A Closer Look at the Camp Experience: Examining ...

Journal of Outdoor Recreation, Education, and Leadership

2016, Vol. 8, No. 2, pp. 180–199

https://doi.org/10.18666/JOREL-2016-V8-I2-7694

A Closer Look at the Camp Experience: Examining Relationships Between Life Skills, Elements of Positive Youth Development, and Antecedents of Change Among Camp Alumni Barry A. Garst Ryan J. Gagnon Clemson University

Anja Whittington Radford University

Abstract Understanding program components that contribute to positive youth outcomes following camp experiences can help program providers bring a greater level of intentionality to their efforts. The purposes of this study were twofold: (a) to develop reliable and valid measures of life skill development, elements of positive youth development (PYD), and antecedents of change within the context of camp and (b) to examine potential relationships between life skill development, elements of PYD, and antecedents of change to better understand elements that influence youth outcomes in camp. Data were collected from 429 camp alumni using an online survey. Exploratory factor analysis was used to explore the reliability and validity of the three proposed scales, and hierarchical multiple regression was used to examine how selected variables contributed to the participants’ outcomes scores. Study results suggest three psychometrically sound instruments were developed to measure these constructs. Implications for research and practice are explored. KEYWORDS: camp experiences; positive youth development; life skills; antecedents of change; exploratory factor analysis

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A CLOSER LOOK AT THE CAMP EXPERIENCE

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The potential for camp experiences to contribute to the growth and development of youth is well documented (see Henderson, Bialeschki, & James, 2007, and Garst, Browne, & Bialeschki, 2011, for a summary of this research). In the past 15 years, an extensive body of research investigating youth outcomes in traditional and specialized camps has emerged (most recent studies including Devine, Piatt, & Dawson, 2015; Hill, Gagnon, Ramsing, Goff, & Kennedy, 2015). Although considerable attention has been paid to the outcomes of camp experiences, less interest has been paid to elements that may contribute to those outcomes. As Yohalem and Wilson-Ahlstrom (2010) explained, “While consensus is building within the field about what constitutes effective practice, research that links specific program features to youth outcomes is rare” (p. 352). Labeled mechanisms (Mainieri & Anderson, 2015), conditions (Garst, Franz, Baughman, Smith, & Peters, 2009), elements (Hough & Browne, 2009), and/or antecedents of change (Garst, 2010), many factors are believed to be influential on program outcomes including session length, program structure, staff support, and program intentionality. As interest in these elements has grown in the broader youth development literature (Durlak & Weissberg, 2007) as well as the camp-specific literature (Mainieri & Anderson, 2015), researchers have attempted to unpack the black box (Ewert, 1983) of impactful camp experiences, encouraged by calls for evidence not only for the end product of camp experiences but also for conditions and actions likely to influence success (Garst, 2010). This black box metaphor originated in John Watson’s (1913) behaviorist approach to learning, suggesting that a person (or in this case, a program) is a black box and nothing is known about what goes on inside. Understanding how outcomes might be influenced, produced, or otherwise enhanced may allow camp program providers to bring a greater level of intentionality to their efforts—producing camp experiences most likely to positively affect youth. Although many camp providers may attest to already having this knowledge “on the ground” and in practice, empirical evidence of the antecedents or mechanisms of change to support promising practices is still needed. The relatively low percentage of camps that intentionally target certain programs or initiatives to address specific youth issues suggests that few camp providers use theories of change to guide their programs (American Camp Association, 2011a). Such information about the desired outcomes as well as about the strategies and activities designed to produce those outcomes may help camp program providers develop a “conceptual framework of intentionality . . . that clearly defines what can or cannot be accomplished” (Henderson, Oakleaf, & Bialeschki, 2009, p. 184). Given the lack of clear investigation into these potential mechanisms of change, this study, which examines life skills, elements of positive youth development, and antecedents of change associated with camp experiences, was part of a larger project that explored the long-term effects of camp experiences based on the perceptions of a national sample of camp alumni. The purposes of this study were twofold: (a) to develop reliable and valid instruments that measure life skill development, elements of positive youth development (PYD), and antecedents of change within the context of camp and (b) to examine the relationships between skill development, elements of PYD, and antecedents of change to better understand conditions that influence youth outcomes in camp.

Review of Literature Life Skill Development Through the Camp Experience Enhancement of life skills is a central feature of positive youth development settings (Eccles & Gootman, 2002). Although life skills examined within the context of youth development often lack a clear definition, Duerden and Witt (2011) pointed out that conceptualizations of life skills generally reflect a definition provided by the World Health Organization (WHO, 1997), which described life skills as “abilities for adaptive and positive behavior, that enable individuals [youth] to deal effectively with the demands and challenges of everyday life” (WHO, 1997, p. 1). http://www.ejorel.com/

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These abilities encourage young people to expand their knowledge and to move toward mastery of concepts and practices. Theoretical models such as the “developmental assets” model (Benson, Scales, & Syvertsen, 2011), the 5Cs model of positive youth development (Lerner, Almerigi, Theokas, & Lerner, 2005), the Community Action Framework for Positive Youth Development (Gambone & Connell, 2004), and the Targeting Life Skills model (Hendricks, 1998) often guide research related to life skills developed through youth development programs. A diverse body of research supports the influence of camp experiences on life skill development in youth. These skills, often described as program outcomes, include socioemotional developmental outcomes (Henderson, Bialeschki, Scanlin, Thurber, et al., 2007; Thurber, Scanlin, Scheuler, & Henderson, 2007), career development (Brandt & Arnold, 2006; Duerden et al., 2014; Garst, Baughman, Whittington, & Gagnon, 2015), health and physical activity outcomes (Beets, Weaver, Beighle, Webster, & Pate, 2013; Brown & Fry, 2011; Hickerson & Henderson, 2013), learning and academic outcomes (Garst & Ozier, 2015), environmental awareness (Browne, Garst, & Bialeschki, 2011), resilience (Ungar, 2012), and social-cultural understanding (Fine & Tuvshin, 2010). In the largest state-level multicamp study of the developmental outcomes of camp experiences conducted to date, Garst and Bruce (2003) collected postprogram data from 8,118 campers aged 9–13 and found that social skills and independence were key outcomes of the camp experience. Similarly, the American Camp Association (2005) in a national study of the developmental outcomes of camp experiences compared pre- and postcamp data from 3,400 families and found that social skills as well as physical and thinking skills were critical youth outcomes associated with camp participation. In a study of the effects of summer camp experiences on youth resilience, Merryman, Mezei, Bush, and Weinstein (2012) used a quasi-experimental design including a control group and found that youth who attended camp had greater gains in social skills and positive values compared with youth who did not attend camp. A few studies have examined the influence of camp experience on skills commonly associated with 21st century competencies—skills that have been identified by employers as important for contemporary workforce success (Casner-Lotto, Barrington, & Wright, 2006), including teamwork, social skills, and initiative—that are valuable to employers. In a study of 205 camp counselors, Ferrari and McNeely (2007) found that the camp experience facilitated the development of 21st century skills. Duerden et al. (2014) conducted focus groups with 21 camp alumni to examine the workforce development outcomes of the camp experience. Participants experienced growth in skills related to interpersonal interactions, communication, problem solving, and leadership. Considering the effectiveness of the camp experience for building life skills in youth, there is evidence that the camp experience is distinct from other youth development settings, in that youth spend a significant amount of time outdoors, youth are involved in 1–8 weeks of intense experiences instead of shorter experiences spread out over time, youth and staff are around one another for an extended time, and the ratio of staff to youth is low (Henderson, Thurber, Scanlin, & Bialeschki, 2007). Additionally, researchers have also noted the importance of the duration and intensity of the camp experience for children and adolescents (Ferrari & McNeely, 2007), which can be considerably longer than the amount of time that youth spend in other youth programs, particularly at one time. An important component of research associated with the developmental outcomes of camp experience has been identification of methodologically sound ways to measure outcomes in camp. Camp researchers have identified a need for reliable measures (Henderson et al., 2009), and the American Camp Association’s Camper Growth Index (Henderson, Thurber, Whitaker, Bialeschki, & Scanlin, 2006) and Youth Outcomes Battery (American Camp Association, 2011b) have been developed to address this need (Sibthorp, Browne, & Bialeschki, 2010). Still, the influence of camp experiences as a pathway for later life skill development continues to be underexamined compared with shorter term outcomes (Bialeschki, Henderson, & Journal of Outdoor Recreation, Education, and Leadership


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James, 2007). This lack of understanding has been compounded by inconsistent measurement of life skills within the youth development literature and has resulted in many researchers calling for better conceptualizations and measurement of life skill domains (Duerden & Witt, 2011). In this study, we developed and tested a measure of life skills that may be enhanced through the camp experience.

Elements of Positive Youth Development Over the past few decades, there has been an increase in research regarding the experiences and settings that contribute to positive youth outcomes. During this time, a shift from a deficits-based to a youth development model (Catalano, Berglund, Ryan, Lonczak, & Hawkins, 2002) occurred, reflecting a general consensus that avoidance of risky behaviors does not ensure that young people will develop the skills, competencies, and resources needed to prepare them fully for a successful transition to adulthood (Roth & Brooks-Gunn, 2003). Thus, the concept of PYD emerged based on human development theories that associated positive youth outcomes with specific conditions in a young person’s environment (Lerner et al., 2005). Rather than a deficits-based model, PYD theory focuses on a strengths-based approach for positive development in youth and hypothesizes that those served with a PYD approach will grow when their individual strengths are aligned with appropriate family and community resources (Zarrett & Lerner, 2008). In 2002, to better describe elements that would be indicative of a PYD setting or experience, the National Research Council and Institute of Medicine outlined features of positive youth development settings (Eccles & Gootman, 2002), which included physical and psychological safety; appropriate structure; supportive relationships; opportunities to belong; positive social norms; support for efficacy and mattering; opportunities for skill building; and integration of family, school, and community efforts. These features, which have also become known as the conceptually similar essential elements of positive youth development (U.S. Department of Agriculture, 2001) and the supports and opportunities of the Community Action Framework for Positive Youth Development (Gambone & Connell, 2004), have guided research and measurement on broader program features associated with PYD in camps (American Camp Association, 2006). Building on the work of Roth and Brooks-Gunn (2003), Lerner (2004) proposed three fundamental characteristics (i.e., the “Big Three”) that form the foundation of PYD programs: (1) positive and sustained youth–adult relations, (2) life-skill building activities, and (3) opportunities for youth participation as leaders in family, school, and community activities. Furthermore, Lerner et al. (2005) conceptualized the Five Cs model of youth development—Competence, Confidence, Connection, Character, and Caring—as a way to operationalize the developmental characteristics youth need to become contributing members of society. In this study, we developed and tested a measure of the elements of PYD that was informed by the features of positive youth development (Eccles & Gootman, 2002) as well as by the Community Action Framework for Positive Youth Development (Gambone & Connell, 2004.)

Antecedents of Change Parallel to the orientation of the youth development movement from a deficits-based model to a strengths-based approach, a movement has occurred over the past decade toward understanding specific program characteristics that contribute to PYD. As noted by Roark, Ellis, Wells, and Gillard (2010), “Little is known about staff dispositions, counselor teams, non-counselor staff, leadership techniques, camp policies, the number of summers campers attended, or other mechanisms of change that camps might employ to facilitate such outcomes” (p. 80). Attempts to understand these characteristics have been informed by a number of theoretical approaches, including program theory (Baldwin, Persing, & Magnuson, 2004), self-determination theory (Ryan & Deci, 2000), transformative learning (Mezirow, 2000), social ecology (McLeroy, Bibeau, http://www.ejorel.com/

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Steckler, & Glanz, 1988), developmental systems theory (Lerner et al., 2005), and the Community Action Framework for Positive Youth Development (Gambone, Connell, Klem, Sipe, & Bridges, 2002). (Table 1 summarizes findings and conclusions from conceptual articles as well as from empirical studies exploring contributing factors to PYD outcomes during camp experiences.) Taken as a whole, the findings summarized in Table 1 help to understand factors that may or may not contribute to camper growth and development. For example, camp session length (i.e., the number of days a young person stays at camp; Henderson, Bialeschki, & James, 2007; Thurber et al., 2007), otherwise known as dosage, has generally not been found to predict positive youth outcomes. Additionally, and contrary to conventional wisdom, amount of staff training has not predicted program outcomes (Henderson, Bialeschki, & James, 2007). Although some studies suggest that qualities of camp staff (i.e., how staff either support youth autonomy or are instead controlling) predict positive youth outcomes (Garst et al., 2009), other studies have failed to find this result (Roark et al., 2010). It seems that the most consistent features that contribute to positive youth outcomes during camp experiences are program related. Specifically, program elements such as camp type (day or resident camp) and the amount of structured versus free time provided to youth have been found to be associated with positive outcomes (Schmalz, Kerstetter, & Kleiber, 2011). Furthermore, there is empirical evidence that delivering a camp program with intention (i.e., mental state representing a commitment to carrying out an action in the future; Bratman, 1987) is associated with greater changes in youth outcomes (Garst & Ozier, 2015). Given the variability in the literature on program characteristics that may influence youth development outcomes as a result of camp experiences, in this study we developed and tested a measure of the antecedents of change for positive youth outcomes in camp. Table 1 A Synthesis of Contributing Factors to Youth Development Outcomes During Camp Experiences Author(s)

Key findings/conclusions

Conceptual/theoretical frame

American Camp Camp characteristics associated with Association (2006) optimal youth experiences included camp type, session length (4 weeks or more), gender (being a girl), race/ ethnicity (being White), and camp experience (spending multiple summers at camp). Session length was not a predictor.

Community Action Framework for Youth Development (Gambone, Connell, Klem, Sipe, & Bridges, 2002)

a

Henderson, Bialeschki, & James (2007)

Proposed that social and environmental structures may enhance or prohibit human behaviors (e.g., program components, leadership styles)

Social Ecology (McLeroy, Bibeau, Steckler, & Glanz, 1988)

Thurber, Scanlin, Scheuler, & Henderson (2007)

Age (older youth showed more change than younger youth); program intentionality (camps targeting spirituality). Session length did not support a dosage effect.

Prevention Science (Greenberg et al., 2003); Positive Youth Development (Catalano, Berglund, Ryan, Lonczak, & Hawkins, 2002)

Henderson, Bialeschki, Scanlin, et al. (2007)

No structural elements statistically associated directly with outcomes (i.e., session length, sponsorship, camp structure, camp fees, budget size, and staff training)

Youth Development (Eccles & Gootman, 2002; Baldwin, Caldwell, & Witt, 2005)



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Table 1 (cont.) Author(s)



Ramsing & Sibthorp (2008)

Autonomy support (e.g., providing rationale, choice, and perspective; limiting control) was shown to enhance youth outcomes. Group size was not a predictor.

Self-Determination Theory (Ryan & Deci, 2000)

Hough & Browne (2009)

Youth outcomes associated with program elements included camp staff, structured time, unstructured time, camp type, and accessibility.

Program Theory (Baldwin, Persing, & Magnuson, 2004)

Garst, Franz, Baughman, Smith, & Peters (2009)

Conditions of change that facilitated youth outcomes included exposure/ acceptance, supportive relationships, group goals, traditions, camp context, and context comparisons

Transformative Learning Theory (Mezirow, 2000)

Roark, Ellis, Wells, & Gillard (2010)

No relationship found between camp staff dispositions (autonomysupportive or controlling) and youth outcomes.

Self-Determination Theory (Deci & Ryan, 1985)

a

Garst (2010)

Proposed that “antecedents of change” may include staff performance and program components

Program Theory (Baldwin, Persing, & Magnuson, 2004)

Schmaltz, Kerstetter, & Kleiber (2011)

Found that free-choice program structure facilitated youth outcomes.

Self-Determination Theory (Ryan & Deci, 2000)

a

Garst, Browne, & Bialeschki (2011)

Proposed that youth outcomes may be associated with setting characteristics (nature-based/non-naturebased time [duration, intensity, breadth]); structural characteristics (norms, group organization, traditions, rituals); and program/activity characteristics (experiential learning, choice, positive risk taking)

Community Action Framework for Youth Development (Gambone, Connell, Klem, Sipe, & Bridges, 2002)

Johnson, Goldman, Garey, Britner, & Weaver (2011)

Identified camp as a “moratorium environment” that facilitated identity development among youth

Erikson’s (1968) concept of the psychosocial moratorium

Gillard & Watts (2013)

Examined camp contexts (programs goals, atmosphere, and activities within a living environment). Peer support of competence predicted interest in camp.

Developmental Systems Theory (Lerner, Almerigi, Theokas, & Lerner, 2005)

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Table 1 (cont.) Author(s)



a

Mainieri & Anderson (2015)

Proposed that positive youth outcomes may result because of camp mechanisms plus the influence of context.

Program Theory (Baldwin, Persing, & Magnuson, 2004); Realistic Evaluation (Pawson & Tilley, 1997)

Hill et al. (2015)

Described a variety of camp activities that were associated with selfdetermined behavioral outcomes.

Self-Determination Theory (Deci & Ryan, 2000)

Conceptual study or literature review.

a

Camp Characteristics This study was conducted with a broad sample of day and residential camps. In this study, a camp was defined as a sustained experience that provides a creative, recreational, and educational opportunity in group living often occurring in the outdoors. It utilizes trained leadership and the resources of the natural surroundings to contribute to each camper’s mental, physical, social, and spiritual growth. (American Camp Association, 2012, p. 285) Camps have also been categorized based on camp type (i.e., day camp or overnight camp), target audience (i.e., primary audience targeted by the camp, including all boys, all girls, or coeducational), session length (typically 1 to 8 weeks in length), camp ownership/sponsorship, and program focus. Camp participants can differ based on a variety of characteristics, in addition to demographics, including prior camp experience (i.e., number of years attending camp), whether they have a leadership role in camp (i.e., staff status), and so on. In this study, dimensions of the camp experience examined as independent variables included camp type, session length, camp experience, and staff status.

Method Participants Participants were recruited through a research collaboration with the American Camp Association (ACA), which provided a randomized list of 350 ACA-accredited camps located throughout the United States. This recruitment approach was selected to identify a broader more representative population of camp alumni than would be identified through a smaller more targeted group of camps. Camp directors were contacted in the summer of 2014 via e-mail and asked to share an online survey with their alumni either via Facebook or e-mail, which elicited 427 total respondents. As many camps did not closely track their alumni responses to the survey, total numbers of alumni in general, or participated at various levels, an exact response rate for the sample could not be calculated because the population to whom the advertisements were visible (i.e., the population) was unknown. In spite of the limitations presented by the lack of a response rate for this study, a power analysis conducted prior to the final hierarchical multiple regression indicated that 228 was the minimum sample size necessary given the number of potential independent variables (12 variables) and desired effect size utilizing multiple R2 ≥ .350 (see Cohen, Cohen, West, & Aiken, 2003).



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Instrument An online Qualtrics survey was created and made available to camp alumni for 45 days. The survey contained both short answer and Likert-style questions related to participant demographics, skill development that alumni associated with camp participation, alumni perceptions of camp as a setting for PYD, and components of the camp experience that alumni believe contributed to developmental outcomes. Three subscales were developed based on a review of the relevant literature in a 1–4 Likert format. The subscales used a retrospective pretest (RPT) format (Davis, 2003) with questions set up so that respondents were asked to compare themselves currently with how they were prior to the camp experience. RPT designs have become common in studies of program effects (Marshall, Higginbotham, Harris, & Lee, 2007) because concerns associated with incomplete data sets (Raidl et al., 2004) and response shift bias (Sibthorp, Paisley, Gookin, & Ward, 2007) can be avoided. Response shift bias is best described as a change in a participant’s personal metric for answering questions from pretest to posttest due to a new appreciation of a concept being learned (Klatt & Taylor-Powell, 2005). The first scale was developed to measure skill development (SD) as a result of the camp experience and contained 43 items with questions that asked respondents to “Please identify to what extent, if any, each of the following skills was impacted by your camp experience.” Respondents could choose from 1 (no extent) to 4 (to a great extent). The second scale was designed to measure antecedents of change (AOC) and consisted of 14 items with questions such as “How important were the following camp components in promoting change in you as an individual: Being Away from Home?” Respondents could choose from 1 (not at all important) to 4 (very important). The third scale consisted of seven items that asked questions related to camp as a positive youth development setting (PYD) with questions such as “To what extent did your camp experience provide the following: Supportive Adult Relationships?” Respondents could choose from 1 (no extent) to 4 (to a great extent).

Scale Validation Before potential relationships were tested, the data were screened for outliers using leverage values, examination of scree plots, and the normality of data. This screening resulted in the removal of three cases. Next, a series of factor analyses was conducted. Simply put, factor analysis uses observed variables (i.e., survey questions) to measure unobserved (i.e., latent factors) variables (Field, 2013). To determine if the three subscales (Skill Development, Elements of PYD, and Antecedents of Change) were valid and reliable measures, an exploratory factor analysis (EFA) was conducted. EFAs were conducted separately on the subscales because of the layout of the survey (i.e., questions sets were separated by electronic page breaks or other; questions asked using different range values). For instance, the AOC scale asked questions using the response choices of 1 = not at all important to 4 = very important, and the YD subscale used response choices of 1 = no extent to 4 = to a great extent. Skill development. To determine the reliability and validity of the skill development scale, an EFA was conducted on the 43-item scale using SPSS 22 software. The suitability of the EFA was assessed prior to the analysis. Inspection of the correlation matrix showed that all variables had at least one correlation above 0.3. The overall Kaiser–Meyer–Olkin (KMO) measure was .856 with all individual items above 0.7. Bartlett’s test of sphericity was significant (p ≤ .001). The combination of the acceptable sphericity and KMO scores indicated that the sample was adequate in size and likely factorable. Next, a parallel analysis was conducted with simulated data for eigenvalue comparison to the actual data set. An EFA was then conducted using maximum likelihood estimation and a promax rotation. These methods were chosen because they do not assume that variables in different factors are uncorrelated (orthogonal). As indicated by the results of the parallel analysis, seven factors were specified. After examination of the pattern matrix for simple structure, when items are neither http://www.ejorel.com/

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multidimensional nor weakly loading onto a single factor, 14 items were eliminated. The EFA was conducted again, resulting in an additional 17 items being removed. The most common reasons for an item (i.e., question) being removed (21 items) were multidimensionality (loading onto multiple factors) and weak loadings onto all factors and no clear primary factor (10 items). The final version of the subscale contained 12 items loading onto three factors (F1, SelfDetermined Behavior (SDB), eight items; F2, Critical Thinking, two items; F3, Physical WellBeing, two items). See Table 2 for the final factor loadings. After scale validity was determined, a reliability analysis was conducted using Cronbach’s alphas (α) and Joreskog’s rho (ϱ). Factor 1 (SDB) indicated good reliability as evidenced by both Joreskog’s rho and Cronbach’s alpha (ϱ = .905, α = .862). As the other two factors only possessed two items each, it was meaningless to conduct reliability analyses (e.g., Joreskog’s rho or Cronbach’s alpha), and a Pearson’s correlation was deemed more appropriate (see Eisinga, Grotenhuis, & Pelzer, 2012). Both Factor 2 and 3 indicated good reliability as indicated by Pearson’s correlations (F2, r = .770; F3, r = .782). Given the evidence of reliability and validity in the skill development subscale, composite scores were created for each factor for relationship testing using the mean transformation function in SPSS (F1, M = 3.59, SD = .432; F2, M = 3.28, SD = .734; F3, M = 3.18, SD = .756). Table 2 Exploratory Factor Analysis Loadings of Camp Skill Development Scale (N = 427) Factors Self-determined behavior

Item

Critical thinking

Physical well-being

Confidence

.861

-.138

-.050

Self-Efficacy

.767

-.069

-.054

Competence

.704

.001

.052

Initiative

.605

.164

-.044

Making New Friends

.524

-.062

-.053

Courage

.518

.170

.167

Resiliency

.482

.119

.020

Perseverance Critical Thinking Problem Solving Feelings of Physical Strength Physical Fitness

.480

.187

.150

-.083

.918

.018

.012

.903

-.081

-.088

.009

1.008

.039

-.071

.821

Note. All items were prefaced with “Please identify to what extent the following skill was impacted by the camp experience . . .” Items in bold indicate factor and composite. All loadings were obtained from the pattern matrix table in SPSS. Elements of positive youth development. To determine the validity and reliability of the seven-item Elements of Positive Youth Development (EPYD) scale, an EFA was conducted using SPSS 22 software. To ensure that an EFA was the proper test, several analyses were conducted. The correlation matrix indicates that all variables had at least one correlation above 0.3, the KMO measure was .791, and Bartlett’s test of sphericity was significant (p ≤ .001). The convergence of these three analyses indicate that the data were likely factorizable and had an appropriate sample size. Journal of Outdoor Recreation, Education, and Leadership


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An EFA using a maximum likelihood estimation and a promax rotation was conducted to determine the number of factors present to ready the actual data for comparison to parallel analysis. However, the results of the initial EFA loaded onto only one factor, thus indicating a parallel analysis was unnecessary. The findings from the first iteration of the EFA with this question set indicate that all six items could be kept because of good unidimensionality as evidenced by the factor matrix. To ensure reliability, a Cronbach’s alpha and Joreskog’s rho were conducted and results indicated high levels of reliability (ϱ = .904, α = .854). After it was determined that the subscale was valid and reliable, a composite score was created (M = 3.66, SD = .433) for further relationship testing. (See Table 3 for final factor loadings.) Table 3 Exploratory Factor Analysis Loadings of Elements of Positive Youth Development Scale (N = 411) Item

Factor loading

Opportunity to learn and practice skills Opportunities for skill building Supportive adult relationships Emotional safety Sense of belonging Opportunity to develop close relationships with peers Physical safety

.776 .771 .700 .697 .647 .628 .546

Note. All items were prefaced with “To what extent did your camp experience provide the following . . .” All loadings were obtained from the pattern matrix table in SPSS. Antecedents of change. To determine the validity and reliability of the 14 item Antecedents of Change (AOC) scale, an EFA was conducted. Prior to the initial EFA, we conducted a parallel analysis to determine the potential number of factors present in our sample using randomized data and results indicated up to five factors potentially present. To ensure that the data were factorable, we investigated the correlation matrix, KMO scores, and sphericity. Results indicated that the sample was adequate and the data factorable, as evidenced by all variables having at least one correlation above 0.3, the KMO score being .878, and Bartlett’s test of sphericity being significant (p ≤ .001). The initial EFA indicated that nine items were a poor fit with this subscale because of poor unidimensionality (five items) and poor loadings (four items). The final subscale consisted of five items (see Table 4 for final factor loadings.) To ensure that the scale was reliable, a Cronbach’s alpha and Joreskog’s rho were conducted, both results indicating a high level of reliability (ϱ = .821, α = .804). As the subscale was determined to be a valid and reliable measure, a composite score was created for further relationship testing (M = 3.63, SD = .455). Table 4 Exploratory Factor Analysis Loadings of Antecedents of Change Scale (N = 411) Item

Factor loading

Being treated fairly Staff attention and interaction Sense of community Small groups Leadership opportunities

.796 .736 .703 .618 .599

Note. All items were prefaced with “How important were the following components in promoting change in you as an individual . . .” All loadings were obtained from the pattern matrix table in SPSS. http://www.ejorel.com/

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Relationship Testing Through the Regression Model To build the hierarchical regression model, we consulted previous research and conducted Pearson’s and Spearman’s correlations. The variables were entered into the regression model based on a review of the camp literature (Bialeschki et al., 2007; Garst et al., 2009). Of the variables tested in the regression model, two were measured on a nominal scale: Camp Type and Staff Status; as such, they were recoded into “dummy” variables for each, in which groups are measured using zeros and ones (Field, 2013). We conducted Spearman’s correlations on the camp type variable and the staff status variable because these variable were not interval or ordinal level data, and as such, Pearson’s correlations would have been inappropriate. Means, standard deviations, and correlations for these variables are presented in Table 5. Table 5 Means, Standard Deviations, and Correlations of Tested Variables (N = 411) Variable

M (SD)

1

2

3

4

5

6

7

1. PYD

3.66 (.433)

2. AOC

3.62 (.455)

.610**

3. CT

3.28 (.731)

.451**

.499**

4. PWB

3.18 (.756)

.330**

.248**

.314**

5. SDB

3.59 (.432)

.552**

.497**

.567**

6. Staff Status

–

-.155**

-.282**

-.154**

7. Camp Type

–

-.069

-.057

-.032

8.Session Length

6.68 (4.43)

.085

.079

.004

.131**

.208**

-.252**

.067

9. Years

7.84 (3.68)

.169**

.184**

.195**

.071

.138**

-.395**

.068

8

.500** .014 -.071

-.133** -.040

-.025

.110*

Notes. Spearman’s correlations conducted on staff status and camp type; all other variables utilize Pearson’s correlations; staff status and camp type are dichotomous variables, and frequencies for these variables are presented in Table 6. * p ≤ .05. **p ≤ .01.

Results Sample Descriptives The sample consisted of 429 respondents, who were primarily female (n = 339, 79%), White (n = 414, 96.5%), and married (n = 238, 56%), and the majority had a personal income of $0.00$50,000/year (n = 193, 45%). Respondents were primarily aged 25–34 years (25.2%) and reJournal of Outdoor Recreation, Education, and Leadership


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ported an average of 7.84 years (SD = 3.68) of attending camp. Of the total respondents, 317 reported some administrative or counselor role as part of their camp experience (74.2%), and 110 reported as campers only (25.8%). See Table 6 for a full description of the sample. Table 6 Sample Descriptives (N = 429) Demographic Gender Male Female No response Race White Black Native American Asian Hispanic Multiple Income $0.00–50,000 $50,001–100,000 $100,001–150,000 $150,001–200,000 > $200,000 No response Age Ranges 18–24 years 25–34 years 35–44 years 45–54 years 55–64 years 65–74 years ≥ 75 years No response Average Length of Camp 1 week 2 weeks 3 weeks 4 weeks 5 weeks 6 weeks 7 weeks 8 weeks 9 weeks 10 weeks > 10 weeks No response

n 85 339 5

%

414 3 4 2 3 3

19.8 79.0 1.2 100.0 96.5 0.7 0.9 0.5 0.7 0.7

193 130 41 15 16 34

45.0 30.3 9.6 3.5 3.7 7.9

77 108 93 52 56 32 6 5

17.9 25.2 21.7 12.1 13.0 7.5 1.4 1.2

107 33 77 56 8 29 7 81 11 9 5 6

24.9 7.7 17.9 13.1 1.9 6.8 1.6 18.9 2.6 2.0 1.2 1.4


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Table 6 (cont.) n

Demographic Camp Type Residential Day Camp No response Target Audience Co-ed All-Girls All-Boys No response

%

412 15 2

96.0 3.5 0.5

287 131 9 2

66.9 30.5 2.1 0.5

Regression Model A hierarchical multiple regression was conducted to determine if the addition of AOC (Model 2), Session Length (Model 3), and then Target Audience (Model 4) improved the prediction of SDB over and above PYD (Model 1) alone. See Table 7 for details on each regression model. In Model 4, the combination of PYD, AOC, Session Length, and Target Audience accounted for 38.1% of the variance in predicting the SDB (Model 4) and was statistically significant, R2 = .381, F(1, 406) = 62.573, p ≤ .001, adjusted R2 = .375. In Model 4, the unique effect sizes of PYD (sr2 = .115), AOC (sr2 = .071), Session Length (sr2 = .098), and Target Audience (sr2 = .018) uniquely explained 11.5%, 7.1%, 9.8%, and 1.8% of variance in SDB score. The variables of staff status, years spent at camp, and camp type (resident or day camp) were not significant predictors in this regression and thus were excluded from further modeling. Table 7 Hierarchical Multiple Regression Predicting Self-Determined Behavior Score From PYD, AOC, Session Length, and Target Audience Model 1 Variable

B

Constant

1.529

PYD

.563**

AOC

Model 2 β

B

Model 3 β

1.106 .547

B

Model 4 β

1.080 .387

.388**

.377

.378**

.368

.282**

.284

.274**

.276

.279**

.281

.014**

.144

.013**

.134

.073*

.081

Target Audience Model F ∆R² ∆F

.300 174.975** .300 174.975**

β

.398**

Session Length R²

B 1.079

.355 112.087**

.375

.381

81.402**

62.573**

.055

.020

.006

34.758**

13.283**

4.179*

Note. N = 416. *p ≤ .05. **p ≤ .001

Discussion The purposes of this study were twofold: to begin the validation of three subscales measuring life skill development, elements of PYD, and antecedents of change associated with camp Journal of Outdoor Recreation, Education, and Leadership


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experiences and to examine the relationships between skill development, elements of PYD, and antecedents of change. The results suggest that three psychometrically sound instruments were developed to measure these constructs. The skill development scale contained 12 items that loaded onto three factors for measuring skill growth associated with camp experiences: SDB, critical thinking, and physical well-being. Although this study was not framed from the perspective of self-determination theory (SDT; Deci & Ryan, 2000), the SDB factor items of confidence, self-efficacy, competence, initiative, friend making, courage, resiliency, and perseverance strongly reflected prior SDT research in the three-factor model. The emergence of “critical thinking” (composed of problem solving and critical thinking items) as one of the top three factors supported the work of Duerden et al. (2014), who found that the development of problem-solving skills was a long-term effect that camp alumni associated with camp experiences. The similarity in alumni perceptions of camp as an experience that builds problem-solving and/or critical thinking skills may reflect the importance of having sufficient time (retrospectively reflecting on the camp experience later in life) to appreciate certain types of skills, particularly those that may be more cognitively complex. The PYD scale factor loadings substantiated the supports and opportunities approach that forms the foundation of the Community Action Framework for PYD (Gambone & Connell, 2004), with the strongest factor loadings reflected in items associated with skill building, supportive relationships, emotional and physical safety, and opportunities to belong. This finding lends additional support to camp-related studies that have used the Community Action Framework for PYD (Thurber et al., 2007) and suggests that the Community Action Framework may be an excellent starting point for camps seeking to evaluate their camp experiences as a setting for PYD or develop a theory of change to guide their camps programs based on a PYD approach. Henderson et al. (2006), reflecting on the appropriateness of the Community Action Framework as a guiding theory for camp research, suggested that the framework “described how strategies such as relationships, activities, and program structure become the tools for reaching the intended outcomes generally described as learning, social relationships, positive values, and positive identity” (p. 7). In general, the findings of this study strongly support prior research indicating that camp is a setting for PYD. A primary purpose of this study was to better understand life skill development, elements of PYD, and antecedents of change to better understand elements that influence youth outcomes in camp. Our findings reflect conceptual overlap between the elements of PYD and AOC factors, which is not entirely surprising. In the camp literature, researchers have noted that mechanisms of change (identified as AOC in this study) may not be as critical for influencing the extent to which a young person’s camp experience is developmental as long as PYD is considered in the program delivery model (Henderson, Bialeschki, & James, 2007). However, the potential influence of small group size, as a component of the AOC factor, was a unique finding and may suggest that group size plays a role in positive outcomes received by camp participants. This finding diverged from results found by Ramsing and Sibthorp (2008), who studied the influence of group size on youth perceptions of autonomy support in camp. In their study, group size was not a significant predictor of youth perceptions of autonomy support. In addition, we examined camp structural variables that might also contribute to AOC. As noted in the results, Session Length and Target Audience contributed to the model. In fact, the combination of PYD, AOC, Session Length, and Target Audience accounted for 38.1% of the variance in predicting SDB, the most prominent life skill factors. The influence of session length in contributing to developmental outcomes appeared to contradict the work of Thurber et al. (2007), who found that session length did not support a dosage effect for change at camp. Several variables were not significant predictors, nor did they contribute in a meaningful way to effect sizes including Camp Type (resident or day camp), Camp Experience, and Staff Status. This was a particularly important finding for practitioners and even parents, who may question, for http://www.ejorel.com/

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example, the possible developmental advantages for youth who attend resident camps over day camps or the possible cumulative influence of attending camp every summer for multiple years. This study refutes the importance of these variables for contributing to youth skill development. Failure to identify Camp Experience as a predictive variable for PYD diverged from the ACA’s (2006) findings. In a national study of camper perceptions of camp as a PYD setting, the ACA found that spending multiple summers at camp was important for youth to experience optimal growth. The differential importance of prior camp experience between the ACA’s study and the current study may reflect differences between the samples that were studied. In the ACA’s study, youth aged 10–17 were surveyed to determine factors that contributed to “optimal experiences” from the perspective of PYD. In the current study, camp alumni ranged from 18 years old to more than 75 years old. The importance of spending multiple summers at camp may be more salient for younger campers or may be perceived as more influential across a young person’s shorter life span than it is for camp alumni who have more life experiences across a broader life span.

Limitations A few study limitations are acknowledged. First and foremost, although this was a national study involving a random sample of camps from across the country, camps did not closely track their alumni responses to the survey. The unknown response rate makes it difficult to generalize the findings. Consistent with survey research using similar sampling approaches (Jun & Kyle, 2011), we recognize that the inability to definitively compare our sample characteristics with the overall population of camp alumni reflects a notable study design limitation, yet the response rate challenge has been noted by other camp researchers (Roark et al., 2010). For the intent of our study, and consistent with prior literature, however, the data still enabled us to establish tentative conclusions about the study’s guiding theories. Second, the format of some questions (e.g., age and income), designed to be simple for the respondents, was in ranges rather than exact numbers, which limited the analysis options for those variables. Third, weaknesses were identified in the life skills scale. The scale was not based on prior psychometric investigation; the scale used a 1–4 response choice range; and 31 items were dropped, which suggests problems with the question wording.

Future Directions We encourage researchers to replicate this study using a sampling strategy that will allow the response rate to be closely monitored. Furthermore, the measures developed in this study would benefit from additional testing. We believe the SDB scale and the AOC scale hold the most promise for future research—the elements of the PYD scale less so only because it replicated the findings of Gambone and Connell (2004) with essentially the same items found in their model. Researchers and camp program providers interested in life skill development through camp experiences, particularly from the perspective of camp alumni, are encouraged to incorporate the SDB, critical thinking, and physical well-being scales into such studies. Although this study synthesized prior research related to mechanisms that contribute to positive youth outcomes in camp and contributed to the body of knowledge related to the relationship between AOC factors and life skill development, there is more to be learned. For example, the finding associated with group size as a possible contributing factor is interesting and (as discussed earlier) conflicts with prior research (Ramsing & Sibthorp, 2008). Additional quantitative (e.g., benchmarking studies of group size in camps, examining relationship between group size and developmental outcomes) as well as qualitative (e.g., perceptions of camp group size; comparing youth, staff, director, and parent perspectives; meanings associated with group size) studies focusing specifically on group size may illustrate the potential influence of this antecedent on camper outcomes. Journal of Outdoor Recreation, Education, and Leadership


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References American Camp Association. (2005). Directions: Youth development outcomes of the camp experience. Retrieved from http://www.acacamps.org/sites/default/files/images/research/ directions.pdf American Camp Association. (2006). Inspirations: Developmental supports and opportunities of youths’ experiences at camp. Retrieved from http://www.acacamps.org/resourcelibrary/research/inspirations-developmental-supports-and-opportunities-youthsexperiences American Camp Association. (2011a). Camp sites, facilities, and programs report: 2011. Retrieved from http://www.acacamps.org/research/improve/2011-sites-facilities-programsreport American Camp Association. (2011b). Youth outcomes battery (2nd ed). Retrieved from http:// www.acacamps.org/research/youth-outcomes-battery American Camp Association. (2012). Accreditation process guide. Martinsville, IN: Author. Baldwin, C., Caldwell, L., & Witt, P. (2005). Deliberate programming with logic models: From theory to outcomes. In P. A. Witt & L. L. Caldwell (Eds.), Recreation and youth development (pp. 219–239). State College, PA: Venture. Baldwin, C., Persing, J., & Magnuson, D. (2004). Role of theory, research, and evaluation in adventure education. Journal of Experiential Education, 26, 167–183. https://doi. org/10.1177/105382590402600307 Beets, M. W., Weaver, R. G., Beighle, A., Webster, C., & Pate, R. R. (2013). How physically active are children attending summer day camps? Journal of Physical Activity & Health, 10, 850– 855. https://doi.org/10.1123/jpah.10.6.850 Benson, P. L., Scales, P. C., & Syvertsen, A. K. (2011). The contribution of the developmental assets framework to positive youth development theory and practice. Advances in Child Development and Behavior, 41, 197–230. https://doi.org/10.1016/c2010-0-66913-6 Bialeschki, M. D., Henderson, K. A., & James, P. A. (2007). Camp experiences and developmental outcomes for youth. Child and Adolescent Psychiatric Clinics of North America, 16, 769–788. https://doi.org/10.1016/j.chc.2007.05.011 Brandt, J., & Arnold, M. A. (2006). Looking back, the impact of the 4-H camp counselor experience on youth development: A survey of counselor alumni. Journal of Extension, 44(6). Retrieved from https://joe.org/https://www.joe.org/joe/2006december/rb1.php Bratman, M. (1987). Intention, plans, and practical reason. Cambridge, MA: Harvard University Press. https://doi.org/10.1086/293169 Brown, T. C., & Fry, M. D. (2011). Strong girls: A physical-activity/life skills intervention for girls transitioning to junior high. Journal of Sport Psychology in Action, 2, 57–69. https://doi.org /10.1080/21520704.2011.573060 Browne, L., Garst, B., & Bialeschki, M. D. (2011). Engaging youth in environmental sustainability: Impact of the Camp2Grow program. Journal of Park and Recreation Administration, 29(3), 70–85. Casner-Lotto, J., Barrington, L., & Wright, M. (2006). Are they really ready to work? Employers’ perspectives on the basic knowledge and applied skills of new entrants to the 21st century U.S. workforce. Retrieved from Partnership for 21st Century Skills website: http://www.p21.org/ storage/documents/FINAL_REPORT_PDF09-29-06.pdf Catalano, R. F., Berglund, M. L., Ryan, J. A. M., Lonczak, H. S., & Hawkins, J. D. (2002). Positive youth development in the United States: Research findings on evaluations of positive youth development programs. Prevention & Treatment, 5, 15. https://doi.org/10.1037/15223736.5.1.515a


196


Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlational analysis for the behavioral sciences (3rd ed.). New York, NY: Routledge. https://doi. org/10.4324/9780203774441 Davis, G. A. (2003). Using a retrospective pre–post questionnaire to determine program impact. Journal of Extension, 41(4). Retrieved from http://joe.org/joe/2003august/tt4.php Deci, E., & Ryan, R. (1985). Intrinsic motivation and self-determination in human behavior. New York, NY: Plenum Press. https://doi.org/10.1007/978-1-4899-2271-7 Deci, E., & Ryan, R. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. h t t p s : / / d o i . org/10.1037/0003-066x.55.1.68 Devine, M. A., Piatt, J., & Dawson, S. L. (2015). The role of a disability-specific camp in promoting social acceptance and quality of life for youth with hearing impairments. Therapeutic Recreation Journal, 40, 310–325. https://doi.org/10.18666/trj-2015-v49-i4-6240 Duerden, M., & Witt, P. (2011). Assessing the need for the development of standardized life skills measures. Journal of Extension, 49(5). Retrieved from http://www.joe.org/joe/2011october/ rb5.php Duerden, M., Witt, P., Garst, B., Bialeschki, D., Schwarzlose, T., & Norton, K. (2014). The impact of camp employment on the workforce development of emerging adults. Journal of Park and Recreation Administration, 32(1), 26–44. Durlak, J. A., & Weissberg, R. P. (2007). The impact of after-school programs that promote personal and social skills. Chicago, IL: Collaborative for Academic, Social, and Emotional Learning. Eccles, J., & Gootman, J. A. (Eds.). (2002). Community programs to promote youth development. Washington, DC: National Academies Press. https://doi.org/10.17226/10022 Eisinga, R., Grotenhuis, M. T., & Pelzer, B. (2012). The reliability of a two-item scale: Pearson, Cronbach, or Spearman-Brown. International Journal of Public Health, 58, 637–642. https:// doi.org/10.1007/s00038-012-0416-3 Erikson, E. H. (1968). Identity: Youth and crisis. New York, NY: Norton. https://doi.org/10.1016/ s0033-3182(68)71853-3 Ewert, A. W. (1983). Outdoor adventure and self-concept: A research analysis. Eugene, OR: Institute of Recreation Research & Service, Department of Leisure Studies & Services. Ferrari, T. M., & McNeely, N. N. (2007). Positive youth development: What’s camp counseling got to do with it? Findings from a study of Ohio 4-H camp counselors. Journal of Extension, 45(2). Retrieved from http://www.joe.org/joe/2007april/rb7.php Field, A. (2013). Discovering statistics through SPSS (4th ed.). Los Angeles, CA: Sage. Fine, S., & Tuvshin, T. (2010). Cosmopolitan citizenship through the residential camp experience: Comparative research in North America and Central Asia. Abstracts from the Coalition for Education in the Outdoors Tenth Biannual Research Symposium (pp. 40–42). Retrieved from http://www2.cortland.edu/dotAsset/12f4edef-17dd-4966-be77-3606fefc69f0.pdf Gambone, M. A., & Connell, J. P. (2004). The community action framework for youth development. The Prevention Researcher, 11(2), 17–20. Gambone, M. A., Connell, J. P., Klem, A. M., Sipe, C. L., & Bridges, L. (2002). Finding out what matters for youth: Testing key links in a community action framework for youth development. Philadelphia, PA: Youth Development Strategies. Garst, B. A. (2010). From what to how: Targeting specific factors that influence outcomes. Journal of Extension, 48(6). Retrieved from https://joe.org/joe/2010december/comm1.php Garst, B. A., Baughman, S., Whittington, A., & Gagnon, R. J. (2015). Influences of resident camp experiences on career choice: A case study of female alumnae. Research in Outdoor Education, 13(1), 59–82.



197

Garst, B. A., Browne, L., & Bialeschki, M. D. (2011). Youth development and the camp experience. New Directions for Youth Development, 130, 73–88. https://doi.org/10.1002/yd.398 Garst, B. A., & Bruce, F. (2003). Identifying 4-H camping outcomes using a standardized evaluation process across multiple 4-H educational centers. Journal of Extension, 41(3). Retrieved from https://joe.org/joe/2003june/rb2.php Garst, B. A., Franz, N. K., Baughman, S., Smith, C., & Peters, B. (2009). “Growing without limitations:” Transformation among young adult camp staff. Journal of Youth Development, 4(1). Retrieved from http://www.nae4ha.com/assets/documents/JYD_090401final.pdf Garst, B. A., & Ozier, L. (2015). Enhancing youth outcomes and organizational practices through a camp based reading program. Journal of Experiential Education, 38, 324–338. https://doi. org/10.1177/1053825915578914 Gillard, A., & Watts, C. E. (2013). Program features and developmental experiences at a camp for youth with cancer. Children and Youth Services Review, 35, 890–898. https://doi. org/10.1016/j.childyouth.2013.02.017 Greenberg, M. T., Weissberg, R. P., O’Brien, M. U., Zins, J. E., Fredericks, L., Resnik, H., & Elias, M. J. (2003). Enhancing school-based prevention and youth development through coordinated social, emotional, and academic learning. American Psychologist, 58, 466. https://doi.org/10.1037/0003-066x.58.6-7.466 Henderson, K. A., Bialeschki, M. D., & James, P. A. (2007). Overview of camp research. Child and Adolescent Psychiatric Clinics of North America, 16, 755–767. https://doi.org/10.1016/j. chc.2007.05.010 Henderson, K. A., Bialeschki, M. D., Scanlin, M. M., Thurber, C., Whitaker, L. S., & Marsh, P. E. (2007). Components of camp experiences for positive youth development. Journal of Youth Development, 1(3), 1–12. https://doi.org/10.1177/0192513x07301428 Henderson, K. A., Oakleaf, L., & Bialeschki, M. D. (2009). Questions raised in exploring spiritual growth and camp experiences. Leisure/Loisir, 33(1), 179–195. https://doi.org/10.1080/149 27713.2009.9651435 Henderson, K. A., Thurber, C. A., Scanlin, M., & Bialeschki, M. D. (2007). Sorting out what makes a difference: Youth development findings from camp settings. Search Institute Insights & Evidence, 4(1), 1–11. Henderson, K. A., Thurber, C. A., Whitaker, L. S., Bialeschki, M. D., & Scanlin, M. M. (2006). Development and application of a camper growth index for youth. Journal of Experiential Education, 29(1), 1–17. https://doi.org/10.1177/105382590602900103 Hendricks, P. A. (1998). Targeting life skills model. Retrieved from Iowa State University Extension website: http://www.extension.iastate.edu/4h/explore/lifeskills Hickerson, B., & Henderson, K. A. (2013). Opportunities for promoting youth physical activity: An examination of youth summer camps. Journal of Physical Activity and Health, 11, 199– 205. https://doi.org10.1123/jpah.2011-0263 Hill, E., Gagnon, R. J., Ramsing, R., Goff, J., & Kennedy, B. (2015). Measuring the impact of family diabetes camp: Using self-determination theory. Therapeutic Recreation Journal, 40, 310–325. https://doi.org/10.18666/trj-2015-v49-i4-6308 Hough, M., & Browne, L. (2009, February). Connecting camp mechanisms to camper outcomes: A case for program theory. Paper presented at the annual meeting of the American Camp Association Conference, Orlando, Florida. Johnson, S. K., Goldman, J. A., Garey, A. I., Britner, P. A., & Weaver, S. E. (2011). Emerging adults’ identity exploration: Illustrations from inside the “camp bubble.” Journal of Adolescent Research, 26, 258–295. https://doi.org/10.1177/0743558410376832 Jun, J., & Kyle, G. T. (2011). Understanding the role of identity in the constraint negotiation process. Leisure Sciences, 33, 309–331. https://doi.org/10.1080/01490400.2011.583157 Klatt, J., & Taylor-Powell, E. (2005, October). Synthesis of literature relative to retrospective pretest http://www.ejorel.com/

198


design. Paper presented at the 2005 Joint CES/AEA Conference, Toronto. Lerner, R. M. (2004). Liberty: Thriving and civic engagement among American youth. Thousand Oaks, CA: Sage. https://doi.org/10.4135/9781452233581 Lerner, R. M., Almerigi, J. B., Theokas, C., & Lerner, J. V. (2005). Positive youth development. Journal of Early Adolescence, 25(1), 10–16. https://doi.org/10.1177/0272431604273211 Mainieri, T. L., & Anderson, D. M. (2015). Exploring the “black box” of programming: Applying systematic implementation evaluation to a structured camp curriculum. Journal of Experiential Education, 38, 144–161. https://doi.org/10.1177/1053825914524056 Marshall, J., Higginbotham, B., Harris, V., & Lee, T. (2007). Assessing program outcomes: Rationale and benefits of posttest-then-retrospective-pretest designs. Journal of Youth Development: Bridging Research and Practice, 2. Retrieved from http://www.nae4ha.com/ assets/documents/JYD_070201_final.pdf McLeroy, K. R., Bibeau, D., Steckler, A., & Glanz, K. (1988). An ecological perspective on health promotion programs. Health Education & Behavior, 15, 351–377. https://doi. org/10.1177/109019818801500401 Merryman, M., Mezei, A., Bush, J. A., & Weinstein, M. (2012). The effects of a summer camp experience on factors of resilience in at-risk youth. The Open Journal of Occupational Therapy, 1(1), 1–33. https://doi.org/10.15453/2168-6408.1016 Mezirow, J. (2000). The Jossey-Bass higher and adult education series: Learning as transformation: Critical perspectives on a theory in progress. San Francisco, CA: Jossey-Bass. Pawson, R., & Tilley, N. (1997). Realistic evaluation. Los Angeles, CA: Sage. https://doi. org/10.4135/9781412950596.n474 Raidl, M., Johnson, S., Gardiner, K., Denham, M., Spain, K., Lanting, R., . . . Barron, K. (2004). Use retrospective surveys to obtain complete data sets and measure impact in Extension programs. Journal of Extension, 42(2). Retrieved from http://www.joe.org/joe/2004april/ rb2.php Ramsing, R., & Sibthorp, J. (2008). The role of autonomy support in summer camp programs: Preparing youth for productive behaviors. Journal of Park and Recreation Administration, 26(2), 61–77. Roark, M. F., Ellis, G. D., Wells, M. S., & Gillard, A. (2010). Measuring relationships between camp staff and camper developmental outcomes: An application of self-determination theory. Journal of Park and Recreation Administration, 28(3), 79–94. Roth, J., & Brooks-Gunn, J. (2003). Youth development programs: Risk, prevention, and policy. Journal of Adolescent Health, 32, 170–182. https://doi.org/10.1016/S1054139X(02)00421-4 Ryan, R., & Deci, E. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi. org/10.1037/0003-066x.55.1.68 Schmalz, D. L., Kerstetter, D. L., & Kleiber, D. A. (2011). An evaluation of developmental outcomes at a free-choice oriented girls summer camp. Journal of Outdoor Recreation, Education, and Leadership, 3(1). https://doi.org/10.7768/1948-5123.1069 Sibthorp, J., Browne, L., & Bialeschki, M. D. (2010). Problem solving and camp connectedness: Two new measures for the ACA Youth Outcomes Battery. Research in Outdoor Education, 10, 1–12. Sibthorp, J., Paisley, K., Gookin, J., & Ward, P. (2007). Addressing response shift bias: Examining the use of retrospective pretests in recreation research and evaluation. Journal of Leisure Research, 39, 295–315. Thurber, C., Scanlin, M., Scheuler, L., & Henderson, K. (2007). Youth development outcomes



199

of the camp experience: Evidence for multidimensional growth. Journal of Youth and Adolescence, 36, 241–254. https://doi.org/10.1007/s10964-006-9142-6 Ungar, M. (2012, September/October). Camps help make children resilient. Camping Magazine, 2012, 22–27. U. S. Department of Agriculture. (2001). Prepared and engaged youth: National 4-H Impact Assessment Project. Washington, DC: Author. Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Bulletin, 20, 158–177. https://doi.org/10.1037/h0074428 World Health Organization. (1997). Life skills education for children and adolescents in schools. Retrieved from http://whqlibdoc.who.int/hq/1994/WHO_MNH_PSF_93.7A_ Rev.2.pdf Yohalem, N., & Wilson-Ahlstrom, A. (2010). Inside the black box: Assessing and improving quality in youth programs. American Journal of Community Psychology, 45, 350–357. https://doi.org/10.1007/s10464-010-9311-3 Zarrett, N., & Lerner, R. M. (2008). Ways to promote the positive development of children and youth. Child Trends, 11, 1-5. https://doi.org/10.1037/e456902008-001
