Search results

This study examines chronic illness, disability and social inequality within an exposure-vulnerabilities theoretical framework.

Using the National Survey of Drug Use and Health (NSDUH), a preeminent source of national behavioral health estimates of chronic medical illness, stress and disability, for selected sample years 2005–2014, we construct and analyze two foundational hypotheses underlying the exposure-vulnerabilities model: (1) greater exposure to stressors (i.e., chronic medical illness) among racial/ethnic minority populations yields higher levels of serious psychological distress, which in turn increases the likelihood of medical disability; (2) greater vulnerability among minority populations to stressors such as chronic medical illness exacerbates the impact of these conditions on mental health as well as the impact of mental health on medical disability.

Results of our analyses provided mixed support for the vulnerability (moderator) hypothesis, but not for the exposure (mediation) hypothesis. In the exposure models, while Blacks were more likely than Whites to have a long-term disability, the pathway to disability through chronic illness and serious psychological distress did not emerge. Rather, Whites were more likely than Blacks and Latinx to have a chronic illness and to have experienced severe psychological distress (both of which themselves were related to disability). In the vulnerability models, both Blacks and Latinx with chronic medical illness were more likely than Whites to experience serious psychological distress, although Whites with serious psychological distress were more likely than these groups to have a long-term disability.

Several possibilities for understanding the failure to uncover an exposure dynamic in the model turn on the potential intersectional effects of age and gender, as well as several other covariates that seem to confound the linkages in the model (e.g., issues of stigma, social support, education).

This study (1) extends the racial/ethnic disparities in exposure-vulnerability framework by including factors measuring chronic medical illness and disability which: (2) explicitly test exposure and vulnerability hypotheses in minority populations; (3) develop and test the causal linkages in the hypothesized processes, based on innovations in general structural equation models, and lastly; (4) use national population estimates of these conditions which are rarely, if ever, investigated in this kind of causal framework.

This study examines the relationship between the innovation ecosystem and performance measurement models. Although the innovation ecosystem and measurement models are widely recognized, the existing literature lacks a comprehensive understanding of the relationship between the proposed themes. Furthermore, it does not reveal how studies can be grouped to propose a thematic typology of the relationship.

The authors present a systematic literature review conducted in the Web of Science and Scopus databases, from a textual corpus that aided the proposition of the typology that aims to provide answers regarding the addressed themes.

The results of this review are based on a total of sixty peer-reviewed articles from the innovation ecosystem literature and performance measurement models between 1995 and 2020. The results make several contributions to the literature. First, by integrating evidence from empirical studies, the authors identified a typology formed by three classes: (1) ecosystem agents (2) analytical focus and (3) structured measurement tools. Second, the authors verified the relationship between the themes and discovered the existence of gaps to be filled, with the proposition of three drivers. Third, the authors presented a comprehensive mapping of field studies with a descriptive analysis of the textual corpus.

The results of the research provide important implications for researchers, managers and policy makers. Furthermore, the authors suggest directions for future research, including the need to examine the performance of the entire innovation ecosystem, integrating the different agents that exist for performance measurement.