Whiplash injury is a common neck injury caused by frontal collisions during sports. While muscle activation patterns during impact are critical to injury mechanisms, how cervical and lumbar electromyographic (EMG) responses scale with collision intensity remains unclear. This investigation compares neck and low-back EMG profiles under incremental impact intensities, providing biomechanical insights to optimize protective strategies for high-risk populations exposed to dynamic acceleration environments. 35 male subjects were selected. Age range: 19-22 years old; height: 173.6 ± 4.1cm; weight: 70.2 ± 6.4kg. Front impact was simulated on a specific testing apparatus by applying forward traction along the head with three different loads: 2.5 kg, 5 kg, and 7.5 kg. The height of vertical collision is 10cm. An electromyographic(EMG) system (Delsys, USA) was used for recording the muscle-- bilateral Erector Spinae(ES), Trapezius(TR), sternocleidomastoid (SCM), splenius capitis (SC)-- activity at a rate of 2000 Hz. Python 3.1.1 was used to analyze the EMG data. A bandpass filter was used (20–450 Hz, 4-pole Butterworth). Maximum voluntary isometric contractions (MVC) were used for data standardization. The indicators were the root mean square (RMS), mean power frequency (MPF), and integral electromyographic (iEMG). SC：2.5kg：RMS=2.75±4.17, MPF=62.99±10.4, iEMG=1.75±2.99; 5kg：RMS=3.38±5.71, MPF=67.14±8.24, iEMG=2.53±4.6;7.5kg：RMS=4.06±5.62, MPF=69.82±7.01; iEMG=2.71±3.93. TR：2.5kg: RMS=0.48±0.5, MPF=69.74±11.68, iEMG=0.32±0.51; 5kg: RMS=0.46±0.43, MPF=73.09±9.34, iEMG=0.34±0.42; 7.5kg: RMS=0.5±0.38, MPF=73.13±11.61, iEMG=0.41±0.43. SCM-L: 2.5kg: RMS=5.74±5.83,MPF=64.62±9.42, iEMG=3.67±3.91; 5kg: RMS=6.79±7.1, MPF=63.38±10.1, iEMG=4.62±5.43; 7.5kg: RMS=6.04±5.7, MPF=69.82±12.68, iEMG=4.57±4.67. ES：2.5kg: RMS=0.99±1.34，MPF=65.67±10.18, iEMG=0.56±0.67; 5kg: RMS=1.17±2.37, MPF=65.99±7.83, EMG=0.75±1.3; 7.5kg: RMS=1.88±4.42, MPF=65.33±9.41, iEMG=1.73±5.5. Repeated measures ANOVA is used to assess muscle metrics across various positions and intensities. RMS (load: p=0.001, η^2=0.011; muscle: p < 0.001,η^2=0.168; load*muscle: p=0.219,η^2=0.010), MPF (load: p=0.001, η^2=0.028; muscle: p=0.025,η^2=0.036; load*muscle: p=0.181,η^2=0.027). iEMG (load: p < 0.001, η^2=0.016; muscle: p < 0.001, η^2=0.135; load*muscle: p=0.206, η^2=0.015). 1) Within a certain range of collision intensity, the activation response characteristics of the human neck and waist increase with increasing intensity. 2) There is no interaction effect between muscle position and load.

Advanced footwear technology (AFT) has reshaped distance running performance, but concerns remain regarding its potential biomechanical implications discussed in the injury literature. This study investigates whether the improved running economy provided by AFT occurs without systematic increases in biomechanical variables that have been discussed in the literature in relation to running-related injuries. Thirty recreational runners completed treadmill trials in three shoe conditions: Nike Vaporfly 3 (NV3; PEBA foam + carbon-fiber plate), Nike Invincible 3 (NI3; PEBA foam), and Brooks Levitate 5 (BL5; TPU foam). Running in each shoe was conducted at 10.8 and 12.6 km·h-1. Oxygen uptake, heart rate (HR), and biomechanical variables related to injury risk (vertical average loading rate (VALR), vertical instantaneous loading rate (VILR), braking impulse, contact time, and contralateral pelvic drop) were analyzed using a two-way repeated measures ANOVA. Compared with both NI3 and BL5, NV3 significantly reduced oxygen uptake (mean difference: -1.749 ± 0.259 and -1.914 ± 0.215 mL·kg-1·min-1, respectively, p < 0.001) and HR (mean difference: -4.750 ± 0.637 and -5.433 ± 0.720 beats·min-1, respectively, p < 0.001). The BL5 exhibited substantially higher VALR and VILR than both NV3 and NI3 (all p < 0.001) and NV3 exhibited significantly higher VALR values than NI3 (p = 0.006). Braking impulse was lowest in NI3, and no significant shoe condition effects were observed for contralateral pelvic drop or contact time. AFT shoes combining PEBA foam with a carbon-fiber plate improved running economy without increases in the biomechanical variables examined, which have been discussed in the literature in relation to running-related injuries. AFT shoes can enhance metabolic performance, while PEBA-only shoes may better suit sessions focused on cushioning and impact management.

OBJECTIVE:To investigate the correlation between 24 h activity behaviors and body fat percentages in children with intellectual disabilities(ID), and the changes in body fat percentage of children with ID after isochronous substitution between behaviors in 24 h activity behaviors. METHODS:From February to May 2024, the stratified random sampling strategy to recruit 207 children with ID aged 6-12 years old from six special education schools in Jinan City. The 24 h activity behaviors were assessed using triaxial accelerometers, and body fat percentages(BF%) were measured with a multi-frequency bioelectrical impedance analyzer. Compositional data were analyzed in R. Multiple linear regression examined associations between 24 h activity behaviors and BF%. Using 5-min increments, the isotemporal substitution was applied to explore dose-response effects of reallocating time between behaviors. RESULTS:The time in moderate-to-vigorous physical activity(MVPA) was negatively correlated with BF%(β=-3.68, P&lt;0.01), and the time of SB was positively correlated with body fat percentage(β=3.78, P&lt;0.01); reallocating time to MVPA significantly reduced BF% when replacing sleep(SLP), SB, and light-intensity physical activity(LPA) by 1.39%, 1.99%, and 1.51%, respectively. The substitution effects between MVPA and SLP/SB/LPA were asymmetric. Replacing SB with LPA reduced BF% by 0.47%, and replacing SB with sleep reduced BF% by 0.59%; substitution effects among LPA, SLP, and SB were approximately symmetric. CONCLUSION:Among children with ID, 24 h activity behaviors are associated with BF%. Of all substitutions analyzed, replacing SB with MVPA produced the greatest reduction in BF%.

Introduction:Spinal health significantly impacts adolescents' posture, athletic performance, mental well-being, and quality of life. It provides data support for promoting the physical and mental health of adolescents and implementing the construction of a strong education country. Methods:This study employed computer vision recognition technology to screen and evaluate the spinal health status of 4,534 adolescents aged 6-18. Through a 12-week exercise intervention, the study compared the effects of different exercise programs on adolescents' spinal health. Results:(1) The spine characteristics of 4,534 children and adolescents aged 6 ~ 18 years old showed that there were more middle and high risk people with neck forward tilt, neck roll, overall spine roll, high and low shoulder and pelvic rotation, and the tilt or rotation angle of boys was larger than that of girls. (2) From the perspective of age, the tilt angle of children and adolescents in the low age group and 18 years old is larger. (3) Football, badminton and dance can improve the spine tilt angle of adolescents, but different sports have different effects on different parts of the spine. Conclusion:(1) Children and adolescents aged 6-18 have different degrees of problems in the neck, chest, waist, spine, shoulder joint and pelvis. (2) There are age and gender differences in spine health of adolescents aged 6-18 years old, and the problems of low age group and 18 years old are more prominent. (3) When using exercise to improve spinal health issues, it is essential to select different types of sports based on the tilt of different body parts and arrange the exercise intensity reasonably according to individual health conditions and physical capabilities.

Objective:The purpose of this study was to examine the differences in the lower-limb muscle activities and kinematics between figure skating Axel type jumps with different number of rotations in youth figure skaters. We hypothesized that skaters would exhibit increased lower limb flexion during jump propulsion phase, lower limb extension at take-off and greater muscle activation levels as jump rotation increases. Methods:Eleven youth figure skaters (age: 12 ± 4.29 years; height: 146.82 ± 17.71 cm; body mass: 37.02 ± 14.47 kg) performed Waltz Jump (0.5 rotations), Single Axel Jump (1.5 rotations), and three of them additionally performed Double Axel Jump (2.5 rotations). Lower-limb kinematics were recorded using two high-speed cameras. Muscle activities of Rectus Femoris, Long Head of Biceps Femoris, Tibialis Anterior, Lateral Gastrocnemius, and Medial Gastrocnemius of both legs were measured. The differences between the jumps were compared using paired samples t-test. Comparison of EMG data between different muscles parts was performed by One-way ANOVA. Due to limited data, Double Axel jump was compared with descriptive analysis. Results:More difficult Axel type jump had higher jump height, shorter jump distance, faster jump take-off vertical velocity, and greater hip flexion during propulsion phase. The RMS and iEMG values of the left medial and lateral gastrocnemius and right tibialis anterior increased as the jump difficulty increased. Moreover, there were significant differences between different muscle parts RMS values and iEMG values in both Waltz jump and Single Axel jump (p < 0.01). Biceps femoris and rectus femoris indicated to have the highest RMS values and iEMG values in Waltz jump and Single Axel jump. Conclusion:More difficult Axel type jumps require greater hip flexion during propulsion phase and greater activities in hamstrings, quadriceps and tibialis anterior before jump take-off. Youth figure skaters can improve jump height, take-off vertical velocity and overall qualities of jumps by enhancing multi-joint movement, muscle coordination and take-off leg strength. These findings provide insights into the lower-limb biomechanical characteristics of figure skating jumps, and potentially leading to refinement of training programs for the youth figure skaters to optimize jump performances and to reduce potential lower extremity injuries.

PurposePlantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design.MethodsA sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28 years, height 1.76 ± 0.04 m, weight 72.21 ± 5.69 kg). Plantar pressure data were collected during 5 trials at the subjects’ preferred walking speed (1.15 ± 0.04 m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features.ResultsThe predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89 N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = −4.43N/m, RMSE = 14.73 N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution.ConclusionThe pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.

ObjectiveTo investigate the relationship between college students' physical activities and Internet addiction, to investigate the role self-control control plays in this relationship, and to provide a theoretical foundation for the alleviation of college students' tendency to Internet addiction and intervention treatment.MethodsA questionnaire survey was conducted on 471 college students using the International Physical Activity Questionnaire (IPAQ), the Revised Chen Internet Addiction Scale (CIAS-R), and the Self-Control Scale (SCS).ResultsInternet addiction was significantly negatively correlated with physical activities (overall; min/WK, r = −0.115, P < 0.05), with high-intensity physical activities (min/WK, r = −0.179, P < 0.01), and with low-intensity physical activities (r = −0.103, P < 0.05); self-control was significantly positively correlated with physical activities (overall; min/WK, r = 0.150, P < 0.01), with moderate—intensity physical activities (min/WK, r = 0.139, P < 0.01) while it was significantly negatively correlated with Internet addiction (min/WK, r = −0.349, P < 0.01). The mediating effect follows the path: physical activity → self-control → internet addiction.ConclusionPhysical activity can have a direct negative effect on college students' Internet addiction, and also influence Internet addiction through the mediating effect of self-control.

This study aimed to clarify the biomechanical adaptations recreational runners experience during a half marathon. Thirty-seven healthy runners completed a half marathon as fast as possible on a laboratory-instrumented treadmill. Kinematic and kinetic data were collected every 5 km from 0 to 20 km. As mileage accumulated, peak vertical ground reaction force (GRF) decreased from 5 km onward (p < 0.005) and impulse declined from 10 km (p < 0.05). Ground contact time increased from 10 km (p < 0.05). Joint-level adaptations included an increased hip extension moment (p < 0.005) and hip adduction angle from 10 km (p < 0.05), decreased knee abduction moment from 5 km (p < 0.005), and greater knee flexion angle at 10 km (p < 0.001) and 15 km (p = 0.031). Additionally, the symmetry angle of peak vertical GRF decreased at 20 km, suggesting improved interlimb symmetry under fatigue. These findings provide insight into fatigue-related biomechanical adaptations during long-distance running. Further research is needed to clarify how these changes relate to injury development.

Objectives: This study aimed to explore the independent and joint associations of daily sitting time and leisure-time physical activity (LTPA) with sarcopenia among older adults. Methods: The participants were 847 community-dwelling adults aged 60 or older from Beijing and Shanghai, China. Sarcopenia was diagnosed based on the criteria established by the Asian Working Group for Sarcopenia (2019). Daily sitting time and LTPA were self-reported using the Physical Activity Scale for the Elderly (PASE). Logistics regression models were used to explore the associations between daily sitting time, LTPA, and sarcopenia. To examine joint associations, participants were classified based on daily sitting time and LTPA levels. Final models were adjusted for sociodemographic variables, lifestyle factors, and chronic conditions. Results: Prolonged sitting time and insufficient LTPA were independently associated with higher odds of sarcopenia. Among insufficiently active participants, sitting for 1–2 h, 2–4 h, and more than 4 h per day was associated with 5.52-fold (95% CI: 1.13–26.83), 6.69-fold (95% CI: 1.33–33.59), and 12.82-fold (95% CI: 2.75–59.85) increased odds of sarcopenia, respectively, compared to sitting for less than 1 h. For those meeting the physical activity guideline (≥150 min of LTPA per week), only sitting for more than 4 h per day was significantly associated with higher odds of sarcopenia (OR: 7.25, 95% CI: 1.99–26.36). Conclusions: Prolonged sedentary behavior was associated with increased odds of sarcopenia. The higher odds of sarcopenia associated with more than 4 h daily sitting may not be offset by achieving the recommended levels of physical activity.

ObjectiveThe present study aims to investigate the effects of different modes of high-intensity interval training on the self-control and physical fitness levels of college students.Methods1. The participants of this study comprised 58 college students, who were randomly divided into three groups: an online experimental group (A = 20), an online-offline experimental group (B = 18), and a control group (C = 20). The Chinese Self-Control Scale (CSCS) and the Physical Fitness Level Test (PHLT) were administered to all participants before and after the intervention, and the test results were then assigned to the respective scores. Group A performed online only, Group B performed online-offline Tai Chi practice, 40 min/1 time/week, 30 min/1 time/week jogging and 40 min/2 times/week high-intensity interval training for 8 weeks, and Group C did not undergo high-intensity interval training. 2. Statistical analysis was performed using SPSS 25.0, including one-way ANOVA for pre-test group differences, paired t-tests for within-group differences, and ANOVA and LSD tests for post-test group differences.Results1. A significant improvement in the total score of self-control was observed in group B (p < 0.001), while no significant change was observed in groups A and C. 2. A significant enhancement in standing long jump scores was observed in both groups A and B (p < 0.01 and p < 0.001, respectively), while group A demonstrated a significant enhancement in seated forward bending scores (p < 0.05). Additionally, group B exhibited a substantial improvement in 50-m scores (p < 0.01). The results of the differences between groups showed significant differences in 50-m scores (p < 0.01, B > A; A > C; B > C) and standing long jump scores (p < 0.05, B > A; B > C).Conclusion1. A variety of high-intensity interval training (HIIT) formats have been demonstrated to enhance the physical fitness and health of university students. 2. The online-offline HIIT methodology has been shown to assist in enhancing the self-control of university students. 3. The online-offline HIIT methodology has the capacity to more effectively improve the self-control ability and physical fitness of college students.SuggestionPhysical education teachers implement high-intensity interval training programs using online and offline methods to enhance self-control and fitness in university students.

Under the strategy of Healthy China, students’ physical health status not only affects their future life and studies but also influences social progress and development. By monitoring and measuring the daily PA levels of Chinese students over a week, this study aimed to fully understand the current PA status of students at different times, providing data support for improving students’ PA levels and physical health. (1) Wearable fitness trackers have advantages such as low cost, portable wearability, and intuitive test data. By exploring the differences between wearable devices and PA testing instruments, this study provides reference data to improve the accuracy of wearable devices and promote the use of fitness trackers instead of triaxial accelerometers, thereby advancing scientific research on PA and the development of mass fitness. A total of 261 students (147 males; 114 females) were randomly selected and wore both the Actigraph GT3X+ triaxial accelerometer and Huawei smart fitness trackers simultaneously to monitor their daily PA levels, energy metabolism, sedentary behavior, and step counts from the trackers over a week. The students’ PA status and living habits were also understood through literature reviews and questionnaire surveys. The validity of the smart fitness trackers was quantitatively analyzed using ActiLife software 6 Data Analysis Software and traditional analysis methods such as MedCal. Paired sample Wilcoxon signed-rank tests and mean absolute error ratio tests were used to assess the validity of the smart fitness trackers relative to the Actigraph GT3X+ triaxial accelerometer. A linear regression model was established to predict the step counts of the Actigraph GT3X+ triaxial accelerometer based on the step counts from the smart fitness trackers, aiming to improve the accuracy of human motion measurement by smart fitness trackers. There were significant differences in moderate-to-high-intensity PA time, energy expenditure, metabolic equivalents, and step counts between males and females (p < 0.01), with females having higher values than males in both moderate-to-high-intensity PA time and step counts. Sedentary behavior showed significant differences only on weekdays between males and females (p < 0.05), with females engaging in less sedentary behavior than males. (2) There was a significant difference in sedentary time between weekdays and weekends for students (p < 0.05), with sedentary time being higher on weekends than on weekdays. (3) Compared with weekends, female students had significantly different moderate-to-high-intensity PA time and sedentary time on weekdays (p < 0.01), while no significant differences were observed for male students. (4) Under free-living conditions, the average daily step count monitored by the smart fitness trackers was lower than that measured by the Actigraph GT3X+ triaxial accelerometer, with a significant difference (p < 0.01), but both showed a positive correlation (r = 0.727). (5) The linear regression equation established between the step counts monitored by the smart fitness trackers and those by the Actigraph GT3X+ triaxial accelerometer was y = 3677.3157 + 0.6069x. The equation’s R2 = 0.625, with an F-test value of p < 0.001, indicating a high degree of fit between the step counts recorded by the Huawei fitness tracker and those recorded by the triaxial accelerometer. The t-test results for the regression coefficient and constant term were t = 26.4410 and p < 0.01, suggesting that both were meaningful. The tested students were able to meet the recommended total amount of moderate-intensity PA for 150 min per week or high-intensity PA for 75 min per week according to the “Chinese Adult PA Guidelines”, as well as the recommended daily step count of more than 6000 steps per day according to the “Chinese Dietary Guidelines”. (2) Female students had significantly more moderate-to-high-intensity PA time than male students, but lower energy expenditure and metabolic equivalents, which may have been related to their lifestyle and types of exercise. On weekends, female students significantly increased their moderate-to-high-intensity PA time compared with males but also showed increased sedentary time exceeding that of males; further investigation is needed to understand the reasons behind these findings. (3) The step counts monitored by the Huawei smart fitness trackers correlated with those measured by the Actigraph GT3X+ triaxial accelerometer, but the step counts from the fitness trackers were lower, indicating that the fitness trackers underestimated PA levels. (4) There was a linear relationship between the Huawei smart fitness trackers and the Actigraph GT3X+ triaxial accelerometer. By using the step counts monitored by the Huawei fitness trackers and the regression equation, it was possible to estimate the activity counts from the Actigraph GT3X+ triaxial accelerometer. Replacing the Actigraph GT3X+ triaxial accelerometer with Huawei smart fitness trackers for step count monitoring significantly reduces testing costs while providing consumers with intuitive data.

ObjectiveTo examine the association between 24-hour movement behaviors and depressive symptoms in older adults using compositional data analysis, and to investigate the dose-response characteristics of time reallocations between movement behaviors in relation to depressive symptoms.MethodsA cross-sectional study was conducted among 1093 urban-dwelling older adults aged 60 years and above in selected communities of Jinan City, Shandong Province, China, between April 2024 and September 2024. The Chinese version of the International Physical Activity Questionnaire-Long Form (IPAQ-LF) was used to estimate time spent in moderate to vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), sedentary behavior (SB), and sleep (SLP) across a typical 24-hour day. The Chinese version of the Patient Health Questionnaire Depression Scale-9 item (PHQ-9) was applied to assess depressive symptoms. Compositional isotemporal substitution models were employed to explore the associations between time reallocations among 24-hour movement behaviors and depressive symptoms, accounting for the co-dependent nature of time-use data.Results(1) The geometric means of time spent in MVPA, LPA, SB, and SLP were 25.33 minutes, 141.26 minutes, 738.10 minutes, and 455.15 minutes, respectively. Variation matrix analysis revealed the highest log-ratio variance between MVPA and SB (0.168), and the lowest between SLP and SB (0.031). (2) The prevalence of screening-positive depressive symptoms was 16.29% among Chinese urban older adults. (3) Results from compositional linear regression models showed that time allocated to MVPA, LPA, and SLP (relative to the remaining movement behaviors) was negatively associated with depressive symptoms, while time spent in SB was positively associated. (4) Dose-response analysis further indicated that: (a) MVPA substitutions with other movement behaviors exhibited nonlinear and markedly asymmetric effects on depressive symptoms; (b) replacing MVPA with LPA, SB, or SLP resulted in increasingly larger changes in predicted scores as substitution duration increased, whereas the reverse substitution (MVPA for other movement behaviors) produced progressively smaller changes; and (c) substitutions between SB and LPA displayed linear and symmetrical effects.ConclusionsThe findings provide evidence of an association between 24-hour movement behaviors and depressive symptoms in Chinese urban-dwelling older adults and reinforce the importance of achieving a balance between different types of movement behaviors over a 24-hour period for mental health.

Using multiple fusion algorithms to optimize the classification and feature extraction of plantar pressure during walking stance phase in healthy people, and explore the diversity of plantar pressure distribution. 243 healthy young male individuals was studied to collect data on plantar impulse and maximum pressure indices from ten distinct regions of the foot during walking. Principal component analysis was utilized to reduce the dimensionality of the data. Optimized clustering and feature extraction algorithms categorized the plantar pressure characteristics and extracted key indicators. Classification discriminant functions were developed using linear discriminant analysis. Analysis of variance compared the differences in features between various plantar pressure distribution patterns. Three types of plantar pressure distribution were identified by multiple fusion algorithms, and four indicators were extracted, including impulses of Toe1, Meta1, Meta5 and Midfoot. The average accuracy rates of original data and cross-validation were 89.70% and 88.50%. Based on one-way analysis of variance, the distribution types were ultimately determined as thumb extension type, midfoot-lateral forefoot push-off type, and normal type. Plantar pressure distribution during walking in healthy people can be categorized into thumb extension type, midfoot-lateral forefoot push-off type, and normal type. Among them, the impulses around the first metatarsophalangeal joint region, fifth metatarsal bone region and midfoot region showed better classification performance. It is recommended that future studies combine the current findings and use prospective studies to further analyze the relationship between gait characteristics and sports injuries.

Objective: To compare the efficacy of exercise modalities for simultaneously improving homeostasis model assessment for insulin resistance (HOMA-IR) and total testosterone in women with polycystic ovary syndrome (PCOS). Methods: We conducted a Bayesian network meta-analysis of 19 randomized controlled trials (n = 808) to evaluate six exercise interventions: yoga, moderate-intensity continuous training (MICT), high-intensity interval training (HIIT), resistance training (RT), combined aerobic-resistance training (CT), and control (CG). Primary outcomes were changes in HOMA-IR and total testosterone, with interventions ranked via surface under the cumulative ranking curve (SUCRA). Results: For HOMA-IR reduction, yoga (SUCRA = 90.73%; SMD = −0.73, 95% CrI: −1.3 to −0.086) and HIIT (SUCRA = 74.12%; SMD = −0.47, 95% CrI: −0.75 to −0.15) demonstrated superior efficacy versus MICT (SUCRA = 50.56%) and CT (SUCRA = 42.29%), while RT was the least effective (SUCRA = 32.53%). For testosterone lowering, yoga was ranked the highest again (SUCRA = 92.46%; SMD = −0.85, 95% CrI: −1.7 to −0.12), followed by MICT (SUCRA = 75.72%; SMD = −0.56, 95% CrI: −0.97 to −0.25) and HIIT (SUCRA = 61.12%; SMD = −0.42, CrI: −0.88 to −0.12). CT and RT showed non-significant effects for both outcomes (p > 0.05). Conclusions: Yoga is the optimal intervention for dual-pathway improvement in PCOS. HIIT and MICT provide outcome-specific benefits (metabolic vs. endocrine), whereas CT and RT necessitate protocol refinement. Systematic review registration: This systematic review and network meta-analysis study was registered in PROSPERO (CRD420251011979).