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Study design
This cross-sectional observational study was conducted between September 10 and October 20, 2023, at Beijing Sports University, Beijing, China. The study adhered to STROBE guidelines.
Sample size calculation
A sample size of at least 30 participants was calculated in advance by PASS 2021(NCSS LLC., Kaysville, U.T., USA) to allow for an inter-rater test-retest reliability study that would result in an ICC of at least 0.75, with an expected 0.9 and beta of 0.8. alpha was 0.05, and the dropout rate was 10%.
Participants
30 Participants were recruited from the Beijing Sports University through announcements and personal referrals. Participants were eligible for inclusion if they were 17 ∼ 25 years college students; had navicular drop test > 10 mm; had no history of lower limb injury within 6 months; had no history of surgery on hip, knee, and ankle joints; and had no serious medical conditions. Participants were excluded if they had vestibular dysfunction or other diseases that affected balance; taking unknown drugs; rheumatoid, neurological, or other causes that affected the hip and knee joints muscles or function.
Written informed consent was obtained from the participants before the start of the study. The Sports Science Experiment Ethics Committee of Beijing Sport University approved the study protocol (2,023,154 H). This trial was registered at the Chinese Clinical Trial Registry (ChiCTR2300075906) on 19/09/2023.
Testing procedures
The Guidelines for Reporting Reliability and Agreement Studies were used to implement and report this interrater and test-retest reliability study [26]. To examine the inter-rater and test-retest reliability of the YBT, the extent of agreement and reproducibility were calculated between the measurements by two different raters who were fully experienced in the use of YBT. In the first trial, the participant would perform 6 practice sessions to eliminate the learning effect before the formal YBT-LQ and perform the test by the rater within 20 min of the practice session. Subsequently, after a 20-minute break, the test was administered by another rater. A 14-day interval was set between the test and the retest to prevent actual changes in dynamic balance ability and memory effects.
All raters were pre-trained and proficient in the testing process. Hiding test data immediately after completion of the test so that the rater did not have access to each subject’s previous score to minimize bias. All test data would be double-entered into the computer to ensure proper.
Navicular drop test
The navicular drop test (NDT) was performed to measure the change in height of the medial longitudinal arch of the foot. The participant seated in a chair with the knee flexed to 90° and the second toe aligned with the knee so that the talonavicular joint was in a neutral position. The height between the ground and the navicular tuberosity was measured and noted by the evaluator using a vernier caliper. Then, the participant stood up and measured the height again. The difference between the height of the navicular tubercle in the non-weight-bearing and weight-bearing positions of the foot was calculated. Repeated the test 3 times on both the right and left sides and take the average value. Navicular drop exceeding 10 mm was diagnostic of a flexible flatfoot [27].
Leg length measure
Participants were instructed to lie in a supine position. They lifted their hips and returned to the starting position. To make sure the pelvis was in alignment, the participant were passively straightened the legs. The participants’ flexible flatfoot side leg length was measured centimeters from the anterior superior iliac spine (ASIS) to the most distal part of the medial malleolus using a cloth tape. This measurement was used to normalize the maximal reach distance. The leg length measurement was carried out before the first trial.
Y balance test lower quarter
The test was carried out by the standardized YBT methodology advised by Plisky et al. [13]. The trial protocol was conducted on the side leg with the flexible flatfoot, which was the only difference from the YBT-LQ. The YBT-LQ was completed using the Y Balance Test Kit. Before the test, participants were shown the YBT demonstration video and provided detailed instructions on how to take it. According to the previous research protocol [28,29,30], the practice phase consisted of six trials in three different directions in order to minimize the learning effect. Participants performed the YBT-LQ at least 3 times and up to 6 times in each direction after the practice phase. All tests were conducted with participants standing barefoot on the pedals, with their single lower limb supported by the flatfoot side. The distal end of the second toe of the supporting leg was located behind the red indicator line, and the contralateral lower limb was extended in three directions, pushing the rectangular indicator block as far as possible with the tip of the foot. Then, recorded the reading of the proximal end of the rectangular block to the nearest 0.5 cm. The outcome of that test was deemed invalid if participants were (1) unable to controllably return to the starting position, (2) accelerate the rectangular block with the outstretched foot to move it farther, (3) touch the ground with their forefoot, (4) or contact the top of the rectangular block for support. The maximal reach distance in each direction was recorded for the 3 valid tests.
The normalized maximal reach distance per reach direction was calculated as follows (Eq. 1) and used as an outcome measure. Additionally, Filipa et al. [31] supplied a formula (Eq. 2) that was used to determine the normalized composite score (CS).
$$\begin{array}{l}Normalized{\rm{ }}\ maximal{\rm{ }}\ reach{\rm{ }}\ distance{\rm{ }}\left( {\% {\rm{ }}\ leg{\rm{ }}\ length{\rm{ }}\left[\ {LL} \right]} \right){\rm{ }} = {\rm{ }}\\\left( {absolute{\rm{ }}\ maximal{\rm{ }}\ reach{\rm{ }}\ distance{\rm{ }}\left[ {cm} \right]} \right){\rm{ }}/{\rm{ }}LL{\rm{ }}\left[ {cm} \right]){\rm{ }} \times {\rm{ }}\ 100\% \end{array}$$
(1)
$$\begin{array}{l}Composite{\rm{ }}\ score{\rm{ }}\left( {\% {\rm{ }}LL} \right){\rm{ }} = {\rm{ }}\\\left\{ {\left( {AT{\rm{ }} + {\rm{ }}PM{\rm{ }} + {\rm{ }}PL} \right){\rm{ }}/{\rm{ }}\left( {leg{\rm{ }}\ length{\rm{ }} \times {\rm{ }}3} \right)} \right\}{\rm{ }} \times {\rm{ }}100\% \end{array}$$
(2)
Statistical analysis
Reliability refers to the consistency of a test or measurement [32]. Calculating the ICC can demonstrate relative reliability, which is the degree to which individuals maintain their location in a sample with repeated measurements [33]. The maximal reach distance in each direction and composite score were calculated as absolute values and values normalized to leg length. The relative reliability of the maximal reach distance in each direction and of the composite score was analyzed by calculating ICC. The inter-rater reliability was determined using the ICC(2,1) and the test-retest reliability was determined using the ICC(3,1).ICC< 0.50 was considered “poor”, 0.50<ICC< 0.75 was considered “moderate”, 0.75<ICC< 0.9 was considered “good”, and ICC ≥ 0.90 was considered “excellent” [24].
The absolute reliability of the data was assessed using the standard error of measurement (SEM) that estimates the amount of error related to the measurement (Eq. 3). Moreover, the minimal detectable change (MDC95%) and the smallest worthwhile change(SWC) were calculated using the formula (Eq. 4 and Eq. 5) to ensure the differences between test and re-test measurements were real and outside the error range [24, 34]. It is worth mentioning that the study was conducted on a population of college students with flexible flatfoot, and there were no strict inclusion requirements for the fitness status of the participants, so the SWC calculated by 0.6 multiplied by SD is relevant for both high and low fitness level participants [34]. For all analyses, the Statistical Package for the Social Sciences (SPSS version 27.0) was used (IBM Corp., Armonk, N.Y., USA).
$$SEM = SD * \sqrt {1 – {\rm{ICC}}}$$
(3)
$$MDC95\% = 1.96 * \sqrt 2 * SEM$$
(4)
Bland-Altman plot is a simple and intuitive graphical method of responding to data agreement. The 95% limits of agreement (LOA) was defined as two standard deviations above and below the mean of the difference scores. Plotting the difference between the YBT-LQ and comparison test values versus the mean of the YBT-LQ and comparison test scores yielded Bland-Altman plots with 95% limits of agreement, which were used to visually display measurement errors against true values. Statistical analyses were performed using MedCalc, version 19.4 for Windows (MedCalc Software, Ostend, Belgium).
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