We use confirmatory factor analysis (CFA) to test the validity and reliability of three non-cognitive factors-resilience, grit, and growth mindset-as well as to examine whether those factors predict academic success for a sample of students primarily represented by first-year African American students at three Historically Black Colleges and Universities (HBCUs) and one Minority Serving Institution (MSI). The findings indicate that initial growth mindset and grit scores predicted GPA, whereas changes in resilience over the academic year predicted the number of credit hours taken at the end of the first year. Results add to the ongoing debate about the credibility and utility of noncognitive factors for fostering success.

Latinos in the United States represent a disproportionate burden of illness and disease and face barriers to accessing health care and related resources. Culturally tailored, evidence-based interventions hold promise in addressing many of these challenges. Yet, ensuring patient voice is vital in the successful development and implementation of such interventions. Thus, this paper examines the application of analytic hierarchy process (AHP) to inform the augmentation and implementation of an evidence-based chronic disease self-management programme for underserved Latinos living with both minor depression and chronic illness. The process of AHP allows for direct input from the individuals that would utilize such a programme, including afflicted individuals, their family members and the health educators/promotores that would be responsible for implementation. Specifically, 45 participants, including 15 individuals with chronic disease, 15 family members/caregivers and 15 promotores, partook in the Stakeholder Values Questionnaire, which elicited preferences and values regarding major goals, processes and content for the intervention. AHP was employed to analyse pairwise comparison ratings and to determine differences and similarities across stakeholder groups. This analytical technique allowed for the adaptation of the EBI to stakeholders' specific priorities and preferences and facilitated complex decision-making. Findings not only shed light on similarities and differences between stakeholder groups, but also the magnitude of these priorities and preferences and allowed the intervention to be driven by the participants, themselves. Applying AHP was a unique opportunity to optimize the decision-making process to inform cultural adaptation of an EBI while considering multiple viewpoints systematically.

The purpose of this paper is to share lessons learned from a collaborative, community-informed mixed-methods approach to adapting an evidence-based intervention to meet the needs of Latinos with chronic disease and minor depression and their family members. Mixed-methods informed by community-based participatory research (CBPR) were employed to triangulate multiple stakeholders' perceptions of facilitators and barriers of implementing the adapted intervention in community settings. Community partners provided an insider perspective to overcome methodological challenges. The study's community informed mixed-methods: research approach offered advantages to a single research methodology by expanding or confirming research findings and engaging multiple stakeholders in data collection. This approach also allowed community partners to collaborate with academic partners in key research decisions.

Informal caregiving can be fundamental to disease management. Yet, the psychosocial, physical, and financial burden experienced by caregivers can be significant. In the US, Latinos experience increasing rates of chronic conditions, the highest uninsured rates in the country, and a growing dependence on informal caregivers. This article explores the impact of caregiving on caregivers of individuals with comorbid chronic disease and depression. Findings highlight the impact of caregiving on financial insecurity, balancing competing demands, increased emotional distress, and community supports. Findings support the inclusion of caregivers in disease management programs to enhance psychosocial outcomes for both caregivers and their patients.

The co-occurrence of depression and chronic diseases is often under-recognized, under-treated, and under-studied. Among Latinos, complex structural and cultural barriers exist which complicate the translation of chronic disease self-management programs (CDSMP) for this population. To better understand those barriers and deliver a CDSMP designed to best meet local needs, a community-based, mixed methods study was designed. Formative research was conducted through focus groups with Latinos with chronic illness and minor depression (ICD) and family members to obtain insight into perceived needs and interviews with stakeholders to assess barriers and facilitators to the adoption of CDSMPs. Analytic Hierarchy Process was employed to determine core elements of a CDSMP for ICDs, family members, and the promotores who deliver these programs. Findings guided the transcreation of a CDSMP. This study offers a promising model for enhancing the effects of evidence-based interventions and emphasizes the importance of meeting differing needs within the local population.

Depression is prevalent in primary care (PC) practices and poses a considerable public health burden in the United States. Despite nearly four decades of efforts to improve depression care quality in PC practices, a gap remains between desired treatment outcomes and the reality of how depression care is delivered.This article presents a real-world PC practice model of depression care, elucidating the processes and their influencing conditions.Grounded theory methodology was used for the data collection and analysis to develop a depression care model. Data were collected from 70 individual interviews (60 to 70 min each), three focus group interviews (n = 24, 2 h each), two surveys per clinician, and investigators' field notes on practice environments. Interviews were audiotaped and transcribed for analysis. Surveys and field notes complemented interview data.Seventy primary care clinicians from 52 PC offices in the Midwest: 28 general internists, 28 family physicians, and 14 nurse practitioners.A depression care model was developed that illustrates how real-world conditions infuse complexity into each step of the depression care process. Depression care in PC settings is mediated through clinicians' interactions with patients, practice, and the local community. A clinician's interactional familiarity ("familiarity capital") was a powerful facilitator for depression care. For the recognition of depression, three previously reported processes and three conditions were confirmed. For the management of depression, 13 processes and 11 conditions were identified. Empowering the patient was a parallel process to the management of depression.The clinician's ability to develop and utilize interactional relationships and resources needed to recognize and treat a person with depression is key to depression care in primary care settings. The interactional context of depression care makes empowering the patient central to depression care delivery.

PURPOSE Despite the sophisticated development of depression instruments during the past 4 decades, the critical topic of how primary care clinicians actually use those instruments in their day-to-day practice has not been investigated. We wanted to understand how primary care clinicians use depression instruments, for what purposes, and the conditions that influence their use. METHODS Grounded theory method was used to guide data collection and analysis. We conducted 70 individual interviews and 3 focus groups (n = 24) with a purposeful sample of 70 primary care clinicians (family physicians, general internists, and nurse practitioners) from 52 offices. Investigators' field notes on office practice environments complemented individual interviews. RESULTS The clinicians described occasional use of depression instruments but reported they did not routinely use them to aid depression diagnosis or management; the clinicians reportedly used them primarily to enhance patients' acceptance of the diagnosis when they anticipated or encountered resistance to the diagnosis. Three conditions promoted or reduced use of these instruments for different purposes: the extent of competing demands for the clinician's time, the lack of objective evidence of depression, and the clinician's familiarity with the patient. No differences among the 3 clinician groups were found for these 3 conditions. CONCLUSIONS Depression instruments are reinvented by primary care clinicians in their real-world primary care practice. Although depression instruments were originally conceptualized for screening, diagnosing, or facilitating the management of depression, our study suggests that the real-world practice context influences their use to aid shared decision making—primarily to suggest, tell, or convince patients to accept the diagnosis of depression.

Objective . To assess the effect on risk-adjustment of inpatient mortality rates of progressively enhancing administrative claims data with clinical data that are increasingly expensive to obtain. Data Sources . Claims and abstracted clinical data on patients hospitalized for 5 medical conditions and 3 surgical procedures at 188 Pennsylvania hospitals from July 2000 through June 2003. Methods . Risk-adjustment models for inpatient mortality were derived using claims data with secondary diagnoses limited to conditions unlikely to be hospital-acquired complications. Models were enhanced with one or more of 1) secondary diagnoses inferred from clinical data to have been present-on-admission (POA), 2) secondary diagnoses not coded on claims but documented in medical records as POA, 3) numerical laboratory results from the first hospital day, and 4) all available clinical data from the first hospital day. Alternative models were compared using c-statistics, the magnitude of errors in prediction for individual cases, and the percentage of hospitals with aggregate errors in prediction exceeding specified thresholds. Results . More complete coding of a few under-reported secondary diagnoses and adding numerical laboratory results to claims data substantially improved predictions of inpatient mortality. Little improvement resulted from increasing the maximum number of available secondary diagnoses or adding additional clinical data. Conclusions . Increasing the completeness and consistency of reporting a few secondary diagnosis codes for findings POA and merging claims data with numerical laboratory values improved risk adjustment of inpatient mortality rates. Expensive abstraction of additional clinical information from medical records resulted in little further improvement.

This special issue consolidates some recent research findings and scientific thought on co-occurring disorders from both the substance abuse and mental health fields. This summary article recaps and synthesizes the main findings and themes, then considers additional issues in the field today to arrive at an agenda for future co-occurring disorders research. Plans must: (1) encourage and assist further development of treatment programs that respond to an array of types and severities of co-occurring disorders while taking into account the limited resources typically available; (2) continue the development and testing of continuing care models by exploring strategies that will sustain the recovery of treated individuals who remain vulnerable to relapse; and (3) contribute to our understanding of the mechanisms and processes that enable new interventions and practices to be adopted, implemented, and sustained. "Co-occurring disorders" is a relatively new area of research; this special issue illustrates the productivity of work to date and indicates the potential for advances to come.