Introduction

Due to the rapid development of the internet, social media has become deeply embedded in every aspect of life, altering users’ habits in how they receive information. It has become the primary online social platform and information source for the general public, particularly among teenagers.Adolescents growing up in the Internet era exhibit both deep integration with and strong dependency on social media. As early as 2013, approximately 70% of adolescents aged 14–18 reported that they used social media on a daily basis. By 2018, 45% of adolescents indicated that they were online almost constantly1. Their health is profoundly shaped by their online behaviors, and digital media has effectively become a primary platform through which adolescents acquire sports-related knowledge and skills.

Adolescence is a critical stage of human development. As a unique group, adolescents are still in the process of developing their physical functions and cognitive patterns, and have not yet established stable self-management mechanisms, particularly in terms of physical exercise.Most adolescents demonstrate low intrinsic motivation to engage in physical activity and insufficient skills in planning and regulating exercise behavior. Such insufficient physical activity may contribute to an increased risk of obesity, reduced cardiopulmonary fitness, weakened immune function, and a greater susceptibility to negative emotional states2. If we can guide them to establish systematic exercise routines through social media and other methods that interest them during this stage, it will not only help them build strong bodies, but also cultivate lifelong health management skills, laying a solid foundation for their future development. Currently, the physical health of Chinese adolescents is not optimistic, with overall physical fitness being poor3. Behavioural and lifestyle factors, as well as reduced physical activity, are direct causes4.However, adolescents are characterized by a strong preference for novelty and a high capacity for adaptability5. Consequently, they can quickly align with contemporary social and technological trends, and the rapid development of social media has offered them increasingly diverse opportunities for engagement beyond the academic context.However, the dissemination of social media content also has negative, pessimistic, and misleading aspects. Young people’s ability to distinguish right from wrong is not yet mature, making them susceptible to external influences and prone to engaging in inappropriate behaviour, which poses a significant challenge to sports and health education for young people. Therefore, developing a questionnaire on social media sports content production is of great significance for assessing the sports and health levels of young people.

Previous studies on adolescent physical health have primarily adopted macro or meso-level perspectives, focusing on conceptual frameworks, content systems, influence mechanisms, and questionnaire measurements, with an emphasis on the role of external environments in promoting adolescent physical health. For example, Janssen analysed the relationship between adolescent physical activity and fitness health and conducted a literature review on the health benefits of adolescent physical exercise6. Rodríguez established a health knowledge system for adolescent athletes and conducted a qualitative analysis of the health learning process among adolescent athletes7. Yang Yangguo constructed a multi-dimensional indicator system for promoting physical health among children and adolescents in China and used the analytic hierarchy process to measure the weights of each indicator8. Sun Hao employed a mixed-methods approach to reveal the mechanisms through which social media influences adolescent physical behaviour9. Lee developed a questionnaire on sports values for adolescents to identify and guide the value standards for sports behaviour among adolescent athletes10. Overall, research on youth sports health promotion in the context of social media remains limited. Further exploration is needed into how social media content production promotes youth participation in physical exercise and enhances health, and in which specific areas this occurs. One of the functions of social media content production is to promote youth sports health behaviour, but currently there is no established measurement or evaluation tool for social media sports content production.

Based on this, this study focuses on adolescents and has developed the first questionnaire on social media sports content production among adolescents. This provides a valuable tool for further research on social media ‘sports content production’ among adolescents and the relationship between social media content production and the promotion of adolescent sports health. It offers substantive recommendations for promoting adolescent sports health, provides a theoretical basis for the production and improvement of social media and sports content, thereby enhancing the influence of sports health information on the sports health behaviour of adolescent groups and increasing their enthusiasm for participating in physical exercise.

Concept definition and research procedure

Concept definition

Social media, also known as socialised media or social media, is an interactive Web 2.0 application based on the Internet. It is a relationship-based content production and interaction platform used to share views, opinions, insights and experiences. Its characteristics include a large number of users and spontaneous dissemination11.

Content production is an Internet term that refers to the creation of content on a platform. Depending on the type of content, it can be divided into user-generated content (UGC), professionally generated content (PGC), and occupationally generated content (OGC).

User-generated content (UGC) refers to content created and shared by users on the internet through collaborative and participatory modes, thereby exhibiting characteristics of participation and democratisation. Professional Content Generation (PGC) emerged earlier than UGC, with professional elites as the primary creators. The production process and content are highly specialised, characterised by strong quality control and stringent requirements for the creators’ knowledge background and professional qualifications. Occupational Content Generation (OGC) involves industry professionals with specific knowledge and expertise producing content in exchange for compensation.

The three content production methods are closely related yet distinctly different. Since OGC content is fee-based and difficult for adolescents to access, this study emphasises cost-effectiveness and accessibility for adolescents when using social media content production to promote adolescent physical health. Therefore, the content production methods primarily covered in this study are user-generated content (UGC) and professionally generated content (PGC).

Sports content production refers to the creation of content related to sports activities, including user-generated sports content and expert-produced sports-related content. Sports content production is an internet term referring to the systematic process of transforming sports-related elements such as sports events, sports culture, and fitness knowledge into disseminable media products through symbolic encoding, media technology, and organisational practices12. User-generated content production emphasises non-professional creation by users, such as videos, audio, text, and images related to sports that users create and publish online; expert-generated content production highlights the knowledge output of sports professionals, such as sports science popularisation authors and government Weibo accounts.

The social media sports content production referred to in this study is not the sharing of daily sports activities by ordinary users or the one-way dissemination of sports expertise by experts. It is not the traditional, generalised creation and dissemination of information, but rather specifically refers to interactive sports and health content production targeting adolescents (defined by the WHO as aged 10–19 years)13 on social media. Its core characteristics are as follows: at the subject level, it is a collaborative production network composed of sports enthusiasts, sports medicine experts, and health management institutions; in terms of functional orientation, it involves behaviour intervention content formed through data visualisation feedback (e.g., WeChat Sports rankings), community incentives (e.g., fitness challenges), and algorithm adaptation (e.g., personalised training plans).

Research procedure

Table 1 Basic information about the interviewed experts.
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Through preliminary literature review and reading, the questionnaire dimensions were determined based on previous relevant research. During the survey implementation phase, participants were identified for semi-structured interviews. After organising the interview results, the themes and concepts were further refined to finalise the open-ended questionnaire. The open-ended questionnaire was distributed offline, and the collected questionnaires were organised and summarised to determine the preliminary test questions. These were then submitted to professionals in communication studies and sports science for evaluation, followed by further revisions to finalise the preliminary test questionnaire, as detailed in Table 1. The preliminary test questionnaire was distributed, and after collection, the questions were edited according to the standard procedures for questionnaire development to create the final questionnaire.

Methodology

Literature review method

This paper uses keywords such as ‘social media sports content production,’ ‘social media,’ ‘social media interaction,’ and ‘sports content production’ to conduct Chinese literature searches through databases such as China National Knowledge Infrastructure (CNKI), Wanfang, and VIP; it also uses keywords such as ‘Social Media,’ ‘PGC,’ ‘UGC,’ and ‘PUGC’ to conduct literature searches through foreign databases such as PubMed, EBSCO, Elsevier, Web of Science, and PQDD. Additionally, the author utilised the school library’s resources to search for and review books and other literature.

By reviewing journal articles, theses, monographs, and other types of resources related to this study, we gained an understanding of the current state of research on social media content production, including the quantification of ‘content production’ and the development of relevant questionnaires. This provided insights and references for the development of the ‘Social Media Sports Content Production Questionnaire’ used in this study.

Interview method

Interview sample

Fifteen participants (M = 16.04 years old, SD = 1.53 years old) who were representative of the sample were selected for interviews. Among them, there were 8 males and 7 females.

Semi-structured interviews

Before the interview began, participants were informed of the interview duration, recording, and confidentiality matters. The interview was conducted according to the outline, lasting approximately 40 min, with the entire process recorded. The interview outline is provided in the appendix. A total of 15 interview subjects were selected for this interview, and the interview recordings were transcribed into text, amounting to approximately 20,000 words. Based on the interview results, it was determined that adolescents frequently use social media platforms such as QQ, WeChat, and Weibo to connect with others in their daily lives. In terms of social media content production related to sports, this can be divided into User-Generated Content (UGC) and Professional-Generated Content (PGC). In the UGC category, individuals share their exercise routines on these platforms, primarily through photos, videos, and inspirational captions. Interaction with others primarily occurs through QQ and WeChat chats, or by liking and commenting on posts in WeChat Moments. In terms of PGC, adolescents actively seek professional guidance, such as browsing videos and articles posted by sports bloggers on social media or using professional sports apps. The interview outline is shown in Table 2.

Table 2 Interview outline.
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Open-ended survey

Open-ended questionnaire sample

A survey was conducted on students from a certain secondary school in Tai’an City, aged between 10 and 19 (M = 17.04 years, SD = 1.24 years), with a total of 150 participants, including 62 males and 88 females.

Open-ended questionnaire survey

This open-ended questionnaire survey targeted adolescents aged 10–19 to collect more comprehensive information. The outline of the open-ended questionnaire is shown in Table 3. A total of 150 open-ended questionnaires were distributed and collected offline. After excluding two questionnaires from respondents aged 19 or older and two incomplete questionnaires, 146 valid questionnaires remained, resulting in an effective response rate of 97.3%. According to the results of this open-ended questionnaire survey, individuals with regular exercise habits tend to share their exercise records and achievements on social media, primarily in the form of videos, images, and text, and provide timely feedback on others’ exercise-related posts. They also have the habit of having regular exercise partners on social media. When encountering issues they cannot resolve on their own during exercise, they seek assistance from professionals or download specialised software. When watching professional instructional videos, individuals tend to aspire to become professional fitness bloggers or content creators, and are willing to invest their own funds to enhance their related knowledge.

Table 3 Outline of the open-ended questionnaire survey.
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Questionnaire question development

Through interviews and open-ended questionnaire surveys, the preliminary questions for the ‘Social Media Sports Content Production Questionnaire’ were compiled. Subsequently, the questions were submitted to professionals in the fields of communication studies, psychology, and sports science for evaluation. The evaluation criteria included whether the definitions were clear; whether there were any redundant questions; whether each question was concise and accurately reflected the theoretical framework; and whether the questions aligned with the different domains and dimensions. whether the item design covered all dimensions and factor classifications14. Based on the feedback from experts, we carefully revised, deleted and improved the problematic items, and finally formed the first version of the questionnaire on Social Media Sports Content Production (see Table 4), which contains 12 items. The questionnaire used a 5-point Likert scale (1 = completely disagree, 5 = completely agree), and all items were positive scoring, and no reverse scoring items were set to reduce the comprehension difficulty of the subjects and simplified the scoring process.

Table 4 Questionnaire on social media sports content production (preliminary version).
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Table 5 Social media sports content production questionnaire (final version).
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A questionnaire titled ‘Social Media Sports Content Production Questionnaire’ (this is the preliminary version) was distributed to 700 students from a certain middle school in Tai’an City. The participants were aged between 10 and 19 years old (M = 16.58 years, SD = 1.4 years), with 364 males and 336 females. A total of 680 questionnaires were returned. After handling missing values and outliers, 672 valid questionnaires were obtained, with a valid response rate of 96%. Following item analysis and exploratory factor analysis, the remaining items underwent confirmatory factor analysis and reliability and validity testing.

Through the questionnaire compilation process described above, questions were modified and added or deleted based on feedback, ultimately forming the ‘Social Media Sports Content Production Questionnaire’ (see Table 5) targeting adolescents, consisting of nine questions and two dimensions.

The research was reviewed and approved by Qufu Normal University, Jining, China, which confirmed that all procedures followed relevant ethical and regulatory guidelines.Written informed consent to participate in the study was obtained from all participants.

Results

Project analysis

The 672 valid questionnaires were randomly divided into two parts, 336 questionnaires were used for exploratory factor analysis and 336 questionnaires were used for validation factor analysis. The results of the exploratory factor analysis showed that Item 7 did not reach statistical significance between the low-score group and the high-score group (t = 2.15, p = 0.24). Therefore, Items 7 and 9 were removed. All remaining items (10 questions) demonstrated statistically significant differences between the low-score group and the high-score group (p < 0.01). The correlations between each item and the total score were calculated, and Item 8, which had a low total correlation (r < 0.3), was removed15. The final 336 questionnaires were used to conduct confirmatory factor analysis on the items obtained from the last exploratory factor analysis (9 items) to observe the model fit.

Exploratory factor analysis

To optimise the measurement items for the variables, exploratory factor analysis was conducted on the nine items in the preliminary version of the Social Media Sports Content Production Questionnaire.

Table 6 KMO and Bartlett’s test.
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First, Bartlett’s sphericity test and KMO test values were used to determine the suitability of the data for factor analysis. The results showed that KMO = 0.906, which is greater than 0.7, and Bartlett’s sphericity test value was significant (p < 0.001), indicating that the questionnaire data was suitable for factor analysis (see Table 6).

Secondly, principal component analysis was used for factor extraction, with common factors extracted based on eigenvalues greater than 1. Factor rotation was performed using oblique rotation with maximum variance for factor analysis, yielding the initial factor loading matrix (see Table 7). Inappropriate items were deleted based on the following four criteria: (1) items with factor loadings close to those of two or more common factors were deleted; (2) items with only one item under a common factor were deleted; (3) Items with the maximum loading on a common factor less than 0.3 should be deleted; (4) Items with factor loadings less than 0.4 should be deleted.

Table 7 Exploratory factor analysis factor loadings.
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Finally, based on the above criteria, exploratory factor analysis16 was conducted after each deletion, resulting in the removal of item 11, leaving a total of 9 items. Principal component analysis was performed on the remaining 9 items, identifying two common factors with eigenvalues greater than 1: UGC (items 1, 3, 5, 9, and 12) and PGC (items 2, 4, 6, and 10). The total explanatory power of the two common factors reached 68.433%, exceeding 50%, indicating that the two selected factors have good representativeness. The factor loadings are shown in the table below. The factor loadings for all measurement items are greater than 0.5, and the cross-loadings are all less than 0.4. Each item falls into the corresponding factor, indicating that the scale has good structural validity.

Confirmatory factor analysis

In order to further verify the fit between the actual model obtained and the conceptual model, a confirmatory factor analysis was conducted on the items obtained from the final exploratory factor analysis (9 items). The model fit was good. Details are shown in Table 8; Fig. 1.

Table 8 Fit of the confirmatory factor model.
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Fig. 1
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Analysis model of social media content production factors.

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As shown in Table 8, CMIN/DF is 4.352, which is less than the standard of 5. AGFI, GFI, NFI, TLI, IFI, and CFI all meet the standard of 0.9 or above. RMR is 0.024, which is less than 0.08, and RMSEA is 0.031, which is less than 0.08. All fit indices meet general research standards, so it can be concluded that this model has good fit.

Reliability analysis

Internal consistency reliability

Table 9 Internal consistency reliability analysis of social media sports content production.
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As shown in Table 9, the Cronbach’s Alpha coefficients for all variables exceed the standard of 0.7, indicating that the variables have good internal consistency reliability. The CITC values all exceed the standard of 0.5, indicating that the measurement items meet the research requirements. From the ‘Cronbach’s Alpha value after deleting the item,’ it can be seen that deleting any item will not cause an increase in the Cronbach’s Alpha value, which also indicates that the variables have good reliability.

Retest reliability

Table 10 Retest reliability test.
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Based on the principle of voluntariness, 65 participants in the initial sample were retested three weeks later to verify the reliability of the retest, ultimately yielding 62 valid questionnaires. A normality test was conducted on the retest data, with p > 0.05, indicating a normal distribution. The results of the retest reliability analysis showed a high degree of correlation between the two retest total scores (r = 0.792). For details, see Table 10.

Validity analysis

Content validity

The preliminary research was conducted in a thorough manner, involving a review and summary of relevant literature, semi-structured interviews, open-ended questionnaire surveys, and group discussions. The preliminary questionnaire items were submitted to experts for evaluation, and inappropriate items were removed to ensure that the questionnaire better reflected the social media content production status of adolescents, had good representativeness, and high content validity.

Structural validity

Table 11 Structural validity analysis.
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By calculating the total score of the Social Media Sports Content Production Questionnaire and the correlations between the total score and each dimension, as well as the correlations between the dimensions themselves, the structural validity analysis results showed that the correlations between the dimensions (r = 0.514) were smaller than the correlations between the dimensions and the total score (r = 0.861, r = 0.879), indicating that the questionnaire has good structural validity. For details, see Table 11.

Convergent validity

Table 12 Results of confirmatory factor analysis of social media sports content production.
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As shown in Table 12, the standardised factor loadings of all measurement indicators are greater than 0.6, the composite reliability (CR) is greater than 0.7, and the average variance extracted (AVE) is greater than 0.5, indicating that all variables have good convergent validity.

Discussion

Consistency and heterogeneity: interpretation of the findings and the existing literature

We have constructed a two-dimensional model (UGC and PGC), which is well aligned with current research trends in social media and health promotion. First, our findings are highly consistent with previous studies that emphasize the interactive and participatory nature of social media. Sun et al. (2024) reported that various forms of social interaction, such as posting, sharing, commenting, and participating in exercise check-ins, contribute to adolescents’ physical self-perception and self-concept development, thereby influencing their physical activity behaviors9. This finding aligns closely with the items included in the UGC dimension of our questionnaire, including “sharing exercise records,” “discussing exercise-related issues,” and “liking or commenting.”Moreover, in the PGC dimension, our study indicates that adolescents actively engage with fitness-related influencers and use professional exercise applications. This finding aligns with Wang (2023), who reported that physically active adolescents tend to acquire exercise skills through video-based social media platforms, providing mutual support for both sets of findings19.These convergent findings jointly highlight the potential of social media as a tool for physical health promotion among adolescents. Specifically, they demonstrate the shift from passive information acquisition to active, interactive behavioral engagement and cognitive construction, thereby strengthening the credibility of our conclusions.

However, some previous findings differ from or emphasize aspects that are not fully aligned with those of the present study. Rodríguez-Serrano et al. (2017) reported that adolescent athletes primarily rely on peer communication, social media, and online forums to acquire and calibrate health information, while exhibiting skepticism toward information from official or authoritative sources7. This discrepancy may reflect the specific characteristics of the study samples, as professional athletes differ fundamentally from the general adolescent population in their motives for sport participation, environmental contexts, and channels for obtaining knowledge.In contrast, our study focused on a broader population of ordinary middle school students. With limited experience and evaluative skills, these adolescents may demonstrate greater receptiveness to, and reliance on, systematic and specialized information provided by fitness content creators, professional exercise applications, and authoritative institutions. This partially explains why the PGC dimension emerged as an independent construct and could be effectively measured in our study.Furthermore, Fiedler et al. (2023) identified a potential association between digital media use and mental health risks among adolescent athletes21, which appears to contrast with the predominantly positive orientation of our findings. This divergence is likely attributable to differences in the content and nature of social media use. While Fiedler and colleagues focused on generalized media engagement, potentially including exposure to social comparison pressures or negatively valenced content, our study specifically targeted sport-related content production, a domain characterized by clear behavioral orientation and substantial potential for promoting health.

The findings of this study suggest that the effects of social media depend on the specific context of use and the quality of the content. In the future, if adolescents can be effectively guided to engage in constructive production and consumption of sport-related content, it may be possible to mitigate the potential risks associated with generalized social media use while simultaneously leveraging its positive effects.

Intersection and integration: the theoretical foundation of the ‘social media sports content production questionnaire’

The social media sports content production questionnaire developed in this study is primarily based on two layers of research findings. First, through research methods such as literature review, interviews, and open-ended surveys, the content structure of social media sports content production among adolescents was explored. Second, relevant research findings from the fields of social media and adolescent physical exercise were referenced.

Self-presentation theory posits17that individuals consciously manage their self-image in social environments to shape or maintain their identity. Personal perceptions of oneself often stem from others’ evaluations and one’s own perception of those evaluations. As social beings, positive self-presentation and self-image shaping can help individuals gain social capital within a group, a phenomenon particularly evident in sports, especially team and mass participation sports that take place within a crowd.

The Uses and Gratifications Theory posits18 that adolescents select appropriate media based on their own goals and needs, which may include social interaction or information acquisition. Wang Luowei combined the satisfaction theory to analyse the distinct characteristics of adolescents engaged in different types of exercise regarding their social media usage habits, needs, and satisfaction levels. The study found that adolescents engaged in active exercise use video-based social media to acquire sports skills, with their satisfaction stemming from the enhancement of these skills. In contrast, adolescents engaged in passive exercise derive satisfaction from social media content that entertains them during their leisure time19.

Social cognitive theory posits20 that individual behaviour is determined by their cognitive processing of social contexts and information. Perceptions, understandings, and interpretations of objectively existing phenomena influence behavioural responses. Fiedler’s research found that higher athletic performance levels among adolescent athletes are associated with increased social comparison when using social media21, meaning that adolescents develop a comparative mindset toward user-generated sports media content, which increases their motivation to engage in physical exercise and improve their athletic skills, thereby enhancing their athletic performance levels. Social media has a democratic nature and also serves as a platform for adolescents to make friends and express themselves22. Content production emphasises bottom-up influences on adolescents’ sports cognition and emotions23, which helps them actively participate in sports and develop healthy self-management habits.

Additionally, online social network interventions can facilitate effective behavioural change. Health education centred on WeChat can help promote the development of physical exercise habits among university students and has positive application value for improving self-body image24. Studies on using mobile internet to intervene in the sedentary lifestyles of students have also shown that social support provided by peers in online networks and real-time feedback on exercise physiological data significantly improve physical activity levels25. Mobile client service programmes (APPs) that allow friends to share fitness data can promote the maintenance of fitness and healthy behaviours; customised exercise prescriptions from the internet, combined with goal monitoring and feedback, can enhance the positive intervention effects on physical activity levels26. These theories and research findings have gradually become reference criteria for the production of sports-related content on social media among adolescents.

The cross-disciplinary nature of the content structure identified in this study is evident across different disciplines and methodologies, while its integrative nature is reflected in the commonalities observed in theories pertaining to the primary characteristics of adolescent groups or social media content production. Overall, the study encompasses nearly all aspects of the characteristics of social media sports content production. As such, the questionnaire developed in this study for adolescent social media sports content production is supported by a solid theoretical foundation.

Starting point and application: the practical significance of the ‘social media sports content production questionnaire’

Based on the definition of content production and self-presentation theory, combined with local cultural characteristics, a two-dimensional content production framework was systematically and organically integrated to design a questionnaire suitable for studying social media sports content production among Chinese adolescents. This approach addresses the previous practice of directly transplanting foreign scales or cross-contextual measurement tools, overcoming issues related to the validity of empirical data caused by cultural background differences and contextual specificity. It also avoids the use of measurement tools from non-sports contexts, thereby mitigating measurement validity biases resulting from differences in research domain characteristics.

The research results indicate that the ‘Social Media Sports Content Production Questionnaire’ developed in this study has satisfactory reliability and validity, effectively assessing the status of social media sports content production among Chinese adolescents, and demonstrating good measurement characteristics. Future research can utilise this questionnaire to explore the factors influencing Chinese adolescents’ participation in physical exercise in social media contexts, as well as the relationship between adolescents’ psychological needs, behavioural motivations, and cognitive processes. This will enable an exploration from a psychological perspective of how to effectively promote the healthy physical and mental development of adolescents, providing psychological support for the cultivation of physical exercise behaviour.

Additionally, this study takes a exploratory approach, starting with the promotion of physical health among adolescents, and aims to produce a comprehensive, scientific, and high-quality collection of sports and health content. The resulting assessment tool for the production of sports content on social media for adolescents reflects the current societal demands for the physical and mental health development of adolescents in the new era, while closely aligning with current developmental realities. It effectively balances the scientific rigor and practicality of the research, thereby enhancing the effectiveness and targeting of adolescent participation in physical exercise. Therefore, this measurement tool, which starts from ‘adolescents’ and focuses on ‘content production,’ holds significant practical significance.

Limitations and prospects: a review of the value of research on social media sports content production among adolescents

The promotion of adolescent sports and health has been influenced by different socio-economic and cultural factors at different historical periods, necessitating the resolution of distinct issues. In the future, with the rapid development of science and technology, the promotion of adolescent sports and health presents both challenges and opportunities. Social media content production can contribute to this effort, but the following points should be noted:

Ensuring the quality of both user-generated content and expert-generated content is a prerequisite. Both types of content play important roles in promoting adolescent sports health. User-generated content primarily influences adolescents’ sports-related emotions, while expert-generated content primarily influences their sports-related cognition. Sports cognition and sports-related emotions collectively promote sports behaviour. Due to the autonomy, freedom, and openness of content production, its quality varies greatly. Therefore, measures must be taken to ensure the quality of content production when using social media content production to promote adolescent sports health.

Enhancing adolescents’ digital literacy is the core focus. As ‘digital natives,’ adolescents have grown accustomed to using the internet to solve problems in their daily lives and studies. Social media content production, as a tool to promote adolescents’ sports health, is neutral in itself; whether it achieves its purpose depends on the users. In the process of using social media content production to promote adolescents’ sports health, adolescents are the main actors and users of the ‘social media content production’ tool. Therefore, improving adolescents’ digital literacy is the core of using social media content production to promote adolescents’ sports health.

Ensuring the effective functioning of regulatory mechanisms across all sectors is a fundamental prerequisite. The Chinese government has long been engaged in exploring and striving to improve its governance of online content and the construction of an integrated governance system. To create a clean and healthy online environment, the policies and decisions of the Party and government serve as the cornerstone and guarantee for specific governance initiatives, representing the overarching design of the integrated online governance system. Therefore, the Party and government must enhance the modernisation of their online governance capabilities to ensure the orderly and efficient operation of the online governance system. Families, schools, businesses, and society must also take measures to leverage supervisory and regulatory functions. On one hand, they should oversee social media platforms to ensure the provision of high-quality content. On the other hand, they should monitor teenagers’ reasonable, proper, and appropriate use of the internet to effectively reduce the harm caused by the internet to teenagers.

This study focuses on the development of a questionnaire on social media sports content production among adolescents. Due to limitations in research capabilities and conditions, the study has certain shortcomings, and its findings are subject to limitations. Future research should expand the sample scope to other regions and groups nationwide and globally to enhance the validity of the questionnaire in other samples.

Conclusions

The ‘Social Media Sports Content Production Questionnaire’ consists of two dimensions: user-generated content production and expert-generated content production. User-generated content production includes activities such as sharing, interacting, liking, reposting, and commenting, while expert-generated content production includes activities such as accessing professional information, providing professional feedback, and offering professional fitness advice. The questionnaire comprises a total of 9 questions, with 5 questions related to user-generated content production and 4 questions related to expert-generated content production. The questionnaire underwent exploratory factor analysis and confirmatory factor analysis, providing good internal consistency reliability, test-retest reliability, content validity, structural validity, and convergent validity in terms of data quantification. The research results show that the questionnaire has good reliability and validity and is a reliable and effective measurement tool that can be used to measure social media sports content production among adolescents.