Cognitive dissonance and mindset perturbations during crisis: "eco-socio-psycho-somatic" perspectives.

Mandatory and restrictive health regulations during the corona pandemic caused psychic disorders in many people, which even led to clinically relevant mental disorders. At the same time, there was gradually a polarization of opinions among the population. In order to improve future pandemic management, an integrative understanding of these psychosocial processes therefore seems useful. Here we start theoretically with the mental effects of inconsistencies of the information environment by referring to concepts such as the theory of cognitive dissonance. In a next step, we use the psychodynamic theory to understand the affective-motivational defense mechanisms underlying these cognitive states and processes. However, a broader theoretical framework of psychoanalysis seems to make sense, because self-referential processing also influences the style of thinking. For this reason, we use a more comprehensive psychological systems theoretical framework model to integrate these different perspectives. This integrative view refers in part to basic knowledge of health psychology regarding the resistance of unhealthy ways of thinking and behaviors and the possibilities for interventions for change. We then extend this model to a broader picture that also covers the relationship between men and their environment. This results in the perspective of a multidimensional socioecological theoretical framework, which as a heuristic reference model and related to other ecological approaches could also be helpful for various theoretical questions for public health, and could provide a better public understanding of health issues. In line with this perspective, we hypothesize that with regard to the coronavirus disease 2019 pandemic, the acceptance of public health narratives could be increased if a more consistent picture of the scientific descriptions and explanations of the pandemic - similar to the model proposed - could be provided, which would enable the understanding of the origin, course and countermeasures, and thus could have positive collective psycho-hygienic effects.

'Medical Corona Science': Philosophical and systemic issues: Re-thinking medicine? On the epistemology of Corona medicine.

RATIONALE, AIMS, AND OBJECTIVES: The disciplinary profile and the quality of production of knowledge on Corona pandemic is studied. This scientific field is called 'Medical Corona Science'. METHODS: Criteria of analytical philosophy of science and science studies are systematically applied. RESULTS: It is shown that mainly auxiliary medical disciplines such as virology and epidemiology but not clinical disciplines provide Corona knowledge. We see a laboratory-centered, technology- and data-driven science, largely ignoring clinical issues. Therefore we call these approaches "Medical Corona Science" (MCS). We see the need to adapt to features of a 'post-normal science', a 'mode 2 science' and of 'Integration and Implementation Science', especially as clinical knowledge must be integrated. There is also a severe lack of theoretical considerations that could help to frame the pandemic as a complex dynamic system. CONCLUSIONS: We suggest a deeper meta-scientific discussion of the epistemic value of MCS and propose the application of tools from systems science.

Perspectives of (/memorandum for) systems thinking on COVID-19 pandemic and pathology.

Is data-driven analysis sufficient for understanding the COVID-19 pandemic and for justifying public health regulations? In this paper, we argue that such analysis is insufficient. Rather what is needed is the identification and implementation of over-arching hypothesis-related and/or theory-based rationales to conduct effective SARS-CoV2/COVID-19 (Corona) research. To that end, we analyse and compare several published recommendations for conceptual and methodological frameworks in medical research (e.g., public health, preventive medicine and health promotion) to current research approaches in medical Corona research. Although there were several efforts published in the literature to develop integrative conceptual frameworks before the COVID-19 pandemic, such as social ecology for public health issues and systems thinking in health care, only a few attempts to utilize these concepts can be found in medical Corona research. For this reason, we propose nested and integrative systemic modelling approaches to understand Corona pandemic and Corona pathology. We conclude that institutional efforts for knowledge integration and systemic thinking, but also for integrated science, are urgently needed to avoid or mitigate future pandemics and to resolve infection pathology.

Toward a big picture of COVID-19.

The paper aims to illustrate and explain the problems and opportunities for improvement in Covid management that become evident when taking a systems perspective. Critical time delays occurred in the regulation of the pandemic that the management cycle of political cybernetics makes explicit. In general, the executive management of the pandemic in global, regional, and national organizations was unprepared in detecting and responding to the onset of the waves and making appropriate decisions towards differential instead of general lockdowns based on available data. This was further complicated by the mutants of SARS-CoV2 that perpetuated the high dynamics of the pandemic. In addition, the diversity of medical specialisms, without appropriate big picture thinking, led to an imbalanced response that failed to appreciate the role of virology and epidemiology compared to clinical and public health-related issues. In consequence, laboratory experts suggested everyday regulations for the citizens without taking into account wider considerations for empirical research. There was an insufficient effort made for proposed treatment studies using existing agents based on the established understanding of essential physiology and the role of local and systemic chronic inflammation. In contrast, driven by media popularization, drugs that later proved beneficial were put in doubt and other drugs that lacked benefit and potentially caused harm were driven to clinical trials and utilization. Person-centered systems view backed by scientific knowledge and established data would have set better priorities. Finally, we need to take a step back and consider the Corona crisis pandemic in the context of the unidimensional utility-driven handling of natural ecosystems by the culture of industrialized countries. This ever-accelerating destruction of life spaces for species drives adaptations are the basis of zoonoses. There is strong evidence that future pandemics should be faced with a more systemic socio-ecological conceptual framework that also reflects the fatal impact of human civilization on natural ecosystems, no matter if SARS CoV2 is a zoonosis or a laboratory accident. It is critical for the future of our species that we collectively learn from this experience, address limitations in our perspectives, enhance our system-based science and bolster global, regional, and national crisis management. The impact of climate change and biodiversity loss has crossed the horizon and is now clearly in full sight.

Systems analysis shows that thermodynamic physiological and pharmacological fundamentals drive COVID-19 and response to treatment.

Why a systems analysis view of this pandemic? The current pandemic has inflicted almost unimaginable grief, sorrow, loss, and terror at a global scale. One of the great ironies with the COVID-19 pandemic, particularly early on, is counter intuitive. The speed at which specialized basic and clinical sciences described the details of the damage to humans in COVID-19 disease has been impressive. Equally, the development of vaccines in an amazingly short time interval has been extraordinary. However, what has been less well understood has been the fundamental elements that underpin the progression of COVID-19 in an individual and in populations. We have used systems analysis approaches with human physiology and pharmacology to explore the fundamental underpinnings of COVID-19 disease. Pharmacology powerfully captures the thermodynamic characteristics of molecular binding with an exogenous entity such as a virus and its consequences on the living processes well described by human physiology. Thus, we have documented the passage of SARS-CoV-2 from infection of a single cell to species jump, to tropism, variant emergence and widespread population infection. During the course of this review, the recurrent observation was the efficiency and simplicity of one critical function of this virus. The lethality of SARS-CoV-2 is due primarily to its ability to possess and use a variable surface for binding to a specific human target with high affinity. This binding liberates Gibbs free energy (GFE) such that it satisfies the criteria for thermodynamic spontaneity. Its binding is the prelude to human host cellular entry and replication by the appropriation of host cell constituent molecules that have been produced with a prior energy investment by the host cell. It is also a binding that permits viral tropism to lead to high levels of distribution across populations with newly formed virions. This thermodynamic spontaneity is repeated endlessly as infection of a single host cell spreads to bystander cells, to tissues, to humans in close proximity and then to global populations. The principal antagonism of this process comes from SARS-CoV-2 itself, with its relentless changing of its viral surface configuration, associated with the inevitable emergence of variants better configured to resist immune sequestration and importantly with a greater affinity for the host target and higher infectivity. The great value of this physiological and pharmacological perspective is that it reveals the fundamental thermodynamic underpinnings of SARS-CoV-2 infection.

How does the 'environment' come to the person? The 'ecology of the person' and addiction.

Currently, psychiatry lacks a field that can be called "theoretical psychiatry", which uses theoretical concepts and explanatory models: The main stream of research is to collect data of all kinds in the hope that the computational Big Data approach will shed a bright light on the black box of mental disorders. Accordingly, the biology-based Research Domain Criteria of the National Institute of Mental Health have been established. However, as philosophical analyses of concepts and methods have shown, several epistemological gaps stand in the way of a consistent multilevel understanding of mental disorders. Also, the implicit ontological problems in the biological reduction of the psychosocial level and in the integration of so-called hard and soft disciplines are mostly left out. As a consequence, a non-reductive psychological theory of mental disorders is sought that also integrates correlating biological and sociological issues. In this context, one example of promising nonreductive psychiatric research is the option of systems/network psychopathology. The possibilities for integrating different psychological perspectives are highlighted for the field of addiction research and treatment, where pragmatic behaviorist approaches dominate over the theory-based practice of psychoanalysis. In comparing the theoretical constructs of these two approaches, the relevance of the concept of "(social) environment" as the wealth of influential sociocultural factors is discussed at levels superior to the interpersonal micro-level, namely the organizational meso- and societal macro level, which is not sufficiently considered in current biopsychiatry. On this basis of argumentation, the usefulness of grounding and framing psychiatry through the field of ecological sciences, especially human ecology, is demonstrated. Finally, to this end, an outline of an ecological model of mental health and illness is presented.

The Quest for System-Theoretical Medicine in the COVID-19 Era.

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum.

The Human Ecological Perspective and Biopsychosocial Medicine.

With regard to philosophical anthropology, a human ecological framework for the human-environment relationship as an "ecology of the person" is outlined, which focuses on the term "relationship" and aims to be scientifically sound. It also provides theoretical orientations for multiprofessional clinical work. For this purpose, a multi-dimensional basic grid for the characterization of the individual human being is proposed. The necessity and meaningfulness of a differentiation and systematization of the terms "environment", and above all "relationship", are demonstrated, and practical examples and links to similar framework models are given.

Medical knowledge integration and "systems medicine": Needs, ambitions, limitations and options.

Medicine today is an extremely heterogeneous field of knowledge, based on clinical observations and action knowledge and on data from the biological, behavioral and social sciences. We hypothesize at first that medicine suffers from a disciplinary hyper-diversity compared to the level of conceptual interdisciplinary integration. With the claim to "understand" and cure diseases, currently with the label "Systems Medicine" new forms of molecular medicine promise a general new bottom-up directed precise, personalized, predictive, preventive, translational, participatory, etc. medicine. Our second hypothesis rejects this claim because of conceptual, methodological and theoretical weaknesses. In contrary, this is our third hypothesis; we suggest that top-down organismic systems medicine, related to general system theory, opens better options for an integrative scientific understanding of processes of health and disease.

From mind to molecules and back to mind-Metatheoretical limits and options for systems neuropsychiatry.

Psychiatric illnesses like dementia are increasingly relevant for public health affairs. Neurobiology promises progress in diagnosis and treatment of these illnesses and exhibits a rapid increase of knowledge by new neurotechnologies. In order to find generic patterns in huge neurobiological data sets and by exploring formal brain models, non-linear science offers many examples of fruitful insights into the complex dynamics of neuronal information processing. However, it should be minded that neurobiology neither can bridge the explanatory gap between brain and mind nor can substitute psychological and psychiatric categories and knowledge. For instance, volition is impaired in many mental disorders. In experimental setups, a "preactional" brain potential was discovered that occurs 0.5 s before a consciously evoked motor action. Neglecting the specific experimental conditions, this finding was over-interpreted as the empirical falsification of the philosophical (!) concept of "free volition/will." In contrast, the psychology of volition works with models that are composed of several stage-related hierarchically nested mental process cycles that were never tested in obviously "theory-free" neurobiology. As currently neurobiology shows a network turn (or systemic turn), this is one good reason to enhance systemic approaches in theoretical psychology, independently from neurobiology that still lacks "theory." Cybernetic control loop models and system models should be integrated and elaborated and in turn could give new impulses to neuropsychology and neuropsychiatry that conceptually can more easily connect to a network-oriented neurobiology. In this program, the conceptual background of nonlinear science is essential to bridge gaps between neurobiology and psychiatry, defining a real "theoretical" field of neuropsychiatry.

Steps Toward an Integrative Clinical Systems Psychology.

Clinical fields of the "sciences of the mind" (psychotherapy, psychiatry, etc.) lack integrative conceptual frameworks that have explanatory power. Mainly descriptive-classificatory taxonomies like DSM dominate the field. New taxonomies such as Research Domain Criteria (RDoC) aim to collect scientific knowledge regarding "systems" for "processes" of the brain. These terms have a supradisciplinary" meaning if they are considered in context of Systems Science. This field emerges as a platform of theories like general systems theory, catastrophe theory, synergetics, chaos theory, etc. It provides a lot of abstract concepts, constructs, methods and models. We assume that these tools also enable theoretical integration in the diversified field of clinical practice in the sciences of the mind. Additionally, systems thinking in clinical psychology improves conceptual links to currently network-oriented neurobiology. However, clear definitions of systemic terms are necessary to emerge from their mainly metaphorical use. Here we revise mainly terms like "structure", "process" and "dynamics" as they are used already in psychology, psychoanalysis, psychopathology and psychiatry in an ill-defined way. For instance, affective-cognitive structures like "life space" or "object representations" can be seen as products of mental processing. These structures, in turn, modulate dynamics of mental processes. Additionally, we suggest a coupled network concept of emotions and motivations as the main subsystem that modulates mental dynamics that results in a qualitative systemic model of the mind. Finally, we assume that a revisited systemic approach could improve interdisciplinary understanding of the mental.

Methodological Problems on the Way to Integrative Human Neuroscience.

Neuroscience is a multidisciplinary effort to understand the structures and functions of the brain and brain-mind relations. This effort results in an increasing amount of data, generated by sophisticated technologies. However, these data enhance our descriptive knowledge, rather than improve our understanding of brain functions. This is caused by methodological gaps both within and between subdisciplines constituting neuroscience, and the atomistic approach that limits the study of macro- and mesoscopic issues. Whole-brain measurement technologies do not resolve these issues, but rather aggravate them by the complexity problem. The present article is devoted to methodological and epistemic problems that obstruct the development of human neuroscience. We neither discuss ontological questions (e.g., the nature of the mind) nor review data, except when it is necessary to demonstrate a methodological issue. As regards intradisciplinary methodological problems, we concentrate on those within neurobiology (e.g., the gap between electrical and chemical approaches to neurophysiological processes) and psychology (missing theoretical concepts). As regards interdisciplinary problems, we suggest that core disciplines of neuroscience can be integrated using systemic concepts that also entail human-environment relations. We emphasize the necessity of a meta-discussion that should entail a closer cooperation with philosophy as a discipline of systematic reflection. The atomistic reduction should be complemented by the explicit consideration of the embodiedness of the brain and the embeddedness of humans. The discussion is aimed at the development of an explicit methodology of integrative human neuroscience, which will not only link different fields and levels, but also help in understanding clinical phenomena.

A heuristic model for working memory deficit in schizophrenia.

BACKGROUND: The life of schizophrenia patients is severely affected by deficits in working memory. In various brain regions, the reciprocal interactions between excitatory glutamatergic neurons and inhibitory GABAergic neurons are crucial. Other neurotransmitters, in particular dopamine, serotonin, acetylcholine, and norepinephrine, modulate the local balance between glutamate and GABA and therefore regulate the function of brain regions. Persistent alterations in the balances between the neurotransmitters can result in working memory deficits. METHODS: Here we present a heuristic computational model that accounts for interactions among neurotransmitters across various brain regions. The model is based on the concept of a neurochemical interaction matrix at the biochemical level and combines this matrix with a mobile model representing physiological dynamic balances among neurotransmitter systems associated with working memory. RESULTS: The comparison of clinical and simulation results demonstrates that the model output is qualitatively very consistent with the available data. In addition, the model captured how perturbations migrated through different neurotransmitters and brain regions. Results showed that chronic administration of ketamine can cause a variety of imbalances, and application of an antagonist of the D2 receptor in PFC can also induce imbalances but in a very different manner. CONCLUSIONS: The heuristic computational model permits a variety of assessments of genetic, biochemical, and pharmacological perturbations and serves as an intuitive tool for explaining clinical and biological observations. GENERAL SIGNIFICANCE: The heuristic model is more intuitive than biophysically detailed models. It can serve as an important tool for interdisciplinary communication and even for psychiatric education of patients and relatives. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

A heuristic model of alcohol dependence.

BACKGROUND: Substance dependence poses a critical health problem. Sadly, its neurobiological mechanisms are still unclear, and this lack of real understanding is reflected in insufficient treatment options. It has been hypothesized that alcohol effects are due to an imbalance between neuroexcitatory and neuroinhibitory amino acids. However, glutamate and GABA interact with other neurotransmitters, which form a complicated network whose functioning evades intuition and should be investigated systemically with methods of biomedical systems analysis. METHODS AND RESULTS: We present a heuristic model of neurotransmitters that combines a neurochemical interaction matrix at the biochemical level with a mobile describing the balances between pairs of neurotransmitters at the physiological and behavioral level. We investigate the effects of alcohol on the integrated neurotransmitter systems at both levels. The model simulation results are consistent with clinical and experimental observations. The model demonstrates that the drug diazepam for symptoms of alcohol withdrawal effectively reduces the imbalances between neurotransmitters. Moreover, the acetylcholine signal is suggested as a novel target for treatment of symptoms associated with alcohol withdrawal. CONCLUSIONS: Efficient means of integrating clinical symptoms across multiple levels are still scarce and difficult to establish. We present a heuristic model of systemic neurotransmitter functionality that permits the assessment of genetic, biochemical, and pharmacological perturbations. The model can serve as a tool to represent clinical and biological observations and explore various scenarios associated with alcohol dependence and its treatments. It also is very well suited for educational purposes.

Systems biology in psychiatric research: from complex data sets over wiring diagrams to computer simulations.

The classification of psychiatric disorders has always been a problem in clinical settings. The present debate about the major systems in clinical practice, DSM-IV and ICD-10, has resulted in attempts to improve and replace those schemes by some that include more endophenotypic and molecular features. However, these disorders not only require more precise diagnostic tools, but also have to be viewed more extensively in their dynamic behaviors, which require more precise data sets related to their origins and developments. This enormous challenge in brain research has to be approached on different levels of the biological system by new methods, including improvements in electroencephalography, brain imaging, and molecular biology. All these methods entail accumulations of large data sets that become more and more difficult to interpret. In particular, on the molecular level, there is an apparent need to use highly sophisticated computer programs to tackle these problems. Evidently, only interdisciplinary work among mathematicians, physicists, biologists, and clinicians can further improve our understanding of complex diseases of the brain.

Psychopathological changes and quality of life in hepatitis C virus-infected, opioid-dependent patients during maintenance therapy.

AIMS: To examine among maintenance patients (methadone or buprenorphine) with and without hepatitis C virus (HCV) infection (i) the frequency of psychopathological symptoms at baseline and 1-year follow-up; (ii) the association between antiviral interferon (IFN) treatment and psychopathological symptoms; and (iii) to explore whether IFN therapy has an effect on 1-year outcome of maintenance treatment. DESIGN: Naturalistic prospective longitudinal cohort design. SETTING: A total of 223 substitution centres in Germany. PARTICIPANTS: A nationally representative sample of 2414 maintenance patients, namely 800 without and 1614 with HCV infection, of whom 122 received IFN therapy. MEASURES: HCV infection (HCV+/HCV-), IFN (IFN+/IFN-) treatment status and clinical measures. Diagnostic status and severity (rated by clinician), psychopathology (BSI--Brief Symptom Inventory) and quality of life (EQ-5D--EuroQol Group questionnaire). FINDINGS: HCV+ patients revealed indications for a moderately increased psychopathological burden and poorer quality of life at baseline and follow-up compared to HCV- patients. HCV+ patients showed a marked deterioration over time only in the BSI subscale somatization (P = 0.002), and the frequency of sleep disorders almost doubled over time (12.8% at baseline; 24.1% at follow-up; P < 0.01). IFN treatment, received by 10% of HCV+ patients, did not impair efficacy or tolerability of maintenance therapy and was associated overall with neither increased psychopathological burden nor reduced quality of life. CONCLUSIONS: Findings suggest no increased risk among HCV+ patients on maintenance therapy for depressive or other psychopathological syndromes. In our patient sample, IFN treatment was not associated with increased psychopathological burden, reduced quality of life or poorer tolerability and efficacy of maintenance treatment.

["Homo neurobiologicus"--anthropological concepts in modern psychiatry]. / Homo neurobiologicus--Menschenbilder in der modernen Psychiatrie.

The workings of the human brain can now be studied with a large arsenal of modern technical tools which lead us far beyond traditional realms of philosophical self-reflection and conventional experimental psychology. The black box of the human mind has become illuminated with the following consequences: (1) diagnosis and monitoring of mental and neurological diseases have improved significantly; and (2) early interpretations of the brain's workings as we can now see it, influence the way we think and feel about ourselves. They form an inevitable part of modern anthropology, particularly in its applied forms, e.g. psychiatry and psychotherapy. Conservative branches of human studies may be appalled by nimble neuroscientists who suddenly claim superior evidence and authority. It is an open question whether these schools of traditional and of revolutionary data acquisition and thought will find a common language which can also be translated into clinically useful concepts.

The systems view in addiction research.

The wealth of information accessible on the molecular level after completion of sequencing of the human and other genomes and in conjunction with new high-throughput technologies like microarrays has paved the way for research on whole systems rather than on single components. Here we describe exemplarily the construction of a rather complex molecular network involved in alcohol addiction by using information from DNA-microarray studies in alcohol-dependent animals. In this network, haemoglobin downregulation in different parts of the brain reward system plays a central role in affecting synaptic plasticity, circadian rhythmicity and opioid receptors. Furthermore, we discuss the dynamic aspect of biological systems with respect to repeated and intermittent drug intake. This aspect can best be captured by the allostatic model on the molecular level. Using a molecular oscillator model where levels of oscillations are changed by repetitive drug administration, changes in set point adjustment are described that underlay allostatic shifts in drug reinforcement processes.

Feasibility and outcome of substitution treatment of heroin-dependent patients in specialized substitution centers and primary care facilities in Germany: a naturalistic study in 2694 patients.

BACKGROUND: In many countries, buprenorphine and methadone are licensed for the maintenance treatment (MT) of opioid dependence. Despite many short-term studies, little is known about the long-term (12-month) effects of these treatments in different settings, i.e. primary care-based (PMC) and specialized substitution centers (SSCs). OBJECTIVES: To describe over a period of 12 months: (1) mortality, retention and abstinence rates; (2) changes in concomitant drug use, somatic and mental health; and (3) to explore differences between different types of provider settings. METHODS: 12-Month prospective-longitudinal naturalistic study with four waves of assessment in a prevalence sample of N=2694 maintenance patients, recruited from a nationally representative sample of N=223 substitution physicians. RESULTS: The 12-month retention rate was 75%; the mortality rate 1.1%. 4.1% of patients became "abstinent" during follow-up. 7% were referred to drug-free addiction treatment. Concomitant drug use decreased and somatic health status improved. No significant improvements were observed for mental health and quality of life. When controlling for initial severity, small PMC settings revealed better retention, abstinence and concomitant drug use rates. CONCLUSION: The study underlines the overall 12-month effectiveness of various forms of agonist MT. Findings reveal relatively high retention rates, low mortality rates, and improvements in most 12-month outcome domains, except for mental health and quality of life. PMC settings appear to be a good additional option to improve access to MTs.