Robust Implementation Research Articles

Acupuncture: Effective and Recommended but More Implementation Needed

Abstract Acupuncture enjoys a robust evidence base for dozens of clinical conditions and decades of research exploring its mechanisms of action. It has over 9,000 positive recommendations from official government and clinical guidelines. However, it still remains relatively inaccessible in the United States, Europe and elsewhere, especially compared to the strength of evidence-based recommendations for its use. Acupuncture would benefit from robust implementation strategies, utilizing insights and approaches from implementation science. The clinical use of Botox for migraine suffered from weaker evidence of effectiveness and greater evidence of harm, but using a streamlined and robust implementation strategy, Allergan was able to achieve widespread implementation from when it began its efforts around 2010. Such a systematic approach that identifies and overcomes barriers to implementation for acupuncture would benefit millions of people who currently are offered less effective and more invasive treatments, contrary to the recommendations of clinical guidelines.

Efficient single-run implementation of generalized Einstein relation to compute transport coefficients: A binary-based time sampling.

A robust and simple implementation of the generalized Einstein formulation using single equilibrium molecular dynamics simulation is introduced to compute diffusion and shear viscosity. The unique features underlying this framework are as follows: (1) The use of a simple binary-based method to sample time-dependent transport coefficients results in a uniform distribution of data on a logarithmic time scale. Although we sample "on-the-fly," the algorithm is readily applicable for post-processing analysis. Overlapping same-length segments are not sampled as they indicate strong correlations. (2) Transport coefficients are estimated using a power law fitting function, a generalization of the standard linear relation, that accurately describes the long-time plateau. (3) The use of a generalized least squares (GLS) fitting estimator to explicitly consider correlations between fitted data points results in a reliable estimate of the statistical uncertainties in a single run. (4) The covariance matrix for the GLS method is estimated analytically using the Wiener process statistics and computed variances. (5) We provide a Python script to perform the fits and automate the procedure to determine the optimal fitting domain. The framework is applied to two fluids, binary hard sphere and a Lennard-Jones near the triple point, and the validity of the single-run estimates is verified against multiple independent runs. The approach should be applicable to other transport coefficients since the diffusive limit is universal to all of them. Given its rigor and simplicity, this methodology can be readily incorporated into standard molecular dynamics packages using on-the-fly or post-processing analysis.

COVID-19 infection prevention and control for hospital workers in Indonesia.

The outbreak of SARS-CoV-2 in 2019 led to a global pandemic, posing unprecedented challenges to healthcare systems, particularly in hospitals. This study explores the intricacies of strategies employed for preventing and controlling COVID-19 in Indonesian hospitals, with a particular focus on the protocols, challenges, and solutions faced by healthcare professionals. Using a cross-sectional analysis, we examined 27 hospitals and uncovered disparities in their preparedness levels. During our investigation, we observed the robust implementation of infection prevention measures, which encompassed stringent protocols, adequate ventilation, and proper use of personal protective equipment. However, shortcomings were identified in areas such as surveillance, mental health support, and patient management. This study underscores the importance of addressing these gaps, suggesting tailored interventions, and continuous training for healthcare staff. Effective leadership, positive team dynamics, and adherence to comprehensive policies emerge as pivotal factors. Hospitals should strengthen weak areas, ensure the ethical execution of emergency protocols, and integrate technology for tracking and improving standard operating procedures. By enhancing the knowledge and skills of healthcare workers and maintaining strong management practices, hospitals can optimize their efforts in COVID-19 prevention and control, thereby safeguarding the wellbeing of professionals, patients, and communities.

Looking for winning policies to address the climate issue in EU-aviation

This paper analyzes the different climate policies that are used by the EU in the aviation sector. Using a simple model, we study their effects on welfare as well as on their acceptability. The efficiency and acceptability depend on the strength of the international agreements (Paris, 2015; CORSIA, 2020) and on the implementation of the policy within the EU. Four different policies are discussed: carbon taxes, tradeable emission permits, Sustainable Aviation Fuels (SAF) blending mandates and fuel efficiency standards for new aircrafts. The Paris and the CORSIA agreements are both weak agreements where, in the absence of sanctions, the implementation depends on the will of the political majority of the moment. In terms of implementation, it is shown that for intra EU aviation, the insertion of aviation in the EU-ETS with partially auctioned emission permits is probably the most robust and efficient implementation of the Paris agreement as it can result in net zero emissions in 2040–2050. Subsidies for R&D in fuel efficiency and new fuels would be good complements to the ETS system as they also have a positive spillover for the non-EU aviation via better aircrafts and better fuels. SAF mandates are likely to be inefficient implementations of climate policies, they exist because they are more acceptable for the airlines and intensive air transport users.

Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography.

Artificial intelligence (AI) applications in breast imaging span a wide range of tasks including decision support, risk assessment, patient management, quality assessment, treatment response assessment and image enhancement. However, their integration into the clinical workflow has been slow due to the lack of a consensus on data quality, benchmarked robust implementation, and consensus-based guidelines to ensure standardization and generalization. Contrast-enhanced mammography (CEM) has improved sensitivity and specificity compared to current standards of breast cancer diagnostic imaging i.e., mammography (MG) and/or conventional ultrasound (US), with comparable accuracy to MRI (current diagnostic imaging benchmark), but at a much lower cost and higher throughput. This makes CEM an excellent tool for widespread breast lesion characterization for all women, including underserved and minority women. Underlining the critical need for early detection and accurate diagnosis of breast cancer, this review examines the limitations of conventional approaches and reveals how AI can help overcome them. The Methodical approaches, such as image processing, feature extraction, quantitative analysis, lesion classification, lesion segmentation, integration with clinical data, early detection, and screening support have been carefully analysed in recent studies addressing breast cancer detection and diagnosis. Recent guidelines described by Checklist for Artificial Intelligence in Medical Imaging (CLAIM) to establish a robust framework for rigorous evaluation and surveying has inspired the current review criteria.

Property Management Practices Implementation and Cost Measures Efficiency in the City Government of Calamba: Basis for Action Plan

The focus of this study was to assess the implementation of property management practices and efficiency of cost measures in the City Government of Calamba, aiming to provide insights into key areas of concern and potential strategies for improvement. The study employed a descriptive correlational approach, combining quantitative analysis of stakeholder perceptions. Data were collected using a researcher-made questionnaire through paper surveys and Google forms with 134 respondents, consisting of 20 heads and 114 employees from the office concerned with the implementation of property management practices in the City Government of Calamba. For the treatment of quantitative data, the mean and four-point likert scale, paired t-test, the pearson product moment correlation coefficient and multiple linear regression analysis were used. The analysis revealed that first, the level of implementation of property management practices varied across different areas, with planning, acquisition, and utilization demonstrating robust implementation, while maintenance and disposal of public assets exhibited areas for improvement. Second, the assessment of cost measures efficiency reflected generally high, particularly in funding allocation and technology although skilled personnel needs enhancements. Third, the absence of significant differences in assessment between heads and employees underscored organizational cohesion and alignment of perspectives. Fourth, a significant relationship between property management practices and cost measures highlighted their interconnectedness and the importance of a holistic approach to organizational management. Based on the findings, an action plan entitled, “Strengthening the Property Management Practices and Promoting Cost Efficiency in the City Government of Calamba” was proposed to address the areas of concern in the City Government of Calamba, improve its overall property management practices and enhance cost measures efficiency, ultimately leading to more effective and sustainable governance.

Improving Health Equity in Living Donor Kidney Transplant: Application of an Implementation Science Framework

Interventions to improve racial equity in access to living donor kidney transplants (LDKT) have focused primarily on patients, ignoring the contributions of clinicians, transplant centers, and health system factors. Obtaining access to LDKT is a complex, multi-step process involving patients, their families, clinicians, and health system functions. An implementation science framework can help elucidate multi-level barriers to achieving racial equity in LDKT and guide the implementation of interventions targeted at all levels. We adopted the Pragmatic Robust Implementation and Sustainability Model (PRISM), an implementation science framework for racial equity in LDKT. The purpose was to provide a guide for assessment, inform intervention design, and support planning for the implementation of interventions. We applied 4 main PRISM domains to racial equity in LDKT: Organizational Characteristics, Program Components, External Environment, and Patient Characteristics. We specified elements within each domain that consider perspectives of the health system, transplant center, clinical staff, and patients. The applied PRISM framework provides a foundation for the examination of multi-level influences across the entirety of LDKT care. Researchers, quality improvement staff, and clinicians can use the applied PRISM framework to guide the assessment of inequities, support collaborative intervention development, monitor intervention implementation, and inform resource allocation to improve equity in access to LDKT.

Evaluation of the Anti-Corruption Laws and Measures on Investment in Nigeria

Nigeria's persistent corruption problem has significantly impeded its sustainable development and investment attractiveness. The pervasive nature of corruption poses substantial challenges to the nation's economic progress, governance, and both local and international investment opportunities. In response, various anti-corruption laws and measures have been instituted to combat this issue and promote transparency and accountability. This paper evaluates the effectiveness of these laws and measures in enhancing Nigeria's investment climate. Utilizing a doctrinal research methodology, the paper conducts a comprehensive analysis of the legal framework, enforcement mechanisms, and practical outcomes. The paper identifies significant challenges and gaps within the regulatory and implementation mechanisms. It further delineates potential areas for improvement in Nigeria's anti-graft efforts and their impact on investments. The findings suggest that for anti-corruption measures to be effective, the government must demonstrate political will by adequately funding relevant agencies to enable optimal functioning. The paper concludes that the robust implementation of anti-corruption laws and mechanisms will enhance transparency, accountability, and adherence to global best practices, thereby encouraging increased investment in the country.

On the robustification of digital event-based stabilizers for nonlinear time-delay systems

In this paper, the robust stabilization problem by means of quantized sampled-data event-based (QSE) controllers is investigated for nonlinear systems affected by state delays and unknown disturbances. In particular, a methodology for the design of robust QSE stabilizers is provided for control-affine nonlinear systems affected by unknown actuation disturbances and unknown measurement errors. Firstly, the notion of Steepest Descent Feedback (SDF), continuous or not, is suitably revised in order to deal with the robustification of event-based controllers. Then, Input-to-State Stability (ISS) redesign methodologies are used to provide the robustification term which is added to the SDF at hand in order to arbitrarily attenuate the effects of unknown external disturbances affecting the considered control scheme. A spline approximation approach is used in order to cope with the problem of the possible non-availability in the buffer of suitable past values of the system state required for the correct application of the proposed robust QSE controller. It is proved that there exist a suitably fast sampling and an accurate quantization of the input/output channels such that: the robust QSE implementation of SDFs, continuous or not, ensures the semi-global practical stability of the related closed-loop system, regardless of the above disturbances, provided that the observation errors affects marginally the new added control term. The stabilization in the sample-and-hold sense theory is used as a tool to prove the results. The provided results include the case of non-uniform quantization of the input/output channels and the case of aperiodic sampling. Applications are presented in order to validate the results.

NCI-Delirium Model: Co-caring to decrease the incidence of delirium among hospitalized older adults.

Delirium negatively impacts the health and wellbeing of older adults and their family carers and contributes to unnecessary high healthcare costs, estimated at $8.8 billion per year in Australia. Improvements to clinical practice are urgently needed, particularly now, as the COVID-19 pandemic is placing an enormous burden on our hospitals. 
 Innovative strategies that support partnerships with family carers have been reported as key to improved patient outcomes and satisfaction with care, particularly for older adults unable to participate in their own care. This is because carers have intimate knowledge of a family member’s cognitive state to identify early subtle changes others might not. Carers also provide valuable reassurance and familiarity to the older adults during their treatment and can orient them to place and time. 
 Founded on our clinical observations, informed by a scoping review of the literature (in press) and co-designed with carers, consumers, clinicians and policy analysts, we developed a new model of delirium care: NCI-Delirium. NCI-Delirium is a validated, scalable, low risk model that values the lived experience of older adults and carers. NCI-Delirium supports the integration of carers as partners in the care of the older adult from admission into the acute care setting. To support the integration of carers as partners, they are offered a web-based Delirium Toolkit that contains: an education package to build awareness and skill development (e.g., delirium risk factors, therapeutic and preventive strategies and non-pharmacological interventions to manage the reorientation of the hospitalised older adult); a 7-item psychometrically tested screening tool designed for carers to identify delirium symptoms and people at risk of delirium; access to support resources (e.g., counselling, social prescriptions, peer-support); and a co-designed discharge plan with the health team. 
 Preliminary results suggest that NCI-Delirium improves health service delirium outcomes. Carer involvement in this research, and the introduction of their perspectives, has elevated carers’ key relationships with clinicians. Our co-designed solution to support the integration of carers as partners in delirium management has improved carers’ caregiving burden, psychological wellbeing and knowledge of delirium. This translatable co-designed model of care provides the much needed rich and robust clinical, implementation and economic evidence, to address the risk factors associated with the prevalence of delirium in hospitalised older adults. It is anticipated that the model will transform how we integrate carers as partners in care to improve clinical practice, patient and carer experiences; and reduce caregiving burden.
 Globally, the identification and management of risk for delirium is imperative. Delirium is a potentially life-threatening condition, and not well detected in the acute or community care setting. If carers are integrated and supported as partners in care, the capacity to identify symptoms and support the diagnosis of delirium should increase, potentially reducing functional decline, transition to residential aged care facilities and mortality rates. The next steps are to evaluate this co-designed web-based delirium model of care for use by carers in the community and residential aged care setting.

Constrained Delaunay Tetrahedrization: A Robust and Practical Approach

We present a numerically robust algorithm for computing the constrained Delaunay tetrahedrization (CDT) of a piecewise-linear complex, which has a 100% success rate on the 4408 valid models in the Thingi10k dataset. We build on the underlying theory of the well-known tetgen software, but use a floating-point implementation based on indirect geometric predicates to implicitly represent Steiner points: this new approach dramatically simplifies the implementation, removing the need for ad-hoc tolerances in geometric operations. Our approach leads to a robust and parameter-free implementation, with an empirically manageable number of added Steiner points. Furthermore, our algorithm addresses a major gap in tetgen's theory which may lead to algorithmic failure on valid models, even when assuming perfect precision in the calculations. Our output tetrahedrization conforms with the input geometry without approximations. We can further round our output to floating-point coordinates for downstream applications, which almost always results in valid floating-point meshes unless the input triangulation is very close to being degenerate.

High Precision β‐Amyloid 1‐40, β‐Amyloid 1‐42, and Ptau181 Plasma Assay Performance in NCRAD Biomarker Assay Laboratory

AbstractBackgroundTo achieve the robust and reliable implementation of assays in the National Centralized Repository for Alzheimer’s Disease and related Dementias (NCRAD), new assays and platforms must be assessed for performance characteristics. The goal of this study is to assess the [Fujirebio Lumipulse] G1200 performance in comparison to existing platformsMethodPlasma samples utilized for assay precision measurements were collected from healthy control subjects and patients with Alzheimer’s disease (AD) by the Indiana Biobank. Five samples were chosen to span the assay range and were assayed on two separate days. Clinical utility was assessed with plasma samples (N = 179) collected by the Indiana Alzheimer’s Disease Research Center (IADRC). A subset (N = 92) of these samples were also assayed on the Neurology 4‐Plex E Advantage Kit on the [Quanterix] Simoa‐HDx platform. All samples were assayed on the [Fujirebio Lumipulse] G β‐Amyloid 1‐40, β‐Amyloid 1‐42, and Ptau181 plasma assays.Result[Fujirebio Lumipulse] G β‐Amyloid 1‐40, β‐Amyloid 1‐42, and Ptau181 plasma assays had an average inter‐assay coefficient of variation of 2.6%, 2%, and 2% respectively (Figure 1). In samples with both [Fujirebio Lumipulse] and Simoa‐HDx pTau181 data, linear regression showed an R^2 of 0.80 and slope of 1.67. Bland‐Altman analysis showed a consistent bias of 54%. Once results were standardized by Z‐score, slope was near one, y‐intercept near zero, demonstrating comparability of results. Area Under Receiver Operating Characteristic curve (AUC) for IADRC samples with PET data was 0.84 for Aβ 42/40 ratio alone and 0.87 including age, sex and APOE status. AUC for Ptau181 alone was 0.83 and 0.89 including age, sex and APOE status. Assays were able to detect differences in clinical diagnosis or amyloid status (Figure 2A and B).ConclusionThe [Fujirebio Lumipulse] assays exhibited high precision. When standardized by Z‐score, the [Fujirebio Lumipulse] Ptau181 assay was comparable to the Simoa‐HDx Ptau181v2 assay allowing comparison of data between assay platforms. AUCs for amyloid PET were higher when considering age, sex and APOE status in the model. The assays were able to differentiate between clinical diagnoses and amyloid status suggesting suitability for implementation.

Age‐related Modularity Changes of the Structural Brain Network: The Framingham Study

AbstractBackgroundWhile studies have consistently shown that brain network efficiency decreases with age, data on age‐related reconfiguration of network modules are scarce. We assessed structural brain networks from healthy adults of the Framingham Study to explore age‐related modularity differences.MethodStructural brain networks of 2,903 healthy adults (mean age 55, SD 0.96, range 25‐95, 53% female) were obtained from DTI probabilistic tractography. Connectivity matrices were constructed from 72 cortical and subcortical regions. First, we calculated efficiency to check the validity of our data. Second, we constructed a multilayer network with each layer representing one age decile and calculated modularity for each layer using a robust implementation of the Louvain community‐detection algorithm (Blondel et al., 2008). Third, we compared modular structures between each layer and a reference group (youngest) using the variation of information (VI), an index measure of distance between two modular patterns (e.g. modularity at different ages). Finally, we calculated the participation coefficient, a measure of modular node integration, and the node flexibility, a measure of module allegiance change and assessed their relationships with age.ResultEfficiency decreased with age (b = ‐0.34, SE 0.02, p<0.001), being stable until approximately 50 and declining linearly thereafter (see Figure 1, panel a). Modularity showed a u‐shaped trajectory with most integration at the fifth decile of age (see Figure1, panel b). VI index revealed that modular reconfiguration was greatest between the youngest and the oldest age decile (0.43). Participation coefficient was highest at the fifth decile (see Figure2, panel c) and in frontal nodes (see Figure2, panel a), where it also exhibited high variability. Frontal variability followed a complex pattern (Figure2, panel b). Conversely, central and temporal‐occipital nodes showed less participation and variability (see Figure2, panels a and b), and the lowest flexibility (see Figure3).ConclusionBrain network modules reconfigure with aging. This reconfiguration is non‐uniform. While midline‐near modules, including the cingulate and parieto‐occipital cortices, show relative stability, frontal modules seemed to reconfigure considerably, as seen by increased average flexibility (change in modular allegiance) and less integration with advancing age, as seen by declining participation coefficients.

Age‐related Modularity Changes of the Structural Brain Network: The Framingham Study

AbstractBackgroundWhile studies have consistently shown that brain network efficiency decreases with age, data on age‐related reconfiguration of network modules are scarce. We assessed structural brain networks from healthy adults of the Framingham Study to explore age‐related modularity differences.MethodStructural brain networks of 2,903 healthy adults (mean age 55, SD 0.96, range 25‐95, 53% female) were obtained from DTI probabilistic tractography. Connectivity matrices were constructed from 72 cortical and subcortical regions. First, we calculated efficiency to check the validity of our data. Second, we constructed a multilayer network with each layer representing one age decile and calculated modularity for each layer using a robust implementation of the Louvain community‐detection algorithm (Blondel et al., 2008). Third, we compared modular structures between each layer and a reference group (youngest) using the variation of information (VI), an index measure of distance between two modular patterns (e.g. modularity at different ages). Finally, we calculated the participation coefficient, a measure of modular node integration, and the node flexibility, a measure of module allegiance change and assessed their relationships with age.ResultEfficiency decreased with age (b = ‐0.34, SE 0.02, p<0.001), being stable until approximately 50 and declining linearly thereafter (see Figure 1, panel a). Modularity showed a u‐shaped trajectory with most integration at the fifth decile of age (see Figure1, panel b). VI index revealed that modular reconfiguration was greatest between the youngest and the oldest age decile (0.43). Participation coefficient was highest at the fifth decile (see Figure2, panel c) and in frontal nodes (see Figure2, panel a), where it also exhibited high variability. Frontal variability followed a complex pattern (Figure2, panel b). Conversely, central and temporal‐occipital nodes showed less participation and variability (see Figure2, panels a and b), and the lowest flexibility (see Figure3).ConclusionBrain network modules reconfigure with aging. This reconfiguration is non‐uniform. While midline‐near modules, including the cingulate and parieto‐occipital cortices, show relative stability, frontal modules seemed to reconfigure considerably, as seen by increased average flexibility (change in modular allegiance) and less integration with advancing age, as seen by declining participation coefficients.

Accelerating spiral deblurring with square kernels and low-pass preconditioning.

Robust implementation of spiral imaging requires efficient deblurring. A deblurring method was previously proposed to separate and deblur water and fat simultaneously, based on image-space kernel operations. The goal of this work is to improve the performance of the previous deblurring method using kernels with better properties. Four types of kernels were formed using different models for the region outside the collected k-space as well as low-pass preconditioning (LP). The performances of the kernels were tested and compared with both phantom and volunteer data. Data were also synthesized to evaluate the SNR. The proposed "square" kernels are much more compact than the previously used circular kernels. Square kernels have better properties in terms of normalized RMS error, structural similarity index measure, and SNR. The square kernels created by LP demonstrated the best performance of artifact mitigation on phantom data. The sizes of the blurring kernels and thus the computational cost can be reduced by the proposed square kernels instead of the previous circular ones. Using LP may further enhance the performance.

Rural development through people's participation in Gram Sabha: A study from Central India

Rural development can never be possible without a robust implementation of governmental policies in rural regions. The Panchayati Raj institutions were introduced in India in 1993 with the goal of rural development through the people's participation. In this context, this study explores the level of involvement of villagers in Gram Sabha and their awareness of state development policies and investigates gender participation in rural development. The study adopts both quantitative and qualitative research methodologies. The data have been collected from the village Chitoura, Sagar, district of Madhya Pradesh (MP) via semi-structured interview methods, case studies, and observations. A total of 50 villagers were selected as respondents through random sampling. Notably, the findings point out that the Panchayati Raj institutions are failing to deliver the development policies on the ground due to a lack of awareness among the villagers and poor participation of women in village activities. This study recorded that caste and gender hinder rural development as some specific castes gained more benefits from the Panchayati Raj institution. Keywords: Gram sabha; Panchayati Raj institution; rural development; women representatives.

Telehealth Diabetes Prevention Program for Adults With Prediabetes in an Academic Medical Center Setting: Protocol for a Hybrid Type III Trial.

Diabetes is a costly epidemic in the United States associated with both health and economic consequences. These consequences can be mitigated by participation in structured lifestyle change programs such as the National Diabetes Prevention Program (DPP) led by the Centers for Disease Control and Prevention. Mississippi consistently has among the highest rates of diabetes and prediabetes nationally. Implementing the National DPP through large health care systems can increase reach and accessibility for populations at the highest risk for diabetes. Translational research on the National DPP in Mississippi has not been studied. This study aims to evaluate the implementation and impact of the National DPP delivered using telehealth modalities at the University of Mississippi Medical Center in Jackson, Mississippi. An effectiveness-implementation hybrid type III research design is proposed. The study design is guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework and the Practical, Robust Implementation and Sustainability Model. Participants are being recruited via provider referral, and the DPP is being delivered by trained lifestyle coaches. Study participants include adult (≥18 years) patients eligible for the DPP with at least 1 encounter at 1 of 3 ambulatory clinic specialties (lifestyle medicine, family medicine, and internal medicine) between January 2019 and December 2023. The National DPP eligibility criteria include a BMI ≥25 kg/m2 and hemoglobin A1c between 5.7% and 6.4%. The University of Mississippi Medical Center criteria include Medicare or Medicaid beneficiaries. The University of Mississippi Medical Center's a priori implementation plan was developed using the Consolidated Framework for Implementation Research and includes 23 discrete strategies. The primary aim will use an embedded mixed method process analysis to identify and mitigate challenges to implementation. The secondary aim will use a nonrandomized quasi-experimental design to assess the comparative effectiveness of the DPP on health care expenditures. A propensity score matching method will be implemented to compare case subjects to control subjects. The primary outcomes include patient referrals, participant enrollment, retention, engagement, the incidence of diabetes, and health care resource use and costs. At baseline, of the 26,151 patients across 3 ambulatory clinic specialties, 1010 (3.9%) had prediabetes and were eligible for the National DPP. Of the 1010 patients, more than half (n=562, 55.6%) were aged 65 years or older, 79.5% (n=803) were Medicare beneficiaries, 65.9% (n=666) were female, and 70.8% (n=715) were obese. This is the first translational study of the National DPP in Mississippi. The findings will inform implementation strategies impacting the uptake and sustainability of the National DPP delivered in an academic medical setting using distance learning and telehealth modalities. ClinicalTrials.gov NCT04822480; https://clinicaltrials.gov/study/NCT03622580. DERR1-10.2196/50183.

A Robust Control Approach to AMSs by Using the Implementation of Strong and Weak Robustness

A Robust Control Approach to AMSs by Using the Implementation of Strong and Weak Robustness

Implementation and effectiveness of a physician-focused peer support program.

The practice of medicine faces a mounting burnout crisis. Physician burnout leads to worse mental health outcomes, provider turnover, and decreased quality of care. Peer support, a viable strategy to combat burnout, has been shown to be well received by physicians. This study evaluates the Peer Outreach Support Team (POST) program, a physician-focused peer support initiative established in a 2-hospital system, using descriptive statistical methodologies. We evaluate the POST program using the Practical Robust Implementation and Sustainability Model (PRISM) framework to describe important contextual factors including characteristics of the intervention, recipients, implementation and sustainability infrastructure, and external environment, and to assess RE-AIM outcomes including reach, effectiveness, adoption, implementation, and maintenance. This program successfully trained 59 peer supporters across 11 departments in a 2-hospital system over a 3-year period. Trained supporters unanimously felt the training was useful and aided in general departmental culture shift (100% of respondents). After 3 years, 48.5% of physician survey respondents across 5 active departments had had a peer support interaction, with 306 successful interactions recorded. The rate of interactions increased over the 3-year study period, and the program was adopted by 11 departments, representing approximately 60% of all physicians in the 2-hospital system. Important implementation barriers and facilitators were identified. Physician recipients of peer support reported improved well-being, decreased negative emotions and stigma, and perceived positive cultural changes within their departments. We found that POST, a physician-focused peer support program, had widespread reach and a positive effect on perceived physician well-being and departmental culture. This analysis outlines a viable approach to support physicians and suggests future studies considering direct effectiveness measures and programmatic adaptations. Our findings can inform and guide other healthcare systems striving to establish peer support initiatives to improve physician well-being.

Modelling Robot Architectures with AADL

Robots are complex systems composed of many interacting subsystems, each coordinating a multitude of hardware and software components. In the last twenty years, robotic frameworks helped accelerate the development process by providing a reference structure and publicly available software components. However, current practices are not sustainable for modern robotic systems. In this work, we present a modelling approach based on the Architecture Analysis and Design Language (AADL) to define robotic systems and enhance software development practices for robotics. Additionally, we exploit the model to perform automatic code generation, which reduces development time and guarantees a more reliable and robust implementation.