Impact of coach education on coaching effectiveness in youth sport: A systematic review and meta-analysis

Abstract

Sport plays a crucial role in the health and wellbeing of young people. While positive outcomes from sports participation are often assumed, studies show that these depend significantly on coaches’ attitudes and behaviors, which shape the sporting environment and influence participants’ experiences and outcomes. This study provides a systematic review with meta-analysis of various coach education program interventions (CEPIs), aiming to answer the question: How do CEPIs impact coaching effectiveness compared to standard coaching practices without such programs? Analyzing a total of 45 studies (N = 180,658), this systematic review is divided into a narrative section followed by a meta-analysis. Positive effects of CEPIs were observed in 78% of the studies, seen in coaches’ knowledge gain, attitude shifts, and behavioral changes, as well as in athletes’ physical and psychological outcomes, both within and outside of sport. Overall, a significant moderate to large effect of CEPIs on coaching effectiveness (g = 0.47, k = 264, 95% CI [0.36, 0.59]) was noted. Specifically, a large overall effect on coach outcomes (g = 0.73, k = 71, 95% CI [0.47, 1.00]) and a moderate to large overall effect on athlete outcomes (g = 0.38, k = 193, 95% CI [0.28, 0.47]) were observed. These findings generally support the positive impact of CEPIs on coaching effectiveness across the reviewed studies. However, the effects varied in magnitude, scalability, and sustainability for coaches and athletes. The discussion focuses on insights derived from CEPIs and future improvement strategies.

Keywords

Children learning mental health professional development training

Sport holds great potential in promoting health and wellbeing among individuals, especially in the youth population.^1–3 However, merely participating in sports does not automatically lead to positive developmental outcomes. Studies have indicated that sports participation can, in some cases, be associated with increased risk-taking behaviors, such as substance use, aggression, and antisocial behaviors.^4,5 Considering these potential risks, youth sports participation experience is significantly influenced by the knowledge, attitudes, and behaviors of coaches.^6,7 These factors are crucial in determining the quality of coaching and, consequently, the outcomes for young athletes.^8–11 Given the essential role of coaches in shaping athletes’ experiences and outcomes, it is crucial to understand what constitutes effective coaching and how it can be evaluated and enhanced.

Coaching effectiveness

Coaching effectiveness, while a concept with some detractors, has been widely used as a “unifying label” for understanding and evaluating coaching practice.¹² The evolution of this concept reflects the field's growing understanding of the complex nature of coaching. Early approaches to assessing coaching effectiveness often provided partial accounts, focusing on isolated aspects such as coach behaviors or athlete satisfaction.^12–15 These limited perspectives failed to capture the multifaceted nature of coaching and its impacts on athletes. To address these limitations, Côté and Gilbert proposed a holistic model of coaching effectiveness comprising three integral components: coaches’ knowledge, athletes’ outcomes, and coaching contexts.¹⁶ This model represented a significant advancement in conceptualizing coaching effectiveness by integrating multiple dimensions of coaching practice and its impacts.

The first component, coaches’ knowledge, encompasses a blend of professional, interpersonal, and intrapersonal knowledge. This includes sport-specific skills, effective athlete interaction, and the ability to self-reflect and learn from experience. The second component, athletes’ outcomes, pertains to the impact of coaching on various aspects of athletes’ development, including their psychomotor skills, performance, well-being, and personal growth. As key outcomes, Côté and Gilbert specifically emphasized the development of competence, confidence, connection, and character, collectively known as the 4Cs.¹⁶ The third component acknowledges the diversity of coaching contexts, highlighting the need for adaptability across different settings and developmental stages.

Côté and Gilbert's 4Cs have similarities to many Positive Youth Development (PYD) models.^16,17 PYD applied in sport emphasizes the development of life skills and positive attributes through sport participation and is a globally popular framework for understanding athlete outcomes that can be achieved by effective coaches in the youth sport context.¹⁸ While PYD remains widely used in coaching research and practice, it has faced criticism in recent years. Camiré et al. argued that the PYD framework needs to be better operationalized, does not adequately address issues of social justice in sport, and is limited by its humanist conceptions of relationships and development.¹⁷ Building on this multidimensional view of coaching effectiveness, Jowett argued that the coach-athlete relationship is at the heart of coaching effectiveness.¹⁹ This perspective aligns with the interpersonal knowledge component in Côté and Gilbert's model but places even greater emphasis on the quality of the coach-athlete relationship.¹⁶ Jowett proposed that the quality of this relationship, characterized by closeness, commitment, complementarity, and co-orientation, significantly influences athletes’ motivation, performance, and well-being.¹⁹ From this standpoint, effective coaching fundamentally involves creating and maintaining high-quality coach-athlete relationships that serve as a medium for achieving important goals.

While these various perspectives offer valuable insights into coaching effectiveness, there remains a need for an integrative framework that can accommodate multiple dimensions of coaching practice and its impacts. Despite ongoing debates and critiques, Côté and Gilbert's model remains at the forefront of coaching effectiveness research and practice.¹⁶ As Lyle noted, although the model sets a high standard by equating effectiveness with excellence, it offers a comprehensive approach integrating key aspects of coaching knowledge, athlete outcomes, and contextual factors.¹² Its holistic nature allows for potential incorporation of emerging perspectives, such as the emphasis on coach-athlete relationships and considerations of social justice, while maintaining a focus on tangible athlete outcomes. Given its multifaceted nature and continued relevance, Côté and Gilbert's model provides an appropriate guiding framework to examine the impact of coach education on coaching effectiveness in the current study.¹⁶

Coach education

Key components of the integrative definition of coaching effectiveness inform, implicitly and explicitly, coach education and professional development programs, which have shown substantial benefits in enhancing coaching skills.²⁰ Driska demonstrated this in a nationwide coach education program for swimming in the United States, where coaches not only improved their technical skills but also adopted developmentally appropriate practices.²¹ In a Belgian study, Reynders and colleagues further highlighted the positive impact of such training on coaches’ autonomy-supportive styles and structured coaching, aligning well with athletes’ perceptions and leading to increased athlete motivation and engagement.²² Athletes who are motivated and engaged are more likely to experience enjoyment, develop skills, and maintain long-term participation.

The contextual and developmental demands of coaching in youth sports significantly influence coaches’ decisions, shaping behaviors that are conducive to athlete development.²³ Numerous coach education program interventions (CEPIs) are grounded in theoretical frameworks like Self-Determination Theory (SDT) and Achievement Goal Theory (AGT), focusing on modifying coaching behaviors (e.g. communication, feedback provision, and use of reinforcement and encouragement) to promote positive sporting environments and affect a variety of psychological outcomes in youth athletes.^24–29 Additionally, certain CEPIs aim to provide coaches with humanistic skills, problem-solving capabilities, and a tailored coaching approach to facilitate positive developmental outcomes in sports.^14,30 Some programs have incorporated principles from PYD, emphasizing the cultivation of the 4Cs, competence (physical and social skills), confidence (self-esteem and self-efficacy), connection (positive bonds with others), and character (morality and integrity), in youth athletes.^18,31,32

The advent of online training and technology-enhanced learning has opened new avenues in the field of coach education, offering innovative methods for knowledge dissemination and skill development.^33–35 Studies showed that online learning platforms, especially those utilizing video-based interactions, were effective in promoting collaborative learning, critical reflection, and analytical coach-athlete interactions.^36,37 Moreover, Kroshus et al. reported that online education platforms significantly improved coaches’ communication regarding concussions with collegiate athletes.³⁸

Within the spectrum of CEPIs, Nelson et al. delineated three distinct categories: formal, informal, and non-formal.³⁹ Formal CEPIs generally consist of certification programs implemented by national sports associations or governing bodies. Informal CEPIs, in contrast, revolve around personal experiences and social interactions, often occurring in contexts where learning is not the primary objective.^40,41 Non-formal CEPIs are characterized by structured yet non-institutionalized educational activities, specifically designed to impart particular knowledge to targeted groups. These often manifest as workshops, seminars, and clinics, facilitated by coaches or researchers in controlled environments conducive to contextualized learning experiences.^30,41,42

Despite the varying approaches, there is a consensus among coaches favoring non-formal CEPIs for the acquisition of knowledge pivotal to fostering youth development in sports.^20,37,42 Varying empirical studies corroborated the effectiveness of non-formal CEPIs in enhancing team dynamics, strengthening positive coach-athlete relationships, and producing favorable outcomes in athletes.^9,10,43,44 However, despite these positive findings, there remains discrepancies in the literature regarding the integration and application of knowledge within non-formal CEPIs, and how this knowledge is effectively transferred to end-users.⁴⁵ The gap noted earlier underscores the need for further research to optimize the design and delivery of non-formal CEPIs, ensuring their relevance and applicability in contemporary coaching contexts.

The present study

As the body of empirical research grows, it increasingly substantiates the connection between coach education and subsequent shifts in coaching knowledge, attitudes, and behaviors, which collectively influence athletes’ experiences and outcomes.^46–48 However, there is a dearth of information in the current literature on a comprehensive integration of these outcomes within the coaching effectiveness framework that simultaneously addresses both coach and athlete perspectives in the realm of CEPIs. To address this gap, our study aims to deepen the understanding of the impact of CEPIs on coaching effectiveness. As such, this endeavor was intended to make a substantial contribution to the field of coach education, enriching both theory and practice. To address the question, how CEPIs affect coaching effectiveness compared to standard practices without such programs, this study serves a dual purpose: (a) to identify research trends in the existing literature on the effects of CEPIs on youth sport coaches, and (b) to examine the impact of CEPIs, along with potential moderating factors, on coaching effectiveness at both the coach and athlete levels.

Method

We conducted a systematic review and meta-analysis to address the aforementioned research purposes, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.⁴⁹

Search and screening

Bibliographic databases served as the primary method of identifying eligible studies. The search strategy included use of the following databases: PubMed, SPORTDiscus, PsycInfo, MEDLINE Complete, Education Resources Information Center (ERIC), Dimensions, and Google Scholar. Keyword combinations used in the search are listed in Table 1. The current review also conducted manual searches of relevant papers and backward reference searches of other reviews. The review protocol was registered in the PROSPERO international prospective register of systematic reviews, and the registration number is CRD42023479392.

Table 1.

Flowchart of search strategy.

Concept	Keywords
I. Outcome: Coaching Effectiveness	coaching effectiveness or efficiency or knowledge or attitude or intention or behavi* or confidence or engagement or communication or feedback or support* or autonomy or social or competence or relatedness or leadership or mastery or ego or climate or well-being or satisfaction or retention or commitment or motivation or regulation or safe* or anxiety or develop* or positive youth development or social emotional learning or goal orientation or achievement or context* or ecology
II. Participant (Primary): Coach	coach* or youth sport coach* or facilitator* or teacher*
III. Participant (Secondary): Athlete	youth or adolescents or young people or teen or young adult* or children or kids or young athlet* or youth athlet* or subject* or boy or girl or male or female or health*
IV. Intervention: Training	training or workshop or professional development or formal or informal or nonformal or online or in-person or hybrid or short-term or long-term or education* or learning or intervention or control or active control or specific or non-exposed control group
V. Research design	experimental* or quasi experimental* or pre experimental* or observational* or randomized control trial* or RCT or cluster randomized trial* or cross sectional* or case-control* or mixed method*

Note: Bibliographic databases: PubMed, SPORTDiscus, APA PsycInfo, MEDLINE Complete, ERIC, and Dimensions; We used “OR” to separate keywords within each concept and “AND” to separate each concept; The latest search of the aforementioned databases was on November 18, 2023

Inclusion and exclusion criteria

Eligibility criteria were formed using PICOS framework referring to Participants, Interventions, Comparison conditions, Outcomes, and Study designs.⁵⁰

Participants

Studies were included if they involved coaches active in youth sports programs and athletes under 18 participating at the start of the data collection. Studies focusing on coaches at the college or professional level; or athletes over 18 years of age, or who were affected by a particular disease, disorder, injury, or trauma at the time of the study were excluded.

Intervention

Varying interventions were included: training programs ranging from formal, structured courses to more flexible informal and nonformal training approaches, including in-person, online, and hybrid formats; interventions of varying lengths, from concise sessions (minimum 30 min) to extended programs (up to 12 months); and, aiming at enhancing coaching effectiveness, covering technical knowledge, promoting social-emotional growth and well-being, emphasizing injury prevention and management, and fostering mastery and a supportive climate for youth athletes. Studies without introducing training details (e.g. formation, content, and duration) or trainings designed for college or elite level learners were excluded. In addition, non-exposed control or waiting list control or other active coaching practices that do not include the specific training and development programs were compared.

Outcome measures

All coaching effectiveness measurement results within the selected studies were considered as outcomes, including coach- and athlete-level outcomes. Primarily, studies with the following data were included: coaching techniques and knowledge, measured using standardized coaching skill assessments or self-reported coaching knowledge questionnaires; coaching behavior, evaluated through systematic observation checklists or self-reported behavior style surveys; intentions in creating a positive youth sport environment, assessed using athlete surveys or relative psychometrics. Athlete-level outcomes mainly involved: athletes’ performance and physical literacy; perceived coaching effectiveness, mastery climate, enjoyment, mental health, and well-being.

Study designs

The inclusion criteria for studies were as follows: original empirical studies written in English and published in the last two decades (2003–2023). Studies were excluded if they were meta-analyses or other systematic reviews.

Studies selection and data extraction

Titles and abstracts were independently screened by two authors. Accordingly, the full texts of the initial studies were subsequently screened by the authors for adherence to inclusion criteria, resulting in the final selection of studies. Mendeley software was used for recording and managing related literature. The PRISMA flow diagram illustrates the search and screening process (Figure 1).

Figure 1.

PRISMA flowchart of search strategy and screening.

Assessment of risk of bias

The Cochrane Collaboration tools were used for bias risk assessment in included studies, examining aspects such as confounding variables, participant selection, interventions, missing data, outcome measures, and reported results. The risk of bias in non-randomized studies of interventions (ROBINS-I) tool, part of the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework, was used to evaluate both randomized and non-randomized studies.^51,52 This approach allowed for a unified bias risk assessment, with all subcategories equally contributing to the overall quality rating. Findings on evidence quality and bias risk were visualized using the Risk-of-Bias VISualization (robvis) platform (see Appendix A Figure 1).

Quality assessment and level of evidence

The quality of selected studies was assessed using the PRISMA checklist and a modified version of the Critical Appraisal Skills Program checklist. The assessment, performed independently by two authors, entailed a 7-question metric spanning five key aspects, in terms of research question, study design, data collection, data analysis, and reporting of results, where each question was rated as 1 (agree) or 0 (disagree). Studies achieving a score of six or above were categorized as high quality, those with scores between four to six as moderate quality, and those scoring below four were excluded due to low quality. An adopted rating scheme was used, RCTs were classified under the first level of evidence, non-randomized controlled trials under the second, and uncontrolled studies under the third in the current study.⁵³ Any disagreements were resolved through discussions and if necessary, a third author was consulted. The quality assessment and level of evidence results, and the interrater reliability are illustrated in Appendix Tables 1 and 2, respectively.

Data analysis and synthesis

Data analysis

Characteristics of each study, including demographics, study design, and training details, were systematically reviewed and extracted into Microsoft Excel. These elements covered authors, study site, journal, sample size, coaching experience, data analysis methods, training type, duration, and key findings. Meta-analysis was conducted using R (version 4.3.2, R Core Team). Given that a single study might report multiple outcomes, each type of study-level outcome was treated independently as a separate entity.⁵⁴ To account for the potential nesting of effect sizes within studies and control for cross-study connections, we implemented three-level models using hierarchical meta-analysis.⁵⁴ All effect sizes were converted to Hedges’ g which was calculated based on studies reported quantitative training outcomes, including sample size, mean, and standard deviation of each group. Other effect sizes such as partial eta square (η_p²) and Cohen's d presented in the original papers were converted into Hedges’ g for further analysis. Pooled effect sizes were categorized as small, Hedges’ g ≤ 0.15; small to moderate, 0.15 < Hedges’ g ≤ 0.36; moderate to large, 0.36 < Hedges’ g ≤ 0.65, or large, Hedges’ g > 0.65.^55,56

Heterogeneity and publication bias

Tests for heterogeneity among the studies utilized the Q and the I² statistics. Statistical heterogeneity was evaluated using the p-value, Tau², and I², with I² values of 25% indicating low, 50% moderate, and 75% or higher indicating high heterogeneity. Sensitivity analysis was executed by excluding studies with a high risk of bias. For assessing publication bias, the funnel plot and Egger test were employed.

Subgroup analysis

Subgroup analyses were conducted based on five categories as sports, training type, formation, duration, and study design. Sports were further categorized into three groups, team sport (e.g. basketball and soccer), individual sport (e.g. swimming and equestrian), and mixed which included multiple team and individual sport. Given Nelson and colleagues, training types were divided into three different types in terms of formal, informal, and nonformal.³⁹ And training was identified into in-person, online, and hybrid formations. Duration of CEPIs was categorized into three levels including single workshop or session, medium-term with multiple sessions, and long-term throughout the entire season or year. Further, types of study design in included studies were identified according to Campbell and Stanley's taxonomy.⁵⁷ These analyses were conducted to closely examine and clarify the impact of variability in research designs and training programs on coaching effectiveness related outcomes.

Data visualization

On the basis of similarity and differences within the selected studies, we applied a co-occurrence analysis to explore the collaborations among key themes via VOSviewer (Version 1.6.16). Specifically, this procedure was designed to recognize the research trends and patterns in the field of coach education. A full counting co-occurrence map was constructed in a three-step process as described by Van Eck and Waltman.⁵⁸

Results

Demographic characteristics

As shown in Table 2, the frequencies of the sport, study site, and participants combinations in the 45 included studies. The median publication year of these studies is 2016 (M_year= 2016; SD = 5.55; range from 2004 to 2023). Focusing on youth sport coaches (n = 180,658, M_age= 24.84, SD_age= 8.35), the data revealed an average of five years of coaching experience (M_experience= 4.93, SD_experience= 4.07). Excluding one study²⁵ with a considerable large coach sample, the average sample size was adjusted to 27.02 coaches (SD = 42.37; range from 2 to 185). Regarding youth athletes (n = 3655, from grade 4 to 12), they were included in 30 studies, with two studies^59,60 not specifying age or grade levels. The average athlete sample size was 83.07 (SD = 93.63; range from 23 to 350). In addition, parents (n = 312) were included in four studies.^3,29,61,62 Detailed demographics in selected studies are presented in the Supplementary File, Appendix Table 3.

Table 2.

Demographic characteristics in selected studies.

	References numbers	No. of studies
Soccer	27, 45, 59–61, 63, 69, 71, 72, 76, 78, 79, 84, 85	14
Mixed	3, 31, 32, 38, 43, 62, 64, 65, 80–82, 86, 87	13
Basketball	9, 26, 28, 29, 30, 67, 75, 77, 83	9
Swimming	24, 25, 66	3
Floorball	88	1
Gaelic football	68	1
Handball	74	1
Netball	1	1
Rowing	70	1
Rugby	73	1
United States	9, 24–26, 28, 29, 38, 45, 64, 65, 75, 77, 85, 86, 88	15
Australia	1, 3, 61, 67, 78, 79, 84	7
Canada	27, 30, 66, 73, 82, 83	6
Spain	71, 72, 76	3
Portugal	31, 32, 74	3
United Kingdom	59, 63, 70	3
Poland	80, 81	2
Ireland	68, 87	2
Norway/France	60, 69	2
Singapore	43, 62	2
Coach and athlete	1, 9, 24–28, 31, 43, 45, 66–68, 70–72, 74–77, 79–83, 85	26
Coach	30, 32, 38, 59, 63, 64, 69, 73, 78, 84, 86–88	13
Coach, athlete, and parent	3, 29, 61, 62	4
Coach and Athletic Director	65	1
Coach and Coach Educator	60	1

Note: Forty-five studies are included in the current study; Studies were categorized into sport used in the coach education intervention, study site, and participants; Mixed sports include soccer, basketball, football, baseball, volleyball, ice hockey, floorball, rugby, swimming, equestrian, etc.; Studies⁶² and⁴³ also included physical education teachers and teachers in their studies.

Type and formation

The majority of CEPIs in the current study were nonformal (n = 40), with the exception of one informal⁶³ and four formal^32,38,60,64 trainings. Most nonformal CEPIs (n = 25) were delivered in-person by researchers, certificated psychologists, or coach educators.^{9,24–26,28,29,43,45,65–81} These in-person CEPIs included various formats such as workshops with additional learning resources,^{24,25,27,68,69,73,80,81} observation and feedback sessions,^26,31,66,76 and training with group discussion and reflection,^{28,30,70,77–79,82,83} along with quizzes.⁷⁰ Several in-person CEPIs also incorporated established training models like ‘Coach Beyond’,⁶⁵ ‘PASS IT Back’,⁴⁵ ‘Play Like a Champion Today’.²⁸ Additionally, hybrid CEPIs combining in-person and online learning were observed^{1,3,31,61,84,85} featuring workshops and online modules with group discussions, assessments, and reflection sessions. The study also included five exclusively online CEPIs with sessions such as ‘ACTive’,⁸⁶ a ‘MOOC’,⁵⁹ ‘One Good Coach™’,⁸⁷ an online concussion training,⁸⁸ and a visual presentation.²⁷ Excluding one in-person CEPI,⁶⁰ the remaining were delivered online, either asynchronously^25,38 or synchronously.³² The duration of these CEPIs ranged from 30 min to 15 weeks, except for one study²⁶ where the duration wasn't specified as feedback was provided via email. Most online CEPIs lasted between 60 to 90 min, except for a multi-session training totaling 24 h.³² Lastly, in-person workshops typically spanned three to four hours, with some being shorter^{24,25,66,73,74,76,78,79} and others longer.^{3,31,43,45,59,60,68,69,80,81,84}

Conceptual framework and training protocol

The learning theories, training protocols, and expectations across CEPIs exhibited considerable diversity, falling into various distinct domains. In terms of learning theories and frameworks employed in CEPIs, those based on AGT and SDT were predominant in the majority of the studies.^{9,24–26,28,29,45,60,66,68–81,85} Additionally, other frameworks like PYD,^{26,30–32,82,83} the Quality Teaching Framework,^1,84 and the Experiential Learning Theory^43,62 were also utilized. Specifically for concussion and mental health-related CEPIs, models such as the Health Belief Model, the Health Action Process Approach framework, and the Community-Based Participatory Research Model were applied.^{3,65,73,87,88} Through CEPIs, trainees enhanced their coaching strategies, their ability to foster motivational climates and their efficacy in coach-athlete interactions.^{1,9,24–32,45,60,61,63,65,68–72,74–85} They also learned to promote physical activity and psychomotor skills in athletes,^66,67 create safe physical and psychological environments,^{3,38,43,62,73,86–88} and support holistic wellness and social-emotional development of athletes. The collated data regarding the conceptual framework, learning objectives, and training protocols are detailed in the Supplementary File, Appendix Table 4.

Research design and assessment

Within the body of research on CEPIs, six qualitative studies^{30,32,43,62,69,83} were selected, covering both in-person and online formats. Semi-structured interviews emerged as the primary method for collecting qualitative data. In addition to these, focus group interviews⁸³ and personal journals³⁰ were also utilized, particularly in conjunction with two in-person workshops. Furthermore, 11 mixed-method studies were incorporated, offering both qualitative and quantitative insights into CEPIs.^{28,45,59,60,63,65,68,70,78,85,87} These studies frequently included open-ended questions^28,65,78 and reflective exercises⁸⁵ for collecting feedback and learning outcomes from trainees. The qualitative data in these studies was predominantly analyzed through thematic analysis, meticulously detailing data coding procedures and trustworthiness establishment.^{30,32,43,62,69,78,83} However, a subset of studies mentioned using content analysis as their primary analytical method.^{28,45,65,68,70,85}

In the quantitative realm of CEPIs, quasi-experimental designs were most frequently adopted,^{3,9,27,29,31,66,71,72,74,75,77,79–82,84,88} with RCTs^{1,24,25,38,61,67,86} next. Pre-experimental designs^26,73,76,84 and ex post facto designs⁶⁴ were also employed. A diverse array of psychometric tools was used for outcome evaluation, including pre-established scales,^{1,3,9,24–29,31,38,45,60,61,64,67,68,70–77,79–82,84–86,88} systematic observations,^{1,24,25,31,61,63,66,70,74,76,84} psychomotor assessments,^80,81 and accelerometers.⁶⁷ Additionally, video and notational analyses were applied to scrutinize coach and athlete behaviors during practices and games.^1,74,76,84 Inferential statistical techniques such as analysis of variance (ANOVA), multivariate analysis of variance (MANOVA), and multilevel modeling (MLM) were utilized to analyze intervention effects. Details of the research designs, data modalities and analyses, as well as outcome assessments in these studies, are compiled in the Supplementary File, Appendix Table 5.

Key findings and limitations

Positive outcomes for coaches and athletes were noted in 35 studies, approximately 78% of the total^{1,9,24,25,27–30,38,43,45,59–69,73–76,79–84,86–88} following participation in CEPIs. Coaches reported an increased adoption of autonomy-supportive behaviors, enhancing their confidence and competence.^1,43,61,69 They also demonstrated a greater use of various task-related behaviors to create a motivational and task-oriented climate.^{9,27,75,76,84} Furthermore, the incorporation of video feedback and reflection within CEPIs was instrumental in enhancing coaches’ self-awareness, challenging pre-existing notions, and developing more informed coaching practices.⁶³ Coaches also became more adept at collaborating with athletes, fostering a positive team environment, trust, feedback, and friendships, and involving athletes in team decisions. This approach promoted independence, critical thinking, problem-solving, and life skills extending beyond sports.^{30,43,61,62,82,83} Notably, coaches’ knowledge of concussion and mental health, communication about safety, and injury prevention behaviors and intentions improved.^{3,38,65,86,87} CEPIs also influenced learners’ engagement on social, networked digital platforms, facilitating active learning that bridged personalization with social learning to establish relevance and build community.⁵⁹ Additionally, coaches’ roles as moral educators were strengthened, with a focus on fostering athletes’ character development.²⁸ Significant enhancements in coaches’ transformational leadership behaviors, such as appropriate role modeling, fostering group goal acceptance, and intellectual stimulation, were noted.⁷⁹

Athletes, on the other hand, experienced improvements in psychomotor and game skills, as well as positive self-perceptions.^1,74,81 They also reported a stronger connection with their coaches, a reduction in antisocial behaviors, and advancements in cognitive skills and goal setting by season's end in CEPI groups.^79,82 Additionally, there was a marked increase in physical activity levels, active play, and engagement in playful activities.^1,67 CEPIs proved effective in stimulating athletes’ intrinsic motivation, mastery goal orientation, enjoyment, and long-term participation in sports.^61,69,75,80 Furthermore, these interventions were instrumental in preventing athlete burnout, reducing anxiety, and enhancing well-being.^9,29,68,80 The distinctive or novel elements of the studies included are detailed in the Supplementary File, Appendix Table 6.

Interestingly, 33% of the studies reported non-significant or contradictory outcomes related to CEPIs.^{1,3,24–26,31,32,67,68,70–72,77,82,85} For instance, some coaches experienced a decrease in encouragement behaviors post-training, and group membership did not significantly influence the rate of fear of failure change in young athletes.²⁵ Furthermore, no significant differences were observed in either autonomy-supportive or controlling behaviors among coaches participating in CEPIs.^68,85 While athletes showed minor increases in self-esteem during the season, the interventions did not significantly affect these changes.²⁴ Additionally, in seven CEPIs, no significant improvements or even decreases were noted in athletes’ enjoyment, intrinsic motivation, confidence, competence, sport commitment, perceptions of empowerment, mental toughness, or wellbeing.^{1,26,67,68,71,77,82}

While CEPIs effectively enhanced athletes’ mental health literacy, particularly concerning depression and anxiety, no significant changes were observed in athletes’ intentions to seek help through mental health professionals, perceived familial support, or psychological distress.³ Over time, athletes’ developmental experiences and the coach-athlete relationship remained largely unchanged,³¹ and there was even a slight increase in antisocial behaviors by the end of the season.⁸² Post intervention, athletes reported higher levels of psychological needs thwarting compared to baseline measurements,⁷⁰ and a decrease in satisfaction with their coaches.⁷² Coaches, on the other hand, expressed challenges in applying strategies learned from CEPIs in practical settings.^32,60 One study suggested that CEPIs should shift from a traditional ‘knowledge transfer’ approach to a more cooperative learning environment, where coaching knowledge is shared and created in context.⁷⁸ Moreover, a study highlighted gender differences in CEPIs outcomes, notably finding them more effective in boosting self-esteem among younger girls with initially low self-esteem levels.²⁴

The limitations of included studies were thoroughly addressed, with the exception of one study.³⁰ The most frequently reported limitation, noted in 15 studies, was the limited generalizability of findings due to the use of small convenience samples.^{1,24,43,59,60,62,64,65,77,78,80,82,83,87,88} Fourteen studies lacked clarity in reporting coach-specific data, such as group size, coaching experience, age, or grade level coached.^{3,26,28,38,61,63–65,67,70,80–82,87} Many studies reported limited participant demographic data. Only 20%^{9,24,25,28–30,75,82,83} and about 18%^{24,25,28,38,65,67,85,86} of studies provided socioeconomic status (SES) and ethnicity information, respectively. Moreover, several studies^{43,71,72,74,77,82,83,86} noted imbalances in group characteristics (e.g. gender, ethnicity, SES, coaching or athletic experience) that could potentially influence the findings. Additionally, three studies^29,63,75 addressed potential confounding variables, such as the initiation of multiple trainings during the intervention period and the absence of objective observations, a concern highlighted in other studies.^9,32,69 The efficacy of the interventions was often assessed only in the short term, without the benefit of a longitudinal perspective.^{26,67,76,78,79} Other limitations included inconsistencies in online modules and self-paced learning,^3,28,85 as well as low participant retention rates.^31,70 A significant concern was the underreporting or lack of measurement of athlete outcomes in 15 studies,^{30,32,38,59,60,64,65,69,73,78,84,86–88} crucial for evaluating coaching effectiveness. Finally, a third of the studies (n = 14) indicated issues with missing data in coach and athlete samples, affecting the reliability of statistical analyses such as t-tests, ANOVAs, or MANOVAs, highlighting this as a major limitation in handling clustered data.

Meta analytic results

Thirty-three out of 45 studies (73%) reported quantitative data qualified for meta-analysis. The homogeneity test revealed significant heterogeneity among the included studies (Q = 86,290.54, df = 263, I²_{Level 2}= 61.65%, I²_{Level 3}= 38.02%, τ²_{Level 2}= 0.12, τ²_{Level 3}= 0.08), leading to the use of a three-level random-effect model for the meta-analysis. The comparative assessment of three-level and two-level models demonstrated that the inclusion of a third level improved the accuracy of pooled effect estimation (χ²= 42.39, ΔBIC = 36.82, p < .001). Specifically, approximately 99% of the variance in observed effects was due to variance in true effects rather than sampling error. The variance of true effect sizes, measured in g units, was 0.12 within-clusters and 0.08 between-clusters. Further analysis of Egger's regression test suggests no publication bias in the relevant (t = −1.20, SE = 0.74, p = .232) and the funnel plot is shown in Figure 2. A significant moderate to large CEPIs effect on coaching effectiveness (g = 0.47, k = 264, 95% CI [0.36, 0.59]) was observed (t = 8.29, p < .001). Subsequently, the effect of CEPIs on coaching effectiveness was categorized into two major domains as outcomes regards to coaches and athletes.

Figure 2.

Funnel plot of publication biases.

As for coaches, a large overall effect (g = 0.73, 95% CI [0.47, 1.00]; k = 71, t = 5.57, p < .001) was observed. Further, CEPIs brought a large effect on psychological outcomes such as attitude, intentions, and competence (g = 0.86, 95% CI [0.49, 1.22]; k = 25, t = 4.86, p < .001). In the following, a large effect was found on knowledge gains (g = 0.93, 95% CI [0.35, 1.50]; k = 11, t = 3.60, p < .001), and a moderate to large effect on behavioral changes (g = 0.56, 95% CI [0.23, 0.90]; k = 35, t = 3.40, p = .002). Coaches participated in hybrid type of CEPIs exhibited a large effect (g = 0.90, 95% CI [0.49, 1.31]; k = 26, t = 4.53, p < .001). A smaller but still large effect was also found in online CEPIs (g = 0.70, 95% CI [0.424, 1.15]; k = 26, t = 3.14, p = .004). However, no significant effect of in-person CEPIs was observed (k = 19, t = 2.08, p = .052). Nonformal CEPIs demonstrated a large effect (g = 0.79, 95% CI [0.49, 1.09]; k = 54, t = 5.33, p < .001) on coach outcomes. Comparingly, formal CEPIs demonstrated a moderate to large effect (g = 0.51, 95% CI [−0.14, 1.16], k = 16); however, this effect was not statistically significant (t = 1.66, p = .117). Compared to those including multiple sports (g = 0.82, 95% CI [0.42, 1.23], k = 31, t = 4.20, p < .001), CEPIs including team sports showed a larger effect (g = 0.84, 95% CI [0.45, 1.23]; k = 28, t = 4.43, p < .001). However, no significant effect was observed on CEPIs including individual sports (k = 12, t = 0.88, p = .397). Accordingly, given research designs in CEPIs, a large intervention effect on coaches was found on RCTs studies (g = 0.79, 95% CI [0.28, 1.31]; k = 37, t = 3.11, p = .004), following by non-RCTs studies (g = 0.74, 95% CI [0.47, 1.01]; k = 34, t = 5.57, p < .001). Coaches participated in single workshop CEPIs demonstrated a remotely larger effect (g = 0.79, 95% CI [0.39, 1.19], k = 38, t = 4.00, p < .001) than those who attended long-term CEPIs that involved multiple training sessions spanning a season or year (g = 0.68, 95% CI [0.29, 1.08], k = 33, t = 3.56, p = .001).

Per athlete outcomes, a moderate to large overall effect (g = 0.38, 95% CI [0.28, 0.47]; k = 193, t = 7.79, p < .001) was observed. For the CEPIs group, a moderate to large effect on performance such as psychomotor and game performance (g = 0.58, 95% CI [0.41, 0.74]; k = 28, t = 7.29, p < .001) were noted. The effect of CEPIs on athlete SDT, AGT, and mental health related outcomes was observed to range from small to moderate (g = 0.32, 95% CI [0.23, 0.41]; k = 148, t = 6.86, p < .001). However, no significant effect was observed on athletes’ behavioral change such as anti/prosocial behaviors and physical activity (k = 17, t = 1.86, p = .081). Athletes of their coaches in hybrid CEPIs (g = 0.39, 95% CI [0.06, 0.72]; k = 45, t = 2.40, p = .021) and in-person CEPIs (g = 0.38, 95% CI [0.28, 0.48]; k = 145, t = 7.45, p < .001) exhibited a moderate to large effect. No significant effect was found on CEPIs only applied online training (k = 3, t = 4.01, p = .057). In addition, CEPIs including team sports showed a moderate to large effect (g = 0.39, 95% CI [0.27, 0.51]; k = 127, t = 6.36, p < .001) and including multiple sports (g = 0.29, 95% CI [0.15, 0.44]; k = 54, t = 4.16, p < .001). CEPIs that included individual sports exhibited a marginally significant effect (g = 0.39, 95% CI [0.00, 0.78], k = 12, t = 2.21, p = .049). Moderate to large intervention effects was observed given RCTs studies (g = 0.55, 95% CI [0.20, 0.89]; k = 39, t = 3.22, p = .003) compared to a smaller effect given non-RCTs studies (g = 0.33, 95% CI [0.25, 0.42]; k = 154, t = 7.93, p < .001). Lastly, athletes of their coaches in medium-term CEPIs, which included multiple training sessions, demonstrated a moderate to large effect (g = 0.43, 95% CI [0.27, 0.58], k = 72, t = 5.43, p < .001), following by long-term CEPIs (g = 0.35, 95% CI [0.15, 0.55], k = 79, t = 3.46, p < .001) and single workshop CEPIs (g = 0.31, 95% CI [0.19, 0.43], k = 42, t = 5.27, p < .001).

Key themes and patterns

The co-occurrence analysis, as depicted in Figure 3, on the key themes and keywords in the selected studies, illustrates the research patterns and trends on CEPIs. The color scale transitions from darker to lighter hues, demonstrating the trend of the selected studies from 2003 to date. Shifting our focus to the key theme clusters showed that coaches, athletes, and evidence-based interventions were identified as core clusters within selected studies which were correlated with coach education, effectiveness, assessment, behavior, SDT and AGT elements, and PYD. Further, the results in the co-occurrence analysis demonstrated from the other side that there was a trend that up-to-date investigations and CEPIs were on several key domains such as knowledge, intentions, support, and enjoyment in training sessions and coaching practices.

Figure 3.

Co-occurrence map and key themes in selected studies.

Discussion

The current study aimed to evaluate the impact of CEPIs on coaching effectiveness in the youth sport context. Findings indicate a positive, moderate to large enhancement in coaching effectiveness attributable to a wide range of CEPIs that varied in scope, intervention type, and dosage. However, the impact of CEPIs on coaching effectiveness varied, was not uniformly scalable, and lacked consistent sustainability across different sports for coaches and athletes.

In terms of knowledge gain, attitudes, confidence, and competence, coaches showed greater improvements through non-formal CEPIs. They also expressed a view that formal education is more beneficial for coach developers than coaches themselves, due to its focus on a “train and certify” approach rather than learner-centered methods.⁸⁹ Supporting this, coaches in this study acknowledged the value of formal programs in teaching foundational skills like risk management, safety, and organization, especially for less experienced coaches.⁹⁰ Reflecting these insights, there has been a recent shift from traditional CET/MAC frameworks to more diverse, often online, non-formal training models. These models are particularly suitable for youth sports, where many coaches are volunteers.⁸⁶

In the matter of duration, medium-term CEPIs, characterized by multiple training sessions over a four to six-week period, demonstrated a greater impact on athlete outcomes, suggesting an ideal balance between comprehensive learning and participant engagement. The finding highlights the importance of providing sufficient time for knowledge acquisition and skill development while maintaining participant motivation. However, it's critical to recognize that the specific duration and structure of the training program should be tailored to the unique needs and constraints of the organization, coaches, and athletes involved. Factors such as the content complexity, coaches’ prior knowledge and experience, and available resources should be considered when determining the most appropriate training duration. Therefore, examining the long-term retention and application of the knowledge and skills acquired through the different training durations would be valuable in assessing their enduring impact on coach behaviors and athlete outcomes.

Further, both online and hybrid CEPIs demonstrated a moderate to large significant impact on enhancing coaching effectiveness. Diverging from traditional in-person workshops, these contemporary CEPI formats typically incorporate extensive season-long reflections, mentorship, discussions, and follow-up online modules.^{1,3,31,61,84,85} Internet-based training, recognized for its cost-effectiveness and flexibility, provides a promising alternative for coach education. Recent research by Van Woezik and colleagues suggested future training paradigms might benefit from integrating a comprehensive database of free resources accessible online, enabling coaches to learn at their own pace.⁹¹ This approach aims to reduce time and distance barriers significantly. Furthermore, incorporating interactive multimedia in these online sessions could enhance the overall training impact, fostering better knowledge retention and developing a habit of continuous learning.⁸⁶ Such enhancements are vital for ensuring that coaching education yields long-term practical benefits. Online training is increasingly acknowledged as a valuable tool for training time-constrained coaches.⁹² As evidenced in several studies within this review,^64,87,88 online training programs support schools and programs in meeting the extensive educational requirements imposed by state-level sports laws.^93,94 However, it is crucial to address the limitations of online training, particularly its current inadequacy in providing behavioral feedback, an element coaches find highly informative and crucial for understanding their impact on players.^74,76 This highlights the need for researchers and course designers to evolve online training models to include not just interactive experiences but also individualized feedback loops that allow coaches to reflect on implementation within their sport-specific contexts. This is not a direct substitute for observation of coaching practices but does allow for reflection on training received.

Additionally, accessibility to quality training resources is a significant barrier to coach development, further exacerbating educational inequities. In Australia, volunteers or entry-level community coaches often lack the necessary knowledge and skills to foster a positive sporting environment or maximize the outcomes of football coaching sessions.^84,95,96 A comparable situation is observed in the United States, where the majority of youth sports coaches are volunteers, typically parents.⁹⁷ This reliance on volunteerism introduces additional challenges, such as gender disparities and constraints in training resources, within the youth sports coaching landscape.⁹⁸ Therefore, there is a pressing need for training that specifically targets strategies for creating positive sporting environments and enhancing learning and engagement in community-level coaching. In this context, online or hybrid non-formal training, with a certain level of quality control, may offer an effective solution to impart fundamental coaching knowledge and techniques to most of the community and school-based coaches.

While the development of coach knowledge is crucial, the sports experiences and outcomes of athletes are equally vital for understanding coaching effectiveness. Two-thirds of the studies documented positive developmental outcomes by integrating athlete data, highlighting the importance of considering their perspectives. The mediational model of coach-athlete interactions suggests a discrepancy between coaches’ behaviors and athletes’ perceptions,^76,99 which could be also understood through the lens of the coach-athlete relationship.^19,100 When there is a lack of shared understanding and open communication between coaches and athletes, it might lead to a mismatch in perceptions and experiences.¹⁰¹ The meta-analysis revealed a notable pattern indicating that athletes often did not experience the same level of benefits as their coaches, potentially due to their perceptions of coaching behaviors differing from the coaches’ intentions. The findings highlight the need for coaches to prioritize building strong, positive relationships with their athletes and regularly seeking feedback to ensure alignment between their intentions and athletes’ experiences. These findings also highlight the reality that coaching happens in the context of the broader youth sports system in which coaches are only one influencing factor. Athlete outcomes are further shaped by the family, team, and environmental contexts in which coaching happens.¹⁰²

Coaches occupy a central and critical position in young sport settings with many possible “spill-over” effects into other areas of athletes’ lives beyond sport.⁴⁵ It is widely recognized that the skills, values, and attitudes developed in sports settings can transfer to other areas of life. This is evidenced by significant correlations between mastery and ego achievement in sports with academic success,⁷⁵ emotional intelligence,¹⁰³ and social-emotional skills.^104,105 However, the impact of CEPIs varies by gender. Studies indicate that girls benefit more than boys in aspects like physical activity and self-esteem.^9,24,28,67 This highlights the need for future research to focus on large-scale interventions tailored to girls, especially under the guidance of female coaches. The current study results underscore the multifaceted impact of coaching, emphasizing the need for a holistic approach in coach education that addresses both the development of coaches and the diverse experiences and needs of athletes.

In conjunction with coaches, parents are a crucial component of the youth sports equation. While CEPIs predominantly focus on coaches, a key aspect of the youth sports environment, parents of athletes also emerge as vital participants. Their involvement can significantly impact the dynamics of youth sports programs, sometimes leading to challenges.^29,106,107 Consequently, developing parallel programs tailored for parents could effectively promote positive psychosocial and mental health outcomes in young athletes.^3,29,61

If the ultimate goal is to foster youth development through sports, with a primary focus on athlete outcomes rather than solely on coaching, it's essential to consider interventions that directly engage athletes. Athletes, being at the core of the ecological system of sports, could benefit immensely from specialized workshops.⁵¹ Reflecting on the research by Vella and colleagues on youth mental health literacy and resilience, which involved athletes, parents, and coaches, future studies could adopt a comprehensive ecological approach.³ Given that, this approach would entail incorporating a diverse group of participants and integrating curricula focused on social-emotional learning alongside mental health literacy. Such a holistic strategy could yield more profound and lasting benefits in the realm of youth sports and development.

Coaching ineffectiveness

The identification of insignificant or controversial outcomes from CEPIs is as crucial as recognizing significant positive results. These outcomes offer valuable insights into the barriers and challenges that hinder the effective implementation and adoption of training learnings.⁷⁰ Approximately one-third of the reviewed studies reported non-significant or contradictory results concerning CEPIs. Factors contributing to these outcomes may include entrenched social norms, flaws in study design, and inappropriate statistical analyses.

In the opinion of Hertting, coach education and learning are considered as ongoing sociocultural processes.¹⁰⁸ Prior to the CEPIs implementation, a pivotal step involves researchers and coach educators confronting entrenched cultural barriers in youth sports. These barriers, characterized by a preference for control-oriented coaching, a ‘win-at-all-costs’ mentality, and a masculine-centric culture, significantly impede the promotion of healthier coaching practices. Mahoney et al. highlighted the complexity and long-term commitment required to address these harmful cultural norms, particularly the prevalence of controlling coaching behaviors.⁷⁰ Such behaviors often stem from external pressures faced by coaches, including expectations regarding athlete performance and reactions to athletes’ passive engagement, as identified by Mageau and Vallerand¹⁰⁹ and Reeve.¹¹⁰ To counteract these influences, Reeve and colleagues suggested strategies including reducing power imbalances between coaches and athletes, redefining coaching responsibilities in collaboration with stakeholders, and emphasizing the negative consequences of control-oriented practices.¹¹¹ Incorporating coaches in the development and implementation of autonomy-supportive interventions is crucial. As Michie and colleagues¹¹² and McLean and Mallett¹¹³ argued, such collaborative approaches, tailored to meet coaches’ specific needs, are likely to be more effective in facilitating lasting behavioral change. Moreover, drawing upon critical theory and critical pedagogy, Newman et al. emphasized the necessity of integrating critical positive youth development perspectives into coach education programs to equip coaches with specific strategies for systematically and deliberately addressing social issues within their coaching practices.¹¹⁴

Furthermore, results showed that while coaches gained knowledge from the online training, it might not have been effectively transformed into coaching practice. The absence of long-term retention of outcomes, as noted in previous studies,⁸⁸ could stem from various factors, such as the lack of interactive multimedia or insufficient emphasis on reflection and discussion. Enhancements like increasing session frequency, incorporating booster sessions, introducing self-monitoring procedures, or providing ongoing feedback could potentially amplify the training's effectiveness, applicable to both online and hybrid formats. Moreover, to address the limitations of immediate post-training assessments, future research should employ a longitudinal design. The longitudinal design should include control groups (e.g. attention control, waiting list control) and follow-up measures to evaluate both short-term (immediate post-test) and long-term (e.g. 6-month follow-up) knowledge retention.²²

Additionally, the inherent multilevel nature of sports and coaching data necessitates appropriate analytical approaches.¹¹⁵ MLM is particularly beneficial in coaching science, allowing the analysis of how contextual factors at a higher level (e.g. team level) influence individual behaviors (e.g. athlete outcomes). The value of MLM in capturing these complex interactions is underscored by Myers and colleagues.¹¹⁶ The necessity for MLM arises from the frequent violation of the independence assumption in individual-level observations, a limitation often encountered in alternative statistical procedures like analysis of variance, as observed in several studies.^{26–28,31,70–72,74,77,79,81,85} Traditional single-level analyses, when applied to coach-athlete cluster data, can result in inaccurately high significance levels, as highlighted by Papaioannou and colleagues.¹¹⁷ Given the importance of athlete outcomes, perceived coaching behaviors, and motivational climate as indicators of coaching effectiveness, implementing MLM offers a more robust analytical framework than single-level analyses.

To our knowledge, this is the first systematic review and meta-analysis examining the effect of CEPIs on coaching effectiveness. The findings could be beneficial for coach education practices and future research endeavors. However, despite the strengths of this study, several limitations should be acknowledged. Firstly, although coaching effectiveness is defined as a combination of coach knowledge, athlete outcomes, and coaching context in a well-established model, measuring the impact of CEPIs on coaching effectiveness through a single model has limitations. The lens of what “coaching effectiveness” means has been broadened in the past 10 to 15 years to encompass a more robust inclusion of PYD outcomes including moral education, social-emotional wellness, identity, and mental health as well as equity and justice-oriented outcomes.^114,118,119 It is essential to recognize that various factors, such as the uniqueness of the team and coach dynamics, the age and gender of athletes, type of sport, delivery of CEPIs, and coaches’ backgrounds, all appear to influence coaching effectiveness. Besides, due to most interventions being delivered via in-person and hybrid formations, there was a limited sample size to quantify the effect of online CEPIs. In addition, most of the included studies were conducted in the United States, Australia, Canada, and European countries. Consequently, CEPIs studies conducted in developing countries are under-represented in the findings. Beyond that, the limited demographic information reported in selected studies regarding participants’ SES and ethnicity undermines the generalizability of the research findings. Due to these limitations, the interpretation and generalizability of the results should be approached with caution.

Future research directions

Future research should investigate coaches’ effectiveness in influencing athletes’ mental health outcomes, examining the mechanisms through which coaches’ behaviors and the team culture they create impact well-being and identifying best practices for promoting emotional safety and mental health across coaching contexts. A more specific examination of CEPIs across diverse samples, considering factors such as gender, race/ethnicity, and SES, is warranted to inform the development of inclusive and culturally responsive coach education programs. Exploring the effectiveness of decentralized and flexible coach education models that emphasize sociocultural learning processes and mentorship, as well as investigating support systems tailored to diverse coaches’ and athletes’ identities, remain important priorities.

Moreover, examining developmental issues in relation to coach behavior is crucial to design age-appropriate interventions that optimize athlete development and well-being across different stages. Researchers should consider how coaches’ knowledge, awareness, and experiences may influence their behaviors and effectiveness when working with athletes of various ages and skill levels. To address these research directions, it is imperative to utilize validated measurement tools, representative samples, athletes’ voices, and ecologically valid research designs that capture both subjective and objective data over extended periods, including follow-up assessments post-intervention. Adopting a broader perspective, moving beyond traditional coach education to include a comprehensive support system for youth athletes and caregivers, could enhance coach retention, improve coach-athlete interactions, and support long-term athlete development.

Conclusions

Coach education emerges as a catalyst of moderate yet positive transformations in both coaches and youth athletes, with the scale tipping favorably towards more significant advancements in coaches’ development. Early-career, self-motivated coaches particularly exhibited significant gains in coaching effectiveness through CEPIs. While these findings are promising, they should be approached with caution due to variability in their magnitude, scalability, and sustainability for both coaches and athletes. The presence of certain insignificant or contradictory results in the study offers critical insights for the ongoing development and refinement of CEPIs.

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Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Longxi Li

Hannah O. Olson

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