The street is considered an atypical context of development that involves a series of physical and psychological risks for the youth inserted in it. The street-involved youth growing up in conditions of low family income, lack of housing, failure in school, familial abuse and neglect, violence and perceived public stigma (Asante, 2015; Petersen, Koller, Motti-Stefanidi, & Verma, 2016). This, in turn, the trajectory of exposure to several adversities increases health-risk behavior such as consumption of psychoactive substances, sexual risk behavior, suicide, infractions acts ( Embleton , Lee, Gunn, Ayuku, & Braitstein, 2016). Recent studies reveal a sustained effort to improve the positive youth development despite difficult life situations, taking into consideration the strengths, emotions and other psychological processes, as well as effective policies and interventions that promote youth flowering (Petersen et al., 2016). Thus, even in situations of extreme stress, it is important to consider personal and social resources, which function as protective actions and can generate positive developmental results (Masten, 2014).

Few studies have included positive development measures for street-involved youth. In this literature, some authors have highlighted subjective well-being (SWB) as an important indicator of mental health (Castaños-Cervantes & Sánchez-Sosa, 2015), psychosocial adjustment ( Morais, Koller, & Raffaelli, 2010) and related to the support network (peers, families and institutions) and engaging in leisure and recreational activities (Lima & Morais, 2016a). SWB is composed of different dimensions that are positive (PA) and negative affects (NA) and life satisfaction (LS) (Diener, 1984). Affects are emotional responses of pleasure (e.g., feeling contented) and displeasure (e.g., feeling humiliated) to everyday events. Satisfaction is relative to the cognitive judgment of global life and its various domains (e.g., family, school) from comparisons between a person's life circumstances and a pattern chosen by one.

The literature recommends that SWB measurement is performed by self-report measures that evaluate each of its components (PA, NA, and LS) to the detriment of global evaluations of happiness (Diener, Suh, Lucas, & Smith, 1999). Some results on the SWB of street-involved youth indicated that this population faced adversities with health implications such as presenting anxious and depressive symptoms associated with low levels of well-being (Castaños-Cervantes & Sánchez-Sosa, 2015). While other authors have shown that young people are satisfied with their lives and PA rather than NA more often despite they have experienced several and intense negative life events (Lima & Morais, 2016b; Morais et al., 2010).

The findings mentioned above were predominantly based on variable-centered analysis and present statistical results-oriented by the variables that do not characterize the individuality of the sample. This approach had important contributions to the theoretical and empirical construction of the SWB; however, it limited mapping of the relations between the observed variables. In contrast, the person-centered analysis considers that the individual is an organized whole with an individual functioning system. In their applications, variables are used to construct profiles grouping the individuals by their scores through statistical analysis, with cluster analysis as commonly used. The variables included in such analysis have no meaning in themselves. They are components of the standard in analysis and interpreted simultaneously about the other variables (Bergman & Magnusson, 1997).

The person-centered analysis guides this study, suitable approach to field studies of development focusing on individuals' lives over time (Hart, Atkins, & Fegley, 2003). Regarding longitudinal studies with vulnerable youth, there is a shortage in the literature, implying limits to understanding development in a risk context. Observations that extend over some time make it possible to capture what is maintained or modified in people's lives. This chronology in the research facilitates the identification of the interaction processes of the personal and contextual systems implied in the individuals' responses to life events, as well as their progress across the course of their lives (Lerner, 2015). The target population of this study is difficult to access and has a high circulation among different environments, characteristics that make it difficult to follow the cases (Morais, Koller, & Raffaelli, 2012). Theoretical and methodological efforts are needed to contribute to a broader range of developmental processes for street-involved youth.

Given the above, this study sought to contribute to the complex understanding of the development of street-involved youth. It addressed the individual (SWB), contextual (street, family, institution and life events) dimensions and subsequent patterns of youth behavior (health-risk behavior) under adverse conditions. The objective of this study was to longitudinally characterize SWB profiles of street-involved youth, verifying how different groups differ regarding sociodemographic characteristics; besides the stressful events and health-risk behaviors, which are used in this study as a risk variable and indicator of psychosocial adjustment, respectively.

Stressful events are adverse life events that alter the environment and incite tension, affecting individuals' responses and that make youth susceptible to negative developmental outcomes (Masten & Garmezy, 1985) and health-risk behaviors are severe behavioral and mental health-related problems (Asante, 2015). Thus, we tested the hypothesis that youth who feel more PA and LS have lower risk indicators, greater adjustment, and social support. Participants were grouped into clusters based on different SWB levels and described based on sociodemographic characteristics (age, gender, relationships with the street, family, and institution), SWB (LS, PA, and NA), stressful events (number and impact) and health-risk behaviors (suicidality, sexual risk, and drug use). Afterward, the different groups were compared to SWB, stressful events and health-risk behaviors in Times 1, 2 and 3, with a minimum of six months interval between each.

Method

It is a longitudinal study (three-time points with six months interval between each data collect), of descriptive and analytical design. It was proposed a person-centered analysis while understanding that the constituent elements of SWB interact in an integrated way in people was made. The data are from a more extensive study with street-involved youth from three Brazilian cities (Fortaleza, Porto Alegre, Salvador). The measures were based on published scales and had already been adapted and piloted with young Brazilians who lived in institutional environments and in the street.

Contextualization

The sample of Brazilian street-involved youth of this study were recruited in different settings. Specifically, we briefly described data collection spaces. Institutional shelter (or "homeless shelter") is a protective measure that consists of the removal of the child or adolescent from his / her family of origin, when some (or several) situations of violation of rights occur, such as when the child/teenager is a victim of neglect, physical or sexual violence. In this case, the child/adolescent —from a court order—starts living in an institution that should be as similar as possible to a residence, for a period that can extend for a maximum of two years ¹ . At the shelter, the children/adolescents perform all activities necessary for their survival and their routine (food, sleep, hygiene, school, leisure, etc.).

Differently, in open institutions young people have the freedom to walk through these spaces, for example, using them only a day per week or for three days in different shifts, depending on the rules of the institution and the young person's desire. In this case, no court order has required the child/adolescent to remain in that space. However, in the case of non-compliance with rules and regulations, young people are deprived of the use of these services, usually for 72 hours. These spaces are like pass houses, where young people find protection, and can be sent to an institutional shelter, to their families or returning to the streets. Regarding the third data collection space, the street, there was only a small portion of the sample (from Fortaleza) that was properly in the streets, sleeping in porches, bus terminals and frequenting the city center and beaches, a reality that explained the change in the profile of this population.

Participants

In Time 1, 113 youth who had to live on the street for at least six months of the first data collection were recruited in institutions shelter (80%), open institutions serving street-involved youth (17%) and street (3%). The participants were recruited in Fortaleza (n = 45, 39.8%), Salvador (n = 40, 35.4%), and Porto Alegre (n = 28, 24.8%). There were no significant differences between cities for sex and age. The following shows the number of respondents in each data collect Time: 81 (72%) young people were interviewed in T2 and 68 (61%) in T3. The analytical sample of this article consisted of 104 young people who completed all measures related to SWB (PA, NA, and LS) in Time 1. These young ones ranged from 9 to 18 years (M = 14.22 years, SD = 2.4) and the majority (82%) were males and (91%) non-white.

Instruments

Participant’s Form. A set of 11 questions for sociodemographic categorization of participants based on the Life Experience Interview (Raffaelli, Koller, & Morais, 2007) was created. In this article, we analyzed the items that dealt with the sociodemographic data: age, sex, relations with the institution (a type of institution attended), street and family (contact intensity - weak, medium and strong).

Stressful Events (Number and Impact). It is a checklist of 22 events that could have occurred during the last six months (e.g., relocation, return home, death threat, and the death of a friend or family member). The frequency of occurrence of the events was used to calculate the number of events. For those events occurred, participants rated each one as impact (5 items; 1- nothing stressful to 5 - totally stressful). The average of the total impact is achieved by dividing the sum of the assigned impact values by the events experienced by the total number of events with a valid impact.

Health-Risk Behaviors. Formed from a combination of three indicators (suicidality, sexual risk, and drug use). For its construction, the following steps were conducted: 1) the transformation of each adjustment indicator into a standardized score (z-score); and 2) the sum of the normalized scores of all indicators (suicide rate, sexual risk, and drug use).

Suicidality Index. Computed from items on suicide ideation and attempted suicide, being ranked in 0 (no ideation and attempts), 1 (thought about suicide but had no attempt), 2 (attempted once) and 3 (attempted two or more times).

Sexual Risk Index. Composed of the sum of four indicators (already had sex, sexual intercourse before the age of 13, two or more partners in the last 6 months, no condom at the last sexual intercourse). Values ranged from 0 (no risk) to 4 (presence of all sexual risk behaviors).

Drugs Use. Drug use was measured by the frequency of consumption of seven drugs (licit and illicit: alcohol, cigarettes, marijuana, cocaine, crack and others) in the last month, with values from 0 (did not consume) to 7 (consumed all types drugs).

Positive and Negative Affect. The measurement of affect was obtained by the Positive and Negative Affect Schedule for Children (PANAS-C, Watson, Clark, & Tellegen, 1988; Laurent et al., 1999) adapted by Raffaelli et al. (2007). It is a two-factor scale (Positive Affect, 17 items, alpha = 0.86; Negative Affect, 17 items, alpha = 0.89) of 34 items classified in five points (1 - not at all to 5 - very much). Feeling participatory, determined, strong and courageous are examples of PA. While feeling sad, humiliated, worried, and nervous are examples of items of NA.

Life Satisfaction. Composed of five items (1 - strongly disagree to 5 - strongly agree) of the Life Satisfaction Scale (Diener, Emmons, Larsen, & Griffin, 1985) adapted by Koller et al. (1996) (alpha = 0.72). One example is the following questions: "Is your life close to your ideal?" and "Are you satisfied with your life?”.

Data Collect Procedures

The composition of the sample performed three stages. In the first stage, the potential recruitment places identified included social assistance institutions that provided services to street-involved youth. In the second stage, places identified as regular meeting places for young people were selected for the recruitment of participants. In the third stage, the research team was inserted in these spaces, beginning the ecological engagement with six-month duration. This approach privileged the insertion of the researcher into the research context, enabling the researcher-participant interaction regularly of time (Koller, Morais, & Paludo, 2016). Participants were eligible if they had current or recent street experience (e.g., sleeping, working, or “hanging out” on the street) or engage in illicit or risky street-based activities (e.g., drug trafficking, sexual exploitation). After selection and acceptance, the participants completed a set of measures in three times (T1, T2, and T3) with an interval of six months between each one. The instruments were applied, on average, in two individual 35-minute meetings, conducted by the research assistants duly trained in the joint study protocol.

Data Analysis Procedures

We conducted a hierarchical cluster analysis to identify groups of street-involved youth with different SWB profiles at Time 1. The Ward method with squared Euclidean distance as a measure of proximity was used. The score for each variable was standardized (z-score), before the analysis, to minimize the effects of different scales between variables. The selection of the clusters based on an inspection of the dendrogram branches and the coherence of the resulting clusters through the analysis of variance, being verified the existence of significant variability between the clusters in relation to the components of SWB. For the longitudinal characterization of the clusters, descriptive statistics (mean, standard deviation, frequency, and percentage) and analysis of comparison (ANOVA) between clusters were carried out, considering the differentiation of the groups in the other variables investigated over time (T1, T2, and T3). The data were analyzed using the Statistical Package for Social Sciences - SPSS (version 19), considering a level of significance of p<0.05.

Ethical aspects

The Ethics Committee from the institution of origin of the authors (Protocol 2011023) approved the study, and we followed all procedures necessary for the research with youth in situations of social vulnerability, suitably.

Results

Profiles Identification

The cluster analysis performed with the three components of the SWB (LS, PA, and NA) indicated three distinct SWB profiles of young people in the street situation. As depicted in Figure 1, clusters include an average SWB (n = 56; 49.6%) characterized by moderate LS, PA, and NA. A positive SWB (n = 21; 18.6%) defined by high LS and PA and low NA; and a negative SWB (n = 27; 23.9%) distinguished by low LS and PA and moderate NA. The values of SWB variables correspond to normalized means and are described in Table 2.

As for the sociodemographic characterization, as shown in Table 1, clusters do not differ significantly in gender. On the topic of the age, the follow-up test (LSD) verified that the positive SWB is composed of younger children/adolescents than the negative SWB. Regarding the relationship with the streets, all clusters had medium to strong contact intensity, and there are no significant differences between the groups. The clusters differed significantly for the variables’ intensity of contact with family [F (2) = 1.14, p <0.05, Cohen’s d = 1.20] and type of institution (open institution) [F (2) = 3.6, p <0.05, Cohen’s d = 0.68]. The post hoc analysis (LSD) identified that positive SWB was made up of young people with stronger family ties than the other groups. Participants who composed the average SWB and positive SWB clusters used the open institutions more frequently than those of the negative SWB.

In order to verify the distinction between the three clusters regarding the components of SWB, comparisons were made (ANOVA). The results of the analysis of variance highlighted significant differences between clusters for LS [F (2) = 18.37, p < 0.001, Cohen’s d = 1.53], PA [F (2) = 92.54, p < 0.001, Cohen’s d = 2.13] and NA [F (2) = 22.8, p < 0.001, Cohen’s d = 1.37]. The post hoc test (LSD) identified that all clusters differed significantly from each other for SWB variables. Table 2 indicates the differences by subscripts. It is also shown that the ANOVA values and the large effect size observed in the analyses suggested that the PA highlighted the strongest element of dissimilarity in the clusters.

Longitudinal characterization of profiles on the SWB, Stressful Events and Health-Risk Behaviors

Table 2 presents the descriptive analysis and comparisons between groups for SWB variables, stressful events and health-risk behaviors in Times 1, 2 and 3. In T1, besides the clusters differ in relation to SWB as previously described in the identification of the profiles, there were significant differences for the health-risk behaviors [F (2) = 6.24, p < 0.01, Cohen’s d = 0.96] and sexual risk [F (2) = 8.73, p < 0.001, Cohen’s d = 1.08]. Follow-up tests (LSD) indicated that the positive SWB group included participants with lower levels of health-risk behaviors and sexual risk than the other groups, as well as suicidality lower than the negative SWB group.

At Time 2, clusters had significant differences for PA [F (2) = 12.65, p < 0.001, Cohen’s d = 1.56]. Analyzes with the LSD test indicated that the positive SWB group had higher mean PA than the other groups, as well as higher LS levels and lower NA levels than the average SWB group. In T3, there were significant differences between the clusters in the PA [F (2) = 5.32, p <0.01, Cohen’s d = 1.89], LS [F (2) = 4.62, p <0.01, Cohen’s d = 1.12] and health-risk behaviors [F (2) = 3.18, p < 0.05, Cohen’s d = 0.88]. The post hoc (LSD) test indicated that the negative SWB group had lower LS levels than the other groups, as well as higher health-risk behaviors and the impact of stressful events than positive SWB. This cluster still stood out for lower means of health-risk behaviors than the average SWB cluster. The different SWB profiles did not differ significantly in terms of the number of stressors and drug use at any time (T1, T2, and T3).

Discussion

SWB profiles of street-involved youth was characterized longitudinally, verifying how groups differ in relation to the sociodemographic characteristics; besides the stressful events and health-risk behaviors. The focus on the individual through the person-centered analysis allowed the identification of SWB typologies of this population. We found three groups: average SWB, positive SWB, and negative SWB. This approach showed distinct profiles of young people who tend to have different patterns of adaptation.

In general, the positive SWB was formed by predominantly male and younger people, whereas the negative SWB was composed of older adolescents with a higher percentage of girls, although the majority was boys. It was highlighted that positive SWB had the highest levels of SWB and the lowest levels of health-risk behaviors, while the negative SWB had the lowest levels of SWB and higher levels of health-risk behaviors. Almost half of the sample comprised the average SWB, which revealed that young people who, in their trajectories, experienced stressors and engaged in risky behaviors have a decrease in the level of well-being when compared to the normative youth population (Bandeira, Natividade, & Giacomoni, 2015).

Some studies have presented street-involved youth with worse indicators of physical (e.g., liver disease, HIV) and mental health (e.g., anxiety and depression) related to suicide, drug use and sexual risk (Embleton et al., 2016; Hills, Meyer-Weitz, & Asante, 2016). In this population, drug use was associated with sexual risk behavior, mainly having multiple sexual partners and unprotected sex (Cheng et al., 2016). In this positive focus study, taken together, the results indicate that the differences in SWB are linked to the simultaneous differences in health-risk behaviors, especially suicidality and sexual risk. That is, higher well-being rates indicate less involvement in disruptive behaviors. This confirms that the previous studies identify SWB as an important health indicator, while the well-being experience drives the young people to increase their personal goals and consequent healthy development (Antaramian, Huebner, Hills, & Valois, 2010). The promotion of SWB can, therefore, be an effective strategy in reducing the risks that seriously undermine the development.

According to the findings of this study, the three groups had the street as a significant development context. Even though it did not differentiate, positive SWB had slightly lower contact with the street, which suggests that these young people chose other insertion environments. It corroborates the results of this group with greater intensity of contact with the family and to have gone more frequently to open institutions, whether in search of temporary shelter or to participate in socio-educational projects. Such data may be related to the protective role played by institutions and the continuity of the affective ties in the family. In institutions, young people can establish relationships of trust with professionals and receive social support, either through professional or socio-educational activities (Rodarte et al., 2015). Institutions that work in formal and vocational education, as well as the provision of services to the family aiming at promoting family attachment, seem to be adequate measures related to well-being and developmentally healthy.

Consistent with previous studies, street-involved youth are in conditions of extreme vulnerability (Castaños-Cervantes & Sánchez-Sosa, 2016). The number and impact of stressful events showed young people experiencing poverty, violence and other circumstances conducive to behavioral problems. According to the cumulative risk model, the accumulation of these stressful events increases the likelihood of negative results (Haggerty, Sherrod, Garmezy, & Rutter, 2000). As observed in the results of this study, in T3, the negative SWB group evaluated the events as more stressful than the positive SWB, indicating that the combination over time of multiple negative events may exceed the effective response capacity in coping with the risk (as shown by the high levels of health-risk behaviors).

The overall results in this study supported the hypothesis that youth with high levels of well-being (PA and LS) have greater adjustment, greater social support, and lower impact of stressful events (no differences were found to a number of stressful events). These findings indicated that the opportunity to maintenance and enhancement of personal resources and social support can be help youth to develop survival and resilience strategies (Cénat, Derivois, Hébert, Amédée, & Karray, 2018). Finally, it is concluded that despite the risk context, many participants feel PA and LS, though it is alerted to the frequency of stressful events and health-risk behaviors, including increasing these vulnerabilities over the ages. The most vulnerable young people have experienced intense stressors, reduced social support, and lower well-being. It is highlighted that engagement in health behaviors (e.g., substance use attitudes), recreational and educational activities, and the development and maintenance of family and institutional ties may favor SWB levels.

This study had some limitations. Because it was a longitudinal study, participants had not been interviewed in the three times, making it difficult to identify different patterns of functioning related to the variables investigated in the subsequent year. This was due to the high circulation of young people through different spaces, and it was difficult to resume contact, even though there were methodologies for the case follow-up. For example, contact phones became non-existent due to the high flow of phone number exchanges, young ones who went to another city to escape death threats by traffickers and an adolescent was murdered for a drug debt. Despite these restrictions, we evaluated that this study had good sample retention compared to other studies with a street-involved youth (Neiva-Silva, 2008). In addition, the sample of this study comprises a low number of young girls, interfering in analysis stratified by sex. However, it must consider that such limitation is a characteristic of studies with this population since once on the street-involved girls are more vulnerable to become engaged in activities related to sexual exploitation, so the access to them has become more difficult.

Despite these limitations, this is a precursor study in Brazil in the longitudinal investigation of the SWB of young people in street situation. The results show the existence of different profiles of street-involved youth, confirming the initial hypothesis of SWB as an important indicator of better patterns of adjustment and development and maintenance of protective relationships. This information can be useful for interventions and public policies of attention to the youth population in street situation. Future research could verify whether different SWB profiles, stressful events, and patterns of health-risk behaviors remain in adulthood or if other positive variables (e.g., sense of life) explain why some street-involved youth experience greater well-being than others.

Acknowledgements

The authors thank the National Council for Scientific and Technological Development (CNPq); Coordination for the Improvement of Higher Education Personnel (CAPES); and Cearense Foundation to Support Scientific and Technological Development (FUNCAP) for the funding received for this study.

References

Notes:

* Research article. This article resulted from the doctoral thesis of the first author.

¹ The maximum time of institutionalization (two years) is provided for in Brazil Law 12.010/2009. However, in practice, this time tends to exceed the limit of two years, due to the difficulties of working to reinsert the family (in the family of origin, extensive or substitute).

Author notes:

^a Corresponding author. Email: rebecafflima@gmail.com

Additional information:

How to cite: Lima, R. F. F., & Morais, N. A. (2019). Subjective well-being profiles of street-involved youth: a longitudinal analysis based on clusters. Universitas Psychologica, 18(2). https://doi.org/10.11144/Javeriana.upsy18-2.swbp

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