Digital Health Literacy in School Physical Education: A Grounded Theory Framework for Teacher Competence

Digital Health Literacy in School Physical Education: A Grounded Theory Framework for Teacher Competence | 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 Digital Health Literacy in School Physical Education: A Grounded Theory Framework for Teacher Competence Yu Yang, Weijin Shi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8908787/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As digital technologies transform health information environments, digital health literacy has become a core professional competence for school-based health education. Physical education teachers play a critical role in shaping students’ health behaviours. However, the structural composition of their digital health literacy remains undertheorised.This qualitative study used a grounded theory approach to conduct semistructured interviews with 34 participants from 12 provinces in China. Interview data were analysed with NVivo 15.0 through open, axial and selective coding, which was supplemented by relevant literature and policy documents. The analysis generated a Digital Health Literacy Framework for Primary and Secondary School PE Teachers comprising three core dimensions: Digital Health Awareness and Critical Literacy, Digital Teaching Practice and Innovative Application Competence and Digital Security Ethics and Environmental Awareness Competence. These dimensions were further operationalised through eight categories, 40 concepts and 214 empirical statements, thus reflecting a multilevel structure from information appraisal and data-informed teaching to ethical and contextual judgement. The proposed framework conceptualises PE teachers’ digital health literacy as a systematic, interconnected competency system rather than a set of isolated skills. It provides a theoretical basis for designing assessment tools and targeted professional development and offers a reference point for international comparison and policy-making in digital health and PE. Digital health literacy Digital Teaching Competence Grounded theory Physical Education Teachers Data Ethics in Education Figures Figure 1 1. Introduction Within the contemporary convergence of global public health and education policies, rapid advances in digital technologies are reshaping the ways health information is produced, disseminated and interpreted. This transformation aligns with arguments by digital health literacy scholars that health competence now depends on technological engagement and critical evaluation skills (Anurogo et al., 2023 ; Matthews, 2021 ; Yoon et al., 2022 ). The World Health Organisation’s (WHO) Global Digital Health Strategy (2020–2025) similarly identifies improved digital health literacy as essential for navigating increasingly complex health environments and mitigating widening health inequalities. This emphasis signals a broad shift from traditional health education models towards competency-based approaches that integrate technology use, critical judgement and self-management (Arias López et al., 2023 ; Nutbeam, 2021 ). Within this macro context, education systems, which are the central mechanisms of social reproduction, have been assigned a new mission: preparing future citizens to operate effectively within digital health ecosystems. Correspondingly, global policy trends increasingly position schools as key sites for cultivating integrated health and digital competencies (Khurana et al., 2022 ; Sørensen, 2024 ; Wilkesmann, 2025 ). Schools, particularly at the primary and secondary levels, are central arenas for advancing this new educational mission. Within this setting, the role of physical education (PE) teachers is undergoing a notable paradigm shift. As reflected in the Health Promoting Schools framework, teachers are increasingly positioned as holistic facilitators of students’ physical, cognitive and digital wellbeing (Knoke et al., 2024 ). Rather than serving solely as instructors of motor skills, they are becoming ‘bridge-builders’ who connect the digital health domain with students’ embodied practices, thus guiding the development of lifelong health behaviours. Therefore, their professional competence extends beyond pedagogical and physiological knowledge to include data interpretation, digital platform navigation and critical appraisal of online health content (Andreas Raab, 2023 ; Kealy-Ashby et al., 2025 ). However, this expanding role raises a fundamental question that remains insufficiently theorised: what is the underlying structure of digital health literacy required of PE teachers in the digital era? The absence of a clear conceptual model constitutes a significant bottleneck for theoretical development and practical innovation in this emerging field. Digital health literacy has evolved from a static cognitive skill to a dynamic, context-responsive competence that is shaped by digital environments (De Santis et al., 2021 ; Ji et al., 2024 ; Palumbo et al., 2022 ). It builds on functional, interactive and critical health literacy, thereby requiring individuals not only to access but also to evaluate critically and apply digital health information across platforms (Junaedi et al., 2024 ; Sørensen et al., 2021 ). The European Commission similarly stresses technical and critical capacities (Abdoh, 2022 ). However, most studies rely on general frameworks or equate digital health literacy with technology use, thus overlooking pedagogical demands in school contexts (Abou Hashish & Alnajjar, 2024 ; Papp-Zipernovszky et al., 2021 ). The professional practice of PE teachers uniquely involves converting abstract digital health information into embodied, actionable behaviours, which is a dimension that is largely underexplored in existing theoretical models. A comprehensive understanding of PE teachers’ digital health literacy requires moving beyond instrumental skills towards a sociological and pedagogical analytical framework that considers social engagement and digitally transformed learning environments (Arufe-Giráldez et al., 2023 ; Rangnow et al., 2024 ). From a social interaction perspective, Collins’ ( 2004 ) interaction ritual chain theory explains how meaningful social engagement generates emotional energy and group cohesion. In digital health education, this concept suggests that PE teachers can transform abstract health knowledge into tangible behavioural commitment by designing ritual-like digital experiences that cultivate belonging and shared purpose (Sukys et al., 2024 ). Several practices, such as digital health challenges or online health communities, enable students to exchange experiences, offer mutual encouragement and collaboratively address health-related tasks, thereby strengthening engagement and digital health literacy (Adil et al., 2021 ; Patil et al., 2021 ; Zakar et al., 2021 ). Accordingly, PE teachers’ digital health literacy necessarily includes the ability to design and facilitate such digital interaction rituals. Students’ cognitive and learning differences require differentiated instruction supported by digital tools. Gardner’s multiple intelligences theory helps explain why PE teachers’ digital health literacy must include recognising diverse learner strengths and adapting instruction accordingly (Lucius & Daryanto, 2024 ). Appropriately selected digital platforms can align health content with students’ varied learning profiles, thereby enhancing the inclusiveness and effectiveness of digital health education (Akbaruddin et al., 2024 ; Rahayu et al., 2025 ). The TPACK framework underscores that effective technology integration requires the coordinated use of technological, content and pedagogical knowledge. When it is applied to PE, it suggests that digital health literacy entails the capacity to align digital tools with health-related content and pedagogical aims, thus enabling informed and contextually appropriate instructional decisions (Souza Júnior et al., 2022 ). From a motivational perspective, self-determination theory posits that intrinsic motivation is strengthened when the psychological needs of autonomy, competence and relatedness are met. When it is applied to digital health education, it suggests that students are likely to engage sustainably in healthy behaviours when digital tools support personalised competence feedback, offer meaningful choice and foster a sense of connection through digital communities (Rota et al., 2025 ; Yeo et al., 2023 ). Accordingly, PE teachers’ digital health literacy includes the capacity to design digital learning environments that activate these motivational processes, thereby positioning teachers not only as facilitators of physical activity but also as designers of motivationally supportive digital ecosystems. In summary, the digital health literacy that is required of primary and secondary school PE teachers is a complex, multidimensional construct that is shaped by the demands of the digital era and embedded in embodied teaching practice. It encompasses capacities for information appraisal, the facilitation of digital interaction, the adaptation of teaching strategies and ethical engagement with health data. However, no existing theoretical model has adequately captured this multifaceted structure, which leaves assessments of PE teachers’ digital health competencies without a clear conceptual foundation and limits the development of coherent preservice and in-service professional training. Given the conceptual ambiguity and the emerging nature of this field, grounded theory provides an appropriate methodological approach. Its emphasis on bottom-up induction, constant comparison and abstraction from empirical data enables the generation of a theory that reflects practical realities (Corbin, 2021 ) particularly in contexts where boundaries remain fluid and complexity is high. Accordingly, this study constructs a data-driven framework of digital health literacy for primary and secondary school PE teachers. Clarifying its core components and theoretical dimensions will support the optimisation of teacher professional development and contribute a substantive Chinese perspective to international research and practice in digital health education. 2. Materials and methods This study adopts grounded theory, which was originally developed by Glaser and Strauss in 1967, as its primary methodological approach. As an inductive qualitative method, grounded theory enables theoretical concepts to emerge directly from empirical data rather than from predetermined assumptions (Chametzky, 2016 ; Guerrero Puerta & Lorente García, 2024 ; Premier University et al., 2023; Rawhani, 2023 ). It provides a structured yet flexible process in which theoretical insights develop progressively through iterative data collection, constant comparison and coding (Akkaya, 2023 ). Notably, grounded theory constitutes a methodological pathway rather than a fixed theoretical system. Over time, the theory has become one of the most widely used qualitative methodologies across various fields, such as nursing, sociology, healthcare and education, and is valued for its capacity to generate midrange theories that link empirical observations with conceptual abstraction (Conejero & MacLennan, 2023 ). Its application in PE research has likewise expanded, thus reflecting its suitability for capturing the complex, practice-based and interactional characteristics of PE, which are often overlooked by traditional quantitative approaches (Chen et al., 2023 ). Over time, Glaser and Strauss developed methodological differences that led to two distinct variants of grounded theory, which largely reflect contrasting positions on whether researchers should enter analysis with prior assumptions or maintain theoretical neutrality (Howard-Payne, 2016 ). In the past two decades, Strauss’s version has become the most widely cited. This approach adopts a bottom-up logic and employs three progressive coding procedures, namely, open, axial and selective coding, through which data are successively conceptualised, linked and integrated into a coherent theoretical framework (Corbin, 2021 ; Dixon-Woods et al., 2005 ). Unlike hypothesis-driven methods, this discovery-oriented process enables theoretical insights to emerge directly from empirical patterns, thereby making grounded theory particularly valuable in fields where conceptual foundations remain underdeveloped (Al-Eisawi, 2022 ). Consequently, iterative data collection and systematic coding represent the core of grounded theory research. This study ensures methodological rigour by adopting a multisource data strategy to build a comprehensive analytical foundation. Primary data were collected through semistructured interviews, while secondary sources were gathered through systematic searches of China National Knowledge Infrastructure, Web of Science and policy documents issued by the Ministry of Education of the People’s Republic of China and the General Administration of Sport of China. The integration of these data sources broadens the theoretical and policy context for analysing PE teachers’ digital health literacy and supports the development of a research design that is conceptually informed and grounded in local educational realities. 2.1 Participants This study applies grounded theory within a qualitative research design to construct a data-driven framework of digital health literacy for primary and secondary school PE teachers. This methodology supports the inductive development of concepts and categories directly from empirical data rather than from predetermined theoretical assumptions (Liu et al., 2024 ). Consistent with grounded theory principles, theoretical sampling was adopted, which emphasised purposeful selection and relatively small sample sizes to capture diverse and conceptually relevant perspectives. Theoretical sampling in grounded theory highlights purposeful case selection to obtain the most conceptually rich information rather than statistical representativeness. Accordingly, participants were selected based on their ability to provide experience-based insights into primary and secondary school PE teachers’ digital health literacy (Lupton, 2021 ). Two groups were recruited: (1) frontline PE teachers who were directly engaged in teaching practice and (2) experts and scholars in PE and health education who offered broad theoretical perspectives. Grounded theory typically relies on small samples that are aimed at reaching theoretical saturation; the sample size is determined by informational depth rather than numerical adequacy (Qin et al., 2025 ). An initial target of approximately 20 participants was set. However, concurrent data collection and analysis revealed that frontline teachers contributed particularly rich empirical cases. Therefore, the sampling was adjusted dynamically to increase the proportion of frontline practitioners. Recruitment continued until no new categories emerged and theoretical saturation was achieved. In total, 34 participants from 12 provinces across North China, East China, South China, Southwest China and Northwest China were interviewed. We ensured anonymity by assigning numerical identifiers (P1–P34) to all participants. Table 1 presents the demographic information in detail. Table 1 Basic Information of Interview Participants (N = 34) No. Form Title Location Instrument 1 Individual interviews PE teachers in primary and secondary schools Eastern China Tencent Meeting App 2 Individual interviews PE teachers in primary and secondary schools Southern China Tencent Meeting App 3 Individual interviews PE teachers in primary and secondary schools Western China Tencent Meeting App 4 Individual interviews PE teachers in primary and secondary schools Western China Tencent Meeting App 5 Individual interviews PE teachers in primary and secondary schools Northern China Tencent Meeting App 6 Individual interviews PE teachers in primary and secondary schools Eastern China Phone Recording App 7 Individual interviews PE Teachers in Higher Education Eastern China Email 8 Individual interviews PE teachers in primary and secondary schools Central China Tencent Meeting App 9 Individual interviews PE Teachers in Higher Education Eastern China Email 10 Individual interviews PE teachers in primary and secondary schools Eastern China Tencent Meeting App 11 Individual interviews PE teachers in primary and secondary schools Northern China Tencent Meeting App 12 Individual interviews PE teachers in primary and secondary schools Northern China Tencent Meeting App 13 Individual interviews PE teachers in primary and secondary schools Eastern China Tencent Meeting App 14 Individual interviews PE teachers in primary and secondary schools Northern China Tencent Meeting App 15 Individual interviews PE teachers in primary and secondary schools Eastern China Voice Recorder 16 Individual interviews PE teachers in primary and secondary schools Eastern China Email 17 Individual interviews PE Teachers in Higher Education Eastern China Email 18 Individual interviews PE teachers in primary and secondary schools Eastern China Email 19 Individual interviews PE teachers in primary and secondary schools Eastern China Voice Recorder 20 Individual interviews PE teachers in primary and secondary schools Eastern China Voice Recorder 21 Individual interviews PE teachers in primary and secondary schools Eastern China Email 22 Individual interviews PE teachers in primary and secondary schools Eastern China Email 23 Focus group PE teachers in primary and secondary schools Tencent Meeting App 24 Focus group PE teachers in primary and secondary schools Tencent Meeting App 25 Group interviews (8 persons) PE teachers in primary and secondary schools Voice Recorder 2.2 Interview An interview guide titled ‘Exploring the Structure of Digital Health Literacy Among Primary and Secondary School Physical Education Teachers’ was developed to address the research objectives. The guide was first piloted with three representative PE teachers to ensure methodological rigour. Based on the teachers’ feedback and following consultations with two experts in school PE and health education, two rounds of revisions were conducted to refine the content, logical structure and wording.The interview guide was developed specifically for this study and is available in Supplementary material 2. Given the geographical dispersion of participants across multiple provinces, data were collected through a combination of face-to-face interviews and online video conferencing. Interview appointments were arranged in advance. Then, the interview guide was sent to participants beforehand to facilitate preparation and ensure the depth of responses. In-person interviews were conducted in quiet, interruption-free environments with each session lasting approximately 40–60 minutes. Throughout the interview process, standard qualitative research ethics were strictly observed. Rapport was established to create a psychologically safe atmosphere, thus enabling participants to express their experiences and perspectives openly. Semistructured interviews allowed for flexibility: while centred on core questions, the sequence was adapted based on participants’ responses. Leading questions were deliberately avoided. Instead, active listening and probing techniques were employed to elicit specific behaviours, contextual details and illustrative examples. For instance, when participants reported using digital health tools in PE teaching, follow-up questions explored tool types, usage scenarios, student reactions and observed teaching outcomes. This approach ensured the collection of rich, detailed data that were necessary for analysing and theorising the structure of PE teachers’ digital health literacy. 2.3 Data analysis Following each interview, audio recordings were transcribed verbatim to ensure accuracy and preserve the integrity of participants’ original statements. In total, 34 transcripts comprising approximately 120,000 words were generated. Qualitative data analysis software NVivo 15.0 was used to organise and code the data systematically. In addition to interview data, relevant literature and policy documents related to school PE were incorporated to enrich the analytical context. Then, all data were subjected to grounded theory’s three-stage coding procedure, namely, open, axial and selective coding. Throughout the analysis, codes were iteratively revised through constant comparison to refine categories and ensure analytic rigour. This process facilitated the development of a comprehensive framework of digital health literacy among primary and secondary school PE teachers. 2.3.1 Open coding Open coding, which is the first and foundational stage of the coding process in grounded theory, involves systematically examining the raw data to identify and label meaningful units. This stage requires careful, line-by-line analysis to ensure that potentially relevant information is not overlooked. It comprises three core processes: labelling, conceptualisation and categorisation. During labelling, which is also referred to as preliminary conceptualisation, interview data were inductively analysed and compared to generate concise statements that captured the essential meaning of participants’ expressions (see Table 2 ). Each statement reflected a distinct aspect of digital health literacy as articulated by interviewees while preserving the original semantic intent. Through this process, a total of 214 statements that were relevant to primary and secondary school PE teachers’ digital health literacy were identified. These statements were recorded using the naming convention ‘EN + statement number’ (e.g. E5 Acquiring digital health information through exchanges with colleagues or peers; E206 Quantifying teaching evaluations through digital health tools) (see Table 3 ). Table 2 Example of the labelling process for raw data Data source Original Data Labelling Interview materials numbered 6 I utilise digital health tools in my daily teaching practice to guide students. One specific application involves employing fitness applications to record students' exercise data in real time. These applications not only track metrics such as activity levels, heart rate, and calorie expenditure but also 3provide personalised health recommendations. In class, I guide students to understand their exercise status by displaying this data in real time, helping them set appropriate exercise goals. Furthermore, this data enables me to assess students' physical fitness more accurately and develop more suitable training programmes tailored to each student's characteristics. E35 Assessing digital health information apps to evaluate student exercise data E49 Utilising digital health tools to alleviate teaching workload E51 Assisting Students in Setting Exercise Goals via Digital Health Tools E57 Optimising exercise training plans through digital health tools E59 Enhancing the scientific rigour of teaching evaluations through digital health tools E206 Quantifying teaching evaluations through digital health tools Table 3 Examples of 214 tagged labels result Labels E1 Acquiring digital health information through academic journals E2 Obtaining digital health information through online courses E3 Obtaining digital health information via social media E4 Obtaining digital health information through government or education authority channels E5 Acquiring digital health information through exchanges with colleagues or peers E6 Acquiring digital health information through industry seminars or academic conferences …… E32 Evaluating the effectiveness of digital health tools through trial use E33 Testing digital health tools via small-scale pilot programmes E34 Monitoring students' heart rates using fitness trackers E35 Assessing digital health information apps to evaluate student exercise data E36 Employing smart devices to support classroom teaching E37 Utilising motion capture or correction technology to assist instruction …… E205 Assessing improvements in student health through digital health data E206 Quantifying teaching evaluations through digital health tools E207 Personalising teaching evaluations through digital health tools E208 Comparing individual student progress using digital health tools E209 Analysing class-wide physical activity levels via digital health tools E210 Integrating digital health tools with traditional assessment methods E211 Applying digital health tools in physical education teaching for secondary school or university entrance examinations E212 Adapting digital health tools for teaching in volunteer support or frontier regions E213 Optimising digital health tool implementation based on student feedback E214 Collaborating with colleagues to refine operational procedures for digital health tools Conceptualisation involves refining and consolidating the labelled statements according to principles of validity, similarity and relevance. Statements with closely related meanings were grouped to form high-level concepts (see Table 4 ). Through this process, 40 concepts were distilled from the initial 214 labelled statements. These concepts were recorded using the convention ‘DN + concept name’ (e.g. D4 Capable of extending postclass physical exercises and implementing digital follow-up management) (see Table 5 ). Table 4 Example of conceptualisation process from 214 labels Result of Conceptualisation Label Reference Original Data Reference D17 Feedback on teaching effectiveness and process optimisation with a focus on tool application E95 Communicate with digital health tool developers You could enquire with the developers of health apps about the principles behind their testing. For instance, last time there was an app claiming to correct spinal alignment. I rang their customer service directly to ask whether the algorithm team possessed any medical background. They stammered and couldn't provide a clear answer, so I promptly decided against using it. E96 Adjusting teaching programmes when digital health tools fail to meet expected outcomes Should outcomes fall short of expectations, one must first adjust lesson plan design. For instance, if exercise load or intensity proves inadequate, enhancing intensity within the lesson plan is paramount to achieving desired objectives. E99 Simplifying usage procedures when digital health tools prove overly complex As an experienced teacher, my demand for digital health tools is low, primarily because installing and operating the equipment wastes class time. Schools lack fixed, sufficient equipment, requiring queuing for use, which disrupts teaching progress. However, I recognise the tools' advantages and hope schools will provide adequate equipment and simplify operational procedures in future to facilitate classroom use. E214 Collaborate with colleagues to refine operational procedures for digital health tools I would engage in peer discussions and knowledge sharing. As a new teacher, I would learn from experienced colleagues, exchanging insights and perspectives on the practical application of digital health tools. Table 5 Examples of 40 Concept Results Concepts generated from conceptualisation process Label References D1 Capable of acquiring digital health information from multiple channels E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, E13, E14, E15 D2 Ability to evaluate and verify information content E16, E17, E18, E19, E20, E21, E22, E23, E24, E25, E97, E98, E155 D3 Capable of selecting and evaluating educational technology tools E26, E27, E28, E29, E30, E31, E32, E33, E69,E75 D4 Capable of extending post-class physical exercises and implementing digital follow-up management E40, E54, E113, E149 …… …… D37 Capable of addressing issues encountered when using digital health tools E100, E101, E102, E103, E104, E105 D38 Ability to enhance digital health literacy through multiple channels E156, E157 D39 Possesses clear functional requirements for digital health tools in teaching E181, E182 D40 Focuses on identifying limiting factors in the application of digital health technologies E136, E138 Categorisation refers to deriving overarching categories from the established concepts, assigning appropriate category labels and ensuring that each category remains conceptually distinct while sufficiently encompassing its constituent concepts (see Table 6 ). Through this process, eight categories were generated from the 40 concepts. These categories follow the naming convention ‘CN + category name’ (e.g. C8 Digital teaching technology requirements outlook and functional critique literacy) (see Table 7 ) Table 6 Example of conceptualisation process from 40 concepts Result of Categorisation Conceptualisation Reference Labeling Reference Original Data Reference C5 Digital Collaboration and Resource Integration Literacy D10 Ability to Integrate and Apply Interdisciplinary Teaching Resources E88 Collaborating with cross-disciplinary teachers to deliver digital health instruction Sport itself is inherently interdisciplinary, encompassing fields such as exercise physiology and psychology. When analysing sports injury data with the school doctor, we observed a general lack of flexibility in one particular class, prompting us to incorporate stretching exercises into the curriculum. E159 Enhancing Digital Health Literacy Through Interdisciplinary Learning I engage in exchanges with colleagues regarding digital health initiatives, such as sharing insights on fitness tracker usage during teaching and research group sessions, and discussing how to adapt teaching approaches based on data. I also collaborate with teachers from other subjects, for instance, discussing with mathematics teachers how to integrate fitness data into statistical teaching to enhance pupils' comprehensive skills. …… …… …… D32 Emphasis on collaborative expansion models for digital teaching resources E142 Acquiring Digital Health Resources Through Industry-Academia Collaboration We hope to enhance privacy protection technologies for digital health solutions and improve data security. We also hope that schools will enter into contracts with relevant parties to safeguard the privacy of students and staff, thereby preventing data misuse. E143 Acquiring Digital Health Resources Through Inter-Institutional Collaboration Organise student case studies in the classroom to explore digital health application scenarios (such as discrepancies in fitness app data); host seminars inviting experts to share technological developments while encouraging staff and students to exchange usage insights; conduct collaborative research with institutions and enterprises (e.g., ‘Practical Application of AI Motion Correction Systems in Basketball Instruction’) and share findings; attend academic conferences to deliver oral presentations on digital health teaching research and receive peer feedback. Table 7 Examples of 8 categories result Categories Concepts Number of labels C1 Digital information processing and evaluation literacy D1 Ability to access digital health information from multiple channels 15 D2 Capable of conducting information content evaluation and verification practices 13 D22 Possesses an intrinsic understanding of digital health literacy 10 D37 Capable of addressing issues encountered when using digital health tools 6 D38 Capable of enhancing digital health literacy through multiple avenues 2 …… …… …… C8 Digital teaching technology requirements outlook and functional critique literacy D27 Prospects for functional requirements of teaching tools 5 D39 Clear functional requirements for digital health tools in teaching 2 2.3.2. Axial coding Axial coding, which is the second and central stage of the coding process in grounded theory, involves reestablishing connections among the categories that were generated during open coding. This stage requires a detailed comparison and analysis of intercategory relationships to identify high-level primary categories. Through axial coding, three primary categories were identified, following the naming convention ‘BN + category name’: B1 Digital Health Awareness and Critical Literacy, B2 Digital Teaching Practice and Innovative Application Competence and B3 Digital Security Ethics and Environmental Awareness Competence (see Table 8 ). Table 8 Eight categories derived from axis coding Main Categories Sub-Categories B1 Digital Health Awareness and Critical Literacy C1 Digital Information Processing and Evaluation Literacy C6 Critical Reflection and Digital Sustainability Literacy C8 Digital Teaching Technology Requirements Outlook and Functional Critique Literacy B2 Digital Teaching Practice and Innovative Application Competence C2 Digital Tool Application and Optimisation Competence C3 Digital Instruction Monitoring and Data Analysis Competence C5 Digital Collaboration and Resource Integration Competence B3 Digital Security Ethics and Environmental Awareness Competence C4 Data Security and Ethical Standards Competence C7 Digital Instructional Environment and Implementation Feasibility Awareness 2.3.3. Selective coding Selective coding represents the final stage of grounded theory analysis during which the ‘core category’ is identified and systematically linked to all other categories. This stage involves validating intercategory relationships, integrating categories whose conceptualisation remains incomplete and elevating the analysis to a high level of abstraction. Building on the eight categories and the three primary categories generated through previous coding stages, continual comparison with the original data enabled the identification of the overarching core category: ‘Digital Health Literacy of Primary and Secondary School Physical Education Teachers’. This core category synthesises all labels, concepts, categories and subcategories that are developed throughout the coding process, thus providing an integrated and coherent representation of the phenomenon under investigation. 2.4 Theoretical saturation test A systematic theoretical saturation test was conducted to ensure the rigour and completeness of the theoretical framework (Naeem et al., 2024 ). The purpose of this test was to determine whether the constructed Structural System of Digital Health Literacy for Physical Education Teachers sufficiently captured all essential categories and properties of the phenomenon. Consistent with qualitative research standards, theoretical saturation was defined as the point at which additional data no longer produced new concepts or category attributes. For validation, all interview transcripts were randomly divided into two sets: approximately 80% of the data served as the primary analytic corpus, while the remaining 20% were reserved as a saturation test sample. Coding of the validation sample in NVivo 15.0 revealed no new concepts, categories or relational structures. The existing model adequately accounted for all relevant information contained in the reserved data. These procedures confirm that the core theoretical construct developed in this study has reached saturation, thereby demonstrating strong completeness and methodological rigour (Saunders et al., 2018 ). 3 Results The Digital Health Literacy Framework for Primary and Secondary School Physical Education Teachers comprises three dimensions, eight categories, 40 concepts and 214 statements (Fig. 1 ) : (a)Digital Health Awareness and Critical Literacy, including digital information processing and evaluation literacy, critical reflection and continuous development literacy and digital teaching technology requirements outlook and functional critique literacy; (b)Digital Teaching Practice and Innovative Application Competence encompass digital tool application and optimisation in teaching, instructional monitoring and data analysis as well as digital collaboration and resource integration; (c)Digital Security Ethics and Environmental Awareness Competence encompass awareness of data security and ethical standards competence alongside understanding of the digital instructional environment and implementation feasibility awareness. This structural framework illustrates that digital health literacy for primary and secondary school PE teachers represents a comprehensive professional competency system. It integrates three core dimensions, namely, cognitive critique, practical application and ethical environment, which collectively encompass eight essential competency domains and are operationalised through 40 specific capability indicators. The framework reflects the expanded professional requirements that are posed by the digital era and provides a systematic theoretical basis for the cultivation and assessment of PE teachers’ digital health literacy. 3.1 Digital health awareness and critical literacy The dimension Digital Health Awareness and Critical Literacy represents the meta-competence that underpins the entire digital health literacy framework for PE teachers. It serves as the cognitive foundation through which teachers interpret, evaluate and respond to digital health information prior to any technical or pedagogical application (Evans, 2024 ). This competence encompasses the ability to understand systematically, assess prudently and reflect critically on the value, credibility and limitations of digital health information and technologies. It enables teachers to move beyond passive information consumption towards active judgement that filters misinformation, bias and commercial health narratives (Wallace et al., 2023 ). Aligned with UNESCO’s conceptualisation of digital literacy, which positions critical thinking as a core component, this dimension highlights that digital competence extends beyond technical skills to include the ability to question, interpret and evaluate digital content (Nurfazri et al., 2024 ). Accordingly, this competence positions teachers as gatekeepers of digital health information by equipping them to discern authenticity and assess the educational potential and risks that are associated with emerging technologies. 3.1.1 Digital information processing and evaluation literacy The category Digital Information Processing and Evaluation Literacy constitutes the foundational skillset that enables PE teachers to navigate and utilise digital health resources effectively (Fletcher et al., 2024 ). It refers to the ability to locate information systematically across diverse channels, such as academic databases, professional platforms and online courses, and assess its reliability, scientific validity and timeliness. This competence allows teachers to filter and translate complex digital content into accessible knowledge for school-based health education (Bezeau et al., 2025 ). Given the prevalence of information overload, teachers must not only recognise authoritative sources but also distinguish pseudoscientific and commercially driven content. Without such discernment, educators risk inadvertently transmitting inaccurate information to students, thereby undermining their long-term health judgement (Zakharov et al., 2022 ). Therefore, this competence requires ongoing engagement with current developments in the field and the use of various strategies, such as cross-verifying, assessing source credibility and comparing claims against established scientific principles. One teacher outlined their screening criteria: When filtering digital health information, I adhere to standards of authority, timeliness and professionalism, prioritising research from government official releases, international authoritative organisations and university research institutions; ensuring information is published within the last three years (P12-2). Another educator shared their verification practice: Information encountered can be cross-verified. For instance, upon seeing data from a fitness app, I compare it against scientific standards in textbooks. Where uncertainty persists, I consult colleagues within the teaching research group for their perspectives (P2-4). 3.1.2 Critical reflection and digital sustainability literacy The category Critical Reflection and Digital Sustainability Literacy refers to teachers’ capacity for the ongoing, systematic evaluation of their digital teaching practices, including assessing outcomes, identifying limitations and optimising processes. This competence supports teachers’ long-term professional development by enabling them to adapt to evolving technological trends and avoid digital practices becoming outdated, fragmented or misaligned with learner needs (Wohlfart et al., 2024 ). It also encompasses teachers’ awareness of the need to update their digital health literacy continuously through professional training, academic exchange or self-directed learning. Teachers maintain a knowledge base that remains current and pedagogically relevant by actively monitoring emerging technologies and health trends. In this sense, teachers are positioned not merely as technology users but as reflective practitioners who iteratively refine their digital practices to sustain their professional competence in dynamic digital environments. If a tool fails to yield results, one may adjust teaching methods by combining traditional and digital approaches (P3-12). Another educator emphasised the imperative of continuous learning: As physical education teachers, we must keep pace with the times. AI evolves so rapidly that those who fail to keep abreast will inevitably be left behind (P2-11). Regarding development pathways, one teacher suggested: I believe we should first increase our exposure to these tools in daily practice, then participate in offline training to enhance collective awareness of digital health. Subsequently, we can pursue learning through diverse channels (P1-36). 3.1.3 Digital teaching technology requirements outlook and functional critique literacy The category Digital Teaching Technology Requirements Outlook and Functional Critique Literacy refers to educators’ ability to anticipate, articulate and critically evaluate the functional requirements of digital health tools in teaching contexts. This competence marks a shift from passive technology use towards actively shaping technological development to align with pedagogical principles and learner needs (Modra et al., 2021 ). It involves specifying clear instructional requirements, critically assessing tool design, including privacy protection, algorithmic transparency and interface usability, and recognising how embedded system biases may influence learner data, behavioural nudging or access inequalities (Rosenbaum et al., 2024 ). Grounded in classroom practice, educators are positioned to formulate expectations that extend beyond existing market offerings, thus contributing practitioner-informed critiques and recommendations. This outcome reflects a transition from technology adopters to collaborative contributors in digital tool development, thereby enhancing relevance and usability through pedagogical insight (Papić-Blagojević & Račić, 2025 ). It is hoped that future fitness trackers will not only monitor heart rate but also integrate students’ physical condition data to provide personalised rest recommendations ( based on summaries from P18-15). Concurrently, teachers demonstrated strong critical awareness particularly regarding privacy concerns: All educational apps must explicitly state how data is utilised. (This is nonnegotiable based on summaries from P9-19, P5-31, etc.). Some educators questioned the practical utility of such tools: Advanced digital health technologies like motion capture are better suited for professional team training... For most ordinary students, the focus should remain on physical fitness enhancement (P27-8). 3.2 Digital teaching practice and innovative application competence The dimension Digital Teaching Practice and Innovative Application Competence represents the operational core of digital health literacy, where digital knowledge is translated into concrete pedagogical action within school settings (Kim et al., 2024 ). It denotes teachers’ ability to apply digital health tools, data and resources to design personalised instruction, integrate interdisciplinary activities and foster interactive and data-informed learning experiences. When effectively enacted, this competence enhances students’ health literacy and their agency in managing health-related behaviours (Mancone et al., 2024 ). Aligned with the perspectives of the Organisation for Economic Co-operation and Development (OECD), digital competence is ultimately demonstrated not through tool usage alone but through the generation of innovative teaching practices and improved student learning outcomes (Zhang & Wu, 2025 ). Therefore, this dimension underscores the transformation of digital capacity into pedagogically meaningful and outcome-oriented instructional practice. 3.2.1 Digital Tool Application and Optimisation Competence The category Digital Tool Application and Optimisation Competence constitutes the foundational operational layer of digital teaching practice, which enables the translation of digital health concepts into concrete instructional actions and measurable learning outcomes (Gosak et al., 2021 ). It refers to teachers’ ability to select, evaluate and apply educational technology tools systematically in alignment with teaching goals and learner characteristics. This competence allows teachers to adapt digital tools to diverse learner profiles, such as differences in ability, motivation or learning styles, thereby enhancing instructional responsiveness and effectiveness (Yu & Ha, 2021 ). It further includes designing tailored digital health programmes based on students’ physical fitness, health status and interests to optimise teaching outcomes. When evaluating new digital health tools, we first conduct basic trials to test compatibility with school teaching equipment... followed by small-scale pilot implementations... observing student feedback, data accuracy and the extent to which it enhances teaching outcomes (P12-4). Personalised applications demonstrate rich diversity: We set ‘stepwise heart rate targets’ (gradually increasing from 120 to 140 beats per minute) via smart wristbands for students with low fitness levels (P4-28); Digital tools detect health data, identify issues and guide improvements; teaching adapts to individual needs based on physical assessment results (P4-11). 3.2.2 Digital instruction monitoring and data analysis competence The category Digital Instruction Monitoring and Data Analysis Competence is essential for implementing precise and data-driven health education. It enables teachers to move from intuition-based to evidence-informed instructional decision-making, thus ensuring that pedagogical adjustments are grounded in measurable learning indicators (Blegur et al., 2023 ). This competence involves using smart devices to collect real-time digital health data, such as heart rate or exercise load, during PE sessions, followed by quantitative analysis, visualisation and progress tracking at individual and group levels. Such data-driven feedback improves instructional accuracy and enhances students’ self-awareness by enabling them to visualise their own health performance (Almusawi et al., 2021 ; Jastrow et al., 2022 ; Jenny et al., 2021 ; Lupton, 2022 ). It thereby supports instructional decisions and strengthens the shift from experience-based to data-driven teaching. During long-distance running training with pupils... pupils wear heart rate monitors. While running, they understand their performance metrics and appropriate heart rate levels, enabling them to adjust their pace based on real-time data (P2-12). Another teacher highlighted the role of data analysis in assessing student progress: Examining specific metrics, such as improvements in 1000-metre times, alongside fatigue recovery data (e.g., post-exercise heart rate changes); one pupil’s 1000-metre time didn’t improve, but their heart rate recovered more quickly, indicating enhanced cardiorespiratory fitness (P4-19). 3.2.3 Digital collaboration and resource integration competence The category Digital Collaboration and Resource Integration Competence serves as a vital means to expand the boundaries of health education and enhance teaching effectiveness. Through collaborative platforms, educators can codevelop digital health materials, exchange pedagogical strategies and collectively respond to emerging student health needs (Cabero-Almenara et al., 2021 ; Valverde-Berrocoso et al., 2021 ; Xing & Qi, 2023 ). It encompasses the ability to integrate and apply interdisciplinary teaching resources, actively participate in digital collaboration and knowledge sharing within professional communities and leverage home-school partnerships to implement digital collaborative practices. This competence embodies principles of systems thinking and open collaboration. The ability to integrate and apply teaching resources across disciplines represents a significant and new pedagogical approach in PE. Physical education itself is inherently interdisciplinary, encompassing fields such as exercise physiology and psychology. When analysing sports injury data with the school doctor, we identified a general lack of flexibility in one class and promptly incorporated stretching exercises into the curriculum (P4-22). Professional collaboration takes diverse forms: We exchange digital health experiences with peers and initiate ‘digital health workshops’ within teaching groups to share insights on digital tool usage (P14-5). Home-school collaboration presents opportunities and challenges: Physical education teachers communicate infrequently with parents; our current strategy involves sharing vetted educational videos in parent groups... but we avoid recommending specific apps to prevent commercial disputes (P4-23). 3.3 Digital security ethics and environmental awareness competence The dimension Digital Security Ethics and Environmental Awareness Competence provides the ethical and regulatory foundation for digital health literacy, thereby ensuring that technological applications in education remain compliant, secure and sustainable. This competence is critical for preventing data misuse, algorithmic bias and unintended psychological or behavioural risks within school environments (Anurogo et al., 2023 ; Aydınlar et al., 2024 ; Estrada et al., 2022 ; Rivera-Romero et al., 2022 ). Grounded in the ethical principles of the EU’s General Data Protection Regulation (GDPR), it emphasises safeguarding student data, prioritising wellbeing and establishing clear accountability mechanisms to guide educators’ and institutions’ digital practices (Giuffrida & Hall, 2023 ; Trindade et al., 2023 ). 3.3.1 Data security and ethical standards competence This competence constitutes the ethical baseline for digital health practice, thus reflecting teachers’ understanding of and ability to implement data management protocols, security safeguards and privacy requirements in educational contexts. It ensures that the integration of digital technologies does not infringe upon fundamental rights, particularly students’ autonomy over their personal data and digital identities (Bećirović, 2023 ; Hu, 2023 ; Huang, 2023 ). Teachers demonstrate knowledge of key principles, such as data minimisation, anonymisation and encrypted storage, and are expected to act as responsible data stewards. Student health data are leveraged to enhance educational value while upholding stringent ethical standards. Ensuring student data security involves collecting only data directly relevant to teaching, avoiding sensitive information such as names and home addresses and using anonymous identifiers when interpreting fitness tracker data (P14-7). Another educator proposed specific measures: Adhering to the principle of minimal data collection, gathering only health data essential for teaching, employing end-to-end encrypted tools for data storage and transmission and signing stringent data confidentiality agreements with third-party service providers (P11-7). Data misuse risks are also clearly recognised: The proliferation of digital health technologies may lead to the misuse of health data, such as commercial entities leveraging health monitoring to collect students’ behavioural patterns and physical data for targeted advertising or precision marketing (P12-8). 3.3.2 Digital instructional environment and implementation feasibility awareness This competence reflects teachers’ practical awareness of the contextual conditions that are required for meaningful technology adoption; it emphasises that the integration of digital tools in PE must align with students’ developmental readiness, curriculum requirements and pedagogical goals (Menescardi et al., 2021 ; Saiz-González et al., 2025 ; Sorokolit et al., 2025 ). Educators recognise that digital tool implementation is constrained by multiple objective factors and cannot occur uniformly across settings. They demonstrate sensitivity to identifying barriers, such as limited hardware infrastructure, budget restrictions, unstable network conditions and regional disparities; therefore, these factors underscore that effective technology integration depends on selecting tools that match the actual resources and circumstances of schools (Duffy et al., 2022 ; Giebel et al., 2023 ; Gityamwi et al., 2025 ). The fundamental contradiction is: parents prioritise their children’s basic needs over data privacy awareness... Shared devices among pupils are commonplace... Current baseline: resolutely avoid tools requiring facial recognition (P4-32). Another teacher highlighted economic and hardware barriers: The adoption of digital health technologies is constrained by school budgets; some well-funded institutions can equip themselves with smart devices... while underfunded schools can only utilise them during open lessons (P33-7). Additionally, disparities in teacher skills were identified as a factor: ‘Senior teachers learn at a slower pace’ (P10-13) and ‘there is a need to enhance skills in operating digital tools’ (D34). 4. Discussion 4.1 Intrinsic logical connections amongst literacy dimensions: An interdependent organic system The framework developed in this study demonstrates that digital health literacy among primary and secondary school PE teachers constitutes an integrated system rather than a simple aggregation of discrete dimensions. The three primary categories collectively form a coherent cognition–practice–assurance cycle. Digital Health Awareness and Critical Literacy (B1) provides the cognitive foundation, which shapes teachers’ judgement, interpretive depth and decision-making in the selection and use of digital health technologies. Digital Teaching Practice and Innovative Application Competence (B2) represents the operational core, which involves translating cognitive insights into concrete pedagogical actions and generating measurable educational value. Digital Security Ethics and Environmental Awareness Competence (B3) constitutes the regulatory and protective layer, which ensures that digital practices remain safe, ethical, contextually feasible and aligned with institutional constraints. These three dimensions are interdependent and mutually reinforcing. Without critical cognition (B1), digital practice (B2) risks becoming superficial or misaligned. Without practical competence (B2), cognitive understanding (B1) cannot be actualised. Without ethical and contextual safeguards (B3), innovative practices (B2) may become unsafe, inequitable or unsustainable. Accordingly, future professional development for PE teachers should adopt a systematic approach that strengthens the coordinated development of all three dimensions, thus ensuring their integration into a comprehensive and sustainable digital health literacy framework (Duffy et al., 2022 ; Giebel et al., 2023 ; Gityamwi et al., 2025 ). 4.2 Responding to the digital health education transformation: Redefining physical education teachers’ professionalism Amidst the global shift towards educational digitalisation and the recognition of health literacy as a core 21st-century competency, the framework developed in this study directly responds to emerging expectations for advanced professionalism among PE teachers. It demonstrates that digital-era professionalism requires the integration of technological competence with health-oriented pedagogical judgement (Farias-Gaytan et al., 2023 ; Ze et al., 2024 ). Traditionally, PE teacher professionalism has emphasised athletic expertise and instructional techniques. However, this framework shows that in the digital age, professionalism is increasingly enacted through new roles, including critical evaluators of digital health information, data-informed instructional decision-makers and guides for ethical and responsible digital health behaviour. This development aligns with global policy directions, including the WHO’s call to embed health literacy across all policy domains and the OECD’s emphasis on preparing teachers as design agents who are capable of leading educational innovation (Ayre et al., 2023 ; Monkman & Lesselroth, 2025 ; WHO, 2021 ). These trends collectively highlight that teachers are now positioned as mediators of digital transformation and health promotion. The framework repositions PE teachers from practitioners of physical training to integrated digital health educators who combine critical digital literacy, data-driven pedagogical practice and health ethics. It offers a theoretically grounded basis for redefining teacher professionalism in the digital era and provides actionable guidance for updating preservice preparation and revising standards for in-service professional development. 4.3 Theoretical framework and application prospects: Empowering professional development and driving international dialogue The value of this framework lies in its dual function as an explanatory theoretical model and a practical tool for guiding capacity development. At an operational level, it provides education administrators, school leaders and teacher training institutions with a clear roadmap for strengthening teachers’ digital health literacy. For Digital Health Awareness and Critical Literacy (B1), professional learning may focus on tracing digital health information sources, evaluating evidence quality and understanding data ethics. For Digital Teaching Practice and Innovative Application Competence (B2), project-based training can support teachers in designing interdisciplinary health units that integrate wearable technologies and data-informed instruction. For Digital Security Ethics and Environmental Awareness Competence (B3), programmes may incorporate privacy regulations, ethical case discussions and school-level digital environment assessments. At an academic level, the framework offers a shared conceptual foundation and potential basis for developing standardised measurement tools. It enables cross-national comparative research on PE teachers’ digital health literacy, supports policy benchmarking and facilitates knowledge exchange across cultural contexts. Consequently, the framework contributes not only to enhancing professional development systems but also to promoting international dialogue on digital health education within the global PE community. 4.4 Research Limitations and Future Directions This study has several limitations. Although grounded theory procedures were implemented rigorously, the broad scope of the research required a diverse sample. However, the resulting sample size may be limited. Given that the qualitative data were drawn from specific national and regional contexts, the universality and contextual variations of the proposed model require further validation across broad cultural and policy environments. Additionally, the framework developed for this research primarily presents a structural model of literacy. Future research should extend this work by constructing standardised assessment instruments for large-scale quantitative validation and examining how the framework’s dimensions interact to influence students’ health literacy and health behaviours. Future studies may pursue several directions: (1) longitudinal research to trace the developmental trajectory of this literacy framework across different stages of teachers’ careers; (2) design-based research to develop and evaluate professional development interventions grounded in the model; (3) cross-national comparative studies to explore the similarities, differences and underlying mechanisms of digital health literacy development among PE teachers across diverse educational systems and cultural contexts. 5. Conclusion This study constructed a grounded, empirically derived framework for understanding digital health literacy among primary and secondary school PE teachers. The model reveals that teachers’ digital health literacy is a multidimensional and interconnected system that encompasses critical digital awareness, innovative data-informed teaching practice and ethical–contextual judgement. Together, these dimensions provide a coherent foundation for conceptualising how PE teachers navigate, apply and evaluate digital health technologies in educational settings. The framework offers a theoretical basis for strengthening teachers’ professional development and integrating digital health literacy into PE policy and practice. It highlights the need for coordinated capacity building that simultaneously advances cognitive, practical and ethical competencies. As schools continue to respond to the challenges and opportunities of digital health, this framework contributes an evidence-informed direction for supporting teachers’ evolving roles and promoting the healthy, holistic development of young people. Declarations Ethics approval and consent to participate. This study received ethical approval from the Ethics Committee of Shanghai Normal University. This study was conducted in accordance with the Declaration of Helsinki. All participants provided informed consent prior to their involvement. They were informed of the study's purpose, procedures, and their right to withdraw at any time without consequence. Confidentiality and anonymity of all participants have been maintained throughout the research process. Consent for publication Not applicable. Competing Interests The authors declare that they have no competing interests. Funding This work was supported by the Youth Fund Project of the Ministry of Education's Humanities and Social Sciences [Grant Number: 18YJC890033]. Author Contribution YY: Conceptualization, Methodology, Investigation, Formal analysis, Data Curation, Writing – Original Draft. WS: Writing – Review & Editing, Validation, Supervision. Acknowledgement The authors extend their sincere gratitude to all primary and secondary school physical education teachers and higher education experts who participated in this study for their valuable time and insightful contributions. Data Availability The original data generated and analysed during this study are included in the article and its supplementary materials. Further datasets are available from the corresponding author upon reasonable request. 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 Abdoh E. Online health information seeking and digital health literacy among information and learning resources undergraduate students. 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Integrating smartphone apps during differentiated teaching: Promoting increased student engagement and performance in team sports activities in middle school physical education. Phys Activity Health. 2025;9(1):110–23. 10.5334/paah.442 . Rangnow P, Fischer L, Hartmann A, Renninger D, Stauch L, Okan O, Dadaczynski K. Digital health literacy among primary and secondary school teachers—A quantitative study. Front Public Health. 2024;12:1334263. 10.3389/fpubh.2024.1334263 . Rawhani C. Relational coding: Enhancing the transparency and trustworthiness of grounded theory research. Methodological Innovations. 2023;16(1):102–20. 10.1177/20597991221144566 . Rivera-Romero O, Gabarron E, Miron-Shatz T, Petersen C, Denecke K. Social media, digital health literacy, and digital ethics in the light of health equity: IMIA participatory health and social media working group. Yearb Med Inform. 2022;31(1):82–7. 10.1055/s-0042-1742503 . Rosenbaum S, Moberg J, Chesire F, Mugisha M, Ssenyonga R, Ochieng MA, Simbi CMC, Nakyejwe E, Ngatia B, Rada G, Vásquez-Laval J, Garrido JD, Baguma G, Kuloba S, Sebukyu E, Kabanda R, Mwenyango I, Muzaale T, Nandi P, Oxman M. (2024). Teaching critical thinking about health information and choices in secondary schools: Human-centred design of digital resources. F1000Research , 12 , 481. 10.12688/f1000research.132580.3 Rota J, Dias HM, Zanetti MC. Self-determination theory and youth futsal: Motivational and developmental perspectives on early sports engagement. Motricidades: Revista Da Sociedade de Pesquisa Qualitativa Em Motricidade Humana. 2025;9(2):244–54. 10.29181/2594-6463-2025-v9-n2-p244-254 . Saiz-González P, Sierra-Díaz J, Iglesias D, Fernandez-Rio J. Exploring physical education teachers’ willingness and barriers to integrating digital technology in their lessons. Educ Inform Technol. 2025;30(5):5965–87. 10.1007/s10639-024-13060-9 . Saunders B, Sim J, Kingstone T, Baker S, Waterfield J, Bartlam B, Burroughs H, Jinks C. Saturation in qualitative research: Exploring its conceptualization and operationalization. Qual Quant. 2018;52(4):1893–907. 10.1007/s11135-017-0574-8 . Sørensen K. Fostering digital health literacy to enhance trust and improve health outcomes. Comput Methods Programs Biomed Update. 2024;5:100140. 10.1016/j.cmpbup.2024.100140 . Sørensen K, Levin-Zamir D, Duong TV, Okan O, Brasil VV, Nutbeam D. Building health literacy system capacity: A framework for health literate systems. Health Promot Int. 2021;36(Supplement1):i13–23. 10.1093/heapro/daab153 . Sorokolit N, Bodnar I, Rymar O, Shevtsiv U, Shymanova-Stefanyshyn O. (2025). Digital applications in physical education: Experience, benefits, and implementation challenges. Proceedings of the 16th International Scientific and Practical Conference , 3 , 329–335. 10.17770/etr2025vol3.8535 Souza Júnior AFD, Oliveira MRRD, De Araújo C, A. The debate of digital technology in the continuing physical education teacher education: Uses and concepts for teaching and learning. Retos. 2022;46:694–704. 10.47197/retos.v46.94484 . Sukys S, Trinkuniene L, Tilindiene I. Physical education teachers’ health literacy: First evidence from Lithuania. Healthcare. 2024;12(13):1346. 10.3390/healthcare12131346 . Trindade AR, Holley D, Marques CG. (2023). Skills for safety, security, and well-being in the DigComp framework revision and their relevance for a sustainable global (higher) education. In M. J. Sousa, A. De Bem Machado, & G. Aparecida Dandolini, Technologies for Sustainable Global Higher Education (1st ed., pp. 45–75). Auerbach Publications. 10.1201/9781003424543-4 Valverde-Berrocoso J, Fernández-Sánchez MR, Dominguez R, F. I., Sosa-Díaz MJ. The educational integration of digital technologies preCovid-19: Lessons for teacher education. PLoS ONE. 2021;16(8):e0256283. 10.1371/journal.pone.0256283 . Wallace J, Scanlon D, Calderón A. Digital technology and teacher digital competency in physical education: A holistic view of teacher and student perspectives. Curriculum Stud Health Phys Educ. 2023;14(3):271–87. 10.1080/25742981.2022.2106881 . WHO. (2021). Making every school a health-promoting school: Implementation guidance (pp. 68–91). World Health Organization. https://search.worldcat.org/title/1346394778 Wilkesmann J. Innovation and entrepreneurship within health education: International perspectives on multidisciplinary collaboration and digital skills. Routledge; 2025. 10.4324/9781003568650 . Wohlfart O, Mödinger M, Wagner I. Information and communication technologies in physical education: Exploring the association between role modeling and digital literacy. Eur Phys Educ Rev. 2024;30(2):177–93. 10.1177/1356336X231193556 . Xing Z, Qi Y. Development of creativity in physical education teachers using interactive technologies: Involvement and collaboration. Educ Inform Technol. 2023;28(5):5763–77. 10.1007/s10639-022-11422-9 . Yeo LS, Liem GAD, Tan L. Participation in school-based co-curricular activities and developmental outcomes: A self-determination theory perspective. Curr Psychol. 2023;42(35):31600–18. 10.1007/s12144-022-04189-2 . Yoon J, Lee M, Ahn JS, Oh D, Shin S-Y, Chang YJ, Cho J. Development and validation of digital health technology literacy assessment questionnaire. J Med Syst. 2022;46(2):13. 10.1007/s10916-022-01800-8 . Yu H, Ha T. The APPropriate use of technology for assessment in physical education. J Phys Educ Recreation Dance. 2021;92(5):58–61. 10.1080/07303084.2021.1899540 . Zakar R, Iqbal S, Zakar MZ, Fischer F. COVID-19 and health information seeking behavior: Digital health literacy survey amongst university students in Pakistan. Int J Environ Res Public Health. 2021;18(8):4009. 10.3390/ijerph18084009 . Zakharov K, Komarova A, Baranova T, Gulk E. (2022). Information literacy and digital competence of teachers in the age of digital transformation. In A. Beskopylny & M. Shamtsyan, editors, XIV International Scientific Conference INTERAGROMASH 2021 (pp. 857–868). Springer International Publishing. 10.1007/978-3-030-80946-1_78 Ze Z, Zhao X, Chen R. Research on the cultivation path of digital literacy of PE teachers under the background of education digital transformation. Adv Educ Humanit Social Sci Res. 2024;9(1):259. 10.56028/aehssr.9.1.259.2024 . Zhang J, Wu Y. Impact of university teachers’ digital teaching skills on teaching quality in higher education. Cogent Educ. 2025;12(1):2436706. 10.1080/2331186X.2024.2436706 . Additional Declarations No competing interests reported. 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Introduction","content":"\u003cp\u003eWithin the contemporary convergence of global public health and education policies, rapid advances in digital technologies are reshaping the ways health information is produced, disseminated and interpreted. This transformation aligns with arguments by digital health literacy scholars that health competence now depends on technological engagement and critical evaluation skills (Anurogo et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Matthews, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yoon et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The World Health Organisation\u0026rsquo;s (WHO) Global Digital Health Strategy (2020\u0026ndash;2025) similarly identifies improved digital health literacy as essential for navigating increasingly complex health environments and mitigating widening health inequalities. This emphasis signals a broad shift from traditional health education models towards competency-based approaches that integrate technology use, critical judgement and self-management (Arias L\u0026oacute;pez et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Nutbeam, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Within this macro context, education systems, which are the central mechanisms of social reproduction, have been assigned a new mission: preparing future citizens to operate effectively within digital health ecosystems. Correspondingly, global policy trends increasingly position schools as key sites for cultivating integrated health and digital competencies (Khurana et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; S\u0026oslash;rensen, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wilkesmann, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSchools, particularly at the primary and secondary levels, are central arenas for advancing this new educational mission. Within this setting, the role of physical education (PE) teachers is undergoing a notable paradigm shift. As reflected in the Health Promoting Schools framework, teachers are increasingly positioned as holistic facilitators of students\u0026rsquo; physical, cognitive and digital wellbeing (Knoke et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Rather than serving solely as instructors of motor skills, they are becoming \u0026lsquo;bridge-builders\u0026rsquo; who connect the digital health domain with students\u0026rsquo; embodied practices, thus guiding the development of lifelong health behaviours. Therefore, their professional competence extends beyond pedagogical and physiological knowledge to include data interpretation, digital platform navigation and critical appraisal of online health content (Andreas Raab, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kealy-Ashby et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, this expanding role raises a fundamental question that remains insufficiently theorised: what is the underlying structure of digital health literacy required of PE teachers in the digital era? The absence of a clear conceptual model constitutes a significant bottleneck for theoretical development and practical innovation in this emerging field.\u003c/p\u003e \u003cp\u003eDigital health literacy has evolved from a static cognitive skill to a dynamic, context-responsive competence that is shaped by digital environments (De Santis et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ji et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Palumbo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It builds on functional, interactive and critical health literacy, thereby requiring individuals not only to access but also to evaluate critically and apply digital health information across platforms (Junaedi et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; S\u0026oslash;rensen et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The European Commission similarly stresses technical and critical capacities (Abdoh, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, most studies rely on general frameworks or equate digital health literacy with technology use, thus overlooking pedagogical demands in school contexts (Abou Hashish \u0026amp; Alnajjar, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Papp-Zipernovszky et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The professional practice of PE teachers uniquely involves converting abstract digital health information into embodied, actionable behaviours, which is a dimension that is largely underexplored in existing theoretical models.\u003c/p\u003e \u003cp\u003eA comprehensive understanding of PE teachers\u0026rsquo; digital health literacy requires moving beyond instrumental skills towards a sociological and pedagogical analytical framework that considers social engagement and digitally transformed learning environments (Arufe-Gir\u0026aacute;ldez et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rangnow et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). From a social interaction perspective, Collins\u0026rsquo; (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) interaction ritual chain theory explains how meaningful social engagement generates emotional energy and group cohesion. In digital health education, this concept suggests that PE teachers can transform abstract health knowledge into tangible behavioural commitment by designing ritual-like digital experiences that cultivate belonging and shared purpose (Sukys et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Several practices, such as digital health challenges or online health communities, enable students to exchange experiences, offer mutual encouragement and collaboratively address health-related tasks, thereby strengthening engagement and digital health literacy (Adil et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Patil et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zakar et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Accordingly, PE teachers\u0026rsquo; digital health literacy necessarily includes the ability to design and facilitate such digital interaction rituals.\u003c/p\u003e \u003cp\u003eStudents\u0026rsquo; cognitive and learning differences require differentiated instruction supported by digital tools. Gardner\u0026rsquo;s multiple intelligences theory helps explain why PE teachers\u0026rsquo; digital health literacy must include recognising diverse learner strengths and adapting instruction accordingly (Lucius \u0026amp; Daryanto, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Appropriately selected digital platforms can align health content with students\u0026rsquo; varied learning profiles, thereby enhancing the inclusiveness and effectiveness of digital health education (Akbaruddin et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Rahayu et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe TPACK framework underscores that effective technology integration requires the coordinated use of technological, content and pedagogical knowledge. When it is applied to PE, it suggests that digital health literacy entails the capacity to align digital tools with health-related content and pedagogical aims, thus enabling informed and contextually appropriate instructional decisions (Souza J\u0026uacute;nior et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom a motivational perspective, self-determination theory posits that intrinsic motivation is strengthened when the psychological needs of autonomy, competence and relatedness are met. When it is applied to digital health education, it suggests that students are likely to engage sustainably in healthy behaviours when digital tools support personalised competence feedback, offer meaningful choice and foster a sense of connection through digital communities (Rota et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Yeo et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Accordingly, PE teachers\u0026rsquo; digital health literacy includes the capacity to design digital learning environments that activate these motivational processes, thereby positioning teachers not only as facilitators of physical activity but also as designers of motivationally supportive digital ecosystems.\u003c/p\u003e \u003cp\u003eIn summary, the digital health literacy that is required of primary and secondary school PE teachers is a complex, multidimensional construct that is shaped by the demands of the digital era and embedded in embodied teaching practice. It encompasses capacities for information appraisal, the facilitation of digital interaction, the adaptation of teaching strategies and ethical engagement with health data. However, no existing theoretical model has adequately captured this multifaceted structure, which leaves assessments of PE teachers\u0026rsquo; digital health competencies without a clear conceptual foundation and limits the development of coherent preservice and in-service professional training.\u003c/p\u003e \u003cp\u003eGiven the conceptual ambiguity and the emerging nature of this field, grounded theory provides an appropriate methodological approach. Its emphasis on bottom-up induction, constant comparison and abstraction from empirical data enables the generation of a theory that reflects practical realities (Corbin, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) particularly in contexts where boundaries remain fluid and complexity is high. Accordingly, this study constructs a data-driven framework of digital health literacy for primary and secondary school PE teachers. Clarifying its core components and theoretical dimensions will support the optimisation of teacher professional development and contribute a substantive Chinese perspective to international research and practice in digital health education.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003eThis study adopts grounded theory, which was originally developed by Glaser and Strauss in 1967, as its primary methodological approach. As an inductive qualitative method, grounded theory enables theoretical concepts to emerge directly from empirical data rather than from predetermined assumptions (Chametzky, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Guerrero Puerta \u0026amp; Lorente Garc\u0026iacute;a, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Premier University et al., 2023; Rawhani, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It provides a structured yet flexible process in which theoretical insights develop progressively through iterative data collection, constant comparison and coding (Akkaya, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Notably, grounded theory constitutes a methodological pathway rather than a fixed theoretical system.\u003c/p\u003e \u003cp\u003eOver time, the theory has become one of the most widely used qualitative methodologies across various fields, such as nursing, sociology, healthcare and education, and is valued for its capacity to generate midrange theories that link empirical observations with conceptual abstraction (Conejero \u0026amp; MacLennan, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Its application in PE research has likewise expanded, thus reflecting its suitability for capturing the complex, practice-based and interactional characteristics of PE, which are often overlooked by traditional quantitative approaches (Chen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOver time, Glaser and Strauss developed methodological differences that led to two distinct variants of grounded theory, which largely reflect contrasting positions on whether researchers should enter analysis with prior assumptions or maintain theoretical neutrality (Howard-Payne, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In the past two decades, Strauss\u0026rsquo;s version has become the most widely cited. This approach adopts a bottom-up logic and employs three progressive coding procedures, namely, open, axial and selective coding, through which data are successively conceptualised, linked and integrated into a coherent theoretical framework (Corbin, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dixon-Woods et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Unlike hypothesis-driven methods, this discovery-oriented process enables theoretical insights to emerge directly from empirical patterns, thereby making grounded theory particularly valuable in fields where conceptual foundations remain underdeveloped (Al-Eisawi, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequently, iterative data collection and systematic coding represent the core of grounded theory research.\u003c/p\u003e \u003cp\u003eThis study ensures methodological rigour by adopting a multisource data strategy to build a comprehensive analytical foundation. Primary data were collected through semistructured interviews, while secondary sources were gathered through systematic searches of China National Knowledge Infrastructure, Web of Science and policy documents issued by the Ministry of Education of the People\u0026rsquo;s Republic of China and the General Administration of Sport of China. The integration of these data sources broadens the theoretical and policy context for analysing PE teachers\u0026rsquo; digital health literacy and supports the development of a research design that is conceptually informed and grounded in local educational realities.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Participants\u003c/h2\u003e \u003cp\u003eThis study applies grounded theory within a qualitative research design to construct a data-driven framework of digital health literacy for primary and secondary school PE teachers. This methodology supports the inductive development of concepts and categories directly from empirical data rather than from predetermined theoretical assumptions (Liu et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Consistent with grounded theory principles, theoretical sampling was adopted, which emphasised purposeful selection and relatively small sample sizes to capture diverse and conceptually relevant perspectives.\u003c/p\u003e \u003cp\u003eTheoretical sampling in grounded theory highlights purposeful case selection to obtain the most conceptually rich information rather than statistical representativeness. Accordingly, participants were selected based on their ability to provide experience-based insights into primary and secondary school PE teachers\u0026rsquo; digital health literacy (Lupton, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Two groups were recruited: (1) frontline PE teachers who were directly engaged in teaching practice and (2) experts and scholars in PE and health education who offered broad theoretical perspectives.\u003c/p\u003e \u003cp\u003eGrounded theory typically relies on small samples that are aimed at reaching theoretical saturation; the sample size is determined by informational depth rather than numerical adequacy (Qin et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). An initial target of approximately 20 participants was set. However, concurrent data collection and analysis revealed that frontline teachers contributed particularly rich empirical cases. Therefore, the sampling was adjusted dynamically to increase the proportion of frontline practitioners.\u003c/p\u003e \u003cp\u003eRecruitment continued until no new categories emerged and theoretical saturation was achieved. In total, 34 participants from 12 provinces across North China, East China, South China, Southwest China and Northwest China were interviewed. We ensured anonymity by assigning numerical identifiers (P1\u0026ndash;P34) to all participants. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the demographic information in detail.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic Information of Interview Participants (N\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTitle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInstrument\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSouthern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWestern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWestern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorthern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePhone Recording App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE Teachers in Higher Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCentral China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE Teachers in Higher Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorthern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorthern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorthern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVoice Recorder\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE Teachers in Higher Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVoice Recorder\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVoice Recorder\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual interviews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFocus group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFocus group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTencent Meeting App\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup interviews (8 persons)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePE teachers in primary and secondary schools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVoice Recorder\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Interview\u003c/h2\u003e \u003cp\u003eAn interview guide titled \u0026lsquo;Exploring the Structure of Digital Health Literacy Among Primary and Secondary School Physical Education Teachers\u0026rsquo; was developed to address the research objectives. The guide was first piloted with three representative PE teachers to ensure methodological rigour. Based on the teachers\u0026rsquo; feedback and following consultations with two experts in school PE and health education, two rounds of revisions were conducted to refine the content, logical structure and wording.The interview guide was developed specifically for this study and is available in Supplementary material 2.\u003c/p\u003e \u003cp\u003e Given the geographical dispersion of participants across multiple provinces, data were collected through a combination of face-to-face interviews and online video conferencing. Interview appointments were arranged in advance. Then, the interview guide was sent to participants beforehand to facilitate preparation and ensure the depth of responses. In-person interviews were conducted in quiet, interruption-free environments with each session lasting approximately 40\u0026ndash;60 minutes.\u003c/p\u003e \u003cp\u003eThroughout the interview process, standard qualitative research ethics were strictly observed. Rapport was established to create a psychologically safe atmosphere, thus enabling participants to express their experiences and perspectives openly. Semistructured interviews allowed for flexibility: while centred on core questions, the sequence was adapted based on participants\u0026rsquo; responses. Leading questions were deliberately avoided. Instead, active listening and probing techniques were employed to elicit specific behaviours, contextual details and illustrative examples. For instance, when participants reported using digital health tools in PE teaching, follow-up questions explored tool types, usage scenarios, student reactions and observed teaching outcomes. This approach ensured the collection of rich, detailed data that were necessary for analysing and theorising the structure of PE teachers\u0026rsquo; digital health literacy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data analysis\u003c/h2\u003e \u003cp\u003e Following each interview, audio recordings were transcribed verbatim to ensure accuracy and preserve the integrity of participants\u0026rsquo; original statements. In total, 34 transcripts comprising approximately 120,000 words were generated. Qualitative data analysis software NVivo 15.0 was used to organise and code the data systematically.\u003c/p\u003e \u003cp\u003eIn addition to interview data, relevant literature and policy documents related to school PE were incorporated to enrich the analytical context. Then, all data were subjected to grounded theory\u0026rsquo;s three-stage coding procedure, namely, open, axial and selective coding. Throughout the analysis, codes were iteratively revised through constant comparison to refine categories and ensure analytic rigour. This process facilitated the development of a comprehensive framework of digital health literacy among primary and secondary school PE teachers.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Open coding\u003c/h2\u003e \u003cp\u003eOpen coding, which is the first and foundational stage of the coding process in grounded theory, involves systematically examining the raw data to identify and label meaningful units. This stage requires careful, line-by-line analysis to ensure that potentially relevant information is not overlooked. It comprises three core processes: labelling, conceptualisation and categorisation.\u003c/p\u003e \u003cp\u003eDuring labelling, which is also referred to as preliminary conceptualisation, interview data were inductively analysed and compared to generate concise statements that captured the essential meaning of participants\u0026rsquo; expressions (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Each statement reflected a distinct aspect of digital health literacy as articulated by interviewees while preserving the original semantic intent. Through this process, a total of 214 statements that were relevant to primary and secondary school PE teachers\u0026rsquo; digital health literacy were identified. These statements were recorded using the naming convention \u0026lsquo;EN\u0026thinsp;+\u0026thinsp;statement number\u0026rsquo; (e.g. E5 Acquiring digital health information through exchanges with colleagues or peers; E206 Quantifying teaching evaluations through digital health tools) (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExample of the labelling process for raw data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData source\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOriginal Data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLabelling\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterview materials numbered 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI utilise digital health tools in my daily teaching practice to guide students. One specific application involves employing fitness applications to record students' exercise data in real time. These applications not only track metrics such as activity levels, heart rate, and calorie expenditure but also 3provide personalised health recommendations. In class, I guide students to understand their exercise status by displaying this data in real time, helping them set appropriate exercise goals. Furthermore, this data enables me to assess students' physical fitness more accurately and develop more suitable training programmes tailored to each student's characteristics.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE35 Assessing digital health information apps to evaluate student exercise data\u003c/p\u003e \u003cp\u003eE49 Utilising digital health tools to alleviate teaching workload\u003c/p\u003e \u003cp\u003eE51 Assisting Students in Setting Exercise Goals via Digital Health Tools\u003c/p\u003e \u003cp\u003eE57 Optimising exercise training plans through digital health tools\u003c/p\u003e \u003cp\u003eE59 Enhancing the scientific rigour of teaching evaluations through digital health tools\u003c/p\u003e \u003cp\u003eE206 Quantifying teaching evaluations through digital health tools\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExamples of 214 tagged labels result\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabels\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE1 Acquiring digital health information through academic journals\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2 Obtaining digital health information through online courses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE3 Obtaining digital health information via social media\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE4 Obtaining digital health information through government or education authority channels\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE5 Acquiring digital health information through exchanges with colleagues or peers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE6 Acquiring digital health information through industry seminars or academic conferences\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE32 Evaluating the effectiveness of digital health tools through trial use\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE33 Testing digital health tools via small-scale pilot programmes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE34 Monitoring students' heart rates using fitness trackers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE35 Assessing digital health information apps to evaluate student exercise data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE36 Employing smart devices to support classroom teaching\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE37 Utilising motion capture or correction technology to assist instruction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE205 Assessing improvements in student health through digital health data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE206 Quantifying teaching evaluations through digital health tools\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE207 Personalising teaching evaluations through digital health tools\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE208 Comparing individual student progress using digital health tools\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE209 Analysing class-wide physical activity levels via digital health tools\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE210 Integrating digital health tools with traditional assessment methods\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE211 Applying digital health tools in physical education teaching for secondary school or university entrance examinations\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE212 Adapting digital health tools for teaching in volunteer support or frontier regions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE213 Optimising digital health tool implementation based on student feedback\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE214 Collaborating with colleagues to refine operational procedures for digital health tools\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eConceptualisation involves refining and consolidating the labelled statements according to principles of validity, similarity and relevance. Statements with closely related meanings were grouped to form high-level concepts (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Through this process, 40 concepts were distilled from the initial 214 labelled statements. These concepts were recorded using the convention \u0026lsquo;DN\u0026thinsp;+\u0026thinsp;concept name\u0026rsquo; (e.g. D4 Capable of extending postclass physical exercises and implementing digital follow-up management) (see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExample of conceptualisation process from 214 labels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResult of Conceptualisation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLabel Reference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOriginal Data Reference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eD17 Feedback on teaching effectiveness and process optimisation with a focus on tool application\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE95 Communicate with digital health tool developers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYou could enquire with the developers of health apps about the principles behind their testing. For instance, last time there was an app claiming to correct spinal alignment. I rang their customer service directly to ask whether the algorithm team possessed any medical background. They stammered and couldn't provide a clear answer, so I promptly decided against using it.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE96 Adjusting teaching programmes when digital health tools fail to meet expected outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShould outcomes fall short of expectations, one must first adjust lesson plan design. For instance, if exercise load or intensity proves inadequate, enhancing intensity within the lesson plan is paramount to achieving desired objectives.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE99 Simplifying usage procedures when digital health tools prove overly complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAs an experienced teacher, my demand for digital health tools is low, primarily because installing and operating the equipment wastes class time. Schools lack fixed, sufficient equipment, requiring queuing for use, which disrupts teaching progress. However, I recognise the tools' advantages and hope schools will provide adequate equipment and simplify operational procedures in future to facilitate classroom use.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE214 Collaborate with colleagues to refine operational procedures for digital health tools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI would engage in peer discussions and knowledge sharing. As a new teacher, I would learn from experienced colleagues, exchanging insights and perspectives on the practical application of digital health tools.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExamples of 40 Concept Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcepts generated from conceptualisation process\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLabel References\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1 Capable of acquiring digital health information from multiple channels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, E13, E14, E15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2 Ability to evaluate and verify information content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE16, E17, E18, E19, E20, E21, E22, E23, E24, E25, E97, E98, E155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3 Capable of selecting and evaluating educational technology tools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE26, E27, E28, E29, E30, E31, E32, E33, E69,E75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD4 Capable of extending post-class physical exercises and implementing digital follow-up management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE40, E54, E113, E149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD37 Capable of addressing issues encountered when using digital health tools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE100, E101, E102, E103, E104, E105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD38 Ability to enhance digital health literacy through multiple channels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE156, E157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD39 Possesses clear functional requirements for digital health tools in teaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE181, E182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD40 Focuses on identifying limiting factors in the application of digital health technologies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE136, E138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCategorisation refers to deriving overarching categories from the established concepts, assigning appropriate category labels and ensuring that each category remains conceptually distinct while sufficiently encompassing its constituent concepts (see Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Through this process, eight categories were generated from the 40 concepts. These categories follow the naming convention \u0026lsquo;CN\u0026thinsp;+\u0026thinsp;category name\u0026rsquo; (e.g. C8 Digital teaching technology requirements outlook and functional critique literacy) (see Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExample of conceptualisation process from 40 concepts\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResult of Categorisation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConceptualisation Reference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLabeling Reference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOriginal Data Reference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eC5 Digital Collaboration and Resource Integration Literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eD10 Ability to Integrate and Apply Interdisciplinary Teaching Resources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE88 Collaborating with cross-disciplinary teachers to deliver digital health instruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSport itself is inherently interdisciplinary, encompassing fields such as exercise physiology and psychology. When analysing sports injury data with the school doctor, we observed a general lack of flexibility in one particular class, prompting us to incorporate stretching exercises into the curriculum.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE159 Enhancing Digital Health Literacy Through Interdisciplinary Learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI engage in exchanges with colleagues regarding digital health initiatives, such as sharing insights on fitness tracker usage during teaching and research group sessions, and discussing how to adapt teaching approaches based on data. I also collaborate with teachers from other subjects, for instance, discussing with mathematics teachers how to integrate fitness data into statistical teaching to enhance pupils' comprehensive skills.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eD32 Emphasis on collaborative expansion models for digital teaching resources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE142 Acquiring Digital Health Resources Through Industry-Academia Collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWe hope to enhance privacy protection technologies for digital health solutions and improve data security. We also hope that schools will enter into contracts with relevant parties to safeguard the privacy of students and staff, thereby preventing data misuse.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE143 Acquiring Digital Health Resources Through Inter-Institutional Collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOrganise student case studies in the classroom to explore digital health application scenarios (such as discrepancies in fitness app data); host seminars inviting experts to share technological developments while encouraging staff and students to exchange usage insights; conduct collaborative research with institutions and enterprises (e.g., \u0026lsquo;Practical Application of AI Motion Correction Systems in Basketball Instruction\u0026rsquo;) and share findings; attend academic conferences to deliver oral presentations on digital health teaching research and receive peer feedback.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExamples of 8 categories result\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConcepts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of labels\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eC1 Digital information processing and evaluation literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD1 Ability to access digital health information from multiple channels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD2 Capable of conducting information content evaluation and verification practices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD22 Possesses an intrinsic understanding of digital health literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD37 Capable of addressing issues encountered when using digital health tools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD38 Capable of enhancing digital health literacy through multiple avenues\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026hellip;\u0026hellip;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC8 Digital teaching technology requirements outlook and functional critique literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD27 Prospects for functional requirements of teaching tools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD39 Clear functional requirements for digital health tools in teaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. Axial coding\u003c/h2\u003e \u003cp\u003eAxial coding, which is the second and central stage of the coding process in grounded theory, involves reestablishing connections among the categories that were generated during open coding. This stage requires a detailed comparison and analysis of intercategory relationships to identify high-level primary categories. Through axial coding, three primary categories were identified, following the naming convention \u0026lsquo;BN\u0026thinsp;+\u0026thinsp;category name\u0026rsquo;: B1 Digital Health Awareness and Critical Literacy, B2 Digital Teaching Practice and Innovative Application Competence and B3 Digital Security Ethics and Environmental Awareness Competence (see Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEight categories derived from axis coding\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain Categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-Categories\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eB1 Digital Health Awareness and Critical Literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1 Digital Information Processing and Evaluation Literacy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC6 Critical Reflection and Digital Sustainability Literacy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC8 Digital Teaching Technology Requirements Outlook and Functional Critique Literacy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eB2 Digital Teaching Practice and Innovative Application Competence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC2 Digital Tool Application and Optimisation Competence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC3 Digital Instruction Monitoring and Data Analysis Competence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC5 Digital Collaboration and Resource Integration Competence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB3 Digital Security Ethics and Environmental Awareness Competence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC4 Data Security and Ethical Standards Competence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC7 Digital Instructional Environment and Implementation Feasibility Awareness\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3. Selective coding\u003c/h2\u003e \u003cp\u003eSelective coding represents the final stage of grounded theory analysis during which the \u0026lsquo;core category\u0026rsquo; is identified and systematically linked to all other categories. This stage involves validating intercategory relationships, integrating categories whose conceptualisation remains incomplete and elevating the analysis to a high level of abstraction. Building on the eight categories and the three primary categories generated through previous coding stages, continual comparison with the original data enabled the identification of the overarching core category: \u0026lsquo;Digital Health Literacy of Primary and Secondary School Physical Education Teachers\u0026rsquo;. This core category synthesises all labels, concepts, categories and subcategories that are developed throughout the coding process, thus providing an integrated and coherent representation of the phenomenon under investigation.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Theoretical saturation test\u003c/h2\u003e \u003cp\u003eA systematic theoretical saturation test was conducted to ensure the rigour and completeness of the theoretical framework (Naeem et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The purpose of this test was to determine whether the constructed Structural System of Digital Health Literacy for Physical Education Teachers sufficiently captured all essential categories and properties of the phenomenon. Consistent with qualitative research standards, theoretical saturation was defined as the point at which additional data no longer produced new concepts or category attributes.\u003c/p\u003e \u003cp\u003eFor validation, all interview transcripts were randomly divided into two sets: approximately 80% of the data served as the primary analytic corpus, while the remaining 20% were reserved as a saturation test sample. Coding of the validation sample in NVivo 15.0 revealed no new concepts, categories or relational structures. The existing model adequately accounted for all relevant information contained in the reserved data. These procedures confirm that the core theoretical construct developed in this study has reached saturation, thereby demonstrating strong completeness and methodological rigour (Saunders et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003eThe Digital Health Literacy Framework for Primary and Secondary School Physical Education Teachers comprises three dimensions, eight categories, 40 concepts and 214 statements (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) :\u003c/p\u003e \u003cp\u003e(a)Digital Health Awareness and Critical Literacy, including digital information processing and evaluation literacy, critical reflection and continuous development literacy and digital teaching technology requirements outlook and functional critique literacy;\u003c/p\u003e \u003cp\u003e(b)Digital Teaching Practice and Innovative Application Competence encompass digital tool application and optimisation in teaching, instructional monitoring and data analysis as well as digital collaboration and resource integration;\u003c/p\u003e \u003cp\u003e(c)Digital Security Ethics and Environmental Awareness Competence encompass awareness of data security and ethical standards competence alongside understanding of the digital instructional environment and implementation feasibility awareness.\u003c/p\u003e \u003cp\u003eThis structural framework illustrates that digital health literacy for primary and secondary school PE teachers represents a comprehensive professional competency system. It integrates three core dimensions, namely, cognitive critique, practical application and ethical environment, which collectively encompass eight essential competency domains and are operationalised through 40 specific capability indicators. The framework reflects the expanded professional requirements that are posed by the digital era and provides a systematic theoretical basis for the cultivation and assessment of PE teachers\u0026rsquo; digital health literacy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Digital health awareness and critical literacy\u003c/h2\u003e \u003cp\u003eThe dimension Digital Health Awareness and Critical Literacy represents the meta-competence that underpins the entire digital health literacy framework for PE teachers. It serves as the cognitive foundation through which teachers interpret, evaluate and respond to digital health information prior to any technical or pedagogical application (Evans, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This competence encompasses the ability to understand systematically, assess prudently and reflect critically on the value, credibility and limitations of digital health information and technologies. It enables teachers to move beyond passive information consumption towards active judgement that filters misinformation, bias and commercial health narratives (Wallace et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAligned with UNESCO\u0026rsquo;s conceptualisation of digital literacy, which positions critical thinking as a core component, this dimension highlights that digital competence extends beyond technical skills to include the ability to question, interpret and evaluate digital content (Nurfazri et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Accordingly, this competence positions teachers as gatekeepers of digital health information by equipping them to discern authenticity and assess the educational potential and risks that are associated with emerging technologies.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Digital information processing and evaluation literacy\u003c/h2\u003e \u003cp\u003eThe category Digital Information Processing and Evaluation Literacy constitutes the foundational skillset that enables PE teachers to navigate and utilise digital health resources effectively (Fletcher et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It refers to the ability to locate information systematically across diverse channels, such as academic databases, professional platforms and online courses, and assess its reliability, scientific validity and timeliness. This competence allows teachers to filter and translate complex digital content into accessible knowledge for school-based health education (Bezeau et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Given the prevalence of information overload, teachers must not only recognise authoritative sources but also distinguish pseudoscientific and commercially driven content. Without such discernment, educators risk inadvertently transmitting inaccurate information to students, thereby undermining their long-term health judgement (Zakharov et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, this competence requires ongoing engagement with current developments in the field and the use of various strategies, such as cross-verifying, assessing source credibility and comparing claims against established scientific principles.\u003c/p\u003e \u003cp\u003eOne teacher outlined their screening criteria: \u003cem\u003eWhen filtering digital health information, I adhere to standards of authority, timeliness and professionalism, prioritising research from government official releases, international authoritative organisations and university research institutions; ensuring information is published within the last three years\u003c/em\u003e (P12-2). Another educator shared their verification practice: \u003cem\u003eInformation encountered can be cross-verified. For instance, upon seeing data from a fitness app, I compare it against scientific standards in textbooks. Where uncertainty persists, I consult colleagues within the teaching research group for their perspectives\u003c/em\u003e (P2-4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Critical reflection and digital sustainability literacy\u003c/h2\u003e \u003cp\u003eThe category Critical Reflection and Digital Sustainability Literacy refers to teachers\u0026rsquo; capacity for the ongoing, systematic evaluation of their digital teaching practices, including assessing outcomes, identifying limitations and optimising processes. This competence supports teachers\u0026rsquo; long-term professional development by enabling them to adapt to evolving technological trends and avoid digital practices becoming outdated, fragmented or misaligned with learner needs (Wohlfart et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt also encompasses teachers\u0026rsquo; awareness of the need to update their digital health literacy continuously through professional training, academic exchange or self-directed learning. Teachers maintain a knowledge base that remains current and pedagogically relevant by actively monitoring emerging technologies and health trends. In this sense, teachers are positioned not merely as technology users but as reflective practitioners who iteratively refine their digital practices to sustain their professional competence in dynamic digital environments.\u003c/p\u003e \u003cp\u003e \u003cem\u003eIf a tool fails to yield results, one may adjust teaching methods by combining traditional and digital approaches\u003c/em\u003e (P3-12). Another educator emphasised the imperative of continuous learning: \u003cem\u003eAs physical education teachers, we must keep pace with the times. AI evolves so rapidly that those who fail to keep abreast will inevitably be left behind\u003c/em\u003e (P2-11). Regarding development pathways, one teacher suggested: \u003cem\u003eI believe we should first increase our exposure to these tools in daily practice, then participate in offline training to enhance collective awareness of digital health. Subsequently, we can pursue learning through diverse channels\u003c/em\u003e (P1-36).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Digital teaching technology requirements outlook and functional critique literacy\u003c/h2\u003e \u003cp\u003eThe category Digital Teaching Technology Requirements Outlook and Functional Critique Literacy refers to educators\u0026rsquo; ability to anticipate, articulate and critically evaluate the functional requirements of digital health tools in teaching contexts. This competence marks a shift from passive technology use towards actively shaping technological development to align with pedagogical principles and learner needs (Modra et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt involves specifying clear instructional requirements, critically assessing tool design, including privacy protection, algorithmic transparency and interface usability, and recognising how embedded system biases may influence learner data, behavioural nudging or access inequalities (Rosenbaum et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Grounded in classroom practice, educators are positioned to formulate expectations that extend beyond existing market offerings, thus contributing practitioner-informed critiques and recommendations. This outcome reflects a transition from technology adopters to collaborative contributors in digital tool development, thereby enhancing relevance and usability through pedagogical insight (Papić-Blagojević \u0026amp; Račić, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eIt is hoped that future fitness trackers will not only monitor heart rate but also integrate students\u0026rsquo; physical condition data to provide personalised rest recommendations (\u003c/em\u003ebased on summaries from P18-15). Concurrently, teachers demonstrated strong critical awareness particularly regarding privacy concerns: \u003cem\u003eAll educational apps must explicitly state how data is utilised.\u003c/em\u003e (This is nonnegotiable based on summaries from P9-19, P5-31, etc.). Some educators questioned the practical utility of such tools: \u003cem\u003eAdvanced digital health technologies like motion capture are better suited for professional team training... For most ordinary students, the focus should remain on physical fitness enhancement\u003c/em\u003e (P27-8).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Digital teaching practice and innovative application competence\u003c/h2\u003e \u003cp\u003eThe dimension Digital Teaching Practice and Innovative Application Competence represents the operational core of digital health literacy, where digital knowledge is translated into concrete pedagogical action within school settings (Kim et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It denotes teachers\u0026rsquo; ability to apply digital health tools, data and resources to design personalised instruction, integrate interdisciplinary activities and foster interactive and data-informed learning experiences. When effectively enacted, this competence enhances students\u0026rsquo; health literacy and their agency in managing health-related behaviours (Mancone et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAligned with the perspectives of the Organisation for Economic Co-operation and Development (OECD), digital competence is ultimately demonstrated not through tool usage alone but through the generation of innovative teaching practices and improved student learning outcomes (Zhang \u0026amp; Wu, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Therefore, this dimension underscores the transformation of digital capacity into pedagogically meaningful and outcome-oriented instructional practice.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Digital Tool Application and Optimisation Competence\u003c/h2\u003e \u003cp\u003eThe category Digital Tool Application and Optimisation Competence constitutes the foundational operational layer of digital teaching practice, which enables the translation of digital health concepts into concrete instructional actions and measurable learning outcomes (Gosak et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It refers to teachers\u0026rsquo; ability to select, evaluate and apply educational technology tools systematically in alignment with teaching goals and learner characteristics. This competence allows teachers to adapt digital tools to diverse learner profiles, such as differences in ability, motivation or learning styles, thereby enhancing instructional responsiveness and effectiveness (Yu \u0026amp; Ha, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It further includes designing tailored digital health programmes based on students\u0026rsquo; physical fitness, health status and interests to optimise teaching outcomes.\u003c/p\u003e \u003cp\u003e \u003cem\u003eWhen evaluating new digital health tools, we first conduct basic trials to test compatibility with school teaching equipment... followed by small-scale pilot implementations... observing student feedback, data accuracy and the extent to which it enhances teaching outcomes\u003c/em\u003e (P12-4). Personalised applications demonstrate rich diversity: \u003cem\u003eWe set \u0026lsquo;stepwise heart rate targets\u0026rsquo; (gradually increasing from 120 to 140 beats per minute) via smart wristbands for students with low fitness levels\u003c/em\u003e (P4-28); \u003cem\u003eDigital tools detect health data, identify issues and guide improvements; teaching adapts to individual needs based on physical assessment results\u003c/em\u003e (P4-11).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Digital instruction monitoring and data analysis competence\u003c/h2\u003e \u003cp\u003eThe category Digital Instruction Monitoring and Data Analysis Competence is essential for implementing precise and data-driven health education. It enables teachers to move from intuition-based to evidence-informed instructional decision-making, thus ensuring that pedagogical adjustments are grounded in measurable learning indicators (Blegur et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This competence involves using smart devices to collect real-time digital health data, such as heart rate or exercise load, during PE sessions, followed by quantitative analysis, visualisation and progress tracking at individual and group levels. Such data-driven feedback improves instructional accuracy and enhances students\u0026rsquo; self-awareness by enabling them to visualise their own health performance (Almusawi et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jastrow et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Jenny et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lupton, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It thereby supports instructional decisions and strengthens the shift from experience-based to data-driven teaching.\u003c/p\u003e \u003cp\u003e \u003cem\u003eDuring long-distance running training with pupils... pupils wear heart rate monitors. While running, they understand their performance metrics and appropriate heart rate levels, enabling them to adjust their pace based on real-time data\u003c/em\u003e (P2-12). Another teacher highlighted the role of data analysis in assessing student progress: \u003cem\u003eExamining specific metrics, such as improvements in 1000-metre times, alongside fatigue recovery data (e.g., post-exercise heart rate changes); one pupil\u0026rsquo;s 1000-metre time didn\u0026rsquo;t improve, but their heart rate recovered more quickly, indicating enhanced cardiorespiratory fitness\u003c/em\u003e (P4-19).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3 Digital collaboration and resource integration competence\u003c/h2\u003e \u003cp\u003eThe category Digital Collaboration and Resource Integration Competence serves as a vital means to expand the boundaries of health education and enhance teaching effectiveness. Through collaborative platforms, educators can codevelop digital health materials, exchange pedagogical strategies and collectively respond to emerging student health needs (Cabero-Almenara et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Valverde-Berrocoso et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xing \u0026amp; Qi, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It encompasses the ability to integrate and apply interdisciplinary teaching resources, actively participate in digital collaboration and knowledge sharing within professional communities and leverage home-school partnerships to implement digital collaborative practices. This competence embodies principles of systems thinking and open collaboration.\u003c/p\u003e \u003cp\u003eThe ability to integrate and apply teaching resources across disciplines represents a significant and new pedagogical approach in PE. \u003cem\u003ePhysical education itself is inherently interdisciplinary, encompassing fields such as exercise physiology and psychology. When analysing sports injury data with the school doctor, we identified a general lack of flexibility in one class and promptly incorporated stretching exercises into the curriculum\u003c/em\u003e (P4-22). Professional collaboration takes diverse forms: \u003cem\u003eWe exchange digital health experiences with peers and initiate \u0026lsquo;digital health workshops\u0026rsquo; within teaching groups to share insights on digital tool usage\u003c/em\u003e (P14-5). Home-school collaboration presents opportunities and challenges: \u003cem\u003ePhysical education teachers communicate infrequently with parents; our current strategy involves sharing vetted educational videos in parent groups... but we avoid recommending specific apps to prevent commercial disputes\u003c/em\u003e (P4-23).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Digital security ethics and environmental awareness competence\u003c/h2\u003e \u003cp\u003eThe dimension Digital Security Ethics and Environmental Awareness Competence provides the ethical and regulatory foundation for digital health literacy, thereby ensuring that technological applications in education remain compliant, secure and sustainable. This competence is critical for preventing data misuse, algorithmic bias and unintended psychological or behavioural risks within school environments (Anurogo et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Aydınlar et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Estrada et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rivera-Romero et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Grounded in the ethical principles of the EU\u0026rsquo;s General Data Protection Regulation (GDPR), it emphasises safeguarding student data, prioritising wellbeing and establishing clear accountability mechanisms to guide educators\u0026rsquo; and institutions\u0026rsquo; digital practices (Giuffrida \u0026amp; Hall, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Trindade et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Data security and ethical standards competence\u003c/h2\u003e \u003cp\u003eThis competence constitutes the ethical baseline for digital health practice, thus reflecting teachers\u0026rsquo; understanding of and ability to implement data management protocols, security safeguards and privacy requirements in educational contexts. It ensures that the integration of digital technologies does not infringe upon fundamental rights, particularly students\u0026rsquo; autonomy over their personal data and digital identities (Bećirović, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hu, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Huang, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Teachers demonstrate knowledge of key principles, such as data minimisation, anonymisation and encrypted storage, and are expected to act as responsible data stewards. Student health data are leveraged to enhance educational value while upholding stringent ethical standards.\u003c/p\u003e \u003cp\u003e \u003cem\u003eEnsuring student data security involves collecting only data directly relevant to teaching, avoiding sensitive information such as names and home addresses and using anonymous identifiers when interpreting fitness tracker data\u003c/em\u003e (P14-7). Another educator proposed specific measures: \u003cem\u003eAdhering to the principle of minimal data collection, gathering only health data essential for teaching, employing end-to-end encrypted tools for data storage and transmission and signing stringent data confidentiality agreements with third-party service providers\u003c/em\u003e (P11-7). Data misuse risks are also clearly recognised: \u003cem\u003eThe proliferation of digital health technologies may lead to the misuse of health data, such as commercial entities leveraging health monitoring to collect students\u0026rsquo; behavioural patterns and physical data for targeted advertising or precision marketing\u003c/em\u003e (P12-8).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Digital instructional environment and implementation feasibility awareness\u003c/h2\u003e \u003cp\u003eThis competence reflects teachers\u0026rsquo; practical awareness of the contextual conditions that are required for meaningful technology adoption; it emphasises that the integration of digital tools in PE must align with students\u0026rsquo; developmental readiness, curriculum requirements and pedagogical goals (Menescardi et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Saiz-Gonz\u0026aacute;lez et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Sorokolit et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Educators recognise that digital tool implementation is constrained by multiple objective factors and cannot occur uniformly across settings. They demonstrate sensitivity to identifying barriers, such as limited hardware infrastructure, budget restrictions, unstable network conditions and regional disparities; therefore, these factors underscore that effective technology integration depends on selecting tools that match the actual resources and circumstances of schools (Duffy et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Giebel et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gityamwi et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e\u003cem\u003e The fundamental contradiction is: parents prioritise their children\u0026rsquo;s basic needs over data privacy awareness... Shared devices among pupils are commonplace... Current baseline: resolutely avoid tools requiring facial recognition\u003c/em\u003e (P4-32). Another teacher highlighted economic and hardware barriers: \u003cem\u003eThe adoption of digital health technologies is constrained by school budgets; some well-funded institutions can equip themselves with smart devices... while underfunded schools can only utilise them during open lessons\u003c/em\u003e (P33-7). Additionally, disparities in teacher skills were identified as a factor: \u0026lsquo;Senior teachers learn at a slower pace\u0026rsquo; (P10-13) and \u0026lsquo;there is a need to enhance skills in operating digital tools\u0026rsquo; (D34).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Intrinsic logical connections amongst literacy dimensions: An interdependent organic system\u003c/h2\u003e \u003cp\u003eThe framework developed in this study demonstrates that digital health literacy among primary and secondary school PE teachers constitutes an integrated system rather than a simple aggregation of discrete dimensions. The three primary categories collectively form a coherent cognition\u0026ndash;practice\u0026ndash;assurance cycle.\u003c/p\u003e \u003cp\u003eDigital Health Awareness and Critical Literacy (B1) provides the cognitive foundation, which shapes teachers\u0026rsquo; judgement, interpretive depth and decision-making in the selection and use of digital health technologies.\u003c/p\u003e \u003cp\u003eDigital Teaching Practice and Innovative Application Competence (B2) represents the operational core, which involves translating cognitive insights into concrete pedagogical actions and generating measurable educational value.\u003c/p\u003e \u003cp\u003eDigital Security Ethics and Environmental Awareness Competence (B3) constitutes the regulatory and protective layer, which ensures that digital practices remain safe, ethical, contextually feasible and aligned with institutional constraints.\u003c/p\u003e \u003cp\u003eThese three dimensions are interdependent and mutually reinforcing. Without critical cognition (B1), digital practice (B2) risks becoming superficial or misaligned. Without practical competence (B2), cognitive understanding (B1) cannot be actualised. Without ethical and contextual safeguards (B3), innovative practices (B2) may become unsafe, inequitable or unsustainable.\u003c/p\u003e \u003cp\u003eAccordingly, future professional development for PE teachers should adopt a systematic approach that strengthens the coordinated development of all three dimensions, thus ensuring their integration into a comprehensive and sustainable digital health literacy framework (Duffy et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Giebel et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gityamwi et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Responding to the digital health education transformation: Redefining physical education teachers\u0026rsquo; professionalism\u003c/h2\u003e \u003cp\u003eAmidst the global shift towards educational digitalisation and the recognition of health literacy as a core 21st-century competency, the framework developed in this study directly responds to emerging expectations for advanced professionalism among PE teachers. It demonstrates that digital-era professionalism requires the integration of technological competence with health-oriented pedagogical judgement (Farias-Gaytan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ze et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTraditionally, PE teacher professionalism has emphasised athletic expertise and instructional techniques. However, this framework shows that in the digital age, professionalism is increasingly enacted through new roles, including critical evaluators of digital health information, data-informed instructional decision-makers and guides for ethical and responsible digital health behaviour. This development aligns with global policy directions, including the WHO\u0026rsquo;s call to embed health literacy across all policy domains and the OECD\u0026rsquo;s emphasis on preparing teachers as design agents who are capable of leading educational innovation (Ayre et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Monkman \u0026amp; Lesselroth, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; WHO, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These trends collectively highlight that teachers are now positioned as mediators of digital transformation and health promotion.\u003c/p\u003e \u003cp\u003e The framework repositions PE teachers from practitioners of physical training to integrated digital health educators who combine critical digital literacy, data-driven pedagogical practice and health ethics. It offers a theoretically grounded basis for redefining teacher professionalism in the digital era and provides actionable guidance for updating preservice preparation and revising standards for in-service professional development.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Theoretical framework and application prospects: Empowering professional development and driving international dialogue\u003c/h2\u003e \u003cp\u003eThe value of this framework lies in its dual function as an explanatory theoretical model and a practical tool for guiding capacity development. At an operational level, it provides education administrators, school leaders and teacher training institutions with a clear roadmap for strengthening teachers\u0026rsquo; digital health literacy. For Digital Health Awareness and Critical Literacy (B1), professional learning may focus on tracing digital health information sources, evaluating evidence quality and understanding data ethics. For Digital Teaching Practice and Innovative Application Competence (B2), project-based training can support teachers in designing interdisciplinary health units that integrate wearable technologies and data-informed instruction. For Digital Security Ethics and Environmental Awareness Competence (B3), programmes may incorporate privacy regulations, ethical case discussions and school-level digital environment assessments.\u003c/p\u003e \u003cp\u003eAt an academic level, the framework offers a shared conceptual foundation and potential basis for developing standardised measurement tools. It enables cross-national comparative research on PE teachers\u0026rsquo; digital health literacy, supports policy benchmarking and facilitates knowledge exchange across cultural contexts. Consequently, the framework contributes not only to enhancing professional development systems but also to promoting international dialogue on digital health education within the global PE community.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Research Limitations and Future Directions\u003c/h2\u003e \u003cp\u003eThis study has several limitations. Although grounded theory procedures were implemented rigorously, the broad scope of the research required a diverse sample. However, the resulting sample size may be limited. Given that the qualitative data were drawn from specific national and regional contexts, the universality and contextual variations of the proposed model require further validation across broad cultural and policy environments. Additionally, the framework developed for this research primarily presents a structural model of literacy. Future research should extend this work by constructing standardised assessment instruments for large-scale quantitative validation and examining how the framework\u0026rsquo;s dimensions interact to influence students\u0026rsquo; health literacy and health behaviours.\u003c/p\u003e \u003cp\u003eFuture studies may pursue several directions:\u003c/p\u003e \u003cp\u003e(1) longitudinal research to trace the developmental trajectory of this literacy framework across different stages of teachers\u0026rsquo; careers;\u003c/p\u003e \u003cp\u003e(2) design-based research to develop and evaluate professional development interventions grounded in the model;\u003c/p\u003e \u003cp\u003e(3) cross-national comparative studies to explore the similarities, differences and underlying mechanisms of digital health literacy development among PE teachers across diverse educational systems and cultural contexts.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study constructed a grounded, empirically derived framework for understanding digital health literacy among primary and secondary school PE teachers. The model reveals that teachers\u0026rsquo; digital health literacy is a multidimensional and interconnected system that encompasses critical digital awareness, innovative data-informed teaching practice and ethical\u0026ndash;contextual judgement. Together, these dimensions provide a coherent foundation for conceptualising how PE teachers navigate, apply and evaluate digital health technologies in educational settings.\u003c/p\u003e \u003cp\u003eThe framework offers a theoretical basis for strengthening teachers\u0026rsquo; professional development and integrating digital health literacy into PE policy and practice. It highlights the need for coordinated capacity building that simultaneously advances cognitive, practical and ethical competencies. As schools continue to respond to the challenges and opportunities of digital health, this framework contributes an evidence-informed direction for supporting teachers\u0026rsquo; evolving roles and promoting the healthy, holistic development of young people.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study received ethical approval from the Ethics Committee of Shanghai Normal University. This study was conducted in accordance with the Declaration of Helsinki. All participants provided informed consent prior to their involvement. They were informed of the study's purpose, procedures, and their right to withdraw at any time without consequence. Confidentiality and anonymity of all participants have been maintained throughout the research process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Youth Fund Project of the Ministry of Education's Humanities and Social Sciences [Grant Number: 18YJC890033].\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eYY: Conceptualization, Methodology, Investigation, Formal analysis, Data Curation, Writing \u0026ndash; Original Draft. WS: Writing \u0026ndash; Review \u0026amp; Editing, Validation, Supervision.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors extend their sincere gratitude to all primary and secondary school physical education teachers and higher education experts who participated in this study for their valuable time and insightful contributions.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe original data generated and analysed during this study are included in the article and its supplementary materials. Further datasets are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;s note\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll 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. 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Cogent Educ. 2025;12(1):2436706. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/2331186X.2024.2436706\u003c/span\u003e\u003cspan address=\"10.1080/2331186X.2024.2436706\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Digital health literacy, Digital Teaching Competence, Grounded theory, Physical Education Teachers, Data Ethics in Education","lastPublishedDoi":"10.21203/rs.3.rs-8908787/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8908787/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs digital technologies transform health information environments, digital health literacy has become a core professional competence for school-based health education. Physical education teachers play a critical role in shaping students\u0026rsquo; health behaviours. However, the structural composition of their digital health literacy remains undertheorised.This qualitative study used a grounded theory approach to conduct semistructured interviews with 34 participants from 12 provinces in China. Interview data were analysed with NVivo 15.0 through open, axial and selective coding, which was supplemented by relevant literature and policy documents. The analysis generated a Digital Health Literacy Framework for Primary and Secondary School PE Teachers comprising three core dimensions: Digital Health Awareness and Critical Literacy, Digital Teaching Practice and Innovative Application Competence and Digital Security Ethics and Environmental Awareness Competence. These dimensions were further operationalised through eight categories, 40 concepts and 214 empirical statements, thus reflecting a multilevel structure from information appraisal and data-informed teaching to ethical and contextual judgement. The proposed framework conceptualises PE teachers\u0026rsquo; digital health literacy as a systematic, interconnected competency system rather than a set of isolated skills. It provides a theoretical basis for designing assessment tools and targeted professional development and offers a reference point for international comparison and policy-making in digital health and PE.\u003c/p\u003e","manuscriptTitle":"Digital Health Literacy in School Physical Education: A Grounded Theory Framework for Teacher Competence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-07 10:03:59","doi":"10.21203/rs.3.rs-8908787/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"534e564f-86d7-468d-97e3-7c85aefed7ed","owner":[],"postedDate":"April 7th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T08:57:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-07 10:03:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8908787","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8908787","identity":"rs-8908787","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}