Developing norms for the California resilience youth development module: internal assets and school resources subscales.
Resilience and other positive psychological constructs are gaining
attention among school psychologists. Theoretically, external assets
(e.g., support from caring adults, participation in meaningful
activities) help to meet youths' basic developmental needs, which,
in turn, promote the growth of internal assets (e.g., ability to problem
solve, empathize with others). Despite this knowledge, existing measures
of resilience-building assets are underutilized. With the aim of
facilitating broader access to and use of one strengths-based assessment
tool, the current article attempts to further examine and increase the
applicability of the Resilience Youth Development Module (RYDM) of the
California Healthy Kids Survey (CHKS) for practicing school
psychologists. The authors provide normative data on the internal assets
and school-focused external resources subscales of the RYDM, while
examining grade, ethnicity, and gender patterns.
KEYWORDS: resilience, assessment, strength-based, California Healthy Kids Survey
Resilience (Personality trait) (Research)
Furlong, Michael J.
Ritchey, Kristin M.
O'Brennan, Lindsey M.
|Publication:||Name: The California School Psychologist Publisher: California Association of School Psychologists Audience: Academic Format: Magazine/Journal Subject: Psychology and mental health Copyright: COPYRIGHT 2009 California Association of School Psychologists ISSN: 1087-3414|
|Issue:||Date: Annual, 2009 Source Volume: 14|
|Topic:||Event Code: 310 Science & research|
|Geographic:||Geographic Scope: California Geographic Code: 1U9CA California|
There is continuing emphasis in California on accountability and
outcomes within school systems. Federal mandates, such as the No Child
Left Behind and Race to the Top, also raise expectations for school
officials to collect and use data to assess student needs and evaluate
program implementation and outcomes. Concurrently, there is a
substantial initiative among public health and youth development
professionals to encourage schools to create campus conditions that
foster caring relationships and the connectedness of students with
adults in their schools (e.g., Centers for Disease Control and
Prevention, 2009). In response to these state and federal policies, the
California Department of Education (CDE) in conjunction with
WestEd's Health and Human Development Program developed the
California Healthy Kids Survey (CHKS; California Healthy
Kids Survey, 2009; WestEd, 2009a). The CHKS is a school focused questionnaire that measures risk and resilience factors through student self-reports. It has been used in research examining factors influencing smoking and drinking behaviors (Kim & McCarthy, 2006), teenage pregnancy (McDonell, Limber, & Connor-Goodbey, 2007), asthma among Hispanic and Asian students (Davis, Kreutzer, Lipsett, King, & Shaikh, 2006), and risk factors associated with school violence (Furlong, Morrison, Austin, Huh-Kim, & Skager, 2001).
One component of the CHKS is the Resilience Youth Development Module (RYDM; Constantine & Benard, 2001; Constantine, Benard, & Diaz, 1999; WestEd, 2009b), which is designed to measure protective factors among youth in terms of their internal assets and external resources (see www.wested. org/chks/pdf/rydm_presentation.pdf for an overview of the RYDM). Prior research provided evidence supportive of the RYDM's psychometric properties (Hanson & Kim, 2007) and shown that at the school level its subscales are positively associated with higher Academic Performance Index (API) rankings (Hanson & Austin, 2002). However, given that the RYDM was developed as a population-based survey, there is limited evidence supporting its use and interpretation at the student level considering individual differences. Therefore, the aim of this article is to further examine the RYDM's psychometric properties and provide normative information in support of its use as a social-emotional assessment within the practice of school psychology. Such information would allow school psychologists to integrate the RYDM into common assessment contexts. Furthermore, because the RYDM is based in sound research and theory (Benard, 2004), it offers school psychologists a viable, cost-effective measure with which to assess factors associated with youth resilience, a critical component of strength-based assessment (Jimerson, Sharkey, Nyborg, & Furlong, 2004).
Resilience Youth Development Module as a Strength-Based Measure
Given the resource constraints of California's current economic climate, expanding psychological assessment to include positive experiences and characteristics may not be considered a top priority. Fortunately, California already collects such information as part of the biennial CHKS survey, with the RYDM element including items that assess internal assets (personal strengths) and external resources (developmental supports and opportunities). In the RYDM, resilience is theorized to be "an inborn developmental wisdom that naturally motivates individuals to meet their human needs for love, belonging, respect, identity, power, mastery, challenge, and meaning" (WestEd, 2002, p. 2; see also Benard, 2004). Theoretically, external resources (e.g., support from teacher, involvement in school-based activities) help to meet youths' basic developmental needs, which, in turn, promote the enhancement of internal assets (e.g., ability to problem solve and empathize with others). Ideally, these internal assets contribute to healthy social and academic outcomes among youth (Benard, 2004; Benard & Slade, 2009). Prior research suggests that the combintorial effects of youth possessing innate resilience characteristics with protective environmental resources is associated with reductions in health-risk behaviors such as alcohol use, tobacco use, drug abuse, aggressive behavior, juvenile delinquency, and academic disengagement (Garmezy, 1993; Gilman, Huebner, & Furlong, 2009; Hanson & Austin, 2002; Jimerson et al., 2004; Kirby & Fraser, 1997; Tran & Furlong, 2004).
The CHKS is administered to students in grades 7, 9, and 11 at least every two years (there is a different elementary version administered to fifth graders that is not examined in this article). After each survey administration, WestEd provides standard reports that provide useful overviews of district trends related to substance use, school safety, and student resilience (see www.wested.org/cs/chks/print/docs/ chksbsearchhtml, or www.wested.org/hks for district reports). However, these reports have some limitations because information about individual students cannot be gleaned due to the anonymous nature of the survey. However, CHKS raw data files with no unique identifiers are available to individual counties, districts, and even schools. By drawing on these data, it is possible for local education agencies to compare their students' response patterns to students throughout California (WestEd, 2006). However, this is rarely done since it is unlikely that most school psychologists have access to the resources needed to develop local normative information. Consequently, a useful extension of the RYDM would be to develop information about response patterns that would allow school psychologists to use it to assess individual students.
Purpose of this Study
Although prior research has examined the general psychometric properties of the RYDM (Hanson & Kim, 2007), the applicability of this scale for practitioner use with individual students is unavailable. With the ultimate goal of facilitating broader access to and use of this strength-based instrument, the focus of this article is to examine the applicability of the RYDM for practicing school psychologists in California. Given the widespread use of the CHKS, it is our aim to provide normative data on the internal assets and the school-focused external resources subscales of the RYDM, including grade, ethnicity, and gender patterns.
The sample for this study comes from CHKS data collected during the 2006-2007 and 2007-2008 school years from across schools in California. Students included in this study were from districts that administered the CHKS Core Module A, as required of all districts biennially, and the RYDM Module B, which is discretionary. When the CHKS data are processed, the responses of participants are subjected to seven response consistency and reliability checks (WestEd, Jerry Bailey, personal communication, May 11, 2008). This case rejection identifier is included with the raw database obtained and students whose responses did not meet the case validity criteria were not included in this study. Additional selection criteria included valid responses to all items of the RYDM internal assets and external resources items and another measure of school connectedness described later in this article.
The final sample included 141,004 students (55% female, 45% male) in grades 7 (34%), 9 (34%), and 11 (32%). These students were from 50 of the 58 California counties with representation from the following geographic regions: Inland Southern (25%), Northern (17%), San Diego (16%), Los Angeles (15%), San Francisco (14%), and Central (13%).
The CHKS asks students to indicate if they identify with racial-ethnic group categories commonly used in research (Alaskan Native/Native American, Asian/Pacific Islander, African American/Black, White/Not Hispanic, Hispanic, and Other). Students who selected only one ethnic group where placed into the corresponding category and students who selected two or three groups were placed into a multiethnic category. Students who selected four or more ethnic groups were not included in the analysis because they comprised a small subgroup and most of these youths claimed membership in all six ethnic groups, a plausible but unlikely status. The ethnic distribution of the sample was follows: 37% Hispanic, 30% White, 13% multi-racial, 12% African American, 4% Asian, 2% Native Hawaiian Pacific Islander, and 1% Alaskan Native or American Indian.
California Healthy Kids Survey (CHKS). The CHKS includes a mandatory core module administered to all students that focuses on health behaviors and experiences (WestEd, 2006). Core Module A includes sections about diet and exercise, violence, perceptions of safety, harassment and bullying, and the use of alcohol and other drugs. Five additional modules make up the total CHKS measure, one of which is Module B, the RYDM examined in this article.
Resilience Youth Development Module (RYDM). The full RYDM contains 56 items that were designed to measure internal assets (personal strengths) and external resources (protective factors), all of which have been linked to positive developmental outcomes (Benard & Slade, 2009). There is an elementary and secondary version, however, the focus of this article is on the secondary version. This analysis uses the internal assets items and the subset of external resources items that focus on student perceptions of the school context.
The original 18 internal assets items were developed to measure six core constructs based on Benard's resilience model (Benard & Slade, 2009). As the RYDM has been used in California and additional analyses completed, clarifications to its underlying structure and content have been reported. In a detailed analysis, Hanson and Kim (2007) found that the number of items could be reduced due to differential item functioning (across racial-ethnic groups or by gender), inconsistent factor loading patterns, or items cross-loading across factors. Therefore, this study uses the 12 internal asset items identified by Hanson and Kim (2007) that measure four areas of personal strength: self-efficacy, empathy, problem solving, and self-awareness. These four subscales are also reported as a combined Internal Assets score. These are items 1-12 in Appendix A.
RYDM external assets items measure students' perceptions of caring relationships, high expectations, and opportunities for meaningful participation across school, peer, home, and community domains. Given this article's focus on students' functioning in school, we examined the 9 external resource items about the school environment. Hanson and Kim (2007) conducted several factor analyses and found that the 6 items from the Caring Relationship and High Expectation subscales combined to form one factor that they called "School Support" with the 3 Meaningful Participation items holding together in a separate factor. This study focuses on the School Support and School Meaningful Participation subscales (Items 13-21 in Appendix A).
School connectedness. Within the core CHKS module, 5 items assess School Connectedness, a measure originally developed for the National Longitudinal Study of Adolescent Health (Resnick et al., 1997). Numerous studies have shown that this measure of students' beliefs about how much adults at school care about them is associated with lower levels of substance use and higher levels of positive health and academic outcomes (Whitlock, 2006). We included the School Connectedness scale (Items 22-26 in Appendix A) in the present study to examine correlations among the RYDM subscales, as well as provide concurrent validity information for the School Support portion of the RYDM.
The RYDM was administered as part of the biennial CHKS survey. This full CHKS anonymous survey takes approximately 50 minutes to complete and is administered by school personnel during a regular class session. Either passive or active consent was used, at the discretion of each school district. District and school coordinators oversaw survey planning and implementation. School personnel administered the survey using a scrip provided by WestEd (see www.wested.org/chks/pdf/chks_mou_new_ 0809.pdf for the memorandum of understanding that each district completed prior to administering the CHKS). Students' responses were made on scanable response sheets. For this analysis, the raw SPSS data were obtained from WestEd that contained all responses gathered during the 2006-2007 and 20072008 school years.
The overall goal of the analysis was to examine the distribution of student responses to the 26 items assessing Internal Assets (4 subscales: self-efficacy, empathy, problem solving, and self-awareness) and School Resources (3 subscales: School Support, Meaningful Participation, and School Connectedness). Student responses were examined for possible differences by gender, racial-ethnic group, and grade level. Due to the large sample sizes, it was anticipated that even small differences would be significant, even when reducing the experiment-wide p-level; hence, the results focus on the overall effect size of the differences. In addition, to aid interpretation we examined the reliability of each subscale and correlations among subscales provided. Finally, a norm table was produced.
Multivariate analysis. We conducted a 2 (gender) x 6 (racial-ethnic group) x 3 (grade level) Multivariate Analysis of Variance with the 7 Internal Assets and School Resources subscales (the Total Internal Asset score was not included in this analysis). As expected with the substantial sample size, all three main effects were significant: grade, Wilks' Lamda = .993, F = 70.45 (14, 281912), p < .001; gender, Wilks' Lamda = .997, F = 472.37 (7, 140956), p < .001; and ethnicity, Wilks' Lamda = .951, F = 169.23 (42, 661146), p < .001. In addition, all four interaction terms were significant: grade x gender, Wilks' Lamda = .999, F = 7.84 (14, 281912), p < .001; grade x ethnicity, Wilks' Lamda = .997, F = 4.84 (84, 863306),p < .001; gender x ethnicity, Wilks' Lamda = .996, F = 13.53 (42, 661146),p < .001; and grade x gender x ethnicity, Wilks' Lamda = .999, F = 1.44 (84, 863306), p < .001. Although these tests were statistically significant, each of the four interaction effects accounted for less than 0.1% of the variance across the RYDM subscales. Among the three main effects, the amount of variance explained for grade, gender, and ethnicity was 0.3%, 2.3%, and 0.8%, respectively. Given the low amount of variance attributable to grade level, the following analyses separately examined the univariate relations of RYDM response patterns across ethnicities for males and females.
RYDMpatterns. Tables 1 and 2 show the pattern of means and standard deviations for the 4 Internal Asset subscales (including the combined Total Assets score) and the 3 School Resources subscales by ethnicity for males and females, respectively. A one-way ANOVA compared mean scores across ethnic groups and, as shown, the F-ratios for all 8 tests were significant for both males and females. However, the amount of variance attributed to differences in ethnic groups was small, ranging from 0.4% (problem-solving) to 1.7% (self-efficacy) for males and from 0.2% (self awareness) to 2.2% (school connectedness) for females. Although detailed post-hoc comparison information cannot be reported due to space constraints, the general pattern that emerged for both males and females was that the Hispanic students tended to have the lowest subscale scores and White students tended to have the highest subscale scores.
RYDM psychometric properties. Tables 1 and 2 also show the internal consistency (alpha coefficients) for each of the RYDM subscales by gender. The results show moderate to high reliabilities for both males (range .75-.93) and females (range .69-.91). As would be expected, the Total Internal Assets and the School Support scores, both of which have the most items, had the highest alpha coefficients. The correlations among of the RYDM scores are reported in Table 3 for males and females.
RYDM norms. Given the pattern of findings reported previously, distributions were developed for each of the RYDM subscales by converting raw scores into percentile ranks for males and females. However, as show in Table 4, the differences between the scores by gender are minimal.
A substantial body of research supports the relation between positive developmental outcomes and students' positive character assets while attending a school with caring and supportive personnel (Appleton, Christenson, & Furlong, 2008, Centers for Disease Control, 2009). This study examined these related constructs as measured by the RYDM. The work of Hanson and Kim (2007) had previously examined the RYDM item bias, and verified that the factor structure of these scales held across racial-ethnic groups. Using their derived factor structure, the current paper further examined the pattern of Internal Assets and External School Resources among a sample of California students in grades 7, 9, and 11. We found that the variation of RYDM scores attributable to grade and ethnicity were small, less than 1%, however, there was more variance attributable to gender (2.3%). Most of the variation in scores was related to individual differences across students. This result, and the finding that the reliabilities of the scores were moderate to high for both males and females, support using the RYDM as part of socialemotional assessments with individual students. To this end, Table 4 provided normative data based on the responses of more than 141,000 California students. Although we conclude that the results lend support for school psychologists to include the 26 RYDM items examined in this study in their assessment resources, we provide some additional context to better inform this practice.
Integrating the RYDM Positivity Measures into Social-Emotional Assessments
In evaluating the use of RYDM as a social-emotional assessment, it is instructive for school psychologists to consider if assessing only pathology and disability is sufficient to inform effective treatment and to evaluate mental health and functioning. Historically, psychologists have viewed mental health as one broad category of functioning, but some have suggested that mental health involves not one but two broad domains. When considering assessments, is it worthwhile to assess components of well-being? Is it possible to completely shift and focus resources on measures of thriving and optimal development? These questions are potentially important given research suggesting that preventive interventions should consider risk, protective, and other environmental factors associated with mental health symptoms (Tomb & Hunter 2004). The RYDM was developed to assess aspects of a youth's positive social-emotional condition and may provide a cost-effective resource with which to blend assessments of wellness and psychopathological functioning, thus capturing the full range of human functioning (Dowdy, Furlong, Eklund, Saeki, & Ritchey, in press; Huebner, 2004; Joseph & Linley, 2006; Seligman & Csikszentmihalyi, 2000). When used with individual students, the RYDM appears to have a role as part of the social-emotional portion of a referral assessment plan. Other applications could include being used as a pretest-posttest evaluation of a discrete service, a school benchmarking assessment of students' flourishing administered periodically throughout the year, or as part of a multigating assessment coordinated with other more detailed resilience scales such as ClassMaps (Doll et al., 2009; LeClair, Doll,
Osborn, & Jones, 2009).
Although this study was unique in that it drew upon a substantial sample of California students, it was limited in that the sample consisted only of 7th, 9th, and 11th graders. Only a small percentage of the variation of students' responses was due to grade level, but future research should examine response patterns across grades 7-12. In addition, these data are cross-sectional, so they do not provide information about any possible developmental trends that would be useful to know about when using the RYDM with individual students. A related consideration is that the short- and long-term stability of the RYDM scores is unknown and future research needs to examine this issue. Finally, the full range of information about the RYDM's various validities is not yet developed. We do note, however, that the School Connectedness scale has been used in hundreds of research studies (Whitlock, 2006). The correlations of .48 (females) and .50 (males) between School Connectedness and School Supports provide concurrent validity evidence for this RYDM element.
The 2009 list of Newsweek's selection of America's top 1500 high schools included Hillsdale High in San Mateo County. Of note is that when the RYDM responses at this high school were compared to other county high schools, it was found that the Hillsdale students reported higher levels of school resources (Caring Relationships, 12% higher; High Expectations, 13% higher; and Meaningful Participation, 6% higher) (WestEd, Sean Slade, personal communication June 12, 2009). It is possible that the experience of Hillsdale High School is one that can be replicated in schools throughout California. First, by systematically monitoring students' perceptions of their school via the CHKS biennial survey to keep school personnel and community members informed about the students' perception of their school's climate. District and school policies and practices can be informed using the biennial RYDM survey results in conjunction with its use to evaluate districts' youth development services. Second, school psychologists can also contribute by integrating the RYDM into the psychological assessments of individual students. By better understanding the strengths and needs of specific students related to their internal assets (self-efficacy, problem-solving, empathy, and awareness) and school resources (supports, meaningful participation, and connectedness), school psychologists can implement support services, as recommended by Benard and Slade (2009) for high-risk students that are linked directly to school-wide youth development efforts.
California Healthy Kids Survey Resilience Youth Development Module
Note. For electronic copies and other technical support, e-mail: firstname.lastname@example.org
RYDM Student Internal Assets
Directions: How true do you feel that these statements are about you personally? (1 = Not at All True, 2 = A Little True, 3 = Pretty Much True, 4 = Very Much True)
1. I can work with someone who has different opinions than mine.
2. I can work out my problems.
3. I can do most things if I try.
4. There are many things that I do well.
5. I feel bad when someone gets their feelings hurt.
6. I try to understand what other people go through.
7. I try to understand how other people feel and think.
8. When I need help, I find someone to talk with.
9. I try to work out problems by talking or writing about them.
10. There is a purpose to my life.
11. I understand my moods and feelings.
12. I understand why I do what I do.
RYDM School Supports (Caring Relationships and High Expectation combined)
At my school, there is a teacher or some other adult...
(1 = Not at All True, 2 = A Little True, 3 = Pretty Much True, 4 = Very Much True)
13. who really cares about me.
14. who tells me when I do a good job.
15. who notices when I'm not there.
16. who always wants me to do my best.
17. who listens to me when I have something to say.
18. who believes that I will be a success.
RYDM School Meaningful Participation
At school ... (1 = Not at All True, 2 = A Little True, 3 = Pretty Much True, 4 = Very Much True)
19. I do interesting activities.
20. I help decide things like class activities or rules.
21. I do things that make a difference.
ADD Health School Connectedness Scale (included in the CHKS)
How strongly do you agree or disagree with the following statements about your school?
(1 = Strongly Disagree, 2 = Disagree, 3 = Neither Disagree Nor Agree, 4 = Agree, 5 = Strongly Agree)
22. I feel close to people at this school.
23. I am happy to be at this school.
24. I feel like I am part of this school.
25. The teachers at this school treat students fairly.
26. I feel safe in my school.
Internal Asset items dropped based on analysis by Hanson and Kim (2007) (rationale for dropping item in parentheses)
I have goals and plans for the future. (item functioned differently for Mexican American and Chinese Americans)
I plan to graduate from high school. (only item left from original scale)
I plan to go to college or some other school after high school. (item functioned differently for
I know where to go for help with a problem. (item functioned differently for males and females) I enjoy working together with other students my age. (cross loadings in factor analysis) I stand up for myself without putting others down. (cross loadings in factor analysis)
Appleton, J., Christenson, S., & Furlong, M.J. (2008). Student engagement with school: Critical conceptual and methodological issues of the construct. Psychology in the Schools, 45, 369-386.
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Constantine, N.A., & Benard, B. (2001). California Healthy Kids Survey Resilience Assessment Module: Technical report. Berkeley, CA: Public Health Institute.
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Send correspondence to Michael Furlong, PhD, University of California, Gevirtz Graduate School of Education, Department of Counseling, Clinical, and School Psychology, Santa Barbara, CA 93106. Email: email@example.com. For more information about the California Healthy Kids Survey and the Resilience Youth Development Module, see www.wested/org/hks
Michael J. Furlong
Kristin M. Ritchey
Lindsey M. O'Brennan
University of California Santa Barbara
TABLE 1: Males: Means and Standard Deviations for School-Focused Resilience Youth Development Module (RYDM) Scales and the School Connectedness Scaleby Genderand Ethnicity for Students Attending Traditional Schools in Grades 7, 9, or 11. Ethnicity (Males) A.A/ N.A. P.I. Black Asian RYDM Internal Assets Self-Efficacy 13.0 13.4 13.1 13.2 (range = 4-16) (3.3) (2.9) (2.8) (3.3) Empathy 9.0 9.7 9.6 9.1 (range = 3-12) (2.8) (2.5) (2.4) (2.9) Problem Solving 5.5 5.8 5.6 5.6 (range = 2-8) (2.1) (2.0) (1.9) (2.1) Self-Awareness 9.7 10.1 10.0 9.8 (range = 3-12) (2.7) (2.3) (2.7) (2.5) Total Internal Assets 37.2 39.1 38.2 37.9 (range 12-48) (9.5) (8.2) (8.0) (9.6) RYDM School Resources School Support 18.0 17.8 17.7 17.7 (range = 6-24) (4.6) (4.6) (4.2) (4.8) Meaningful Participation 7.1 7.1 6.8 7.0 (range = 3-12) (2.5) (2.5) (2.4) (2.5) ADD-Health School 17.0 17.3 17.6 16.2 Connectedness (4.7) (4.3) (4.1) (4.7) (range = 5-25) Sample Size 1,043 1,462 8,244 2,818 ANOVA Results Hispanic White M.E. F RYDM Internal Assets Self-Efficacy 12.8 13.7 13.4 189.85 (range = 4-16) (3.1) (2.6) (2.8) Empathy 8.9 9.6 9.4 150.56 (range = 3-12) (2.8) (2.5) (2.6) Problem Solving 5.4 5.7 5.6 44.74 (range = 2-8) (2.1) (2.0) (2.0) Self-Awareness 10.2 10.2 10.0 64.01 (range = 3-12) (2.3) (2.3) (2.3) Total Internal Assets 36.9 39.2 38.3 143.59 (range 12-48) (8.9) (7.8) (8.1) RYDM School Resources School Support 17.3 18.4 17.9 142.38 (range = 6-24) (4.5) (4.3) (4.4) Meaningful Participation 6.5 7.0 6.9 91.43 (range = 3-12) (2.5) (2.5) (2.4) ADD-Health School 16.9 18.0 17.4 153.22 Connectedness (4.3) (4.2) (4.2) (range = 5-25) Sample Size 23,068 19,653 7,701 ANOVA Results p (% var) a RYDM Internal Assets Self-Efficacy .001 .85 (range = 4-16) (1.7%) Empathy .001 .88 (range = 3-12) (1.4%) Problem Solving .004 .76 (range = 2-8) (0.4%) Self-Awareness .006 .84 (range = 3-12) (0.6%) Total Internal Assets .001 .93 (range 12-48) (1.3%) RYDM School Resources School Support .001 .89 (range = 6-24) (1.3%) Meaningful Participation .009 .75 (range = 3-12) (0.8%) ADD-Health School .001 .82 Connectedness (1.4%) (range = 5-25) Sample Size Note. A.A. = Alaskan Native-American Indian; N.A. = Native American; M.E. = Multi-Ethnic; Standard deviations are in parentheses. % var. is the percentage of variance on the analysis attributable to ethnicity. Degrees of freedom for each analysis was 6, 63982. TABLE 2: Females: Means and Standard Deviations for School-Focused Resilience youth Development (RYDM) Scales and the School Connected- nessScalebyGender andEthnicity forStudents Attending Traditional Schools in Grades 7,9, or 11. Ethnicity (Females) A.A/ N.A. P.I. Black Asian RYDM Internal Assets Self-Efficacy 13.1 13.2 13.1 13.4 (range = 4-16) (3.0) (2.7) (2.6) (2.8) Empathy 10.1 10.4 10.3 9.9 (range = 3-12) (2.3) (2.0) (2.0) (2.4) Problem Solving 6.3 6.4 6.3 6.2 (range = 2-8) (1.8) (1.7) (1.8) (1.8) Self-Awareness 9.8 10.0 9.9 10.2 (range = 3-12) (2.5) (2.2) (2.2) (2.3) Total Internal Assets 39.3 40.0 39.6 39.8 (range 12-48) (8.3) (7.2) (7.1) (7.8) RYDM School Resources School Support 18.5 18.3 18.6 18.2 (range = 6-24) (4.4) (4.3) (4.0) (4.5) Meaningful Participation 7.0 7.1 7.0 6.8 (range = 3-12) (2.5) (2.5) (2.4) (2.6) ADD-Health School 17.5 17.7 18.0 16.3 Connectedness (4.6) (4.0) (3.8) (4.4) (range = 5-25) Sample Size 855 1,556 9,175 3,314 Ethnicity (Females) ANOVA Results Hispanic White M.E. F RYDM Internal Assets Self-Efficacy 12.8 13.7 13.4 267.10 (range = 4-16) (2.8) (2.4) (2.6) Empathy 10.0 10.6 10.3 165.96 (range = 3-12) (2.2) (1.9) (2.1) Problem Solving 6.2 6.5 6.3 73.45 (range = 2-8) (1.8) (1.7) (1.8) Self-Awareness 9.9 10.1 9.9 30.29 (range = 3-12) (2.3) (2.2) (2.3) Total Internal Assets 38.8 40.9 39.8 160.66 (range 12-48) (7.7) (6.8) (7.2) RYDM School Resources School Support 18.0 19.2 18.6 198.36 (range = 6-24) (4.4) (4.1) (4.2) Meaningful Participation 6.4 7.2 7.0 258.10 (range = 3-12) (2.5) (2.5) (2.5) ADD-Health School 17.3 18.5 17.8 295.25 Connectedness (4.0) (4.0) (4.0) (range = 5-25) Sample Size 29,206 22,639 10,450 ANOVA Results p (% var) a RYDM Internal Assets Self-Efficacy .001 .82 (range = 4-16) (2.0%) Empathy .001 .85 (range = 3-12) (1.3%) Problem Solving .001 .69 (range = 2-8) (0.6%) Self-Awareness .001 .82 (range = 3-12) (0.2%) Total Internal Assets .001 .91 (range 12-48) (1.2%) RYDM School Resources School Support .001 .89 (range = 6-24) (1.5%) Meaningful Participation .001 .77 (range = 3-12) (2.0%) ADD-Health School .001 .81 Connectedness (2.2%) (range = 5-25) Sample Size Note. A.A. = Alaskan Native/American Indian; N.A. = Native American; M.E. = Multi-Ethnic; Standard deviations are in parentheses. % var. is the percentage of variance on the analysis attributable to ethnicity. Degrees of freedom for each analysis was 6, 77008. TABLE 3: Intercorrelations Among the California Healthy Kids Survey (CHKS) Resilience youth Development Module (RYDM) Internal Asset, School Resources, and School Connectedness Subscales. CHKS RYDM Subscales 1 2 3 4 5 6 7 1. Self-Efficacy -- .64 .60 .73 .89 .37 .34 2. Empathy .59 -- .66 .58 .85 .34 .33 3. Problem Solving .62 .58 -- .54 .81 .34 .37 4. Self-Awareness .65 .50 .54 -- .84 .35 .30 5. Total Internal Assets .88 .85 .81 .83 -- .41 .39 6. School Support .47 .31 .34 .33 .41 -- .47 7. Meaningful Participation .38 .29 .33 .31 .39 .47 -- 8. School Connectedness .31 .26 .27 .30 .35 .48 .41 CHKS RYDM Subscales 8 1. Self-Efficacy .32 2. Empathy .29 3. Problem Solving .27 4. Self-Awareness .31 5. Total Internal Assets .35 6. School Support .50 7. Meaningful Participation .39 8. School Connectedness -- Note. All correlations p < .01. Correlations for females below the diagonal and for males above the diagonal. TABLE 4: Raw Score and Percentile Equivalents for the California Healthy Kids Survey (CHKS) School-Focused Resilience youth Development (RYDM) Scales and the School Connectedness Scale by Gender for Students Attending Traditional Schools in Grades 7, 9, or 11. RYDM Internal Assets Self-Efficacy Empathy Problem Self- Assets Solving Awareness Total 90 16 16 12 12 8 8 12 12 48 48 80 16 16 12 12 8 8 12 12 47 47 70 15 16 12 12 8 7 12 12 45 44 60 15 15 12 11 7 6 11 12 43 41 50 14 14 11 10 7 6 11 11 41 39 40 13 13 10 9 6 5 10 10 39 36 30 12 12 9 8 6 4 9 9 36 35 20 11 11 9 7 5 4 8 8 34 32 10 10 9 7 6 4 2 7 6 30 27 % M F M F M F M F M F Self-EfficacyEmpathy Problem Self- Assets Solving Awareness Total RYDM School Resources ADD Health School Meaningful School Supports Participation Connectedness 90 24 24 10 10 23 22 90 80 22 22 9 9 21 21 80 70 20 21 8 8 20 20 70 60 19 20 7 7 19 19 60 50 18 18 7 7 18 18 50 40 17 17 6 6 17 17 40 30 15 16 5 5 16 16 30 20 13 14 4 4 15 14 20 10 11 12 3 3 12 12 10 % M F M F M F % School Meaningful School Supports Participat Connectedness
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