17.37 [95% CI: 9.54–25.20], Cohen’s d = 0.39, P < 0.001). The proportion failing to meet 60-minute MVPA standards decreased 22.3% in intervention vs. 7.9% in controls (RR = 0.72, 95% CI 0.61–0.85, P < 0.001). Subgroup analyses revealed significant increases in MVPA among boys (mean difference 53.13 [95% CI: 35.98–70.29], Cohen’s d = 0.66, P < 0.001) and the OWOB group (mean difference 39.40 [95% CI: 19.60–59.20], Cohen’s d = 0.24, P < 0.001). By contrast, no significant increases were observed in girls (mean difference 13.53 [95% CI: -4.75–31.81], Cohen’s d = 0.17, P = 0.147) and the thinness group (mean difference − 1.11 [95% CI: -57.71–55.49], Cohen’s d = 0.20, P = 0.969) (Table 2; Fig. 5 and Appendix Table 5). The results of the sensitive analysis (Appendix Tables 6, 7 and 8) were consistent with the primary ITT analysis.

Table 2 Primary and secondary outcomes at baseline and follow-up and change from baseline to 16 weeks-intervention.
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Fig. 3
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Baseline to post-intervention Z-score changes in physical fitness indicators. PFI stands for physical fitness indicators; Z_SU stands for Z score of sit-ups; Z_RS stands for Z score of rope-skipping; Z_SR stands for 50-m dash; Z_SAR stands for Z score of sit-and-reach; Z_FVC stands for Z score of forced vital capacity.

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Fig. 4
figure 4

Distributions of physical fitness indicators scores across time points and subgroups. Data are mean ± SD; PFI stands for physical fitness indicators; BMI stands for body mass index; OWOB stands for overweight/obesity. The distribution parameters were detailed in the Appendix Table 3.

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Fig. 5
figure 5

Subgroup analysis of intervention effects on physical fitness indicators, postural health and moderate-to-vigorous physical activity by sex and BMI status. RR stands for risk ratio; CI stands for confidence interval; BMI stands for body mass index; OWOB stands for overweight/obesity.

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Fig. 6
figure 6

Flow of postural change transitions between baseline and follow-up. Note: The Sankey diagram illustrates postural state transitions, with band widths proportional to the percentage of participants in each flow path. FHP stands for forward head posture; US stands for uneven shoulders; FHP&US stands for concurrent forward head posture and uneven shoulders; Normal stands for the absence of detectable forward head posture or uneven shoulders.

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Discussion

This school-based functional training intervention achieved significant improvements in PFI and postural health among children following the 16-week program. The intervention was found to have potential advantages for enhancing students’ overall PFI (Cohen’s d = 0.28). Significant improvements with small-to-moderate effect sizes were observed in specific components: sit-ups (Cohen’s d = 0.43), sit-and-reach (Cohen’s d = 0.33), and rope-skipping (Cohen’s d = 0.17). In contrast, no significant effect was observed for forced vital capacity (P = 0.725), and the control group demonstrated better performance in the 50-m dash compared to the intervention group (Cohen’s d = 0.18). Postural health improved significantly, with FHP prevalence reduced by 12.6% (RR = 0.65) and uneven shoulders by 23.3% (RR = 0.51). Subgroup analyses revealed critical sex-specific and BMI status patterns. While girls showed particular improvements in PFI (Cohen’s d = 0.53) and postural health (FHP: RR = 0.55; uneven shoulders: RR = 0.41), boys demonstrated significantly greater increases in MVPA (Cohen’s d = 0.66), all with the between-group difference reaching statistical significance. Normal-weight children benefited consistently in PFI (Cohen’s d = 0.46) and uneven shoulders (RR = 0.53), whereas OWOB children showed better improvement in FHP (RR = 0.40) and MVPA (Cohen’s d = 0.24) but limited PFI improvements. These findings substantiate both the feasibility and effectiveness of functional training as a promising, scalable school-based intervention.

The findings were consistent with existing evidence that school-based MSE effectively enhances children’s PFI55,56, demonstrating MSE benefits for children’s physical fitness, particularly muscular strength, flexibility, and coordination32,48. However, the intervention did not achieve statistically significant improvements in cardiorespiratory fitness, likely because enhancements in cardiorespiratory function primarily depend on specialized aerobic training49. While direct comparisons were limited by the paucity of school-based postural intervention studies, the posture outcomes mirror clinical trial evidence demonstrating that functional training effectively improves postural health in children29,50,51.

The intervention demonstrated greater efficacy in improving uneven shoulders than FHP. One hypothesis for this differential effect was that it might have involved distinct biomechanical mechanisms: while uneven shoulders involve neuromuscular coordination across the dynamic lumbar-pelvic-femoral complex (affecting shoulder, spinal, and even lower limb muscle groups)52,53, FHP primarily engages upper body musculature (including cervical paraspinals and pectoralis major)54. However, this remained speculative as these mechanisms were not directly measured in the present study. Furthermore, the pronounced intervention effect on uneven shoulders was accentuated by a marked increase in the prevalence of uneven shoulders within the control group (from 32.4% at baseline to 49.2% at follow-up). This decline in the control group likely reflected natural, age-related trends during a period of rapid growth, when habitual postures and musculoskeletal imbalances would become more entrenched without targeted intervention, which might have been further exacerbated by increased sedentary time and academic pressures throughout the school term12,14,15,55. Sex-specific analyses revealed maximal benefits in girls. One hypothesis for this finding was that MSE might have helped mitigate known sex-related declines in physical self-efficacy by enhancing perceived competence56. Notably, the OWOB group exhibited significantly greater improvements in postural alignment. This effect might have been explained by the hypothesis that children with higher body mass experienced greater training effects, as the prescribed exercises inherently provide greater relative resistance14,57. Furthermore, the intervention demonstrated moderate-to-strong efficacy, with larger effect sizes observed for postural health than for physical fitness. This pattern might have supported the hypothesis that targeted neuromuscular activation yielded more immediate biomechanical adaptations26,29,32, whereas broader fitness gains may require a longer intervention period. These differential effects highlighted a potential strategy for tailored interventions38,49; for example, future programs could incorporate aerobic elements for children with OWOB to amplify fitness outcomes while leveraging their apparent responsiveness in postural improvement. The observed joint improvements in fitness and posture were consistent with the concept that postural training can enhance movement efficiency and force transmission, thereby potentially boosting fitness test performance58.

Furthermore, participants self-reported increased MVPA levels, consistent with previous findings14,59,60. The functional training program, characterized by its emphasis on integrated, multi-joint movements, might have enhanced fundamental movement skills (e.g., dynamic balance, whole-body coordination)29,30,32. This proposed improvement in motor competence could have reduced the perceived barrier to physical activity, making participation more accessible and enjoyable, which, in turn, might have explained the self-reported increase in MVPA. Moreover, a positive feedback loop was postulated, wherein increased MVPA might have synergistically supported gains in physical fitness and postural health. However, as fundamental movement skills were not directly measured, these mechanisms remain speculative and require validation in future studies.

Strengths and limitations

This study offered several notable strengths: First, it provided the first evidence that school-based interventions can effectively improve both postural health and physical fitness in children, addressing a critical gap in current research. Second, the intervention was seamlessly integrated into the existing PE curriculum with minimal disruption, supporting its feasibility and long-term sustainability. Third, functional training was employed as an MSE intervention, demonstrating its safety for children and its practicality in a school setting.

This study had several limitations. First, the primary outcome of MVPA was assessed via self-reported questionnaires, which were susceptible to recall and social desirability biases. This was particularly concerning in a child population, which may overestimate their physical activity levels; future studies should therefore employ objective measures, such as accelerometers, to obtain more accurate data. Second, the lack of a formal process evaluation means that feasibility aspects, such as ease of implementation from the teachers’ perspective and acceptability among both students and teachers, were not assessed. Including these measures in future research would enhance the understanding of intervention scalability and real-world applicability. Third, the absence of long-term follow-up prevents conclusions regarding the sustainability of the intervention effects. Finally, as the functional training intervention was primarily designed to target uneven shoulders, forward head posture, and physical fitness, its potential benefits on other health outcomes remain to be validated.

Conclusion

This study provided promising evidence supporting the effectiveness of functional training in improving children’s physical fitness and postural health. Further studies should evaluate the long-term sustainability of these effects and the generalizability to diverse populations.