Drivers and facilitators of the illegal killing of elephants across 64 African sites

Ivory poaching continues to threaten African elephants. We (1) used criminology theory and literature evidence to generate hypotheses about factors that may drive, facilitate or motivate poaching, (2) identified datasets representing these factors, and (3) tested those factors with strong hypotheses and sufficient data quality for empirical associations with poaching. We advance on previous analyses of correlates of elephant poaching by using additional poaching data and leveraging new datasets for previously untested explanatory variables. Using data on 10 286 illegally killed elephants detected at 64 sites in 30 African countries (2002–2020), we found strong evidence to support the hypotheses that the illegal killing of elephants is associated with poor national governance, low law enforcement capacity, low household wealth and health, and global elephant ivory prices. Forest elephant populations suffered higher rates of illegal killing than savannah elephants. We found only weak evidence that armed conflicts may increase the illegal killing of elephants, and no evidence for effects of site accessibility, vegetation density, elephant population density, precipitation or site area. Results suggest that addressing wider systemic challenges of human development, corruption and consumer demand would help reduce poaching, corroborating broader work highlighting these more ultimate drivers of the global illegal wildlife trade

Psychiatric inpatient expenditures and public health insurance programmes: analysis of a national database covering the entire South Korean population

<p>Abstract</p> <p>Background</p> <p>Medical spending on psychiatric hospitalization has been reported to impose a tremendous socio-economic burden on many developed countries with public health insurance programmes. However, there has been no in-depth study of the factors affecting psychiatric inpatient medical expenditures and differentiated these factors across different types of public health insurance programmes. In view of this, this study attempted to explore factors affecting medical expenditures for psychiatric inpatients between two public health insurance programmes covering the entire South Korean population: National Health Insurance (NHI) and National Medical Care Aid (AID).</p> <p>Methods</p> <p>This retrospective, cross-sectional study used a nationwide, population-based reimbursement claims dataset consisting of 1,131,346 claims of all 160,465 citizens institutionalized due to psychiatric diagnosis between January 2005 and June 2006 in South Korea. To adjust for possible correlation of patients characteristics within the same medical institution and a non-linearity structure, a Box-Cox transformed, multilevel regression analysis was performed.</p> <p>Results</p> <p>Compared with inpatients 19 years old or younger, the medical expenditures of inpatients between 50 and 64 years old were 10% higher among NHI beneficiaries but 40% higher among AID beneficiaries. Males showed higher medical expenditures than did females. Expenditures on inpatients with schizophrenia as compared to expenditures on those with neurotic disorders were 120% higher among NHI beneficiaries but 83% higher among AID beneficiaries. Expenditures on inpatients of psychiatric hospitals were greater on average than expenditures on inpatients of general hospitals. Among AID beneficiaries, institutions owned by private groups treated inpatients with 32% higher costs than did government institutions. Among NHI beneficiaries, inpatients medical expenditures were positively associated with the proportion of patients diagnosed into dementia or schizophrenia categories. However, for AID beneficiaries, inpatient medical expenditures were positively associated with the proportion of all patients with a psychiatric diagnosis that were AID beneficiaries in a medical institution.</p> <p>Conclusions</p> <p>This study provides evidence that patient and institutional factors are associated with psychiatric inpatient medical expenditures, and that they may have different effects for beneficiaries of different public health insurance programmes. Policy efforts to reduce psychiatric inpatient medical expenditures should be made differently across the different types of public health insurance programmes.</p

Promotoras as Mental Health Practitioners in Primary Care: A Multi-Method Study of an Intervention to Address Contextual Sources of Depression

We assessed the role of promotoras—briefly trained community health workers—in depression care at community health centers. The intervention focused on four contextual sources of depression in underserved, low-income communities: underemployment, inadequate housing, food insecurity, and violence. A multi-method design included quantitative and ethnographic techniques to study predictors of depression and the intervention’s impact. After a structured training program, primary care practitioners (PCPs) and promotoras collaboratively followed a clinical algorithm in which PCPs prescribed medications and/or arranged consultations by mental health professionals and promotoras addressed the contextual sources of depression. Based on an intake interview with 464 randomly recruited patients, 120 patients with depression were randomized to enhanced care plus the promotora contextual intervention, or to enhanced care alone. All four contextual problems emerged as strong predictors of depression (chi square, p < .05); logistic regression revealed housing and food insecurity as the most important predictors (odds ratios both 2.40, p < .05). Unexpected challenges arose in the intervention’s implementation, involving infrastructure at the health centers, boundaries of the promotoras’ roles, and “turf” issues with medical assistants. In the quantitative assessment, the intervention did not lead to statistically significant improvements in depression (odds ratio 4.33, confidence interval overlapping 1). Ethnographic research demonstrated a predominantly positive response to the intervention among stakeholders, including patients, promotoras, PCPs, non-professional staff workers, administrators, and community advisory board members. Due to continuing unmet mental health needs, we favor further assessment of innovative roles for community health workers

Efficacy and cost-effectiveness of two online interventions for children and adolescents at risk for depression (E.motion trial): study protocol for a randomized controlled trial within the ProHEAD consortium

Background: Depression is a serious mental health problem and is common in children and adolescents. Online interventions are promising in overcoming the widespread undertreatment of depression and in improving the help-seeking behavior in children and adolescents. Methods: The multicentre, randomized controlled E.motion trial is part of the German ProHEAD consortium (Promoting Help-seeking using E-technology for ADolescents). The objective of the trial is to investigate the efficacy and cost-effectiveness of two online interventions to reduce depressive symptomatology in high-risk children and adolescents with subsyndromal symptoms of depression in comparison to an active control group. Participants will be randomized to one of three conditions: (1) Intervention 1, a clinician-guided self-management program (iFightDepression®); (2) Intervention 2, a clinician-guided group chat intervention; and (3) Control intervention, a psycho-educational website on depressive symptoms. Interventions last six weeks. In total, N = 363 children and adolescents aged ≥ 12 years with Patient Health Questionnaire-9 modified for Adolescents (PHQ-A) scores in the range of 5–9 will be recruited at five study sites across Germany. Online questionnaires will be administered before onset of the intervention, at the end of the intervention, and at the six-month follow-up. Further, children and adolescents will participate in the baseline screening and the one- and two-year school-based follow-up assessments integrated in the ProHEAD consortium. The primary endpoint is depression symptomatology at the end of intervention as measured by the PHQ-A score. Secondary outcomes include depression symptomatology at all follow-ups, help-seeking attitudes, and actual face-to-face help-seeking, adherence to and satisfaction with the interventions, depression stigma, and utilization and cost of interventions. Discussion: This study represents the first randomized controlled trial (RCT) investigating efficacy and cost-effectiveness of two online interventions in children and adolescents aged ≥ 12 years at risk for depression. It aims to provide a better understanding of the help-seeking behavior of children and adolescents, potential benefits of E-mental health interventions for this age group, and new insights into so far understudied aspects of E-mental health programs, such as potential negative effects of online interventions. This knowledge will be used to tailor and improve future help offers and programs for children and adolescents and ways of treatment allocation. Trial registration: German Register for Clinical Trials (DRKS), DRKS00014668. Registered on 4 May 2018. International trial registration took place through the “international clinical trials registry platform” with the secondary ID S-086/2018

Decomposing the parameter space of biological networks via a numerical discriminant approach

Many systems in biology (as well as other physical and engineering systems) can be described by systems of ordinary differential equation containing large numbers of parameters. When studying the dynamic behavior of these large, nonlinear systems, it is useful to identify and characterize the steady-state solutions as the model parameters vary, a technically challenging problem in a high-dimensional parameter landscape. Rather than simply determining the number and stability of steady-states at distinct points in parameter space, we decompose the parameter space into finitely many regions, the number and structure of the steady-state solutions being consistent within each distinct region. From a computational algebraic viewpoint, the boundary of these regions is contained in the discriminant locus. We develop global and local numerical algorithms for constructing the discriminant locus and classifying the parameter landscape. We showcase our numerical approaches by applying them to molecular and cell-network models