TPC-Journal-V4-Issue4

The Professional Counselor \Volume 4, Issue 4 398 In the third step of the regression, after controlling for both OQ pretest scores and SES variables, the psychological variables (subjective social support, treatment expectancy and client motivation) did not predict significantly more variance in outcome, Δ R 2 = .02, F (5, 37) = 0.90, p > .05. Discussion Overall, SES variables significantly predicted counseling outcome. In particular, two of the objective SES variables—education level and health insurance status—each individually predicted greater improvement in counseling, explaining 3% and 4% of the outcome variance, respectively. Contrary to expectations, income level and the subjective SES variables did not predict outcome. Overall, our hypothesis that SES variables would relate to social support, treatment expectancy and motivation was not supported. However, the subjective SES variable—perceived financial security—significantly and positively related to subjective social support. Surprisingly, as a whole, SES variables did not correlate with clients’ subjective sense of social support. The only exception was a significant positive link between subjective social support and perceived financial security. It may be that the perception of having sufficient funds to meet recent individual or family needs aligns with the perception of having a supportive social network. However, the finding that income level did not correlate with social support was interesting given the common perception among mental health workers that low-income clients lack social support (Krause & Borawski-Clark, 1995). In this study, from the perspectives of lower-income clients, there were no perceptions of support system deficits. The degree and frequency with which one experiences positive interactions with peers is the basis of the SSS instrument. Within SES research, social support measures may include community social support, as well as family and peers. The definition of social support may differ from participant to participant. One of the challenges of social support within SES is that lower-SES individuals often experience similar increased economic stressors to others in their social support network (Mickelson & Kubzansky, 2003). Therefore, a more limited study using multiple social support measures is a possible direction for future research. Though the first hypothesis was not supported, the results indicate a trend in the hypothesized direction, with higher perceived financial security being marginally related to treatment expectancy, accounting for 7% of the variance, a medium-sized effect. In other words, before counseling began, clients who reported a greater sense of financial security also had greater expectation of a positive treatment outcome. There was, however, no significant relationship between all other SES indicators and either motivation type. Given that this hypothesis was based on studies of perceptions among mental health professionals working with low-income clients (e.g., Dougall & Schwartz, 2011; Hillerbrand, 1988; Krause & Borawski-Clark, 1995; Leeder, 1996; Seccombe et al., 1998), it is possible that the findings are indicative of SES-related biases in the helping professions. That is, the overall findings of the present study did not reveal significant relationships between SES and social support, treatment expectancy or client motivation, even though clinicians have frequently reported beliefs that such relationships exist. Of the three objective SES variables, education level and health insurance status each predicted greater improvement in counseling. Education level is commonly used in poverty research, which shows that lower education is associated with decreased physical and mental health. For example, Goodman, Slap, and Huang (2003) found that lower household income and parental education were associated with depression and obesity. Similarly, SES studies using neighborhood indices such as zip code or concentrated populations with similar income levels often find lower-income communities facing challenges such as lack of quality education, lower education levels and fewer employment opportunities, with these chronic stressors impacting depressive symptoms (Groh, 2007).