Understanding University Students’ Physical Activity Barriers Through the Theoretical Domains Framework and COM-B Model: A Qualitative Exploration

Understanding University Students’ Physical Activity Barriers Through the Theoretical Domains Framework and COM-B Model: A Qualitative Exploration | 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 Understanding University Students’ Physical Activity Barriers Through the Theoretical Domains Framework and COM-B Model: A Qualitative Exploration Kai Zhu, Xiaopeng Qiu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7391974/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 Purpose the present study qualitatively explored barriers to PA among Chinese university students with low activity levels, using the COM-B model and Theoretical Domains Framework (TDF). Methods Sixteen students were recruited through purposive and snowball sampling, screened using the International Physical Activity Questionnaire Short Form (IPAQ-SF). Semi-structured interviews, lasting 45–60 minutes, were conducted in Mandarin and analysed using framework analysis. Deductive coding was based on TDF domains, while inductive coding allowed new subthemes to emerge. Themes were mapped onto COM-B constructs and linked to potential intervention functions via the Behaviour Change Wheel (BCW). Results Barriers clustered across three domains. Capability barriers included limited exercise skills, narrow or inaccurate knowledge, and weak self-regulation. Opportunity barriers reflected environmental and social constraints, such as inflexible booking systems, limited facilities, and reliance on peers for coordination. Motivational barriers included ambivalent health beliefs, competing academic priorities, and mixed affective responses. Conclusions Chinese university students face a unique constellation of capability, opportunity, and motivational barriers that jointly suppress sustained PA engagement. Interventions should integrate skill-building, restructuring of institutional opportunities, and strategies to strengthen motivation, ensuring culturally and contextually sensitive approaches to behaviour change. Cultural Context College Student Gym ehealth Figures Figure 1 Introduction Regular physical activity is widely recognised as a cornerstone of physical and mental health across the lifespan (Arafa et al., 2024 ; Werneck et al., 2022 ). The World Health Organization (WHO, 2020) recommends that young people aged 18–24 years should engage in at least 150 minutes of moderate-intensity or 75 minutes of vigorous-intensity physical activity per week, along with muscle-strengthening activities on two or more days (Bull et al., 2020 ; WHO, 2021 ). However, the rapid development of the social economy and shifts in production modes and lifestyles have significantly reduced opportunities for adequate activity among young people (Pearce et al., 2022 ; Shimamoto, Suwa, & Mizuno, 2021 ). Increasingly sedentary routines, academic pressures, and technology-driven leisure behaviours contribute to insufficient physical activity, which has been linked to a range of adverse health outcomes (Chen et al., 2025 ; van Sluijs et al., 2021 ). These include heightened risks of obesity, cardiovascular disease, and metabolic disorders, as well as negative effects on mental health, such as elevated risk of depression and anxiety (Chen et al., 2025 ; Liu et al., 2024 ; Manyanga et al., 2019 ) The physical activity behaviours of contemporary college students are affected by many factors, including personal, environmental, and social factors, among others (Estrada-Araoz et al., 2025 ; Peterson, Frederick, & Bopp, 2025 ). Additionally, existing research suggests that the physical activity behaviour of college students is mainly affected by their behavioural intentions, health beliefs, behavioural attitudes, self- evaluations, self-efficacy, behavioural habits, social support, emotional experience, etc (Chen et al., 2025 ; Skinner, Teychenne, & Murphy, 2024 ). However, this type of research has seldom proposed targeted intervention strategies to improve the level of physical activity of college students based on the theory of healthy behaviour change (Brown et al., 2024 ; Ndupu et al., 2023 ). These theories should all reflect the mechanisms of action and change, and human cognition and behaviour can, in turn, be influenced by interventions based on these psychological theories (Atkins et al., 2017 ; Peterson, Frederick, & Bopp, 2025 ). The COM-B model is one of the healthy behaviour transformation models, which suggests that human behaviour (B) is the result of an interaction between the individual’s physical and mental abilities (C) and that social and environmental factors, through motivation (M) and opportunity (O), influence the change in behaviour. The TDF simplifies and integrates a large number of behaviour change theories, thus including 14 domains and 84 components (Susan Michie, 2011 ). While Brown et al. ( 2024 ) have synthesised key influences on university students’ physical activity using the COM-B model and TDF, most existing research has been conducted in Western or Middle Eastern contexts. Such studies have primarily identified general determinants such as time constraints, workload, and access to facilities. Recent studies highlight that Chinese university students generally fail to achieve recommended levels of physical activity, with only around one-third meeting established guidelines (Guo, Wang, & Koh, 2022 ; Liu et al., 2022 ). However, much of this work is descriptive, offering prevalence data but little theory-driven insight into how cultural norms, institutional structures, and psychosocial dynamics interact to shape students’ engagement in physical activity. This underscores the need for contextually grounded, theoretically informed qualitative research to better understand the barriers faced by Chinese undergraduates (Liu et al., 2022 ).. Building on this gap, our study applies the TDF and COM-B model in a qualitative exploration to investigate barriers to physical activity among Chinese university students. By moving beyond descriptive accounts, this approach enables the identification of culturally and context-specific barriers embedded within the university setting, such as rigid booking systems for campus sports facilities, social comparison pressures related to body weight and appearance, and the tension between heavy academic workload and parental expectations. Methods Study Design This qualitative study employed a theory-informed design to explore barriers to physical activity among university students with low activity levels. Initially, a screening process was conducted to identify potential participants. The International Physical Activity Questionnaire–Short Form (IPAQ-SF) was administered to measure participants’ self-reported physical activity over the previous seven days. Students whose total physical activity levels fell within the Low category according to the IPAQ scoring protocol were considered eligible (Committee, 2005 ). Those meeting this criterion were invited to take part in the qualitative interviews. A qualitative descriptive approach was adopted to capture participants’ lived experiences and perceptions in rich detail, while theoretical guidance from the COM-B model and the Theoretical Domains Framework (TDF) informed the development of the interview guide and the analytic framework. The study adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) 32-item checklist to ensure methodological transparency and rigour. Data collection took place between September 2022 and June 2023. This study was approved by the Ethics Committee of Guilin University of Electronic Technology (JGC202017). Written informed consent was obtained from all participants prior to their involvement in the research. Physical activity measurement Physical activity levels were assessed using the International Physical Activity Questionnaire–Short Form (IPAQ-SF), a 7-item instrument designed to capture the frequency (days per week) and duration (minutes per day) of walking, moderate-intensity, and vigorous-intensity physical activities, as well as sedentary behaviour, over the previous seven days (Craig et al., 2003 ; Lee, Macfarlane, et al., 2011 ). This classification method has been widely validated in diverse populations and is recommended for international surveillance of physical activity (Lee, Yu, et al., 2011 ; Wang, Chen, & Zhuang, 2013 ). The IPAQ-SF records participants’ physical activity during the previous seven days through seven items covering vigorous-intensity activity (VPA, e.g., running, aerobics), moderate-intensity activity (MPA, e.g., cycling, recreational swimming), and walking, along with sedentary behaviour (sitting time). For each activity category, participants reported the number of days and the average minutes per day they engaged in that activity. Weekly energy expenditure was calculated in MET-minutes/week by multiplying the activity-specific MET values—8.0 METs for VPA, 4.0 METs for MPA, and 3.3 METs for walking—by the self-reported duration (minutes) and frequency (days). The total physical activity score was obtained by summing the three categories. Participants were then classified into three levels of physical activity following the IPAQ scoring protocol (IPAQ Committee, 2005 ): High (VPA on ≥ 3 days achieving ≥ 1500 MET-minutes/week, or ≥ 7 days of any activity combination totalling ≥ 3000 MET-minutes/week); Moderate (VPA on ≥ 3 days for ≥ 20 minutes/day, or MPA/walking on ≥ 5 days for ≥ 30 minutes/day, or any activity combination on ≥ 5 days totalling ≥ 600 MET-minutes/week); and Low (not meeting the criteria for Moderate or High) (Committee, 2005 ; Wang, Chen, & Zhuang, 2013 ). Theoretical Framework The study was underpinned by two complementary behaviour change frameworks: the TDF and the COM-B model. The TDF consolidates constructs from 33 behaviour change theories into 14 domains and 128 constructs, providing a comprehensive taxonomy of behavioural determinants (Atkins et al., 2017 ; James Cane, 2011 ; Susan Michie, 2011 ). The COM-B model posits that behaviour (B) results from the interaction between Capability (C), Opportunity (O), and Motivation (M) (Michie et al., 2011). Capability includes both physical skills and psychological processes; opportunity comprises environmental and social factors; and motivation involves reflective and automatic processes. Embedding the TDF within the COM-B structure facilitates both detailed identification of determinants and high-level behavioural system mapping. The combined use of COM-B and TDF also supports subsequent application of the Behaviour Change Wheel (BCW) to identify appropriate intervention functions. It has been successfully applied in recent qualitative research exploring barriers and facilitators to physical activity in various populations (Brown et al., 2024 ; Ndupu et al., 2023 ) that shown in Fig. 1: (Susan Michie, 2011 ). Participants and Recruitment Participants were recruited through purposive sampling following an initial screening of physical activity levels using the International Physical Activity Questionnaire Short Form (IPAQ-SF). The questionnaire identified students whose physical activity level was categorised as Low according to the IPAQ scoring protocol, that is, they did not meet the criteria for Moderate or High activity. Eligible students were subsequently invited to take part in the study. Recruitment sought to achieve diversity in gender, academic discipline, and year of study. Snowball sampling was also employed to identify additional eligible participants. Data saturation was determined when no new codes emerged in two consecutive interviews. In total, sixteen students (6 males, 10 females) participated in the study. Detailed characteristics of each participant are provided in Supplementary Material 1. Data Collection Semi-structured, in-depth interviews lasting 45–60 minutes were conducted using a pre-tested interview guide developed from TDF domains mapped to COM-B constructs (Cane et al., 2012; Michie et al., 2011). The guide covered topics including current physical activity behaviours, perceived barriers and facilitators, knowledge and beliefs about exercise, social influences, and environmental context (Table 1 ). All interviews were audio-recorded with informed consent, transcribed verbatim in Mandarin within 24 hours, and cross-checked against the recordings for accuracy. Pilot testing with two students enabled refinement of wording to improve clarity and flow, consistent with recommendations for developing culturally sensitive qualitative protocols (Kallio et al., 2016). Data Analysis Data were analysed using framework analysis, a systematic and flexible approach for applied health research (Bryman & Burgess, 1994 ; Gale et al., 2013 ). This method facilitated both deductive and inductive coding: deductive coding employed the TDF as an a priori framework, while inductive coding allowed new subthemes to emerge from participants’ narratives (Atkins et al., 2017 ; Byrne, 2022 ; Gale et al., 2013 ). The analytic process involved three iterative stages: Open coding – generating initial codes from raw data, resulting in 11 subcategories. Axial coding – clustering related subcategories into six higher-order categories. Selective coding – integrating categories into three overarching COM-B constructs: Capability, Opportunity, and Motivation. Two researchers independently coded transcripts in NVivo 12 (QSR International), meeting regularly to resolve discrepancies. Divergent coding decisions were discussed with a senior researcher until consensus was reached, enhancing dependability (Olmos-Vega et al., 2023 ). Finally, emergent determinants were mapped onto intervention functions using the Behaviour Change Wheel framework (Flannery et al., 2018 ; Gale et al., 2013 ; Susan Michie, 2011 ). Rigour and Trustworthiness We adhered to LINCOLN and Guba ( 1985 ) four criteria for establishing trustworthiness in qualitative research. Credibility was enhanced through member checking, where participants reviewed summaries of findings to confirm accuracy (Urry, Chur-Hansen, & Scholz, 2024 ). Transferability was supported by detailed description of the research context, sampling procedures, and participant characteristics. Dependability and confirmability were strengthened via peer debriefing within the research team and the maintenance of an audit trail documenting analytic decisions (Braun & Clarke, 2019 , 2020 ). Reflexivity was addressed through the use of reflexive journaling, with researchers documenting assumptions and potential biases throughout data collection and analysis (McLeod, 2024 ). Table 1 Semi-structured interview items of the TDF embedded into the COM-B model TDF Items Capability Knowledge Do you know what kind of exercise that behavior college students should maintain every week? Do you know how exercise can improve your health? Capability (physical) Are you confident in participating in sports? Capability (psychological) If you want to keep exercising, what will you do? Opportunity Physical Skills Environmental Context and Resources Are there any sports you are particularly good at? What kind of support does your environment need to provide you to want to participate in sports? Will your exercise behavior be influenced by sports facilities and resources? Social Influences Is your exercise behavior influenced by school, parents, friends? Motivation Goals Beliefs about Capability What situation makes you exercise? Do you have the confidence to stick to sports? Beliefs about Consequences How will your physical activity be affected by COVID-19? Sixteen students participated in the study (6 males, 10 females), participant characteristics was in Table 2 . Analysis generated a theory-informed account of barriers to physical activity, organised around the COM-B components, with inductive themes mapped to TDF domains (Table 3 ). While node counts were used descriptively to indicate relative salience, interpretation prioritised the depth and coherence of participants’ accounts. Table 2 Survey participant characteristics (n = 16) Category Mean (SD) n (%) Age (years) 20.94 (SD = 0.85) BMI (kg/m²) 22.90 (SD = 2.30) Gender Male 6 (37.5%) Female 10 (62.5%) Year of Study Year 1 4 (25.0%) Year 2 4 (25.0%) Year 3 4 (25.0%) Year 4 4 (25.0%) BMI Classification Normal 12 (75.0%) Overweight 3 (18.8%) Underweight 1 (6.2%) Smoking Status No 14 (87.5%) Yes 2 (12.5%) Alcohol Consumption No 11 (68.8%) Yes 5 (31.2%) Self-rated Health Good 10 (62.5%) Fair 3 (18.8%) Excellent 3 (18.8%) Note. BMI classification based on WHO criteria: Underweight (< 18.5 kg/m²), Normal (18.5–24.9 kg/m²), Overweight (25.0–29.9 kg/m²), Obese (≥ 30 kg/m²). Table 3 Open-Encoded Content from the Semi-Structured Interviews Interview Content (initial concept) Conceptualization 15 01 01 Obesity is bad for your health, it affects your constitution, and it's bad for your image. What I know is that when we exercise, we actually sweat. I don't have a professional coach who has specific guidance for us to exercise, so we sweat. We think sweating can achieve the effect of fat loss, so we think it's ok. I have learned about a series of healthy diet in daily life. I usually eat a vegetarian diet. In the morning, I usually eat crude fibber and high-protein food for breakfast, such as eggs, purple potato, corn and vegetables, but sometimes I also eat other high-sugar food, but seldom eat high calorie food. Exercise knowledge 09 1 16 When I was losing weight, sometimes I did not lose weight. Then he would do a lot of analysis for me, and then he would make recipes and training plans for me, tell me what to eat and do every day, and some other things about how to lose weight in the most efficient way through scientific exercise. Everyone knows about the exercise software Keep. I use it to do some aerobic exercises to lose weight. During that period of time, I insisted on doing aerobics and running, but there was still a little change. His body-shaping effect was quite good, and then I came back from a holiday, and I did not insist on doing it. It was not OK to do any exercise again. self-monitoring 01 04 I like playing badminton, but without a partner, what can I do alone? My parents and classmates encourage me to keep doing sports. Peers’ role 07 16 I would take my friends out for a walk every week, because we need to walk the dog, and my friends need to walk the dog so we would go out for a walk, like three or four days a week, like walking the dog. I really like taekwondo and aerobics class. First of all, taekwondo and aerobics class are very interesting. Then the calisthenics teacher will teach you a lot of things, and then it will be fun to warm you up in class. Coaches’ role 16 My parents will urge me to exercise, in the case that I gain weight, and then they think it is not good for health to stay at home every day, not to exercise, supervise me to go running, and walk with them. Parents’ role 07 12 I think sports is to have special sports venues, our fitness equipment only in the community, and then there is almost no special track, these places can run very few, because there are more cars in the street, traffic lights are also more, these sports venues are a little far from my home. When I was losing weight, sometimes I did not lose weight. Then he would do a lot of analysis for me, and then he would make recipes and training plans for me, tell me what to eat and do every day, and some other things about how to lose weight in the most efficient way through scientific exercise. Exercise resources 01 05 Physical health is certainly important, but I think that the kind of body is I like sports, I think I can have one day, but not necessarily to achieve that kind of body builder, like bodybuilders I think is not very good, I want to have a healthy body, as long as they look very healthy. I think physical exercise is important, it can make the physical quality better, and then keep the mental energy is more energetic. Health beliefs 04 After the kind of physical exercise sweating let me feel particularly comfortable, can release the pressure, the body and mind will become a little lighter. Emotional beliefs Table 3 shows the main barriers and influencing factors of college students’ sports behaviour. Higher node numbers indicate that more related content was mentioned in the interview data. Table 4 Corresponding relationships and connotations of the main categories and sub-categories Main category Sub-category Number of nodes Physical Capability Physical skills 12 Psychological Capability Exercise knowledge Self-monitoring 9 14 Health Beliefs Mental health Physical health 6 45 Culture Schools’ role 6 Environmental Context and Resources Public Sports policy Exercise resources 1 55 Social Influences Coaches’ role Peers’ role 3 25 Parents’ role 16 As shown in Table 4 , the main influencing factors of college students’ motor behaviour disorders were sports resources (55), physical health beliefs (45), the role of friends (25), the role of family (16), self-monitoring (14), motor skills (12), and motor knowledge (9). Conversely, mass sports policy, the role of teachers, and school factors had little influence on college students’ physical activity behaviour disorders. Capability — Physical and Psychological As shown in Table 3 , Theme 1 (Skills and Technique Knowledge), students described practical skill gaps that undermined their confidence to start or sustain activity. Technique knowledge was narrow and often shaped by ad-hoc online content rather than systematic instruction (P01, P05), with some equating “sweating” with “effective exercise” (P08), indicating a superficial procedural understanding. In Table 3 , Theme 2 (Self-regulatory Strategies), self-regulation was typically fragile: goals were vague, monitoring inconsistent, and relapse after breaks common. Students described difficulty re-initiating routines following exams or holidays (P09, P13). The coded dataset showed capability-related material clustering under skills (n = 12), exercise knowledge (n = 9), and self-monitoring (n = 14), reflecting under-developed skills and self-management. These themes aligned with the TDF domains Skills, Knowledge, and Behavioural Regulation (Table 4 ), highlighting how limited capability directly impeded sustained physical activity engagement. Opportunity — Environmental Context, Resources and Social Influences Barriers related to environmental context and resources were the most frequently referenced across the data. As shown in Table 3 , Theme 3 (Environmental Constraints), students cited limited or inconvenient facilities, distance to venues, safety concerns, and inflexible booking systems (P07, P11). Resource-related accounts (n = 55) were often interlinked with academic time pressure (Table 4 ). Social influences (Table 3 , Theme 4) were nuanced. Peers were the most influential interpersonal factor (n = 25), acting as both facilitators (companionship, shared routines) and barriers (coordination failures, social comparison) (P04, P06). Parental and teacher influences (n = 16 and n = 3, respectively) (Table 4 ) were generally encouraging but less directly involved (P02, P14). These opportunity-related themes mapped to the TDF domains Environmental Context and Resources and Social Influences (Table 4 ), demonstrating that physical access barriers often co-occurred with social coordination challenges, undermining participation even when students expressed willingness to engage. Motivation — Beliefs, Goals and Affect Motivational barriers centred on health beliefs, competing priorities, and affective responses. In Table 3 , Theme 5 (Health Beliefs and Perceived Consequences), students generally endorsed the health benefits of physical activity, but perceived susceptibility and severity were not always translated into sustained intentions (P04, P12). Academic load and fatigue frequently displaced exercise from daily priorities. In Table 3 , Theme 6 (Affective Responses), emotions shaped engagement in both directions: while some reported stress relief and improved mood post-exercise (P04, P10), others anticipated discomfort, embarrassment, or inefficiency, which reduced motivation (P12). Health-belief-related material was the second most frequent cluster (n = 45) (Table 4 ), underscoring the central but ambivalent role of beliefs in shaping behaviour. These themes corresponded to TDF domains Beliefs about Consequences, Goals, and Emotion (Table 4 ), illustrating how motivation fluctuated with contextual pressures and emotional states. Integration of Themes via TDF and COM-B Mapping inductive themes to TDF domains (Table 4 ) clarified leverage points for change. Capability themes aligned with Skills, Knowledge, and Behavioural Regulation; Opportunity themes with Environmental Context and Resources and Social Influences; Motivation themes with Beliefs about Consequences, Goals, and aspects of Emotion and Social/Professional Role and Identity. The integration highlighted that environmental constraints and peer dynamics frequently co-occurred with fragile self-regulation and ambivalent health beliefs, limiting sustained engagement even among students positively disposed toward activity. Discussion This study applied the COM-B model and the Theoretical Domains Framework (TDF) to qualitatively explore barriers to physical activity among Chinese university students with low levels of exercise participation. By combining inductive thematic analysis with theory-driven mapping, we identified an interlocking set of determinants spanning Capability, Opportunity, and Motivation. Capability-related barriers included insufficient physical skills, narrow and sometimes inaccurate exercise knowledge, and weak self-regulatory strategies. Opportunity barriers were shaped by environmental constraints (e.g., lack of accessible facilities, inflexible booking systems), resource limitations (e.g., time pressures from academic demands), and social influences, particularly peer availability and coordination. Motivational barriers involved ambivalent health beliefs, competing academic priorities, and mixed affective responses to activity. Notably, university students with low physical activity levels face an interconnected set of capability, opportunity, and motivation barriers, where environmental constraints and peer dynamics exacerbate underdeveloped skills, fragile self-regulation, and ambivalent health beliefs, collectively limiting sustained engagement in physical activity. Physical activity barriers in Chinese college students This chain of barriers reflects the tight interdependence of capability, opportunity, and motivation in the COM-B framework. Unlike much Western research that highlights generic constraints such as workload and facility access, our findings underscore context-specific obstacles within Chinese universities: rigid facility booking systems, the cultural salience of body image comparison, and the persistent tension between self-care and parental expectations for academic success. These culturally embedded dynamics amplify motivational ambivalence and self-regulatory fragility, demonstrating how institutional and social environments actively shape health behaviours. Despite widespread awareness of the health benefits of physical activity, our participants described a recurring cycle of “intention, obstruction, and withdrawal.”. Students wanted to exercise, but heavy academic schedules and inflexible campus systems squeezed opportunities, leaving them discouraged when plans repeatedly failed (Journal of Physical & Health, 2025; Neill et al., 2025 ). This erosion of opportunity in turn weakened self-regulation, undermined confidence in their ability to sustain routines, and fuelled ambivalent beliefs valuing activity in principle but questioning its efficiency or worth in practice (Bjornara et al., 2021 ; Tanksale et al., 2021 ). Over time, these psychological tensions, reinforced by peer dynamics and social comparison pressures, made physical activity a fragile and easily abandoned behaviour. Importantly, the mapping of these barriers to TDF domains highlights concrete points for intervention. Building capability will require structured opportunities for skills practice and strategies such as action planning. Expanding opportunity means more than building gyms; it calls for system-level changes to scheduling, affordability, and accessibility (Rhodes, Zhang, & Zhang, 2020 ; Wiium & Safvenbom, 2019 ). Strengthening motivation involves addressing both reflective beliefs and emotional experiences, which could be supported through peer-led initiatives and digital tools that deliver just-in-time encouragement during periods of academic strain (Au et al., 2024 ; Chen et al., 2025 ). By telling this more integrated story of why students fail to be active, our study not only enriches theoretical understanding but also charts a pathway toward culturally sensitive and structurally informed solutions (Chen et al., 2025 ; Guo, Wang, & Koh, 2022 ; Liu et al., 2022 ). Practical implications for intervention design Our findings suggest that interventions to promote physical activity among university students should adopt a multi-component approach that concurrently targets capability, opportunity, and motivation. Building capability could involve structured skills instruction, clear technique standards, and the integration of self-regulation strategies such as action planning and self-monitoring (Bentley et al., 2019 ; Flannery et al., 2018 ). Restructuring opportunity may require expanding accessible low-cost facilities, streamlining booking systems, and protecting dedicated time slots for activity, as recommended by recent systematic reviews (Chen et al., 2025 ; Guo, Wang, & Koh, 2022 ). To address motivational barriers, peer-led programs could be combined with individualised plans to ensure participation is not solely contingent on social coordination, while digital health interventions and just-in-time adaptive interventions (JITAIs) could deliver timely prompts and feedback during academically demanding periods (Ndupu et al., 2023 ; Skinner, Teychenne, & Murphy, 2024 ). Practical Implications The findings of this study have several practical implications for the design and implementation of university-based physical activity promotion strategies, particularly for students with low activity levels. First, the clear mapping of barriers to the COM-B components and TDF domains highlights the need for multi-component interventions that simultaneously address Capability, Opportunity, and Motivation, rather than isolated behaviour determinants. For example, integrating skill-development workshops and structured exercise orientation sessions into university health programmes could strengthen students’ procedural knowledge and self-regulatory strategies, directly enhancing physical capability. Second, the environmental and social opportunity constraints identified, such as limited facility access, inconvenient booking systems, and unstable peer coordination, suggest that structural changes are required alongside individual-level interventions. Universities could improve facility scheduling flexibility, offer more on-campus activity options during peak academic periods, and facilitate peer-matching platforms that connect students with compatible routines. Such changes would reduce logistical barriers while stabilising the positive aspects of peer influence, which our findings show can act as both facilitators and inhibitors of engagement. Third, addressing motivational ambivalence requires interventions that go beyond health education to target students’ affective responses to exercise. Embedding short, enjoyable activity bouts within the academic day, offering non-competitive activity formats, and promoting immediate psychological benefits (e.g., stress relief, mood enhancement) may help reframe physical activity as a valued and rewarding element of daily life, even under high academic pressure. This aligns with dual-process models suggesting that behaviour change is more sustainable when both reflective intentions and automatic affective processes are positively reinforced. Finally, our study underscores the importance of culturally and contextually tailored interventions for Chinese university students, a group underrepresented in existing COM-B/TDF applications. By situating behaviour change strategies within students’ academic schedules, social norms, and campus infrastructure, universities can create supportive ecosystems that normalise and integrate physical activity into everyday student life. Such an approach not only addresses immediate participation barriers but also fosters long-term behaviour patterns that support mental and physical health beyond the university years. Conclusions This study has several strengths. First, it is one of the few qualitative investigations to apply the COM-B model and Theoretical Domains Framework (TDF) to explore barriers to physical activity among Chinese university students with low activity levels. The explicit theoretical integration strengthened the explanatory depth of the findings and provided a clear basis for targeted intervention design. Second, participant recruitment was informed by objective screening using the International Physical Activity Questionnaire–Short Form (IPAQ-SF), ensuring that the sample met clearly defined low-activity criteria. Third, methodological rigour was maintained through adherence to the COREQ 32-item checklist, triangulation of data sources, and deviant case analysis, which enhanced the credibility and trustworthiness of the thematic interpretations. Finally, purposive sampling ensured diversity across gender, academic discipline, and year of study, allowing the analysis to capture a range of perspectives within the target population. However, some limitations should be acknowledged. First, the study relied on self-reported physical activity data from the IPAQ-SF for participant screening, which is subject to recall and social desirability bias. Although the IPAQ-SF is widely used and validated, objective accelerometer data would have further strengthened activity classification. Second, while the sample size was appropriate for qualitative research and data saturation was achieved, findings may not be generalisable to all Chinese university students, particularly those in rural or less resourced institutions. Third, the cross-sectional design captures perceptions at a single point in time, limiting insights into how barriers and facilitators might evolve over the academic year or in response to life transitions. Finally, the study primarily focused on students with low physical activity levels; therefore, comparisons with students meeting activity guidelines were not possible, which might have provided additional explanatory contrast. Declarations Author Contribution K.Z. conceptualised the study, collected and analysed the data, and drafted the initial manuscript.X.Q. supervised the study design and methodology, contributed to the interpretation of findings, and critically revised and edited the manuscript.All authors reviewed and approved the final version of the manuscript and agree to be accountable for all aspects of the work. Acknowledgement The authors thank all participating students for their valuable contributions. Data Availability The qualitative interview data that support the findings of this study are not publicly available due to confidentiality agreements with participants. An anonymised version of the dataset may be made available from the corresponding author (X.Q.) upon reasonable request. References Arafa, A., Yasui, Y., Kokubo, Y., Kato, Y., Matsumoto, C., Teramoto, M., Nosaka, S., & Kogirima, M. (2024). 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Prevalence and correlates of adherence to movement guidelines among urban and rural children in Mozambique: a cross-sectional study. International Journal of Behavioral Nutrition and Physical Activity , 16 (1). https://doi.org/doi:10.1186/s12966-019-0861-y WE - Science Citation Index Expanded (SCI-EXPANDED) McLeod, S. (2024). Narrative analysis in qualitative research. Simply Psychology . Ndupu, L. B., Staples, V., Lipka, S., Faghy, M., Bessadet, N., & Bussell, C. (2023). Application of theoretical domains framework to explore the enablers and barriers to physical activity among university staff and students: a qualitative study. BMC PUBLIC HEALTH , 23 (1), 670. https://doi.org/10.1186/s12889-023-15588-w Neill, R. D., Lloyd, K., Best, P., & Tully, M. A. (2025). School-based mental health interventions: a feasibility study of the R.E.A.C.T. programme. Irish Educational Studies , 1-21. https://doi.org/10.1080/03323315.2024.2441172 Olmos-Vega, F. M., Stalmeijer, R. 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Ann Behav Med , 54 (7), 495-509. https://doi.org/10.1093/abm/kaz068 Shimamoto, H., Suwa, M., & Mizuno, K. (2021). Relationships between Depression, Daily Physical Activity, Physical Fitness, and Daytime Sleepiness among Japanese University Students. Int J Environ Res Public Health , 18 (15). https://doi.org/10.3390/ijerph18158036 Skinner, G., Teychenne, M., & Murphy, J. (2024). Barriers and facilitators to engaging in a university-based exercise programme delivered to students experiencing mental health difficulties: A pilot study. Cogent Mental Health , 3 (1), 1-29. https://doi.org/10.1080/28324765.2024.2380500 Susan Michie, M. M. v. S. a. R. W. (2011). The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Science . Tanksale, R., Sofronoff, K., Sheffield, J., & Gilmour, J. (2021). Evaluating the effects of a yoga-based program integrated with third-wave cognitive behavioral therapy components on self-regulation in children on the autism spectrum: A pilot randomized controlled trial. Autism , 25 (4), 995-1008. https://doi.org/http://dx.doi.org/10.1177/1362361320974841 Urry, K., Chur-Hansen, A., & Scholz, B. (2024). From member checking to collaborative reflection. van Sluijs, E. M. F., Ekelund, U., Crochemore-Silva, I., Guthold, R., Ha, A., Lubans, D., Oyeyemi, A. L., Ding, D., & Katzmarzyk, P. T. (2021). Physical activity behaviours in adolescence: current evidence and opportunities for intervention. Lancet , 398 (10298), 429-442. https://doi.org/10.1016/S0140-6736(21)01259-9 Wang, C., Chen, P., & Zhuang, J. (2013). Validity and reliability of international physical activity questionnaire–short form in Chinese youth. Research quarterly for exercise and sport , 84 (sup2), S80-S86. Werneck, A. O., Vancampfort, D., Stubbs, B., Silva, D. R., Cucato, G. G., Christofaro, D. G. D., Santos, R. D., Ritti-Dias, R. M., & Bittencourt, M. S. (2022). Prospective associations between multiple lifestyle behaviors and depressive symptoms. J Affect Disord , 301 , 233-239. https://doi.org/10.1016/j.jad.2021.12.131 WHO. (2021). WHO Guidelines on Physical Activity and Sedentary Behaviour 2020. Geneva, Switzerland: World Health Organization . Retrieved 2 June from https://www.who.int/publications/i/item/9789240015128 Wiium, N., & Safvenbom, R. (2019). Participation in Organized Sports and Self-Organized Physical Activity: Associations with Developmental Factors. Int J Environ Res Public Health , 16 (4). https://doi.org/10.3390/ijerph16040585 Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":421506,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7391974/v1/3c743712792e8ac791207265.png"},{"id":105048676,"identity":"676925dd-5146-413a-853b-17c78f05bcef","added_by":"auto","created_at":"2026-03-20 09:41:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1162556,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7391974/v1/dcba6bd7-7735-4e04-a1ec-60c7e22249d9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding University Students’ Physical Activity Barriers Through the Theoretical Domains Framework and COM-B Model: A Qualitative Exploration","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRegular physical activity is widely recognised as a cornerstone of physical and mental health across the lifespan (Arafa et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Werneck et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The World Health Organization (WHO, 2020) recommends that young people aged 18\u0026ndash;24 years should engage in at least 150 minutes of moderate-intensity or 75 minutes of vigorous-intensity physical activity per week, along with muscle-strengthening activities on two or more days (Bull et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; WHO, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, the rapid development of the social economy and shifts in production modes and lifestyles have significantly reduced opportunities for adequate activity among young people (Pearce et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Shimamoto, Suwa, \u0026amp; Mizuno, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Increasingly sedentary routines, academic pressures, and technology-driven leisure behaviours contribute to insufficient physical activity, which has been linked to a range of adverse health outcomes (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; van Sluijs et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These include heightened risks of obesity, cardiovascular disease, and metabolic disorders, as well as negative effects on mental health, such as elevated risk of depression and anxiety (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Manyanga et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe physical activity behaviours of contemporary college students are affected by many factors, including personal, environmental, and social factors, among others (Estrada-Araoz et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Peterson, Frederick, \u0026amp; Bopp, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Additionally, existing research suggests that the physical activity behaviour of college students is mainly affected by their behavioural intentions, health beliefs, behavioural attitudes, self- evaluations, self-efficacy, behavioural habits, social support, emotional experience, etc (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Skinner, Teychenne, \u0026amp; Murphy, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, this type of research has seldom proposed targeted intervention strategies to improve the level of physical activity of college students based on the theory of healthy behaviour change (Brown et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ndupu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These theories should all reflect the mechanisms of action and change, and human cognition and behaviour can, in turn, be influenced by interventions based on these psychological theories (Atkins et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Peterson, Frederick, \u0026amp; Bopp, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The COM-B model is one of the healthy behaviour transformation models, which suggests that human behaviour (B) is the result of an interaction between the individual\u0026rsquo;s physical and mental abilities (C) and that social and environmental factors, through motivation (M) and opportunity (O), influence the change in behaviour. The TDF simplifies and integrates a large number of behaviour change theories, thus including 14 domains and 84 components (Susan Michie, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile Brown et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) have synthesised key influences on university students\u0026rsquo; physical activity using the COM-B model and TDF, most existing research has been conducted in Western or Middle Eastern contexts. Such studies have primarily identified general determinants such as time constraints, workload, and access to facilities. Recent studies highlight that Chinese university students generally fail to achieve recommended levels of physical activity, with only around one-third meeting established guidelines (Guo, Wang, \u0026amp; Koh, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, much of this work is descriptive, offering prevalence data but little theory-driven insight into how cultural norms, institutional structures, and psychosocial dynamics interact to shape students\u0026rsquo; engagement in physical activity. This underscores the need for contextually grounded, theoretically informed qualitative research to better understand the barriers faced by Chinese undergraduates (Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)..\u003c/p\u003e\u003cp\u003eBuilding on this gap, our study applies the TDF and COM-B model in a qualitative exploration to investigate barriers to physical activity among Chinese university students. By moving beyond descriptive accounts, this approach enables the identification of culturally and context-specific barriers embedded within the university setting, such as rigid booking systems for campus sports facilities, social comparison pressures related to body weight and appearance, and the tension between heavy academic workload and parental expectations.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis qualitative study employed a theory-informed design to explore barriers to physical activity among university students with low activity levels. Initially, a screening process was conducted to identify potential participants. The International Physical Activity Questionnaire\u0026ndash;Short Form (IPAQ-SF) was administered to measure participants\u0026rsquo; self-reported physical activity over the previous seven days. Students whose total physical activity levels fell within the Low category according to the IPAQ scoring protocol were considered eligible (Committee, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Those meeting this criterion were invited to take part in the qualitative interviews. A qualitative descriptive approach was adopted to capture participants\u0026rsquo; lived experiences and perceptions in rich detail, while theoretical guidance from the COM-B model and the Theoretical Domains Framework (TDF) informed the development of the interview guide and the analytic framework. The study adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) 32-item checklist to ensure methodological transparency and rigour. Data collection took place between September 2022 and June 2023. This study was approved by the Ethics Committee of Guilin University of Electronic Technology (JGC202017). Written informed consent was obtained from all participants prior to their involvement in the research.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePhysical activity measurement\u003c/h3\u003e\n\u003cp\u003ePhysical activity levels were assessed using the International Physical Activity Questionnaire\u0026ndash;Short Form (IPAQ-SF), a 7-item instrument designed to capture the frequency (days per week) and duration (minutes per day) of walking, moderate-intensity, and vigorous-intensity physical activities, as well as sedentary behaviour, over the previous seven days (Craig et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Lee, Macfarlane, et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This classification method has been widely validated in diverse populations and is recommended for international surveillance of physical activity (Lee, Yu, et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wang, Chen, \u0026amp; Zhuang, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe IPAQ-SF records participants\u0026rsquo; physical activity during the previous seven days through seven items covering vigorous-intensity activity (VPA, e.g., running, aerobics), moderate-intensity activity (MPA, e.g., cycling, recreational swimming), and walking, along with sedentary behaviour (sitting time). For each activity category, participants reported the number of days and the average minutes per day they engaged in that activity. Weekly energy expenditure was calculated in MET-minutes/week by multiplying the activity-specific MET values\u0026mdash;8.0 METs for VPA, 4.0 METs for MPA, and 3.3 METs for walking\u0026mdash;by the self-reported duration (minutes) and frequency (days). The total physical activity score was obtained by summing the three categories. Participants were then classified into three levels of physical activity following the IPAQ scoring protocol (IPAQ Committee, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e): High (VPA on \u0026ge;\u0026thinsp;3 days achieving\u0026thinsp;\u0026ge;\u0026thinsp;1500 MET-minutes/week, or \u0026ge;\u0026thinsp;7 days of any activity combination totalling\u0026thinsp;\u0026ge;\u0026thinsp;3000 MET-minutes/week); Moderate (VPA on \u0026ge;\u0026thinsp;3 days for \u0026ge;\u0026thinsp;20 minutes/day, or MPA/walking on \u0026ge;\u0026thinsp;5 days for \u0026ge;\u0026thinsp;30 minutes/day, or any activity combination on \u0026ge;\u0026thinsp;5 days totalling\u0026thinsp;\u0026ge;\u0026thinsp;600 MET-minutes/week); and Low (not meeting the criteria for Moderate or High) (Committee, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Wang, Chen, \u0026amp; Zhuang, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eTheoretical Framework\u003c/h3\u003e\n\u003cp\u003eThe study was underpinned by two complementary behaviour change frameworks: the TDF and the COM-B model. The TDF consolidates constructs from 33 behaviour change theories into 14 domains and 128 constructs, providing a comprehensive taxonomy of behavioural determinants (Atkins et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; James Cane, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Susan Michie, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The COM-B model posits that behaviour (B) results from the interaction between Capability (C), Opportunity (O), and Motivation (M) (Michie et al., 2011). Capability includes both physical skills and psychological processes; opportunity comprises environmental and social factors; and motivation involves reflective and automatic processes. Embedding the TDF within the COM-B structure facilitates both detailed identification of determinants and high-level behavioural system mapping. The combined use of COM-B and TDF also supports subsequent application of the Behaviour Change Wheel (BCW) to identify appropriate intervention functions. It has been successfully applied in recent qualitative research exploring barriers and facilitators to physical activity in various populations (Brown et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ndupu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) that shown in Fig.\u0026nbsp;1: (Susan Michie, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eParticipants and Recruitment\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited through purposive sampling following an initial screening of physical activity levels using the International Physical Activity Questionnaire Short Form (IPAQ-SF). The questionnaire identified students whose physical activity level was categorised as Low according to the IPAQ scoring protocol, that is, they did not meet the criteria for Moderate or High activity. Eligible students were subsequently invited to take part in the study. Recruitment sought to achieve diversity in gender, academic discipline, and year of study. Snowball sampling was also employed to identify additional eligible participants. Data saturation was determined when no new codes emerged in two consecutive interviews. In total, sixteen students (6 males, 10 females) participated in the study. Detailed characteristics of each participant are provided in Supplementary Material 1.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eSemi-structured, in-depth interviews lasting 45\u0026ndash;60 minutes were conducted using a pre-tested interview guide developed from TDF domains mapped to COM-B constructs (Cane et al., 2012; Michie et al., 2011). The guide covered topics including current physical activity behaviours, perceived barriers and facilitators, knowledge and beliefs about exercise, social influences, and environmental context (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All interviews were audio-recorded with informed consent, transcribed verbatim in Mandarin within 24 hours, and cross-checked against the recordings for accuracy. Pilot testing with two students enabled refinement of wording to improve clarity and flow, consistent with recommendations for developing culturally sensitive qualitative protocols (Kallio et al., 2016).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eData were analysed using framework analysis, a systematic and flexible approach for applied health research (Bryman \u0026amp; Burgess, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Gale et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This method facilitated both deductive and inductive coding: deductive coding employed the TDF as an a priori framework, while inductive coding allowed new subthemes to emerge from participants\u0026rsquo; narratives (Atkins et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Byrne, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gale et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The analytic process involved three iterative stages:\u003c/p\u003e\u003cp\u003eOpen coding \u0026ndash; generating initial codes from raw data, resulting in 11 subcategories.\u003c/p\u003e\u003cp\u003eAxial coding \u0026ndash; clustering related subcategories into six higher-order categories.\u003c/p\u003e\u003cp\u003eSelective coding \u0026ndash; integrating categories into three overarching COM-B constructs: Capability, Opportunity, and Motivation.\u003c/p\u003e\u003cp\u003eTwo researchers independently coded transcripts in NVivo 12 (QSR International), meeting regularly to resolve discrepancies. Divergent coding decisions were discussed with a senior researcher until consensus was reached, enhancing dependability (Olmos-Vega et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Finally, emergent determinants were mapped onto intervention functions using the Behaviour Change Wheel framework (Flannery et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gale et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Susan Michie, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eRigour and Trustworthiness\u003c/h3\u003e\n\u003cp\u003eWe adhered to LINCOLN and Guba (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1985\u003c/span\u003e) four criteria for establishing trustworthiness in qualitative research. Credibility was enhanced through member checking, where participants reviewed summaries of findings to confirm accuracy (Urry, Chur-Hansen, \u0026amp; Scholz, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Transferability was supported by detailed description of the research context, sampling procedures, and participant characteristics. Dependability and confirmability were strengthened via peer debriefing within the research team and the maintenance of an audit trail documenting analytic decisions (Braun \u0026amp; Clarke, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Reflexivity was addressed through the use of reflexive journaling, with researchers documenting assumptions and potential biases throughout data collection and analysis (McLeod, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\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\u003e\u003cem\u003eSemi-structured interview items of the TDF embedded into the COM-B model\u003c/em\u003e\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\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTDF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCapability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you know what kind of exercise that behavior college students should maintain every week?\u003c/p\u003e\u003cp\u003eDo you know how exercise can improve your health?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCapability (physical)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAre you confident in participating in sports?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCapability (psychological)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIf you want to keep exercising, what will you do?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOpportunity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Skills\u003c/p\u003e\u003cp\u003eEnvironmental Context and Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAre there any sports you are particularly good at?\u003c/p\u003e\u003cp\u003eWhat kind of support does your environment need to provide you to want to participate in sports?\u003c/p\u003e\u003cp\u003eWill your exercise behavior be influenced by sports facilities and resources?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSocial Influences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIs your exercise behavior influenced by school, parents, friends?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMotivation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGoals\u003c/p\u003e\u003cp\u003eBeliefs about Capability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhat situation makes you exercise?\u003c/p\u003e\u003cp\u003eDo you have the confidence to stick to sports?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBeliefs about Consequences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHow will your physical activity be affected by COVID-19?\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\u003eSixteen students participated in the study (6 males, 10 females), participant characteristics was in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Analysis generated a theory-informed account of barriers to physical activity, organised around the COM-B components, with inductive themes mapped to TDF domains (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). While node counts were used descriptively to indicate relative salience, interpretation prioritised the depth and coherence of participants\u0026rsquo; accounts.\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\u003eSurvey participant characteristics (n\u0026thinsp;=\u0026thinsp;16)\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\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.94 (SD\u0026thinsp;=\u0026thinsp;0.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.90 (SD\u0026thinsp;=\u0026thinsp;2.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (62.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear of Study\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI Classification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (75.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (18.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnderweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (87.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol Consumption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (68.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (31.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-rated Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (62.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (18.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (18.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eNote. BMI classification based on WHO criteria: Underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;), Normal (18.5\u0026ndash;24.9 kg/m\u0026sup2;), Overweight (25.0\u0026ndash;29.9 kg/m\u0026sup2;), Obese (\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;).\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\u003e\u003cem\u003eOpen-Encoded Content from the Semi-Structured Interviews\u003c/em\u003e\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\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInterview Content (initial concept)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConceptualization\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003cp\u003e01\u003c/p\u003e\u003cp\u003e01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObesity is bad for your health, it affects your constitution, and it's bad for your image.\u003c/p\u003e\u003cp\u003eWhat I know is that when we exercise, we actually sweat. I don't have a professional coach who has specific guidance for us to exercise, so we sweat. We think sweating can achieve the effect of fat loss, so we think it's ok.\u003c/p\u003e\u003cp\u003eI have learned about a series of healthy diet in daily life. I usually eat a vegetarian diet. In the morning, I usually eat crude fibber and high-protein food for breakfast, such as eggs, purple potato, corn and vegetables, but sometimes I also eat other high-sugar food, but seldom eat high calorie food.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eExercise knowledge\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e09\u003c/p\u003e\u003cp\u003e1\u003c/p\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhen I was losing weight, sometimes I did not lose weight. Then he would do a lot of analysis for me, and then he would make recipes and training plans for me, tell me what to eat and do every day, and some other things about how to lose weight in the most efficient way through scientific exercise.\u003c/p\u003e\u003cp\u003eEveryone knows about the exercise software Keep. I use it to do some aerobic exercises to lose weight.\u003c/p\u003e\u003cp\u003eDuring that period of time, I insisted on doing aerobics and running, but there was still a little change. His body-shaping effect was quite good, and then I came back from a holiday, and I did not insist on doing it. It was not OK to do any exercise again.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eself-monitoring\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e01\u003c/p\u003e\u003cp\u003e04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI like playing badminton, but without a partner, what can I do alone? My parents and classmates encourage me to keep doing sports.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003ePeers\u0026rsquo; role\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e07\u003c/p\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI would take my friends out for a walk every week, because we need to walk the dog, and my friends need to walk the dog so we would go out for a walk, like three or four days a week, like walking the dog.\u003c/p\u003e\u003cp\u003eI really like taekwondo and aerobics class. First of all, taekwondo and aerobics class are very interesting. Then the calisthenics teacher will teach you a lot of things, and then it will be fun to warm you up in class.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eCoaches\u0026rsquo; role\u003c/em\u003e\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\u003eMy parents will urge me to exercise, in the case that I gain weight, and then they think it is not good for health to stay at home every day, not to exercise, supervise me to go running, and walk with them.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eParents\u0026rsquo; role\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e07\u003c/p\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI think sports is to have special sports venues, our fitness equipment only in the community, and then there is almost no special track, these places can run very few, because there are more cars in the street, traffic lights are also more, these sports venues are a little far from my home.\u003c/p\u003e\u003cp\u003eWhen I was losing weight, sometimes I did not lose weight. Then he would do a lot of analysis for me, and then he would make recipes and training plans for me, tell me what to eat and do every day, and some other things about how to lose weight in the most efficient way through scientific exercise.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eExercise resources\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e01\u003c/p\u003e\u003cp\u003e05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical health is certainly important, but I think that the kind of body is I like sports, I think I can have one day, but not necessarily to achieve that kind of body builder, like bodybuilders I think is not very good, I want to have a healthy body, as long as they look very healthy.\u003c/p\u003e\u003cp\u003eI think physical exercise is important, it can make the physical quality better, and then keep the mental energy is more energetic.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eHealth beliefs\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAfter the kind of physical exercise sweating let me feel particularly comfortable, can release the pressure, the body and mind will become a little lighter.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eEmotional beliefs\u003c/em\u003e\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the main barriers and influencing factors of college students\u0026rsquo; sports behaviour. Higher node numbers indicate that more related content was mentioned in the interview data.\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\u003e\u003cem\u003eCorresponding relationships and connotations of the main categories and sub-categories\u003c/em\u003e\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\u003eMain category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSub-category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of nodes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Capability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical skills\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychological Capability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExercise knowledge Self-monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth Beliefs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMental health Physical health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSchools\u0026rsquo; role\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=\"c1\"\u003e\u003cp\u003eEnvironmental Context and Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePublic Sports policy Exercise resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Influences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoaches\u0026rsquo; role Peers\u0026rsquo; role\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParents\u0026rsquo; role\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\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\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the main influencing factors of college students\u0026rsquo; motor behaviour disorders were sports resources (55), physical health beliefs (45), the role of friends (25), the role of family (16), self-monitoring (14), motor skills (12), and motor knowledge (9). Conversely, mass sports policy, the role of teachers, and school factors had little influence on college students\u0026rsquo; physical activity behaviour disorders.\u003c/p\u003e\u003cp\u003eCapability \u0026mdash; Physical and Psychological\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Theme 1 (Skills and Technique Knowledge), students described practical skill gaps that undermined their confidence to start or sustain activity. Technique knowledge was narrow and often shaped by ad-hoc online content rather than systematic instruction (P01, P05), with some equating \u0026ldquo;sweating\u0026rdquo; with \u0026ldquo;effective exercise\u0026rdquo; (P08), indicating a superficial procedural understanding.\u003c/p\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Theme 2 (Self-regulatory Strategies), self-regulation was typically fragile: goals were vague, monitoring inconsistent, and relapse after breaks common. Students described difficulty re-initiating routines following exams or holidays (P09, P13). The coded dataset showed capability-related material clustering under skills (n\u0026thinsp;=\u0026thinsp;12), exercise knowledge (n\u0026thinsp;=\u0026thinsp;9), and self-monitoring (n\u0026thinsp;=\u0026thinsp;14), reflecting under-developed skills and self-management. These themes aligned with the TDF domains Skills, Knowledge, and Behavioural Regulation (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), highlighting how limited capability directly impeded sustained physical activity engagement.\u003c/p\u003e\u003cp\u003eOpportunity \u0026mdash; Environmental Context, Resources and Social Influences\u003c/p\u003e\u003cp\u003eBarriers related to environmental context and resources were the most frequently referenced across the data. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Theme 3 (Environmental Constraints), students cited limited or inconvenient facilities, distance to venues, safety concerns, and inflexible booking systems (P07, P11). Resource-related accounts (n\u0026thinsp;=\u0026thinsp;55) were often interlinked with academic time pressure (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSocial influences (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Theme 4) were nuanced. Peers were the most influential interpersonal factor (n\u0026thinsp;=\u0026thinsp;25), acting as both facilitators (companionship, shared routines) and barriers (coordination failures, social comparison) (P04, P06). Parental and teacher influences (n\u0026thinsp;=\u0026thinsp;16 and n\u0026thinsp;=\u0026thinsp;3, respectively) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) were generally encouraging but less directly involved (P02, P14). These opportunity-related themes mapped to the TDF domains Environmental Context and Resources and Social Influences (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), demonstrating that physical access barriers often co-occurred with social coordination challenges, undermining participation even when students expressed willingness to engage.\u003c/p\u003e\u003cp\u003eMotivation \u0026mdash; Beliefs, Goals and Affect\u003c/p\u003e\u003cp\u003eMotivational barriers centred on health beliefs, competing priorities, and affective responses. In Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Theme 5 (Health Beliefs and Perceived Consequences), students generally endorsed the health benefits of physical activity, but perceived susceptibility and severity were not always translated into sustained intentions (P04, P12). Academic load and fatigue frequently displaced exercise from daily priorities.\u003c/p\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Theme 6 (Affective Responses), emotions shaped engagement in both directions: while some reported stress relief and improved mood post-exercise (P04, P10), others anticipated discomfort, embarrassment, or inefficiency, which reduced motivation (P12). Health-belief-related material was the second most frequent cluster (n\u0026thinsp;=\u0026thinsp;45) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), underscoring the central but ambivalent role of beliefs in shaping behaviour. These themes corresponded to TDF domains Beliefs about Consequences, Goals, and Emotion (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), illustrating how motivation fluctuated with contextual pressures and emotional states.\u003c/p\u003e\u003cp\u003eIntegration of Themes via TDF and COM-B\u003c/p\u003e\u003cp\u003eMapping inductive themes to TDF domains (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) clarified leverage points for change. Capability themes aligned with Skills, Knowledge, and Behavioural Regulation; Opportunity themes with Environmental Context and Resources and Social Influences; Motivation themes with Beliefs about Consequences, Goals, and aspects of Emotion and Social/Professional Role and Identity. The integration highlighted that environmental constraints and peer dynamics frequently co-occurred with fragile self-regulation and ambivalent health beliefs, limiting sustained engagement even among students positively disposed toward activity.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study applied the COM-B model and the Theoretical Domains Framework (TDF) to qualitatively explore barriers to physical activity among Chinese university students with low levels of exercise participation. By combining inductive thematic analysis with theory-driven mapping, we identified an interlocking set of determinants spanning Capability, Opportunity, and Motivation. Capability-related barriers included insufficient physical skills, narrow and sometimes inaccurate exercise knowledge, and weak self-regulatory strategies. Opportunity barriers were shaped by environmental constraints (e.g., lack of accessible facilities, inflexible booking systems), resource limitations (e.g., time pressures from academic demands), and social influences, particularly peer availability and coordination. Motivational barriers involved ambivalent health beliefs, competing academic priorities, and mixed affective responses to activity. Notably, university students with low physical activity levels face an interconnected set of capability, opportunity, and motivation barriers, where environmental constraints and peer dynamics exacerbate underdeveloped skills, fragile self-regulation, and ambivalent health beliefs, collectively limiting sustained engagement in physical activity.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePhysical activity barriers in Chinese college students\u003c/h2\u003e\u003cp\u003eThis chain of barriers reflects the tight interdependence of capability, opportunity, and motivation in the COM-B framework. Unlike much Western research that highlights generic constraints such as workload and facility access, our findings underscore context-specific obstacles within Chinese universities: rigid facility booking systems, the cultural salience of body image comparison, and the persistent tension between self-care and parental expectations for academic success. These culturally embedded dynamics amplify motivational ambivalence and self-regulatory fragility, demonstrating how institutional and social environments actively shape health behaviours.\u003c/p\u003e\u003cp\u003eDespite widespread awareness of the health benefits of physical activity, our participants described a recurring cycle of \u0026ldquo;intention, obstruction, and withdrawal.\u0026rdquo;. Students wanted to exercise, but heavy academic schedules and inflexible campus systems squeezed opportunities, leaving them discouraged when plans repeatedly failed (Journal of Physical \u0026amp; Health, 2025; Neill et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This erosion of opportunity in turn weakened self-regulation, undermined confidence in their ability to sustain routines, and fuelled ambivalent beliefs valuing activity in principle but questioning its efficiency or worth in practice (Bjornara et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tanksale et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Over time, these psychological tensions, reinforced by peer dynamics and social comparison pressures, made physical activity a fragile and easily abandoned behaviour.\u003c/p\u003e\u003cp\u003eImportantly, the mapping of these barriers to TDF domains highlights concrete points for intervention. Building capability will require structured opportunities for skills practice and strategies such as action planning. Expanding opportunity means more than building gyms; it calls for system-level changes to scheduling, affordability, and accessibility (Rhodes, Zhang, \u0026amp; Zhang, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wiium \u0026amp; Safvenbom, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Strengthening motivation involves addressing both reflective beliefs and emotional experiences, which could be supported through peer-led initiatives and digital tools that deliver just-in-time encouragement during periods of academic strain (Au et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). By telling this more integrated story of why students fail to be active, our study not only enriches theoretical understanding but also charts a pathway toward culturally sensitive and structurally informed solutions (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Guo, Wang, \u0026amp; Koh, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePractical implications for intervention design\u003c/h2\u003e\u003cp\u003eOur findings suggest that interventions to promote physical activity among university students should adopt a multi-component approach that concurrently targets capability, opportunity, and motivation. Building capability could involve structured skills instruction, clear technique standards, and the integration of self-regulation strategies such as action planning and self-monitoring (Bentley et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Flannery et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Restructuring opportunity may require expanding accessible low-cost facilities, streamlining booking systems, and protecting dedicated time slots for activity, as recommended by recent systematic reviews (Chen et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Guo, Wang, \u0026amp; Koh, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). To address motivational barriers, peer-led programs could be combined with individualised plans to ensure participation is not solely contingent on social coordination, while digital health interventions and just-in-time adaptive interventions (JITAIs) could deliver timely prompts and feedback during academically demanding periods (Ndupu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Skinner, Teychenne, \u0026amp; Murphy, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePractical Implications\u003c/h2\u003e\u003cp\u003eThe findings of this study have several practical implications for the design and implementation of university-based physical activity promotion strategies, particularly for students with low activity levels. First, the clear mapping of barriers to the COM-B components and TDF domains highlights the need for multi-component interventions that simultaneously address Capability, Opportunity, and Motivation, rather than isolated behaviour determinants. For example, integrating skill-development workshops and structured exercise orientation sessions into university health programmes could strengthen students\u0026rsquo; procedural knowledge and self-regulatory strategies, directly enhancing physical capability.\u003c/p\u003e\u003cp\u003eSecond, the environmental and social opportunity constraints identified, such as limited facility access, inconvenient booking systems, and unstable peer coordination, suggest that structural changes are required alongside individual-level interventions. Universities could improve facility scheduling flexibility, offer more on-campus activity options during peak academic periods, and facilitate peer-matching platforms that connect students with compatible routines. Such changes would reduce logistical barriers while stabilising the positive aspects of peer influence, which our findings show can act as both facilitators and inhibitors of engagement.\u003c/p\u003e\u003cp\u003eThird, addressing motivational ambivalence requires interventions that go beyond health education to target students\u0026rsquo; affective responses to exercise. Embedding short, enjoyable activity bouts within the academic day, offering non-competitive activity formats, and promoting immediate psychological benefits (e.g., stress relief, mood enhancement) may help reframe physical activity as a valued and rewarding element of daily life, even under high academic pressure. This aligns with dual-process models suggesting that behaviour change is more sustainable when both reflective intentions and automatic affective processes are positively reinforced.\u003c/p\u003e\u003cp\u003eFinally, our study underscores the importance of culturally and contextually tailored interventions for Chinese university students, a group underrepresented in existing COM-B/TDF applications. By situating behaviour change strategies within students\u0026rsquo; academic schedules, social norms, and campus infrastructure, universities can create supportive ecosystems that normalise and integrate physical activity into everyday student life. Such an approach not only addresses immediate participation barriers but also fosters long-term behaviour patterns that support mental and physical health beyond the university years.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study has several strengths. First, it is one of the few qualitative investigations to apply the COM-B model and Theoretical Domains Framework (TDF) to explore barriers to physical activity among Chinese university students with low activity levels. The explicit theoretical integration strengthened the explanatory depth of the findings and provided a clear basis for targeted intervention design. Second, participant recruitment was informed by objective screening using the International Physical Activity Questionnaire\u0026ndash;Short Form (IPAQ-SF), ensuring that the sample met clearly defined low-activity criteria. Third, methodological rigour was maintained through adherence to the COREQ 32-item checklist, triangulation of data sources, and deviant case analysis, which enhanced the credibility and trustworthiness of the thematic interpretations. Finally, purposive sampling ensured diversity across gender, academic discipline, and year of study, allowing the analysis to capture a range of perspectives within the target population.\u003c/p\u003e\u003cp\u003eHowever, some limitations should be acknowledged. First, the study relied on self-reported physical activity data from the IPAQ-SF for participant screening, which is subject to recall and social desirability bias. Although the IPAQ-SF is widely used and validated, objective accelerometer data would have further strengthened activity classification. Second, while the sample size was appropriate for qualitative research and data saturation was achieved, findings may not be generalisable to all Chinese university students, particularly those in rural or less resourced institutions. Third, the cross-sectional design captures perceptions at a single point in time, limiting insights into how barriers and facilitators might evolve over the academic year or in response to life transitions. Finally, the study primarily focused on students with low physical activity levels; therefore, comparisons with students meeting activity guidelines were not possible, which might have provided additional explanatory contrast.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eK.Z. conceptualised the study, collected and analysed the data, and drafted the initial manuscript.X.Q. supervised the study design and methodology, contributed to the interpretation of findings, and critically revised and edited the manuscript.All authors reviewed and approved the final version of the manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank all participating students for their valuable contributions.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe qualitative interview data that support the findings of this study are not publicly available due to confidentiality agreements with participants. An anonymised version of the dataset may be made available from the corresponding author (X.Q.) upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArafa, A., Yasui, Y., Kokubo, Y., Kato, Y., Matsumoto, C., Teramoto, M., Nosaka, S., \u0026amp; Kogirima, M. (2024). Lifestyle Behaviors of Childhood and Adolescence: Contributing Factors, Health Consequences, and Potential Interventions. \u003cem\u003eAm J Lifestyle Med\u003c/em\u003e, 15598276241245941. https://doi.org/10.1177/15598276241245941 \u003c/li\u003e\n\u003cli\u003eAtkins, L., Francis, J., Islam, R., O\u0026apos;Connor, D., Patey, A., Ivers, N., Foy, R., Duncan, E. M., Colquhoun, H., Grimshaw, J. M., Lawton, R., \u0026amp; Michie, S. (2017). 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Participation in Organized Sports and Self-Organized Physical Activity: Associations with Developmental Factors. \u003cem\u003eInt J Environ Res Public Health\u003c/em\u003e,\u003cem\u003e 16\u003c/em\u003e(4). https://doi.org/10.3390/ijerph16040585 \u003c/li\u003e\n\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":"Cultural Context, College Student, Gym, ehealth","lastPublishedDoi":"10.21203/rs.3.rs-7391974/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7391974/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003ethe present study qualitatively explored barriers to PA among Chinese university students with low activity levels, using the COM-B model and Theoretical Domains Framework (TDF).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eSixteen students were recruited through purposive and snowball sampling, screened using the International Physical Activity Questionnaire Short Form (IPAQ-SF). Semi-structured interviews, lasting 45\u0026ndash;60 minutes, were conducted in Mandarin and analysed using framework analysis. Deductive coding was based on TDF domains, while inductive coding allowed new subthemes to emerge. Themes were mapped onto COM-B constructs and linked to potential intervention functions via the Behaviour Change Wheel (BCW).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eBarriers clustered across three domains. Capability barriers included limited exercise skills, narrow or inaccurate knowledge, and weak self-regulation. Opportunity barriers reflected environmental and social constraints, such as inflexible booking systems, limited facilities, and reliance on peers for coordination. Motivational barriers included ambivalent health beliefs, competing academic priorities, and mixed affective responses.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eChinese university students face a unique constellation of capability, opportunity, and motivational barriers that jointly suppress sustained PA engagement. Interventions should integrate skill-building, restructuring of institutional opportunities, and strategies to strengthen motivation, ensuring culturally and contextually sensitive approaches to behaviour change.\u003c/p\u003e","manuscriptTitle":"Understanding University Students’ Physical Activity Barriers Through the Theoretical Domains Framework and COM-B Model: A Qualitative Exploration","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 21:13:27","doi":"10.21203/rs.3.rs-7391974/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":"46df1cb3-b15e-4558-acb4-a0652bddd812","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T09:40:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-11 21:13:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7391974","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7391974","identity":"rs-7391974","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}