Measurement Feedback Research Articles

Process and Implementation Elements of Measurement Feedback Systems: A Systematic Review.

Measurement feedback systems (MFS) can help guide treatment and improve clinical outcomes. Studies of MFS are heterogeneous both in execution and results, and the effects of MFS seem restricted by limited attention to process and implementation elements and by limited adoption by health professionals. The current systematic review mapped the use of process and implementation elements in MFS studies. An overview of therapists' use of and attitudes toward MFS is provided. Three-level meta-analyses were used to test theoretically informed process and implementation elements as moderators of the effects of MFS. Hypotheses and general propositions from Clinical Performance Feedback Intervention Theory (CP-FIT) were used to organize the elements of the studies and were used as moderator variables. Previous studies on MFS interventions have had a limited focus on implementation efforts and process elements that may increase the effects of MFS and their use among therapists. Efforts have sparsely been made to reduce barriers to MFS use, and several studies have reported limited engagement with MFS among therapists. Therapists' attitudes toward MFS, feedback, or standardized measures were heterogeneously reported, making data synthesis challenging. Identified process and implementation elements were not significantly associated with effect sizes in the studies and the results did not support the propositions of CP-FIT. The lack of statistically significant associations may be due to limited reporting of details about process and implementation aspects. More research designed to test hypotheses regarding process and implementation elements is needed to improve the use and effects of MFS. Future studies should aspire to report findings in a manner that allows for an understanding of the implementation process and therapists' adoption of these systems.

Tillage depth regulation system via depth measurement feedback and composite sliding mode control: A field comparison validation study

The existing methodologies employed for the quantification and regulation of tractor’s tillage depth present considerable shortcomings, primarily characterized by their low accuracy and poor disturbance rejection proficiency in complex agricultural terrains. In this study, we present a sophisticated feedback control strategy designed to mitigate these challenges. Our innovative approach hinges on calculating tillage depth from the alignment of the tractor’s hydraulic lifting arm, achieved by employing a mechanical angle sensor. This sensor adeptly gages the angle of the lifting arm, aligning it with the tillage angle of the pull rod and the implement’s angle, resulting in a robust relational model correlating the lifting arm angle with the tillage depth. This pioneering method amalgamates the accuracy inherent in the static model, derived from the tillage angle-based depth measurement, with the dynamic stability afforded by the mechanical ascertainment of the lifting arm angle. In conjunction, we introduce a Hybrid Extended State Observer-Based Backstepping Sliding Mode Controller (HESO-BacksteppingSMC). The HESO is instrumental in estimating unmeasured state variables and lumped disturbances, utilizing the system’s output feedback signal. Our control frame component capitalizes on the fast power-reaching law to yield a continuously smooth control signal, effectively eradicating the conventional chattering phenomenon inherent in controllers and amplifying its functional applicability. Theoretical evaluations affirm the uniformly and ultimately bounded stability of the errors associated with our proposed observer and controller, underscoring their robustness. The superior performance of our proposed tillage depth measurement and control methodology has been corroborated through a series of comprehensive simulation and field plowing trials, attesting to its precision and reliability in complex agricultural settings.

What are the features of high-performing quality improvement collaboratives? A qualitative case study of a state-wide collaboratives programme

ObjectivesDespite their widespread use, the evidence base for the effectiveness of quality improvement collaboratives remains mixed. Lack of clarity about ‘what good looks like’ in collaboratives remains a persistent problem....

A learning observer-based control strategy for PMSM with position sensor fault in railway

In this paper, control strategy for PMSM with position sensor fault in railway is investigated. Conventional control approaches rely on accurate measurement feedback signal by position sensor. However, position sensor of PMSM in trains is prone to failure. To solve such a problem, a learning observer-based control strategy is proposed. Firstly, a novel learning observer is proposed in order to achieve high-precision estimation of electromotive force. Secondly, a combined PD-SMC controller is designed to accelerate speed response. Estimation of position and speed can be deduced from EMFs estimation, the estimated speed information can be employed by proposed PD-SMC controller. The effectiveness and validity of proposed learning observer and PD-SMC controller are verified by simulations and experiments.

From correlation to causation using directed topological overlap matrix: Applications in genomics.

Most causal discovery tools assume the local causal Markov condition. However, the theoretical assumptions that underlie the local causal Markov condition are often not met in practice. This is especially marked in genomics, where the unwanted presence of measurement errors, averaging effects, and feedback loops significantly undermine the legitimacy of the local causal Markov condition. Furthermore, these causal discovery algorithms require very large samples, orders above what is often available. In this paper, relaxing the local causal Markov condition and using Reichenbach's common cause principle instead, we present a more flexible approach to causal discovery, the directed topological overlap matrix (DTOM). DTOM is robust w.r.t the presence of measurement errors, averaging effects, feedback loops, and is significantly more sample efficient. We study the utility of DTOM for discovering causal relations in biological data using three real gene expression data-sets. We first examine if DTOM can help distinguish the Myostatin mutation in the Piedmontese cattle by contrasting the muscle transcriptomes of the Piedmontese and Wagyu crosses: the Myostatin mutation is the cause of the double-muscling the Piedmontese cattle are famous for. We then consider a large-scale gene deletion study in yeast. We show that DTOM allows us to distinguish the deleted gene in a sample knowing only the set of differentially expressed genes in that sample. We then examine the progression of Alzheimer's disease (AD) under the lens of DTOM. The genes implicated as having a causal role in the progression of AD by our DTOM analysis were significantly enriched in cellular components that had been repeatedly implicated in the progression of AD.

Online optimization and tracking control strategy for battery energy storage in DC microgrids

This paper proposes a fast time-varying optimal power flow (OPF) command tracking control algorithm for DC microgrids based on measurement feedback. The algorithm establishes a model by adding power command tracking constraints and considering the power, voltage, and current constraints of the microgrid. A forward-back generation DC power flow sensitivity calculation method is designed to calculate the power output of the energy storage at each node, and charging and discharging decisions are made based on the state of charge (SOC) of the energy storage system, current voltage, and charging and discharging scenarios previous and subsequent. By continuously issuing control decisions, the DC microgrid OPF command tracking solution is achieved. The measurement feedback control scheme used in this algorithm reduces model error and non-iterative calculation error, thus improving calculation and tracking accuracy. The algorithm is tested in a modified 28-node arithmetic system and suppresses voltage fluctuations caused by unstable PV active output effectively, while accurately tracking the power command of the upper level and meeting the voltage safety operation requirements of the microgrid.

Sensitivity to change of the Systemic Therapy Inventory of Change (STIC) intersession scales

Objective: The Systemic Therapy Inventory of Change (STIC) is a systemic measurement feedback system that provides therapists with feedback regarding the multidimensional clinical change in individual, couple, and family therapy. The STIC Intersession scales include Individual Problems and Strengths (IPS), Relationship with Partner (RWP), Family/Household (FH), and Child Problems and Strengths (CPS). They are administered to clients before each therapy session. The purpose of the current study is to investigate the STIC Intersession scales’ sensitivity to change, the ability to detect reliable and valid changes that occur after an intervention. Method: Participants (N = 583) who voluntarily received individual, couple, or family therapy services in a randomized clinical trial attended the study. Results: By comparing the changes in pre-therapy and post-therapy scores of the STIC Intersession scales with those of the corresponding reference measures, the external sensitivity to change of the STIC Intersession scales was supported. The IPS Intersession scale showed greater change than the Beck Anxiety Inventory. However, no evidence supported the discriminant validity of CPS’s change scores. Conclusion: Thus, the STIC Intersession IPS, RWP, and FH can be validly used to assess multi-systemic changes in both research and clinical work.

Exploring the Impact of Actionable Guidance & Feedback on Pro-Environmental Behaviors, Climate Anxiety, and Environmental Efficacy

Evidence indicates that the burning of fossil fuels, deforestation, and pollution are tipping our global climate toward changes that jeopardize the stability of our environments and are likely to impact the overall suitability of our planet for habitation by humans and many other living organisms. As the global climate situation becomes more pronounced and increasingly signals itself as a threat to human wellbeing, a new mental health concern has also begun to delineate itself, that of climate anxiety, which is being felt by individuals across the globe, from mood and decreased levels of functioning, to more severe manifestations like substance abuse, depression, and insomnia. The goal of this work is to review and expand on the concepts of climate anxiety, as well as environmental efficacy, and explore their relationship with proenvironmental behaviors with considerations for the potential moderating effects that actionable guidance and measurable feedback may have on the adoption and outcomes of those behaviors.

Spontaneous symmetry breaking and localization in nonequilibrium steady states of interactive quantum systems

The time evolution of a physical system is generally described by a differential equation, which can be solved numerically by adopting a difference scheme with space–time discretization. This discretization, as a numerical artifact, results in accumulated errors during evolution and thus usually plays a negative role in simulations. In a quantum circuit, however, the “evolution time” is represented by the depth of the circuit layer, and thus is intrinsically discrete. Hence, the discretization-induced error therein is not a numerical artifact, but a physical observable effect responsible for remarkable nonequilibrium phenomena absent in conventional quantum dynamics. In this paper, we show that the combination of measurement feedback and temporal discretization can give rise to a new type of quantum dynamics. As physical consequences of this interactive quantum dynamics, a nonequilibrium steady state with spontaneous symmetry breaking is revealed in a zero-dimensional (single-qubit) system. A localization mechanism distinct from that in the well-established Anderson localization has also been proposed in a one-dimensional interactive quantum system.

Oral-malodor measurement and intention to quit smoking in men: A before-after study.

Few studies have examined the effect of feedback based on oral-malodor measurements on the motivation to quit smoking. Therefore, this study examined whether oral-malodor measurements were associated with the intention to quit smoking. This retrospective, uncontrolled before-after study invited smokers to a workplace health event in 2019 and 2020 to motivate them to quit smoking. They attended seminars on oral health and smoking cessation aids, and then underwent respiratory function and oral-malodor measurements using exhaled and oral cavity air, respectively. Intention to quit smoking was evaluated by answers to questions regarding the intention to quit in the next 1 or 6 months in questionnaires collected before and after the event. This study analyzed 241 men aged 20-54 years (mean: 33.2 ± 10.5) to examine factors associated with the intention to quit in multivariable logistic regression analyses for age, tobacco type (cigarettes and heated-tobacco products), and category of tobacco consumption. Before the event, 8.7%, 17.0%, and 74.3% of smokers had intended to quit in the next month, the next six months, or had no intention to quit, respectively. After the event, the respective percentages were 17.8%, 26.6%, and 55.6%. A higher methyl mercaptan concentration, a volatile sulfide component of oral malodor, was significantly associated with the intention to quit in the next month (adjusted odds ratio, AOR=4.24; 95% CI: 1.52-11.8, p=0.006). The participants with higher daily tobacco consumption were less likely to acquire the intention to quit in the next six months (AOR=0.37; 95% CI: 0.15-0.92, p=0.032). Other variables, such as lung age deficit, exhaled CO concentration, and hydrogen sulfide concentration (another component of oral malodor), were not significantly associated. Oral-malodor measurement feedback may help motivate men to quit smoking in the next 1 month rather than in the next six months.

Incremental control as an enhanced and robust implementation of gain scheduled controllers avoiding hidden coupling terms

This paper proposes a new and simple method to combine incremental control with the classical proportional-integral (PI) control in order to increase the robustness properties of the resulting control law. The proposed method avoids hidden coupling terms in a similar manner to the differential PI controller implementation (DPI) and hence allows for fast gain scheduling. The integral action is accomplished by feedback of actuator measurements and therefore avoids integrator windup without complicated anti-windup schemes. The control law obtains an increase in robust performance with a response less sensitive to variations in flight dynamic parameters when compared to the equivalent PI controller. Improvement in disturbance rejection is also obtained with a faster and more robust response. Increased robustness toward input time delay is observed by example. The trade-off between increased robustness and sensitivity to sensor noise and delay can be adjusted with an intuitive tuning parameter. The novel method, denoted incremental DPI (iDPI), is investigated in the context of fixed-wing flight control. The concept is verified as a retrofit for an industry-level PI baseline controller for the longitudinal motion of a fixed-wing aircraft using a high-fidelity simulation model.

Training Community Therapists in Core Elements of CBT and Family Therapy for Adolescent Externalizing Problems

ABSTRACT Objective This pilot study tested pragmatic methods for training therapists in core techniques of two evidence-based interventions (EBIs) for adolescent externalizing problems: cognitive-behavioral therapy (CBT) or family therapy (FT). Training methods were designed to help therapists accurately self-monitor their use of EBIs and increase delivery of EBIs with current clients. The study compared coder training only versus coder training plus fidelity-focused consultation. Method Therapists (N = 42) from seven behavioral health clinics reported on 65 youth clients; four clinics elected to train in CBT and three in FT. Therapists were randomized to either coder training only, consisting of a 25-week observational coder training course (didactic instruction and mock session coding exercises in core EBI techniques); or coder training plus fidelity-focused consultation, consisting of direct-to-therapist fidelity measurement feedback along with fidelity-focused expert consultation. During the 25 weeks of training, therapists submitted self-report data on EBI use along with companion session audiotapes subsequently coded by observational raters. Results Compared to coder training only, coder training plus fidelity-focused consultation produced superior effects in therapist ability to judge the extensiveness of EBI techniques in online coding sessions, as well as therapist ability to self-rate use of EBI techniques with their own cases. In both conditions, therapists who trained in CBT showed a significant, though modest, increase in real-world delivery of core CBT techniques; this did not occur for FT. Conclusions Pragmatic training and consultation methods show promise as viable and effective options for enhancing EBI fidelity monitoring and, for CBT, increasing EBI delivery.

Qualitative study of international key informants’ perspectives on the current and future state of healthcare quality measurement and feedback

ObjectivesThe aim of this study is to explore the current and future state of quality measurement and feedback and identify factors influencing measurement feedback systems, including the barriers and enablers...

Fault-tolerant attitude coordination control for multiple flexible spacecraft using vector measurements

This paper addresses the control problems of distributed attitude coordination for multiple flexible spacecraft based on the feedback of inertial vector measurements. It is assumed that the angular velocity information is not available, and the modal variable cannot be measured. The orientation error model with vector measurements is introduced. And then the distributed attitude synchronization control scheme is presented without actuator faults or disturbances. It is guaranteed that the desired equilibrium is locally asymptotically stable and the undesired equilibrium is unstable. Meanwhile, the domain of attraction is given by inequality constraints. In the case that there exist actuator faults and external disturbances, a robust fault-tolerant control strategy is developed to realize attitude synchronization. The hyperbolic tangent function in place of sign function is adopted to eliminate external disturbances. Meanwhile, the adaptive laws are proposed to estimate actuator faults. The salient feature of these control approaches is that no modal variable observers are utilized and the control schemes are robust to the inertia uncertainty of spacecraft. Finally, numerical simulations are implemented to manifest the validity of the presented control schemes.

Pediatric Inpatient Leaders, Views Changed with COVID-19: A Call to Re-engage in Quality Improvement.

Pediatric Inpatient Leaders, Views Changed with COVID-19: A Call to Re-engage in Quality Improvement.

Quantum feedback induced genuine magnon–photon–magnon entanglement and steering in a cavity magnonical system

We present an alternative scheme to generate genuine tripartite entanglement and steering among one photon and two magnons in a cavity magnonical system, where two yttrium iron garnet spheres are respectively placed inside two microwave cavities driven by a two-mode squeezed field and subjected to homodyne-measurement feedback. It is found that quantum feedback on two cavities plays a crucial role in enhancing quantum correlations of photons and magnons. In the absence of measurement feedback, only bipartite entanglement between two magnons is existent. In contrast, when the continuous measurement feedback is present, two magnons are strongly entangled and magnon–photon entanglement also appears. More importantly, the stable genuine magnon–photon–magnon tripartite entanglement and steering could be obtained based on the homodyne-measurement feedback on two microwave cavities, which are robust against the thermal fluctuations. The work we present provides a feasible way to manipulate the multipartite quantum correlations including entanglement and steering in hybrid quantum systems.

How Politicians Learn from Citizens’ Feedback: The Case of Gender on Twitter

AbstractThis article studies how politicians react to feedback from citizens on social media. We use a reinforcement‐learning framework to model how politicians respond to citizens’ positive feedback by increasing attention to better received issues and allow feedback to vary depending on politicians’ gender. To test the model, we collect 1.5 million tweets published by Spanish MPs over 3 years, identify gender‐issue tweets using a deep‐learning algorithm (BERT) and measure feedback using retweets and likes. We find that citizens provide more positive feedback to female politicians for writing about gender, and that this contributes to their specialization in gender issues. The analysis of mechanisms suggests that female politicians receive more positive feedback because they are treated differently by citizens. To conclude, we discuss implications for representation, misperceptions, and polarization.

Energy Management System (EMS) Based on Model Predictive Control (MPC) for an Isolated DC Microgrid

Microgrids have become an alternative for integrating distributed generation to supply energy to isolated communities, so their control and optimal management are important. This research designs and simulates the three levels of control of a DC microgrid operating in isolated mode and proposes an Energy Management System (EMS) based on Model Predictive Control (MPC), with real-time measurement feedback for optimal energy dispatch, which ensures power flow distribution and operation at minimum cost while extending the lifespan of the BESS. The EMS can react to disturbances produced in the lower control levels. The microgrid’s performance is analyzed and compared in two scenarios without EMS, and with EMS against changes in irradiation and changes in electricity demand. The fulfillment of the power balance is evaluated by analyzing the power delivered by each generation unit, the operating cost, and the state of charge of the battery (SOC).

Building a knowledge graph for operational hazard management of utility tunnels

The operational hazard management of the utility tunnel infrastructure is crucial for sustainable and resilient urban development. It not only involves various domain expertise such as safety, pipeline, structure, equipment, and electricity, but also requires timely and efficient access to and decision support from the relevant information of critical resources. However, current operational hazard management practices rely mainly on the experience of engineers, rendering it difficult to ensure management quality, thus increasing the risk of utility tunnel accidents. Hence, a knowledge graph-based decision support approach is proposed herein for the operational hazard management of utility tunnels, which illustrates the ontology design and information extraction from structured field inspection data and unstructured normative text files. The experimental case study demonstrates that this approach can improve the hazard management capabilities of utility tunnels by providing decision aids such as query, analysis, and control measure feedback.

Educating Mental Health Trainees About Measurement-Based Care: A Scoping Review.

Measurement-based care (MBC) refers to the routine use of symptom rating scales to guide treatment decisions. Although effective, it is an underused approach to enhance patient care. A significant barrier to integration of MBC is insubstantial foundational training. This scoping review aims to survey the literature on MBC educational curricula for mental health trainees. Investigators searched Ovid Medline, PsycINFO, Embase, Cochrane Central, and Ebsco CINAHL through June 2021 to select records that described studies of MBC educational programs for undergraduate, graduate, or postgraduate learners in mental healthcare. From 1270 unique records, 1263 were excluded in abstract/title and full-text screening. This scoping review included seven articles, of which most were empirical or case studies and took place in the USA. These curricula involved many delivery formats, including lectures and in-service training. Measured learner outcomes include those that are learner-focused (i.e. learner reaction, or attitudinal/behavioral change) and organizational-focused (i.e. increased clinical use of MBC). Mechanisms of positive outcomes are posited to include enhanced stakeholder support and continual curriculum improvement. MBC curricula can be taught in various formats to diverse learners in mental healthcare. Contextual factors, such as dedicated resources, MBC champions, supervisor training, online measurement feedback systems, simple measures, and gathering and disseminating feedback may facilitate curricular success by fostering stakeholder support and continual program improvement. To address literature gaps, future research in MBC education should involve educational frameworks in designing curriculum and address the use of quality improvement approaches in the implementation of MBC education.