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Academic Medicine : Journal of the... Sep 2023Technology-enhanced simulation has been used to tackle myriad challenges within health professions education. Recently, work has typically adopted a mastery learning...
Technology-enhanced simulation has been used to tackle myriad challenges within health professions education. Recently, work has typically adopted a mastery learning orientation that emphasizes trainees' sequential mastery of increasingly complex material. Doing so has privileged a focus on performance and task completion, as captured by trainees' observable behaviors and actions. Designing simulation in these ways has provided important advances to education, clinical care, and patient safety, yet also placed constraints around how simulation-based activities were enacted and learning outcomes were measured. In tracing the contemporary manifestations of simulation in health professions education, this article highlights several unintended consequences of this performance orientation and draws from principles of adaptive expertise to suggest new directions. Instructional approaches grounded in adaptive expertise in other contexts suggest that uncertainty, struggle, invention, and even failure help learners to develop deeper conceptual understanding and learn innovative approaches to novel problems. Adaptive expertise provides a new lens for simulation designers to think intentionally around how idiosyncrasy, individuality, and inventiveness could be enacted as central design principles, providing learners with opportunities to practice and receive feedback around the kinds of complex problems they are likely to encounter in practice. Fostering the growth of adaptive expertise through simulation will require a fundamental reimagining of the design of simulation scenarios, embracing the power of uncertainty and ill-defined problem spaces, and focusing on the structure and pedagogical stance of debriefing. Such an approach may reveal untapped potential within health care simulation.
Topics: Humans; Learning; Feedback; Delivery of Health Care; Computer Simulation; Clinical Competence
PubMed: 37094295
DOI: 10.1097/ACM.0000000000005257 -
Methods in Molecular Biology (Clifton,... 2024We briefly present machine learning approaches for designing better biological experiments. These approaches build on machine learning predictors and provide additional...
We briefly present machine learning approaches for designing better biological experiments. These approaches build on machine learning predictors and provide additional tools to guide scientific discovery. There are two different kinds of objectives when designing better experiments: to improve the predictive model or to improve the experimental outcome. We survey five different approaches for adaptive experimental design that iteratively search the space of possible experiments while adapting to measured data. The approaches are Bayesian optimization, bandits, reinforcement learning, optimal experimental design, and active learning. These machine learning approaches have shown promise in various areas of biology, and we provide broad guidelines to the practitioner and links to further resources.
Topics: Bayes Theorem; Machine Learning; Research Design
PubMed: 38468097
DOI: 10.1007/978-1-0716-3658-9_19 -
Statistics in Medicine Dec 2023Interest in incorporating historical data in the clinical trial has increased with the rising cost of conducting clinical trials. The intervention arm for the current...
Interest in incorporating historical data in the clinical trial has increased with the rising cost of conducting clinical trials. The intervention arm for the current trial often requires prospective data to assess a novel treatment, and thus borrowing historical control data commensurate in distribution to current control data is motivated in order to increase the allocation ratio to the current intervention arm. Existing historical control borrowing adaptive designs adjust allocation ratios based on the commensurability assessed through study-level summary statistics of the response agnostic of the distributions of the trial subject characteristics in the current and historical trials. This can lead to distributional imbalance of the current trial subject characteristics across the treatment arms as well as between current control data and borrowed historical control data. Such covariate imbalance may threaten the internal validity of the current trial by introducing confounding factors that affect study endpoints. In this article, we propose a Bayesian design which borrows and updates the treatment allocation ratios both covariate-adaptively and commensurate to covariate dependently assessed similarity between the current and historical control data. We employ covariate-dependent discrepancy parameters which are allowed to grow with the sample size and propose a regularized local regression procedure for the estimation of the parameters. The proposed design also permits the current and the historical controls to be similar to varying degree, depending on the subject level characteristics. We evaluate the proposed design extensively under the settings derived from two placebo-controlled randomized trials on vertebral fracture risk in post-menopausal women.
Topics: Female; Humans; Bayes Theorem; Computer Simulation; Prospective Studies; Research Design; Sample Size; Clinical Trials as Topic
PubMed: 37750361
DOI: 10.1002/sim.9913 -
Artificial Life Aug 2023Plants thrive in virtually all natural and human-adapted environments and are becoming popular models for developing robotics systems because of their strategies of...
Plants thrive in virtually all natural and human-adapted environments and are becoming popular models for developing robotics systems because of their strategies of morphological and behavioral adaptation. Such adaptation and high plasticity offer new approaches for designing, modeling, and controlling artificial systems acting in unstructured scenarios. At the same time, the development of artifacts based on their working principles reveals how plants promote innovative approaches for preservation and management plans and opens new applications for engineering-driven plant science. Environmentally mediated growth patterns (e.g., tropisms) are clear examples of adaptive behaviors displayed through morphological phenotyping. Plants also create networks with other plants through subterranean roots-fungi symbiosis and use these networks to exchange resources or warning signals. This article discusses the functional behaviors of plants and shows the close similarities with a perceptron-like model that could act as a behavior-based control model in plants. We begin by analyzing communication rules and growth behaviors of plants; we then show how we translated plant behaviors into algorithmic solutions for bioinspired robot controllers; and finally, we discuss how those solutions can be extended to embrace original approaches to networking and robotics control architectures.
Topics: Humans; Robotics; Neural Networks, Computer; Plants; Adaptation, Physiological
PubMed: 36787453
DOI: 10.1162/artl_a_00396 -
Global Health, Science and Practice Dec 2023The RF approach is a framework of intervention development that aims to collect timely data that serve as feedback and provide flexibility, agility, and adaptability to...
The RF approach is a framework of intervention development that aims to collect timely data that serve as feedback and provide flexibility, agility, and adaptability to intervention planners and implementers to make changes that enhance their success.
PubMed: 38110199
DOI: 10.9745/GHSP-D-23-00450 -
IEEE Transactions on Neural Networks... Aug 2023Data augmentation has been observed playing a crucial role in achieving better generalization in many machine learning tasks, especially in unsupervised domain...
Data augmentation has been observed playing a crucial role in achieving better generalization in many machine learning tasks, especially in unsupervised domain adaptation (DA). It is particularly effective on visual object recognition tasks as images are high-dimensional with an enormous range of variations that can be simulated. Existing data augmentation techniques, however, are not explicitly designed to address the differences between different domains. Expert knowledge about the data is required, as well as manual efforts in finding the optimal parameters. In this article, we propose a novel domain-adaptive augmentation method by making use of a state-of-the-art style transfer method and domain discrepancy measurement. Specifically, we measure the discrepancy between source and target domains, and use it as a guide to augment the original source samples using style transferred source-to-target samples. The proposed domain-adaptive augmentation method is data and model agnostic that can be easily incorporated with state-of-the-art DA algorithms. We show empirically that, by using this domain-adaptive augmentation, we are able to gradually reduce the discrepancy between the source and target samples, and further boost the adaptation performance using different DA algorithms on three popular domain adaption datasets.
PubMed: 34874869
DOI: 10.1109/TNNLS.2021.3128401 -
Journal of Thermal Biology Aug 2023Given the increasing trend of global warming and extreme weather conditions, including heat waves and its effects on health, the present study was done to investigate... (Review)
Review
BACKGROUND
Given the increasing trend of global warming and extreme weather conditions, including heat waves and its effects on health, the present study was done to investigate adaptive behaviors of communities in the world for combating heat waves.
METHOD
ology: In this systematic review, out of 1529 results, 57 relevant and authoritative English papers on adaptation to heat waves hazard were extracted and evaluated using valid keywords from valid databases (PubMed, WOS, EMBASE, and Scopus). In addition, multiple screening steps were done and then, the selected papers were qualitatively assessed. Evaluation results were summarized using an Extraction Table.
RESULTS
In this paper, the adaptive behaviors for combating heat waves hazard were summarized into 11 categories: Education and awareness raising, Adaptation of critical infrastructure, Governments measures, Health-related measures, Application of early warning system, Protective behaviors in workplace, Physical condition, Adaptive individual behaviors, Design and architecture of the building, Green infrastructure (green cover), and Urban design.
CONCLUSION
The findings of this study showed that community actions have significant effects on adaptation to heat wave. Therefore, for reducing heat wave-related negative health effects and vulnerability, more attention should be paid to the above-mentioned actions for mitigation, preparation, and responding regarding heat waves.
PROSPERO REGISTRATION NUMBER
CRD42021257747.
Topics: Hot Temperature; Acclimatization; Adaptation, Physiological; Global Warming; Adaptation, Psychological; Climate Change
PubMed: 37499408
DOI: 10.1016/j.jtherbio.2023.103588 -
Scandinavian Journal of Occupational... Oct 2023Heat waves impact the health of older adults, and occupations are important for health. An overview of research focussed on older adults' occupations in heat waves can... (Review)
Review
BACKGROUND
Heat waves impact the health of older adults, and occupations are important for health. An overview of research focussed on older adults' occupations in heat waves can be useful for occupational therapy practice.
OBJECTIVE
To identify what the literature shows about older adults' experience and performance of, and participation in, occupations in heat waves.
MATERIAL AND METHOD
This scoping review included a literature search in five academic databases, four databases for grey literature, and a manual search. Literature in English regarding older adults 60+ and their occupations in heat waves were eligible.
FINDINGS
Twelve studies were included. Findings showed that older adults adapt their occupations using bodily, environmental, and social interaction strategies and by changing their daily routines. Personal, environmental, social, and economic factors facilitate and maintain occupations in heat waves.
CONCLUSION
Older adults adapt their occupations in heat waves and different factors impact how they can be adapted. Future research is needed to explore how older adults experience their occupations in heat waves, and to deepen the knowledge about their heat-adaptive strategies.
SIGNIFICANCE
The findings support the role of occupational therapists in the design and practice of interventions managing the impact of heat waves in daily life.
Topics: Humans; Aged; Hot Temperature; Occupational Therapy; Occupations; Adaptation, Physiological
PubMed: 37402383
DOI: 10.1080/11038128.2023.2231165 -
Biomimetics (Basel, Switzerland) Jan 2024In the field of three-dimensional object design and fabrication, this paper explores the transformative potential at the intersection of biomaterials, biopolymers, and... (Review)
Review
In the field of three-dimensional object design and fabrication, this paper explores the transformative potential at the intersection of biomaterials, biopolymers, and additive manufacturing. Drawing inspiration from the intricate designs found in the natural world, this study contributes to the evolving landscape of manufacturing and design paradigms. Biomimicry, rooted in emulating nature's sophisticated solutions, serves as the foundational framework for developing materials endowed with remarkable characteristics, including adaptability, responsiveness, and self-transformation. These advanced engineered biomimetic materials, featuring attributes such as shape memory and self-healing properties, undergo rigorous synthesis and characterization procedures, with the overarching goal of seamless integration into the field of additive manufacturing. The resulting synergy between advanced manufacturing techniques and nature-inspired materials promises to revolutionize the production of objects capable of dynamic responses to environmental stimuli. Extending beyond the confines of laboratory experimentation, these self-transforming objects hold significant potential across diverse industries, showcasing innovative applications with profound implications for object design and fabrication. Through the reduction of waste generation, minimization of energy consumption, and the reduction of environmental footprint, the integration of biomaterials, biopolymers, and additive manufacturing signifies a pivotal step towards fostering ecologically conscious design and manufacturing practices. Within this context, inanimate three-dimensional objects will possess the ability to transcend their static nature and emerge as dynamic entities capable of evolution, self-repair, and adaptive responses in harmony with their surroundings. The confluence of biomimicry and additive manufacturing techniques establishes a seminal precedent for a profound reconfiguration of contemporary approaches to design, manufacturing, and ecological stewardship, thereby decisively shaping a more resilient and innovative global milieu.
PubMed: 38248622
DOI: 10.3390/biomimetics9010048 -
Microbiology (Reading, England) Aug 2023Studies of microbial evolution, especially in applied contexts, have focused on the role of selection in shaping predictable, adaptive responses to the environment.... (Review)
Review
Studies of microbial evolution, especially in applied contexts, have focused on the role of selection in shaping predictable, adaptive responses to the environment. However, chance events - the appearance of novel genetic variants and their , i.e. outgrowth from a single cell to a sizeable population - also play critical initiating roles in adaptation. Stochasticity in establishment has received little attention in microbiology, potentially due to lack of awareness as well as practical challenges in quantification. However, methods for high-replicate culturing, mutant labelling and detection, and statistical inference now make it feasible to experimentally quantify the establishment probability of specific adaptive genotypes. I review methods that have emerged over the past decade, including experimental design and mathematical formulas to estimate establishment probability from data. Quantifying establishment in further biological settings and comparing empirical estimates to theoretical predictions represent exciting future directions. More broadly, recognition that adaptive genotypes may be stochastically lost while rare is significant both for interpreting common lab assays and for designing interventions to promote or inhibit microbial evolution.
Topics: Mutation; Biological Evolution
PubMed: 37561015
DOI: 10.1099/mic.0.001365