Introduction

Physical Literacy (PL) is a new concept that has been widely disseminated internationally in the last three decades.1 This concept has attracted great attention2,3,4,5,6,because it not only emphasizes the use of physical activity (PA) to cope with the health crisis of the epidemic of chronic diseases in contemporary societies7,8,9, but also provides doctrinal support for the integration of physical activity into the whole process of human lifespan10.PA insufficiency, which is overweight and obesity rates, and the rising prevalence of chronic diseases among Chinese adults, has become important public health issues. 11The 2019 Outline for Building a Strong Sporting Nation, issued by China’s State Council, explicitly states the strategic goal of “enhancing people’s PL.” 11 Boosting PL is a new initiative to address PA insufficiency and declining health in adults9,11,13. PL is a required literacy for individuals to promote and maintain positive PA behaviors and health throughout the lifespan. 14,15 Sport school college students are early adults and need more attention.

A necessary prerequisite for realizing individual or group PL enhancement is to clarify how PL can be measured16, or even if it can be measured17. Whitehead (1977) defines PL as the motivation, confidence, physical ability, and knowledge and understanding that individuals need in PA, emphasizing its lifelong and holistic nature. 16,18,19 From a psychological perspective, the formation of PL is closely related to an individual’s perception- behavior theory16,20, i.e., through the interaction between the body and the environment, an individual is able to better understand his or her own abilities and enhance athletic performance19,21. The Perceived Physical Literacy Instrument (PPLI) is a prominent tool in the assessment of perceived physical literacy. 13,22,23,24As an assessment tool, the PPLI has been used by researchers in several countries, including China21,22,23, Spain25, France14, Turkey26, and has been shown to be effective for physical education teachers on several occasions22,26. Educational / Sports college students, as future physical education teachers, may become implementers of public health policies (direct participants, practical significance for China’s 2030 Strong Nation Strategy). The characteristics of their perception of PL require greater attention.

After three decades of development, a core group of authors has formed in the research area of PL. 11 Evidence-based research on the relationship between PL and health has been ongoing, but consideration of the role of PL in promoting positive health behaviors has been limited. 27 Perception-behavior theory is closely related to embodied cognition, which holds that cognition is shaped through bodily experience and activity, rather than through information-processing processes independent of the body. 28 According to the monistic embodied nature of PL 29, the embodied cognition of PL among educational/sports college students focuses on the perception of “affordances” in the educational/sports environment through physical practice30, so as to form a deep understanding of motor skills. The embodied cognition of teachers’ physical literacy focuses on how to help students understand motor skills through physical demonstration and verbal guidance31, thereby forming “affordances” within the teaching environment. The embodied cognition of undergraduate students’ (non-physical education majors) physical literacy, driven by the public health imperative for wellness, fosters “affordances” for a health-promoting environment for physical activity. 23 It is evident that the embodied cognition of perceived PL among educational/physical education college students exhibits characteristics of a motor -environmental affordance; the embodied cognition of perceived PL among physical education teachers exhibits characteristics of a teaching-environmental affordance; and the embodied cognition of perceived PL among undergraduate students (non-physical education majors) exhibits characteristics of a health-environmental affordance. Furthermore, a more direct expression is that the environmental nourishment of embodied cognition in the perceived PL of education/physical education college students differs from that of physical education teachers and undergraduate students (non-physical education majors). This may also represent a gap in theoretical value (the framework linking PL with Perception-Behavior Theory and embodied cognition).

Based on previous research and the aforementioned study materials, our research objective is to observe the physiological cross-sectional profile of perceived PL among educational/physical education college students (cross-cultural validation of PPLI).

Our research examines the psychological structure characteristics of PL among college students in education/physical education institutions as emerging adults (H0, verifying Whitehead’s PL attributes), providing evidence for longitudinal sequential observations of PL features in adult groups (practical value).

Educational/physical education college students, as potential reserves for physical education teachers, may become implementers of public health policies (practical significance for China’s 2030 Strong Nation Strategy). Therefore, we selected the PPLI to verify its differences in psychological structure characteristics compared to physical education teachers’ PL (H1).

Based on the well-known gap in embodied cognitive environmental affordances of perceived PL among the three groups (educational/physical education college students, physical education teachers, and undergraduate-non-physical education students), our study (theoretical value) focuses more on observing the embodied cognitive environmental affordance characteristics of perceived PL among educational/physical education college students (H2).

Methods

Expert groups

Our research focuses on structural modeling of PL for educational/physical education college students. The naming of the factor structure of the structural model of PPLI is one of the difficulties. The names of the factor structures were determined, according to Whitehead’s concept of PL. We invited five senior researchers (two professors and three associate professors, three of whom were PhD), to help us work together on the analysis of the data and the naming of the structural factors, as well as experts to help with the content reliability validation of the PPLI.

The first meeting was conducted after all the researchers collected research information on the three keywords of PL, PPLI, and embodied cognition, respectively. In the first meeting, H0, H1, and H2 were identified, and the theoretical framework of PPLI was identified as Whitehead’s concept of PL and embodied cognition in the perspective of perception-behavior theory. Scientific papers, in China National Knowledge Infrastructure (CNKI, Chinese database) and five English databases (ProQuest, ERIC, Science Direct, Scopus and Sport Discus), were searched.

Design of PPLI

The second meeting was conducted jointly by all the researchers and the expert group. The group began by jointly identifying 18 items for the PPLI. The PPLI has been repeatedly validated: it demonstrates excellent test-retest reliability (ICC, 0.81–0.91, > 0.7), good to excellent internal consistency (α, 0.78–0.88; ω, 0.71–0.77), and good convergent validity (correlation range: 0.41–0.87). 21,23,24,25 Secondly, it was discussed together, Whitehead’s concept of PL (two kernel, internal and external; six attributes; two stages)21,23,24,25.From the research data, it can be found that the internal kernel includes 3 attributes of the first stage (motivation, confidence and physical competence, and interaction with the environment); while the external kernel includes 3 attributes of the second stage (knowledge and understanding, physical self-awareness and self-confidence, and self-expression and communication with others).The results of the validation of the physical education teachers’ PPLI were further discussed, and it was determined that the embodied perceptions of their PL were mainly reflected in the 3-Dimensions 9-Items. (see Table 1)

Table 1 Items of the original 18-item version of perceived physical literacy Instrument.
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Subsequently, the expert panel collaborated with all authors to establish the back-translation process for the PPLI, ensuring scientific rigor and accuracy in cross-cultural research. The back-translation of the PPLI was jointly completed by one professor and two authors. One author first translated the PPLI from English to Simplified Chinese, then submitted it to the professor. The professor verified the translation’s accuracy and clarity; if issues were found, the first step was repeated before submitting to the second author. The second author then translated the simplified Chinese version back into American English and submitted it to the professor. The professor conducted a second verification to ensure the accuracy and clarity of the second author’s translation. If issues were identified, further discussion was required until the back-translation met the fundamental requirements of scientific research (fidelity to the original text, scientific rigor, accuracy, and precision).

All authors worked together to finalize the preface section and the basic information section of the PPLI. The preface section of the questionnaire included a confirmation format for the informed consent form (once completed, it is deemed as signing the informed consent form). In the Basic Information section, add entries for demographic variables (category, gender, age, grade, sport, sport level, coaching level, and education). The analysis of demographic variables was not included in our study design, but the addition of a basic information section to the PPLI helped to improve the reliability of the sample.

Data collection and sampling

The present study was a cross-sectional observational study (the subjects of the study were educational/sports college students, aged 18 years and above). The data were collected with an ethical review based on the principles of the Declaration of Helsinki (the review committee was the school of the first author, document number: NSI-2024PE-0417).

Prior to the start of sampling, preparations related to data collection were carried out.

The version of the PPLI used in our study consisted of 18 items. We set a sample size of > 360 to ensure the requirements of the most optimal model32,33, and to meet the requirement of having 20 data per item in pursuit of the optimal model34. From October 2024, data collection began. We used the Questionnaire Star questionnaire platform to create the questionnaire, and generate an electronic QR code to facilitate its distribution. The first round of questionnaire distribution was conducted through the WeChat tool platform. Dissemination among college students at two colleges in Nanjing (Nanjing Sport Institute and Nanjing Normal University). At two universities, eight faculty members (specializing in physical education or sports training, teaching 400 students) were recruited to assist in distributing the first round of questionnaires.

Each respondent, after filling out the questionnaire, immediately generates a piece of data (which can be observed by the researcher on the Questionnaire Star platform). Each respondent, after completing the questionnaire, was encouraged to further disseminate the questionnaire by snowballing. Researchers are confident in the sample size design, because the authors hail from two distinct provinces within China. Additionally, during the research design phase, we established a five-member research team, with three experts drawn from two other universities (both of which have undergraduate programs in physical education and sports training). After the first round of questionnaires (21 days, 3 weeks), we observed 480 responses (350 from Educational/Sports college students) via the Wenjuanxing platform. Consequently, we conducted a second round of distribution, recruiting two instructors from two additional universities (Nantong University and Shanghai Normal University) to distribute questionnaires to 200 students. The second round took 11 days (total 741 responses, 561 from the education/sports school students). The survey was halted when the data for the “Sports school student” option reached ≥ 450 (calculated based on a 20% attrition/outlier rate: 450 = 360 ÷ 0.8).

A special note is required: In the preamble section of the questionnaire, we conducted the collection of the Informed Consent Form (each respondent, by completing the questionnaire in its entirety, agrees with the content of the Informed Consent Form, and each piece of data indicates the signing of the Informed Consent Form.). Each respondent has the right to answer any question freely and can stop answering any question at any time. Each respondent was told that the purpose of the questionnaire, which was to conduct a scientific statistical study, was that the answers were not right or wrong in order to improve the validity of the questionnaire.

Every respondent was privacy-protected (the questionnaire only involved the collection of publicly available basic information), and no private data was collected or generated.

Data analysis

Data preparation is the first step in our data analysis study. SPSSAU24, an online professional data analysis platform, was chosen as the analytical tool for data computation. Data precision has also been taken into account by using rounding criteria and retaining percentile decimals, unless there are special requirements (e.g., P < 0.001).

We remeasured the content validity of the PPLI. Steps in content validity index (CVI) testing: item level (I-CVI) followed by scale level (S-CVI). Criteria for content validity tests: I-CVI ≥ 0.8, an acceptable criterion; S-CVI ≥ 0.9, an acceptable criterion. 35 Methodology for content validity validation: five senior researchers were invited to complete the assessment of the content relevance of each entry of the PPLI using a four-point Likert scale (1 = not relevant, 4 = highly relevant), followed by the use of EXCEL as a computational tool. Data storage and saving: After downloading the data from the Questionnaire Star platform, all the data were saved in a local EXCEL.

Data cleaning is the second step in data analysis. We began with a descriptive statistical analysis based on preliminary calculations of basic information, using percentage and frequency indicators. Descriptive statistics were done to guarantee the adequacy of the sample and to complete the qualification of the respondents. For clarity, we incorporated Grubbs’ test (p < 0.05, acceptable) to examine the exclusion/removal of outliers for each variable36. We used Cronbach’s alpha (> 0.6, an acceptable criterion,36 as an indicator to verify internal consistency for the total sample. The total sample was split into two SHEETs for storage, taking into account the principles of least amount of data (feeling satisfied) and average ratio (1:1, 37. Name one subset of the data SHEETEFA is for exploratory factor analysis (EFA), and another subset of the data SHEETCFA is for confirmatory factor analysis (CFA). The clear expression indicates that two data subsets are randomly split to facilitate further cross-validation. For SHEETEFA and SHEETCFA, internal consistency tests were performed separately (Cronbach’s alpha was calculated). Sampling adequacy was then assessed by calculating Kaiser-Meyer-Olkin (KMO) values (> 0.8) for both data subsets using the KMO index38. The KMO values for both data subsets were calculated using the KMO index.

Performing EFA calculations is the third step in data analysis. EFA calculations were carried out with the main goal of exploring the factor structure of SHEETEFA. To prevent small sample sizes or unsatisfactory kurtosis of variables, we used maximum likelihood estimation (an oblique rotation) for ideal parameter estimation, performed by Varimax rotation and with a factor of > 0.4 (otherwise deleted)39. Principal component analysis of SHEETEFA, using the Bartlett’s test of sphericity (p ≤ 0.001), analyzed the correlation between the scale items, with a commonality of greater than 0.40 for each item and a factor loading of greater than or equal to 0.32 used as a criterion38. Based on previous research, the criteria for factor deletion in EFA were established: First, EFA calculations were performed with the goal of retaining as many items as possible (N = 18) and dimensions [maximum dimensions, N = 6 (18/3)]; If an item exhibited factor loadings greater than or equal to 0.32 on two or more factors simultaneously, it was designated as a cross-item (to be deleted); If model fit remains unsatisfactory, qualitative criteria for item exclusion are adopted from the SUM team’s structural model for physical education teachers.

Performing the CFA calculations for SHEETCFA is the fourth step in data analysis.

The main goal of CFA is to perform data model refinement and identification of factor structures. The structural model of the PPLI, which focuses on model fitting for practicing CFA, calculates three indices of absolute, parsimonious, and incremental fit of the model. In particular, we chose the Standardized Root Mean Square Residual (SRMR ≤ 0.1) as the absolute model fit criteria36,40,41. Among them, we chose the parsimony normative fit index (PNFI > 0.5) and the parsimony goodness-of-fit index (PGFI ≥ 0.50) as the model parsimony fitting criteria38,40,41. In particular, we chose the comparative fit index (CFI > 0.95), the Tucker-Lewis index (TLI > 0.95), and the normative fit index (NFI > 0.95), as model incremental fit criteria38,40,41.

Results

Sample characteristics

According to the data monitoring of the questionnaire star platform, data collection for this study, 741 valid data, including 504 (32 days) for educational/sports college students, which meets the requirements of sample adequacy (180 for each of the two subsets of the basic objectives). The detailed explanation was deleted/data not included: Total of 237 cases (237 = 741 − 504), including 180 cases from eligibility screening (deleted, non-educational/sports college students) and 57 outliers (deleted, Grubbs test, p < 0.05).32

CVI In terms of content validity, there is acceptable content validity, with the I-CVI of the PPLI ranging from 0.8 to 1 and the S-CVI above 0.9 (SCVI = 0.93). (Cronbach alpha) alpha coefficient, indicating that internal consistency is satisfied and acceptable, by estimating the dataset missing value of 0.93 (> 0.7).

Demographic characteristics This study was not intended to be a controlled or sequential study; however, we performed demographic characterization, conducted an eligibility review, and found that the data were able to meet the basic requirements of this study (see Table 2). (1) Gender: 47.02% of males 237, 52.98% of females 267, with females outnumbering males. (2) Age: 18–19 years 214 accounted for 42.46%, 20–21 years 195 accounted for 38.69%, and 22 years and above 95 accounted for 18.85%, with the 18–29 years age group accounting for the majority. (3) Grades: 153 of 30.36% in first grade, 113 of 22.42% in second grade, 156 of 30.95% in third grade, and 82 of 16.27% in fourth grade, with first and third grades predominating. (4) Items: 50.95% of 257 in the physical shape category, 42.26% of 213 in the physical fitness category, and 6.75% of 34 in the other categories, with the physical shape category predominating (possibly related to the results of the China Physical Fitness Monitor). (5) Educational/sports level grades: no grade 200 accounted for 39.68%, Grade 3 237 accounted for 47.02%, Grade 2 and above 67 accounted for 13.29%, with Grade 3 predominating (in line with the situation of physical education majors in China). (6) Coach certificate level: no certificate 126 accounting for 25.00%, junior 271 accounting for 53.77%, middle 85 accounting for 16.87%, senior 22 accounting for 4.37%, junior mostly (in line with China’s industrial situation). (7) Academic qualifications: specialized 189 accounting for 37.50%, undergraduate 240 accounting for 47.62%, master 66 accounting for 13.10%, doctor 9 accounting for 1.79%, undergraduate predominates (in line with China’s education situation).

Table 2 Most relevant demographic characteristics of the Respondents.
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Characteristics of the dataset For the 504 valid data, computer production of random sequences (1:1 ratio) was used to obtain two subsets SHEETEFA and SHEETCFA (252 each). The first subset, SHEEETEFA, was used for EFA, (Cronbach alpha) alpha coefficient of 0.89 (> 0.7), which is acceptable for internal consistency. The second subset, SHEETCFA, was used to CFA, (Cronbach alpha) alpha coefficient of 0.96 (> 0.7), which is acceptable for internal consistency.

EFA

We performed three rounds of 22-step dimensionality reduction computations for a subset of SHEETEFA data (N = 252). For the first round of calculations, a 12-step process was performed with the criterion of retaining as many question items as possible (N = 18), and dimensionality [maximum dimensionality, N = 6(18/3)]42. The results of the first round of calculations were compared and analyzed to obtain a final structural model of the 16-item 3-factor PPLI, removed items 17 and 18 (adopted from the SUM team’s structural model for physical education teachers). For the second round of calculations, a 5-step process was performed with the criteria of progressively removing cross-cutting items and retaining as many dimensions as possible [maximum dimensions, N = number of retained question items/3]. For the second round of calculations, six cross-items were progressively removed, including items 2, 3, 5, 10, 11, and 12, yielding a structural model of the 14-item 3-factor PPLI. For the third round of calculations, a five-step process was performed based on the gradual removal of cross-items, with the criterion of retaining as many items and dimensions as possible. The third round of calculations, which progressively removed three cross-projects, including 2, 3, and 5, did not result in any desired structural model of PPLI.

We compared the two relatively ideal structural models obtained, and with the principle of retaining as many question items as possible, the structural model of the 16-item, 3-factor PPLI was considered to be the most ideal model, as shown in the pattern matrix in Table 3. This 3-factor, 16 - item model loaded explained 63.37% of the variance, which used maximum likelihood estimation (an oblique rotation). Factor correlation validation data indicated adequate 16 items with factor loadings ranging from 0.64 to 0.90 (> o.32). The total correlations for the calibration items ranged from 0.50 to 0.89 (> 0.4).

Table 3 3-Dimensional 16-item structural model of perceived physical literacy Instrument.
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Item content consistency results were met with alpha of 0.88, 0.86, and 0.83 (> 0.7) for the three factor scales. The result of the validation sample adequacy was found to be largely satisfactory with a KMO index of 0.87 (> 0.8). The p-value of the Bartlett’s test of sphericity was 0.000 (p ≤ 0.001), indicating that the validation sample scale correlation results as suitable for principal component analysis.

CFA

We carried out cross validation using a subset of the SHEETCFA data (N = 252), which was computed for CFA. The results of the calculations confirmed that the 18-item 3-factor structural model was acceptable (see Fig. 1). All of the corresponding AVE values for a total of three factors were greater than 0.5 (0.78 to 0.83) and all of the CR values were higher than 0.7 (0.94–0.97), implying that the data from this CFA analysis had good convergent validity of these, the factor loadings of the structural model for the 16-item PPLI ranged from 0.84 to 0.93 (> 0.4). The three fits of the structural model are high: The absolute fit of the model was acceptable with SRMR of 0.03 (< 0.1). The incremental fit of the model was acceptable with an NFI of 0.93 (> 0.90), CFI of 0.95 (> 0.9) and TLI of 0.94 (> 0.90). The parsimonious fit of the model was acceptable with a PNFI of 0.78 (> 0.5), PGFI of 0.62 (≥ 0.50).

Fig. 1
figure 1

Factor structure and standardized.

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Discussion

The results of the data showed that the structural model of the 16-item 3-factor model of the PPLI of the educational/sports college students with acceptable validity answered the psycho-structural characteristics of their PL (H0), showing the phenomenon of perceived PL by the educational/sports college students. 7 items in the first dimension of the structural model, including PL06,07,08,09,10,11 and 12. The second dimension of the structural model, 4 items, consists of PLs 13, 14, 15 and 16. The third dimension of the structural model, 5 items, consists of PL01,02,03,04 and 05.

PPLI is one of the effective tools built by the SUM team to validate perceived PL, based on Whitehead’s PL concept. Whitehead considers the PL phenomenon, which has two stages and three attributes for each stage. The first stage is known as the kernel stage and consists of 1.1 Motivation, 1.2 Confidence and Physical Ability, and 1.3 Interaction with the Environment. The second stage has been made the external stage and includes 2.1 self-awareness and self-confidence, 2.2 self-expression and communication with others, and 2.3 knowledge and understanding. Moreover, the first and second stages have a facilitating effect on each other, which can also be expressed as a phenomenon in which the two stages of the internal and external nuclei have a reciprocal effect on each other.

The first dimension of the structural model, the first three items (PL06,07 and 08) are characterized by self-awareness and self-confidence with the distinctive 1.2 attributes of the internal kernel stage; while the last four items (PL09,10,11 and 12), are characterized by the distinctive 2.2 attributes of the external kernel stage. The second dimension of the structural model, items PL13 and PL14, suggest that educational/sports college students have distinctive internal kernel stage 1.3 attributes; PL15 and 16 combine to have distinctive external kernel stage 2.3 attributes. The third dimension of the structural model, where the five projects (PL01,02,03,04 and 05) are combined, has the distinctive 2.1 attributes of the external kernel stage.

One process worth describing is that PLs 17 and 18, which were considered to be weakly correlated with the second dimension, were removed during the CFA calculations due to the low value of the standardized loading coefficient (< 0.4), which is considered to be weakly correlated with the second dimension. We tried to put PL17 and 18 into the first or third dimension, respectively, but both failed. Missing PLs 17 and 18, however, have distinct kernel stage 1.1 attributes.

Perception-behavior theory perspective

Perception can promote behavior in the perception-behavior theory perspective.

PL was created to address the global phenomenon of physical inactivity and sedentary behaviors and to promote physical activity behaviors. PPLI is one of the effective instruments for a perceived PL. Educational/sports college students, whose main form of learning is educational/sports, can be understood as physical activity relative to non-educational/sports college students (undergraduates), whose physical activity behaviors are more frequent. In comparison to the MA team’s structural model for undergraduate students (3-factor 9-items)23, it can be noted that the structural model for sport college students (3-factor 16-items) validated more elements of ‘s PL conceptualization17,18. This may suggest that educational/sports college students may be objectively equipped to perceive PL relative to non-physical education college students (Ma et al., 2020)23. In contrast to the structural model of the physical education teacher (3-factor 9-item, Sum et al., 2016)22, the structural model of the educational/sports college student (3-factor 16-item), verified to 1.2 and 1.3 of Whitehead’s kernel stage of PL conceptualization17,19. This may indicate that educational/sports college students, relative to the physical education teachers (H1), have more explicit confidence and physical ability in perceiving PL, as well as a more distinct willingness to interact with the environment. 22

Based on the number of validated items (16), it is possible that education/sports college students exhibit more comprehensive perceived PL compared to undergraduate students (non-sports students) and physical education teachers. According to the Perceived-Behavior Theory, this suggests that education/sports college students may have higher PA levels, or that their PA is more likely to translate into lifelong behavioral patterns.

Embodied cognition and environmental affordances

The monistic embodied nature of PL 29 and embodied cognition, the perception of “affordances” in the motor environment through bodily practices30, leading to a deep understanding of motor skills, and the formation of rational cognition through bodily perceptions (experiences and activities)28, which together trigger behavioral occurrence. Looking at the structural model of the educational/sports college student, we validate to the structure of Whitehead’s three dimensions of the external kernel stage, intertwined with the two dimensions of the internal kernel stage. The first dimension consists of kernel stage 1.2 attributes and external kernel stage 2.2 attributes, and the second dimension consists of kernel stage 1.3 attributes and external kernel stage 2.3 attributes. This intertwined structure may be the result of the interplay between physical perception and rational cognition of physical activity behaviors in educational/sports college students, and the materialization of bodily practices to perceive the affordances of the motor environment. This indirectly verifies that PL, which starts from embodied cognition as a logical starting point, requires givens in the exercise environment, which can also be understood as a condition for the formation of PL (H2).

There is a significant difference in the athletic environment given to educational/sports college students versus physical education teachers (Sum et al., 2016, 2020)22, versus undergraduates (Ma et al., 2020)23. The embodied cognition of PL perceived by educational/sports college students exhibits characteristics of a motor-environmental affordance; the embodied cognition of PL perceived by physical education teachers exhibits characteristics of a teaching-environmental affordance; the embodied cognition of PL perceived by undergraduate students (non-sports students) exhibits characteristics of a health-environmental affordance. Furthermore, more directly stated, the environmental affordances of the perceived PL in the cognition of educational/sports college students differ from those of physical education teachers and undergraduates (non-sports students). The effects of PL on physical activity behaviors should be different depending on the affordances of the motor environment. The structural model of educational/sports college students, which was not validated for PLs 17 and 18, corresponds to the motivation for perceiving PL, suggesting that the affordances of the sport environment given to educational/sports students does not fully promote the formation of physical activity.

Based on the 18 items of motor-environmental affordances characteristics observed among educational/sports college students (16 items observed, 2 items not observed), we can infer that motor-environmental affordances may not be a necessary and sufficient condition for perceived PL.

Contributions and limitations

CONTRIBUTION: We verified a structural model of perceived PL in educational/sports college students, which has the potential to be either very rich or not obvious from a perceptual perspective. We obtained a largely acceptable 3-factor, 16-item structural model that validated most of the attributes of Whitehead’s PL concept (5 out of a total of 6). We conducted an initial logical analysis, comparing educational/sports college students to undergraduate students, and to physical education teachers, and although it was a qualitative observation, we found logical points that contributed to the differences between the three. The comparison between educational/sports college students and physical education teachers is a longitudinal observation under a professional attribute, and the comparison between educational/sports college students and undergraduate students is a horizontal observation under a social configuration. Whether observed vertically or horizontally, educational/sports college students need more attention as a special group in early adulthood.

Limitations: we did as much sample size collection as possible, but the data model can also only represent the results of this data calculation. This is a limitation of the self-reported data in this paper. The unvalidated 1.1 motivation for perceived PL does not mean that educational/sports college students have no perceived motivation for physical education behaviors, it only means that motivation is not significant in terms of perceived PL. Both the comparisons with physical education teachers and between undergraduate students are results of a qualitative comparison that need to be further validated by evidence-based research. This paper treats educational/physical education college students as a sample of early adulthood, reflecting a gap in the representativeness of the sample. It merely observes the PL phenomenon in early adulthood within one group and cannot fully represent all its characteristics. Although this study incorporates PPLI’s English-Chinese bidirectional translation methodology, different research approaches (English-Chinese bidirectional translation) may yield varying results. This represents a limitation of the cultural adaptation (cross-cultural research) employed in this paper. The snowball sampling method employed in this study introduces certain limitations to the rigor of random sampling in scientific research. it is possible that results would differ if strictly random sampling had been used.

Conclusion

As an instrument for measuring perceived PL, the PPLI is a reliable and valid instrument for measuring perceived PL of educational/sports college students. From the results of EFA and CFA, our study observed that sports college students possess a relatively comprehensive range of perceptual PL phenomena. the affordances of the sport environment given are not a sufficient condition for perceiving PL, and maybe not a necessary one.