Physical and Social-Motivational Contextual Correlates of Youth Physical Activity in Underresourced Afterschool Programs

Abstract

Afterschool programs (ASPs) have become increasingly recognized as a key context to support youth daily physical activity (PA) accrual. The purpose of the present study was to assess the physical and social-motivational climate characteristics of ASPs associated with youth PA, and variations in contextual correlates of PA by youth sex. Systematic observations of 7 ASPs serving underserved youth (minority, low income) was conducted using the System for Observing Play and Leisure Activity in Youth and a social-motivational climate observation tool founded on self-determination theory. For five program days at each site, teams of two coders conducted continuous observations of youth PA (sedentary, moderate, vigorous), five physical features (e.g., equipment availability), eight staff interactions (e.g., encourage PA), and seven motivational climate components (e.g., inclusive). Aligned with previous research, regressions controlling for variations by site indicated that organized PA, provision of portable equipment, and staff PA participation and supervision are key correlates of youth PA. Moreover, as the first study to systematically observe motivational-context characteristics of ASPs, we identified several key modifiable motivational features that are necessary to address in order to increase youth engagement in PA during the out-of-school hours. Among motivational features assessed, “relatedness” components (positive peer relations, inclusive/cooperative activities) were primary correlates of girls’ PA. In contrast, all three motivational features specified by self-determination theory (support for autonomy, mastery/competence, and inclusion/relatedness) were correlated with boys’ PA. Findings are discussed in terms of policy and practice for understanding strengths and needs of ASPs to effectively engage youth in PA.

Keywords

afterschool determinants motivation physical activity youth

Physical inactivity has been identified as a primary contributor of childhood obesity and related diseases, with minority, low-income youth at greatest risk of inactivity and its health consequences (Ogden, Carroll, Curtin, Lamb, & Flegal, 2010). Despite ample research supporting coordinated school-based health programs for reducing youth inactivity and risk for obesity (Centers for Disease Control and Prevention, 2011), substantial evidence across studies indicate that we should not rely solely on schools for youth daily PA accrual (e.g., M. Cox, Schofield, Greasley, & Kolt, 2006; McKenzie & Lounsbery, 2009; National Association for Sport and Physical Education & American Heart Association, 2006). Deficits in staff capacity and training, and time constraints resulting from increased emphasis on basic education skills and test scores, leave many schools struggling to incorporate adequate PA opportunities throughout the school day, and 50% to 92% of youth still acquire far below the national recommended guidelines of 60 minutes of daily PA (Fakhouri et al., 2014; Nader, Bradley, Houts, McRitchie, & O’Brian, 2008; U.S. Department of Health and Human Services, 2008). Consequently, afterschool programs (ASPs) have become increasingly recognized as an additional key context to support youth PA accrual (e.g., Coleman, Geller, Rosenkranz, & Dzewaltowski, 2008; Huberty, Beets, Beighle, & McKenzie, 2013; Trost, Rosenkranz, & Dzewaltowski, 2008; Zarrett & Bell, 2014), with the goal for ASPs to fulfill one third (20 minutes) of adolescents’ recommended daily moderate-to-vigorous physical activity (MVPA; Trost et al., 2008).

Afterschool Programs for Supporting Youth Physical Activity

Within the United States, 8.4 million youth participate in ASPs for an average 8.1 hours/week of their out-of-school time (Afterschool Alliance, 2009), and many of these school- and community-based programs provide relatively healthy environments compared with alternative afterschool arrangements (e.g., home alone; Frank, Andresen, & Schmid, 2004; Robinson, 2001). In particular, youth development programs (e.g., 4-H, Boys & Girls Clubs of America), which are highly accessible to underserved youth (Afterschool Alliance, 2009), and are uniquely characterized by their emphasis on providing youth highly safe, structured settings, positive mentors, and positive overarching goals, have begun to develop healthy lifestyles missions and policies (Beets, Rooney, Tilley, Beighle, & Webster, 2010), and commonly feature PA as one part of the “curriculum.” However, despite the proposed benefits of ASPs, previous research has reported mixed findings on the associations between ASP participation and healthy behaviors. Using objective PA assessments (e.g., systematic observations, accelerometry) some studies have demonstrated youth are acquiring one third of their recommended daily PA (Trost et al., 2008) or more (e.g., Coleman et al., 2008, reported an average 47 minutes) during ASP hours, where several other studies found the amount of activity youth accumulate within ASPs is well below policy-recommended levels (Beets, Huberty, & Bieghle, 2012; Rosenkranz, Welk, & Dzewaltowski, 2011), and girls are at especially high risk for inactivity during their time spent in ASPs (Rosenkranz, Welk, Hastmann, & Dzewaltowski, 2011; Trost et al., 2008). These mixed findings indicate significant variations in the quality of the PA opportunities offered in these settings, with some setting features better at engaging youth in PA than others. However, little research to date, has examined the nature of the PA opportunities offered in ASPs or characteristics of ASPs that act to either engage or discourage youth participation in PA.

Underresourced programs, defined by their limited funding, facilities and equipment, minimum enrollment fees, and service/accessibility to underserved youth (minority status, low income), face greater structural challenges for getting youth active than more resourced programs (e.g., access to recreational indoor/outdoor spaces, funding, staff capacity, and training), and serve a youth population identified as at greatest risk for obesity and related disease (Afterschool Alliance, 2012; Phillips, 2010). Therefore, a targeted examination of the physical and social-motivational climate of underresourced programs would provide valuable insight into the specific strengths and challenges faced by these programs, and could make important contributions to policy and practice (e.g., Phillips, 2010) by identifying key modifiable climate features to effectively increase youth PA within the confines of limited resource.

Context Features for Promoting Youth Physical Activity

Beyond program dose (e.g., attendance, duration) scholars have argued that a consideration of youth engagement is key for determining the degree to which youth will benefit from their ASP participation. However, only a few studies have examined contextual features of ASPs that are associated with youth PA engagement (Rosenkranz, Welk, & Dzewaltowski, 2011), targeting three particular contextual correlates of youth PA previously identified in school-based PA research: availability of organized activities (Coleman et al., 2008; Trost et al., 2008), access to recreational equipment (Huberty et al., 2013; Rosenkranz, Welk, & Dzewaltowski, 2011), and staff behaviors (Coleman et al., 2008; Huberty et al., 2013). These studies indicate that staff verbal promotion and active participation with youth in PA are related to higher rates of youth MVPA within ASP settings (Coleman et al., 2008; Huberty et al., 2013), and access to portable equipment (Huberty et al., 2013; Trost et al., 2008) and organized/structured free play (Huberty et al., 2013; Rosenkranz, Welk, & Dzewaltowski, 2011) may also be important for youth PA despite some inconsistencies across studies (Coleman et al., 2008; Trost et al., 2008).

However, in addition to adequate access to equipment, space, and other structural features that support PA, the positive youth development framework (PYD; Lerner, 2005) and self-determination theory (SDT; Ryan & Deci, 2000) along with previous research (Braithwaite, Spray, & Warburton, 2011; Weiss, Amorose, & Kipp, 2012; Zarrett, Skiles, & Sorensen, 2012; Zarrett, Sorensen, & Skiles, 2013), suggests that facilitation of engagement also requires consideration of the motivational climate of the program context. Specifically, participation in PA during program hours is likely to be highly dependent on whether the PA program components (1) are “engaging” (optimally challenging), (2) provide youth opportunities to make their own choices (autonomy), and (3) facilitate positive social connections, support, and sense of inclusion/belonging with peers and staff (Braithwaite et al., 2011; Eccles & Gootman, 2002; Granger, Durlak, Yohalem, & Reisner, 2007; National Research Council and Institute of Medicine, 2002).

The Current Study

In the present study, a systematic observation tool designed by the first author and founded on the theoretical foundations of SDT, was used to assess variations in key physical and social-motivational climate characteristics of underresourced ASPs and the relation of these climate characteristics to rates of youth PA (energy expenditure measured in METS). Given differences in girls and boys afterschool PA accrual, variations in context predictors of PA by youth sex were also considered (see Table 1 for a detailed description of program features assessed). To our knowledge, this is the first study to conduct systematic observations of PA-based motivational-climate features within ASPs. Educators and applied behavioral analysts refer to this approach as ecobehavioral assessment, and in education research it has been shown to provide an important heuristic for methodologically identifying situational factors that either promote or impede the occurrence of specified student behaviors during subsequent school years and grade levels (Greenwood, Carta, Kamps, Terry, & Delquadri, 1994).

Table 1.

Constructs of the SOPLAY and MCOT-PA Systematic Observational Assessment.

Context constructs	Description
Conditions	Physical conditions of the facility for PA
Accessible	Youth are able to access and allowed in the space (e.g., door unlocked)
Usable	Area is usable for PA (sufficient space, not too wet or windy)
Supervised	Program staff are present
Organized	Organized PA is being held in the space
Equipment	Portable PA equipment is available (e.g., balls, jump ropes)
Activity	Levels of youth PA
Sedentary	(e.g., lying, sitting, standing still)
Walking	(e.g., walking, shifting weight from foot to foot)
Vigorous	(e.g., running, sit-ups, climbing, etc.)
Climate^a	Activity components
Clarity of rules	Youth understand activity rules and are able to follow them. Youth know what is expected of them
Autonomy/choice	Youth have opportunities to make choices and voice opinions (e.g., activity options are available, participation is not mandated)
a. Structured autonomy	—Youth are provided guided choices and opportunities for input
b. Unstructured autonomy	—Youth are left in a recreational space for unstructured free play
High engagement	Activity is optimally challenging and fun (e.g., skill level appropriate; youth are smiling, squealing, laughing or “in the zone”)
Inclusion	Most youth are allowed, able, and willing to participate in the activity (e.g., no youth are discouraged from participating)
Positive interactions	Youth demonstrate enjoyment interacting with peers (e.g., helping each other, working together as a team, encouraging one another)
Bullying	Youth are involved in negative social interactions (e.g., pushing, yelling, teasing)
Staff interaction	Staff components
Promotes PA during program	Staff prompts or directs PA (e.g., “roll the ball, don’t bounce it,” “go ahead”)
Increases activity engagement	Staff encourages increased intensity of PA (e.g. “go, go,” “hustle”)
Praises or reinforces PA	Staff uses verbal or nonverbal praise to encourage PA (e.g. “nicely done on that move,” gives a high five)
Promotes out-of-program PA, fitness, or motor skills	Staff reminds or encourages PA outside the program (e.g., practice that skill at home, you can play this game with your neighbors)
Demonstrates/participates in PA	Staff models PA behavior (e.g., shows a new skill, plays game with youth)
Disciplines^a	Staff disciplines youth
Observes	Staff watches youth activity
General interaction	There is staff engagement, but it is not related to PA (e.g., management)
Other-task (disengaged)	Staff is disengaged (e.g., on their phone, back turned to youth while talking to someone else)

Note. SOPLAY = System for Observing Play and Leisure Activity in Youth; MCOT-PA = Motivational Climate Observation Tool for Physical Activity; PA = physical activity.

The newest version of the MCOT-PA includes additional climate codes including “competitive” and “mastery” activities. In the newest form, discipline is further specified as punitive versus constructive.

Method

Participants/Setting

ASPs were recruited from widely accessible national and state-based youth programming organizations (e.g., Boys and Girls Club). All recruited ASPs were considered low-resourced sites, having limited funding, facilities and equipment, minimum enrollment fees ($0-25 per week) and serving a primarily underserved youth population defined by both minority status (87% across sites; range = 53% to 98%) and low socioeconomic status (90% across sites on free or reduced lunch, range = 77% to 100%). Only ASPs which offered their program daily (5 days/week) throughout the school year, included a PA component as part of the daily curriculum (indoor/outdoor recreation), and was founded on a PYD framework (e.g., included a program mission and daily curriculum centered on fostering physical, psychological, and achievement-related well-being rather than a specified set of skills such as “improving basketball skills”) were considered for inclusion in the study.

Program directors from each of nine organizations that met criteria were approached about participation in the study and a total of seven ASP sites agreed to participate. ASPs varied in enrollment (22-99 youth), location (urban = four sites, rural =three sites), and physical capacity (e.g., access to indoor/outdoor recreational spaces). There were a total of 28 staff (12 of whom were paid employees) across sites with an average staff–child ratio of 1:15. Staff ranged in age from 18 to 80 years (average age category = 51-60 years), on average, had worked for the program for 2 years, and were primarily female (N = 22) and African American (N = 24). The majority of the sites (five ASPs) targeted youth from Grades K to 6 (M = 11 years). Two sites were targeted to youth from Grades K through 12; however, the majority of youth attending these programs were also between 7 and 12 years old (M = 11 years). Although daily attendance varied, all ASPs required youth to enroll in the program in the early fall and the majority of youth attended the program daily. Thus, the same group of youth was observed across the observation period (44% female).

Study Measures

Physical Activity Observations

Each program session was evaluated for youth PA levels using SOPLAY (McKenzie, 2005; McKenzie, Marshall, Sallis, & Conway, 2000). SOPLAY was designed to obtain observational data on the number of students and their PA levels (sedentary, walking/moderate, vigorous) during play/leisure in a specified activity area and includes assessments of area accessibility, usability, supervision, presence of organized activity, portable equipment, and average daily temperature. Although no field-based validity study of the SOPLAY measure has been conducted, validity of the activity codes used by SOPLAY have been established through heart rate monitoring (McKenzie, Sallis, & Nader, 1991; Rowe, Schuldheisz, & van der Mars, 1997). For the present study, observed activity levels were used to establish estimates of total energy expenditure for each scan using metabolic equivalents (METS)–based scoring from a standard compendium (sedentary = 1.5 METS, walking/moderate = 3 METS, vigorous = 6 METS (Ainsworth et al., 2000; Harrell et al., 2005; McKenzie, Cohen, Sehgal, Williamson, & Golinelli, 2006), in order to account for all people in the observed area, including those who may be minimally active (McKenzie et al., 2006).

Observation of the ASP Motivational Context

The social-motivational climate of ASPs was assessed using the MCOT-PA, an extension of the SOPLAY protocol that was developed by the first author. The MCOT-PA includes nine staff interaction components, and seven climate components to assess key social contextual features of youth settings derived from previous research and the theoretical foundations of PYD and SDT. The climate components assess the degree to which the setting: (1) involves activity choices which emphasize cooperative team-based goals and/or are inclusive of all youth, (2) facilitates positive peer interactions, (3) provides optimally challenging/engaging activity opportunities, and (4) incorporates students’ choice and input (structured and unstructured autonomy). The staff interaction component assesses staff behaviors that foster youth engagement and cooperative play, encourage and assist youth to feel competent in the activity, and allow all youth to have input and feel respected and valued in the process (see Table 1 for a description of all SOPLAY and MCOT-PA constructs). The MCOT-PA has demonstrated adequate interrater reliability and predictive/convergent validity in previous PA-based studies of other youth settings (e.g., Zarrett et al., 2013).

Procedure

Using the System for Observing Play and Leisure Activity in Youth (SOPLAY) tool and protocol (McKenzie, 2005), and the Motivational Climate Observation Tool for Physical Activity (MCOT-PA; Zarrett, Skiles, & Sorensen, 2012; Zarrett, Sorensen, & Skiles, 2013), a team of two coders (1 primary, 1 reliability coder) observed daily activities at each ASP for 5 program days across a 2-week period. Aligned with previous research (Coleman et al., 2008) and the SOPLAY protocol (McKenzie, 2005), each observation was on a different day of the week and spanned a 2-week period to improve the likelihood of acquiring a more comprehensive account of the varied activities that take place in each ASP. Continuous observation scans (one after the other) were conducted throughout each day of observation resulting in a total of 786 observation scans. For the present study, only scans conducted during each program’s free-play hour were examined (Total free-play observation scans = 585; average number of free-play observation scans for each program = 83.6). Each scan assessed level of youth PA, type of activity offered, five physical features of the setting, nine staff interaction components, and seven social climate components (see Table 1 for a detailed summary of ASP features assessed). By assessing all PA and context characteristics as part of each scan we were able to capture the activity of youth and the climate as they co-occur.

Prior to data collection, all three of the study’s coders (two doctoral students, one paid research assistant with 8 years of data collection experience) completed an extensive observer training (four lab sessions, and two 2-week field trials; see Zarrett et al., 2013, for detailed description of training) and established interobserver reliability. To ensure continued reliability throughout the study, 1 day at each ASP was dedicated to practice observations where the observers would map out the physical layout of the site, familiarize themselves with the program “curriculum,” and conduct practice scans in the new setting. All ASP scans were conducted in pairs, whereby one coder was designated as the primary coder and the other coder served as the reliability check. Coders were on a continued rotation at each program, and alternated primary and reliability roles so that all coders had approximately similar number of days at each program and as the primary coder (Interrater reliability [% agreement] = .98).

Statistical Analyses

For the purpose of the present study, data are reported for only the daily 1-hour “free-play” component of each program. Descriptive statistics were used to summarize proportion (%) of observation scans in which youth were participating in sedentary, moderate, and vigorous PA, and the proportion (%) of scans in which PA-based climate features (physical, social-motivational, and staff behavioral) were observed. A series of linear regression models were conducted for the full sample, and then separately for males and females, to examine the independent contributions of physical-environment features, social-motivational climate features, and staff behaviors, to observed levels of youth PA (energy expenditure in METS). Given observations were nested within seven ASPs, differences in variability between ASPs was controlled for in all analyses.

To evaluate the additive effect of context features (e.g., whether the presence of two features is related to higher energy expenditure than the presence of a single feature, and the presence of three features is related to higher energy expenditure than the presence of two features, etc), three sum scores were created for physical, social-motivational, and staff behavioral features, respectively. Random effects analysis of variance models, controlling for variability between ASPs, compared the additive effect of context features on youth PA (METS).

Results

Physical Activity

Across ASPs, youth were involved in MVPA in 27.4% (9.6% vigorous) of observed scans, with the remaining 72.6% of free-play scans consisting of youth in sedentary activities. The proportion of scans by youth sex indicated that boys were more active than girls with 33.5% (12.4% vigorous) of boys’ observed free-play scans involving MVPA as compared with only 18.9% (5.7% vigorous) of girls’ scans. For both boys and girls, unstructured active free play and more sedentary social activities (talking with friends on the gym sidelines) were the two most prominent activities observed across scans (together making up 65.7% of males’ and 73.9% of females’ scans). However, social activities were observed in a greater percentage of girls’ scans (43.8%) than boys’ (27.3%), and active free play was more prominent for boys (38.4%) than girls (30.1%). Among the remaining activities observed, boys participated in organized sports in significantly more scans than girls (15.4% vs. 8.4% sports), but girls were observed participating in PA games (e.g., tag) slightly more regularly than boys (4.1% vs. 1.7). Computer work, and crafts were similar across boys and girls, but slightly more scans of management (e.g., going over rules of game; 12.6% vs. 10.4%), and staff discipline (2.0% vs. 0.3%) was observed for boys than girls.

Mechanisms for Promoting Youth Physical Activity

Physical Environment

ASP areas dedicated to supporting PA were highly “accessible” (99.7% of all scans) and “usable” (99.7% of all scans) across sites. The majority of these areas were also “supervised” by program staff (79.3% of scans) but provided youth limited “PA equipment” (42.2% of scans) or “organized PA” games/activities (26.7% of scans). Males were more frequently observed using PA equipment, engaging in organized PA, and being supervised than female participants (see Table 2). Average outdoor temperatures were similar across ASPs and ranged from 58°F to 80°F (M = 69.1°F).

Table 2.

Percentage of Observed Instances of Physical Activity–Based Physical, Social-Motivational, and Staff Characteristics Across the Sample and for Females and Males Separately.

Characteristic	Total	Female	Male
Physical
Accessible	99.7	99.7	99.8
Useable	99.7	99.7	99.8
Supervised	79.3	78.1	82.5
Organized activity	26.7	22.2	32.0
Equipment	42.2	38.8	45.9
Social-motivational factors
Clear rules	23.4	23.4	28.1
High engagement	16.4	15.3	19.2
Inclusion	10.9	9.8	13.6
Positive interactions	8.7	9.3	9.9
Structured autonomy	21.9	20.0	21.1
Unstructured autonomy	53.4	54.7	53.5
Bullying	0.0	0.0	0.0
Staff factors
Initiate PA	1.9	1.0	2.2
Increase PA	0.5	0.5	0.6
Praise PA	0.2	0.3	0.2
Promote PA outside program	0.3	0.5	0.4
Other-task (disengaged)	0.0	0.0	0.0
Demonstrate/participate in PA	6.7	7.0	7.6
Observe	63.3	60.6	65.2

Note. PA = physical activity. Total percentages of observed instances included all free-play observations in which at least one child was present. Female percentages required that at least one female was present in the observed activity area. Male observations required that at least one male was present in the observed activity area.

Regression analyses, including all physical-environmental features and controlling for variations by ASP, indicated significant independent contributions of “organized activities”—β = 3.45, t(583) = 2.01, p = .045—and “equipment”—β = 3.41, t(583) = 2.38, p = .018—on youth PA across the sample. Although separate models by youth sex indicated no relations between physical features and females’ PA, the provision of “equipment”—β = 4.20, t(459) = 3.31, p = .001—and “supervision”—β = 2.82, t(459) = 2.02, p = .044—accounted for unique explained variance in males’ PA.

Social-Motivational Context

Observations of the social-motivational context indicated that all ASPs were highly supportive of youth “autonomy,” with 75.3% of the scans consisting of some type of autonomous activity (see Table 2). However, the majority of autonomous instances observed involved “unstructured” free-play activities (53.4% of all scans) rather than the guided autonomy specified by SDT for fostering intrinsic motivation. Across ASPs, 16.4% of the scans included “engaging activities,” and 23.4% of the scans involved activities with clearly defined rules. “Positive interactions” between youth during PA were observed in 8.7% of the scans and 10.9% of the observed free-play activities were “inclusive” of all youth. Compared with boys, there were considerably less observed instances of girls’ access to a PA context that included engaging, inclusive, and clearly defined activities.

Regression analyses which included all social-motivational predictors and controlled for variations by ASPs indicated significant independent contributions of “engaging games”—β = 4.47, t(583) = 2.62, p = .009,—“inclusive games”—β = 10.55, t(583) = 5.19, p < .001,— and “positive peer interactions”—β = 4.68, t(583) = 2.20, p = .028—on youth PA (energy expenditure) across the sample. Separate analyses for males and females indicated “engaging games”—β = 5.69, t(459) = 4.18, p < .001—and, inversely, “unstructured autonomy”—β = −2.82, t(459) = −2.05, p = .041—accounted for unique explained variance in males’ but not females’ PA, and “positive peer interactions” independently contributed to only females’ PA—β = 3.03, t(394) = 2.52, p = .012. “Inclusive games” predicted PA for both males and females (see Table 3).

Table 3.

Regression Models Examining the Associations Between Physical, Motivational, and Staff-Based Program Features and Youth Energy Expenditure (METS) for the Total Sample, and for Males and Females Separately.

	Total		Males		Females
Variable	Β (SE)	β	Β (SE)	β	Β (SE)	β
Physical environment
Average temperature	0.119 (0.152)	.042	0.142 (0.128)	.069	−0.105 (0.086)	−.080
Usable	6.710 (9.535)	.028	3.579 (10.360)	.015	−1.392 (6.288)	−.011
Supervised	2.886 (1.536)	.082	2.818* (1.394)	.098	1.558 (0.837)	.100
Organized PA	3.446* (1.711)	.107	2.054 (1.410)	.088	−0.149 (0.980)	−.010
Equipment provided	3.410* (1.434)	.119	4.203* (1.271)	.192	0.170 (0.767)	.013
R² (adjusted R²)	.148 (.131)		.151 (.130)		.127 (.102)
Social climate
Clear rules	−0.209 (1.571)	−.006	−0.511 (1.277)	−.021	−1.031 (0.906)	−.067
High engagement	4.467* (1.708)	.117	5.691* (1.363)	.206	−1.449 (1.015)	−.081
Inclusion	10.549* (2.031)	.232	6.721* (1.589)	.211	4.726* (1.190)	.219
Positive interactions	4.682* (2.129)	.093	3.094 (1.702)	.085	3.031* (1.201)	.137
Structured autonomy	−.062 (1.741)	−.002	−.659 (1.517)	−.025	0.645 (1.034)	.040
Unstructured autonomy	−1.842 (1.541)	−.065	−2.822* (1.375)	−.129	0.178 (0.853)	.014
R² (adjusted R²)	.283 (.186)		.221 (.200)		.165 (.139)
Staff behavior
Initiate PA	−0.910 (4.292)	−.009	2.851 (3.434)	.038	−5.494 (3.244)	−.085
Increase PA	10.315 (9.562)	.052	10.996 (7.346)	.081	−7.414 (6.233)	−.082
Praise PA	27.266 (16.242)	.079	26.777* (12.448)	.114	3.602 (8.641)	.028
Out-of-program PA	10.066 (9.531)	.041	8.861 (7.319)	.053	−0.118 (4.406)	−.001
Demonstrates PA	12.197* (2.306)	.214	10.372* (1.860)	.251	3.602* (1.294)	.143
Observes PA	4.045* (1.223)	.137	3.173* (1.081)	.138	1.976* (0.693)	.150
R² (adjusted R²)	.165 (.147)		.179 (.157)		.150 (.123)

Note. METS = metabolic equivalents; ASP = afterschool program; SE = standard error; PA = physical activity. All regression models included ASP site as a covariate to control for variations in ASPs.

p < .05.

Staff Behaviors

Observations across ASPs indicated that when staff were present (79.3% of all free-play scans), they were consistently focused on the youth and their well-being (there were no instances where staff were observed in “disengaged/ distracted” activities such as reading the newspaper or talking on the phone). However, we observed minimal interaction related to promoting youth physical activity (22% of scans involved staff–youth interactions unrelated to PA; 3.4% involved discipline, and 1.7% involved management; see Table 2). The most common PA-related staff behavior was “observing” PA (63.3% of scans), followed by a small percentage of instances in which we observed staff “demonstrating or participating” in PA with youth (6.7% of scans). We observed very few verbal cues to “initiate” (1.9% of scans), “increase” (.5% of scans), or “praise” (.2% of scans) physical activity, nor did staff “promote PA outside the ASP” (.3% of scans).

Despite minimal interaction observed by staff, a regression model including all observed staff behaviors and controlling for variations by ASP indicated significant independent contributions of staff “participation” with youth in activities—β =12.20, t(584) = 5.29, p < .001—and “observing” youth—β = 4.05, t(584) = 3.31, p = .001—on youth PA across the sample and for males and females separately. Staff “praise/encouragement” was also predictive of PA, but only for males—β = 26.78, t(460) = 2.15, p = .032.

Additive Effect of Mechanisms for Promoting Youth Physical Activity

A cumulative score of features present for each scan was created for physical, social-motivational, and staff features separately. For physical environment features, access and usability were excluded in the sum scores because they were present in approximately 100% of the scans. Random effects analysis of variance indicated differences in youth PA by the number of features observed in a scan for physical—F(3, 574) = 10.49, p < .001,—social motivational—F(4, 573) = 13.28, p < .001,—and staff features—F(2, 576) = 14.14, p < .001. For both physical and social motivational features, contrasts adjusted for multiple comparisons (Bonferroni) and differences by ASP site, indicated no differences in youth PA between zero and one feature present, but the presence of two features was related to significantly higher PA levels than either one or no features present. Three features was associated with similar PA levels as two features (significantly higher than one or no features, but not different from two features). For staff behaviors a significant difference in youth PA was found with the addition of each staff behavior present, so that the presence of two or more staff behaviors was related to higher average PA levels than the presence of one staff behavior (and no positive behaviors) and one staff behavior was related to higher youth PA than when no positive behaviors were present (see Table 4).

Table 4.

Association Among the Number of Positive Afterschool Program Features and Youth Observed Physical Activity (METS).

Number of features (number/% of scans)	Youth PA in METS Mean (SE)	95% CI
Physical environment
No features (112/19.2)	8.18 (1.33)^a	[5.57, 10.78]
1 feature (218/37.3)	10.75 (0.92)^b	[8.95, 12.55]
2 features (114/19.5)	15.29 (1.29)^{a b}	[12.76, 17.82]
3 features (140/23.9)	17.40 (1.29)^{a b}	[14.87, 19.94]
Social-motivational
No features (56/9.6)	9.29 (1.76)^c	[5.83,12.75]
1 feature (364/62.3)	10.26 (0.70)^d	[8.89, 11.63]
2 features (90/15.4)	18.24 (1.45)^{c d}	[15.39, 21.08]
3 features (54/9.2)	21.44 (1.84)^{c d}	[17.82, 25.05]
4+ features (20/3.4)	19.48 (2.96)^{c d}	[13.65, 25.30]
Staff features
No features (187/32.0)	8.79 (1.01)^e	[6.80, 10.77]
1 feature (374/63.9)	14.12 (0.70)^{e f}	[12.75, 15.49]
2+ features (24/4.1)	21.83 (2.80)^{e f}	[16.32, 27.33]

Note. PA = physical activity; METS = metabolic equivalents. All PA means are adjusted for differences by program (Program 1 = 0.089; Program 2 = 0.235; Program 3 = 0.074; Program 4 = 0.110; Program 5 = 0.110; Program 6 = 0.276; Program 7 = 0.108). Footnotes a to f indicate significant difference in youth PA between number of features at p < .05.

2 features > 0 features; 3 features > 0 features. ^b2 features > 1 features; 3 features > 1 features. ^c2 features > 0 features; 3 features > 0 features; 4+ features > 0 features. ^d2 features > 1 features; 3 features > 1 features; 4+ features > 0 features. ^e1 feature > 0 features; 2 features > 0 features. ^f2+ features > 1 feature.

Discussion

The purpose of the present study was to assess the contributions of key physical and social-motivational climate characteristics of ASPs for promoting youth PA, and variations in contextual correlates of PA by youth sex. First, our findings support previous research that indicated that along with access to portable equipment, supervision, and organized activity, staff behaviors, especially participation with youth in PA (Coleman et al., 2008; Huberty et al., 2013), is a primary correlate of youth PA. Coupled with the minimal observations of staff active involvement with youth during free play, our findings provide support for the dire need of improved PA-based training and support for staff within ASPs (e.g., Beets, Huberty, & Beighle, 2013).

Second, as the first study to systematically observe motivational-based climate characteristics of ASPs, we identified several other key modifiable features that are necessary to address if we aim to increase youth engagement in PA during the out-of-school hours. Aligned with an SDT framework, which specifies the importance of meeting individuals’ needs for connection/relatedness as a key facilitator for increased motivation/engagement, findings from the current study indicated that activities that are inclusive and facilitate positive peer interactions independently contributed to higher observed levels of youth PA. Our observational findings support an extensive literature that has highlighted social reasons and goals (e.g., being with, and making friends) as primary motivations youth report for their participation in PA (A. E. Cox, Duncheon, & McDavid, 2009; Prochaska, Rodgers, & Sallis, 2002; Weiss et al., 2012). However, only a minimal percentage of scans during the programs PA sessions included these critical social features (8.7% and 10.7% of scans for positive peer interactions and inclusive activities, respectively), and perhaps, consequently, youth were found to opt for other more social/inclusive, and unfortunately, more sedentary activities (e.g., talking in the corner of the room with friends) for a considerable proportion of the free-play hour. Together findings suggest that providing ASPs the strategies and resources needed to develop and implement a PA curriculum that is oriented toward meeting youth social needs (e.g., offering more cooperative games that emphasize teamwork and opportunities to build friendships) may be highly effective for improving youth PA engagement in the program.

Findings also suggest that engaging games, (e.g., optimally challenging) is another important climate feature for promoting PA and supports previous SDT-based research and interventions which have focused on providing opportunities for “mastery” as a key component of fostering intrinsic motivation (e.g., Braithwaite et al., 2011; Standage, Duda, & Ntoumanis, 2003; Wang, Chatzisarantis, Spray, & Biddle, 2002; Wilson et al., 2011). However, similar to the minimally observed presence of features related to youth social needs, only a small percentage of scans included activities that were engaging to youth. Given the variability in age and skill set of youth attending most ASPs, future research and intervention will need to identify effective strategies for providing challenging activities that appeal to all youth. Previous SDT-based research has shown that an effective mastery climate (and thus, optimal challenge) is more likely to be achieved when participants work in mixed-ability groupings, positive evaluation for personal improvement is emphasized, opportunities to exercise leadership are available, and variability in pace of learning and execution of the task is accommodated (Braithwaite et al., 2011). Incorporating such strategies into the PA curriculum (e.g., include older youth in junior leadership roles, have staff allocate youth into mixed-ability groups, etc.) may assist in providing challenging and engaging activities for all ASP youth.

Aligned with SDT and the PYD theoretical framework (Benson, Leffert, Scales, & Blyth, 1998; Lerner, 2005), which asserts that youth exposure to contextual affordances across a full range of growth-related opportunities helps reinforce important skills for healthy development, it was expected that rates of youth PA would be reflective of the number of contextual affordances available within ASPs to support and reinforce youth PA. Therefore, along with examining the independent contributions of context features on youth PA, the current study evaluated the potential additive effects of program features to further inform research and policy/practice.

Analyses comparing the additive effect of ASP features on youth PA (METS) indicated that for physical and social-motivational features, at least two features must be present to observe a significant increase in youth energy expenditure. Our findings also suggest that including more than two key features at the physical and motivational climate levels may result in little added benefit to increasing youth PA. Given previous research indicating a linear relation between context features and youth PA (Huberty et al., 2013), our findings were unexpected and can contribute to designing efficient cost-effective solutions to improving the ASP climate for promoting youth PA. Moreover, the additive (linear) effect found for staff behaviors on youth PA (as the number of positive staff features increased, there was substantial increase in youth energy expenditure) acts to further endorse initiatives for providing ASP staff ample PA-focused professional development that addresses best strategies and staff behaviors for engaging all program youth in PA (Beets, Huberty, & Beighle, 2013; Huberty et al., 2013).

Variations by Youth Sex

Although access to portable equipment, supervision, and organized activity were important for promoting youth PA within the ASP setting, contrary to previous studies (e.g., Huberty et al., 2013; Zarrett et al., 2013) our findings identified these as PA correlates primarily for boys, and explained minimal variance in girls’ PA. These sex differences could indicate that physical ASP features may matter less for girls’ than for boys’ PA. However, a second, more likely explanation, is that ASPs may be better equipped (both in equipment and staff training) to provide the types of activities that engage boys more than girls in our culturally and economically specified sample (e.g., basketball, a favorite activity among our sample of males, was a dominant organized activity observed). The significantly fewer observed instances of girls’ organized activity and equipment use compared with boys’ supports this premise. Several researchers have argued that organized activity is only effective when staff are trained and feel competent to implement activities that appeal to youth (e.g., Beets, Webster, Saunders, & Huberty, 2013).

Moreover, observed sex differences in motivational features associated with youth PA indicate that among this sample of underserved youth, social relations (inclusive games, positive peer interactions) appear to be most salient for girls’ PA, and support findings of previous observational studies of youth summer day camps (Zarrett et al., 2012; Zarrett et al., 2013). In contrast, all three motivational features specified by SDT (support for autonomy, mastery/competence, and inclusion/relatedness) were found important for males’ PA. Interestingly, we found “engaging games” was particularly predictive of boys’ PA and may capture the gender differences found in previous research indicating that boys are more likely than girls to have a PA motivational profile that includes both high ego (e.g., winning, performance) and task (mastery) orientation (Wang & Biddle, 2001; Wang et al., 2002). The inverse relations of unstructured autonomy and boys’ PA, coupled with the other physical (supervised activities and equipment), staff (participation with youth), and motivational climate correlates (inclusive and engaging games) found for boys’ PA, suggests that the provision of guided choices across several challenging, inclusive, organized activity opportunities would be effective contextual strategies for increasing boys’ PA. Although our findings only support the relatedness component of SDT for girls’ PA, compared with boys’, girls’ ASP free-play experience was characterized by less supervision, equipment, and fewer organized, inclusive, or engaging activities. Thus, future research will need to explore whether some of the sex differences found in the current study may be attributed to the failure of ASPs to meet girls’ PA-based autonomy and competency needs.

Limitations and Future Directions

This study has several limitations. The current set of analyses identified both the independent contributions of each context feature, and the additive effect of context features on youth PA. Given our findings, which indicate that these context features do, in fact, matter for youth PA, and that the influence of context on youth PA varies by the number of context features present, an important next step would be to conduct a more nuanced examination of how features combine in various ways to support youth PA (Wang et al., 2002; Zarrett et al., 2009). For instance, it may be that the impact of a particular context feature is enhanced or undermined when other particular features are present, or a combination of two or three particular features may have as great an impact on youth PA as having all features present. Furthermore, the observation method used in the current study assumes that all youth within the specified area are exposed to the same climate components observed; however, it is possible that observed components can be directed toward specific youth and not to others (e.g., staff interaction may be only directed toward the boys playing basketball and not to the girls sitting on the sidelines). However, both these limitations reduce the likelihood of detecting significant effects, making this study’s findings particularly robust. Conducting observations on specified individuals (similar to observational methods used in SOFIT; McKenzie et al., 1991), and consideration of interactions among ASP features through the use of cluster analytical techniques, will further delineate the predictive value of the study’s specified climate components.

There are likely additional important physical and social-motivational factors within ASPs for promoting youth PA that are not included in the current, newly developed MCOT-PA. For example, given theory (Nicholls, 1989; Ryan & Deci, 2000) and previous climate-based research/intervention (e.g., Braithwaite et al., 2011; Harwood, Spray, & Keegan, 2008) we anticipate that youth MVPA may vary by motivational-context factors such as the degree to which the activities are performance-based (emphasize winning, competitive), or the interactive styles of ASP staff (e.g., authoritarian, authoritative). Moreover, where the provision of physical and SDT-based social-motivational climate components are considered universal predictors of self-determined (intrinsic) motivation, future research will need to examine potential variations in the effectiveness of each component by important intrapersonal characteristics shown in previous research to influence youth receptivity to PA-based curriculum or intervention, such as weight status (Power, Ulrich-French, Steele, Daratha, & Bindler, 2011; St. George, Wilson, Lawman, & Van Horn, 2013), PA motivational orientation (e.g., Wang & Biddle, 2001), and PA self-efficacy (Robbins, Pender, Ronis, Kazanis, & Pis, 2004). Examination of variations in contextual correlates by youth sex in the current study was a first step toward understanding these possible variations.

Although all ASP sites shared common challenges associated with being underresourced (e.g., staff capacity, funding, etc.) by national standards (Afterschool Alliance, 2012; Phillips, 2010) and were designed and dedicated to providing resources to underserved youth who also share similar challenges, there were still considerable differences between sites (e.g., location, variation in access to indoor and outdoor spaces, square footage of PA areas, number of attending youth). The current study controlled for ASP site in all analyses to account for these variations, with the goal of identifying what social-motivational context features predict youth PA across sites. However, using a larger nationally representative sample of ASPs, future research that examines how location (e.g., rural, urban) and other structural components of ASPs can influence implementation of a supportive PA social-motivational climate and youth PA will further inform policy and practice. Finally, the methods used in the current study did not account for bouts of light PA, potentially resulting in an underestimation of youth PA. Given some research has indicated that light activity may contribute to youth health and long-term engagement in PA (Carson et al., 2013), youth light PA will need to be included in future ASP studies.

Conclusion

The ASP setting is a common developmental context in which millions of youth within the United States spend their out-of-school time. As youth are becoming increasingly inactive, there is pressing need to develop strategies within ASPs to increase children and adolescent motivation and engagement in PA. Given the consistent instability of U.S. funding at national and state levels for supporting afterschool programming in recent years, coupled with increased need for ASP programming within communities (Afterschool Alliance, 2012), the majority of ASPs, especially underresourced programs, will face continued challenges of how to effectively implement the PA components of their programs with shrinking resources and dismal prospects for new support. Consequently, researchers and other youth advocates will need to direct their focus toward developing cost-effective strategies (e.g., requiring minimal capacity) to improve the quality of the physical and motivational climate of ASPs for promoting youth PA.

The present study contributes to our understanding of key social-motivational climate factors that may be easily modifiable and effective in increasing youth PA behaviors within underresourced programs. Overall, the expectation is that youth PA engagement will be greatest for programs demonstrating high “process quality” across the important physical and social-environment features observed in the present study. In light of findings which suggest the importance of key physical and social-motivational context features for youth PA within ASPs, the minimal percentage of observations in which we observed any of these targeted contextual correlates in the present study is disconcerting and indicates that addressing these needs within ASPs may be a promising and cost-effective strategy for increasing youth PA during the afterschool hours.

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.

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