Part II: Why Do Children and Young People Drop Out of Sport? A Dynamic Tricky Mix of Three Rocks, Some Pebbles, and Lots of Sand

Abstract

Organised sport is one potential antidote to the global youth inactivity crisis. Therefore, understanding why young people drop out constitutes a key research endeavour. In part I of this series, we developed and validated a new Youth Sport Dropout Questionnaire (YSDQ). In part II, we used the YSDQ-LV (49-item long version) to examine dropout in 960 university students from seven European countries. A four-stage analysis investigated the relative and combined importance of dropout reasons. Three items—the rocks—were statistically more important: “I prioritised schoolwork and had no time left to take part in sport”; and “I found other things that I enjoyed doing more than sport”; and “I found it stressful when I did not perform/play as well as I expected”. On average, however, these rocks were rated as “moderately important”, along with 19 reasons (the pebbles) rated as “slightly important to moderately important”, and the remaining 27 reasons (the sand) rated as “slightly important to not at all important”. These findings suggest that sport dropout is not caused by a single reason but is underpinned by a dynamic tricky mix of reasons—a series of rocks, pebbles, and sand unique to each young person.

1. Introduction

Globally, only one in five adolescents meet the WHO’s guidelines for physical activity (WHO, 2022). Organised sport has the potential to partially mitigate this trend. In addition, sport can be a catalyst for individual and social growth in underserved communities and underdeveloped nations (UNICEF, 2023) due to its mental (Andermo et al., 2020) and physical (Poitras et al., 2016) health benefits. However, research spanning multiple countries and sports (Emmonds et al., 2023) reveals high levels of sport dropout—defined as discontinuing sport participation either permanently or over an extended period (i.e., one or more successive seasons; Moulds et al., 2024)—from the onset of adolescence. This suggests that organised sport, in its current guise, may no longer be a reliable solution. In some sports (i.e., cycling, swimming, martial arts), between 70 and 90% of registered participants disengage by age 18 (Emmonds et al., 2023). Moreover, adolescents who drop out from sports experience greater psychological difficulties and more social and emotional problems (Vella et al., 2015).

Previous reviews have identified up to 150 factors contributing to youth sport dropout (Back et al., 2022; Balish et al., 2014; Crane & Temple, 2015). Collectively, these reviews highlight intrapersonal (e.g., lack of enjoyment, motivation, competence, sport experience) and interpersonal factors (e.g., social support, parental pressure) as potentially important factors underpinning dropout. They also acknowledge that dropping out is a highly individualised and multifaceted process (Balish et al., 2014). However, the interrelationships between dropout factors remain relatively unexplored (Crane & Temple, 2015). For a further understanding of existing dropout literature, please consult Part I of this series.

This situation has led to calls for more critical and comprehensive research (Battaglia et al., 2024) to address dropout as a complex, multilevel phenomenon (Balish et al., 2014). Yet, few studies (Molinero et al., 2006; Salguero et al., 2003) have investigated the comparative influence of the drivers of young people discontinuing their participation in organised sport. To the best of our knowledge, no studies have used a system-oriented, theory-driven, and process-focused instrument to understand the relative importance and levelness of the broad range of reasons why young people drop out from organised sport. Given the limitations of research to date, and the known complexity of the dropout phenomenon, our aim was to use the long version of the YSDQ (YSDQ-LV) developed in part I of this two-paper series, to provide a detailed examination of the importance of and interrelationship between different reasons for dropout with a large multi-country sample of young people. By refining our understanding of the factors affecting dropout, we can help organisations adapt and develop effective strategies to prevent it.

2. Materials and Methods

2.1. Instrument

The YSDQ-LV, developed via a review of existing literature, expert consultation and review, and athlete focus groups in Part I of this two-paper series, was used (see Table S1). The YSDQ-LV is a theoretically driven and expert-validated 49-item scale which offers strong face validity to conduct item level assessments of the relative importance of different reasons for dropout. The YSDQ-LV was built using the COM-B framework (Michie et al., 2011), which emphasises that behaviour (B) is the result of the interactions between the capability (C) of an individual to perform the behaviour, the opportunity (O) to perform it, and the motivations (M) towards it. Behaviour change requires one or more of these elements (capability, opportunity, and motivation) to be modified to create a new configuration that initiates and sustains the desired behaviour (Michie et al., 2011). In Part I, an exploratory factor analysis indicated an additional dimension, injury(I), which complemented the original COM configuration in a manner specific to youth sport, leading to the formulation of the COM(I)-B model for the study of youth sport dropout. Therefore, COM(I)-B offers an encompassing behaviour-change theoretical basis from which to conceptualise youth sport participation and dropout. In the current study, dropout is the targeted behaviour we wish to eliminate and substitute by the newly developed behaviour of continued participation.

2.2. Participants

The participants included 960 undergraduate and graduate university students from seven European countries (Germany, n = 41; Hungary, n = 49; Ireland, n = 88; Netherlands, n = 37; Lithuania, n = 7; Spain, n = 330; and United Kingdom, n = 408) who had, at some point in their childhood and adolescence, dropped out of sport. Overall, female participants (73.06%) outnumbered males (24.12%), nonbinary third gender (1.34%), and other (0.51%). A small proportion preferred not to say (0.96%). The students’ age ranged between 16 and 59, and the average age was 26.61, with a standard deviation of 6.43.

2.3. Procedure

Ethical approval was granted from the lead author’s institution. Students were invited to participate via email and through their university’s regular newsletter, which included a link to an online participant information sheet and consent form. Students who provided consent were directed to the online version of the questionnaire built on Qualtrics (QualtricsXM, 2022). Students in each country completed a version of the questionnaire in their native language validated through forward and backward translation. The average completion time was 15 min.

2.4. Analysis

Questionnaire data were exported from Qualtrics and inputted into SPSS (IBM Version 27, Armonk, NY, USA) and a Python (version 3) environment. We undertook a four-stage analysis. In the first stage, we ranked individual reasons—means and 95% confidence intervals—to show the most important single influences on dropping out (Individual Mean Importance or Imp¹). To test if Imp¹ truly represented factor importance, rather than being a descriptive artefact, in the second stage, we calculated the percentage of respondents who answered extremely important (5) or very important (4) to each reason (Individual True Importance or Imp²). In stage three, to continue to ascertain the relative importance of reasons for dropout, we looked at every possible combination of three reasons, and what percentage of the respondents ranked them extremely important (5) or very important (4) (Tripartite Importance or Imp³). In the final stage, to explore how all 49 reasons combined across the sample, we developed a frequency histogram of Total Dropout Scores (TDSs)—the total count for all 49 items—identifying the percentile distribution.

3. Results

With regard to Imp¹,

Table 1. Mean scores and 95% confidence intervals for all dropout factors (Imp¹).

Reason for Dropout	Mean	95% Confidence Interval
34. Prioritised school so no time (O—time)	2.95	2.86–3.05
45. Liked other things more than sport (M—internal motivation)	2.77	2.67–2.86
13. Stressful when I did not perform well (C—mental wellbeing)	2.77	2.68–2.85
43. Did not enjoy taking part anymore (M—internal motivation)	2.55	2.46–2.64
28. Nobody convinced me not to (O—social support)	2.55	2.45–2.64
1. Not good enough to participate (C—competence)	2.44	2.36–2.52
2. Not as good as friends or peers (C—competence)	2.36	2.27–2.44
46. Not worth the effort (M—internal motivation)	2.34	2.25–2.43
14. Coach expectations stressful (C—mental wellbeing)	2.34	2.25–2.42
6. Limited playing time or opportunities (C—competence)	2.33	2.24–2.41
27. No close friends involved in sport (O—social support)	2.24	2.15–2.32
36. Other activities prioritised so no time (O—time)	2.20	2.11–2.28
8. Suffered injuries (C—physical wellbeing)	2.19	2.11–2.28
11. Physical appearance uncomfortable (C—mental wellbeing)	2.17	2.08–2.25
47. Did not want to advance to next level (M—achievement motivation)	2.08	1.99–2.17
4. Coaches didn’t think I was good enough (C—competence)	2.08	1.99–2.16
12. Competitions unenjoyable (C—mental wellbeing)	2.06	1.98–2.14
39. You did not value the benefits of sport (M—external motivation)	2.06	1.98–2.14
17. Difficult to organise participation (C—organisational ability)	2.05	1.97–2.13
24. Did not have positive relationship with coach (O—social enjoyment)	2.04	1.96–2.12
44. Wanted a break (M—internal motivation)	2.04	1.95–2.12
26. Did not have a good relationship with other participants (O—social enjoyment)	2.03	1.95–2.11
16. Friends expectations stressful (C—mental wellbeing)	1.99	1.92–2.07
7. Discomfort Pain Tiredness (C—physical wellbeing)	1.99	1.92–2.07
18. Friends not sporty (O—social desirability)	1.98	1.91–2.06
30. No teams or clubs at my level (O—opportunity)	1.96	1.88–2.04
49. Did not reach level I wanted to and felt too much effort (M—achievement motivation)	1.91	1.83–1.99
29. No local facilities (O—opportunity)	1.89	1.81–1.98
41. Rewards did not motivate me anymore (M—external motivation)	1.88	1.80–1.95
38. You did not know the benefits of sport (M—external motivation)	1.88	1.80–1.96
3. Peers did not think I was good enough (C—competence)	1.87	1.79–1.95
9. Felt high risk of injury (C—physical wellbeing)	1.86	1.79–1.94
42. Felt forced to participate (M—external motivation)	1.81	1.73–1.89
37. Could not afford costs associated (O—material resources)	1.80	1.72–1.88
35. Priorities at home so no time (O—time)	1.79	1.71–1.87
20. Sport not important to my family or community (O—social desirability)	1.79	1.71–1.86
25. Did not have good relationship with sport adults (O—social enjoyment)	1.77	1.69–1.84
40. Stopped getting rewards from sport (M—external motivation)	1.76	1.69–1.84
15. Parent expectations stressful (C—mental wellbeing)	1.75	1.68–1.83
33. No leagues or competitions I enjoyed (O—opportunity)	1.75	1.68–1.83
21. My sport was not important for family or community (O—social desirability)	1.71	1.64–1.78
5. Parents didn’t think I was good enough (C—competence)	1.67	1.60–1.75
19. Friends not into my sport (O—social desirability)	1.66	1.59–1.72
10. Illness or injury outside of sport (C—physical wellbeing)	1.64	1.56–1.71
48. Achieved everything I wanted (M—achievement motivation)	1.62	1.56–1.69
31. No girls only provision (O—opportunity)	1.52	1.45–1.59
23. My sport was not positive for family or community (O—social desirability)	1.48	1.42–1.54
22. Sport not positive in family or community (O—social desirability)	1.46	1.40–1.52
32. Could not support disability (O—opportunity)	1.41	1.35–1.48

shows the mean score for each reason with 95% confidence intervals. C, O, and M denote the dimension of the COM-B model each item belongs to. Sub-dimensions appear in brackets. All items have been abbreviated in tables and figures. For the full item list, please refer to the Supplementary Materials Section. Differences between factors were considered statistically significant where there was no overlap in the confidence interval. Three reasons were found to be significantly more important compared to all others with mean scores that positioned them in the “moderately important” category: (i) “I prioritised schoolwork and had no time left to take part in sport” (M = 2.95, CI = 2.86–3.05); (ii) “I found other things that I enjoyed doing more than sport” (M = 2.77, CI = 2.67–2.86); and (iii) “I found it stressful when I did not perform/play as well as I expected” (M = 2.77, CI = 2.68–2.85). Notably these three reasons each were located in a different area of the COM-B model—opportunity, motivation, and capability, respectively. The remaining 46 reasons fitted into two further categories: (i) items whose means placed them in the “moderately important” to “slightly important” category (n = 19, M ≥ 2 to ≤2.5); and (ii) items which were scored in the “slightly important” to “not important at all” (n = 27, M < 2). Figure 1 shows this distribution graphically.

The analysis of Imp² (Figure 2) revealed that the same three items, which had the highest Imp¹ also had the highest Imp² score. This finding confirms that the mean analysis was not a descriptive artefact (i.e., the highest means could be a combination of 1 and 5 scores) but a true reflection of the importance of these items across the sample.

Adding to the findings of Imp¹ and Imp², the Imp³ analysis—Tripartite Importance—found that the three-factor combination, recurrently rated highest across the sample (

Table 2. Tripartite importance coverage (Imp³).

Three-Factor Combinations	Tripartite Importance—Imp3 (%)
“Stressful when I did not perform well” + “Prioritised school so no time” + “Liked other things more than sport”	70.31
“Suffered Injuries” + “Prioritised school so no time” + “Liked other things more than sport”	69.38
“Limited playing time or opportunities” + “Prioritised school so no time” + “Liked other things more than sport”	69.27
“Stressful when I did not perform well” + “Nobody convinced me not to” + “Prioritised school so no time”	69.17
“Limited playing time or opportunities” + “Stressful when I did not perform well” + “Prioritised school so no time”	68.65
“Stressful when I did not perform well” + “Prioritised school so no time” + “Did not enjoy taking part anymore”	68.65

), matched the factors with the highest Imp¹ and Imp², thus corroborating the overall importance of these three items not only individually but also in conjunction. Table 2 reports the top five Imp³ groupings.

Finally, the TDS frequency analysis shows how almost 50% of the sample had a relatively low TDS of below 95—from a potential maximum total of 245 (Figure 3). Notably, the sample also contained a small number of outliers whose TDS could be as low as 50 or higher than 200. This final stage of the analysis suggests that (i) dropout profiles are varied (i.e., dropout happens at all levels of TDS); and (ii) for the majority of the sample, dropout reflected a combination of multiple factors, with many factors rated “slightly important” (2) and “not important at all” (1).

4. Discussion

4.1. A Dynamic Tricky Mix of Three Rocks, Lots of Pebbles, and Some Sand

Against the background of alarming rates of youth physical inactivity and increasing levels of sport dropout, we examined the individual, relative, and combined importance of reasons for youth sport dropout across seven European nations. We did so by using the YSDQ-LV, a novel 49-item theoretically grounded and expert-validated instrument for the nuanced mass study of participation. The main findings propose the need to profoundly revise our understanding of why and how young people drop out from organised sport. Across the whole sample three factors, or “big rocks”, were rated significantly more important (Imp¹) than all others: (i) having to prioritise schoolwork and not having time for sport; (ii) finding other things to do that were more enjoyable than sport; and (iii) feeling stressed when not performing well. Notably, these items were each located in a different area of the COM-B model (e.g., opportunity, motivation, and capability, respectively), confirming the multifaceted nature of dropout. The Imp¹ scores were corroborated by the Imp² and Imp³ values, demonstrating the overall significance of the three “big rocks” to widespread dropout.

Notably, the three “big rocks” found in our study challenge the commonly accepted view that dropout is primarily related to interpersonal (i.e., relational elements of sport) and intrapersonal (i.e., self-confidence) factors—an issue previously highlighted by Balish et al. (2014). For instance, having to prioritise schoolwork over sport—an Opportunity factor—points towards excessive institutional and societal demands on young people’s educational workload, which can have counterproductive effects on their health and wellbeing (Cosma et al., 2020; De Looze et al., 2020; Scanlan et al., 2016). Likewise, finding other things to do that are more enjoyable than sport—a Motivation factor—indicates a potential mismatch between the demands linked to continued participation, and the natural exploration of a variety of leisure pursuits as adolescents increase their capacity for autonomy and agency (Battaglia et al., 2024; Scanlan et al., 2016). As we discuss in the Recommendations Section, these findings allow us to view dropout from a wider perspective and thus to formulate innovative strategies to mitigate it.

Remarkably, and notwithstanding the above, none of the 49 items, including the top three, were reported as “extremely important” but rather, as shown by the Imp¹ scores and TDS histogram, were placed on a continuum from “moderately important” (i.e., the three big rocks) to “slightly important” (i.e., the pebbles), and “not important at all” (i.e., the sand). This finding supports previous claims that dropout cannot be understood through reductionist approaches (Balish et al., 2014; Battaglia et al., 2024); it is better understood as a response to a blend of moderate- to low-impact determinants (i.e., a mixture of rocks, pebbles, and sand), which likely combine in a unique manner for each young person. For example, none of the injury-related items from the COM(I)-B model developed in part I were rated in the top ten reasons for dropout. That is not to say they are not a significant factor for specific individuals (i.e., a personal rock), but across this sample, they seemed more supplementary, combining with other more significant reasons (i.e., acting as a pebble or grain of sand amongst bigger rocks). This, for instance, is the case for item #8 (“suffered injuries”) which appeared in the top two Imp³ combinations.

Therefore, the decision to drop out appears to be influenced by what Nelson (2022), from a Dynamic System Theory perspective, refers to as a “dynamic tricky mix” of “multiple, complex, non-linear, fluidly and rapidly interacting components, factors, goals, feedbacks, variables and parts” (Nelson, 2022, p. 19). Consequently, attempts to explain—and resolve—dynamic system-based problems with individual manifestations, like youth sport dropout, need to move beyond the oversimplistic and reductionist and embrace and explore the inherent complexity of the forces at play—their dynamic tricky mixes. Factor combinations and relative importance for individuals and groups warrants further investigation.

Notably, this broader understanding of dropout provides a novel behaviourally grounded perspective on how it might be prevented. From this viewpoint, it is plausible to conceive the decision to drop out as a constantly evolving and emerging outcome of the increasing tension between all the potential retention and dropout factors. These tensions may accumulate over time, eventually reaching a threshold where discontinuing participation “makes sense” for an individual. If this holds, it is possible that the decision to drop out may not be triggered by a big rock but rather by a pebble or even a grain of sand, which may have a “last straw” effect, thus explaining why participation and dropout may be understood as dynamic and tricky. Moreover, it is also reasonable to hypothesise that all the dropout factors house an adaptive capacity—they may activate as “retention factors” when their score is very low (i.e., when a child’s family is very supportive of their participation or when they have a group of close friends at the same club). Thus, potential solutions may need to include ways to increase adolescents’ regulatory flexibility and resilience to deal with the emerging challenges to participation across the lifespan (Bonanno, 2021; Bonanno & Burton, 2013), as well as strategies to potentiate relevant retention factors (Gardner et al., 2017; Rottensteiner et al., 2015).

Considering dropout in this way makes it possible to search for new and powerful dynamic tricky mixes that create the necessary environmental and individual conditions—a breakthrough in Nelson’s terminology (Nelson, 2022)—for positive change to occur—in this case, a child or adolescent’s decision to remain engaged in sport.

4.2. Looking for the “Breakthrough” in Youth Sport Dropout

Reducing youth sport dropout requires the understanding that youth sport represents a dynamic system, entwined with other dynamic systems, such as family and school, and embedded within the general larger system of society. While, for some children, single factors may have a significant weight, our data suggest that for the majority, discontinued participation may result from a combination and aggregation of big, medium, and small factors—a unique and perfect blend of big rocks, small pebbles, and some sand.

Our findings, however, indicate that the big rocks tend to be associated with systemic issues, such as schoolwork and a cultural overemphasis on performance, whereas the pebbles may fit more within individualised and local features, such as perceived competence and lack of enjoyment. Identifying a new single dynamic tricky mix which works across contexts to retain all children in sport will be impossible. However, at least at the level of country, local authority, sport, school, and club, it may be possible to combine system conditions and individual strategies and affordances to increase the chances of young people staying in sport.

Looked at from a social policy perspective, this situation is akin to what Chater and Loewenstein (2022) have referred to as s-frame and i-frame interventions. Historically, to ensure community-wide effects, policymakers have relied on making changes at the system level (e.g., s-frame interventions). However, systemic change is expensive, takes time, and normally, at least initially, works against cultural and market forces. Advocates of a more liberal, small-state, non-interventionist approach have proposed a stronger focus on strategies targeted at the individual level (the i-frame), finding ways to drive people towards certain desired behaviours rather than making changes to the systems or bringing in additional regulations to impose those behaviours. Chater and Lowenstein acknowledge that certain societal issues, especially the more complex or “wicked” ones (Rittel & Webber, 1973), require changes at both the s-frame and i-frame level. Reducing dropout—a wicked problem if there ever was one—will require an innovative and concerted coming together of s- and i-frame interventions. The Recommendations Section points to where some of these efforts may be directed based on the findings of this research.

4.3. Strengths and Limitations

This study has some notable strengths. It is the first to use the newly developed YSDQ-LV. With a theoretical and behavioural foundation that has been subject to initial statistical validation (see part I of these series), the YSDQ-LV enables a comprehensive practical assessment of the importance of different reasons for dropout across samples and contexts. Moreover, thIS study is, to the best of our knowledge, the first to use a multi-country sample and thus offers both a fine-grain perspective—through the examination of the 49 factors included in the YSDQ-LV—as well as a broad view of the dropout phenomenon across Europe. Likewise, these results confirm the promise of the YSDQ-LV as a useful practical tool for national and sport-specific organisations to explore dropout in their context with a view to finding tailor-made solutions. Finally, the YSDQ-LV has potential to be also used as a predictive tool to explore the reasons why young people currently taking part in sport may eventually drop out so preventative interventions can be put in place. A pilot study in football has shown notable promise in this respect (Hill et al., 2023).

Conversely, this study has some limitations. Although questionnaire-based research can only provide a relatively blunt picture of dropout in a set population, the future addition of demographic and personal history data may allow researchers to explore how these individual characteristics impact the timing and reasons why young people drop out. Moreover, the findings of survey-based studies may also be affected by distorted recall of events, which may have happened as far as ten years ago. Additional qualitative research is required to elicit the dynamic reality of children who drop out of sport and fully grasp the emergence and realisation of the tricky mixes that activate dropout.

5. Conclusions

Across this two-part paper series, the newly developed YSDQ and YSDQ-LV have been found to provide a useful tool to explore the reasons why children and young people abandon sport. The YSDQ-LV offers strong face validity and consequently could be utilised to provide researchers and practitioners with an applied, theoretically grounded, item-level assessment of the relative importance of different reasons for dropout. By contrast, having been subject to exploratory and confirmatory factor analysis, the YSDQ constitutes a more psychometrically rigorous research tool that will, for example, be useful for researchers seeking to examine relationships between youth sport dropout and other psychological constructs (e.g., motivational orientation, coach behaviour, etc.) Although three factors—the big rocks of schoolwork, excessive pressure, and enjoying other things more—were found to be most important, this study shows how dropout appears to be the result of an individually unique combination—a dynamic tricky mix—of some of those big rocks with myriad moderate-to-low-importance factors—pebbles and sand—which ultimately combine in the decision to drop out. Finding a new single dynamic tricky mix which uniformly works across contexts to retain all children in sport seems a futile pursuit. However, a concerted effort between national (e.g., sport councils and governing bodies) and local organisations (e.g., schools, clubs, local authorities) may create an amalgamation of system conditions—s-frame interventions—and individual strategies and affordances—i-frame interventions—which increase the chances of young people staying in sport. This research point towards where some of these efforts may be best directed and below, we offer some tentative recommendations.

6. Recommendations

6.1. Governments and National Sport Councils

Given the context-specific nature of dropout, national organisations may wish to lead nation-wide reviews of the youth sport landscape to truly understand its nature, especially in relation to which system features (i.e., the big rocks) may hinder sustained participation and what may be done to mitigate them. Creative s-frame interventions to modernise and reconceptualise youth sport, and to remove systemic barriers to participation and dropout factors, may emerge—from funding additional facilities and programmes, to developing a smart phone app for adolescents to find sporting opportunities available to them, and to national educational drives for clubs, schools, coaches, and parents on how to mitigate dropout.

6.2. National Governing Bodies of Sport/National Federations

Emmonds et al. (2023) showed how dropout levels and timing was widely variable across 17 sports across 28 countries. Thus, sport-specific organisations can invest in understanding their own unique “dropout profile”—when children leave their sport and for what specific reasons (i.e., what are their specific rocks, pebbles, and sand). This novel understanding may lead to the revision of long-standing traditions and cultural artefacts which deter participation (e.g., necessary s-frame changes). For example, reviewing competition formats and systems, modernising training methodologies, eliminating dated hierarchies and exclusive practices, and creating new game formats may yield positive outcomes for a greater number of children. This may also include deliberately developing attractive and accessible opportunities to re-sample a sport that had been a feature of earlier life, especially during the dropout-sensitive period of adolescence.

6.3. Schools, Clubs, and Coaches

At ground level, given the importance of structural and coach-related factors on dropout seen in this study, the delivery agents need to be given the tools to continue to create developmental, motivational, caring, and safe sport climates (Bronkhorst et al., 2018) wherein children can thrive and enjoy sport in their own terms (Coaching Children Collaborative, 2023; Lara-Bercial et al., 2022).

More specifically, schools may have to find a greater balance between their academic workload and what this means for children’s ability to engage in sport and physical activity. This may include a combination of reducing homework, providing homework clubs in school time so children do not have to complete it at home, and increasing opportunities to do sport within the school. Sporting organisations may also help by offering homework clubs at their sites.

6.4. Children and Their Parents

From age 12 to 14, when dropout figures increase dramatically (Emmonds et al., 2023), parents and children need to be supported with tools and resources (i-frame interventions) to value and sustain their own participation through the lifespan. The notion of physical literacy (Whitehead, 2010), as an evolving positive relationship with movement, and physical activity (Sport England, 2023), which revolves around the person’s capacity to know, feel, connect, and do (Sport Ireland & Sport Northern Ireland, 2022), provides a “workable” conceptual and ideological framework to do so.