Contrasting perspectives of strategy making: applications in 'Hyper' environments

We revisit the original meaning of turbulence in the socioecological tradition of organization studies and outline a perspective on strategy making grounded in that tradition. This entails a contrast of the socioecological perspective with the more well-known neoclassical perspective on strategy, based on their core decision premises and their different understandings of environmental turbulence. We argue that while some mainstream strategy approaches have taken important strides toward addressing advanced turbulence, many others remain tethered to the neoclassical origins of the strategy discipline and are insufficiently responsive to the new landscape of strategy that now characterizes many industries. This new landscape is construed as the ‘hyper environment’, in which positive feedback processes and emergent field effects produce high volatility. We use two case illustrations from the US healthcare sector to examine how neoclassical and socioecological perspectives contribute to strategizing in hyper environments. Implications for strategic management theory and practice flow from this analysis

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment

Effects of a Web-Based Intervention for Adults with Chronic Conditions on Patient Activation: Online Randomized Controlled Trial

BACKGROUND: With almost one-half of Americans projected to have at least one chronic condition before 2020, a vital role of the health care system is to develop informed, engaged individuals who are effective self-managers of their health. Self-management interventions (SMIs) delivered face-to-face or by telephone (traditional SMIs) are associated with improved self-management knowledge, skills, and self-efficacy, which are expressed by the composite construct of patient activation, a predictor of health outcomes. Web-based interventions to support self-management across the spectrum of chronic diseases have the potential to reach a broader population of patients for extended periods than do traditional SMIs. However, evidence of the effectiveness of Web-based interventions on patient activation is sparse. High-quality studies featuring controlled comparisons of patients with different chronic conditions are needed to explore the interaction of Web-based interventions and patient activation. OBJECTIVE: To explore the effect of a Web-based intervention on the patient activation levels of patients with chronic health conditions, measured as attitudes toward knowledge, skills, and confidence in self-managing health. METHODS: For this 12-week study, prospective participants were selected from the patient panel of a regional health care system in the United States. The 201 eligible participants were randomly assigned to two groups. Intervention group participants had access to MyHealth Online, a patient portal featuring interactive health applications accessible via the Internet. Control participants had access to a health education website featuring various topics. Patient activation was assessed pre- and posttest using the 13-item patient activation measure. Parametric statistical models (t test, analysis of variance, analysis of covariance) were applied to draw inferences. RESULTS: The Web-based intervention demonstrated a positive and significant effect on the patient activation levels of participants in the intervention group. A significant difference in posttest patient activation scores was found between the two groups (F(1,123) = 4.438, P = .04, r = .196). Patients starting at the most advanced development of patient activation (stage 4) in the intervention group did not demonstrate significant change compared with participants beginning at earlier stages. CONCLUSIONS: To our knowledge, this is the first study to measure change in patient activation when a Web-based intervention is used by patients living with different chronic conditions. Results suggest that Web-based interventions increase patient activation and have the potential to enhance the self-management capabilities of the growing population of chronically ill people. Activated patients are more likely to adhere to recommended health care practices, which in turn leads to improved health outcomes. Designing Web-based interventions to target a specific stage of patient activation may optimize their effectiveness. For Web-based interventions to reach their potential as a key component of chronic disease management, evidence is needed that this technology produces benefits for a sustained period among a diverse population