Abstract
Objectives. We investigated prospective associations among assets (e.g., family communication), which research has shown to protect youths from risk behavior, and successful transition to early adulthood (STEA).
Methods. We included participants (n = 651) aged 18 years and older at study wave 5 (2007–2008) of the Youth Asset Study, in the Oklahoma City, Oklahoma, metro area, in the analyses. We categorized 14 assets into individual-, family-, or community-level groups. We included asset groups assessed at wave 1 (2003–2004) in linear regression analyses to predict STEA 4 years later at wave 5.
Results. Individual- and community-level assets significantly (P < .05) predicted STEA 4 years later and the associations were generally linear, indicating that the more assets participants possessed the better the STEA outcome. There was a gender interaction for family-level assets suggesting that family-level assets were significant predictors of STEA for males but not for females.
Conclusions. Public health programming should focus on community- and family-level youth assets as well as individual-level youth assets to promote positive health outcomes in early adulthood.
Youth development programming addresses youth risk reduction through strategies to strengthen “youth assets,” which represent skills, competencies, relationships, and opportunities that help youths to overcome challenges and successfully transition through developmental stages into adulthood.1–3 Considerable research supports the belief that programs focusing on building and strengthening youth assets (e.g., positive peer role models, family communication, school connectedness) help protect youths from engaging in risk behaviors such as tobacco, alcohol, and drug use; violence; and early initiation of sexual intercourse.4–10
The majority of youth-development research has focused on the avoidance of risk behaviors as the outcomes of interest. A much smaller body of research has found that youth assets are also associated with positive outcomes such as school achievement, exercise, seat belt use, and bicycle helmet use.11,12 More importantly, it is believed that assets not only protect youths from engaging in risk behaviors and promote positive health behaviors and outcomes, but also increase the odds that a person will mature into a healthy, functional adult.13,14 Therefore, the primary goal of this study was to examine prospective associations between youth assets and successful transition to early adulthood (STEA).
Early or emerging adulthood (18–25 years of age) has been described as a relatively new and distinct period of the life course made possible by industrialization, cultural changes such as delays in marriage and parenting from the early to the late 20s, and the often lengthy pursuit of undergraduate and graduate college degrees.15 Emerging adulthood generally represents a time when individuals are entering their physical, cognitive, and behavioral prime. It is also a volitional period of time between adolescence and full adulthood during which young people explore various social roles and pathways to adulthood.15 In light of this perspective, it would be useful to identify factors associated with successful transition into this period of life.
A review by Eccles et al.16 concluded that there is evidence that youth assets are associated with early adult outcomes although the definition of assets as well as the markers of success for the emerging adulthood outcomes were widely defined. The research is largely based on resiliency studies in which the focus is on youths who are at risk for negative health outcomes because of significant childhood adversity. For example, one of the first studies focusing on STEA was conducted by Werner et al. who followed a cohort from birth to adulthood.17,18 They found that indicators of resiliency (e.g., better reasoning, achievement-oriented attitude, close bond with caregiver, having several close friends) were related to overall success in life and satisfaction with work, family, and social life, and psychological well-being of adults in their mid-30s. The results of another resiliency study indicated that planfulness, emotional autonomy, and nonparent adult support were factors associated with competent functioning in emerging adulthood.10 Burt and Paysnick19 summarized resiliency research noting that past peer and current young adult relationships as well as personal factors such as cognitive ability and self-control predict STEA.
Youth assets have been grouped into domains such as physical, intellectual, psychological, and social.14 Another approach to organizing and understanding asset and health outcome research is through the socioecological model, which suggests that health behaviors and outcomes are influenced by multiple levels or pathways of change that range from individual to policy factors.20 For example, it is possible that youths who avoid risk behaviors and eventually make a successful transition to early adulthood may greatly benefit not only from individual assets such as responsible decision-making but also from family assets, such as warm and caring relationships with parents, as well as community assets, such as a strong association with school.
In summary, there is a need for further investigation in the youth development field that does not fall under the rubric of resiliency or risk behavior–prevention research. In particular, research that attempts to identify specific assets that may be associated with specific aspects of STEA is warranted.16 We examined prospective associations between specific youth assets and a multidimensional STEA outcome in a randomly selected cohort of racially/ethnically diverse youths who were not assumed to be at risk attributable to significant childhood adversity.
METHODS
Data were from the Youth Asset Study (YAS). The YAS was a 5-wave longitudinal study of youth–parent dyads living in the Oklahoma City, Oklahoma, metropolitan area. The study was funded by the Centers for Disease Control and Prevention to prospectively investigate relationships among youth assets, sexual behaviors, and other health-related youth behaviors.
Sampling and Data Collection
We stratified census tracts by income and race/ethnicity by using 2000 Census data21 and then randomly selected with the goal of obtaining a diverse community-based study population. We included 20 census tracts in the study. We conducted door-to-door canvassing within the selected census tracts to obtain the baseline sample of youths and parents. One youth (aged 12–17 years at wave 1) and 1 parent from each consenting household participated in the study.22
We collected data from youth–parent pairs by using computer-assisted personal or self-interviewing procedures conducted in their homes by 2-person interviewing teams. We collected 5 waves of data annually from the participants beginning with the baseline survey conducted in 2003–2004 and concluding in 2007–2008. A total of 1111 youth–parent pairs agreed to participate in the study with a response rate of 61% that we calculated with the formula suggested by the American Association for Public Opinion Research.23 The retention rate across all 5 waves (i.e., valid completed youth interview for all 5 waves) was 89% (986 of 1111).
Demographic variables of interest included race/ethnicity, gender, youth’s age at wave 5 (categorized into 18–19 years vs 20–22 years), school status at wave 5, parental education at wave 1, and family structure. We categorized family structure over the course of the study as 2-parent households, 1-parent households, or inconsistent households, which were defined as youths residing in both 1- and 2-parent households over the 5 data collection periods or being “independent” from parents before age 18 years.
Measures
Youth asset groups.
We assessed 17 youth assets via multi-item constructs with established validity and adequate reliability.3 We analyzed 14 youth assets (Cronbach reliability α in parentheses) for this study; 4 assets operated at the individual level, 4 at the family level, and 6 at the community level. The individual-level assets were responsible choices (0.67), educational aspirations for the future (0.61), religiosity (0.86), and good health practices (i.e., exercise, nutrition; 0.78). The family-level assets were family communication (0.74), relationship with mother (0.86), relationship with father (0.92), and parental monitoring (0.83). The community-level assets were nonparental adult role models (0.55), community involvement (0.82), peer role models (0.77), use of time (i.e., sports; other group activity such as reading club, honor society, various specific interest groups; 0.74), use of time (i.e., religion; 0.58), and school connectedness (0.72). We did not include 3 individual-level assets—general aspirations for the future, general self-confidence, and cultural respect—in the analysis because of their low variability and high prevalence.
We conceptualized and developed the asset constructs on the basis of literature reviews, previous research, and psychometric testing.3,24,25 The complete asset survey as well as its psychometric properties has been previously published.3 We summed and divided items representing each asset by the number of items to create a score ranging from 1 (almost never or strongly disagree) to 4 (almost always or strongly agree).
Successful transition to early adulthood.
We assessed STEA via 4 items adapted from the research literature. Each item assessed 1 dimension of STEA: general health, social support, life satisfaction, and financial health. We standardized the responses to each item so that each item contributed equally (5 points each) to the STEA score, which ranged from 4 (poor) to 20 (best).
We assessed general health26 via the item, “In general, would you say your health is excellent, very good, good, fair, or poor?” (possible responses: 5 = excellent; 4 = very good; 3 = good; 2 = fair; 1 = poor).
We assessed social health27 via the item, “There is someone in your life with whom you can share your innermost thoughts and feelings” (possible responses: 4 = strongly agree; 3 = agree; 2 = disagree; 1 = strongly disagree).
We assessed life satisfaction28 via the item, “Using a scale of 1–7, please indicate your agreement with the following item: I am satisfied with my life” (possible responses: 7 = strongly agree; 6 = agree; 5 = slightly agree; 4 = neither agree nor disagree; 3 = slightly disagree; 2 = disagree; 1 = strongly disagree).
We assessed financial health29 via the item, “How much responsibility do you take for the following: earning your own living?” (possible responses: 5 = I am completely responsible for this all of the time; 4 = I do this most of the time; 3 = I do this half the time; 2 = Somebody else does this for me most of the time; 1 = Somebody else does this for me all the time).
Statistical Analysis
We performed analysis of variance to compare mean STEA across asset group levels. We conducted the Jonckheere–Terpstra test to assess the linear trend of the mean STEA across ordinal asset group levels. We included youth asset groups assessed at wave 1 in linear regression analyses, controlling for the demographic variables, to predict wave-5 STEA assessed 4 years later. We compared youths with 0, 1, or 2 assets (individual-level assets) or youths with 0 or 1 asset (family- and community-level assets) with youths with more assets to determine if a higher number of assets was associated with a greater mean STEA outcome.
We assessed all 2-way interactions between demographic variables and the asset groups with the F-statistic from type III sums of squares. We assessed model assumptions with residual analysis (linearity, constant variance, normality). Significant interactions resulted in stratification by the demographic variable involved in the interaction or inclusion of an interaction term in the model. We performed analysis with SAS for Windows version 9.2 (SAS Institute, Cary, NC). We used an α level of .05 for all analyses including interactions.
RESULTS
We included youth participants aged 18 years or older at wave 5 of the study in the analyses. Of the 653 youths who met this definition, 2 did not answer all the STEA questions and were excluded from the study. The mean age of the 651 youths included in the study at wave 5 was 19.2 years (±1.1; range = 18–22 years); 55% of the participants were female; and the sample’s race/ethnicity was 41% non-Hispanic White, 26% non-Hispanic Black, 25% Hispanic, and 8% other. Fifty-five percent of the youths were currently in school. Parental education was reported as 15% for both parents with less than a high-school degree, 56% for at least 1 parent with a high-school degree, and 30% for at least 1 parent with a college degree. Family structure was reported by the youths as 57% living in 2-parent households, 25% in 1-parent households, and 18% in inconsistent households. At wave 5, 26% of the youths reported they did not live with a parent, guardian, or other supervising adult.
The mean STEA score was 15.5 (SD = 2.3; range = 7–20) suggesting that the participants typically had a fairly high STEA outcome at wave 5. The mean STEA score was not significantly different across youth race and gender, school status, family structure, or parental educational level. However, younger youths (aged 18–19 years) had a significantly lower (P = .012) mean STEA compared with older youths (aged 20–22 years; 15.3 vs 15.8). The group with the lowest STEA score was Hispanic youths (mean STEA = 15.2 ±2.4) and the highest STEA scores were for youths aged 20 to 22 years (mean STEA = 15.8 ±2.2).
As shown in Table 1, the percentage of youths with 4 assets from any asset group was greatest for the individual-level asset group with 45% of the youths having all 4 individual-level assets. By contrast, just 27% of youths possessed 4 family-level assets and only 20% of youths possessed 4 community-level assets. A similar percentage of youths (17% to 19%) reported having just 1 or 2 of the assets from any asset group.
TABLE 1—
Number and Percentage of Youths Possessing Assets and Mean Successful Transition to Early Adulthood Outcome by Number of Assets Within Each Asset Level: Youth Asset Study; Oklahoma City, OK, Metro Area; 2003–2008
| Youth Assets | No. (%) | STEA Outcome, Mean (SD) | ANOVA (Jonckheere–Terpstra) |
| Individual-level assets | |||
| 0–2 | 121 (19) | 14.8 (2.5) | < 0.0001 (< 0.0001) |
| 3 | 235 (36) | 15.3 (2.2) | |
| 4 | 295 (45) | 16.0 (2.3) | |
| Family-level assets | 0.0049 (0.0067) | ||
| 0–1 | 112 (17) | 15.1 (2.4) | |
| 2 | 139 (21) | 15.3 (2.4) | |
| 3 | 225 (35) | 15.6 (2.4) | |
| 4 | 175 (27) | 15.8 (2.2) | |
| Community-level assets | < 0.0001 (< 0.0001) | ||
| 0–1 | 112 (17) | 14.9 (2.6) | |
| 2 | 121 (19) | 15.1 (2.4) | |
| 3 | 169 (26) | 15.4 (2.2) | |
| 4 | 133 (20) | 15.9 (2.3) | |
| 5–6 | 116 (18) | 16.3 (2.0) |
Note. ANOVA = analysis of variance; STEA = successful transition to early adulthood. The sample size was n = 651.
The mean STEA score differed across levels of all 3 asset groups before we controlled for demographic variables (Table 1). In fact, there was a significant linear trend for all 3 asset groups. The mean STEA scores increased as the number of assets possessed by youths also increased.
There were no significant interactions between the individual-level asset group and the demographic variables. Compared with youths with 0 to 2 assets, youths with 3 (P = .044) or 4 (P < .001) individual-level assets had significantly higher mean STEA scores after we controlled for the demographic variables (Table 2; Figure 1).
TABLE 2—
Linear Regression Analyses of Assets on Successful Transition to Early Adulthood by Asset Group: Youth Asset Study; Oklahoma City, OK, Metro Area; 2003–2008
| Assets | b (95% CI) |
|
Individual-level assetsa | |
| 0–2 vs 3 assets | 0.53* (0.01, 1.04) |
| 0–2 vs 4 assets | 1.17* (0.66, 1.67) |
|
Family-level assets | |
| Malesb | |
| 0–1 vs 2 assets | 0.72 (–0.18, 1.63) |
| 0–1 vs 3 assets | 1.29* (0.47, 2.12) |
| 0–1 vs 4 assets | 1.68* (0.80, 2.56) |
| Females,b Non-Hispanic White | |
| 0–1 vs 2 assets | 1.42* (0.05, 2.80) |
| 0–1 vs 3 assets | 0.25 (–0.92, 1.42) |
| 0–1 vs 4 assets | 0.67 (–0.55, 1.88) |
| Females,b Non-Hispanic Black | |
| 0–1 vs 2 assets | –1.12 (–2.50, 0.26) |
| 0–1 vs 3 assets | 0.41 (–0.88, 1.70) |
| 0–1 vs 4 assets | 0.79 (–0.77, 2.35) |
| Females,b Non-Hispanic other | |
| 0–1 vs 2 assets | –0.32 (–2.64, 2.00) |
| 0–1 vs 3 assets | –0.46 (–2.86, 1.94) |
| 0–1 vs 4 assets | –2.33 (–4.91, 0.25) |
| Females,b Hispanic | |
| 0–1 vs 2 assets | –0.85 (–2.25, 0.54) |
| 0–1 vs 3 assets | –0.94 (–2.29, 0.42) |
| 0–1 vs 4 assets | –0.79 (–2.17, 0.59) |
|
Community-level assetsa | |
| Aged 18–19 y | |
| 0–1 vs 2 assets | –0.11 (–0.91, 0.68) |
| 0–1 vs 3 assets | –0.06 (–0.79, 0.68) |
| 0–1 vs 4 assets | 0.27 (–0.49, 1.04) |
| 0–1 vs 5–6 assets | 0.99* (0.19, 1.79) |
| Aged 20–22 y | |
| 0–1 vs 2 assets | 0.49 (–0.40, 1.39) |
| 0–1 vs 3 assets | 1.28* (0.45, 2.12) |
| 0–1 vs 4 assets | 2.22* (1.29, 3.15) |
| 0–1 vs 5–6 assets | 2.22* (1.27, 3.18) |
Note. CI = confidence interval; STEA = successful transition to early adulthood. The sample size was n = 651.
Adjusted for youth age, race/ethnicity, and gender; parental education; family structure; and school enrollment.
Adjusted for youth age and race/ethnicity, parental education, family structure, and school enrollment.
*P < .05.
FIGURE 1—
Predicted mean successful transition to early adulthood (STEA) score at wave 5 and number assessed at wave 1 for (a) individual-level assets and (b) community-level assets: Youth Asset Study; Oklahoma City, OK, metro area; 2003–2008.
There were significant interactions between youth gender (P = .013) and youth race/ethnicity (P = .017) and the family-level asset group. We therefore stratified data by gender. After we controlled for demographic variables, male youths with 3 (P = .002) or 4 (P < .001) family-level assets had significantly higher mean STEA scores than did male youths with 0 or 1 assets (Table 2; Figure 2). For females, the relationship between the family-level assets and the STEA outcome varied significantly (P = .025) by race/ethnicity (Figure 2). White females with 2 family-level assets had significantly higher (P = .042) STEA scores than did White females with 0 or 1 assets.
FIGURE 2—
Predicted mean successful transition to early adulthood (STEA) score at wave 5 and number of family-level assets assessed at wave 1 among (a) males and (b) females: Youth Asset Study; Oklahoma City, OK, metro area; 2003–2008.
There was a significant interaction between youth age and the community-level asset group. For youths aged 18 to 19 years at wave 5, the mean STEA score was significantly greater (P = .016) for those with 5 or 6 community-level assets compared with those with 0 or 1 assets (Table 2; Figure 1). For youths aged 20 to 22 years at wave 5, the mean STEA score was significantly greater for those with 3 (P = .003), 4 (P < .001), or 5 or 6 community-level assets (P < .001) compared with youths with 0 or 1 asset.
DISCUSSION
In this longitudinal study, we investigated associations between 14 assets and STEA in a community-based random sample of racially/ethnically diverse youths. We categorized youth assets into 1 of 3 pathways of behavioral change (individual, family, community).20 Assets, assessed at baseline when the youths were aged 14 to 18 years, significantly predicted STEA 4 years later when the participants were aged 18 to 22 years. In general, the more assets the youths possessed the stronger their STEA outcome was 4 years later. Individual-level and community-level assets were generally consistent predictors of STEA. The family-level assets were equally strong predictors of STEA for males; however, there were inconsistent findings for females with the results varying by race/ethnicity.
These results agree with resiliency research, which found that individuals exposed to significant trauma in their childhood were more likely to demonstrate a variety of positive outcomes in adulthood (e.g., satisfaction with work and social life, psychological well-being, competent functioning) if they possessed certain factors or assets (e.g., close bond with caregiver, nonparental adult support) in their youth.10,17,18 The results also support the belief that youths from the general population (i.e., youths not necessarily experiencing significant childhood adversity) who possess assets not only are more likely to avoid participation in risk behaviors but that they are also more likely to mature into healthy functional adults.13,14 In this study, young adults who possessed as few as 2 assets in their youth were more likely to report better general health and more positive levels of social support, life satisfaction, and financial health in early adulthood. Moreover, there appeared to be an additive or cumulative effect in which progressively more assets (up to as many as 6) were associated with an increasingly stronger STEA outcome. This additive effect was also reported in a study of assets and youth sexual risk behaviors.30
The study’s results are noteworthy because of the effect of the community- and family-level assets compared with the individual-level assets. Health promotion programs that have the goal of changing youth outcomes typically intervene exclusively with youths by implementing strategies that, for example, increase knowledge and improve attitudes and behavior. It is far less common for programming to also include parents and even more rare to focus on community factors that may improve youth outcomes. The results of this study suggest that comprehensive interventions that focus on family-level factors (e.g., family communication, parent–child relationships) and community-level factors (e.g., nonparental adult role models, community involvement, school connectedness) as well as individual-level assets (e.g., responsible choices, educational aspirations for the future) may be the most effective at promoting STEA. The results support a central tenet of the ecological model that suggests that successful health promotion programming should intervene at various levels of influence.20
Another perspective is provided by developmental psychologists who have suggested that the challenge of adolescence is to develop a sense of self as competent and that this is essential in gaining autonomy later in adolescence.31 They believe this is most likely achieved while maintaining a sense of connection with significant others. The findings of the present study confirm the importance of not only individual-level assets, but also connections to both family and community that form the support for the adolescent who is moving toward autonomy and a successful transition into adulthood.
There was a notable exception to the notion that assets from various levels of influence positively influence STEA and that more assets lead to a better STEA. The family-level assets appeared to have little association with STEA for females in contrast to having a strong association with STEA for all males. This suggests there may be something about family dynamics that were revealed by the 4 family-level assets (family communication, parental monitoring, relationship with mother, relationship with father) that is gender-specific. Perhaps for female youths, the family-level asset–STEA association is complicated by cultural values, norms, and expectations in regard to parent–daughter relationships. It is difficult to believe that for females family-level assets just do not matter in regard to STEA. Analyses of these data involving other outcomes found that family-level assets are protective from risk behaviors by female youths such as alcohol use, initiation of sexual intercourse, and pregnancy before age 20 years.32–34 Additional research is necessary to further explore these potentially complex relationships.
Finally, the study revealed an interesting age effect for the community-level assets. The results indicated stronger and more consistent associations between assets and the STEA outcome for participants who were aged 20 to 22 years at study conclusion compared with participants who were aged 18 or 19 years at study conclusion. Community-level assets, such as nonparental adult role models, community involvement, and school connectedness, are perhaps even more important for older youths and young adults as they transition into early adulthood.
Limitations of the study included the measurement of the STEA outcome. We assessed each of the 4 STEA dimensions by using a single item that was adapted from an established multi-item scale that assessed 1 of the STEA dimensions. Although each item appears to have reasonable face validity, the validity of the items as well as the overall STEA construct is unknown and could not be assessed in the study. Another limitation was that the study drew from the general population and therefore an unknown percentage of the youth sample may have experienced significant childhood adversity (however defined). Finally, the STEA questions were assessed only at waves 4 and 5 of the study and therefore STEA status at earlier waves could not be considered in the analyses.
This study is the first to our knowledge to investigate prospective associations among youth assets and successful transition to early adulthood. The results indicate that programs designed to build and strengthen youth assets may also promote positive health outcomes in early adulthood. Contrary to adolescent health promotion projects that deliver programming exclusively to youths, these results indicate that programs that also focus on community- and family-level asset-building strategies may be more efficacious.
Results from this study as well as other research suggests that policymakers and program funders should consider emphasizing and supporting community-based asset programming that involves parents, schools, and community leaders and that creates opportunities for youths to engage in activities that strengthen specific assets, which in turn will reduce youth risk behaviors and promote positive outcomes.4–10 Families, schools, and community leaders can partner to identify and implement asset-building programming that best meets the needs of youths. Time and financial resources are limited and, therefore, asset-based health promotion programming, which considerable research suggests prevents multiple risk behaviors as well as promotes positive health behaviors and outcomes, may be a more efficient as well as effective strategy for healthy youth development.
Acknowledgments
The Youth Asset Study was supported by funding from the Centers for Disease Control and Prevention grant 5 U01 DP000132 and the Inasmuch Foundation.
Note. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or Inasmuch Foundation.
Human Participant Protection
This study underwent and received full review and approval from the institutional review board of the University of Oklahoma Health Sciences Center.
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