Xulin Zhang
Jingfei Yan
Weiqiang Zhu
Xiaoya Fu3- 1College of Physical Education and Health, East China Normal University, Shanghai, China
- 2Ministry of Physical Education, Shanghai Institute of Technology, Shanghai, China
- 3College of Physical Education, Ningxia Normal University, Guyuan, China
Introduction: Adolescence represents a pivotal stage in the development of healthy behaviors, where establishing positive physical activity habits can have enduring effects on an individual's overall wellbeing. The ecological model highlights the influence of environmental factors on human behavior, with the family environment playing a significant role in shaping the physical activity habits of adolescents.
Methods: The aim of this scale is to develop a reliable and effective tool, customized for the unique societal context of China, to assess how family factors influence the physical activity habits of Chinese adolescents. Participants were recruited through stratified cluster sampling from 24 secondary schools in six Chinese provinces between October and November 2021, resulting in 1,061 participants. Analysis was conducted on 1,004 valid questionnaires, divided into two samples. Sample 1, consisting of 502 students (248 males and 254 females; Mage = 15.5), underwent item analysis and exploratory factor analysis. Sample 2, comprising 502 students (267 males and 235 females; Mage = 16.5), underwent confirmatory factor analysis and internal consistency reliability analysis.
Results: Through exploratory factor analysis, we extracted three factors comprising 15 items: “Family Environment Construction” (4 items), “Family Action Support” (6 items), and “Family Health Awareness” (5 items). The Cronbach's alpha values for these factors ranged from 0.890 to 0.894. Confirmatory factor analysis confirmed a satisfactory model fit (CMIN/DF = 1.45, SRMR = 0.027, GFI = 0.991, TLI = 0.989, RMSEA = 0.03).
Discussion: The scale demonstrated strong internal consistency and test-retest reliability, confirming its effectiveness in empirical research. This study holds significant implications for enhancing the physical activity levels of adolescents, promoting their physical and mental wellbeing, enriching their developmental experiences, and contributing to their overall sense of happiness.
1 Introduction
Physical activity is defined as any bodily movement produced by skeletal muscles that requires energy expenditure, encompassing activities such as walking, cycling, sports, and recreational activities (World Health Organization, 2022). Physical activity contributes significantly to enhancing overall health and reducing the risk of chronic diseases, including cardiovascular diseases, cancer and diabetes (World Health Organization, 2022). Regular engagement in physical activity plays a crucial role in promoting the health and well-being of individuals, particularly during adolescence, which is a critical period for the development of health behaviors (van Sluijs et al., 2021). Establishing positive patterns of physical activity during this stage can have long-lasting effects on individuals' health and wellbeing throughout their lives.
The application of health behavior theories in physical activity has revealed the role of environmental influences, most commonly “barriers,” “facilitating conditions,” or “contextual influences” (Godin, 1994). Bandura (1986)'s social cognitive theory provides valuable insights into the interplay among environmental, personal, and behavioral factors. The varying impact of these factors is contingent upon the specific activity, individual characteristics, and environmental context. Transitioning to the work of Sallis and Hovell (1990), who introduced a social cognitive model for physical activity behavior, emphasizes the pivotal role of environmental attributes within a framework where multiple determinants interact across various levels. Within this model (Sallis and Hovell, 1990) the “ecological” model of health behavior provides a holistic understanding of how diverse determinants interact across various levels in individuals' physical and socio-cultural environments. The family environment, as a primary socializing agent, holds significant influence adolescents' exercise behaviors and habits (Roque Garay, 2018; Korom et al., 2023). Families provide the foundation for learning and adopting health behaviors (Hunt et al., 2015). Extensive research has demonstrated the impact of the family environment on the formation of exercise habits among adolescents (Mota, 1998; Zovko et al., 2021). For example, factor such as family support (Kuo et al., 2007; Álvarez Muñoz and Hernández Prados, 2023; Hu and Cai, 2023), parental role modeling (Adkins et al., 2017; Do et al., 2023), and the availability of resources and opportunities for physical activity within the family context (Álvarez Muñoz and Hernández Prados, 2023) have been found to be crucial in influencing adolescents' exercise behaviors. The family environment encompasses various aspects, including parental attitudes (Cleland et al., 2011; Whooten et al., 2023), parental involvement (Kuo et al., 2007), family socioeconomic status (Cleland et al., 2011), and the home physical activity environment (Kuo et al., 2007; Cleland et al., 2011). Understanding the influence of the family environment on adolescent exercise behavior can lead to the development of effective interventions and programs to promote physical activity and cultivate exercise habits among adolescent. According to recent statistics, only 20% of Chinese youth aged 5–17 engage in 60 min of moderate to vigorous activity daily, which fall far below the recommendations set by the World Health Organization (Liu, 2023). The Childhood Blue Book: China Children's Development Report (2021) reveals an alarming increase of 8.7 percentage points in the rates of overweight and obesity among elementary and middle school students from 2010 to 2019 (Zhao and He, 2023). This highlights the urgent need for interventions promoting physical activity in this population.
However, a lack of scientific measurement and evaluation tools hinders a comprehensive understanding of how families influence adolescents' physical activity and exercise habits. Prior family-focused models such as the Family Influence Scale (Taylor et al., 1994) and Family Eating and Activity Habits Questionnaire (Golan et al., 2006) have quantified influences like parenting practices and role modeling on youth dietary and activity behaviors. However, these Western-developed tools lack cultural adaptation for the Chinese context. They often emphasize adolescent autonomy (Chai et al., 2018) rather than filial piety norms (Deng et al., 2022) This indicates a need for localized measurement models to fully capture family environment dynamics shaping Chinese adolescents' physical activity habits. To measure the influence of the family environment on adolescent physical activity behaviors, the development of a reliable and valid measurement tool is crucial. Firstly, current assessment tools often lack a comprehensive focus on family factors. Several existing studies exhibit limitations in exploring a wide array of family factors. For example, some studies employ retrospective surveys (Kim et al., 2007), diminishing relevance in understanding contemporary family environment impacts. Additionally, a substantial number rely solely on self-reports from adolescents (Henry et al., 2014), neglecting to incorporate parent perspectives. The lack of instruments evaluating various real-time family influences underscores the necessity for a culturally adapted scale that comprehensively addresses this gap. Others summarize influencing dimensions too broadly, failing to provide comprehensive content (McMurray et al., 1993; Joosse et al., 2008; Moreno et al., 2011). Secondly, within the Chinese context, the localization of evaluation tools for practical applications is not ideal, limiting their effectiveness in research. Chinese researchers mainly rely on foreign questionnaires or scales with revisions to measure physical activity habit of the local population. These primarily focus on family health awareness factors, such as individual physical fitness, health status (Wang, 2011), the importance attached to health (Lin, 2019), and the benefits of physical activity (Hu, 2017). Other factors include the family's economic and educational environment (Lv et al., 2020), parents' educational philosophy (Weng, 2015), parents' personality, and children's time monitoring and allocation (Chu and Xiao, 2020). However, these measurements often lack adequate localization to the unique Chinese context and norms. Concepts such as academic pressure (Xie et al., 2004), parenting style (Xie et al., 2022), filial piety (Cao and Tan, 2021) differ between Western and Chinese cultures. Directly applying measurement tools developed abroad could fail to capture family factors shaping physical activity habits among Chinese adolescents and potentially lead to erroneous interpretations.
Therefore, the primary aim of this study is to develop and validate a scale for assessing the influence of the family environment on the formation of physical activity habits among Chinese adolescents. This research holds significant implications: Firstly, it contributes to a comprehensive understanding of how families influence adolescents' physical activity habits and enhances effective promotion of physical activity. Secondly, it facilitates the development of assessment tools better suited to China's local contexts by specifically focusing on family factors relevant to Chinese adolescents. Lastly, the study aims to gain experience localizing and developing measures of how families impact physical activity for Chinese adolescents.
2 Materials and methods
2.1 Original items for scale development
This study reviewed and analyzed peer-reviewed empirical studies published before January 2023 that employed the social-ecological theory framework to examine how family environment influences adolescents' physical activity habits. The inclusion criteria were: (1) study population of adolescents; (2) investigation of the relationship between family environment variables and adolescent physical activity; (3) use of social-ecological theory to guide the research. Based on the literature review, an interview guide was developed to elicit perspectives on family factors affecting adolescents' activity habits.
The original item pool was created through the following steps: First, extensive potential items grounded in the social-ecological theory and literature were generated through group discussion by the research team. Next, a panel of seven experts in adolescent development and health behavior research evaluated the items for relevance and specificity, with items endorsed by at least five experts retained. The resulting preliminary item pool underwent two rounds of qualitative interviews to obtain target population feedback on the relevance, clarity and construct coverage of the items. The first round involved 2 in-depth individual interviews (approx. 35 mins each) and 4 focus group discussions with 4–5 adolescents per group (approx. 30 mins each), with a total of 18 adolescents. The second round included 4 in-depth individual interviews (approx. 25 mins each) and 5 focus groups of 4–7 adolescents (approx. 35 mins each), with a total of 34 adolescents. Based on the interview data, items were added, eliminated and modified. Finally, the research team held group discussions to reach consensus on the final selection of items for the initial pool.
Subsequently, seven experts in relevant research fields were invited to evaluate the scale. The experts reviewed and examined the content validity index (item-level CVI, I-CVI) of the scale, identified issues, and provided specific modification suggestions. Based on the experts' recommendations, the item content of the scale was modified and revised, resulting in the development of a preliminary version of the “Chinese Adolescents' Physical Activity Habit Formation Scale: Family Environmental Influencing Factors.”
2.2 Participants
The questionnaire survey method was employed in this study, taking into account the regional division of China's three major economic belts, to represent adolescents across China's diverse geographic and socioeconomic areas. To minimize selection bias, multi-stage cluster sampling was utilized. Schools were randomly selected from each region, then classes within chosen schools were randomly sampled to obtain a nationally representative, unbiased participant group. The multistage cluster sampling was utilized to select 1,061 participants from 24 middle schools in six provinces across eastern, central and western China. The effective response rate was 94.6%. Among the collected questionnaires 1,004 were deemed valid and randomly divided into two equal groups: sample 1 and sample 2, each consisting of 502 participants. Scale item analysis and exploratory factor analysis were conducted on sample 1 (248 boys, 254 girls; Mage = 15.5), while confirmatory factor analysis was performed on sample 2 (267 boys, 235 girls; Mage = 16.5).
The recruitment process involved a convenience sample of adolescent students from local schools. All participants' parents or legal guardians provided written informed consent, allowing their children to participate in research. The study received ethical approval from the Ethics Committee of East China Normal University, and this approval ensured that written informed consent was obtained from all participating adolescents and their parents or legal guardians (Ethical approval number: HR 476-2020).
2.3 Items and scoring method
Based on previous relevant scientific research findings and expert opinions, a scale was developed to assess the family factors influencing the development of physical activity habits among Chinese adolescents. The scale consists of three factors and 28 items. Factor 1: “Family Environment Construction” (FEC) comprises 8 items; Factor 2: “Family Action Support” (FAS) includes 12 items; and Factor 3: “Family Health Awareness” (FHA) consists of 8 items. The specific content of each factor and its corresponding items can be found in Table 1.
Table 1. Initial scale composition.
The core evaluation method employed in the scale is the 5-point Likert scale, where respondents indicate their level of agreement or compliance using the following scale: “1” for completely non-compliant, “2” for not very compliant, “3” for average, “4” for compliant, and “5” for very compliant. It is important to note that reverse-scored item is included in the scale, such as the item “Parents do not seem to normally participate in physical activities within the family health awareness factor, as shown in Table 1. Prior to data analysis, the reverse-scored item in the scale is reversed to ensure consistency in scoring.
2.4 Statistical analysis
This study conducted statistical analysis of the data using SPSS24.0 and Mplus 8.3. Initially, descriptive analysis was performed, wherein categorical variables were presented in terms of frequency and percentage, while numerical variables were characterized using the mean and standard deviation (Kim et al., 2020). Subsequently, expert validity evaluation was applied to assess the appropriateness of the scale items, following the methodology proposed by Polit and Beck (2006). The discrimination of each measurement item was tested through item analysis (Raykov and Marcoulides, 2011). Furthermore, exploratory factor analysis was utilized to delve into and optimize the scale structure (Costello and Osborne, 2019), The adequacy of the data for factor analysis was scrutinized using the Kaiser-Meyer-Olkin (KMO) parameter and the Bartlett sphericity test (Kleinbaum, 2013). The reliability of the scale was gauged using Cronbach's coefficient α serving as the reliability measurement index (Tavakol and Dennick, 2011). To verify the scale structure, confirmatory factor analysis was conducted (Brown, 2015), assessing the structural validity of the scale using Composite Reliability and Average Variance Extracted to test combined reliability and convergent validity, respectively. Finally, based on sample 2, content validity was reevaluated.
3 Results
3.1 Expert assessment of the initial scale
In this study, seven experts were invited to inspect and analyze the survey scale that was designed and compiled in advance. The evaluation criteria used by the experts are outlined in Table 2. According to the guidelines, when the number of expert evaluations exceeds six, the I-CVI value should be >0.78 (Fleiss et al., 2013). After statistically summarizing the evaluations provided by the experts, items with I-CVI values lower than 0.78 in the initial scale were deemed inadequate and subsequently removed. The remaining items that met the requirements I-CVI criteria were retained.
Table 2. Expert evaluation results of the initial scale.
Based on expert feedback, inappropriate items were removed. The qualified and reasonable scale items were compiled into a test scale, resulting in a preliminary measurement scale that demonstrated expert validity. The preliminary measurement scale was then evaluated by experts, and items such as items 4, 6, 7, 8, 9, 10, 12, 16, 18, 20, 21, 23, and 24, which had low I-CVI values 0.78 or below, were excluded. The remaining 15 items were retained for further analysis.
3.2 Item analysis
After the evaluation by experts, the original 28 items of the scale were reduced to 15 items. In sample 1, which consisted of the 502 valid adolescent questionnaires, the average score for each adolescent's family environment factor was calculated based on the scoring method using the 15-items pre-test scale. The total scores of all subjects were ranked in ascending order. The low group was defined as the material information below 27%, the middle group as the data between 27% and 73%, and the high group as the data above 73% (Kelley, 1939).
Independent samples t-test were conducted to determine if there were significant differences between the high and low groups. Table 3 presents the analysis results of the family environment factor subscale items. The family environment factor subscale was analyzed using the critical ratio analysis method based on various indicators. The score for the first 27% was 147, while the score for the last 27% is 139. After conducting the resolution coefficient test and t-test, items with t-values > 3 and P < 0.001 were retained. As a result, item Q29 was eliminated, and the scale was reduced to 15 items.
Table 3. Inspection results of scale items.
3.3 Exploratory factor analysis and optimization of the scale
The study first tested the suitability of the remaining 15 items related to family environment factors for factor analysis. The Kaiser-Meyer-Olkin (KMO) value was found to be 0.916, which is >0.8, indicating that the variables are suitable for factor analysis. The Bartlett's sphericity test yielded an approximate chi-square value of 4,704.563 with a significance of 0.000, meeting the significance level (P < 0.05) (Table 4). These results suggest that the items are not independent and that there are common factors present in the overall correlation matrix, supporting the suitability of factor analysis for the “Chinese Adolescents' Physical Activity Habit Formation Scale: Family Environmental Influencing Factors.”
Table 4. Kaiser-meyer-olkin test and bartlett sphericity test.
Principal component analysis was conducted to extract common factors with eigenvalues >1, and items with factor loadings exceeding 0.5 were retained. The exploratory factor analysis results in Table 5 indicate that each item's communalities are higher than 0.4, indicating effective extraction of research item information. Through this process, a total of three factors were obtained, each with eigenvalues >1. The variance explanation by these three factors after rotation was 25.938%, 23.747%, and 20.410%, respectively, with a cumulative variance explanation of 25.938%, 49.686% %, and 70.096%. These factors effectively capture the relevant information. The optimized scale consists of 15 items, which were categorized into three factors.
Table 5. Results of exploratory factor analysis.
Factor 1 comprises 6 items (Q1, Q2, Q3, Q4, Q5, and Q6) that reflect family members' support, encouragement and rewards, and it is named “Family Environment Construction” (FEC). Factor 2 consists of 5 items (Q7, Q8, Q9, Q10, and Q11) that primarily reflect the parents' healthy lifestyle and their recognition of healthy behaviors, leading to its naming as “Family Action Support” (FAS). Factor 3 includes 4 items (Q12, Q13, Q14, and Q15) that reflect family-related information on physical activity, goal planning, and the creation of physical activity space, thus termed “Family Health Awareness” (FHA).
3.4 Reliability analysis of scale content
As shown in Table 6, presents the results of the internal consistency analysis of the measured data. The Cronbach α values for the three dimensions “FEC,” “FAS,” and “FHA” are 0.894, 0.890, and 0.894, respectively. The Cronbach α value of the overall scale is 0.914. These values indicate high reliability, as each dimension and the total scale surpass the recommended threshold of 0.8. Furthermore, the overall scale demonstrates excellent reliability with a value exceeding 0.9. These findings indicates that the “Chinese Adolescents' Physical Activity Habit Formation Scale: Family Environmental Influencing Factors” is reliable and effectively captures the family environment factors that influence the development of physical activity habits among adolescents.
Table 6. Reliability analysis results of the scale based on sample 1.
Primarily, with the application of Cronbach α, the corrected item-total correlation (Corrected Item-Total Correlation, CITC) and the Cronbach's α coefficient after item deletion (Cronbach's Alpha if Item Deleted, CAID) to determine the structure and dimensions of the research. The reliability was quantified, and Table 7 indicates the results of the reliability analysis based on sample 2. It shows that the CITC value of each measurement item is >0.4, the CAID value is lower than the Cronbach's α coefficient of the corresponding variable, the Cronbach's α of FEC, FAS, and FHA is higher than 0.7, and the total Cronbach's α coefficient of the scale is 0.915. The analysis results indicate that the family environment factor and its dimensions have high reliability. This demonstrates that the actual situations of the selected samples are relatively stable and consistent.
Table 7. Reliability analysis results of the scale based on sample 2.
3.5 Confirmatory factor analysis of the scale
The validity of the research structure and its dimensions was assessed through Confirmatory Factor Analysis (CFA) (Wu, 2010). The results of confirmatory factor analysis, as shown in Table 8, indicate a good fit with χ2 = 126.175, df = 87, χ2/df = 1.45, RMSEA = 0.03, SRMR = 0.027, CFI = 0.991, TLI = 0.989. These indices meet the fitting requirements established by Hu and Bentler (1999). The χ2/df value falls within an acceptable range below 5 (Bentler and Bonett, 1987). In this study, suggesting that the first-order 3-factor confirmatory factor analysis model adequately represents the home environment based on the data. Therefore, the confirmatory factor model demonstrates a sound structure.
Table 8. Results of confirmatory factor analysis.
The standardized factor loading of the items ranged from 0.667 to 0.849, and the composite reliability (CR) value for each variable exceed 0.7. These findings indicate that all variables analyzed exhibited desirable composite reliability. Additionally, the average variance extracted (AVE) of each variable exceeds 0.5, indicating good convergent validity. In summary, the family environment factor and its dimensions demonstrated good reliability and validity in this study.
3.6 Test-retest reliability
In this study, we surveyed a sample of 56 high school students using the Chinese Youth Activity Habit Formation Scale. To prevent the results of the initial test from affecting the second test, we introduced a 2-week interval between the pre-test and post-test. The retest reliability coefficient ranged from 0.79 to 0.84, and the correlation coefficients for the three dimensions were 0.832, 0.863, and 0.832, respectively. All these coefficients surpassed 0.7, with an overall coefficient of 0.890. The retest correlation coefficients of the scale meet the necessary criteria, confirming that the reliable retest reliability of Chinese Adolescents' Physical Activity Habit Formation Scale: Family Environmental Influencing Factors is reliable and fulfills the retest requirements.
4 Discussion
4.1 Results interpretation
Existing studies have predominantly concentrated on family factors influencing adolescents' physical activity. For instance, research have delved into the impact of parental behaviors, such as role modeling (Madsen et al., 2009; Yao and Rhodes, 2015) and parental support (Edwardson et al., 2013; Langer et al., 2014) on youth activity levels. Other have investigated the effects of the family's physical home environment on adolescent behaviors (Trost et al., 2003; Spurrier et al., 2008). However, there has been limited theoretical discussion and few studies exploring factors within the family environment that contribute to the development of adolescents' physical activity habits.
The findings of this study make several notable contributions by identifying three key family environment factors influencing Chinese adolescents' physical activity habits: Family Environment Construction (FEC), Family Action Support (FAS), and Family Health Awareness (FHA). The identification of these specific elements provides new evidence that aspects of the family environment play a crucial role in shaping activity patterns during adolescence. Family Environment Construction (FEC) appears to be a particularly relevant factor in China, possibly due to the cultural emphasis on parental management of children's time. Furthermore, Family Environment Construction (FEC) was found to impact activity time, type, space and interests, aligning with previous literature that illustrates the multifaceted influences of the family environment on youth behaviors (McIver et al., 2009). Family Action Support (FAS) positively predicted physical activity, aligning with previous research that indicates family support enhances adolescent self-efficacy, facilitating participation (Quarmby and Dagkas, 2010; Dai and Chen, 2019). This underscores the necessity for interventions aimed at enhancing parental support. Moreover, results from Family Health Awareness (FHA) revealed that parental modeling positively influenced adolescents' activity levels (Ren et al., 2012; Sigmundová et al., 2014), highlighting the necessity for widespread public health messaging regarding parental impacts. Overall, these findings underscore the family environment's role as a key determinant of healthy physical activity habits during adolescence in China, while also suggesting cultural variations in the relative strength of specific family influence factors.
To address the limitations of using foreign-related scales in measuring family environment factors influencing the formation of physical activity habits, this study focuses on addressing issues such as poor measurement relevance and a failure to capture the key elements affecting habit formation. Drawing on classic questionnaires and scales from both domestic and international sources, this study developed a localized “Chinese Adolescents' Physical Activity Habit Formation Scale: Family Environmental Influencing Factors.”
While the scale development process was rigorous, a key innovation lies in the cultural specificity tailored to Chinese adolescents, differentiating it from existing family influence scales. For instance, Western scales often emphasize adolescent autonomy (Chai et al., 2018), while this scale captures Chinese cultural values such as filial piety (Peng and Li, 2023) and parental authority over play time (Deng et al., 2022). The localized conceptualization enhances the validity of measuring family dynamics influencing physical activity behaviors among Chinese youth.
The scale development process was both rigorous and comprehensive. It drew on previous research findings, used the Harman single-factor test to assess common method bias, conducted item analysis to test item discrimination, explored and optimized the scale's structure, and employed Cronbach's α as a reliability measurement index. The scale's structure was further validated through confirmatory factor analysis, and CR and AVE were used to assess the scale's reliability and validity, respectively.
This study systematically refined the initial scale, measuring family environmental influences on physical activity among Chinese adolescents. Expert advice was incorporated to optimize the questionnaire, enhancing its precision. Refinements involved consolidating related factors, revising dimensions, and eliminating items through rigorous statistical testing and expert review. Specifically, factors related to activity space design and atmosphere creation were combined into “space atmosphere creation.” The initial 28 items were reduced after an evaluation process that included content validation by experts and subsequent statistical analysis. Items such as Q4, Q6, Q16, and Q23 were eliminated due to inadequate relevance based on an item-CVI threshold. Q29 was deleted due to poor discrimination between respondent groups. This iterative refinement process ensured that only the most valid and reliable items were retained. Specifically, items with I-CVI scores below 0.78 were eliminated to retain the most pertinent survey questions. The remaining items then underwent additional evaluation of discrimination, reliability, and validity, resulting in the removal of any that did not meet psychometric standards. This rigorous scale development methodology focused on refining the initial family environmental influences scale through expert input and statistical testing. The adjustments successfully optimized item content and dimension structure while eliminating inadequate components. This systematic approach resulted in a 15-item scale demonstrating strong psychometric properties.
This study developed a culturally-adapted scale assessing family environmental influences on Chinese adolescents' physical activity through a rigorous multiphase process involving expert reviews and statistical optimization. The methodology ensured retention of only the most valid and reliable items, resulting in a precise, highly reliable 15-item scale tailored to the Chinese context, as shown in Table 9. This newly developed scale makes important theoretical contributions by filling a significant research gap—the prior lack of quantitative models customized to assess family environment influences specific to Chinese adolescents. Availability of a validated tool tailored to the Chinese context represents an essential advancement, enabling more rigorous investigation of culturally-specific familial factors affecting youth physical activity. Practically, the scale provides an empirical foundation to inform the development of culturally-appropriate family-based interventions aimed at modifying key environment elements to promote healthy adolescent activity habits.
Table 9. Formal scale.
In conclusion, the rigorous methodology undertaken to develop and optimize this culturally-adapted scale, coupled with its enhanced precision and reliability, represents an important contribution. The scale will allow deeper investigation of Chinese familial determinants shaping youth activity patterns. Additionally, findings generated can inform family-focused intervention strategies to promote healthy adolescent physical activity behaviors in China.
4.2 Limitations and areas for future research
In this study, it is crucial to acknowledge certain limitations. Firstly, despite conducting a thorough review and inclusion of item sources during the formation of the item pool, with a concerted effort to encompass a wide range of potential family factors, some items were still excluded based on expert evaluation, potentially resulting in the oversight of certain assessment details. Therefore, it is imperative to recognize the significance of further enhancing the scale's specificity and intricacy in future research, building upon the foundation established in this study.
Secondly, while our comprehensive survey covered multiple cities across diverse regions of China, validating the universality and efficacy of the scale, there is still room for expanding the sample size. Obtaining a more diverse range of samples would contribute to further confirming the scale's applicability.
Thirdly, given the focus of our study on the specific Chinese context, congruent with Chinese policy and cultural background, potential limitations might arise concerning the scale's practicality in other cultural and national contexts.
Notwithstanding these limitations, the scale holds substantial research value in terms of fostering localization and comprehensiveness, aligning seamlessly with the initial objectives. It represents the most extensive scale developed to date for assessing the impact of family environmental factors on the formation of physical activity habits among Chinese adolescents. Consequently, our scale provides invaluable insights into the cultivation of physical activity levels among Chinese adolescents.
5 Conclusion
In conclusion, this study developed and validated the “Chinese Adolescents' Physical Activity Habit Formation Scale: Family Environmental Influencing Factors,” comprising three key factors: “Family Environment Construction” (FEC), “Family Action Support” (FAS), and “Family Health Awareness” (FHA). Reliability and validity analysis indicate this scale provides an objective and effective tool to measure family environmental influences on adolescent physical activity habits.
In summary, the development and validation of the “Chinese Adolescents' Physical Activity Habit Formation Scale: Family Environmental Influencing Factors” represents a significant advancement for research on family determinants of physical activity and wellbeing among Chinese youth. The availability of a reliable and valid scale tailored to the Chinese adolescent population will enable a more robust quantitative investigation into how family environmental factors, unique to the Chinese cultural context, shape physical activity habits. This culture-specific tool can inform targeted interventions involving Chinese families, schools, and communities to promote participation in regular physical activity among adolescents, with significant implications for improving youth wellbeing at the national level in China. Overall, the scale provides an essential culturally grounded tool for deepening understanding and improving key family-level determinants of healthy adolescent development in China.
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Ethics statement
This study has been reviewed and approved by the Ethics Committee of East China Normal University (HR 476-2020). The studies were conducted in accordance with local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants' legal guardians/next of kin.
Author contributions
XZ, JY, WZ, and XF contributed to the conception and design of the study. JY and XF were involved in implementing the study and data collection. XZ undertook data analysis and wrote the first draft of the manuscript. XZ, JY, and WZ polished and revised the draft. All authors contributed to the article and approved the submitted version.
Funding
This study was funded by the 2023 Youth Fund for Humanities and Social Science Research of the Ministry of Education, research title: “Model Construction and Empirical Research on Influencing Factors of physical Activity Habit Formation of Chinese Adolescents” (Project No. 23XJC890048).
Acknowledgments
The authors thank all the participants who made this study possible.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Adkins, M., Bice, M. R., Heelan, K., and Ball, J. (2017). Enhancing physical education with a supplemental physical activity program. J. Phys. Educ. Recreat. Dance 88, 28–34. doi: 10.1080/07303084.2017.1356765
Álvarez Muñoz, J. S., and Hernández Prados, M. Á. (2023). Types of family leisure activities in families with adolescents. J. Family Issues 10, 0192513X221150995. doi: 10.1177/0192513X221150995
Bandura, A. (1986). Social foundations of thought and action: a social cognitive theory. Englewood Cliffs [Preprint]. Available at: https://cir.nii.ac.jp/crid/1570854174839355904 (accessed December 15, 2023).
Bauer, K. W., Nelson, M. C., Boutelle, K. N., and Neumark-Sztainer, D. (2008). Parental influences on adolescents' physical activity and sedentary behavior: longitudinal findings from Project EAT-II. Int. J. Behav. Nutr. Phys. Activ. 5, 12. doi: 10.1186/1479-5868-5-12
Bentler, P. M., and Bonett, D. G. (1987). Citation-classic-significance tests and goodness of fit in the analysis of covariance-structures. Curr. Contents/Soc. Behav. Sci. 37, 16–16.
Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research. Second Edition. London: Guilford Publications.
Cao, G., and Tan, X. (2021). The study on the process of adolescents' adolescent - parent conflict regarding schoolwork. Youth Stud. 3, 82–93.
Chai, H. Y., Niu, G. F., Chu, X. W., Wei, Q., Song, Y. H., and Sun, X. J. (2018). Fear of missing out: what have I missed again? Adv. Psychol. Sci. 26, 527. doi: 10.3724/SP.J.1042.2018.00527
Chu, X., and Xiao, H. (2020). Teenager physical exercise habit formation influencing factor model establishment and analysis. J. Phys. Educ. 27, 116–123. doi: 10.16237/j.cnki.cn44-1404/g8.2020.03.018
Cleland, V., Timperio, A., Salmon, J., Hume, C., Telford, A., and Crawford, D. (2011). A longitudinal study of the family physical activity environment and physical activity among youth. Am. J. Health Promot. 25, 159–167. doi: 10.4278/ajhp.090303-QUAN-93
Costello, A., and Osborne, J. (2019). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Pract. Assess. Res. Eval. 10, 7. doi: 10.7275/jyj1-4868
Dai, J., and Chen, H. (2019). An social ecological perspective of analyzing factors influencing Chinese adolescents' in-school physical activity levels. J. ShangHai Univ. Sport 43, 85–91. doi: 10.16099/j.sus.2019.03.013
Deng, J., Lv, Z., Long, Z., Liu, T., and Lu, Y. (2022). Parental educational expectations and adolescents' perceived academic stress: moderating role of physical activity. J. Phys. Educ. 38, 37–45. doi: 10.16419/j.cnki.42-1684/g8.2022.05.009
Do, B., Lopez, N. V., Dunton, G. F., and Mason, T. B. (2023). Motivational and self-regulatory processes associated with weight-related parenting behaviors. Obesity Pillars 5, 100049. doi: 10.1016/j.obpill.2022.100049
Du, Y. (2013). Studies on the cultivation of the adolescent physical exercise habit—taking Yantai city as an example. Master Dissertation. Ludong University.
Edwardson, C. L., Gorely, T., Pearson, N., and Atkin, A. (2013). Sources of activity-related social support and adolescents' objectively measured after-school and weekend physical activity: gender and age differences. J. Phys. Activ. Health 10, 1153–1158. doi: 10.1123/jpah.10.8.1153
Fleiss, J. L., Levin, B., and Paik, M. C. (2013). Statistical Methods for Rates and Proportions. New York, NY: John Wiley and Sons.
Godin, G. (1994). “Social-cognitive models,” in Advances in Exercise Adherence, ed. R. K. Dishman (Champaign, IL, England: Human Kinetics Publishers) 113–136.
Golan, M., Kaufman, V., and Shahar, D. R. (2006). Childhood obesity treatment: targeting parents exclusively v. parents and children. Br. J. Nutr. 95, 1008–1015. doi: 10.1079/BJN20061757
Henry, B. W., Smith, T. J., and Ahmad, S. (2014). Psychometric assessment of the: measuring parents' views on food and behavior and attitudes questionnaire for healthy habits physical activity. Public Health Nutr. 17, 1004–1012. doi: 10.1017/S136898001200554X
Hu, L., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equat. Model. 6, 1–55. doi: 10.1080/10705519909540118
Hu, S., and Cai, D. (2023). Development of perceived family support and positive mental health in junior high school students: a three-year longitudinal study. J. Early Adolesc. 43, 216–243. doi: 10.1177/02724316221101534
Hu, Y. (2017). Construction and application of evaluation index system of exercise and fitness of children and youth in China. Ph.D. Dissertation. Shanghai University of Sport.
Hunt, P., Barrios, L., Telljohann, S. K., and Mazyck, D. (2015). A whole school approach: collaborative development of school health policies, processes, and practices. J. School Health 85, 802–809. doi: 10.1111/josh.12305
Joosse, L., Stearns, M., Anderson, H., Hartlaub, P., and Euclide, J. (2008). Fit kids/fit families: a report on a countywide effort to promote healthy behaviors. Wisconsin Med. J. 107, 231.
Kelley, T. L. (1939). The selection of upper and lower groups for the validation of test items. J. Educ. Psychol. 30, 17–24. doi: 10.1037/h0057123
Kim, D. H., Kang, I. S., and Lee, S. (2007). Social support, self-concept and self-efficacy as correlates of adolescents' physical activity and eating habits. J. Korean Acad. Family Med. 28, 292–301.
Kim, M., Mallory, C., and Valerio, T. (2020). Statistics for Evidence-Based Practice in Nursing. Burlington, MA: Jones and Bartlett Learning.
Kleinbaum, D. G. (2013). Applied Regression Analysis and Other Multivariable Methods. Fifth edition. Boston, MA: Cengage Learning.
Korom, B., Malloy, M., Remmers, C., Cevilla, M., Dione, K., Papanek, P., et al. (2023). “It's about being healthy”; a novel approach to the socio-ecological model using family perspectives within the Latinx community. BMC Public Health 23, 1–10. doi: 10.1186/s12889-023-15005-2
Kuo, J., Voorhees, C. C., Haythornthwaite, J. A., and Young, D. R. (2007). Associations between family support, family intimacy, and neighborhood violence and physical activity in urban adolescent girls. Am. J. Public Health 97, 101–103. doi: 10.2105/AJPH.2005.072348
Langer, S. L., Crain, A. L., Senso, M. M., Levy, R. L., and Sherwood, N. E. (2014). Predicting child physical activity and screen time: parental support for physical activity and general parenting styles. J. Pediatr. Psychol. 39, 633–642. doi: 10.1093/jpepsy/jsu021
Li, J., and Liang, S. (2020). Development and validation of the adolescent physical activity promoting factor scale—grounded theory construction based on the “three non-disconnection models of family-school-community”. J. Sports Sci. 41, 84–103. doi: 10.13598/j.issn1004-4590.2020.01.027
Lin, J. (2019). Research on the characteristics and development mechanism of learning interests in physical education. Ph.D. Dissertation. Northeast Normal University.
Liu, Y. (2023). A study on the influence parents' physical behavior and pupils' participation in sports. J. Jilin Sport Univ. 39, 96–108. doi: 10.13720/j.cnki.22-1286.2023.03.012
Lv, H., Wang, K., and Liu, H. (2020). Family sports environment and young children's physically active lifestyle: the mediating role of family social capital. J. Beijing Sport Univ. 43, 77–88. doi: 10.19582/j.cnki.11-3785/g8.2020.05.008
Madsen, K. A., McCulloch, C. E., and Crawford, P. B. (2009). Parent modeling: perceptions of parents' physical activity predict girls' activity throughout adolescence. J. Pediatr. 154, 278–283.e2. doi: 10.1016/j.jpeds.2008.07.044
McIver, K. L., Brown, W. H., Pfeiffer, K. A., Dowda, M., and Pate, R. R. (2009). Assessing children's physical activity in their homes: the observational system for recording physical activity in children-home. J. Appl. Behav. Analy. 42, 1–16. doi: 10.1901/jaba.2009.42-1
McMurray, R. G., Bradley, C. B., Harrell, J. S., Bernthal, P. R., Frauman, A. C., and Bangdiwala, S. I. (1993). Parental influences on childhood fitness and activity patterns. Res. Quart. Exer. Sport 64, 249–255. doi: 10.1080/02701367.1993.10608809
Moreno, J. P., Kelley, M. L., Landry, D. N., Paasch, V., Terlecki, M. A., Johnston, C. A., et al. (2011). Development and validation of the family health behavior scale. Int. J. Pediatr. Obes. 6, e480–486. doi: 10.3109/17477166.2011.575148
Mota, J. (1998). Parents' physical activity behaviors and children's physical activity. J. Hum. Move. Stud. 2, 89–100.
Nakahori, N., Sekine, M., Yamada, M., and Tatsuse, T. (2016). The relationship between home environment and children's dietary behaviors, lifestyle factors, and health: super food education school project by the japanese ministry of education, culture, sports, science and technology. Japanese J. Public Health 63, 190–201. doi: 10.11236/jph.63.4_190
Peng, J., and Li, N. (2023). Controlling parenting style: historicalevolution, generative logic and crack path. Renmin Univ. China Educ. J. 3, 153–165.
Polit, D. F., and Beck, C. T. (2006). The content validity index: Are you sure you know what's being reported? Critique and recommendations. Res. Nurs. Health 29, 489–497. doi: 10.1002/nur.20147
Qiao, Y. (2011). Forming mechanism and affecting factors of exercising habits of teenagers. J. Phys. Educ. 18, 87–94. doi: 10.16237/j.cnki.cn44-1404/g8.2011.03.023
Quarmby, T., and Dagkas, S. (2010). Children's engagement in leisure time physical activity: exploring family structure as a determinant. Leisure Stud. 29, 53–66. doi: 10.1080/02614360903242560
Raykov, T., and Marcoulides, G. A. (2011). Introduction to Psychometric Theory. London: Routledge. doi: 10.4324/9780203841624
Ren, J., Ping, J., Shu, S., Yang, Y., and Dai, J. (2012). Building of physical and health education model of adolescent and intervention strategies —based on a survey of primary and secondary students in Shanghai. China Sport Sci. 32, 31–36. doi: 10.16469/j.css.2012.09.006
Rhodes, R. E., Berry, T., Faulkner, G., Latimer-Cheung, A. E., O'Reilly, N., Tremblay, M. S., et al. (2019). Application of the multi-process action control framework to understand parental support of child and youth physical activity, sleep, and screen time behaviours. Appl. Psychol. 11, 223–239. doi: 10.1111/aphw.12150
Roque Garay, A. (2018). Promoción de estilos de vida saludable en el entorno familiar. Nutr. Clin. Dietet. Hospit. 4, 183–188. doi: 10.12873/374roquegaray
Sallis, J. F., and Hovell, M. F. (1990). Determinants of exercise behavior. Exer. Sport Sci. Rev. 18, 307. doi: 10.1249/00003677-199001000-00014
Sigmundová, D., Sigmund, E., Vokáčová, J., and Kopková, J. (2014). Parent-child associations in pedometer-determined physical activity and sedentary behaviour on weekdays and weekends in random samples of families in the Czech Republic. Int. J. Environ. Res. Public Health 11, 7163–7181. doi: 10.3390/ijerph110707163
Spurrier, N. J., Magarey, A. A., Golley, R., Curnow, F., and Sawyer, M. G. (2008). Relationships between the home environment and physical activity and dietary patterns of preschool children: a cross-sectional study. Int. J. Behav. Nutr. Phys. Activity 5, 1–12. doi: 10.1186/1479-5868-5-31
Tavakol, M., and Dennick, R. (2011). Making sense of Cronbach's alpha. Int. J. Med. Educ. 2, 53–55. doi: 10.5116/ijme.4dfb.8dfd
Taylor, W. C., Baranowski, T., and Sallis, J. F. (1994). “Family determinants of childhood physical activity: a social-cognitive model,” in Advances in Exercise Adherence, ed. R. K. Dishman (Champaign, IL, England: Human Kinetics Publishers) 319–342.
Tenjin, K., Sekine, M., Yamada, M., and Tatsuse, T. (2020). Relationship between parental lifestyle and dietary habits of children: a cross-sectional study. J. Epidemiol. 30, 253–259. doi: 10.2188/jea.JE20190015
Timperio, A. F., van Stralen, M. M., Brug, J., Bere, E., Chinapaw, M. J. M., De Bourdeaudhuij, I., et al. (2013). Direct and indirect associations between the family physical activity environment and sports participation among 10–12 year-old European children: testing the EnRG framework in the ENERGY project. Int. J. Behav. Nutr. Phys. Activ. 10, 1–10. doi: 10.1186/1479-5868-10-15
Trost, S. G., Sallis, J. F., Pate, R. R., Freedson, P. S., Taylor, W. C., and Dowda, M. (2003). Evaluating a model of parental influence on youth physical activity. Am. J. Prev. Med. 25, 277–282. doi: 10.1016/S0749-3797(03)00217-4
van Sluijs, E. M., Ekelund, U., Crochemore-Silva, I., Guthold, R., Ha, A., Lubans, D., et al. (2021). Physical activity behaviours in adolescence: current evidence and opportunities for intervention. Lancet 398, 429–442. doi: 10.1016/S0140-6736(21)01259-9
Wang, K. (2011). A study of conceptual model,evaluation methods and educational intervention of physical exercise habits of college students. Ph.D. Dissertation. East China Normal University.
Weng, M. (2015). Research on the habits of physical exercise of middle school students in china – taking Hainan province as an example. Ph.D. Dissertation. Shaanxi Normal University.
Whooten, R., Horan, C., Aguirre, A., Dartley, A. N., and Taveras, E. (2023). Parent and pediatrician perspectives on physical activity promotion in pediatric primary care: a preliminary mixed methods study. Am. J. Health Promot. 37, 65–76. doi: 10.1177/08901171221113317
World Health Organization (2022). Physical activity. Available online at: https://www.who.int/news-room/fact-sheets/detail/physical-activity (accessed November 12, 2023).
Wu, M. (2010). Questionnaire Statistical Analysis Practice - SPSS Operation and Application. Chongqing: Chongqing University Press.
Xie, Y., Fang, Y., and Wang, H. (2004). Current situation and speculation of sport exercise habit. Shandong Sports Sci. Technol. 1, 42–44. doi: 10.14105/j.cnki.1009-9840.2004.01.016
Xie, Y., Shi, Z., Yin, L., and Lan, L. (2022). A meta-analysis of the relationships between Chinese parenting styles and child academic achievement. Best Evid. Chinese Educ. 12, 1589–1595. doi: 10.15354/bece.22.ab009
Yao, C. A., and Rhodes, R. E. (2015). Parental correlates in child and adolescent physical activity: a meta-analysis. Int. J. Behav. Nutr. Phys. Activ. 12, 10. doi: 10.1186/s12966-015-0163-y
Zhao, J., and He, J. (2023). Values, dilemmas and strategies of parents'participation in children's family sports. J. Shenyang Sport Univ. 42, 62–68.
Keywords: Chinese adolescents, physical activity habit, family environment, scale development, factor analysis
Citation: Zhang X, Yan J, Zhu W and Fu X (2024) Development and validation of the Chinese family environment influencing physical activity habits scale. Front. Psychol. 14:1243658. doi: 10.3389/fpsyg.2023.1243658
Received: 21 June 2023; Accepted: 18 December 2023;
Published: 16 January 2024.
Edited by:
Chong Chen, Yamaguchi University Graduate School of Medicine, JapanReviewed by:
Ragna Stalsberg, Norwegian University of Science and Technology, NorwayJin Yan, The University of Newcastle, Australia
Copyright © 2024 Zhang, Yan, Zhu and Fu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Weiqiang Zhu, zwq223tyxx@163.com
†These authors have contributed equally to this work and share first authorship