Evaluating the Coaching for Life Skills online training program: A randomised controlled trial

Psychology of Sport & Exercise 48 (2020) 101649

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Psychology of Sport & Exercise journal homepage: www.elsevier.com/locate/psychsport

Evaluating the Coaching for Life Skills online training program: A randomised controlled trial

T

Martin Camiréa,∗, Kelsey Kendellena, Scott Rathwellb, Stéphanie Turgeonc a

University of Ottawa, School of Human Kinetics, University of Ottawa, 125 University Private, Ottawa, K1N 6N5, Canada University of Lethbridge, Department of Kinesiology and Physical Education, University of Lethbridge, 4401 University Drive, Lethbridge, T1K 3M4, Canada c University of Montreal, School of Psychoeducation, University of Montreal, 90 Vincent d’Indy Avenue, Montreal, H2V 2S9, Canada b

A R T I C LE I N FO

A B S T R A C T

Keywords: Student-athlete Competence Autonomy Relatedness Youth Development

Objectives: High school sport is considered a suitable context in which to develop life skills, yet most coaches are not equipped with the knowledge/tools needed to deliberately teach life skills. The purpose of the study was to evaluate the effectiveness of the Coaching for Life Skills online training program in helping coaches create environments conducive to the teaching of life skills. Design: Randomised controlled trial using a concurrent multiple baseline across groups design. Method: A total of 1,238 (58.8% male) Canadian high school coaches completed baseline testing examining coach-athlete relationship, coach interpersonal behaviours, and life skills teaching. Participants were then randomly assigned to an experimental, waitlist, or control group. A final sample of 285 (59.7% male) participants completed the trial (i.e., 36 experimental, 58 waitlist, and 191 control). Data were analysed using 3 x 3 repeated measures factorial analyses. Results: Across the three constructs assessed, there were no significant within-subject main effects for time, group, or for the interaction between time and group. Conclusions: Although the results were not statistically significant, visual analysis indicated positive directional changes for all three dependent variables, with increases in mean scores observed for both experimental and waitlist group participants following their completion of the Coaching for Life Skills online training program. Findings have implications for the design of online coach training programs aimed at helping coaches teach life skills through sport.

1. Introduction High school sport is situated as a suitable context in which to develop life skills given its standing as one of the most popular extracurricular activities for students (Camiré & Kendellen, 2016). In Canada, over 750,000 students practice high school sports, referred to as school-sponsored sports practiced outside regular class hours in which students compete in organised interscholastic leagues that lead to endof-season championships (School Sport Canada, 2018). Life skills (e.g., communication, time management, teamwork) are defined as skills “that enable individuals to succeed in the different environments in which they live, such as school, home and in their neighbourhoods” (Danish, Forneris, Hodge, & Heke, 2004, p. 40). Gould and Carson (2008) discussed how for a skill learned in sport to be deemed a “life” skill, it must transfer and be used beyond sport. Otherwise, if a skill is

applied solely in sport, it constitutes a sport skill. Consistent with this notion, Pierce, Gould, and Camiré (2017) defined life skills transfer as the: Ongoing process by which an individual further develops or learns/ internalises a personal asset (psychosocial skill, knowledge, disposition, identity construction or transformation) in sport and then experiences personal change through the application of the asset in one or more life domains beyond the context where it was originally learned (p. 194). Past research has indicated that the positive (e.g., lower depressive symptoms, higher grade point averages) and negative (e.g., discrimination, favouritism) outcomes experienced by students in high school sport are, in many cases, highly influenced by the climates created by coaches (Buford-May 2001; Dworkin & Larson, 2006; Jewett et al., 2014; Van Boekel et al., 2016). Coaches are ideally situated to mentor students and help them excel in and beyond sport when they

∗

Corresponding author. University of Ottawa, School of Human Kinetics, University of Ottawa, 125 University Private, Ottawa, K1N 6N5, Canada. E-mail addresses: [email protected] (M. Camiré), [email protected] (K. Kendellen), [email protected] (S. Rathwell), [email protected] (S. Turgeon). https://doi.org/10.1016/j.psychsport.2020.101649 Received 10 May 2019; Received in revised form 13 November 2019; Accepted 10 January 2020 Available online 16 January 2020 1469-0292/ © 2020 Elsevier Ltd. All rights reserved.

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Hancock, 2014), recent models (Bean, Kramers, Forneris, & Camiré, 2018; Holt et al., 2017) clearly stress that developmental gains are maximised when coaches choose to teach life skills in intentional manners. For instance, in the Holt et al. (2017) model of positive youth development (PYD) through sport, it is posited that: “The combined effects of a PYD climate [implicit approach] and a life skills focus [explicit approach] will produce more PYD outcomes than a PYD climate alone” (p. 38). Correspondingly, in the Bean et al. (2018) implicit/ explicit continuum of life skills development and transfer, it is stated that youth sport participants have a greater likelihood of experiencing positive development outcomes when coaches become more explicit in their approach to teaching life skills. Thus, when it comes to life skills teaching, a high level of intentionality is a desired characteristic and youth sport coaches should hence be trained to adopt explicit approaches. However, the reality is that few coaches are trained to teach life skills (Vella, Oades, & Crowe, 2013) and many face barriers in accessing life skill-specific coach education (Santos et al., 2017), despite life skills being heralded as a priority for coach education (Newman, Ortega, Lower, & Paluta, 2016). In attempts to help youth sport coaches adopt explicit life skills teaching approaches, researchers have developed specialised training opportunities (e.g., Falcão, Bloom, & Gilbert, 2012; Ferris, Ettekal, Agans, & Burkhard, 2016; Harwood, Barker, & Anderson, 2015; Koh, Camiré, Bloom, & Wang, 2017; Santos et al., 2019; Strachan, MacDonald, & Côté, 2016; Vella et al., 2013). Generally speaking, evaluations of these specialised training opportunities have yielded positive outcomes, with coaches indicating increases in awareness (Santos et al., 2019), knowledge (Falcão et al., 2012), self-reflection (Ferris et al., 2016), and confidence (Koh et al., 2017) as it pertains to teaching life skills. However, it is important to consider the small scale of these evaluations, with most having occurred in a single setting/ team/club and none including more than 20 coaches. Further, the majority of studies relied on qualitative interviews and/or nonvalidated forms/surveys as data collection techniques, the exception being Vella et al. (2013) who used a quasi-experimental pre-post design with validated scales. None of the evaluations proceeded to the random assignment of participants, limiting the inferences that can be made. Some of these specialised training opportunities have been delivered as self-administered online education programs, in recognition of coaches’ time pressures and due to the inherent flexibility of this approach. For example, Strachan et al. (2016) evaluated ProjectSCORE!, a self-directed module-based online program offering readings, videos, and activities designed to use the 4Cs (i.e., competence, confidence, connection, character) as a platform for teaching positive development through sport. In the coach’s locker room on the ProjectSCORE! website, coaches can access activities (e.g., in the character section) intended to help them integrate life skills such as respect and leadership in their coaching. The four coaches who completed the pilot evaluation of ProjectSCORE! were interviewed and asked to describe their experiences. Findings indicated how coaches believed the online modules were useful in helping them prepare lessons integrating the 4Cs into their coaching. Although participants indicated being satisfied with this online intervention (Strachan et al., 2016), the study’s design and small sample preclude conclusions being drawn in terms of the effectiveness of online coach education initiatives. If we consider the inherent educational mandate of high school sport, it is imperative that coaches make deliberate efforts to go beyond teaching sport-specific skills; they must be afforded opportunities to learn how to intentionally teach life skills in ways that meet their needs and priorities (Newman et al., 2016). In a study conducted by Camiré, Rocchi, and Kendellen (2016) that involved 3,062 Canadian high school coaches, results indicated how coaches faced many time pressures (e.g., meeting family obligations, managing administrative duties) that hindered their ability to access coach education and learn how to teach life skills. Consequently, they rated internet coach education as an initiative most useful to their professional development. Likewise, Thrower,

offer appropriate instructions, build quality relationships, satisfy students’ basic psychological needs, and deliberately teach life skills (Bailey et al., 2009; Carson Sackett & Gano-Overway, 2017). Explanations have been advanced linking coach-created climates to life skills development, most notably that (a) sport’s inherent skill-building nature affords coaches opportunities to foster life skills acquisition (Bean & Forneris, 2016), (b) sport’s social nature affords coaches opportunities to help athletes build social capital and learn interpersonal life skills such as communication and teamwork (Camiré, 2015), and (c) the density of interactions afforded through sport (e.g., practices, games, locker room, team bus) allows coaches to foster desired life skills-related outcomes (Petitpas, Cornelius, Van Raalte, & Jones, 2005). From a theoretical standpoint, several conceptual models have been proposed to delineate the links between the coach-athlete relationship, basic psychological needs, and life skills teaching. Hodge, Danish, and Martin (2013) advocated for the integration of the basic psychological needs of autonomy (i.e., acting in ways consistent with one’s sense of self), competence (i.e., experiencing mastery during interactions with individuals in the environment), and relatedness (i.e., feeling securely attached and respected by significant others) within their Life Development Intervention model. Within their updated model, the three needs are positioned as key mechanisms leading to life skills development, with specific needs associated with the learning/refinement of specific life skills (e.g. autonomy with self-control, competence with coping with stress, relatedness with consideration of others’ feeling). Newman and colleagues (e.g., Newman & Alvarez, 2015; Newman, Kim, Alvarez, & Tucker, 2018), in their Coaching on the Wave model, proposed that for coaches to develop a positive team culture, they must recognise the coach-athlete relationship as foundational in helping them address the basic psychological needs (i.e., through collective valuing activities) as well as the teaching of life skills (i.e., through intentional, facilitative, and sequenced activities). From an empirical standpoint, past research has demonstrated associations between the coach-athlete relationship, basic psychological needs, and life skills teaching. For example, studies have shown how close, committed, and complementary relationships between coaches and athletes can promote athletes’ well-being through the satisfaction of their basic psychological needs (Choi, Cho, & Huh, 2013; Felton & Jowett, 2013; Jowett et al., 2017). Further, studies conducted with award-winning high school coaches have shown how the creation of strong coach-athlete relationships is key to effective life skills teaching (Collins, Gould, Lauer, & Chung, 2009; Gould, Collins, Lauer, & Chung, 2007). Associations between basic psychological needs satisfaction and positive psychosocial outcomes have also been reported, with needs satisfaction shown to predict outcomes that include increases in selfesteem, identity reflection, and initiative (Bean & Forneris, 2019; Bean, Forneris, & Brunet, 2016). Recently, Camiré, Rathwell, Turgeon, and Kendellen (2019) surveyed 1,238 Canadian high school coaches, examining associations between the coach-athlete relationship, basic psychological needs, and life skills teaching. Structural equation modelling was used to test the relationships between these three variables, with the basic psychological needs as a mediator. Results indicated that coaches’ perceptions of their interpersonal behaviours satisfying athletes’ basic psychological needs either fully or partially mediated the positive relationships between the coach-athlete relationship and life skills teaching. Thus, strong coach-athlete relationships and coach interpersonal behaviours that satisfy athletes’ autonomy, competence, and relatedness ought to be regarded as foundational pieces of the life skills teaching process in high school sport. Although empirical studies (e.g., Bean & Forneris, 2016; Chinkov & Holt, 2016) have indicated how both implicit (i.e., a focus on teaching sport skills with little/no attention paid to teaching life skills and life skills transfer) and explicit (i.e., a focus on the concurrent teaching of sport skills, life skills, and life skills transfer) approaches to coaching can foster life skills development and transfer (Turnnidge, Côté, & 2

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competence, and relatedness, and (c) teaching life skills and their transfer. For optimising the coach-athlete relationship, coaches are provided with several examples of relationship-building strategies that take into consideration notions of closeness, commitment, and complementarity (Jowett, 2007). For exhibiting interpersonal behaviours that support athletes’ autonomy, competence, and relatedness, coaches are exposed to concrete strategies known to satisfy the basic psychological needs as well as examples of autonomy-supportive change-oriented feedback they can use with their athletes (Carpentier & Mageau, 2016). For teaching life skills and their transfer, coaches are shown several evidence-informed strategies (Camiré, Forneris, Trudel, & Bernard, 2011; Pierce, Kendellen, Camiré, & Gould, 2018), many supplemented with videos, offering coaches visual examples of how they can teach sport skills and life skills concurrently. The online interface of the CLS program is designed to be interactive in nature; it is fully narrated, includes reflective activities, and offers an integrated notetaking system. A pause-rewind feature is also at coaches’ disposal, allowing them to navigate the modules at their own pace. At the end of the program, coaches complete a short quiz (i.e., designed as a reflective exercise, not a formal evaluation), with detailed feedback offered for every question on why they answered it correctly or incorrectly. For a detailed description of the conceptual foundation of the CLS program, please see (Camiré et al., 2018).

Harwood, and Spray (2019) highlighted the benefits of online education, particularly in relation to the economies of money, time, planning, and travel accrued compared to traditional face-to-face delivery models. Further, adult learners have indicated preferences for self-administered online education programs as these can be completed at one’s own pace and allow greater flexibility when accounting for work commitments and childcare responsibilities (Breitenstein, Gross, & Christophersen, 2014). Despite the claimed benefits, very few online coach education programs specific to life skills exist and even fewer have been formally evaluated. To date, evaluations have been conducted with very small samples and generally lack in methodological rigour, limiting the strength of the inferences that can be made. As Newman et al. (2016) discussed, getting answers to questions of coach education effectiveness is vital if self-administered online education programs are to be further pursued as a worthwhile medium for helping coaches intentionally create environments conducive to life skills development. 1.1. The present study The purpose of the study was to evaluate the effectiveness of the Coaching for Life Skills (CLS) online training program in helping coaches create environments conducive to the teaching of life skills, using a randomised controlled trial design. We hypothesised that compared to baseline, coaches in the experimental and waitlist groups would, after completing the CLS program, perceive (a) enhanced coach-athlete relationships, (b) increased use of coach interpersonal behaviours that satisfy athletes’ basic psychological needs, and (c) increased use of strategies for teaching life skills, while coaches in the control group would not.

2. Method 2.1. Design A 3 x 3 randomised controlled trial was conducted using a concurrent multiple baseline across groups design, through which an intervention is introduced in a staggered fashion across groups with the goal of testing the hypothesis that change is observed only after the introduction of the intervention (Morgan & Morgan, 2008). Consistent with CONSORT guidelines for randomised control trials (Schulz, Altman, & Moher, 2010), participants were randomly assigned to three groups following baseline testing (i.e., experimental, waitlist, or control). The design is considered double blind as research team members were blinded to participant allocation and participants were blinded to the study purpose. Research team members never interacted with any of the participants, thereby rendering experimenter bias a non-concern. Interactions with participants were limited to one research assistant (i.e., hired solely to oversee data collection, not involved in analysis and writing) responsible for participant allocation (i.e., using an online randomiser software that rendered group allocation purely to chance) by emailing links to the CLS program and surveys at specific intervals. In terms of intervention fidelity, the CLS program functions as an online, stand-alone, and self-directed coach education initiative, meaning experimental and waitlist participants received the intervention in an identical manner.

1.2. Coaching for life skills program The CLS program was developed for high school coaches to help them create environments conducive to the teaching of life skills. A focus on life skills is a high priority in high school sport given the mandate to “promote and advocate for positive sportsmanship, citizenship and the total development of student athletes through interscholastic sport” (School Sport Canada, 2018). The CLS program is grounded in the PYD approach (Larson, 2000), where life skills are positioned as key assets to be facilitated in the process of nurturing youth thriving. Consistent with several ProjectSCORE! design elements (e.g., evidence-informed, self-administered, online, module-based, use of videos), the CLS program was conceived as a short-duration (i.e., ~90min completion time) coach education initiative intended to inform coaches on the key role they play in creating environments conducive to the deliberate teaching of life skills. The CLS program was initially piloted using an in-person format and assessed using a qualitative process evaluation design (Camiré, Kendellen, Rathwell, & Felber Charbonneau, 2018). Results of the pilot evaluation indicated that coaches believed the CLS program increased their awareness of the importance of nurturing coach-athlete relationships and of using high school sport as a context for teaching life skills. In terms of recommendations for future iterations of the CLS program, pilot results were consistent with those of past studies with Canadian high school coaches (e.g., Camiré et al., 2016) and indicated how coaches had a preference for short, easy to access, and flexible online coach education Thus, the CLS program was designed with those results in mind. Further, the pilot evaluation led to minor adjustments being made to the CLS program, including (a) creating videos of life skills strategies, (b) providing examples of life skills strategies for several sports, and (c) shifting proportions from less theory to more practical activities. The CLS program is organised in five modules exposing coaches to tools and strategies for (a) optimising the coach-athlete relationship (b), exhibiting interpersonal behaviours that support athletes’ autonomy,

2.2. Recruitment Once university ethical approval was received, the research team worked with the executive directors of three Canadian provincial high school athletic associations (i.e., Alberta Schools’ Athletic Association, British Columbia School Sports, School Sports Newfoundland and Labrador) to recruit coaches. To coach high school sports in these three provinces, coaches must officially register with their respective high school athletic association. Thus, each organisation compiles an annual coaching list (i.e., first/last name, email, and affiliated school) encompassing all coaches (i.e., population) coaching high school teams in their province. The three executive directors agreed to share their 2017–2018 coaching lists with the research team (i.e., a memorandum of understanding was signed with each province setting strict parameters on list usage). Using the coaching lists, we proceeded to email the study invitation letter in January 2018 to the 11,395 coaches 3

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Fig.1. CONSORT flow diagram.

waited two weeks to complete the Time 3 survey (seven weeks after Time 1). For the control group, upon completing the Time 1 survey, participants completed the Time 2 survey (i.e., three weeks after Time 1) and Time 3 survey (i.e., seven weeks after Time 1). Control group participants were granted access to the CLS program six months after the trial was completed, meaning there was no chance of contamination. Please see Fig. 2 for a visual representation of the intervention design.

coaching high school sports in these three provinces. In the study invitation letter emailed in each province, a statement of support from the executive director was included. The aim of this statement of support was to encourage coaches to participate, assured that their provincial high school athletic association formally approved the study. A response rate of 12.9% (n = 1,467) was obtained. Please see Fig. 1 for the CONSORT flow diagram. 2.3. Procedure

2.4. Participants From the 1,467 participants who answered the online baseline survey (i.e., Time 1), 190 were excluded for not meeting the inclusion criteria (i.e., they were not actively coaching in 2017–2018 due to retirement or leave of absence) while 39 were excluded for incomplete data (n = 1,238). Following baseline testing, participants were randomly assigned to either the experimental, waitlist, or control group. Participants in all three groups were required to complete the online survey at two additional time points over the course of the trial. The online survey was identical for all three groups and participants were asked to complete it at each time point within one week. At each time point, survey items were randomly ordered within each validated scale to prevent order effects. For the experimental group, upon completing the Time 1 survey, participants were immediately emailed a link providing access to the CLS program and given one week to complete it. Upon completion of the CLS program, participants completed the Time 2 survey (i.e., three weeks after Time 1) and Time 3 survey (i.e., seven weeks after Time 1). For the waitlist group, upon completing the Time 1 survey, participants waited three weeks to complete the Time 2 survey. Immediately after completing the Time 2 survey, participants were emailed a link providing access to the CLS program and given one week to complete it. Upon completion of the CLS program, participants

In terms of inclusion criteria, only coaches who completed the CLS program within the allotted 1-week timeframe were included in the analyses. Further, only coaches who completed the online survey, at all three time points, within the allotted 1-week timeframe were included in the analyses. Such strict inclusion criteria (i.e., holding all three groups to a rigid timeline) guarded against threats to internal validity such as maturation and history by ensuring that “groups [were] treated and observed in an identical manner” (Akobeng, 2008, p. 280). In total, 285 (males = 170, 59.7%) high school coaches from Alberta (53.4%), British Columbia (37.5%), and Newfoundland and Labrador (9.1%) completed the trial, met the inclusion criteria, and were included in the analyses. The final sample included 36 experimental group participants, 58 waitlist group participants, and 191 control group participants. Coaches were on average 42.2 years of age (SD = 11.1). Most coaches held a university degree (n = 232, 81.4%) and were full-time teachers at the school where they coached (n = 183, 64.2%). The majority reported coaching one sport (n = 168, 59.3%) in 2017–2018, while the remaining reported coaching two or more sports (n = 116, 40.7%). Finally, 217 (76.1%) coaches reported having received coach training during their career in Canada’s National Coaching 4

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Fig. 2. Intervention design.

Participants’ perspective on life skills teaching was measured using a modified coach version of the Life Skills Scale for Sport (LSSS; Cronin & Allen, 2017). Changes to the scale included small alterations to the instructions, stem, and wording of items in order to capture the perspective of the coach. Instructions in the original version were “Please rate how much your sport has taught you to perform the skills listed below”, which were changed in the coach version to “Please rate the extent to which you have taught your athletes to perform the skills listed below.” The original stem “This sport has taught me …” was changed to “Through sport, I teach my athletes to …” Finally, nine items were slightly modified to capture the perspective of the coach. For example, item 8 “Set goals so that I can stay focused on improving” was modified to “Set goals so that they can stay focused on improving”. This 43-item scale is divided into eight subscales: teamwork (e.g., work well within a team), goal setting (e.g., set challenging goals), social skills (e.g., start a conversation), problem solving and decision making (e.g., think carefully about a problem), emotional skills (e.g., notice how they feel), leadership (e.g., be a good role model for others), time management (e.g., control how they use their time), and interpersonal communication (e.g., speak clearly to others). Items are measured on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree), with higher scores indicating higher levels of perceived life skills teaching. Cronin and Allen (2017) found the LSSS had good structural, convergent, and discriminant validity, as well as test-retest reliability. The modified coach version of the LSSS used in the present study was tested with a large sample of Canadian high school coaches (n = 1,238) and evidence for the factorial validity and internal consistency reliability of the scale was found (Camiré et al., 2019; CFI = 0.953, TLI = 0.949, SRMR = 0.031, RMSEA = 0.036 (90% CI = 0.034–0.037), and SBχ2 = 2133.31 (p < 0.01).

Certification Program. The coaches’ demographic characteristics are consistent with those of coaches in other large-scale studies conducted with Canadian high school coaches (e.g., Camiré et al., 2016). 2.5. Instruments Participants’ perspective on the coach-athlete relationship was measured using the Coach-Athlete Relationship Questionnaire (CARTQ; Jowett & Ntoumanis, 2004; Yang & Jowett, 2012). The scale consists of 11 items measured on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree) divided into three subscales: closeness (e.g., I feel close to my athletes), commitment (e.g., I respect my athletes), and complementarity (e.g., When I coach my athletes, I feel responsive to their efforts). Higher scores indicated a perceived higher quality coachathlete relationship. Recently, (Camiré et al., 2019) employed the CART-Q with Canadian high school coaches (n = 1,238) and found good model fit: CFI = 0.922, TLI = 0.896, SRMR = 0.043, RMSEA = 0.084 (90% CI = 0.077–0.0.092), and SBχ2 = 401.75, p < .001. Participants’ perspective on their interpersonal behaviours while coaching was measured using the Interpersonal Behaviors Questionnaire-Self (IBQ-Self; Rocchi, Pelletier, & Desmarais, 2017). This 24-item scale measures supportive behaviours (e.g., Support the choices they make for themselves) as well as thwarting behaviours (e.g., Pressure them to do things my way). Items are divided into six subscales: autonomy-supportive, competence-supportive, relatedness-supportive, autonomy-thwarting, competence-thwarting, and relatednessthwarting, all of which are measured on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree). Higher scores on the support subscales indicated greater perceived display of need-supportive behaviours and lower scores on the thwarting subscales indicated lower perceived display of need-thwarting behaviours. Camiré et al. (2019) employed the IBQ-Self with Canadian high school coaches (n = 1,238) and found it had good psychometric properties CFI = .967, TLI = 0.962, SRMR = 0.032, RMSEA = 0.029 (90% CI = 0.025–0.033), and SBχ2 = 484.83, p < .001.

3. Preliminary analyses Prior to conducting the main analyses, descriptive statistics were inspected and transformations were performed using SPSS 25 (George & Mallery, 2018). First, the percentages of missing data and patterns of 5

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complementary evidence to statistical analyses by helping to consider the effect of an intervention (Bourret & Pietras, 2014; Smith, 2012; Tate et al., 2016). Although not all studies are amenable to visual analysis, the design adopted in the present study (i.e., 3 x 3) meant that trends across group and time could be compared. In this sense, visual analysis was particularly useful given the use of our concurrent multiple baseline across groups design, as the staggered sequence of initiation to the CLS program made it possible to observe how directional changes on our dependent variables were related to participating in the CLS program. Thus, having an experimental group and a waitlist group who received the intervention at different times, in addition to a true control group, added to the internal validity of the study. The visual analysis allowed for more information to be gathered regarding the intervention effect by considering if changes in the dependent variable coincided with the introduction of the intervention at different time points. Another reason why visual analysis was used relates to the strict timelines of the trial (i.e., to guard against validity threats), which resulted in underpowered statistical analyses (i.e., power ˂ 0.80). Of note, interpretations made from visual analysis must be drawn cautiously and should not be considered equivalent in terms of rigour to interpretations derived from statistical analyses performed on adequately powered samples (Kendall, Comer, & Chow, 2013).

missingness were assessed. Missing data percentages were small (less than 2%) for all variables and data were missing at random. Missing data were treated using multiple imputations (Schlomer, Bauman, & Card, 2010). All analyses were conducted using total scores for each questionnaire (i.e., the sum of all items), with negatively worded items reverse scored when calculating total scores. Initial descriptive statistics showed that some scale level data were outliers (i.e., ± 1.96 SD). Thus, Winsorising was applied to bring outliers within the normal range (i.e, ± 1.95 SD; Tabachnick & Fidell, 2013). Scale scores were then screened at each time point for normality using confidence intervals (Wright & Herrington, 2011). Results indicated a negative skew for the CART-Q at Time 1, skewness = −0.81; CI (−1.29 – -0.32) and at Time 2, skewness = −0.34; CI (−0.62 – -0.05). The LSSS had evidence of skewness at Time 1 = −0.33; CI (−0.62 – -0.05). Evidence of kurtosis for the CART-Q was found at Time 2, Kurtosis = −0.63; CI (−1.20 – -0.07) and Time 3, Kurtosis = −0.86; CI (−1.42 – -0.30). Kurtosis was found for the IBQ-Self at Time 1, Kurtosis = −0.69; CI (−1.26 – -0.13) and for the LSSS at Time 3, Kurtosis = −0.58; CI (−1.14 – -0.01). Past studies have found negative skew and kurtosis for these scales (Cronin & Allen, 2017; Jowett & Ntoumanis, 2004; Rocchi et al., 2017). Although confidence intervals indicated some skewness and kurtosis, all values were within acceptable ranges (i.e., ≥ |2.00|; George & Mallery, 2018). Thus, parametric tests were used. Please see Table 1 for descriptive statistics. ANOVAs and chi-square analyses were performed to identify if significant differences existed between the experimental, waitlist, and control groups on demographic variables. Results indicated that the groups did not differ by age, F(2, 282) = 0.24, p = .784, ηp2 = 0.002, gender χ2(2, N = 285) = 1.63, p = .443, level of education, F(2, 282) = 0.37, p = .691, ηp2 = 0.003, occupation (i.e., teacher or other), χ2(2, N = 285) = 0.96, p = .618, marital status (i.e., single, married, divorced), χ2(12, N = 284) = 9.98, p = .618, number of sports coached, F(2, 281) = 0.05, p = .953, ηp2 < 0.001, type of sports coached (i.e., individual, team, or both) χ2(4, N = 283) = 9.21, p = .056, and coach training (i.e., yes or no), χ2(2, N = 284) = 2.43, p = .296.

5. Results 5.1. Coach-athlete relationship All assumptions were tested. Box’s M (143.61) was significant, p < .001, indicating that there were significant differences between the covariance matrices. Additionally, Mauchly’s Test was significant, χ2(2) = 86.14, p < .001, meaning that the assumption of sphericity was not met. Thus, the Greenhouse-Geisser correction was applied when interpreting results (Tabachnick & Fidell, 2013). Levene’s Test was also significant for the CART-Q at Time 1, F(2, 282) = 6.32, p = .002, indicating that variance differed across groups. As a result, a more stringent α of .025 was applied to determine significance (Tabachnick & Fidell, 2013). 3 x 3 repeated measures factorial analysis. There was no significant within-subject main effect for time, F(1.58, 446.19) = 0.47, p = .58, ηp2 = 0.002, group F(2, 282) = 1.04, p = .36, ηp2 = 0.007, or the time-group interaction F(3.16, 446.19) = 3.04, p = .026, ηp2 = 0.021. A small effect was found for the time-group interaction (ηp2 = 0.021). Visual inspection. For the experimental group, mean scores on the CART-Q increased after completing the CLS program (T1: M = 68.53, SD = 11.46; T2: M = 70.33, SD = 5.08), and gains were generally maintained at follow up (T3: M = 70.25, SD = 4.77). For the waitlist group, mean scores decreased from Time 1 (M = 68.86, SD = 5.09) to Time 2 (M = 67.97, SD = 5.83), then increased back to baseline levels

4. Main analyses The main analyses were conducted in two steps. In step one, 3 x 3 repeated measures factorial analyses were run to test the main effect of group (i.e., experimental, waitlist, control) and time (i.e., Time 1, Time 2, Time 3), as well as the interaction between group and time on the dependent variables of interest. Effect sizes were interpreted using partial eta squared (ηp2), with values greater than 0.01, 0.06, and 0.14 representing small, medium, and large effect sizes, respectively (Cohen, 1988). In step two, a visual analysis of the estimated marginal means was performed to see if trends existed across the dependent measures. Visual analysis has been employed to compare baseline and intervention trends in small sample designs (Kazdin, 2011) and can act as Table 1 Descriptive Statistics. Scale

CART-Q

IBQ-Self

LSSS

Time

1 2 3 1 2 3 1 2 3

M

SD

Skewness

Kurtosis

Confidence intervals

Statistic

SE

Statistic

Statistic

SE

Statistic

SE

Skewness

69.17 69.03 69.29 144.06 143.20 144.09 261.69 259.71 261.11

0.587 0.305 0.283 0.626 0.653 0.626 1.259 1.374 1.346

5.687 5.148 4.773 10.573 11.031 10.562 21.258 23.198 22.724

−0.805 −0.335 −0.022 −0.091 −0.102 0.000 −0.334 −0.233 −0.110

0.249 0.144 0.144 0.144 0.144 0.144 0.144 0.144 0.144

0.429 −0.632 −0.860 −0.560 −0.695 −0.491 −0.010 −0.473 −0.576

0.493 0.288 0.288 0.288 0.288 0.288 0.288 0.288 0.288

−1.29 −0.62 −0.30 −0.37 −0.38 −0.28 −0.62 −0.52 −0.39

Kurtosis −0.32 −0.05 0.26 0.19 0.18 0.28 −0.05 0.05 0.17

−0.54 −1.20 −1.42 −1.12 −1.26 −1.05 −0.57 −1.04 −1.14

1.40 −0.07 −0.30 0.00 −0.13 0.07 0.55 0.09 −0.01

Note: CART-Q = Coach-Athlete Relationship Questionnaire; IBQ-Self = Interpersonal Behaviors Questionnaire-Self; LSSS = Life Skills Scale for Sport; M = mean; SD = standard deviation; SE = standard error. 6

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Fig. 3. Coach-Athlete Relationship Questionnaire (CART-Q) Mean Scores by Group Empty shapes represent pre-intervention scores. Filled shapes represent post-intervention scores. T = time.

significant for the LSSS at Time 1, F(2, 282) = 4.40, p = .013. Thus, a more stringent α of .025 was applied to determine significance (Tabachnick & Fidell, 2013). 3 x 3 repeated measures factorial analysis. There was no significant within-subject main effect for time, F(1.84, 519.54) = 0.48, p = .602, ηp2 = 0.002. A significant small effect for group was observed, F(2, 282) = 4.41, p = .013, ηp2 = 0.030, but upon inspecting the within subject contrasts, the simple contrast between the experimental and control groups was non-significant, F(1, 282) = 0.003, p = .958 ηp2 < 0.001. The simple contrast between the waitlist and control groups was also non-significant, F(1, 282) = 0.95, p = .331, ηp2 = 0.003. No significant effect was found for the interaction between time and group, F(3.69, 519.54) = 1.93, p = .110, ηp2 = 0.014. Although non-significant, a small effect was found for the time-group interaction. Visual inspection. For the experimental group, mean scores on the LSSS increased after completing the CLS program (T1; M = 267.25, SD = 18.94; T2; M = 268.42, SD = 20.99), then decrease at Time 3 (T3; M = 265.28, SD = 23.90). For the waitlist group, mean scores on the LSSS decreased from Time 1 (M = 254.24, SD = 26.42) to Time 2 (M = 252.60, SD = 22.88), then increased after completing the CLS program (T3: M = 257.50, SD = 23.56). For the control group, mean scores on the LSSS decreased from Time 1 (M = 262.91, SD = 19.39) to Time 2 (M = 260.22, SD = 23.16), then increased from Time 2 to Time 3 (T3: M = 261.42, SD = 22.20). Please see Fig. 5 for mean life skills teaching scores by group.

after completing the CLS program (T3; M = 68.88, SD = 5.21). For the control group, mean scores decreased from Time 1 (M = 70.03, SD = 4.71) to Time 2 (M = 69.11, SD = 4.90), and remained relatively stable at Time 3 (M = 69.24, SD = 4.63). Please see Fig. 3 for mean coach-athlete relationship scores by group. 5.2. Coach interpersonal behaviours All assumptions were tested. Box’s M (18.21) was non-significant, p = .124, indicating that there were no significant differences between the covariance matrices. Mauchly’s test was significant, χ2(2) = 19.09, p < .001, meaning that the assumption of sphericity was not met. Thus, the Greenhouse-Geisser correction was applied when interpreting the results (Tabachnick & Fidell, 2013). Levene’s Test was significant for the IBQ-Self at Time 3, F(2, 282) = 3.02, p = .050 indicating that variance differed across groups. As a result, a more stringent α of .025 was applied to determine significance (Tabachnick & Fidell, 2013). 3 x 3 repeated measures factorial analysis. There was no significant within-subject main effect for time, F(1.88, 529.24) = 0.84, p = .433, ηp2 = 0.003, group, F(2, 282) = 1.46, p = .233, ηp2 = 0.010 or the time-group interaction, F(3.75, 529.24) = 1.48, p = .210, ηp2 = 0.010. A small effect was found for group (ηp2 = 0.010) and the time-group interaction (ηp2 = 0.010). Visual inspection. For the experimental group, mean scores on the IBQ-Self increased after completing the CLS program (T1; M = 143.78, SD = 9.87; T2; M = 145.64, SD = 9.85) then marginally decreased at follow up (T3; M = 145.00, SD = 10.71). For the waitlist group, mean scores on the IBQ-Self decreased from Time 1 (M = 142.47, SD = 10.13) to Time 2 (M = 140.48, SD = 12.22), then increased after completing the CLS program (T3; M = 142.79, SD = 12.61). For the control group, mean scores decreased from Time 1 (M = 144.59, SD = 10.83) to Time 2 (M = 143.56, SD = 10.76) and increased from Time 2 to Time 3 (T3: M = 144.32, SD = 9.86). Please see Fig. 4 for mean coach interpersonal behaviour scores by group.

6. Discussion The purpose of the study was to evaluate the effectiveness of the CLS online training program in helping coaches create environments conducive to the teaching of life skills. The study aimed to extend the results of our qualitative pilot study (Camiré, Kendellen, Rathwell, & Felber Charbonneau, 2018), using a randomised controlled trial design. The effectiveness of the CLS online training program is discussed in relation to the two steps of analysis.

5.3. Life skills teaching

6.1. 3x 3 repeated measures factorial analyses

All assumptions were tested. Box’s M (30.31) was significant, p = .003, suggesting there were significant differences between the covariance matrices. Additionally, Mauchly’s Test was significant, χ2(2) = 25.14, p < .001, meaning the assumption of sphericity was not met. Thus, the Greenhouse-Geisser correction was applied when interpreting the results (Tabachnick & Fidell, 2013). Levene’s Test was

The results of our qualitative pilot study (Camiré et al., 2018) indicated that coaches believed the program increased their awareness of the importance of nurturing quality coach-athlete relationships and of using high school sport as a context for teaching life skills. In the 7

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Fig. 4. Interpersonal Behaviors Questionnaire-Self (IBQ-Self) Mean Scores by Group Empty shapes represent pre-intervention scores. Filled shapes represent post-intervention scores. T = time.

Falcão et al., 2012), and did not randomise participants (e.g., Vella et al., 2013), the present study adds to the literature in terms of rigour in evaluating the effectiveness of coach education interventions. However, by using a randomised controlled trial to improve the study’s internal validity, the strict design was accompanied by a high attrition rate, especially in the experimental and waitlist groups, which led to a small sample size and running underpowered analyses. Thrower et al. (2019), who created a self-administered online education program for sport parents, experienced similar high attrition. High attrition rates above 50% and even 70% have also been reported for online education programs using a RCT design in the workplace (e.g., Griffiths, Bennett, Walker, Goldsmid, & Bennett, 2016) and in medicine (e.g., Ilic, Nordin, Glasziou, Tilson, & Villanueva, 2015). In the present study, low response and completion rates may be explained by the impersonal nature of online education as well as the tedious demands imposed on coaches in having to complete what was a thorough program evaluation. It is important to note, as identified in previous evaluations of online coach education courses (Santos et al., 2019; Strachan, et al., 2016), that flexibility, the primary benefit of online platforms, is often

current study, we tested the hypothesis that coaches who participated in the CLS program would perceive (a) enhanced coach-athlete relationships, (b) increased use of coach interpersonal behaviours that satisfy athletes’ basic psychological needs, and (c) increased use of strategies for teaching life skills, and that coaches in the control group would not. The results of the repeated measures factorial analyses were not statistically significant, and only a few small effects were found, meaning that the CLS program did not lead to hypothesised desired outcomes. Three factors must be considered as having potentially contributed to the lack of significance. First, conducting a randomised controlled trial to evaluate a PYDfocused coach education course contributes to the literature and adds to the growing body of knowledge in this area. Several of these types of courses have been developed in recent years by researchers in Canada (Falcão et al., 2012; Strachan et al., 2016), the United Kingdom (Harwood et al., 2015), Australia (Vella et al., 2013), the United States (Ferris et al., 2016), Singapore (Koh et al., 2017), and Portugal (Santos et al., 2019). Given that these evaluations had small samples (e.g., Strachan et al., 2016), relied mainly on semi-structured interviews (e.g.,

Fig. 5. Life Skills Scale for Sport Mean Scores by Group Empty shapes represent pre-intervention scores. Filled shapes represent post-intervention scores. T = time. 8

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may have influenced coaches’ perceived actions, from a life skills teaching perspective, in subsequent sport seasons.

tempered by reduced feelings of engagement, lack of meaningful interaction, and the absence of practical components. To improve participants’ engagement in evaluations of online education programs such as the CLS, future research in this area is needed to understand how coaches can be better incentivised. In the present study, coaches who completed the trial were entered into a draw to win one of two iPads but incentives could also have included continuing education credits that helped coaches maintain their coaching certification. Moving forward, a greater understanding of coaches’ motivations for (e.g., eagerness to learn, desire to foster athlete development) and challenges to (e.g., perceived lack of time, lack of perceived relevance of the material presented) completing online education would be beneficial for designing interventions with high(er) retention rates. As suggested by Santos et al. (2019), blended learning approaches can help promote engagement and facilitate learning. However, the logistical, human, and financial resources required for effective implementation often mitigate the benefits of blended approaches as the in-person components are very difficult to offer on a large(r) scale. Second, the data gathered were self-report, which may have caused biased responses related to self-presentation and social desirability. Specifically, when completing the self-report measures, the coaches may have been influenced by the desirability inherent in some of the items found in the CART-Q, IBQ-Self, and LSSS that make it difficult, from a self-preservation standpoint, to answer anything other than a five, six, or seven on the 7-point scale (Randall & Fernandes, 1991). In the present study, in attempts to control for social desirability, we used valid and reliable scales, ensured there were no interactions between research team members and participants, and used anonymous online surveys (Grimm, 2010). However, we did not use a social desirability questionnaire, which future work in this area employing self-report measures should include to help control the effect of this bias (Larson, 2018). With regards to the measures, in future work, researchers should also consider using scales that more accurately capture perceived behaviour change, meaning the extent to which coaches feel they can intentionally improve their relationships, interpersonal behaviours, and life skills teaching. On another note, a potential selection bias must be considered, with the coaches who participated in the study perhaps deciding to do so due to their high perceived coaching efficacy. Such factors may help explain the very high scores gathered from participants at Time 1, creating a ceiling effect that left little room for possible upward mobility in scoring at Time 2 and Time 3. Liddle, Deane, Batterham, and Vella (2019) reported similar ceiling effects in their RCT evaluating a mental health literacy program for adolescent sport participants, which may have contributed to the lack of change observed over time. Further, for experimental and waitlist group coaches, completing the CLS program may have made them realise they were not intentionally teaching life skills as much as they thought they were at Time 1. This may help explain the absence of statistically significant increases in scoring for these coaches following CLS completion. To gain another lens into intervention effectiveness, future evaluations should look to integrate athletes’ perceptions of (a) the coach-athlete relationship, (b) coaches’ interpersonal behaviours, and (c) coaches’ life skills teaching before/after their coaches complete the CLS program. Third, the trial was of short duration, with perceived change assessed three weeks and seven weeks following baseline testing. Previous research has shown that the time it takes for people to change and for new habits to form is highly variable across individuals (Lally, van Jaarsveld, Potts, & Wardle, 2010). In their RCT evaluation of a mental health literacy program, Liddle et al. (2019) noted that the time between the intervention and follow-up was only four weeks, likely contributing to the lack of perceived behaviour change as participants had little opportunity to exhibit a helping behaviour as they did not come into contact with a person experiencing a mental illness. In the present study, measurement efforts were bound by the relatively short length of high school sport seasons (i.e., usually a few months). Moving forward, longer term follow-ups are needed to measure how the CLS program

6.2. Visual analysis Although the results of our repeated measures factorial analyses were not statistically significant, a visual analysis was conducted to assess directional changes in coaching behaviours following the completion of the CLS program (Amrhein, Greenland, & Mcshane, 2019). As Kendall et al. (2013) stated, “statistically meagre results may disguise meaningful changes in participant functioning” (p. 51). In the present study, the use of a concurrent multiple baseline across groups design (Morgan & Morgan, 2008) made it possible to assess, through visual inspection of mean scores, changes occurring post-intervention compared with changes occurring simply due to the passage of time (Gallo, Comer, & Barlow, 2013). Specifically, visual inspection of mean scores suggested positive directional changes for all three dependent variables following completion of the CLS program. For coach-athlete relationships, coach interpersonal behaviours, and life skills teaching, mean scores increased for the experimental and waitlist groups after completing the CLS program, while control group mean scores decreased from Time 1 to Time 2. Such results tend to suggest that the CLS program may have played a positive role in contributing to coaches’ perceptions of their behaviours when coaching their students. Such findings are worth considering given previous research indicating the presence of a positive relationship between the coach-athlete relationship and life skills teaching, with this relationship mediated by coaches’ interpersonal behaviours (Camiré et al., 2019). Previous research (Smith, Smoll, & Barnett, 1995; Smith, Smoll, & Cumming, 2007) with programs such as Coach Effectiveness Training and Mastery Approach to Coaching has also indicated how short-duration training initiatives can lead to some favourable learning outcomes, with trained coaches deemed more supportive, more fun, more mastery-oriented, and less punitive than untrained coaches. In developing the CLS as a self-administered online education program, coaches’ preferences for short-duration, internet-based, and flexible learning opportunities were considered to help them meet their growing responsibilities as educators of youth (Camiré et al., 2016; Newman et al., 2016). Six months following the study, the CLS program was made available free of charge to high school coaches across Canada on www.schoolcoach.ca, School Sport Canada’s online e-learning platform. Although coaches’ preferences were carefully considered, it is important to situate how the choices made from a dosage perspective (e.g., type of content presented, program length, program format) may have influenced the results in terms of the effects observed. In particular, a proper balance in terms of program length must be achieved, with lengthier programs possibly leading to greater effects but perhaps also higher attrition rates. Nevertheless, moving forward, the positive directional changes gleaned from the visual inspection should be seen as promising, suggesting that the CLS program may have helped some coaches reflect on how they can further (a) foster quality coach-athlete relationships, (b) display interpersonal behaviours that satisfy students’ basic psychological needs, and (c) teach life skills. 8. Conclusion The study was the first to evaluate the effectiveness of a self-administered online coach education program using a randomised controlled trial. Though not statistically significant, the results suggest positive directional changes in coaches’ perceptions of the coach-athlete relationship, interpersonal behaviours, and life skills teaching following program completion. Given that recent models (Bean et al., 2018; Holt et al., 2017) situate intentionality as crucial in maximising the developmental gains of sport participation, the CLS program can have direct application for coaches, helping them create environments conducive to the intentional teaching of life skills through high school sport. Beyond 9

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the results presented in the present trial, the lasting practical impact for coaches lies in having the CLS program available free of charge on www.schoolcoach.ca. Despite evidence of some positive directional changes, moving forward, more research is needed to precisely delineate how effective online life skills education can be in helping coaches create settings conducive to life skills teaching. In particular, qualitative research could be especially relevant moving forward in terms of addressing the limitations of the intervention by gaining insider knowledge from coaches on what they deemed to be the program’s “active ingredients” (e.g., videos, reflective activities) that were most useful to them. By continuously seeking improvements to both content and delivery, self-administered online education can serve as a flexible as well as meaningful option in coaches’ learning repertoire.

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Funding This work was supported by an Insight Grant (435-2015-0116) from the Social Sciences and Humanities Research Council of Canada awarded to Martin Camiré. CRediT authorship contribution statement Martin Camiré: Conceptualization, Methodology, Writing - review & editing, Supervision, Funding acquisition. Kelsey Kendellen: Investigation, Project administration. Scott Rathwell: Methodology, Software, Validation, Formal analysis, Writing - original draft. Stéphanie Turgeon: Software, Formal analysis, Visualization, Writing original draft. Declaration of competing interest The authors wish to state that they have no conflict of interest to declare. Acknowledgements The authors would like to acknowledge the contributions of Michael Steele and Deanna Metro for their assistance during data collection. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.psychsport.2020.101649. References Akobeng, A. K. (2008). Assessing the validity of clinical trials. Journal of Pediatric Gastroenterology and Nutrition, 47, 277–282. https://doi.org/10.1097/MPG. 0b013e31816c749f. Amrhein, V., Greenland, S., & Mcshane, B. (2019). Scientists rise up against statistical significance. Nature, 567, 305–307. https://doi.org/10.1038/d41586-019-00857-9. Bailey, R., Armour, K., Kirk, D., Jess, M., Pickup, I., & Sandford, R. (2009). The educational benefits claimed for physical education and school sport: An academic review. Research Papers in Education, 24, 1–27. https://doi.org/10.1080/ 02671520701809817. Bean, C., & Forneris, T. (2016). Examining the importance of intentionally structuring the youth sport context to facilitate psychosocial development. Journal of Applied Sport Psychology, 28, 410–425. https://doi.org/10.1080/10413200.2016.1164764. Bean, C., & Forneris, T. (2019). Examining the role of needs support in mediating the relationship between programme quality and developmental outcomes in youth sport. International Journal of Sport and Exercise Psychology, 17, 350–366. https://doi. org/10.1080/1612197X.2017.1350825. Bean, C., Forneris, T., & Brunet, J. (2016). Investigating discrepancies in program quality related to youth volleyball athletes' needs support. Psychology of Sport and Exercise, 26, 154–163. https://doi.org/10.1016/j.psychsport.2016.07.001. Bean, C., Kramers, S., Forneris, T., & Camiré, M. (2018). The implicit/explicit continuum of life skills development and transfer. Quest, 70, 456–470. https://doi.org/10.1080/ 00336297.2018.1451348. Bourret, J. C., & Pietras, C. J. (2014). Visual analysis in single‐case research. In G. J. Madden, W. V. Dube, T. D. Hackenberg, G. P. Hanley, & K. A. Lattal (Eds.). APA handbook of behavior analysis (pp. 191–218). Washington, DC: American

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