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. Author manuscript; available in PMC: 2025 Feb 8.
Published in final edited form as: Nurs Res. 2024 Feb 8;73(3):188–194. doi: 10.1097/NNR.0000000000000722

Mediation of Psychological Capital in Youth Experiencing Homelessness

Lynn Rew 1, Natasha Slesnick 2, Shelli Kesler 3, Hyekyun Rhee 4
PMCID: PMC11047266  NIHMSID: NIHMS1963753  PMID: 38652691

Abstract

Background:

Youth who experience homelessness engage in behaviors that place them at high risk for disease and injury. Despite their health-risk behaviors, these youth display psychological capital, positive attributes of hope, efficacy, resilience, and optimism that motivate them to engage in health-promoting behaviors such as safer sex. However, this array of positive psychological attributes has not been studied in this vulnerable population.

Objectives:

The specific aim of this analysis was to determine whether factors of psychological capital mediated the relationship between background risk factors (e.g., race/ethnicity, educational attainment, reason for being homeless, sexual abuse history, and HIV status) and outcomes of condom intention, safer sex behaviors, and life satisfaction among youth who participated in a longitudinal intervention study.

Methods:

Using a Solomon four-group design, 602 youth were recruited from drop-in centers in two large cities (Columbus, Ohio, and Austin, Texas) to participate in a brief intervention that included outcomes of enhanced communication skills, goal setting, safer sex behaviors, drug refusal skills, and life satisfaction. Using an autoregressive, cross-lagged, longitudinal mediation model, we tested the direct and indirect effects of background factors, psychological capital, and intervention outcomes. Models were tested for the intervention group alone and the total sample.

Results:

There were no significant direct or indirect effects of background factors on intervention outcomes among the intervention group, and the model fit was poor. There were also no significant mediating paths via factors of psychological capital and poor model fit for the combined group.

Discussion:

Findings provide important information about intrinsic strengths of youth experiencing homelessness and psychological capital as a significant construct for understanding health behaviors among disadvantaged and underserved youth. The lack of significant mediation effects may have been due, in part, to the lack of a robust measure of psychological capital. Further study with various background factors and outcomes would contribute further to our understanding of how best to support this population.

Keywords: efficacy, gratitude, homelessness, hope, mediation, optimism, psychological capital, resilience, youth

Youth experiencing homelessness (YEH) often engage in sexual behaviors that place them at risk for disease and injury. This risk increases when alcohol and other drugs are part of the profile (Asante et al., 2016; Nyamathi, 2012). Despite these risky aspects of everyday life for an estimated half-million youths in the U.S., there is growing evidence that they also exhibit positive attributes reflected in their health-promoting behaviors (Lightfoot et al., 2011) and life satisfaction (Rew et al., 2019). The study of YEH has been dominated by a deficit approach focusing on attributes and experiences that highlight their problems and shortcomings. It is well established that many YEH have experienced maltreatment within their families (Auerswald & Goldblatt, 2016), including parental substance use and neglect (Lightfoot et al., 2018,) and subsequently were likely to have been victimized on the street (Bender et al., 2017).

Indeed, YEHs are often disconnected from family members and report high levels of family conflict, lack of parental protection, chaos, and physical or sexual abuse (Ferguson, 2009; Tyler, 2006). Homelessness is considered an isolating experience, with many researchers concluding that a sizable number of those experiencing homelessness are lonely and feel shunned by society and family (Rew, 2002; Rokach, 2005), although the role of loneliness in the erosion of well-being is not well-understood (Perron et al., 2014). Researchers have found that social isolation and feelings of loneliness are related to increased vulnerability to health problems, physical and sexual abuse, neglect, sex trade, being abandoned, insecure attachments, and suicide (Kidd & Shahar, 2008). In contrast to the view of YEH as socially isolated and vulnerable to health problems, there is increasing evidence that they also have social connections to peers at work, school, and other organizations that protect them from health-risk behaviors (Brown et al., 2020; Lightfoot et al., 2018).

YEH also often face many educational challenges. Compared to stably housed youth, YEH have lower education attainment and achievement, which also contributes to the risk of experiencing homelessness later in adulthood (Morton et al., 2018). Obtaining employment has been marked as an essential goal for improving their quality of life and housing status (Kilian et al., 2012; Marshall et al., 2022). However, due to employment barriers (e.g., lack of identification and transportation, criminal history) and the need for financial security, YEH often turn to riskier forms of income generation such as survival sex, dealing drugs, panhandling, or theft that can have negative effects on their emotional and physical health (Ferguson et al., 2011). In addition, many YEH display psychological strengths such as hope and optimism that can contribute to their further educational and employment development (Cooley et al., 2019). An intervention to promote both internal and external feelings of empowerment has been found to enhance the networking skills of adults experiencing homelessness and improve their opportunities for “occupational engagement” (Lambdin-Pattavina et al., 2020, p. 280).

Recently, there has been a shift to viewing this vulnerable population from a more strengths-based approach. For example, using a participatory photovoice intervention guided by the positive youth development framework, Bender et al. (2017) found that YEH between 18 and 21 increased their social connectedness and resiliency. Social connectedness has been associated with subjective well-being in YEH (Barczyk et al., 2014). Similarly, Lightfoot et al. (2011) found that YEH who experienced social support exhibited few problem behaviors and were likely to set healthy goals and make healthy decisions. Another positive attribute—gratitude—has also been found to relate positively to life satisfaction in this population (Rew et al., 2019).

Positive attributes of hope, efficacy, resilience, and optimism comprise a construct known as psychological capital (PsyCap; Luthans et al., 2007). The construct of PsyCap originated from positive psychology and the study of employee behavior in organizational psychology. In contrast to the “disease model” of psychology and the concept of “learned helplessness” stimulated by the works of Maier and Seligman (1976), positive psychology evolved from questions of virtue and human flourishing (Seligman, 2018; Seligman & Csikszentmihalyi, 2000). As a result, positive psychology shifted the focus from fixing what was missing or broken to enhancing people’s intrinsic strengths and promoting self-actualization. The studies of PsyCap have focused primarily on working adults whereas fewer studies have focused on youth (Preston et al., 2021). Fewer studies of PsyCap have focused, more specifically, on marginalized American youth who have been viewed primarily in light of their deficits. In a pilot study of 80 female YEH, our team found that providing an intervention based on a framework of PsyCap resulted in increased hope, resiliency, self-efficacy to refuse alcohol, and social connectedness (Rew et al., 2017). We speculated, then, that positive attributes such as those identified as PsyCap could be a potential mechanism for interventions useful to YEH. The specific aim of this analysis was to determine whether PsyCap factors (hope, self-efficacy for safe sex, resilience, optimism, social connectedness, and gratitude) mediated the relationship between background risk factors (e.g., race/ethnicity, educational attainment, sexual abuse history, earning money through survival sex, and HIV status) and outcomes of condom intention, safer sex behaviors, and life satisfaction among YEH who participated in a longitudinal test of an intervention to promote healthy sexual behaviors.

Methods

Design and Setting

The study was based on a Solomon four-group design (i.e., participants randomly assigned to pretest with or without the intervention or no pretest with or without the intervention), and details of the method and initial findings are described elsewhere (Rew et al., 2022). The multisite setting for this longitudinal intervention study was drop-in centers (DICs) for YEH in two major cities: Austin, Texas, and Columbus, Ohio. The study received approval from university institutional review boards in these two cities. A single DIC in Columbus and two DICs in Austin all offered YEH services, including case management, clothing, laundry services, educational programs, and meals. The services in Columbus, however, were available 24 hr a day, 7 days a week, whereas those in Austin were limited to a few hours per day, 3–4 days per week, depending upon staff availability.

Longitudinal Study Protocol

Staff employed at the DICs in Austin and Columbus made initial contact with eligible youth and described the purpose of the longitudinal study. Trained graduate research assistants subsequently obtained written, informed consent from those interested in participating. A total of 917 YEH were screened at the two locations; 209 did not meet the inclusion criteria for participation, 67 declined participation, and 39 failed to return after consenting. A final sample of 602 participants was then randomly assigned to one of four conditions: (1) pretest plus intervention [Texas n = 66; Ohio n = 84]; (2) pretest plus services as usual (SAU/control condition) [Texas n = 65; Ohio n = 86]; (3) intervention with no pretest [Texas n = 65; Ohio n = 86]; (4) SAU with no pretest [Texas n = 66; Ohio n = 84]. Posttest assessments at 3 weeks, 3 months, and 6 months were significantly higher among the Ohio participants than those in Texas (Rew et al., 2022).

Data Collection

Data were collected using valid and reliable scales (Cronbach’s alpha =.71 – .92) for all theoretical variables at four time points. Demographic data were collected from all four groups of participants following their enrollment. Two groups were randomized to receive a pretest consisting of all theoretical variables, and all four groups completed three posttests consisting of the same variables (hope, self-efficacy for substance refusal, self-efficacy for safe sex, resilience, optimism, gratitude, social connectedness, intention to use condoms, safe sex behaviors, and life satisfaction). Posttests were given immediately upon the conclusion of the intervention and 3 months and 6 months after enrollment. For participants who received SAU [i.e., control condition = SAU) rather than the intervention, the first posttest was conducted approximately 3 weeks after enrolling in the study. All data were collected through personal interviews done by trained research assistants who were not the same as individuals providing the intervention. All data were recorded on laptop computers and stored in Research Electronic Data Capture for future analysis.

Intervention

The clinical trial to test the intervention was registered at the University of Texas at Austin (NCT02553616). The brief intervention consisted of six modules delivered one-on-one to participants randomized to Groups 1 and 3. These modules were delivered by graduate research assistants trained by the investigators, using laptop computers, and focused on the future conceptualization of self as “best possible,” using principles of motivational interviewing. Information presented in the modules, along with skills practiced, included assertive communication, setting reasonable goals, decision-making about safe sex behaviors and minimizing substance use, correct usage of both male and female condoms, and enhancing self-efficacy or confidence (Rew et al., 2019).

Data Analysis

An autoregressive, cross-lagged, longitudinal mediation model was used to test the direct and indirect effects of risk factors, psychological capital, and outcomes in homeless youth collected across four waves (Figure 1). This method estimates effects between variables, controlling for changes over time and allowing for bidirectional causality (Magnusson Hanson et al., 2016). The risk manifest variable was defined as the sum across the following: Hispanic (1 = yes, 0 = no), Black (1 = yes, 0 = no), Latinx (1 = yes, 0 = no), American Indian (1 = yes, 0 = no), school dropout (1 = yes, 0 = no), school suspended (1 = yes, 0 = no), parent alcohol/drug abuse (1 = yes, 0 = no), abused by parent/guardian (1 = yes, 0 = no), neglect by parent/guardian (1 = yes, 0 = no), sexual minority (1 = yes, 0 = no), sexual abuse history (1 = yes, 0 = no), HIV positive (1 = yes, 0 = no), received money in exchange for survival sex (1 = yes, 0 = no).

Figure 1.

Figure 1

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Standardized Estimates and p values from Longitudinal Mediation Model of Risk Factors, Psychological Capital Variables, and Healthy Behavior Outcomes Across Four Waves in YEH who Participated in the Intervention.

Note. YEH = youth experiencing homelessness. *p < .05, **p < .01, ***p < .001.

The psychological capital latent variable was defined at each wave as the scores from the hope (Snyder, 2003), optimism (Scheier & Carver, 1985), resilience (Wagnild & Young, 1993), social connectedness (Blum et al., 1988), safe-efficacy for safe sex (Hanna, 1999), and gratitude (McCullough et al., 2002) scales. The outcome latent variable was defined at each wave as the scores from the condom intention (Jemmott & Jemmott, 1991), safe sex behavior (Dorio et al., 1992), and life satisfaction (Pavot & Diener, 1993) scales. The sexual health outcome variables of condom intention and safe sex behavior were selected for this analysis to reflect the purposes of the intervention that focused on taking personal responsibility for sexual attitudes (e.g., intention) and behaviors (e.g., talking about safer sex with a potential partner, stopping to put on a condom).

Longitudinal mediation was conducted using Iavaan (Rosseel, 2012) in the R Statistical Package (v4.1.2). We used maximum likelihood estimation with robust standard errors to handle nonnormality (Rosseel, 2012). Further, we used full-information maximum likelihood estimation to reduce bias associated with missing data. Standard errors were estimated using 5,000 nonparametric bootstrap samples. Model fit was evaluated using the comparative fit index (CFI), the Tucker–Lewis Index (TLI), and the root mean square error of approximation (RMSEA). We conducted the structural equation modeling (SEM) in the intervention group, and the combined sample. In the combined sample, an additional risk factor was considered (intervention group [0 = yes, 1 = no]).

Results

The overall sample was predominantly male (55%), heterosexual (69.9%), and White (34%). The average age was 21 (SD = 1.8) years. There were no significant differences in the subsamples from the two cities by age or sex, but there were significantly more Black YEH in Ohio than in Texas (65.8% v. 32.4%; X 2 (1) = 63.26, p ≤ .001) and more Latinx in Texas than in Ohio (84.3% v. 8.6%; X 2 (1) = 54.75, p ≤ .001; Rew et al., 2022, p. 947). Table 1 summarizes the number of participants, means, and standard deviations for all theoretical variables across pre- and posttests (1–3), as well as risk-factor responses.

Table 1.

Number of Participants and Variables

Theoretical Variables Pre-text (n); Mean (SD) Post-test 1 (n); Mean (SD) Post-test 2 (n); Mean (SD) Post-test 3 (n); Mean (SD)
Hope 254; 4.62 (1.00) 480; 4.76 (0.97) 412; 4.84 (0.95) 410; 4.90 (0.93)
Optimism 253; 4.79 (1.00) 480; 4.94 (0.98) 412; 4.96 (0.97) 410; 5.01 (0.92)
Resilience 254; 7.60 (1.00) 480; 7.64 (1.03) 411; 7.73 (1.01) 410; 7.83 (0.91)
Safe-sex self-efficacy 254; 5.12 (1.00) 480; 5.03 (1.06) 411; 5.13 (1.02) 410; 5.16 (0.96)
Social connectedness 254; 2.92 (1.00) 480; 3.11 (0.97) 411; 3.17 (0.99) 410; 3.25 (0.98)
Gratitude 254; 4.59 (1.00) 480; 4.71 (0.98) 411; 4.72 (0.91) 410; 4.79 (0.94)
Risk-score Variables Number “Yes” (%) Risk-score Variables Risk-score Variables
No treatment 269 (53.5) Parents/guardians abusive 147 (29.2)
Race: Black 273 (54.3) Parents neglectful 158 (31.4)
Race: American Indian 94 (18.7) Sexual minority 139 (27.6)
Latina(o) 86 (17.1) Childhood sexual abuse 224 (44.5)
Dropped out of school 170 (33.8) Engaged in survival sex 31 (6.2)
Suspended from school 24 (4.8) HIV positive 8 (1.6)
Parents used drugs 90 (17.9)
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There were no significant direct or indirect effects of risk factors on healthy behavior outcomes with no significant mediating paths via PsyCap in the intervention group (p > .13, Table 2, Figure 1). Accordingly, the model fit was poor for the intervention group (CFI = 0.60, TLI = 0.56, RMSEA = 0.10).

Table 2.

Longitudinal Mediation Effects for the Intervention Group. Standardized Estimates and 95% Confidence Intervals

Estimate CI lower CI upper p value
Direct 0.005 −0.067 0.078 .882
Med1 (risk->outcome1->psychcap2->outcome3) 0.000 −0.001 0.001 .791
Med2 (risk->psychcap1->psychcap2->outcome3) −0.014 −0.031 0.004 .125
Med3 (risk->psychcap1->outcome2->outcome3) −0.009 −0.025 0.007 .277
Med4 (risk->psychcap2->outcome3) 0.010 −0.004 0.023 .168
Total Indirect (Med1+Med2+Med3+Med4) −0.013 −0.035 0.009 .235
Total (Direct + Total Indirect) −0.008 −0.075 0.060 .823
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Note. CI = confidence interval

Similarly, there were no significant direct or indirect effects of risk factors on healthy behavior outcomes with no significant mediating paths via PsyCap in the combined sample (p > .18, Table 3, Figure 2). Moreover, the model fit was also poor for the combined sample (CFI = 0.61, TLI = 0.56, RMSEA = .11).

Table 3.

Longitudinal Mediation Effects of Psychological Capital Variables in Full Sample of Youth Experiencing Homelessness

Estimate CI lower CI upper p value
Direct −0.032 −0.082 0.018 .211
Med1 (risk->outcome1->psychcap2->outcome3) 0.000 0.000 0.000 .539
Med2 (risk->psychcap1->psychcap2->outcome3) −0.005 −0.013 0.003 .253
Med3 (risk->psychcap1->outcome2->outcome3) 0.000 −0.007 0.006 .933
Med4 (risk->psychcap2->outcome3) 0.002 −0.002 0.006 .369
Total Indirect (Med1+Med2+Med3+Med4) −0.003 −0.012 0.005 .456
Total (Direct + Total Indirect) −0.035 −0.086 0.016 .175
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Note. CI=confidence interval. Standardized estimates and 95% CI are shown.

Figure 2.

Figure 2

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Standardized Estimates and p-values from Longitudinal Mediation Model of Risk Factors, Psychological Capital Variables, and Healthy Behavior Outcomes Across Four Waves in YEH who did or did not Participate in the Intervention.

Note. YEH = youth experiencing homelessness. *p < .05, **p < .01, ***p < .001.

Discussion

The intervention developed and tested in the parent study was based on developing the intrinsic positive attributes of YEH. These included the original components of PsyCap (i.e., hope, self-efficacy, resilience, and optimism) with the addition of two other positive attributes (social connectedness and gratitude) and outcomes of safer sex behaviors, condom intention, and life satisfaction. This study represented the shift to strengths-based and away from deficits when measuring attributes of YEH.

Findings from the initial analyses of data from this longitudinal intervention study indicated that the intervention for YEH who participated in the study resulted in significantly improved scores on measures of hope, resilience, optimism, gratitude, and social connectedness (Rew et al., 2022). However, to our surprise, we found no mediating paths via these positive psychological variables to positive behavioral outcomes. This might be partially explained by the fact that in this analysis, we first included the entire sample, comprising both those who received the intervention and those in the SAU control condition. This led us to conduct a second data analysis from those in the intervention group only.

We used an enhanced operationalization of PsyCap in this analysis. That is, we included measures of social connectedness and gratitude in addition to the original PsyCap attributes of hope, efficacy, resilience, and optimism. Although Luthans et al. (2007) suggested that these and other positive attributes might contribute to the higher-order construct of PsyCap, they have not been established by empirical study of this population. Thus, further study is needed to limit the examination of mediators to those variables established in the theoretical study of PsyCap to date (i.e., hope, efficacy, resilience, and optimism); moreover, our measures of self-efficacy were influenced by Bandura’s (1997) assertion that self-efficacy should be domain-specific, which is how we operationalized efficacy for this study rather than using a generic measure of self-efficacy. It is also possible that the measured PsyCap might not be comprehensive or specific enough to capture other positive attributes directly or indirectly responsible for YEH’s positive changes in outcome behaviors assessed in this study.

A final possibility for the lack of observed mediation is that other factors—not measured—contribute to the underlying mechanisms of change in risk behaviors among YEH. While psychological capital has been linked to changes in risk behaviors, it is likely one of several underlying mechanisms. For example, social cognitive theory (Bandura, 1989) includes the concept of reciprocal determinism in which the cognitive, behavioral, and environment factors interact to result in change in behaviors. Positive attitudes can lead to the employment of health-promoting behaviors in the youths’ repertoire; however, this relationship is likely also influenced by factors external to the youth associated with the high-risk living environment of the street, such as close proximity to predators and victimization experiences. That is, while PsyCap underscores the strengths and potential of individuals in the face of adversity, YEH also experience barriers outside of their control which can theoretically influence their cognitive (e.g., motivational) and behavioral (ability to apply skills) systems. Victimization, hunger, fear, and pain negatively affect even the strongest of wills. To shed light on those mechanisms beyond PsyCap associated with risk behavior change among youth immersed in the dehumanizing experience of homelessness may require multiple complex and interacting factors—internal and external to the individual—to be identified and targeted in future mediational analyses.

Conclusion

This analysis shows that shifting the focus from problem behaviors and deficits in this vulnerable population to positive attributes is possible. This analysis failed to support positive attributes as buffering factors protecting YEH from engaging in risk behaviors; however, such negative findings should not be construed as evidence discounting the positive effect of PsyCap on healthy behavioral outcomes among such vulnerable young people as YEH without consideration of its complex interplay with other individual and contextual circumstances. Further research is warranted to adequately understand the roles of PsyCap in a broader ecological context. An examination of PsyCap variables (i.e., hope, self-efficacy, resilience, optimism, social connectedness, and gratitude) as mechanisms that explain changes in behaviors of youth experiencing homelessness is ripe for further investigation.

Funding:

R01 HD083576 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development awarded to the first author, Donna Lynn Rew.

This research was supported by and awarded to the first author (Rew) from the National Institute of Child Health and Human Development/National Institutes of Health (R01HD083576).

The University of Texas at Austin Institutional Review Board approved this study (#2015–07-0009). The Ohio State University Institutional Review Board approved this study (#2014B0130).

Footnotes

Clinical Trial Registration: The University of Texas at Austin (UTexasAustin), DRew (user)

Protocol ID-R01-HD083576

NCT:02553616

Conflict of Interest: The authors report no conflicts of interest.

The authors report no conflicts of interest to report.

Institutional Review Board Approval: The University of Texas at Austin # 2015-07-0009.

Clinical Trial Registration: ClinicalTrials.gov. Bethesda (MD): National Library of Medicine (US). 2000 Feb 29 - Identifier NCT02553616, An intervention to promote healthy behaviors in homeless youth; 2015 Sept 16 [cited 2015 Sept 17]. Available from: https://clinicaltrials.gov/study/NCT02553616#study-record-dates

The data sets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author upon reasonable request.

Contributor Information

Lynn Rew, Denton & Louise Cooley and Family Centennial Professor in Nursing, The University of Texas at Austin School of Nursing.

Natasha Slesnick, EHE Distinguished Professor and Associate Dean of Research & Administration, Department of Human Sciences, The Ohio State University.

Shelli Kesler, Director of Statistical Services, Cain Center for Nursing Research, The University of Texas at Austin School of Nursing.

Hyekyun Rhee, La Quinta Motor Inns, Inc. Centennial Professor in Nursing, The University of Texas at Austin School of Nursing.

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