Benefits on Sales Generated by Innovation

The object of the research is to assess whether organizations’ ability to innovate may be able to explain abnormal returns to firms by composing risk factor models. Using R&D investment indicators and published patents from a global sample of companies for the period 1992 to 2018, the 3-factor, 4-factor and 5-factor risk models were applied. Partly the case is that increased investment in innovation contributes to better sales performance and, consequently, excess returns. Regarding the rolling-regression method, the results show few scenarios in which the ability to innovate is an explanatory factor for financial performance.

Suicide Models and Treatment Models Are Separate Entities. What Does It Mean for Clinical Suicide Prevention?

Theoretical models of suicide are based on risk factors associated with suicide, such as psychiatric pathology, genetics, epigenetics, functional brain disorders, and impaired decision making. In current clinical practice, the predominant risk model is the medical model, which posits that treating suicide risk is primarily a matter of treating psychiatric disorders. However, even comprehensive risk factor models cannot overcome the basic problem that, by their nature, they cannot accommodate the suicidal person’s psychological experience of suicidality. Risk factor models do not translate into effective treatment models. Suicide risk is highly personal and fluid, and is related to individual vulnerabilities and to person-specific events triggering suicidal thoughts and actions. Clinicians need treatment models that are meaningful to suicidal patients. Understanding the single person’s suicidality requires a patient-centered approach. Therapeutic interventions that effectively reduce the risk of suicidal behavior have been developed from general principles of psychotherapy. Therapy process factors associated with effective therapies are working alliance, validation of the individual patient’s thoughts and feelings, active treatment engagement. Psychological therapies need patients who are active participants in a collaborative working relationship between therapist and patient. The goal must be to jointly develop a meaningful understanding of the suicidal crisis. In view of the limited personal resources in health care systems it is important that effective therapies are brief and effective. Future research must aim to improve our understanding of the factors involved in effective therapies in order to optimize treatments for individuals at risk. This may also include the integration of biological risk factors in psychological treatment models.

The Contributions of Propensity, Delinquent Peers, Low Parental Supervision, and Empathy to the Emergence of Antisocial Behavior in Childhood and Adolescence: Testing Developmental Path Models Combining Psychological- and Sociological-Criminological Approaches

Psychological- and sociological-criminological research refers to, for example, cumulative risk factor models (e.g., Lösel & Bender, 2003) and Situational Action Theory (SAT; e.g., Wikström, 2006). The German longitudinal study “Chances and Risks in the Life Course“ (research project A2, Collaborative Research Center 882; e.g., Reinecke, Stemmler, & Wittenberg, 2016) focuses upon the development of antisocial behavior from a psychological and sociological point of view. Two-wave panel data of two cohorts (children and adolescents) were utilized to test the power of developmental path models investigating the development of antisocial behavior. Individual risk seems to have both direct and indirect influences on antisocial behavior, supporting the ideas of risk factor models; antisocial behavior might be the outcome of the interaction between propensity and criminogenic exposure, so there is evidence for SAT. Additionally, empathy seems to be related to both propensity and low parental supervision. Implications for the study of antisocial behavior in childhood and adolescence are discussed in line with developmental criminology.

Household economic burden and outcomes of patients with schizophrenia after being unlocked and treated in rural China

Aims Patients with severe mental disorders in low-resource settings have limited access to services, resulting in overwhelming caregiving burden for families. In extreme cases, this has led to the long-term restraining of patients in their homes. China underwent a nationwide initiative to unlock patients and provide continued treatment. This study aims to quantify household economic burden in families after unlocking and treatment, and to identify factors associated with increased burden due to schizophrenia. Methods A total of 264 subjects were enrolled from three geographically diverse provinces in 2012. Subjects were patients with schizophrenia who were previously put under restraints and had participated in the ‘unlocking and treatment’ intervention. The primary outcome was the current household economic burden, obtained from past year financial information collected through on-site interview. Patient disease characteristics, treatment, outcomes and family caregiving burden were collected as well. Univariate and multivariate linear regression were used to construct risk factor models for indirect economic burden. Results After participating in the intervention, 85% of patients continued to receive mental health services, 70% used medication as prescribed and 80% were never relocked. Family members reported significantly decreased caregiving burden after receiving the intervention. Mean direct and indirect household economic burdens were CNY963 (US$31.7) and CNY11 724 (US$1670) per year, respectively, while family total income was on average CNY12 108 (US$1913) per year. Greater disease severity and poorer patient psychosocial function at time of study were found to be independent factors related to increased indirect burden. Conclusions The ‘unlocking and treatment’ intervention has improved the lives of patients and families. Indirect burden due to disease is still a major economic issue that needs to be addressed, potentially through improving treatment and patient functioning. Our findings contribute to the unravelling and eventual elimination of chronic restraining of mentally ill patients in low-resource settings.

Opportunities and Limitations of Vascular Risk Factor Models in Studying Plasticity-Promoting and Restorative Ischemic Stroke Therapies

Major efforts are currently made promoting neuronal plasticity and brain remodeling in the postacute stroke phase. Experimental studies evaluating new stroke therapies are mostly performed in rodents, which compared to humans exhibit a short lifespan. These studies widely employ young, otherwise healthy, rodents that lack the vascular risk factors and comorbidities of stroke patients. These risk factors compromise postischemic neurological recovery and brain plasticity and in several contexts reduce the brain responsiveness to recovery-inducing plasticity-promoting treatments. By examining risk factor models, which have hitherto been used for studying experimentally induced ischemic stroke, this review outlines the possibilities and limitations of risk factor models in the evaluation of plasticity-promoting and restorative stroke treatments.

Risk models vs characteristic models from an investor’s perspective

Purpose The purpose of this paper is to analyze the implications of the risk versus characteristic debate from the perspective of a mean-variance investor. Design/methodology/approach Expected returns and the variance-covariance matrix are estimated based on various characteristic and risk models and evaluated for the purpose of mean-variance portfolios. Findings Return estimates from characteristic models are most informative to investors. Risk-factor models provide the most informative estimates of the risk. A mean-variance investor should rely on combinations of the two model types. Originality/value Although the risk vs characteristic debate is a binary academic debate, our findings from an investor's perspective suggest to make use of the best of both worlds.

A novel principled method for the measurement of vascular robustness uncovers hidden risk for premature CVD death

The detection of high risk for premature death of cardiovascular disease (CVD) among individuals with low-to-moderate risk factor scores is a major challenge. Systems biology suggests that the vasculature's functional robustness against risk factor challenges may serve as a novel discriminator of mortality risk under similar risk factor loads. However, principled methods to measure vascular robustness are not available. To develop a score for the vasculature's functional robustness we used a recently presented method that applies computational physiological modeling to the quantitation of vascular function. We hypothesized that the expected inverse robustness-mortality association is verifiable as a significant robustness-calendar age trend in a cross-sectional investigation of a population cohort of risk factor-challenged individuals. Using only functional parameters of the cardiovascular system we applied multivariate linear regression to derive from our study population of 372 adults gender-specific multivariate robustness scoring algorithms. For any individual, the deviation of his/her robustness score from the value of the regression function characterizes the deviation of the individual’s fatal CVD event probability from its age-appropriate fatal CVD event probability. Robustness correlated linearly with calendar age in our risk factor-challenged but not in our unchallenged cohorts. This observation supports the hypothesis of preferential elimination of less robust individuals along the aging trajectory under risk factor challenges. We conclude that physiologically principled scoring for vascular robustness may serve as a biomarker of vulnerability to CVD risk factor challenges, prognosticating otherwise undetectable elevated risk for premature CVD mortality. NEW & NOTEWORTHY We developed a principled method for the derivation of a vascular robustness score that we translated into a correction factor for calendar age. We demonstrated the score’s potential to uncover risk for premature cardiovascular death in apparently healthy young adults whose risk elevation remains hidden in conventional risk factor models.