2.1 Research subjects

The study included 120 male students enrolled in the public basketball elective course at our university. The recruitment period was from June 2024–June 2025.

All participants were non-sports major students whose basketball experience was limited to basic physical education courses or recreational activities. None of the students had any professional or semi-professional training experience, ensuring sample homogeneity in terms of professional background. The students were selected using random sampling and were randomly assigned to two groups: 60 students in the experimental group and 60 in the control group. There were no significant differences between the two groups in terms of age or academic major distribution (p > 0.05, Table 1).

Details of the randomization process:

1. Sequence generation

After recruiting 120 male university students from an elective basketball course who met the inclusion criteria and signed the informed consent form, a computer-generated randomization method was used to determine the group assignment for each participant.

Specifically, a research assistant independent of the project (not involved in the subsequent training or data collection) used the random number generation function of statistical software (such as SPSS or R) to create a list of 120 random numbers. These numbers were then arranged in ascending order. The participants corresponding to the first 60 numbers on the list were assigned to the experimental group (receiving functional training), while those corresponding to the last 60 numbers were assigned to the control group (receiving conventional basketball skill drills). This method ensured that every participant had an equal (50%) chance of being assigned to the either group and that the allocation outcome was completely unpredictable.

2. Allocation concealment

To ensure that the researchers responsible for recruitment and participant management could not foresee the group assignment, we implemented allocation concealment using the Sequentially Numbered, Opaque, Sealed Envelopes (SNOSE) method. The specific procedure was as follows:

The 120 computer-generated group assignments (60 “Experimental Group” + 60 “Control Group”) were printed on small, non-translucent cards.

Each card was placed in an individual opaque envelope and sealed.

All 120 envelopes were sequentially numbered from 1 to 120.

Upon confirming a student’s official enrollment in the study, the allocating researcher took an envelope according to its sequence number (e.g., the first enrolled student received envelope #1, the second received envelope #2, and so on).

The researcher opened the corresponding envelope in the presence of the participant, and both became aware of the group assignment at that moment.

3. Implementation

The entire allocation process was supervised by the project’s principal investigator. The generation of the random sequence and the preparation and numbering of the envelopes were carried out by an independent third-party research assistant. The on-site researchers responsible for recruiting students and opening the envelopes were blinded to the group assignments before opening the envelopes. They could not determine the contents in advance by any means (e.g., holding them up to a light or touching them). This series of rigorous procedures ensured the true randomness of the allocation process, effectively preventing potential selection bias, whether conscious or unconscious, in which researchers might otherwise assign students with specific characteristics to a particular group. This approach guaranteed a high degree of comparability between the experimental and control groups at the start of the study.

2.2 Research methods

2.3 Experimental plan

Based on students’ comprehensive physical condition and the practical context of our university’s basketball teaching, the experimental period was set for 12 weeks, with two 30-minute training sessions per week.

(1) Experimental process

Before commencing the 12-week training experiment, a pre-test was administered to all 120 students to ensure no significant initial differences in basketball skill levels between the experimental and control groups. The pre-test items were identical to the post-test items and included: the triangle lateral shuffle, 30-second continuous shooting under the basket, and full-court round-trip dribble layups. An independent samples t-test analysis of the pre-test data revealed no significant differences between the two groups on any of the indicators (p > 0.05). This confirmed that both groups had similar baseline basketball skill levels before the experiment, satisfying the fundamental requirements for experimental research.

Before the experiment, the experimental group formulated a teaching plan aligned with the experimental objectives. Students in the experimental group primarily followed the functional training program, while the control group adhered to the traditional basketball training methods. Additionally, the baseline physical abilities of both groups were assessed. Questionnaires were distributed to evaluate students’ extracurricular exercise plans, the presence of any visible or hidden health issues, involvement in sports-related clubs, and whether they had previously received professional sports training. The experimental sample selection followed strict inclusion and exclusion criteria.

To minimize the impact of irrelevant variables on the experimental results, the process was closely monitored. Both groups were instructed not to add extra training plans during the study. Participation in sports-related clubs was strictly prohibited. Students were asked to maintain a regular diet, ensuring adequate protein and carbohydrate intake, while limiting fat consumption and avoiding snacks such as puffed foods and carbonated beverages. Participants were encouraged to maintain healthy routines, including avoiding smoking, excessive alcohol consumption, staying up late, maintaining consistent sleep schedules, and balancing a nutritional diet. External disturbances were also minimized, ensuring that only one variable, the training method, differed between the two groups. Throughout the 12-week training period, the experimental group followed the functional training approach, while the control group adhered to the traditional teaching method.

Monitoring and Execution Details for Variables such as Diet, Extracurricular Activities, and Sleep.

1. Design and implementation of control measures

To reduce the influence of confounding factors on the experimental results, a structured protocol was designed and strictly implemented. A structured protocol was implemented, which ensured standardization of lifestyle factors across participants and maintained internal validity throughout the experiment (Table 2).

2. Adherence assurance mechanisms

To ensure participant compliance and maintain experimental consistency, multiple strategies were implemented, including educational guidance, financial incentives, peer supervision, and real-time technological monitoring. The detailed procedures for each strategy are presented in Table 3.

3. Actual implementation and challenges

The intervention was successfully implemented with a 96.67% recovery rate for dietary logs (2320 out of 2400 logs) and a 91.7% completion rate for sleep diaries (220 of 240 participants submitted records for ≥10 weeks). However, 18.3% of participants (n = 44) experienced partial data loss from activity trackers due to device issues.

Major challenges:

Difficulty in eliminating social drinking: Two students from the control group consumed alcohol at a birthday party, detected by a breathalyzer test; their data were excluded.

Unavoidable late nights during final exams: During weeks 11–12, the sleep compliance rate dropped to 72.5% compared to 85.7% in the preceding period.

Uncontrollable dietary choices in the cafeteria: Approximately 13% of the students reported consuming fried foods at least twice per week despite dietary restrictions.

4. Adherence validation and data processing

Quantitative adherence indicators:

A composite scoring system (maximum score: 10 points) was used to quantify adherence:

Group-based Processing:

High-adherence group (≥8 points, n = 89): All data were retained.

Medium-adherence group (6–7.9 points, n = 13): Data were retained but flagged as being at risk for bias.

Low-adherence group (<6 points, n = 18): Data were excluded from sensitivity analyses.

Statistical analysis adjustment:

The adherence score was introduced as a covariate in the mixed-effects model:

(2) Training plan for experimental and control groups

The experimental group underwent a structured functional training program aimed at improving basketball-specific skills by enhancing core strength, stability, and coordinated movement patterns. Each session systematically incorporated core strength and stability exercises, such as planks, standing rotational medicine ball pushes, and TRX chest presses, alongside upper-and lower-body strength exercises. The program was designed to enhance foundational movement patterns to improve basketball-specific skills, including shooting, defense, and dribbling. A sample weekly training plan is presented in Table 4, while the complete protocol is detailed in Supplementary material 2.

The control group participated in a traditional basketball skills program based on the standard university physical education curriculum. This included conventional drills such as stationary shooting, passing, and dribbling. Training frequency and session duration were identical to those of the experimental group. The detailed weekly schedule for the control group is presented in Table 5, and the complete training plan can be found in Supplementary material 3.

Overview of the training program design principles

I. Design principles for the experimental group (functional training)

1. Overall goal and fundamental principles:

The functional training protocol was designed based on the principle of training integrated movement patterns rather than isolated muscle groups. Its primary objective was to develop a robust athletic foundation to support the execution of basketball-specific skills (e.g., shooting, defensive movements, and quick directional changes). The program was structured around three core tenets:

Core to extremity: In basketball, all power originates from the core and is transferred to the limbs through the kinetic chain. A stable core is a prerequisite for efficient force generation and energy transfer. Therefore, the training plan prioritizes core strength and stability in every session.

Multi-planar movement: Basketball requires coordinated movement in all three planes, i.e., sagittal plane (forward/backward movements), frontal plane (lateral movements), and transverse plane (rotational movements). The program integrates rotational drills, lateral movements, and change-of-direction exercises to replicate real-game demands.

Neuromuscular control: The training aimed not only to increase muscular strength but also to optimize the central nervous system’s ability to coordinate movement, thereby enhancing balance, proprioception, and reaction time.

2. Rationale and expected outcomes for specific exercise selection:

Core stability exercises (e.g., various planks/bridges): Reason for selection: These are the cornerstone of functional training. The exercises progress from stable positions (e.g., support on both elbows and feet) to unstable conditions (e.g., single-arm/single-leg variations), to continuously challenge the core’s anti-rotation and anti-extension capabilities. Expected outcome: To enhance trunk rigidity, which provides a stable “platform” for shooting, helps maintain balance during defensive encounters and physical contact, and effectively prevents lower back injuries.

Lower body strength and stability exercises (e.g., squats, mini-band lateral walks/kickbacks): Reason for selection: Squats are a fundamental strength-building movement, while mini-band exercises effectively activate the gluteal muscle groups, which are often neglected in traditional training. Expected outcome: To improve vertical jump height, the speed of the first step, and the power of defensive slides. Activating the glutes helps maintain knee stability, reducing the risk of non-contact knee injuries.

Power and multi-planar strength exercises (e.g., medicine ball/slam ball rotational throws, overhead throws): Reason for Selection: These exercises directly mimic the force production patterns in basketball, such as rotational passes and powerful layups. They train explosive power in the transverse plane, an element often lacking in traditional strength training. Expected outcome: To increase passing speed and power, and to enhance body control when shooting and passing while in motion.

Agility and reaction drills (e.g., various footwork drills, crossover steps, quick-reaction choppy steps): Reason for selection: These are low-intensity plyometric exercises designed to train the body’s ability to rapidly absorb and release energy. Expected outcome: To shorten muscle reaction time, improve the speed and fluidity of footwork and changes of direction, which directly correspond to the “triangle lateral shuffle” and “full-court round-trip dribble layup” tests of basketball-specific skills.

3. Connection to the research hypotheses:

The protocol was designed to directly test the study’s primary hypotheses. First, it was hypothesized that by targeting fundamental movement patterns, the intervention would lead to significant improvements in both Functional Movement Screen (FMS) scores and basketball-specific skills. The enhanced athletic foundation was expected to create a greater capacity for skill development compared to traditional training. Second, it was hypothesized that measurable improvements in physical competence and body control would correlate with enhanced psychological well-being. This would be evidenced by increased self-efficacy and reduced symptom scores on the Symptom Checklist-90 (SCL-90).

II. Design principles for the control group (traditional basketball training)

1. Overall goal and fundamental principles:

The training protocol for the control group was designed to emulate conventional teaching methodologies widely adopted in university-level general physical education basketball courses. The protocol was based on the principle of specificity in skill acquisition, which posits that motor improvements are directly related to the specific tasks practiced.

Principle: The primary mechanism for improvement is the extensive repetition of specific basketball techniques. This process aims to refine the motor programs associated with these actions, leading to the development of robust procedural memory, often referred to as “muscle memory”.

Objective: The immediate goal was to enhance student proficiency and accuracy in performing isolated technical skills, such as stationary dribbling, shooting, and passing.

2. Rationale and expected outcomes for specific exercise selection:

Isolated skill drills (e.g., stationary dribbling, stationary one-handed over-the-shoulder shooting, two-person passing): Rationale: This approach aligns with traditional pedagogical models for introductory basketball instruction. By breaking down the game into its fundamental technical components, the cognitive and motor load on learners is reduced, facilitating the mastery of foundational movements. Expected outcome: Improved ball control, greater stability in shooting form, and enhanced accuracy in passing and receiving.

Skill drills with movement (e.g., passing while moving, shooting on the move): Rationale: Once students mastered basic techniques, drills involving movement were incorporated to simulate real-game situations. Expected outcome: Improved ability to execute technical skills in motion, a critical requirement during gameplay.

Basic tactical instruction and scrimmages (e.g., half-court offensive and defensive sets, full-court 5-on-5 gameplay): Rationale: This component serves as a comprehensive application of previously acquired skills and was essential for maintaining student engagement. Expected outcome: Enhanced decision-making abilities and improved technical application in competitive, game-like environments.

3. Connection to the research hypotheses:

The control group served as the baseline for this study. It was anticipated that participants in this group would demonstrate some improvement in basketball-specific skills due to direct practice. However, we hypothesize that the potential for improvement would be limited, since this training approach does not explicitly address functional movement competencies. Consequently, we predicted that the magnitude of skill improvement in the control group would be significantly lower than that of the experimental group. Furthermore, the control group would show no significant changes in FMS scores or in measures of psychological well-being.

This comparative design enabled the study to determine whether, within a finite instructional period, investing time in optimizing the body’s “hardware” (via functional training) produces greater improvement in overall basketball competence, physical fitness, and mental health than focusing solely on refining technical “software” (traditional training).

III. Methods for standardizing exercise intensity between the two groups

1. Objective methods for directly measuring exercise intensity

(1) Using heart rate monitoring devices: Heart rate is a commonly used physiological indicator for measuring exercise intensity.

Tools and methods: During the study, each participant wore a heart rate monitoring device (such as a heart rate strap or a smart wristband).

Each student’s predicted maximum heart rate was calculated using the formula (220-age), and target training heart rate zones were set:

Moderate intensity: 60%–70% of maximum heart rate.

Moderate-to-high intensity: 70%–85% of maximum heart rate.

Heart rate data were recorded before, during, and after each training session to calculate the average heart rate and ensure participants remained within the target range.

Data recording and analysis: All heart rate data were downloaded and analyzed uniformly after each training session. If a student’s heart rate was significantly outside the target zone (below 60% or above 85%), researchers would promptly record it and adjust it in subsequent training sessions.

(2) External workload regulation

Load standardization in the experimental design:

Experimental group: Participants utilized standardized equipment to maintain a consistent training load. This included: Medicine balls: Every student used a medicine ball of the same specification (weight maintained at 2 kg). Mini-bands: A specification with a moderate resistance coefficient was selected to ensure a similar training load for all students. TRX training: The angle and repetition count of movements were controlled to standardize the load level.

The activity load for the control group was primarily limited by the frequency of instructional movements (e.g., the number of repetitions per minute for stationary single-hand dribbling drills) and the number of sets. Specific operational methods: The experimental sessions strictly adhered to time controls for each exercise (e.g., 30 seconds of exercise/20 seconds of rest) and standardized loads (e.g., squats required a full range of motion from standing to a 90-degree knee bend).

Post-session monitoring was conducted for each student to ensure that the actual load of the training sessions did not exceed the designed requirements.

2. Subjective evaluation methods: Rate of perceived exertion (RPE)

Rating tool and implementation: This study employed the Borg RPE scale (6–20-point system) to monitor the exercise intensity of students during each training session. On the Borg scale, a score of 6 represents no significant exertion (e.g., standing or walking), while 20 signifies maximal exertion (e.g., sprinting or performing at maximum load).

Before the formal start of the experiment, all participants received training on the RPE scale to familiarize themselves with its rating criteria. For example: RPE of 12–14: Moderate-intensity exercise (feels sustainable). RPE of 15–16: Moderately high-intensity exercise (requires effort but can still be maintained for a period). RE participants were required to assess their own training intensity and record their RPE value at the midpoint and end of each training session.

The target intensity range for this study was set at an RPE of 12–16 (moderate to moderately high intensity).

The average RPE scores for the experimental and control groups were compiled after each session and compared using an independent samples t-test to ensure the relative consistency of exercise intensity.

3. Indirect methods for intensity control

(1) Standardization of movement time and frequency:

By strictly regulating the completion time (e.g., a standard of 30 seconds) and the number of sets (e.g., 3 sets) for each exercise, a basic uniformity of exercise intensity was maintained. Operational method: Supervisors ensured that each student completed the movements and rest periods according to the prescribed rhythm during the sessions.

(2) External load control:

For both the experimental and control groups, exercise load parameters were limited or increased (e.g., using medicine balls of a uniform weight, specific resistance levels for mini-bands, or controlling the duration of gameplay segments) to distribute the same physical load evenly between the two groups.

(3) Video assessment technology:

Indirect assessment was performed by analyzing video recordings to evaluate factors such as the fluidity of key movements and the visualization of power output in both groups.

4. Data aggregation and analysis

RPE and heart rate data: The RPE values (subjective perceived intensity) and average heart rate (objective measured data) obtained from each training session were recorded separately.

The exercise intensities of the experimental and control groups were compared weekly to determine if there were any significant differences. If a significant difference was found, adjustments were made to the equipment load for the experimental group or the frequency of training drills for the control group to better equate the training loads.

Outcome evaluation: The final evaluation of the intensity control throughout the intervention process was based on a combination of multiple indicators, including RPE, heart rate, and exercise load. If significant differences in intensity between the two groups were found, this would be detailed in the limitations section of the study.

This multi-faceted monitoring strategy was designed to ensure the comparability of exercise intensity, thereby strengthening the internal validity of the research findings.

2.4 Evaluation indicators

This study used three primary categories of evaluation indicators, i.e., Basketball-specific sports skills, Functional Movement Screen (FMS) performance, and psychological health status, to assess the effects of the intervention.

(1) Sports skills: The evaluation consists of three basketball-specific skills: 30-second continuous shooting under the basket, full-court shuttle dribble layups, and lateral slide movement. Data from both groups before and after 12 weeks of training were collected and compared to assess basic sports ability and the degree of improvement.

(2) Functional movement screen (FMS) test: The test consists of seven screening items: squat, hurdle step, straight lunge, shoulder flexibility, active straight-leg raise, trunk stability push-up, and trunk rotation stability. Each movement in the FMS test is rated on a 4-point scale (3, 2, 1, and 0). If any pain occurs during the screening, the item is recorded as 0 points. In the shoulder collision test, push-up test, and kneeling back extension tests, if pain occurred, the result was recorded as positive (+), and the corresponding screening test was skipped, and scored 0. A horizontal and vertical comparison of the experimental data before and after 12 weeks of training was conducted for both groups, along with a comparison of data improvement.

(3) Psychological health assessment: The psychological health levels of both groups were assessed using the Symptom Checklist-90 (SCL-90) [8] before and after the 12-week training. The SCL-90 is a widely used psychological health assessment tool, primarily employed to evaluate a variety of psychological symptoms and their severity as experienced by an individual over the past week. The scale comprises 10 factors (consisting of 90 items) that comprehensively assess an individual’s psychological health status from multiple dimensions, including sensations, emotions, thoughts, consciousness, behavioral habits, interpersonal relationships, and patterns of eating and sleeping. The 10 factors are: Somatization: Physical discomfort associated with psychological distress, such as headaches or chest pain. Obsessive-Compulsive: Unwanted and persistent thoughts, impulses, and behaviors that an individual cannot get rid of. Interpersonal sensitivity: Feelings of unease, inferiority, and negative expectations in social interactions. Depression: Characterized primarily by low mood, diminished interest or pleasure, loss of energy, and pessimism. Anxiety: Feelings of restlessness, being on edge, nervousness, and tension. Hostility: Thoughts, feelings, and behaviors such as annoyance, argumentativeness, throwing objects, and even temper outbursts. Phobic anxiety: Fear of specific situations, places, or objects. Paranoid ideation: Paranoid thinking, including suspicion, hostility, and ideas of reference. Psychoticism: Reflects symptoms such as disordered thinking and distorted perception. Additionally, the scale provides a total score that reflects the individual’s overall level of psychological distress. Each item is scored on a 5-point rating system (1–5 points, ranging from no symptoms to severe symptoms). The total score and factor scores were analyzed. A smaller total score indicates better psychological health, and a smaller factor score indicates fewer negative symptoms in that factor. To ensure the reliability of this measurement tool within the present study, an internal consistency reliability test was conducted on the collected questionnaire data. The results showed that the Cronbach’s alpha coefficient for the SCL-90 total scale was 0.963. The Cronbach’s alpha coefficients for the individual factors were as follows: Somatization, 0.882; Obsessive-Compulsive, 0.868; Interpersonal sensitivity, 0.864; Depression, 0.901; Anxiety, 0.875; Hostility, 0.831; Phobic anxiety, 0.803; Paranoid ideation, 0.803; Psychoticism, 0.863; and Other, 0.771. According to generally accepted standards, a Cronbach’s alpha coefficient above 0.7 indicates that a scale has good reliability. The results of this measurement demonstrate that the scale possesses excellent internal consistency and is suitable for the assessment of psychological health in this study.

Selection and analysis of basketball skill tests and FMS

(1) Selection of basketball skill tests

This study selected three basketball-specific skill assessments, i.e., 30-second continuous shooting under the basket, full-court round-trip dribble layup, and the triangle lateral shuffle.

Rationale: Continuous shooting and full-court dribble layups measure shooting accuracy, dribbling ability, speed, and mastery of core basketball fundamentals. The triangle lateral shuffle assesses agility, defensive movement speed, and coordination, which are crucial for basketball defense. These test movements are simple, scalable, and widely applicable, making them suitable for male university students with limited basketball experience. The tests are challenging but not overly technical, allowing for accurate measurement of skill progression over time.

Suitability for the general university student population: These test movements are easy to train and universally applicable, making them suitable for male university students who are not sports majors. For students with a basic level of basketball proficiency, the tests are challenging but do not have a high technical barrier, enabling a quantifiable assessment of their improvement in fundamental skills.

Validated application: These tests are widely used in university basketball teaching and research, and related studies have demonstrated their validity and reliability in measuring the basketball-specific skills of university students.

Testing objective: The aim is to assess whether students’ basic basketball skills (such as shooting, dribbling, and defensive agility) have improved after a short-term training intervention, providing direct data to support the effectiveness of incorporating functional training into basketball classes.

(2) Selection of the FMS

This study incorporated seven indicators from the FMS system for assessment, including deep squat, hurdle step, in-line lunge, shoulder mobility, active straight-leg raise, trunk stability push-up, and rotary stability.

Rationale for selection: The FMS was selected due to its status as a widely validated and reliable tool for evaluating fundamental movement patterns that are foundational to complex athletic skills. The seven tests provide a holistic assessment of kinetic chain mobility and stability, systematically evaluating neuromuscular coordination (e.g., deep squat, in-line lunge), dynamic flexibility (e.g., active straight-leg raise), and core stability (e.g., trunk stability push-up, rotary stability).

General applicability to the university student population: The FMS test is designed for non-professional athletes, and its simple testing methods make it suitable for the general population. As the research subjects, male university students generally have a good foundation of movement and a lower incidence of sports injuries, which allows the FMS to effectively evaluate their progress in motor function, especially the improvement of their movement patterns resulting from functional training.

Testing objective: FMS evaluates multiple aspects of physical performance. The Deep Squat assesses lower-body strength and stability, while the Hurdle Step and In-Line Lunge measure dynamic balance and coordination. The Active Straight-Leg Raise evaluates flexibility and hip mobility, and Shoulder Mobility tests upper-body range of motion and flexibility. Additionally, trunk stability tests examine core strength and control. Overall, the FMS helps to identify potential movement dysfunctions and provides an effective tool to assess improvements in comprehensive physical capabilities following functional training.

(3) Validity and specificity of the tests

Commonly used and validated: The basketball-specific skill testing methods are standard procedures widely adopted in teaching and training, especially in university physical education courses. Their validity and repeatability have been verified by numerous related studies.

Established assessment system: The FMS is a universal assessment system in the fields of sports medicine and functional training. It is recognized for its ability to help identify movement limitations and functional deficits and is also used to evaluate the effectiveness of exercise interventions. Its applicability and reliability have been validated by extensive research.

Aspects of physical and motor function assessed: The basketball skill tests primarily evaluate specific sports skills (shooting accuracy, dribbling technique, agility, and defensive ability). The FMS, on the other hand, assesses the body’s functional movement capabilities, including flexibility, stability, coordination, strength, and the quality of movement patterns.

The selection of these basketball skill tests and the FMS was based on the specific skill demands commonly found in university basketball instruction and the scientific and practical utility of functional movement assessment. The basketball skill tests can objectively evaluate the improvement in specific skills resulting from the training, while the FMS can reflect improvements in motor function and the correction of potential movement flaws, providing multidimensional support for the effectiveness of functional training. The combination of these two types of tests ensures a comprehensive evaluation of the training’s effects from both technical and physical function perspectives.

Rationale for selecting the SCL-90:

The researcher’s choice of the SCL-90 scale was primarily based on the following points:

(1) Broad applicability and authority: The SCL-90 is one of the most widely recognized psychological health assessment scales, used globally across clinical practice, scientific research, and mental health screening. (2) Comprehensive assessment scope: The tool evaluates a wide range of psychopathological symptoms and offers an in-depth overview of an individual’s psychological state. (3) Standardization and reliability: The SCL-90 is a standardized and highly reliable tool, validated in both university populations and athlete groups. Its high Cronbach’s α = 0.963 confirms excellent internal consistency for this study.

Validation in similar contexts and populations:

The SCL-90 scale has been extensively applied and validated in contexts and populations like those in this study: General university student population: The SCL-90 has been widely used to assess mental health in non-athlete college populations, demonstrating strong reliability and validity. Athlete population: The scale has also been applied to athlete populations, including for the mental health assessment of university athletes. Although some research suggests its factor structure may require further validation in this specific group, it is still considered an effective tool for assessing the overall severity of psychological symptoms in athletes. Research on the impact of physical training: Several studies have also employed the SCL-90 to investigate the effects of physical activity on mental health, which is highly relevant to the article’s theme (the impact of functional training on mental health). For instance, some research has used the SCL-90 to examine the influence of different levels of physical activity on various dimensions of university students’ mental health.

2.5 Statistical analysis

The collected data were analyzed using SPSS 26.0 (IBM, Armonk, NY, USA). The Shapiro-Wilk test was applied to examine the normality of data distributions, and Bartlett’s test was used to assess the homogeneity of variances. Data that followed a normal distribution were expressed as mean ± standard deviation (SD), and between-group comparisons were conducted using independent-samples t-tests. Data with a skewed distribution or unequal variances were analyzed using the Mann-Whitney U test and are presented as the median (M) and interquartile range M (P25, P75). Categorical variables were expressed as frequencies and percentages, and differences between groups were analyzed using the chi-square test or Fisher’s exact test, where appropriate. A p-value of < 0.05 was considered statistically significant.

For analyses involving multiple comparisons, the Bonferroni correction was employed to control the overall Type I error rate. First, the overall significance threshold was set at α = 0.05. The total number of independent hypothesis tests (m) was determined, and the adjusted significance level for each test was calculated as α’ = α/m. Each p-value obtained from the statistical tests was then compared with the adjusted α’; statistical significance was concluded only when p < α’.

2.6 Data integrity, attendance monitoring, and handling of participant attrition

Participant attrition:

Participants in this study underwent a screening process before the intervention. Initially, a total of 130 students were recruited and assessed. Before the formal 12-week experiment began:

Exclusion via questionnaire screening: Based on the “Physical Health and Sports Experience Questionnaire”, 5 students (2 from the experimental group, 3 from the control group) were excluded because they did not meet the inclusion criteria (e.g., having a history of professional training or health issues that could affect the experiment). Early withdrawal: An additional 5 students (3 from the experimental group, 2 from the control group) voluntarily withdrew before the intervention started for personal reasons (such as scheduling conflicts).

Therefore, the final effective sample that entered and completed the 12-week intervention study consisted of 120 students (60 in the experimental group and 60 in the control group). All data analysis in this study is based on these 120 participants who completed the entire research protocol. This analytical strategy is known as a Completer Analysis.

Attendance rate monitoring and verification:

To ensure the strict implementation of the research protocol and achieve a 100% attendance rate, we implemented the following monitoring and verification measures: Dedicated personnel: A research assistant was assigned to each group to be responsible for taking attendance at every session. Advance reminders: Students were notified of the time and location of each training session one day in advance. A second reminder was sent one hour before the session was scheduled to begin on the day of the training. Paper-based sign-in: All participants were required to sign in at both the beginning and the end of each of the 24 training sessions to confirm their full participation. Immediate follow-up: The research assistants’ duties included checking the sign-in sheets within 5 minutes of the start of a session. If any student was found to be absent, they were immediately contacted by phone or text message to ascertain the reason for their absence. Make-up session mechanism: A weekly “make-up session” was pre-established to accommodate students who might miss a class due to illness or other important reasons. Any student who was absent for an unavoidable reason (requiring relevant documentation, such as a doctor’s note) was required to complete a make-up session with identical content and intensity within the same week. Research records show that a total of 8 make-up sessions were arranged for individuals over the entire experimental period, and all students complied with this rule, thereby ensuring that every participant completed all 24 training sessions.

Questionnaire response rate monitoring and verification:

To guarantee a 100% response rate for both the pre- and post-intervention questionnaire surveys, the following strategies were adopted: On-site centralized completion and collection: All questionnaires (including the initial “Physical Health and Sports Experience Questionnaire” and the second survey at the end of the experiment) were distributed collectively during class time in a classroom or at the training venue. Sufficient time allocation: Researchers provided participants with ample time to complete the questionnaires on the spot and offered necessary guidance to answer any questions. Immediate collection and verification: After the questionnaires were completed, they were collected uniformly on-site by a research assistant. During collection, the assistant checked each questionnaire individually for any missing items, ensuring the validity and completeness of every form. This process effectively prevented the loss or failure by submitting questionnaires.

Handling of missing data:

This study employed a completer analysis (also known as a Per-protocol analysis) strategy, meaning that only the data from the 120 participants who completed the full 12-week intervention and participated in all pre- and post-test assessments were analyzed. Participants who withdrew before the experiment began were excluded from the final analysis. Thanks to the rigorous attendance and questionnaire collection monitoring mechanisms described above, there was no missing data for this final sample of 120 participants. Consequently, it was not necessary to use complex statistical methods, such as Multiple Imputation, to handle missing values in this study.

3.1 Sports skills data and improvement degree

After 12 weeks of functional training, both groups demonstrated improvements in all three sports skills tests, including lateral slide movement, 30-second continuous shooting under the basket, and full-court shuttle dribble layups. The experimental group showed significantly better performance in lateral slide movement, and 30-second continuous shooting under the basket than the control group (Cohen’s d = 0.452, Cohen’s d = 0.952, p < 0.05, Table 6). Furthermore, comparisons of the degree of improvement showed that the experimental group outperformed the control group across all three skill measures (Table 7). To ensure the reliability of these findings, the Bonferroni correction was applied to adjust the significance threshold for multiple comparisons. Given that the number of comparisons was m = 2 (pre-intervention vs. post-intervention), the adjusted significance level was calculated as:

Comparing the original p-value with the adjusted significance level:

Pre- vs. post-treatment comparison:

Original p-value: < 0.001.

Adjusted α: 0.025

Since < 0.001 < 0.025, we can reject the null hypothesis. This means the post-experiment results are statistically significant.

Pre- vs. post-treatment comparison: Since the p-value < 0.001 is less than the adjusted significance level of 0.025, it shows statistical significance.

Therefore, after applying the Bonferroni correction, it can be concluded that both groups showed significant improvements in the three indicators of motor skills post-experiment.

3.2 FMS test data and improvement degree

After the experiment, there were no significant differences between the groups in shoulder flexibility, trunk stability push-up, and trunk rotation stability (Cohen’s d = 0.529, 0.499, 0.428, p > 0.05). In contrast, the experimental group, which performed functional training, achieved significantly greater improvements in the remaining four FMS components compared with the control group. Specifically, statistically significant differences were observed in deep squat, hurdle step, straight lunge, active straight-leg raise (Cohen’s d = 0.475, 0.467, 0.515, 0.421, respectively; p < 0.05, Table 8). After the 12-week training, both groups showed improvements in the FMS results, with the experimental group achieving an overall improvement of 25.17%, and the control group achieving 13.70%. The difference in improvement for shoulder flexibility was minimal, while there were significant differences in improvements in squat, hurdle step, straight lunge, active straight-leg raise, trunk stability push-up, and trunk rotation stability between the two groups (Table 9). After Bonferroni correction, both groups showed significant improvement in the seven indicators of the FMS test post-experiment.

3.3 Psychological health evaluation

After the experiment, there was no significant difference in terror scores between the groups (Cohen’s d = 0.494, p > 0.05); however, for other indicators, the experimental group showed significantly lower scores compared to the control group (Cohen’s d = 0.684, Cohen’s d = 0.469, Cohen’s d = 0.518, Cohen’s d = 0.389, Cohen’s d = 0.390, Cohen’s d = 0.524, Cohen’s d = 0.608, Cohen’s d = 0.456, p < 0.05, Table 10). Post-experiment, the scores for each dimension of the SCL-90 scale decreased to a certain extent in both groups. The overall reduction in the experimental group reached 41.76%, while the overall reduction in the control group was 28.16%. There was a considerable difference in the magnitude of the score reductions between the control and experimental groups across the various dimensions of the SCL-90 scale (Table 11). After Bonferroni correction, both groups showed significant improvement in the scores for each dimension of the SCL-90 scale post-experiment.