Revealing the hierarchical structure of microbial communities.

Measuring the dynamics of microbial communities results in high-dimensional measurements of taxa abundances over time and space, which is difficult to analyze due to complex changes in taxonomic compositions. This paper presents a new method to investigate and visualize the intrinsic hierarchical community structure implied by the measurements. The basic idea is to identify significant intersection sets, which can be seen as sub-communities making up the measured communities. Using the subset relationship, the intersection sets together with the measurements form a hierarchical structure visualized as a Hasse diagram. Chemical organization theory (COT) is used to relate the hierarchy of the sets of taxa to potential taxa interactions and to their potential dynamical persistence. The approach is demonstrated on a data set of community data obtained from bacterial 16S rRNA gene sequencing for samples collected monthly from four groundwater wells over a nearly 3-year period (n = 114) along a hillslope area. The significance of the hierarchies derived from the data is evaluated by showing that they significantly deviate from a random model. Furthermore, it is demonstrated how the hierarchy is related to temporal and spatial factors; and how the idea of a core microbiome can be extended to a set of interrelated core microbiomes. Together the results suggest that the approach can support developing models of taxa interactions in the future.

Participation of Veterans Affairs Medical Centers in veteran-centric community-based service navigation networks: A mixed methods study.

OBJECTIVE: To understand the determinants and benefits of cross-sector partnerships between Veterans Affairs Medical Centers (VAMCs) and geographically affiliated AmericaServes Network coordination centers that address Veteran health-related social needs. DATA SOURCES AND SETTING: Semi-structured interviews were conducted with AmericaServes and VAMC staff across seven regional networks. We matched administrative data to calculate the percentage of AmericaServes referrals that were successfully resolved (i.e., requested support was provided) in each network overall and stratified by whether clients were also VAMC patients. STUDY DESIGN: Convergent parallel mixed-methods study guided by Himmelman's Developmental Continuum of Change Strategies (DCCS) for interorganizational collaboration. DATA COLLECTION: Fourteen AmericaServes staff and 17 VAMC staff across seven networks were recruited using snowball sampling and interviewed between October 2021 and April 2022. Rapid qualitative analysis methods were used to characterize the extent and determinants of VAMC participation in networks. PRINCIPAL FINDINGS: On the DCCS continuum of participation, three networks were classified as networking, two as coordinating, one as cooperating, and one as collaborating. Barriers to moving from networking to collaborating included bureaucratic resistance to change, VAMC leadership buy-in, and not having VAMCs staff use the shared technology platform. Facilitators included ongoing communication, a shared mission of serving Veterans, and having designated points-of-contact between organizations. The percentage of referrals that were successfully resolved was lowest in networks engaged in networking (65.3%) and highest in cooperating (85.6%) and collaborating (83.1%) networks. For coordinating, cooperating, and collaborating networks, successfully resolved referrals were more likely among Veterans who were also VAMC patients than among Veterans served only by AmericaServes. CONCLUSIONS: VAMCs participate in AmericaServes Networks at varying levels. When partnerships are more advanced, successful resolution of referrals is more likely, especially among Veterans who are dually served by both organizations. Although challenges to establishing partnerships exist, this study highlights effective strategies to overcome them.

To be or not to be compliant? Hospitals' initial strategic responses to the federal price transparency rule.

OBJECTIVE: To understand US hospitals' initial strategic responses to the federal price transparency rule that took effect January 2021. DATA SOURCES AND STUDY SETTING: Primary interview data collected from 12 not-for-profit hospital organizations in six US metropolitan markets. All but one organization were multihospital systems; the 12 organizations represent a total of 81 hospitals. STUDY DESIGN: Exploratory, cross-sectional, qualitative interview study of a convenience sample of hospital organizations across six geographically and compliance diverse markets. DATA COLLECTION/EXTRACTION METHODS: In-depth, semi-structured, qualitative interviews with 16 key informants across sampled organizations between November 2021 and March 2022. Interviews solicited data about internal organizational factors and external market factors affecting strategic responses. Transcribed interviews were de-identified, coded, and analyzed using the constant comparative method. PRINCIPAL FINDINGS: Hospitals' strategic responses were influenced internally by the degree of the regulation's alignment with organizational values and goals, and task complexity vis-a-vis available resources. We found extensive variation in organizational capabilities to comply, and all but one organization relied on consultants and vendors to some degree. Key external factors driving strategic responses were hospitals' variable perceptions about how available price information would affect their competitive position, bottom line, and reputation. Organizations with more confidence in their interpretation of the environment, including how peers or purchasers would behave, and greater clarity in their own organization's position and goals, had more definitive initial strategic responses. In the first year, organizations' strategic responses skewed toward compliance, especially for the rule's consumer shopping requirements. CONCLUSIONS: A deeper understanding of the realities of operationalizing price transparency policy for hospitals is needed to improve its impact.

Toward a more comprehensive understanding of organizational influences on implementation: the organization theory for implementation science framework.

Introduction: Implementation is influenced by factors beyond individual clinical settings. Nevertheless, implementation research often focuses on factors related to individual providers and practices, potentially due to limitations of available frameworks. Extant frameworks do not adequately capture the myriad organizational influences on implementation. Organization theories capture diverse organizational influences but remain underused in implementation science. To advance their use among implementation scientists, we distilled 70 constructs from nine organization theories identified in our previous work into theoretical domains in the Organization Theory for Implementation Science (OTIS) framework. Methods: The process of distilling organization theory constructs into domains involved concept mapping and iterative consensus-building. First, we recruited organization and implementation scientists to participate in an online concept mapping exercise in which they sorted organization theory constructs into domains representing similar theoretical concepts. Multidimensional scaling and hierarchical cluster analyses were used to produce visual representations (clusters) of the relationships among constructs in concept maps. Second, to interpret concept maps, we engaged members of the Cancer Prevention and Control Research Network (CPCRN) OTIS workgroup in consensus-building discussions. Results: Twenty-four experts participated in concept mapping. Based on resulting construct groupings' coherence, OTIS workgroup members selected the 10-cluster solution (from options of 7-13 clusters) and then reorganized clusters in consensus-building discussions to increase coherence. This process yielded six final OTIS domains: organizational characteristics (e.g., size; age); governance and operations (e.g., organizational and social subsystems); tasks and processes (e.g., technology cycles; excess capacity); knowledge and learning (e.g., tacit knowledge; sense making); characteristics of a population of organizations (e.g., isomorphism; selection pressure); and interorganizational relationships (e.g., dominance; interdependence). Discussion: Organizational influences on implementation are poorly understood, in part due to the limitations of extant frameworks. To improve understanding of organizational influences on implementation, we distilled 70 constructs from nine organization theories into six domains. Applications of the OTIS framework will enhance understanding of organizational influences on implementation, promote theory-driven strategies for organizational change, improve understanding of mechanisms underlying relationships between OTIS constructs and implementation, and allow for framework refinement. Next steps include testing the OTIS framework in implementation research and adapting it for use among policymakers and practitioners.

Modeling autopoiesis and cognition with reaction networks.

Maturana and Varela defined an autopoietic system as a self-regenerating network of processes. We reinterpret and elaborate this conception starting from a process ontology and its formalization in terms of reaction networks and chemical organization theory. An autopoietic organization can be modelled as a network of "molecules" (components) undergoing reactions, which is (operationally) closed and self-maintaining. Such organizations, being attractors of a dynamic system, tend to self-organize-thus providing a model for the origin of life. However, in order to survive in a variable environment, they must also be resilient, i.e. able to compensate perturbations. According to the "good regulator theorem" this requires some form of cognition, i.e. knowing which action to perform for which perturbation. Such cognition becomes more effective as it learns to anticipate perturbations by discovering invariant patterns in its interactions with the environment. Nevertheless, the resulting predictive model remains a subjective construction. Such implicit model cannot be interpreted as an objective representation of external reality, because the autopoietic system does not have direct access to that reality, and there is in general no isomorphism between internal and external processes.

The role of self-maintaining resilient reaction networks in the origin and evolution of life.

We characterize living systems as resilient "chemical organizations", i.e. self-maintaining networks of reactions that are able to resist a wide range of perturbations. Dissipative structures, such as flames or convection cells, are also self-maintaining, but much less resilient. We try to understand how life could have originated from such self-organized structures, and evolved further, by acquiring various mechanisms to increase resilience. General mechanisms include negative feedback, buffering of resources, and degeneracy (producing the same resources via different pathways). Specific mechanisms use catalysts, such as enzymes, to enable reactions that deal with specific perturbations. This activity can be regulated by "memory" molecules, such as DNA, which selectively produce catalysts when needed. We suggest that major evolutionary transitions take place when living cells of different types or species form a higher-order organization by specializing in different functions and thus minimizing interference between their reactions.

Modelling Worldviews as Stable Metabolisms.

The emergence and evolution of worldviews is a complex phenomenon that requires strong and rigorous scientific attention in our hyperconnected world. On the one hand, cognitive theories have proposed reasonable frameworks but have not reached general modeling frameworks where predictions can be tested. On the other hand, machine-learning-based applications perform extremely well at predicting outcomes of worldviews, but they rely on a set of optimized weights in a neural network that does not comply to a well-founded cognitive framework. In this article, we propose a formal approach used to investigate the establishment of and change in worldviews by recalling that the realm of ideas, where opinions, perspectives and worldviews are shaped, resemble, in many ways, a metabolic system. We propose a general modelization of worldviews based on reaction networks, and a specific starting model based on species representing belief attitudes and species representing belief change triggers. These two kinds of species combine and modify their structures through the reactions. We show that chemical organization theory combined with dynamical simulations can illustrate various interesting features of how worldviews emerge, are maintained and change. In particular, worldviews correspond to chemical organizations, meaning closed and self-producing structures, which are generally maintained by feedback loops occurring within the beliefs and triggers in the organization. We also show how, by inducing the external input of belief change triggers, it is possible to change from one worldview to another, in an irreversible way. We illustrate our approach with a simple example reflecting the formation of an opinion and a belief attitude about a theme, and, next, show a more complex scenario containing opinions and belief attitudes about two possible themes.

Increasing Access to Organization Theories for Implementation Science.

Background: Organization theories offer numerous existing, highly relevant, yet largely untapped explanations of the organizational dynamics underlying evidence-based intervention (EBI) implementation. Rooted in ideas regarding power, autonomy, and control, organization theories can explain how and why organizations adopt, implement, and sustain EBI use. Although they have gained visibility, organization theories remain underused in implementation research, perhaps due to their inaccessibility to implementation scientists. To improve access to organization theory among implementation scientists, we summarized organization theories with relevance to implementation science. Methods: Led by the Cancer Prevention and Control Research Network (CPCRN) Organization Theory for Implementation Science workgroup, we employed a modified Delphi process to reach a consensus among 18 experts at the intersection of organization and implementation science regarding organization theories with relevance to implementation science. From texts that described the organization theories, using standardized abstraction forms, two investigators independently abstracted information regarding constructs, propositions regarding how or why constructs might influence implementation, the potential relevance of organization theories' propositions for implementation, and overviews of each theory. The investigators then reconciled discrepancies until reaching consensus. A third investigator reviewed reconciled abstraction forms for accuracy, coherence, and completeness. Findings: We identified nine organization theories with relevance to implementation science: contingency, complexity, institutional, network, organizational learning, resource dependence, sociotechnical, and transaction cost economics. From the theories, we abstracted 70 constructs and 65 propositions. An example proposition from institutional theory is: "Coercive, mimetic, and normative pressures contribute to organizations…within an organizational field [becoming increasingly similar]." These propositions can be operationalized as levers to facilitate EBI implementation. Conclusions: To increase use in the field, organization theories must be made more accessible to implementation scientists. The abstraction forms developed in this study are now publicly available on the CPCRN website with the goal of increasing access to organization theories among an interdisciplinary audience of implementation scientists through the CPCRN Scholars program and other venues. Next steps include consolidating organization theory constructs into domains and translating the resulting framework for use among researchers, policymakers and practitioners, aiding them in accounting for a comprehensive set of organization theory constructs thought to influence EBI implementation.

Facilitating mindful safety practices among first-line workers in the Chinese petroleum industry through safety management practices and safety motivation.

The petroleum industry is a high-risk industry and operates under the social technical system. Therefore, the safety behavior of employees needs to be paid high attention. Thus, six dimensions of safety management practices are identified as independent variables to predict a special component of common safety behavior-mindful safety practices in the Chinese petroleum industry. High-reliability organization theory is adopted as the underpinning theory. A total 255 first-line workers from a Chinese petroleum company participated in this survey. The results reveal that safety training and safety communication and feedback are positively related to safety motivation. Moreover, workers' involvement and safety promotion policy have direct and positive impacts on mindful safety practices. Further, safety motivation is found to play a mediating role in the prediction of mindful safety practices in the Chinese petroleum industry. These findings give new insights for petroleum companies into how to promote mindful safety practices in the workplace.

Goals as Emergent Autopoietic Processes.

While the phenomena of reaching a goal is generally represented in the framework of optimization, the phenomena of becoming of a goal is more similar to a "self-organization and emergent" rather than an "optimization and preexisting" process. In this article we provide a modeling framework for the former alternative by representing goals as emergent autopoietic structures. In order to conceptually situate our approach, we first review some of the most remarkable attempts to formally define emergence, and identify that in most cases such definitions rely on a preexisting system to be observed prior and post emergence, being thus inadequate for a formalization of emergent goals corresponding to the becoming of a systems as such (e.g. emergence of life). Next, we review how an implementation of the reaction networks framework, known as Chemical Organization Theory (COT), can be applied to formalize autopoietic structures, providing a basis to operationalize goals as an emergent process. We next revisit the definitions of emergence under the light of our approach, and demonstrate that recent taxonomies developed to classify different forms of emergence can be naturally deduced from recent work aimed to explain the kinds of changes of the organizational structure of a reaction network.

Conceptual Progress for Explaining and Predicting Self-Organization on Anodized Aluminum Surfaces.

Over the past few years, researchers have made numerous breakthroughs in the field of aluminum anodizing and faced the problem of the lack of adequate theoretical models for the interpretation of some new experimental findings. For instance, spontaneously formed anodic alumina nanofibers and petal-like patterns, flower-like structures observed under AC anodizing conditions, and hierarchical pores whose diameters range from several nanometers to sub-millimeters could be explained neither by the classical field-assisted dissolution theory nor by the plastic flow model. In addition, difficulties arose in explaining the basic indicators of porous film growth, such as the nonlinear current-voltage characteristics of electrochemical cells or the evolution of hexagonal pore patterns at the early stages of anodizing experiments. Such a conceptual crisis resulted in new multidisciplinary investigations and the development of novel theoretical models, whose evolution is discussed at length in this review work. The particular focus of this paper is on the recently developed electroconvection-based theories that allowed making truly remarkable advances in understanding the porous anodic alumina formation process in the last 15 years. Some explanation of the synergy between electrode reactions and transport processes leading to self-organization is provided. Finally, future prospects for the synthesis of novel anodic architectures are discussed.

Goal Directedness, Chemical Organizations, and Cybernetic Mechanisms.

In this article, we attempt at developing a scenario for the self-organization of goal-directed systems out of networks of (chemical) reactions. Related scenarios have been proposed to explain the origin of life starting from autocatalytic sets, but these sets tend to be too unstable and dependent on their environment to maintain. We apply instead a framework called Chemical Organization Theory (COT), which shows mathematically under which conditions reaction networks are able to form self-maintaining, autopoietic organizations. We introduce the concepts of perturbation, action, and goal based on an operationalization of the notion of change developed within COT. Next, we incorporate the latter with notions native to the theory of cybernetics aimed to explain goal directedness: reference levels and negative feedback among others. To test and refine these theoretical results, we present some examples that illustrate our approach. We finally discuss how this could result in a realistic, step-by-step scenario for the evolution of goal directedness, thus providing a theoretical solution to the age-old question of the origins of purpose.

Using organization theory to position middle-level managers as agents of evidence-based practice implementation.

Middle-level managers (MLMs; i.e., healthcare professionals who may fill roles including obtaining and diffusing information, adapting information and the intervention, mediating between strategy and day-to-day activities, and selling intervention implementation) have been identified as having significant influence on evidence-based practice (EBP) implementation. We argue that understanding whether and how MLMs influence EBP implementation is aided by drawing upon organization theory. Organization theories propose strategies for increasing MLMs' opportunities to facilitate implementation by optimizing their appreciation of constructs which we argue have heretofore been treated separately to the detriment of understanding and facilitating implementation: EBPs, context, and implementation strategies. Specifically, organization theory encourages us to delineate different types of MLMs and consider how generalist and hybrid MLMs make different contributions to EBP implementation. Organization theories also suggest that MLMs' understanding of context allows them to adapt EBPs to promote implementation and effectiveness; MLMs' potential vertical linking pin role may be supported by increasing MLMs' interactions with external environment, helping them to understand strategic pressures and opportunities; and how lateral connections among MLMs have the potential to optimize their contribution to EBP implementation as a collective force. We end with recommendations for practice and future research.

Beyond planetary-scale feedback self-regulation: Gaia as an autopoietic system.

The Gaia hypothesis states that the Earth is an instance of life. However, appraisals of it tend to focus on the claim that life is a feedback self-regulator that controls Earth's chemistry and climate dynamics, yet, self-regulation by feedbacks is not a definitive characteristic of living systems. Here, we consider the characterization of biological systems as autopoietic systems (causally organized to self-produce through metabolic efficient closure) and then ask whether the Gaia hypothesis is a tractable question from this standpoint. A proof-of-concept based on Chemical Organization Theory (COT) and the Zero Deficiency Theorem (ZDT) applied on a simple but representative Earth's molecular reaction network supports the thesis of Gaia as an autopoietic system. We identify the formation of self-producing organizations within the reaction network, corresponding to recognizable scenarios of Earth's history. These results provide further opportunities to discuss how the instantiation of autopoiesis at the planetary scale could manifests central features of biological phenomenon, such as autonomy and anticipation, and what this implies for the further development of the Gaia theory, Earth's climate modelling and geoengineering.

Structure and Hierarchy of SARS-CoV-2 Infection Dynamics Models Revealed by Reaction Network Analysis.

This work provides a mathematical technique for analyzing and comparing infection dynamics models with respect to their potential long-term behavior, resulting in a hierarchy integrating all models. We apply our technique to coupled ordinary and partial differential equation models of SARS-CoV-2 infection dynamics operating on different scales, that is, within a single organism and between several hosts. The structure of a model is assessed by the theory of chemical organizations, not requiring quantitative kinetic information. We present the Hasse diagrams of organizations for the twelve virus models analyzed within this study. For comparing models, each organization is characterized by the types of species it contains. For this, each species is mapped to one out of four types, representing uninfected, infected, immune system, and bacterial species, respectively. Subsequently, we can integrate these results with those of our former work on Influenza-A virus resulting in a single joint hierarchy of 24 models. It appears that the SARS-CoV-2 models are simpler with respect to their long term behavior and thus display a simpler hierarchy with little dependencies compared to the Influenza-A models. Our results can support further development towards more complex SARS-CoV-2 models targeting the higher levels of the hierarchy.

Structure and Hierarchy of Influenza Virus Models Revealed by Reaction Network Analysis.

Influenza A virus is recognized today as one of the most challenging viruses that threatens both human and animal health worldwide. Understanding the control mechanisms of influenza infection and dynamics is crucial and could result in effective future treatment strategies. Many kinetic models based on differential equations have been developed in recent decades to capture viral dynamics within a host. These models differ in their complexity in terms of number of species elements and number of reactions. Here, we present a new approach to understanding the overall structure of twelve influenza A virus infection models and their relationship to each other. To this end, we apply chemical organization theory to obtain a hierarchical decomposition of the models into chemical organizations. The decomposition is based on the model structure (reaction rules) but is independent of kinetic details such as rate constants. We found different types of model structures ranging from two to eight organizations. Furthermore, the model's organizations imply a partial order among models entailing a hierarchy of model, revealing a high model diversity with respect to their long-term behavior. Our methods and results can be helpful in model development and model integration, also beyond the influenza area.

Rethinking Teacher Turnover: Longitudinal Measures of Instability in Schools.

While there is a robust literature examining the patterns and causes of teacher turnover, few articles to date have critically examined the measures of turnover used in these studies. Yet, an assessment of the way turnover is measured is important, as the measures become the means by which the "problem" of turnover becomes defined and its varying dimensions understood. In this conceptual essay, we outline a typology of teacher turnover measures, discussing both measures used in existing teacher turnover literature as well as new measures that we have developed. We illustrate each of the measures using 10 years of administrative data from Texas. We discuss how the measures can help illuminate different ways in which staff instability can affect schools and identify schools that suffer from particularly severe staffing issues. We conclude with implications for policymakers and researchers who may seek to apply these measures to future empirical studies.

Firms, crowds, and innovation.

The purpose of this article is to suggest a (preliminary) taxonomy and research agenda for the topic of "firms, crowds, and innovation" and to provide an introduction to the associated special issue. We specifically discuss how various crowd-related phenomena and practices-for example, crowdsourcing, crowdfunding, user innovation, and peer production-relate to theories of the firm, with particular attention on "sociality" in firms and markets. We first briefly review extant theories of the firm and then discuss three theoretical aspects of sociality related to crowds in the context of strategy, organizations, and innovation: (1) the functions of sociality (sociality as extension of rationality, sociality as sensing and signaling, sociality as matching and identity), (2) the forms of sociality (independent/aggregate and interacting/emergent forms of sociality), and (3) the failures of sociality (misattribution and misapplication). We conclude with an outline of future research directions and introduce the special issue papers and essays.

Hospital Characteristics are Associated With Readiness to Attain Stage 2 Meaningful Use of Electronic Health Records.

PURPOSE: To examine the difference between rural and urban hospitals as to their overall level of readiness for stage 2 meaningful use of electronic health records (EHRs) and to identify other key factors that affect their readiness for stage 2 meaningful use. METHODS: A conceptual framework based on the theory of organizational readiness for change was used in a cross-sectional multivariate analysis using 2,083 samples drawn from the HIMSS Analytics survey conducted with US hospitals in 2013. FINDINGS: Rural hospitals were less likely to be ready for stage 2 meaningful use compared to urban hospitals in the United States (OR = 0.49) in our final model. Hospitals' past experience with an information exchange initiative, staff size in the information system department, and the Chief Information Officer (CIO)'s responsibility for health information management were identified as the most critical organizational contextual factors that were associated with hospitals' readiness for stage 2. Rural hospitals lag behind urban hospitals in EHR adoption, which will hinder the interoperability of EHRs among providers across the nation. The identification of critical factors that relate to the adoption of EHR systems provides insights into possible organizational change efforts that can help hospitals to succeed in attaining meaningful use requirements. CONCLUSION: Rural hospitals have increasingly limited resources, which have resulted in a struggle for these facilities to attain meaningful use. Given increasing closures among rural hospitals, it is all the more important that EHR development focus on advancing rural hospital quality of care and linkages with patients and other organizations supporting the care of their patients.

Research on Harmonious Doctor-patient Relationship from the Perspective of Harmonious Management Organization Theory / 中国医学伦理学

Through the analysis of current situation of the tension relationship between doctor and patient,this paper expounded that the harmonious management organization theory took the cooperation order as the core of the development of the group organization,and emphasized the running-in process of the internal staffs in the collective group.And it pointed out that the internal cooperation between doctor and patient had the certain cooperation order,and also had obstacles that might cause conflict in cooperation from the perspective of the harmonious management organization theory.This paper analyzed and understood the process of doctor-patient coordination at the group level of harmonious management organization theory,explored and analyzed the obstacles that might cause the conflict during the cooperation process and the reasons in the view of innovation,explored and concluded relevant measures to ease the tension of the doctor-patient relationship,and finally achieved the outcome of maximization of common interests and optimization of treatment effect.