Objective Stigma associated with mental illness continues to be a significant barrier to help seeking, leading to negative attitudes about mental health treatment and deterring individuals who need services from seeking care. This study examined the impact of public stigma (negative attitudes held by the public) and internalized stigma (negative attitudes held by stigmatized individuals about themselves) on racial differences in treatment seeking attitudes and behaviors among older adults with depression. Method Random digit dialing was utilized to identify a representative sample of 248 African American and White adults older adults (over the age of 60) with depression (symptoms assessed via the Patient Health Questionnaire-9). Telephone based surveys were conducted to assess their treatment seeking attitudes and behaviors, and the factors that impacted these behaviors. Results Depressed older adult participants endorsed a high level of public stigma and were not likely to be currently engaged in, nor did they intend to seek mental health treatment. Results also suggested that African American older adults were more likely to internalize stigma and endorsed less positive attitudes toward seeking mental health treatment than their White counterparts. Multiple regression analysis indicated that internalized stigma partially mediated the relationship between race and attitudes toward treatment. Conclusion Stigma associated with having a mental illness has a negative influence on attitudes and intentions toward seeking mental health services among older adults with depression, particularly African American elders. Interventions to target internalized stigma are needed to help engage this population in psychosocial mental health treatments.

Introduction Perceived social isolation (PSI) is associated with substantial morbidity and mortality. Social media platforms, commonly used by young adults, may offer an opportunity to ameliorate social isolation. This study assessed associations between social media use (SMU) and PSI among U.S. young adults. Methods Participants were a nationally representative sample of 1787 U.S. adults aged 19–32 years. They were recruited in October–November 2014 for a cross-sectional survey using a sampling frame that represented 97% of the U.S. population. SMU was assessed using both time and frequency of using 11 social media platforms, including Facebook, Twitter, Google+, YouTube, LinkedIn, Instagram, Pinterest, Tumblr, Vine, Snapchat, and Reddit. PSI was measured using the Patient-Reported Outcomes Measurement Information System scale. In 2015, ordered logistic regression was used to assess associations between SMU and SI while controlling for eight covariates. Results In fully adjusted multivariable models that included survey weights, compared with those in the lowest quartile for SMU time, participants in the highest quartile had twice the odds of having greater PSI (AOR=2.0, 95% CI=1.4, 2.8). Similarly, compared with those in the lowest quartile, those in the highest quartile of SMU frequency had more than three times the odds of having greater PSI (AOR=3.4, 95% CI=2.3, 5.1). Associations were linear (p<0.001 for all), and results were robust to all sensitivity analyses. Conclusions Young adults with high SMU seem to feel more socially isolated than their counterparts with lower SMU. Future research should focus on determining directionality and elucidating reasons for these associations.

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Using Apple’s Screen Time application to obtain reported actual iPhone and social media (SM) use, we examined the accuracy of retrospective estimates of usage, how inaccuracies bias associations between use and psychosocial well-being (depression, loneliness, and life satisfaction), and the degree to which inaccuracies were predicted by levels of well-being. Among a sample of 325 iPhone users, we found that (a) participants misestimated their weekly overall iPhone and SM use by 19.1 and 12.2 hours, respectively; (b) correlations between estimated use and well-being variables were consistently stronger than the correlations between reported actual use and well-being variables; and (c) the degree of inaccuracy in estimated use was associated with levels of participant well-being and amount of use. These findings suggest that retrospective estimates of digital technology use may be systematically biased by factors that are fundamental to the associations under investigation. We propose that retrospective estimates of digital technology use may be capturing the construct of perceived use rather than actual use, and discuss how the antecedents, correlates, and consequences of perceived use may be distinct from those of actual use. Implications of these findings are discussed in view of the ongoing debate surrounding the effects of digital technology use on well-being.

Using data from a random sample of women from the welfare caseload in an urban Michigan county, the authors investigate the prevalence of domestic violence and its association with mental health, health, and economic well-being. Nearly a quarter of the women experienced physical partner violence in the past 12 months, and almost two thirds in their lifetimes. Recent victims had significantly higher rates of five psychiatric disorders (depression, generalized anxiety disorder, post-traumatic stress disorder, drug dependence, and alcohol dependence) and health problems than women who never experienced domestic violence. Recent partner violence was also associated with greater material hardship. Analyses did not indicate any significant association between domestic violence, past or present, and employment.