Development and initial validation of the adolescent exercise habits scale (AEHS) among Chinese population

Development and initial validation of the adolescent exercise habits scale (AEHS) among Chinese population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Development and initial validation of the adolescent exercise habits scale (AEHS) among Chinese population Jin Wu, Huasen Yu, Liqing Li, Yuhang Yang, Zeyang Zhang, Xiaopan Hu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6991427/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Dec, 2025 Read the published version in BMC Public Health → Version 1 posted 9 You are reading this latest preprint version Abstract Background Establishing regular exercise habits during adolescence is essential for fostering lifelong physical activity participation. Despite its importance, reliable and culturally appropriate tools to assess exercise habits among Chinese adolescents remain limited. This study aimed to develop and validate the adolescent exercise habit scale (AEHS), a psychometrically sound instrument for assessing self-reported exercise habits in this population. Methods Grounded in a multidimensional conceptual framework, the initial 33-item pool was generated based on literature review and expert consultation. A total of 1346 students aged 12 to 18 from Jiangsu China completed the preliminary version of the scale. Item analysis and exploratory factor analysis (EFA) were conducted to refine the scale structure, followed by confirmatory factor analysis (CFA) to test its factorial validity. In addition, we employed a percentile-based method to classify adolescents' exercise habit levels according to their scale scores. Results The final AEHS consisted of 12 items loading on three dimensions: exercise consistency, self-motivation, and integration of exercise into daily life. The AEHS showed acceptable internal consistency, content validity, convergent validity and criterion-related validity (Cronbach’s α ranged from 0.705 to 0.855, CVI values ranged from 0.79 to 0.87, AVE values ranged from 0.378 to 0.603, and correlation coefficients ranged from 0.564 to 0.659). The AEHS also enables the classification of adolescents' exercise habits into low, moderate, and high levels based on their total scores. Conclusions Overall, the AEHS appears to be a valid and reliable tool for evaluating adolescent exercise habits in Chinese contexts and may contribute to more targeted interventions in physical activity promotion. exercise habits Adolescents Scale development Consistency Self-motivation daily-life integration Introduction Regular physical exercise during adolescence is widely recognized as a cornerstone of fitness and mental health, contributing to the chronic diseases prevention, motor competence development [1] , and psychological well-being promotion [ 2-3] . Despite its well-documented benefits, sustained engagement in physical exercise remains a challenge for many adolescents, with participation often characterized by irregularity and decline over time[ 4] . In this context, understanding and measuring the formation of exercise habits has become increasingly important. However, the lack of comprehensive and psychometrically reliable instruments to assess adolescents' exercise habits limits both empirical research and the design of effective interventions. Currently, the Self-Report Habit Index (SRHI) is the most widely used instrument internationally for assessing exercise habits. The SRHI consists of 12 items and assesses habit strength across three core dimensions: automaticity, repetition, and relevance to self-identity[ 5] . Gardner et al. (2012) proposed a simplified version of the SRHI, the Self-Report Behavioral Automaticity Index (SRBAI), which consists of four items and focuses specifically on the automaticity component of habitual behavior[ 6] . Although the SRHI and SRBAI are widely recognized and theoretically grounded in measuring habitual behaviors, its application in measuring physical exercise habits among Chinese adolescents presents several limitations. These include cultural inadaptability, cognitive misalignment with adolescent developmental stages, omission of institutional factors within the Chinese education system and the lack of seamless translatability into Chinese. More importantly, both the SRHI and SRBAI overlook key characteristics inherent to exercise behavior itself, such as its time-consuming nature and associated physical discomfort. A single exercise session often involves a series of sub-actions—such as changing clothes, showering, and cooling down—and as exercise intensity increases, individuals may experience unpleasant physiological sensations including shortness of breath and muscle soreness[ 7] . Clearly, for adolescents, maintaining regular physical activity is unlikely to be entirely automatic or unconscious; rather, it often requires conscious effort to overcome multiple barriers[ 8] . In addition, although objective measurement tools such as accelerometers are considered the gold standard for accurately identifying adolescents’ physical activity levels [9] ，they fall short in assessing the multidimensional nature of exercise habits. Exercise habit encompasses not only behavioral frequency and intensity, but also critical psychological dimensions such as stability, volition, and identity. These constructs cannot be adequately captured by objective instruments alone, nor can such tools determine whether the observed behavior is truly habitual in nature. Compared to objective methods, subjective assessments provide richer insights into the psychological and behavioral mechanisms underlying exercise habits, particularly in adolescents. They are practical, scalable, and informative for stakeholders such as parents and physical education teachers, who play vital roles in shaping and supporting adolescent exercise habits. Several Chinese scholars have shown increasing interest in the measurement of exercise habits, proposing multidimensional approaches that assess behavioral repetition[ 10] , and volitional control[ 11] , as well as automaticity[ 12] . Although these measurement tools offer valuable references, they were primarily developed and validated in adult populations, which may limit their applicability to adolescents. As a result, a measurement gap remains for those seeking to assess self-perceived exercise habits among Chinese adolescents. As such, in response to this measurement gap，the present study aims to develop and valid the self-reported adolescent exercise habits scale (AEHS). The scale is original and has not been published or submitted elsewhere. Conceptualizing and measuring adolescents’ exercise habits Defining the exercise habits among adolescents Clarifying the conceptual connotation of exercise habits among adolescents is a prerequisite for the scale development. Existing scholars have primarily explored the notion of exercise habits from neurophysiological and behavioral psychological perspectives. Representative views include: (1) exercise habit is a stable conditioned reflex formed through long-term participation in fitness activities[ 13] , (2) it is a stable, automated behavioral tendency and cognitive pattern formed through repeated practice in specific contexts, underpinned by positive attitudes and beliefs about physical fitness[ 14] , and (3) it is a state in which physical activity behavior meets certain fixed standards in terms of duration and frequency[ 15] . Our study contends that although the aforementioned three conceptual frameworks reflect certain characteristics of exercise habits, they remain insufficient and warrant further refinement. The neurophysiological perspective, for instance, oversimplifies the unique nature of exercise habits by classifying them as mere conditioned reflexes, thereby neglecting the substantial volitional effort required to establish and maintain regular physical exercise. Unlike other daily habits that may form with minimal resistance, the formation of exercise habits necessitates sustained self-regulation and persistence. While the behavioral psychology perspective emphasizes the positive association between exercise habits and conscious engagement—highlighting constructs such as cognitive schemas or belief-based support—these theoretical interpretations often diverge from empirical realities. According to the minimum effort theory of physical activity, human behavior is largely governed by tendencies to minimize energetic cost, known as Behaviors Minimizing Energetic Cost (BMEC). Even in modern societies with abundant food and resources, BMEC-related neural pathways—shaped through long-term evolutionary pressures—continue to influence behavior, leading individuals to avoid unnecessary physical exertion such as exercise. For adolescents in particular, it is especially challenging to maintain unwavering beliefs or consistent cognitive commitments toward physical exercise. Therefore, defining exercise habits predominantly through constructs like cognitive schemas or belief-based support may fail to capture their practical essence, thereby diminishing the theoretical model’s applicability to real-world behavior change. Building upon previous conceptualizations while critically reflecting on their limitations, the present study seeks to reconceptualize exercise habits from a novel perspective. The concept of lifestyle sports[ 16] provides a promising framework for this innovative conceptualization. From this perspective, exercise habits are regarded as an essential component of a healthy human lifestyle. The formation of exercise habits is conceptualized as a process in which individuals internalize physical exercise as part of their personal lifestyle: marking a transformation from externally driven participation to intrinsically motivated engagement[ 17] . Based on this perspective, the present study defines exercise habits as a form of embodied practice through which adolescents integrate physical exercise into their daily lives. Rather than focusing narrowly on the frequency of exercise behavior, this conceptualization elevates exercise habit to the level of lifestyle, aligning more closely with the value orientation of lifelong physical activity in the era of core physical literacy. As such, it offers broader theoretical potential and practical relevance. Structure of adolescents’ exercise habits Regarding the structural dimensions of measuring adolescents' exercise habits, existing studies have proposed two main perspectives: a two-factor model and a four-factor model. The two-factor model emphasizes repetition and volitional effort as the core dimensions, while the four-factor model further expands the structure to include repetition, volitional effort, automaticity, and consistency. This study partially agrees with these conceptualizations. First, we support the inclusion of consistency or repetition as a fundamental component of exercise habits. This view is grounded in the inherent characteristics of habitual behavior. Namely, its regularity and persistence over time. If a behavior occurs infrequently or is easily disrupted by external factors, it is difficult to classify it as a true habit. In this context, a habitual exercise behavior should manifest as consistent and sustained engagement over a certain period. Secondly, we argue that including volitional effort as a core dimension of adolescents' exercise habits does not align with the developmental characteristics of this age group. Adolescence is a period marked by rapid physical and psychological changes, during which individuals begin to develop autonomy and self-awareness, often accompanied by emotional instability and fluctuating motivation[ 18] . Compared to childhood and adulthood, adolescents generally exhibit lower levels of attentional control and willpower[ 19] . Moreover, unlike behaviors such as eating or smoking which tend to emerge spontaneously in daily life, engaging in regular physical exercise is not instinctive. From an evolutionary standpoint, exercise can be considered a counter-evolutionary behavior, often involving physical discomfort and effort. Thus, it is unrealistic to assume that adolescents can sustain exercise habits purely through consistent willpower or belief in fitness values. This study contends that, instead of volitional effort, the development of exercise habits among adolescents relies more heavily on intrinsic motivation. Such motivation stems from adolescents' positive attitudes toward physical exercise and their active engagement in exercise behaviors. As posited by Self Determination Theory, individuals are more likely to form sustained exercise habits when the behavior is self-endorsed and autonomously regulated, rather than externally imposed[ 20] . Finally, based on the research team's long-term observation and documentation of adolescents' exercise behaviors, it has been found that the formation of exercise habits among adolescents essentially involves the integration of physical exercise into daily life as an embodied practice. This process represents an external manifestation of the lifestyle sports. During this transformation, adolescents’ agency and creativity are fully expressed, and their sense of presence and well-being is continuously enhanced. In turn, this positive experiential feedback reinforces and motivates the continued development of exercise habits[ 21] . The inclusion of daily-life integration as a structural component of adolescents’ exercise habits aligns well with the core principles of physical literacy, lifestyle sports, and lifelong physical activity. These frameworks all emphasize internalizing physical exercise as a life attitude, embedding it into everyday routines, and recognizing it as an indispensable component of daily life[ 22]-[23] . When physical exercise becomes genuinely embedded in daily life, it tends to manifest as an "anytime and anywhere" behavior that requires minimal deliberation or exertion of willpower. In summary, this study proposes consistency, self-motivation, and daily-life integration as the three fundamental dimensions for measuring exercise habits among adolescents as illustrated in Table 1. Notably, the inclusion of the daily-life integration dimension offers a novel perspective for the development of measurement tools. The three dimensions form a progressive, hierarchical structure, indicating that the formation of exercise habits among adolescents begins with stable exercise behaviors, advances to self-determined attitudes toward exercise, and ultimately evolves into the incorporation of exercise into everyday life. Table 1. Dimensions and Theoretical Foundations of the EHAS Dimensions Definition Theoretical Foundations consistency Refers to the consistent and regular performance of physical exercise over a certain period, with low susceptibility to external interference. Existing Research Consensus self-motivation Reflects the adolescent's conscious motivation and autonomous intention to engage in physical exercise. Self Determination Theory daily-life integration Refers to the degree to which physical exercise is embedded in daily life. Physical Literacy Methods Item Generation Based on the confirmed basic structure of the adolescent exercise habit scale (see Table 1), an original item pool was developed through a comprehensive review of relevant literature. At the same time, a focus group was established consisting of three graduate students majoring in Physical Education and five adolescents who regularly participate in physical exercise. The group reviewed the clarity and appropriateness of each item. Based on their feedback, indistinct or inappropriate items were removed, resulting in the formation of the final item pool. The final item pool was then evaluated by 13 experts, each with more than five years of experience in adolescent physical activity research or physical education teaching. These experts were asked to rate the appropriateness of each item for its respective dimension using a 4-point Likert scale, where a score of 4 indicated high appropriateness and a score of 1 indicated low appropriateness. Based on the expert ratings, the Content Validity Index (CVI), probability of chance agreement (Pc), and Kappa coefficient were calculated for each item. Items with a CVI below 0.78, or those with a CVI above 0.78 but a Kappa coefficient below 0.74, were considered potentially problematic. In such cases, qualitative feedback from experts was referenced to revise, delete, or adjust the items accordingly. As a result, an initial adolescent physical exercise habit scale consisting of 33 items was developed in Chinese language and items were rated on a 5-point Likert scale ranging from 1 (definitely disagree) to 5 (definitely agree). Sample The recruitment of participants in this study was approved by the Ethics Review Committee of East China Normal University (protocol number: HR 206-2024). Considering that the required sample size should be 10 to 20 times the number of items[ 24] , along with an estimated 5%–10% invalid response rate, a minimum of 348 participants was deemed necessary. Based on this calculation, data collection was conducted from October to November 2023 in three junior high schools and three senior high schools in Jiangsu province, China. A total of 1,480 questionnaires were distributed through offline means, and 1,464 were returned. After excluding invalid responses, 1,346 valid samples were obtained, resulting in a response rate of 90.95%. Statistical Analysis The total sample was randomly and evenly divided into two equal subsamples (Sample 1 and Sample 2) for cross-validation. Sample 1 was used for item analysis and exploratory factor analysis (EFA), while Sample 2 was used for confirmatory factor analysis (CFA). Item reduction analysis was conducted by using the item discrimination index and item-total correlation coefficients. First, the total scores of all items in Sample 1 were calculated for each participant and ranked from highest to lowest. The top 27% of participants were classified as the high-score group, and the bottom 27% as the low-score group. Independent samples t -tests were performed to compare item scores between the two groups. Items that did not show statistically significant differences were considered to have low discrimination and were eliminated. Second, item-total correlation coefficients were computed, and items with correlation coefficients less than 0.30 were removed. The EFA was conducted to examine the dimensional structure of the scale. Prior to the EFA, the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity were performed to assess the sampling adequacy and factorability of the data. A KMO value greater than 0.70 and a statistically significant result from Bartlett’s test ( p < 0.001) indicated that the data were suitable for factor analysis. To explore the underlying dimensional structure of the scale, principal component analysis (PCA) was performed, and varimax rotation was applied. Items with low loadings were removed based on commonly adopted criteria in previous studies. The item deletion criteria were as follows: (1) a factor loading less than 0.40; (2) the difference in factor loadings of the same item across two or more factors was less than 0.10 and (3) cross-loadings greater than 0.40 on two or more factors. During the analysis, only one item was removed at a time, followed by a new round of exploratory factor analysis (EFA), until an optimal factor structure was achieved. The CFA was conducted to examine the construct validity of the scale. Model fit was considered acceptable if the following criteria were met: χ²/df between 1 and 5, Goodness of Fit (GFI) > 0.80, Root Mean Square Error Approximation (RMSEA) 0.80, Comparative Fit Index (CFI) > 0.90 and Tucker Lewis Index (TLI) > 0.90. GFI, CFI and TLI above 0.85 were considered acceptable as marginal fit. In addition, to test convergent validity, average variance extracted (AVE) per construct was calculated, with the requirement of all the constructs at 0.5 as good, and 0.36 as acceptable Cronbach’s a coefficient was used to assess the internal consistency of the scale, indicating the degree to which the items measure the same construct or dimension. A Cronbach’s alpha value between 0.70 and 0.80 was considered indicative of good internal consistency. For content validity, at the initial stage of scale development, 13 experts with relevant experience were invited to evaluate the appropriateness of the scale items. A Content Validity Index (CVI) greater than 0.78 or a Kappa coefficient greater than 0.74 was considered indicative of satisfactory content validity. For criterion validity, the item “Please rate your overall physical exercise habit” was used as the criterion variable, representing participants’ overall self-perception of their physical exercise habit. Correlations between the total score and each item score with the above item were calculated to examine the criterion-related validity of the scale. Results Participants’ characteristics The sample consisted of 1,346 adolescents, including 714 males and 632 females. Approximately 598 participants were high school students and 748 were junior high school students, with ages ranging from 12 to 18 years. Item reduction analysis of AEHS Item discrimination analysis revealed that Items 4, 8, and 24 showed no significant difference in scores between the high-score and low-score groups, and were therefore excluded from the scale. The item-total correlation analysis showed that the remaining 30 items were all significantly correlated with the total score ( p < 0.01), with correlation coefficients ranging from 0.439 to 0.774. These items were retained for subsequent analyses. Exploratory factor analysis of the AEHS The initial EFA was conducted on the 30 items retained after item analysis. The KMO value was 0.954, and Bartlett’s test of sphericity was statistically significant ( p < 0.01), indicating that the data were appropriate for factor analysis. A PCA was conducted using varimax rotation to explore the underlying factor structure. Items with low factor loadings were removed from the scale during the analysis. The results of the first EFA revealed that Items 2, 6, 9, 11, 14, 16, 17, 18, 20, 26, and 33 exhibited cross-loadings, with factor loadings greater than 0.40 on two or more factors. Therefore, these items were removed from the scale. After the deletion of each item, the KMO test, Bartlett’s test of sphericity, and EFA were re-conducted to ensure the adequacy of the data and the stability of the factor structure. Due to space limitations, only the results of the final EFA are presented in this paper. After three rounds of EFA, a total of three factors were extracted, accounting for 68.53% of the cumulative variance (see Table 2). These three factors were consistent with the theoretically hypothesized structure of this study. Based on the thematic content of the items within each factor, they were respectively labeled as consistency (4 items), self-motivation (4 items), and daily-life Integration (4 items). The full English version of the scale is available in the supplementary materials. Table2. Factor structures by Exploratory Factor Analysis Sign Items Factor loading Communality F 1 F 2 F 3 S 1 Participates in moderate-intensity physical activity (e.g., noticeable increase in heart rate and breathing) at least three times per week. 0.777 0.634 S 3 I stick to my exercise routine regardless of whether others (classmates, peers, or friends) do it or not. 0.669 0.603 S 5 I can persist in exercising even when I feel like giving up or taking a break. 0.710 0.513 S 7 I still engage in physical exercise despite heavy academic pressure. 0.628 0.593 S 22 Compared with other activities, I often regard physical exercise as one of my daily life priorities. 0.786 0.832 S 23 Life feels dull and meaningless if I cannot engage in physical exercise. 0.834 0.781 S 25 Daily physical exercise has become a part of my routine. 0.807 0.747 S 32 Like eating and sleeping, physical exercise is a natural part of my daily routine that I do without needing reminders. 0.783 0.777 S 10 I actively take part in physical activities both at school and in my free time. 0.785 0.728 S 12 I take the initiative to exercise even without being pushed by teachers or parents. 0.842 0.726 S 13 I actively seek solutions when facing difficulties in physical exercise, such as asking teachers or classmates and looking for information elsewhere. 0.551 0.548 S 15 I am eager to try various sports or learn new sports skills. 0.881 0.750 Eigenvalue 3.178 2.542 2.504 Cumulative variance explained 47.635 11.608 9.282 68.525 注：F1 = Consistency；F2 = Daily-life integration；F3 = Self-motivation Confirmatory factor analysis of the AEHS The CFA was then conducted in order to replicate the factor structure identified through the EFA with sample 2. The model fit indices were as follows: χ²/df = 3.952 ( p < 0.05), SRMR = 0.059, RMSEA = 0.076, GFI = 0.925, TLI = 0.903, and CFI = 0.925, indicating that the proposed theoretical model demonstrated an acceptable and satisfactory fit to the data. All standardized factor loadings were statistically significant ( p < 0.001), and all items significantly loaded onto the same factor as they had in the EFA. Reliability The Cronbach’s α coefficients for each subscale of the instrument ranged from 0.705 to 0.855, and the composite reliability (CR) values ranged from 0.693 to 0.858, indicating acceptable to good internal consistency (see Table 3). Table 3. AEHS reliability and average variance extracted（AVE） Domain Item Cronbach's a CR Factor loading AVE Consistency S1 0.705 0.693 0.681 0.378 S3 0.590 S5 0.770 S7 0.528 Self-motivation S10 0.834 0.832 0.749 0.554 S12 0.724 S13 0.671 S15 0.826 daily-life Integration S22 0.855 0.858 0.857 0.603 S23 0.798 S25 0.637 S32 0.798 Validity Initially, the scale items were evaluated by a panel of experts. The final 12 items retained had Content Validity Index (CVI) values range from 0.79 to 0.87, all exceeding the recommended threshold of 0.78. The corresponding Kappa values ranged from 0.79 to 0.87, also surpassing the acceptable minimum of 0.74. These results indicate a low probability of agreement occurring by chance, suggesting that the scale possesses satisfactory content validity. Secondly, the Average Variance Extracted (AVE) values for the three dimensions of the scale were 0.378, 0.554, and 0.603, respectively (see Table 3). All values exceeded the minimum acceptable threshold of 0.36, indicating that the scale demonstrates acceptable convergent validity. Finally, the correlations between the three dimensions and the total score of the scale with the overall self-rating score ranged from 0.564 to 0.659. All correlation coefficients were statistically significant at the 0.01 level, indicating positive relationships and supporting the criterion-related validity of the scale. Adolescent Exercise Habit Classification Criteria The finalized Adolescent Exercise Habit Scale, after reliability and validity testing, consists of three dimensions, each containing four items, for a total of 12 items. The scale adopts a 5-point Likert rating format, with total scores ranging from 12 to 60. A statistical analysis of the total score distribution across the 1,346 valid samples revealed a skewed distribution, as indicated by the Kolmogorov–Smirnov test (D = 0.039, p < 0.05). Therefore, the quantile method was employed to establish categorical levels of adolescent physical exercise habits. Based on an ascending sort of the total scores, participants were classified into three levels of exercise habit strength using percentile cutoffs. The 25th percentile score (32 points) was set as the cutoff for the low-score group, while the 75th percentile score (48 points) was used as the cutoff for the high-score group. Accordingly, scores within the range of 12 ≤ total score ＜ 32 were categorized as low level, 32 ≤ total score ＜ 48 as moderate level, and 48 ≤ total score ≤ 60 as high level (see Table 4). Compared with the four-level classification proposed in previous studies [ 11 ] , the three-level classification scheme offers greater practicality, with clearer and more explicit categorization criteria that enhance ease of understanding and facilitate user proficiency in application. Table 4. Classification of Score Levels for the AEHS Category Score range Characteristics of Physical Exercise Low 12≤score＜32 No established exercise habit; participation is infrequent and inconsistent. Middle 32≤score＜48 Physical exercise is somewhat regular but prone to interruption. High 48≤score≤60 A well-developed exercise habit has been formed, with physical activity fully integrated into daily life. Discussion On the basis of a clearly defined conceptualization of adolescent exercise habits, this study developed an item pool and initially validated the psychometric properties of the scale using a sample of 1,346 Chinese adolescents. The results demonstrated that the Adolescent Exercise Habit Scale exhibited acceptable factorial validity, satisfactory reliability, and significant discriminative power, indicating that it is a valid instrument for assessing the level of exercise habits among adolescents. Three dimensions: Consistency, self-motivation, and daily-life integration Three dimensions have been derived from the 12-item scale, including consistency, self-motivation and daily-life integration. The structure of AEHS obtained in EFA was consistent with the predefined conceptual framework. Firstly, the study identified consistency as a critical dimension of exercise habits, which demonstrated sound structural and predictive validity in the adolescent sample, indicating its effectiveness in capturing the persistence of individuals’ exercise behaviors. Typically, exercise frequency is considered the most salient feature of habitual physical exercise[ 25] . For adults, engaging in physical exercise at least three times per week is often regarded as a benchmark for the formation of an exercise habit. However, in the context of Chinese adolescents, physical activity frequency is generally guaranteed due to participation in at least three 40-minute mandatory physical education classes per week, along with voluntary extracurricular exercise of approximately one hour per day. It is, in fact, the heavy academic burden that frequently disrupts adolescents’ exercise routines. Therefore, using consistency to characterize the extent to which adolescents’ physical activity behaviors can resist external interference may better capture the actual process of exercise habit formation among this population. This is because frequency merely reflects how often a behavior occurs, whereas consistency captures the extent to which the behavior is sustained, self-initiated, and resistant to external disruptions. Secondly，according to Self-Determination Theory, long-term behavioral adherence is largely influenced by the extent to which the behavior is self-determined. That is, behaviors initiated volitionally and experienced as autonomous are more likely to be internalized and sustained over time[ 26] . In the context of physical exercise, when adolescents perceive exercise as a personally endorsed choice rather than a response to external pressures, the behavior is more likely to become habitual. Clearly, the inclusion of the dimension of self-motivation is theoretically justified and empirically grounded. Finally, the dimension of daily-life integration aligns closely with the concept of lifelong physical activity advocated by physical literacy. From the perspective of physical literacy theory, integration into daily life is not merely an extension of exercise frequency, but rather a deeper manifestation of adolescents’ internalization of physical exercise as a routine component of their everyday lives. Therefore, assessing the extent to which individuals naturally integrate physical exercise into diverse daily life contexts can better capture whether such behaviors have been socialized, contextualized, and meaningfully internalized. This dimension serves as a crucial predictor of their lifelong engagement in physical exercise. Reliability and Validity of AEHS The psychometric evaluation of the EHAS provides robust support for its reliability and validity. The internal consistency of each subdimension reached acceptable thresholds, suggesting that the items coherently represent their respective constructs. Composite reliability indices further confirmed the structural stability of the measurement model. In terms of validity, content validity was ensured through a rigorous item development process grounded in theoretical frameworks and expert consultation. The scale also demonstrated acceptable convergent validity, indicating that each construct effectively captures the underlying conceptual domain it was designed to measure. Moreover, the observed positive associations with external criterion measures provide evidence for satisfactory criterion-related validity, supporting the scale’s capacity to reflect meaningful behavioral tendencies in adolescent physical exercise habits. Collectively, these findings affirm the sound measurement properties of the instrument and its applicability in future research on youth exercise behavior. Classification of Adolescent Exercise Habit Levels Based on the total scores of the AEHS, this study categorized adolescents’ physical exercise habits into three levels—low, moderate, and high—thus overcoming the traditional unidimensional approach that solely relies on exercise frequency or duration to assess the quality of exercise habits. The decision to adopt a tiered evaluation framework for adolescent physical exercise habits stems from both conceptual and practical considerations. Theoretically, habit is not a dichotomous construct but a continuum that reflects varying degrees of behavioral automaticity, motivational internalization, and contextual integration. Binary classifications—such as active vs. inactive—fail to capture the nuanced progression from intention-driven participation to deeply ingrained routines. By segmenting habit strength into low, moderate, and high levels, the present framework acknowledges the gradual and multidimensional nature of habit development, as proposed by recent models in health psychology and behavioral science[ 27] . Practically, such stratification enables more targeted interventions: those in the early phase may benefit from motivational priming, whereas individuals with moderate-level habits may require environmental restructuring to reinforce consistency. Furthermore, this classification facilitates longitudinal tracking of habit consolidation, offering a dynamic lens to assess intervention efficacy over time. Strengths and limitations To the best of our knowledge, this is the first study to develop and preliminarily validate the psychometric properties of the exercise habit scale in adolescents. A notable strength of the present study lies in its conceptual advancement over previous research that primarily equated exercise habits with behavioral frequency. Moreover, The AEHS was developed with consideration for the unique cultural context of Chinese adolescents, ensuring relevance and appropriateness in measuring exercise habits within this population. This study has several limitations. First, due to resource and time constraints, the data used for scale development were collected solely from adolescents in Jiangsu Province, lacking regional diversity in the sample. This may limit the generalizability of the AEHS. Second, further investigation involving more locations and a larger sample size is necessary to enhance the scale’s applicability across different populations. Third, data were collected via self-reported paper questionnaires, which, although beneficial for adolescent comprehension, could be complemented by other data sources such as diaries, observations, and teacher reports to strengthen the scale’s scientific rigor. Fourth, given that modifications were made to achieve satisfactory model fit, the CFA model remains provisional and requires further replication. Finally, due to the absence of a gold standard for evaluating physical exercise habits and the cross-sectional nature of this study, no further validation of the habit level classification was conducted. Future research should consider collecting longitudinal data to dynamically track adolescents’ physical exercise behaviors over time, thereby verifying whether the classification criteria reflect real-world conditions. Such longitudinal data should not only include observable indicators such as exercise frequency and duration but also emphasize implicit information related to adolescents’ cognition and affect toward physical exercise during their development. Conclusion The AEHS is a 12-item, theoretically grounded instrument with acceptable construct validity and reliability for identifying adolescents’ exercise habits. Unlike traditional assessment paradigms that rely solely on the repetitiveness of exercise behaviors, this scale incorporates dimensions such as behavioral consistency, self-motivation, and daily-life integration, offering a more comprehensive reflection of the multidimensional nature of exercise habits. Moreover, the habit-level classification based on total scores provides a foundational reference for understanding the developmental stages of exercise habit formation among adolescents. This classification facilitates the precise identification of individuals' current stages of habit development and offers evidence to inform targeted educational interventions and behavioral promotion strategies. Declarations Acknowledgments The authors would appreciate support and input from Professor Youping Sun and his students at East China Normal University, Shanghai, and the members of East China Normal University Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education Author contributions Jin Wu wrote the main manuscript text. Liqiang Li and Huasen Yu performed data analysis.Yuhang Yang and Zeyang Zhang were in charge of data collection. Xiaopan Hu and Zufeiya Tuerdi prepared participant recruitment.All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work. Funding This research was supported by the Project of Shaanxi Provincial Department of Education Science Research Program “Epidemiological Investigation and Exercise Intervention Research on Adolescent Idiopathic Scoliosis” (23JK0698) Data availability The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate This scale development study is conducted in compliance with the ethical principles of the 1964 Declaration of Helsinki and its later amendments. The recruitment of participants in this study was approved by the Ethics Review Committee of East China Normal University (protocol number: HR 206-2024). School administrators and parents/legal guardians were informed in advance about the study’s purpose, procedures, and voluntary nature. Written informed consent was obtained from all parents/guardians. Participation was voluntary, and no financial incentives were provided. Consent for publication Not applicable. Conflicts of interest The authors have no conflicts of interest to disclose References Menescardi C, De Meester A, Morbée S, Haerens L, Estevan I. The role of motivation in the conceptual model of motor development in childhood. Psychol Sport Exerc. 2022;61:102188. Biddle SJ, Asare M. Physical activity and mental health in children and adolescents: a review of reviews. Br J Sports Med. 2011;45(11):886–95. Wassenaar TM, Wheatley CM, Beale N, Nichols T, Salvan P, Meaney A, et al. The effect of a one-year vigorous physical activity intervention on fitness, cognitive performance and mental health in young adolescents: the Fit to Study cluster randomised controlled trial. Int J Behav Nutr Phys Act. 2021;18:1–15. Bélanger M, Casey M, Cormier M, Laflamme Filion A, Martin G, Aubut S, Chouinard P, Savoie SP, Beauchamp J. Maintenance and decline of physical activity during adolescence: insights from a qualitative study. 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The building of a concept model of physical exercise habits of teenagers. J Phys Educ. 2013;20(05):93–6. Weng Q. A Study on Exercise Habits among Chinese Secondary School Students [dissertation]. Shanxi: Shanxi Normal University; 2015. Yan J, Sun H, Zhang J, Liu Z. Analysis and implications of international experience on the factors, measurement methods and intervention strategies of forming physical activity habits. J Beijing Sport Univ. 2022;45(04):63–77. Lally P, Gardner B. Promoting habit formation. Health Psychol Rev. 2013;7(sup1): S137–58. Aarts H, Paulussen T, Schaalma H. Physical exercise habit: on the conceptualization and formation of habitual health behaviours. Health Educ Res. 1997;12(3):363–74. Tappe KA, Glanz K. Measurement of exercise habits and prediction of leisure-time activity in established exercise. Psychol Health Med. 2013;18(5):601–11. Bignold WJ. Developing school students' identity and engagement through lifestyle sports: a case study of unicycling. Sport Educ Soc. 2013;18(2):184–99. Rannikko A, Harinen P, Torvinen P, Liikanen V. The social bordering of lifestyle sports: inclusive principles, exclusive reality. J Youth Stud. 2016;19(8):1093–109. Hazen E, Schlozman S, Beresin E. Adolescent psychological development: a review. Pediatr Rev. 2008;29(5):161–8. Jones M, Defever E, Letsinger A, Steele J, Mackintosh KA. A mixed-studies systematic review and meta-analysis of school-based interventions to promote physical activity and/or reduce sedentary time in children. J Sport Health Sci. 2020;9(1):3–17. Ntoumanis N, Moller AC. Self-Determination Theory informed research for promoting physical activity: contributions, debates, and future directions. Psychol Sport Exerc. 2025;102879. Fremling L, Phillips LA, Bottoms L, Desai T, Newby K. Comparing positive versus negative intrinsic rewards for predicting physical activity habit strength and frequency during a period of high stress. Appl Psychol Health Well Being. 2025;17(1):e12650. Grauduszus M, Wessely S, Klaudius M, Joisten C. Definitions and assessments of physical literacy among children and youth: a scoping review. BMC Public Health. 2023;23(1):1746. Bocarro J, Kanters MA, Casper J, Forrester S. School physical education, extracurricular sports, and lifelong active living. J Teach Phys Educ. 2008;27(2):155–66. Thompson B. The ten commandments of good structural equation modeling behavior: a user-friendly introductory primer on SEM. 1998. Lee Y, Yoon YJ. Exploring the formation of exercise habits with the latent growth model. Percept Mot Skills. 2019;126(5):843–61. Xu Z, Shamsulariffin S, Azhar Y, Xi M. Does Self‐Determination Theory associate with physical activity? A systematic review of systematic reviews. Int J Psychol. 2025;60(3):e70044. Wood W, Rünger D. Psychology of habit. Annu Rev Psychol. 2016;67(1):289–314. Additional Declarations No competing interests reported. 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Despite its well-documented benefits, sustained engagement in physical exercise remains a challenge for many adolescents, with participation often characterized by irregularity and decline over time[\u003csup\u003e4]\u003c/sup\u003e. In this context, understanding and measuring the formation of exercise habits has become increasingly important. However, the lack of comprehensive and psychometrically reliable instruments to assess adolescents\u0026apos; exercise habits limits both empirical research and the design of effective interventions.\u003c/p\u003e\n\u003cp\u003eCurrently, the Self-Report Habit Index (SRHI) is the most widely used instrument internationally for assessing exercise habits. The SRHI consists of 12 items and assesses habit strength across three core dimensions: automaticity, repetition, and relevance to self-identity[\u003csup\u003e5]\u003c/sup\u003e.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eGardner et al. (2012) proposed a simplified version of the SRHI, the Self-Report Behavioral Automaticity Index (SRBAI), which consists of four items and focuses specifically on the automaticity component of habitual behavior[\u003csup\u003e6]\u003c/sup\u003e. Although the SRHI and SRBAI are widely recognized and theoretically grounded in measuring habitual behaviors, its application in measuring physical exercise habits among Chinese adolescents presents several limitations. These include cultural inadaptability, cognitive misalignment with adolescent developmental stages, omission of institutional factors within the Chinese education system and the lack of seamless translatability into Chinese. More importantly, both the SRHI and SRBAI overlook key characteristics inherent to exercise behavior itself, such as its time-consuming nature and associated physical discomfort. A single exercise session often involves a series of sub-actions\u0026mdash;such as changing clothes, showering, and cooling down\u0026mdash;and as exercise intensity increases, individuals may experience unpleasant physiological sensations including shortness of breath and muscle soreness[\u003csup\u003e7]\u003c/sup\u003e. Clearly, for adolescents, maintaining regular physical activity is unlikely to be entirely automatic or unconscious; rather, it often requires conscious effort to overcome multiple barriers[\u003csup\u003e8]\u003c/sup\u003e.\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eIn addition, although objective measurement tools such as accelerometers are considered the gold standard for accurately identifying adolescents\u0026rsquo; physical activity levels\u003csup\u003e\u0026nbsp;[9]\u003c/sup\u003e，they fall short in assessing the multidimensional nature of exercise habits. Exercise habit encompasses not only behavioral frequency and intensity, but also critical psychological dimensions such as stability, volition, and identity. These constructs cannot be adequately captured by objective instruments alone, nor can such tools determine whether the observed behavior is truly habitual in nature. Compared to objective methods, subjective assessments provide richer insights into the psychological and behavioral mechanisms underlying exercise habits, particularly in adolescents. They are practical, scalable, and informative for stakeholders such as parents and physical education teachers, who play vital roles in shaping and supporting adolescent exercise habits.\u003c/p\u003e\n\u003cp\u003eSeveral Chinese scholars have shown increasing interest in the measurement of exercise habits, proposing multidimensional approaches that assess behavioral repetition[\u003csup\u003e10]\u003c/sup\u003e, and volitional control[\u003csup\u003e11]\u003c/sup\u003e, as well as automaticity[\u003csup\u003e12]\u003c/sup\u003e. Although these measurement tools offer valuable references, they were primarily developed and validated in adult populations, which may limit their applicability to adolescents. As a result, a measurement gap remains for those seeking to assess self-perceived exercise habits among Chinese adolescents. As such, in response to this measurement gap，the present study aims to develop and valid the self-reported adolescent exercise habits scale (AEHS). The scale is original and has not been published or submitted elsewhere.\u003c/p\u003e\n\u003cp\u003eConceptualizing and measuring adolescents\u0026rsquo; exercise habits\u003c/p\u003e\n\u003ch2\u003eDefining the exercise habits among adolescents\u003c/h2\u003e\n\u003cp\u003eClarifying the conceptual connotation of exercise habits among adolescents is a prerequisite for the scale development. Existing scholars have primarily explored the notion of exercise habits from neurophysiological and behavioral psychological perspectives. Representative views include: (1) exercise habit is a stable conditioned reflex formed through long-term participation in fitness activities[\u003csup\u003e13]\u003c/sup\u003e, (2) it is a stable, automated behavioral tendency and cognitive pattern formed through repeated practice in specific contexts, underpinned by positive attitudes and beliefs about physical fitness[\u003csup\u003e14]\u003c/sup\u003e, and (3) it is a state in which physical activity behavior meets certain fixed standards in terms of duration and frequency[\u003csup\u003e15]\u003c/sup\u003e. Our study contends that although the aforementioned three conceptual frameworks reflect certain characteristics of exercise habits, they remain insufficient and warrant further refinement. The neurophysiological perspective, for instance, oversimplifies the unique nature of exercise habits by classifying them as mere conditioned reflexes, thereby neglecting the substantial volitional effort required to establish and maintain regular physical exercise. Unlike other daily habits that may form with minimal resistance, the formation of exercise habits necessitates sustained self-regulation and persistence.\u003c/p\u003e\n\u003cp\u003eWhile the behavioral psychology perspective emphasizes the positive association between exercise habits and conscious engagement\u0026mdash;highlighting constructs such as cognitive schemas or belief-based support\u0026mdash;these theoretical interpretations often diverge from empirical realities. According to the minimum effort theory of physical activity, human behavior is largely governed by tendencies to minimize energetic cost, known as Behaviors Minimizing Energetic Cost (BMEC). Even in modern societies with abundant food and resources, BMEC-related neural pathways\u0026mdash;shaped through long-term evolutionary pressures\u0026mdash;continue to influence behavior, leading individuals to avoid unnecessary physical exertion such as exercise.\u003c/p\u003e\n\u003cp\u003eFor adolescents in particular, it is especially challenging to maintain unwavering beliefs or consistent cognitive commitments toward physical exercise. Therefore, defining exercise habits predominantly through constructs like cognitive schemas or belief-based support may fail to capture their practical essence, thereby diminishing the theoretical model\u0026rsquo;s applicability to real-world behavior change.\u003c/p\u003e\n\u003cp\u003eBuilding upon previous conceptualizations while critically reflecting on their limitations, the present study seeks to reconceptualize exercise habits from a novel perspective. The concept of lifestyle sports[\u003csup\u003e16]\u003c/sup\u003e provides a promising framework for this innovative conceptualization. From this perspective, exercise habits are regarded as an essential component of a healthy human lifestyle. The formation of exercise habits is conceptualized as a process in which individuals internalize physical exercise as part of their personal lifestyle: marking a transformation from externally driven participation to intrinsically motivated engagement[\u003csup\u003e17]\u003c/sup\u003e. Based on this perspective, the present study defines exercise habits as a form of embodied practice through which adolescents integrate physical exercise into their daily lives. Rather than focusing narrowly on the frequency of exercise behavior, this conceptualization elevates exercise habit to the level of lifestyle, aligning more closely with the value orientation of lifelong physical activity in the era of core physical literacy. As such, it offers broader theoretical potential and practical relevance.\u003c/p\u003e\n\u003ch2\u003eStructure of adolescents\u0026rsquo; exercise habits\u003c/h2\u003e\n\u003cp\u003eRegarding the structural dimensions of measuring adolescents\u0026apos; exercise habits, existing studies have proposed two main perspectives: a two-factor model and a four-factor model. The two-factor model emphasizes repetition and volitional effort as the core dimensions, while the four-factor model further expands the structure to include repetition, volitional effort, automaticity, and consistency. This study partially agrees with these conceptualizations. First, we support the inclusion of consistency or repetition as a fundamental component of exercise habits. This view is grounded in the inherent characteristics of habitual behavior. Namely, its regularity and persistence over time. If a behavior occurs infrequently or is easily disrupted by external factors, it is difficult to classify it as a true habit. In this context, a habitual exercise behavior should manifest as consistent and sustained engagement over a certain period.\u003c/p\u003e\n\u003cp\u003eSecondly, we argue that including volitional effort as a core dimension of adolescents\u0026apos; exercise habits does not align with the developmental characteristics of this age group. Adolescence is a period marked by rapid physical and psychological changes, during which individuals begin to develop autonomy and self-awareness, often accompanied by emotional instability and fluctuating motivation[\u003csup\u003e18]\u003c/sup\u003e. Compared to childhood and adulthood, adolescents generally exhibit lower levels of attentional control and willpower[\u003csup\u003e19]\u003c/sup\u003e. Moreover, unlike behaviors such as eating or smoking which tend to emerge spontaneously in daily life, engaging in regular physical exercise is not instinctive. From an evolutionary standpoint, exercise can be considered a counter-evolutionary behavior, often involving physical discomfort and effort. Thus, it is unrealistic to assume that adolescents can sustain exercise habits purely through consistent willpower or belief in fitness values. This study contends that, instead of volitional effort, the development of exercise habits among adolescents relies more heavily on intrinsic motivation. Such motivation stems from adolescents\u0026apos; positive attitudes toward physical exercise and their active engagement in exercise behaviors. As posited by Self Determination Theory, individuals are more likely to form sustained exercise habits when the behavior is self-endorsed and autonomously regulated, rather than externally imposed[\u003csup\u003e20]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFinally, based on the research team\u0026apos;s long-term observation and documentation of adolescents\u0026apos; exercise behaviors, it has been found that the formation of exercise habits among adolescents essentially involves the integration of physical exercise into daily life as an embodied practice. This process represents an external manifestation of the lifestyle sports. During this transformation, adolescents\u0026rsquo; agency and creativity are fully expressed, and their sense of presence and well-being is continuously enhanced. In turn, this positive experiential feedback reinforces and motivates the continued development of exercise habits[\u003csup\u003e21]\u003c/sup\u003e. The inclusion of daily-life integration as a structural component of adolescents\u0026rsquo; exercise habits aligns well with the core principles of physical literacy, lifestyle sports, and lifelong physical activity. These frameworks all emphasize internalizing physical exercise as a life attitude, embedding it into everyday routines, and recognizing it as an indispensable component of daily life[\u003csup\u003e22]-[23]\u003c/sup\u003e. When physical exercise becomes genuinely embedded in daily life, it tends to manifest as an \u0026quot;anytime and anywhere\u0026quot; behavior that requires minimal deliberation or exertion of willpower.\u003c/p\u003e\n\u003cp\u003eIn summary, this study proposes consistency, self-motivation, and daily-life integration as the three fundamental dimensions for measuring exercise habits among adolescents as illustrated in Table 1. Notably, the inclusion of the daily-life integration dimension offers a novel perspective for the development of measurement tools. The three dimensions form a progressive, hierarchical structure, indicating that the formation of exercise habits among adolescents begins with stable exercise behaviors, advances to self-determined attitudes toward exercise, and ultimately evolves into the incorporation of exercise into everyday life.\u003c/p\u003e\n\u003cp\u003eTable 1. Dimensions and Theoretical Foundations of the EHAS\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"598\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19.5652%;\"\u003e\n \u003cp\u003eDimensions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45.3177%;\"\u003e\n \u003cp\u003eDefinition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35.1171%;\"\u003e\n \u003cp\u003eTheoretical Foundations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5652%;\"\u003e\n \u003cp\u003econsistency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.3177%;\"\u003e\n \u003cp\u003eRefers to the consistent and regular performance of physical exercise over a certain period, with low susceptibility to external interference.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1171%;\"\u003e\n \u003cp\u003eExisting Research Consensus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5652%;\"\u003e\n \u003cp\u003eself-motivation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.3177%;\"\u003e\n \u003cp\u003eReflects the adolescent\u0026apos;s conscious motivation and autonomous intention to engage in physical exercise.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1171%;\"\u003e\n \u003cp\u003eSelf Determination Theory\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5652%;\"\u003e\n \u003cp\u003edaily-life integration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45.3177%;\"\u003e\n \u003cp\u003eRefers to the degree to which physical exercise is embedded in daily life.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.1171%;\"\u003e\n \u003cp\u003ePhysical Literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Methods","content":"\u003ch2\u003eItem Generation\u003c/h2\u003e\n\u003cp\u003eBased on the confirmed basic structure of the adolescent exercise habit scale (see Table 1), an original item pool was developed through a comprehensive review of relevant literature. At the same time, a focus group was established consisting of three graduate students majoring in Physical Education and five adolescents who regularly participate in physical exercise. The group reviewed the clarity and appropriateness of each item. Based on their feedback, indistinct or inappropriate items were removed, resulting in the formation of the final item pool.\u003c/p\u003e\n\u003cp\u003eThe final item pool was then evaluated by 13 experts, each with more than five years of experience in adolescent physical activity research or physical education teaching. These experts were asked to rate the appropriateness of each item for its respective dimension using a 4-point Likert scale, where a score of 4 indicated high appropriateness and a score of 1 indicated low appropriateness. Based on the expert ratings, the Content Validity Index (CVI), probability of chance agreement (Pc), and Kappa coefficient were calculated for each item. Items with a CVI below 0.78, or those with a CVI above 0.78 but a Kappa coefficient below 0.74, were considered potentially problematic. In such cases, qualitative feedback from experts was referenced to revise, delete, or adjust the items accordingly. As a result, an initial adolescent physical exercise habit scale consisting of 33 items was developed in Chinese language and items were rated on a 5-point Likert scale ranging from 1 (definitely disagree) to 5 (definitely agree).\u003c/p\u003e\n\u003ch2\u003eSample \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe recruitment of participants in this study was approved by the Ethics Review Committee of East China Normal University (protocol number: HR 206-2024). Considering that the required sample size should be 10 to 20 times the number of items[\u003csup\u003e24]\u003c/sup\u003e, along with an estimated 5%\u0026ndash;10% invalid response rate, a minimum of 348 participants was deemed necessary. Based on this calculation, data collection was conducted from October to November 2023 in three junior high schools and three senior high schools in Jiangsu province, China. A total of 1,480 questionnaires were distributed through offline means, and 1,464 were returned. After excluding invalid responses, 1,346 valid samples were obtained, resulting in a response rate of 90.95%.\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eThe total sample was randomly and evenly divided into two equal subsamples (Sample 1 and Sample 2) for cross-validation. Sample 1 was used for item analysis and exploratory factor analysis (EFA), while Sample 2 was used for confirmatory factor analysis (CFA).\u003c/p\u003e\n\u003cp\u003eItem reduction analysis was conducted by using the item discrimination index and item-total correlation coefficients. First, the total scores of all items in Sample 1 were calculated for each participant and ranked from highest to lowest. The top 27% of participants were classified as the high-score group, and the bottom 27% as the low-score group. Independent samples \u003cem\u003et\u003c/em\u003e-tests were performed to compare item scores between the two groups. Items that did not show statistically significant differences were considered to have low discrimination and were eliminated. Second, item-total correlation coefficients were computed, and items with correlation coefficients less than 0.30 were removed.\u003c/p\u003e\n\u003cp\u003eThe EFA was conducted to examine the dimensional structure of the scale. Prior to the EFA, the Kaiser-Meyer-Olkin (KMO) test and Bartlett\u0026rsquo;s test of sphericity were performed to assess the sampling adequacy and factorability of the data. A KMO value greater than 0.70 and a statistically significant result from Bartlett\u0026rsquo;s test (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) indicated that the data were suitable for factor analysis. To explore the underlying dimensional structure of the scale, principal component analysis (PCA) was performed, and varimax rotation was applied. Items with low loadings were removed based on commonly adopted criteria in previous studies. The item deletion criteria were as follows: (1) a factor loading less than 0.40; (2) the difference in factor loadings of the same item across two or more factors was less than 0.10 and (3) cross-loadings greater than 0.40 on two or more factors. During the analysis, only one item was removed at a time, followed by a new round of exploratory factor analysis (EFA), until an optimal factor structure was achieved.\u003c/p\u003e\n\u003cp\u003eThe CFA was conducted to examine the construct validity of the scale. Model fit was considered acceptable if the following criteria were met: \u0026chi;\u0026sup2;/df between 1 and 5, Goodness of Fit (GFI) \u0026gt; 0.80, Root Mean Square Error Approximation (RMSEA) \u0026lt;0.08, Adjusted Goodness of Fit (AGFI) \u0026gt; 0.80, Comparative Fit Index (CFI) \u0026gt; 0.90 and Tucker Lewis Index (TLI) \u0026gt; 0.90. GFI, CFI and TLI above 0.85 were considered acceptable as marginal fit. In addition, to test convergent validity, average variance extracted (AVE) per construct was calculated, with the requirement of all the constructs at 0.5 as good, and 0.36 as acceptable\u003c/p\u003e\n\u003cp\u003eCronbach\u0026rsquo;s a coefficient was used to assess the internal consistency of the scale, indicating the degree to which the items measure the same construct or dimension. A Cronbach\u0026rsquo;s alpha value between 0.70 and 0.80 was considered indicative of good internal consistency.\u003c/p\u003e\n\u003cp\u003eFor content validity, at the initial stage of scale development, 13 experts with relevant experience were invited to evaluate the appropriateness of the scale items. A Content Validity Index (CVI) greater than 0.78 or a Kappa coefficient greater than 0.74 was considered indicative of satisfactory content validity.\u003c/p\u003e\n\u003cp\u003eFor criterion validity, the item \u003cem\u003e\u0026ldquo;Please rate your overall physical exercise habit\u0026rdquo;\u003c/em\u003e was used as the criterion variable, representing participants\u0026rsquo; overall self-perception of their physical exercise habit. Correlations between the total score and each item score with the above item were calculated to examine the criterion-related validity of the scale.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eParticipants\u0026rsquo; characteristics\u003c/h2\u003e\n\u003cp\u003eThe sample consisted of 1,346 adolescents, including 714 males and 632 females. Approximately 598 participants were high school students and 748 were junior high school students, with ages ranging from 12 to 18 years.\u003c/p\u003e\n\u003ch2\u003eItem reduction analysis of AEHS\u003c/h2\u003e\n\u003cp\u003eItem discrimination analysis revealed that Items 4, 8, and 24 showed no significant difference in scores between the high-score and low-score groups, and were therefore excluded from the scale. The item-total correlation analysis showed that the remaining 30 items were all significantly correlated with the total score (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), with correlation coefficients ranging from 0.439 to 0.774. These items were retained for subsequent analyses.\u003c/p\u003e\n\u003ch2\u003eExploratory factor analysis of the AEHS\u003c/h2\u003e\n\u003cp\u003eThe initial\u0026nbsp;EFA was conducted on the 30 items retained after item analysis. The KMO value was 0.954, and Bartlett\u0026rsquo;s test of sphericity was statistically significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), indicating that the data were appropriate for factor analysis.\u0026nbsp;A PCA was conducted using varimax rotation to explore the underlying factor structure. Items with low factor loadings were removed from the scale during the analysis.\u0026nbsp;The results of the first EFA revealed that Items 2, 6, 9, 11, 14, 16, 17, 18, 20, 26, and 33 exhibited cross-loadings, with factor loadings greater than 0.40 on two or more factors. Therefore, these items were removed from the scale. After the deletion of each item, the KMO test, Bartlett\u0026rsquo;s test of sphericity, and EFA were re-conducted to ensure the adequacy of the data and the stability of the factor structure. Due to space limitations, only the results of the final EFA are presented in this paper.\u003c/p\u003e\n\u003cp\u003eAfter three rounds of EFA, a total of three factors were extracted, accounting for 68.53% of the cumulative variance (see Table 2). These three factors were consistent with the theoretically hypothesized structure of this study. Based on the thematic content of the items within each factor, they were respectively labeled as consistency (4 items), self-motivation (4 items), and daily-life Integration (4 items). The full English version of the scale is available in the supplementary materials.\u003c/p\u003e\n\u003cp\u003eTable2. \u0026nbsp;Factor structures by Exploratory Factor Analysis\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 60px;\"\u003e\n \u003cp\u003eSign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 307px;\"\u003e\n \u003cp\u003eItems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 167px;\"\u003e\n \u003cp\u003eFactor loading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003eCommunality\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eF\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eF\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eF\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eParticipates in moderate-intensity physical activity (e.g., noticeable increase in heart rate and breathing) at least three times per week.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eI stick to my exercise routine regardless of whether others (classmates, peers, or friends) do it or not.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eI can persist in exercising even when I feel like giving up or taking a break.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eI still engage in physical exercise despite heavy academic pressure.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eCompared with other activities, I often regard physical exercise as one of my daily life priorities.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eLife feels dull and meaningless if I cannot engage in physical exercise.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eDaily physical exercise has become a part of my routine.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eLike eating and sleeping, physical exercise is a natural part of my daily routine that I do without needing reminders.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eI actively take part in physical activities both at school and in my free time.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eI take the initiative to exercise even without being pushed by teachers or parents.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eI actively seek solutions when facing difficulties in physical exercise, such as asking teachers or classmates and looking for information elsewhere.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.548\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eS 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 307px;\"\u003e\n \u003cp\u003eI am eager to try various sports or learn new sports skills.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e0.881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 366px;\"\u003e\n \u003cp\u003eEigenvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e2.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 366px;\"\u003e\n \u003cp\u003eCumulative variance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e47.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e11.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e9.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e68.525\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e注：F1 = Consistency；F2 = Daily-life integration；F3 = Self-motivation\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConfirmatory factor analysis of the AEHS\u003c/h2\u003e\n\u003cp\u003eThe CFA was then conducted in order to replicate the factor structure identified through the EFA with sample 2. The model fit indices were as follows: \u0026chi;\u0026sup2;/df = 3.952 (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), SRMR = 0.059, RMSEA = 0.076, GFI = 0.925, TLI = 0.903, and CFI = 0.925, indicating that the proposed theoretical model demonstrated an acceptable and satisfactory fit to the data. All standardized factor loadings were statistically significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), and all items significantly loaded onto the same factor as they had in the EFA.\u003c/p\u003e\n\u003ch2\u003eReliability\u003c/h2\u003e\n\u003cp\u003eThe Cronbach\u0026rsquo;s \u0026alpha; coefficients for each subscale of the instrument ranged from 0.705 to 0.855, and the composite reliability (CR) values ranged from 0.693 to 0.858, indicating acceptable to good internal consistency (see Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3. AEHS reliability and average variance extracted（AVE）\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eDomain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eCronbach\u0026apos;s\u0026nbsp;a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eFactor loading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eAVE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eConsistency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eSelf-motivation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.671\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003edaily-life Integration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eS22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eS23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eS25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eS32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eValidity\u003c/h2\u003e\n\u003cp\u003eInitially, the scale items were evaluated by a panel of experts. The final 12 items retained had Content Validity Index (CVI) values range from 0.79 to 0.87, all exceeding the recommended threshold of 0.78. The corresponding Kappa values ranged from 0.79 to 0.87, also surpassing the acceptable minimum of 0.74. These results indicate a low probability of agreement occurring by chance, suggesting that the scale possesses satisfactory content validity. Secondly, the Average Variance Extracted (AVE) values for the three dimensions of the scale were 0.378, 0.554, and 0.603, respectively (see Table 3). All values exceeded the minimum acceptable threshold of 0.36, indicating that the scale demonstrates acceptable convergent validity. Finally, the correlations between the three dimensions and the total score of the scale with the overall self-rating score ranged from 0.564 to 0.659. All correlation coefficients were statistically significant at the 0.01 level, indicating positive relationships and supporting the criterion-related validity of the scale.\u003c/p\u003e\n\u003ch2\u003eAdolescent Exercise Habit Classification Criteria\u003c/h2\u003e\n\u003cp\u003eThe finalized Adolescent Exercise Habit Scale, after reliability and validity testing, consists of three dimensions, each containing four items, for a total of 12 items. The scale adopts a 5-point Likert rating format, with total scores ranging from 12 to 60.\u003c/p\u003e\n\u003cp\u003eA statistical analysis of the total score distribution across the 1,346 valid samples revealed a skewed distribution, as indicated by the Kolmogorov\u0026ndash;Smirnov test (D = 0.039, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Therefore, the quantile method was employed to establish categorical levels of adolescent physical exercise habits.\u003c/p\u003e\n\u003cp\u003eBased on an ascending sort of the total scores, participants were classified into three levels of exercise habit strength using percentile cutoffs. The 25th percentile score (32 points) was set as the cutoff for the low-score group, while the 75th percentile score (48 points) was used as the cutoff for the high-score group. Accordingly, scores within the range of 12 \u0026le;\u0026nbsp;total score ＜ 32 were categorized as low level, 32 \u0026le;\u0026nbsp;total score ＜ 48 as moderate level, and 48 \u0026le;\u0026nbsp;total score \u0026le; 60 as high level (see Table 4).\u003c/p\u003e\n\u003cp\u003eCompared with the four-level classification proposed in previous studies\u003csup\u003e[\u003c/sup\u003e\u003csup\u003e11\u003c/sup\u003e\u003csup\u003e]\u003c/sup\u003e, the three-level classification scheme offers greater practicality, with clearer and more explicit categorization criteria that enhance ease of understanding and facilitate user proficiency in application.\u003c/p\u003e\n\u003cp\u003eTable 4. Classification of Score Levels for the AEHS\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eScore range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 376px;\"\u003e\n \u003cp\u003eCharacteristics of Physical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eLow\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e12\u0026le;score＜32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 376px;\"\u003e\n \u003cp\u003eNo established exercise habit; participation is infrequent and inconsistent.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e32\u0026le;score＜48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 376px;\"\u003e\n \u003cp\u003ePhysical exercise is somewhat regular but prone to interruption.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e48\u0026le;score\u0026le;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 376px;\"\u003e\n \u003cp\u003eA well-developed exercise habit has been formed, with physical activity fully integrated into daily life.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eOn the basis of a clearly defined conceptualization of adolescent exercise habits, this study developed an item pool and initially validated the psychometric properties of the scale using a sample of 1,346 Chinese adolescents. The results demonstrated that the Adolescent Exercise Habit Scale exhibited acceptable factorial validity, satisfactory reliability, and significant discriminative power, indicating that it is a valid instrument for assessing the level of exercise habits among adolescents.\u003c/p\u003e\n\u003ch2\u003eThree dimensions: Consistency, self-motivation, and daily-life integration \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThree dimensions have been derived from the 12-item scale, including consistency, self-motivation and daily-life integration. The structure of AEHS obtained in EFA was consistent with the predefined conceptual framework. Firstly, the study identified consistency as a critical dimension of exercise habits, which demonstrated sound structural and predictive validity in the adolescent sample, indicating its effectiveness in capturing the persistence of individuals\u0026rsquo; exercise behaviors. Typically, exercise frequency is considered the most salient feature of habitual physical exercise[\u003csup\u003e25]\u003c/sup\u003e. For adults, engaging in physical exercise at least three times per week is often regarded as a benchmark for the formation of an exercise habit.\u003c/p\u003e\n\u003cp\u003eHowever, in the context of Chinese adolescents, physical activity frequency is generally guaranteed due to participation in at least three 40-minute mandatory physical education classes per week, along with voluntary extracurricular exercise of approximately one hour per day. It is, in fact, the heavy academic burden that frequently disrupts adolescents\u0026rsquo; exercise routines. Therefore, using consistency to characterize the extent to which adolescents\u0026rsquo; physical activity behaviors can resist external interference may better capture the actual process of exercise habit formation among this population. This is because frequency merely reflects how often a behavior occurs, whereas consistency captures the extent to which the behavior is sustained, self-initiated, and resistant to external disruptions.\u003c/p\u003e\n\u003cp\u003eSecondly，according to Self-Determination Theory, long-term behavioral adherence is largely influenced by the extent to which the behavior is self-determined. That is, behaviors initiated volitionally and experienced as autonomous are more likely to be internalized and sustained over time[\u003csup\u003e26]\u003c/sup\u003e. In the context of physical exercise, when adolescents perceive exercise as a personally endorsed choice rather than a response to external pressures, the behavior is more likely to become habitual. Clearly, the inclusion of the dimension of self-motivation is theoretically justified and empirically grounded.\u003c/p\u003e\n\u003cp\u003eFinally, the dimension of daily-life integration aligns closely with the concept of lifelong physical activity advocated by physical literacy. From the perspective of physical literacy theory, integration into daily life is not merely an extension of exercise frequency, but rather a deeper manifestation of adolescents\u0026rsquo; internalization of physical exercise as a routine component of their everyday lives. Therefore, assessing the extent to which individuals naturally integrate physical exercise into diverse daily life contexts can better capture whether such behaviors have been socialized, contextualized, and meaningfully internalized. This dimension serves as a crucial predictor of their lifelong engagement in physical exercise.\u003c/p\u003e\n\u003ch2\u003eReliability and Validity of AEHS\u003c/h2\u003e\n\u003cp\u003eThe psychometric evaluation of the EHAS provides robust support for its reliability and validity. The internal consistency of each subdimension reached acceptable thresholds, suggesting that the items coherently represent their respective constructs. Composite reliability indices further confirmed the structural stability of the measurement model. In terms of validity, content validity was ensured through a rigorous item development process grounded in theoretical frameworks and expert consultation. The scale also demonstrated acceptable convergent validity, indicating that each construct effectively captures the underlying conceptual domain it was designed to measure. Moreover, the observed positive associations with external criterion measures provide evidence for satisfactory criterion-related validity, supporting the scale\u0026rsquo;s capacity to reflect meaningful behavioral tendencies in adolescent physical exercise habits. Collectively, these findings affirm the sound measurement properties of the instrument and its applicability in future research on youth exercise behavior.\u003c/p\u003e\n\u003ch2\u003eClassification of Adolescent Exercise Habit Levels\u003c/h2\u003e\n\u003cp\u003eBased on the total scores of the AEHS, this study categorized adolescents\u0026rsquo; physical exercise habits into three levels\u0026mdash;low, moderate, and high\u0026mdash;thus overcoming the traditional unidimensional approach that solely relies on exercise frequency or duration to assess the quality of exercise habits. The decision to adopt a tiered evaluation framework for adolescent physical exercise habits stems from both conceptual and practical considerations. Theoretically, habit is not a dichotomous construct but a continuum that reflects varying degrees of behavioral automaticity, motivational internalization, and contextual integration. Binary classifications\u0026mdash;such as active vs. inactive\u0026mdash;fail to capture the nuanced progression from intention-driven participation to deeply ingrained routines. By segmenting habit strength into low, moderate, and high levels, the present framework acknowledges the gradual and multidimensional nature of habit development, as proposed by recent models in health psychology and behavioral science[\u003csup\u003e27]\u003c/sup\u003e. Practically, such stratification enables more targeted interventions: those in the early phase may benefit from motivational priming, whereas individuals with moderate-level habits may require environmental restructuring to reinforce consistency. Furthermore, this classification facilitates longitudinal tracking of habit consolidation, offering a dynamic lens to assess intervention efficacy over time.\u003c/p\u003e\n\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\n\u003cp\u003eTo the best of our knowledge, this is the first study to develop and preliminarily validate the psychometric properties of the exercise habit scale in adolescents. A notable strength of the present study lies in its conceptual advancement over previous research that primarily equated exercise habits with behavioral frequency. Moreover, The AEHS was developed with consideration for the unique cultural context of Chinese adolescents, ensuring relevance and appropriateness in measuring exercise habits within this population.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, due to resource and time constraints, the data used for scale development were collected solely from adolescents in Jiangsu Province, lacking regional diversity in the sample. This may limit the generalizability of the AEHS. Second, further investigation involving more locations and a larger sample size is necessary to enhance the scale\u0026rsquo;s applicability across different populations. Third, data were collected via self-reported paper questionnaires, which, although beneficial for adolescent comprehension, could be complemented by other data sources such as diaries, observations, and teacher reports to strengthen the scale\u0026rsquo;s scientific rigor. Fourth, given that modifications were made to achieve satisfactory model fit, the CFA model remains provisional and requires further replication. Finally, due to the absence of a gold standard for evaluating physical exercise habits and the cross-sectional nature of this study, no further validation of the habit level classification was conducted. Future research should consider collecting longitudinal data to dynamically track adolescents\u0026rsquo; physical exercise behaviors over time, thereby verifying whether the classification criteria reflect real-world conditions. Such longitudinal data should not only include observable indicators such as exercise frequency and duration but also emphasize implicit information related to adolescents\u0026rsquo; cognition and affect toward physical exercise during their development.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe AEHS is a 12-item, theoretically grounded instrument with acceptable construct validity and reliability for identifying adolescents\u0026rsquo; exercise habits. Unlike traditional assessment paradigms that rely solely on the repetitiveness of exercise behaviors, this scale incorporates dimensions such as behavioral consistency, self-motivation, and daily-life integration, offering a more comprehensive reflection of the multidimensional nature of exercise habits. Moreover, the habit-level classification based on total scores provides a foundational reference for understanding the developmental stages of exercise habit formation among adolescents. This classification facilitates the precise identification of individuals\u0026apos; current stages of habit development and offers evidence to inform targeted educational interventions and behavioral promotion strategies.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would appreciate support and input from Professor Youping Sun and his students at East China Normal University, Shanghai, and the members of East China Normal University Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJin Wu wrote the main manuscript text. Liqiang Li and Huasen Yu performed data analysis.Yuhang Yang and Zeyang Zhang were in charge of data collection. Xiaopan Hu and Zufeiya Tuerdi prepared participant recruitment.All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Project of Shaanxi Provincial Department of Education Science Research Program \u0026ldquo;Epidemiological Investigation and Exercise Intervention Research on Adolescent Idiopathic Scoliosis\u0026rdquo; (23JK0698)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis scale development study is conducted in compliance with the ethical principles\u003c/p\u003e\n\u003cp\u003eof the 1964 Declaration of Helsinki and its later amendments. The recruitment of participants in this study was approved by the Ethics Review Committee of East China Normal University (protocol number: HR 206-2024). School administrators and parents/legal guardians were informed in advance about the study\u0026rsquo;s purpose, procedures, and voluntary nature. Written informed consent was obtained from all parents/guardians. Participation was voluntary, and no financial incentives were provided.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to disclose\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMenescardi C, De Meester A, Morb\u0026eacute;e S, Haerens L, Estevan I. The role of motivation in the conceptual model of motor development in childhood. Psychol Sport Exerc. 2022;61:102188.\u003c/li\u003e\n\u003cli\u003eBiddle SJ, Asare M. Physical activity and mental health in children and adolescents: a review of reviews. Br J Sports Med. 2011;45(11):886\u0026ndash;95.\u003c/li\u003e\n\u003cli\u003eWassenaar TM, Wheatley CM, Beale N, Nichols T, Salvan P, Meaney A, et al. The effect of a one-year vigorous physical activity intervention on fitness, cognitive performance and mental health in young adolescents: the Fit to Study cluster randomised controlled trial. Int J Behav Nutr Phys Act. 2021;18:1\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eB\u0026eacute;langer M, Casey M, Cormier M, Laflamme Filion A, Martin G, Aubut S, Chouinard P, Savoie SP, Beauchamp J. Maintenance and decline of physical activity during adolescence: insights from a qualitative study. Int J Behav Nutr Phys Act. 2011;8:1\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eGardner B, Phillips LA, Judah G. Habitual instigation and habitual execution: definition, measurement, and effects on behaviour frequency. Br J Health Psychol. 2016;21(3):613\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eGardner B, Abraham C, Lally P, de Bruijn GJ. Towards parsimony in habit measurement: testing the convergent and predictive validity of an automaticity subscale of the Self-Report Habit Index. Int J Behav Nutr Phys Act. 2012;9:1\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eVerplanken B, Verplanken B, Ryan. Psychology of habit. Cham: Springer; 2018. p. 32\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003ePereira FHF, Santos-de-Ara\u0026uacute;jo AD, Pontes-Silva A, et al. Regular Physical Exercise Adherence Scale (REPEAS): a new instrument to measure environmental and personal barriers to adherence to regular physical exercise. BMC Public Health. 2023;23(1):2491.\u003c/li\u003e\n\u003cli\u003eChen H, Liu J, Bai Y. Global accelerometer-derived physical activity levels from preschoolers to adolescents: a multilevel meta-analysis and meta-regression. Ann Behav Med. 2023;57(7):511\u0026ndash;29.\u003c/li\u003e\n\u003cli\u003eWang K, Ji L. The building of a concept model of physical exercise habits of teenagers. J Phys Educ. 2013;20(05):93\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eWeng Q. A Study on Exercise Habits among Chinese Secondary School Students [dissertation]. Shanxi: Shanxi Normal University; 2015.\u003c/li\u003e\n\u003cli\u003eYan J, Sun H, Zhang J, Liu Z. Analysis and implications of international experience on the factors, measurement methods and intervention strategies of forming physical activity habits. J Beijing Sport Univ. 2022;45(04):63\u0026ndash;77.\u003c/li\u003e\n\u003cli\u003eLally P, Gardner B. Promoting habit formation. Health Psychol Rev. 2013;7(sup1): S137\u0026ndash;58.\u003c/li\u003e\n\u003cli\u003eAarts H, Paulussen T, Schaalma H. Physical exercise habit: on the conceptualization and formation of habitual health behaviours. Health Educ Res. 1997;12(3):363\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eTappe KA, Glanz K. Measurement of exercise habits and prediction of leisure-time activity in established exercise. Psychol Health Med. 2013;18(5):601\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eBignold WJ. Developing school students\u0026apos; identity and engagement through lifestyle sports: a case study of unicycling. Sport Educ Soc. 2013;18(2):184\u0026ndash;99.\u003c/li\u003e\n\u003cli\u003eRannikko A, Harinen P, Torvinen P, Liikanen V. The social bordering of lifestyle sports: inclusive principles, exclusive reality. J Youth Stud. 2016;19(8):1093\u0026ndash;109.\u003c/li\u003e\n\u003cli\u003eHazen E, Schlozman S, Beresin E. Adolescent psychological development: a review. Pediatr Rev. 2008;29(5):161\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eJones M, Defever E, Letsinger A, Steele J, Mackintosh KA. A mixed-studies systematic review and meta-analysis of school-based interventions to promote physical activity and/or reduce sedentary time in children. J Sport Health Sci. 2020;9(1):3\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eNtoumanis N, Moller AC. Self-Determination Theory informed research for promoting physical activity: contributions, debates, and future directions. Psychol Sport Exerc. 2025;102879.\u003c/li\u003e\n\u003cli\u003eFremling L, Phillips LA, Bottoms L, Desai T, Newby K. Comparing positive versus negative intrinsic rewards for predicting physical activity habit strength and frequency during a period of high stress. Appl Psychol Health Well Being. 2025;17(1):e12650.\u003c/li\u003e\n\u003cli\u003eGrauduszus M, Wessely S, Klaudius M, Joisten C. Definitions and assessments of physical literacy among children and youth: a scoping review. BMC Public Health. 2023;23(1):1746.\u003c/li\u003e\n\u003cli\u003eBocarro J, Kanters MA, Casper J, Forrester S. School physical education, extracurricular sports, and lifelong active living. J Teach Phys Educ. 2008;27(2):155\u0026ndash;66.\u003c/li\u003e\n\u003cli\u003eThompson B. The ten commandments of good structural equation modeling behavior: a user-friendly introductory primer on SEM. 1998.\u003c/li\u003e\n\u003cli\u003eLee Y, Yoon YJ. Exploring the formation of exercise habits with the latent growth model. Percept Mot Skills. 2019;126(5):843\u0026ndash;61.\u003c/li\u003e\n\u003cli\u003eXu Z, Shamsulariffin S, Azhar Y, Xi M. Does Self‐Determination Theory associate with physical activity? A systematic review of systematic reviews. Int J Psychol. 2025;60(3):e70044.\u003c/li\u003e\n\u003cli\u003eWood W, R\u0026uuml;nger D. Psychology of habit. Annu Rev Psychol. 2016;67(1):289\u0026ndash;314.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"exercise habits, Adolescents, Scale development, Consistency, Self-motivation, daily-life integration","lastPublishedDoi":"10.21203/rs.3.rs-6991427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6991427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eEstablishing regular exercise habits during adolescence is essential for fostering lifelong physical activity participation. Despite its importance, reliable and culturally appropriate tools to assess exercise habits among Chinese adolescents remain limited. This study aimed to develop and validate the adolescent exercise habit scale (AEHS), a psychometrically sound instrument for assessing self-reported exercise habits in this population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eGrounded in a multidimensional conceptual framework, the initial 33-item pool was generated based on literature review and expert consultation. A total of 1346 students aged 12 to 18 from Jiangsu China completed the preliminary version of the scale. Item analysis and exploratory factor analysis (EFA) were conducted to refine the scale structure, followed by confirmatory factor analysis (CFA) to test its factorial validity. In addition, we employed a percentile-based method to classify adolescents' exercise habit levels according to their scale scores.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe final AEHS consisted of 12 items loading on three dimensions: exercise consistency, self-motivation, and integration of exercise into daily life. The AEHS showed acceptable internal consistency, content validity, convergent validity and criterion-related validity (Cronbach\u0026rsquo;s α ranged from 0.705 to 0.855, CVI values ranged from 0.79 to 0.87, AVE values ranged from 0.378 to 0.603, and correlation coefficients ranged from 0.564 to 0.659). The AEHS also enables the classification of adolescents' exercise habits into low, moderate, and high levels based on their total scores.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOverall, the AEHS appears to be a valid and reliable tool for evaluating adolescent exercise habits in Chinese contexts and may contribute to more targeted interventions in physical activity promotion.\u003c/p\u003e","manuscriptTitle":"Development and initial validation of the adolescent exercise habits scale (AEHS) among Chinese population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-21 13:25:23","doi":"10.21203/rs.3.rs-6991427/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-22T03:59:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T09:37:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-06T14:33:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217231661848525194404651019954950560441","date":"2025-07-23T06:25:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"266456500986673996601779875425606807094","date":"2025-07-17T12:13:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-17T09:03:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-03T08:15:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-03T02:22:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-07-03T02:20:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"449996e0-8b81-4920-a770-b802a902f3b0","owner":[],"postedDate":"July 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T15:59:36+00:00","versionOfRecord":{"articleIdentity":"rs-6991427","link":"https://doi.org/10.1186/s12889-025-25818-y","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-12-02 15:56:51","publishedOnDateReadable":"December 2nd, 2025"},"versionCreatedAt":"2025-07-21 13:25:23","video":"","vorDoi":"10.1186/s12889-025-25818-y","vorDoiUrl":"https://doi.org/10.1186/s12889-025-25818-y","workflowStages":[]},"version":"v1","identity":"rs-6991427","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6991427","identity":"rs-6991427","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}