Logic Model Research Articles

Implementation outcomes of a digital, trauma-informed care, educational intervention targeting health professionals in a paediatric burns setting: A mixed methods process evaluation

Trauma-informed care practices are associated with a culture of safety following traumatic experiences, including medical trauma. An interactive, web-based training package (‘Responsive CARE’) was developed for voluntary uptake by paediatric burns health professionals to increase staff knowledge about trauma-informed practice. This paper reports on a mixed methods process evaluation conducted alongside a preliminary effectiveness study of ‘Responsive CARE’. The process evaluation was conducted using The Consolidated Framework for Implementation Research (CFIR) and a logic model, to examine feasibility of both the intervention and implementation strategy. Health practitioners (including senior managers) delivering care to children and caregivers attending an outpatient burns service were eligible to enrol in ‘Responsive CARE’. Qualitative interview data and quantitative metadata were used to evaluate the implementation outcomes (adoption, acceptability, fidelity, feasibility and preliminary effectiveness). Children and caregivers attending an outpatient service for change of burn wound dressing or burn scar management during the 3-month control or 3-month intervention period were eligible to enrol in the effectiveness study. The impact on child pain and distress, as well as cost, was investigated using a pretest-posttest design. Thirteen (from anticipated 50 enrolled) health professionals (all female) with mean 10 years (SD=11) of experience with paediatric burns hospital-based outpatient care completed an average of 65% (range 36% to 88%) of available content. Twenty-five semi-structured interviews were completed with health practitioners (21 female) and with 14 caregivers (11 female). Four themes were identified as influencing feasibility and acceptability of the intervention: 1) Keeping a trauma-informed lens; 2) Ways of incorporating trauma-informed care; 3) Working within system constraints; and 4) Being trauma-informed. Preliminary effectiveness data included 177 participants (median age 2 years, and median total body surface area burn 1%). Causal assumptions within the logic model were unable to be fully tested, secondary to lower-than-expected adoption and fidelity. We found no significant difference for pain, distress and per-patient hospital care costs between groups (pre- and post-intervention). Future implementation strategies should include organizational support to keep a trauma-informed lens and to incorporate trauma-informed principles within a medical model of care. Despite efforts to co-design a staff education intervention and implementation approach focused on stakeholder engagement, adaptations are indicated to both the intervention and implementation strategies to promote uptake highlighting the complexity of changing clinician behaviours.

Methods of Modelling Electronic Academic Libraries: Technological Concept of Electronic Libraries

Abstract The relevance of examining modelling methods in academic electronic libraries is justified by the need to understand the library’s structure and ensure its operation in technological terms. The purpose of this study is to analyse the applied modelling methods for electronic libraries serving Kazakhstani and international higher education institutions. The study employed basic (structural, comparative-comparative) and additional (analytical-synthetic, graphical) methods. During this study, it was found that the main modelling methods for modern electronic libraries include the following: conceptual with the establishment of a clear hierarchy between objects of the electronic library and attributes of search queries, logical using search categorisation, informational employing the semantic principle of material construction and systemic-functional ensuring a balance between functions, structure, technologies and the management system. In particular, after modelling the structure of Kazakhstani, British and American digital libraries at universities, it was determined that the Yale University Electronic Library Collection is built on the method of logical modelling, the Electronic Library at L.N. Gumilyov Eurasian National University uses the systemic-functional method, the Cambridge University Electronic Library employs the informational method and the Al-Farabi Library uses the conceptual method.

A service mapping exercise of four health and social care staff mental health and wellbeing services, Resilience Hubs, to describe health service provision and interventions

BackgroundNHS England funded 40 Mental Health and Wellbeing Hubs to support health and social care staff affected by the COVID-19 pandemic. We aimed to document variations in how national guidance was adapted to the local contexts of four Hubs in the North of England.MethodsWe used a modified version of Price’s (2019) service mapping methodology. Service level data were used to inform the analysis. A mapping template was adapted from a range of tools, including the European Service Mapping Schedule, and reviewed by Hub leads. Key data included service model; staffing; and interventions. Data were collected between March 2021 – March 2022 by site research assistants. Findings were accuracy-checked by Hub leads, and a logic model developed to theorise how the Hubs may effect change.ResultsHub goals and service models closely reflected guidance; offering: proactive outreach; team-based support; clinical assessment; onward referral, and rapid access to mental health support (in-house and external). Implementation reflected a service context of a client group with high mental health need, and high waiting times at external mental health services. Hubs were predominantly staffed by experienced clinicians, to manage these mental health presentations and organisational working. Formulation-based psychological assessment and the provision of direct therapy were not core functions of the NHS England model, however all Hubs incorporated these adaptations into their service models in response to local contexts, such as extensive waiting lists within external services, and/or client presentations falling between gaps in existing service provision. Finally, a standalone clinical records system was seen as important to reassure Hub users of confidentiality. Other more nuanced variation depended on localised contexts.ConclusionThis study provides a map for setting up services, emphasising early understandings of how new services will integrate within existing systems. Local and regional contexts led to variation in service configuration. Whilst additional Hub functions are supported by available literature, further research is needed to determine whether these functions should comprise essential components of staff wellbeing services moving forward. Future research should also determine the comparative effectiveness of service components, and the limits of permissible variation.Study registrationresearchregistry6303.

Study and development of a logical model for an ORC based district heating renewable energy system considering discrete analysis

Renewable energy sources may help build energy-efficient, ecologically friendly communities. District heating systems are crucial for distributed renewable energy. The objective of this study is to establish a theoretical framework for a district heating distribution system capable of accommodating bi-directional flow and effectively serving a large number of consumers. Distinction and continuity are present in District Heating System fuel selection and energy demand determination. Scholarly literature suggests many modeling methods for discrete and continuous consumer decision-making. This method has been used to solve transportation, housing, and water problems. The overall demand for consumer choices can be separated into two components: a discrete component with several possibilities and a continuous component. Energy includes social, economic, security, climate, and environmental factors. This study analyzed previous energy logical modeling methods and examines energy consumption trends and climate change. This study supports its claims on modern conflicts using expert interviews, research expertise, and a thorough literature assessment. The model was used to assess control system architectural improvements and low-cost device integration. This study shows the versatility of using real data and model output under varied boundary conditions by using validation. The research suggests that adding waste heat input may make pressure equilibrium in nearby consumer substations harder. Despite assumptions and simplifications, the results show waste heat source features, benefits, and limitations.

Pedestrians injuries in the north east region of Jamaica: a cross sectional study

ABSTRACT To describe the sociodemographic data of injured pedestrians, temporal patterns of injury, injury patterns, and the independent predictors of hospital admission. A two year cross-sectional study was conducted at the Saint Ann’s Bay Regional Hospital in pedestrians with injuries post collision with a motor vehicle. A census was performed in all patients who received either emergency room treatment, hospital admission, or surgical intervention. A 30-item interviewer questionnaire was administered to collect the data. A logical regression model was used to determine independent predictors for hospital admission. Ninety pedestrians were included. Age range: 6-86 years old (Mean=39.9). Males were 63.3%, 75.6% were employed, 31% had a chronic illness and 27% reported marijuana use. Most injuries occurred in April, lowest injury rates occurred in August and September. Twenty two percent of collisions occurred on Saturdays. Most injuries occurred at 5pm and 3pm. Many (54.4%) had a fracture, 73.5% were closed. Approximately 32% had contusions and 6.7% had lacerations. Independent predictors of admission were history of marijuana use and having a fracture. Those with history of marijuana use were 4.21 times more likely to be admitted. Those with fractures were 7.10 times more likely to be admitted. Injury patterns spanned a wide age range. They often involved a high energy mechanism of injury as evidenced by the frequency of fractures, hospital admission and surgery intervention rates. The data also suggests a need to implement marijuana testing programmes in our road users.

D2D Self Organization in IOT via Triple Modular Redundancy Based MDS Code

Device-to-Device (D2D) communication is a key enabling technology to replace base station-to-device(B2D) communication. D2D with IoT realization has spectral and energy-efficient features for on-time quality data transfer. However, the rapid growth of such networks and the dynamic quality of service demands of user equipment require robust and efficient service quality in disasters, outages, and adversarial conditions. To address this challenge, this paper proposes a triple modular redundancy based on the maximum distance separable (TMR-MDS) technique has been proposed, which modifies the repair bandwidth by utilizing more storage occupation and improving the D2D link availability in the system. The proposed TMR-MDS technique will be used, which is composed of two phases: trust management modules and triple modular redundancy storage modules. As part of the initial stage of trust management, a fuzzy logic model is employed to determine the user’s trust value after the user’s behaviour is examined. Second, using the majority voting scheme to improve triple modular redundancy storage. Furthermore, if any problem occurs in the node, then it will self-organize. MATLAB is used to evaluate the performance of the proposed system. The overall system performance is evaluated in terms of the network’s trust level, and the communication cost of the proposed strategy. As per the experimental results, the proposed TMR-MDS method has a better performance of 12.67%, 23.68%, and 25.87% than hierarchical bi-partite, double replication MDS, and unequal repairing locality code.

Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction.

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

Discussing Patient Emotions in Audiology: Provider Experiences With the Implementation Process of Hearing Loss Psychological Inflexibility Screenings.

This study aimed to investigate barriers and facilitators experienced by clinical educators and graduate students when talking with patients about difficult emotions and thoughts related to their hearing. A longitudinal observational design was used and an Implementation Research Logic Model guided the process. Five clinical educators and five graduate students participated in the study. Participants completed pre- and postmeasures and attended individual debriefing sessions during the 8-month study period. Four themes emerged from the debriefing sessions: (a) learning process, (b) confidence, (c) barriers, and (d) supervision. Participants described that the Acceptance and Action Questionnaire-Managing Child Hearing Loss and Acceptance and Action Questionnaire-Adult Hearing Loss served as a reminder to ask about patients' internal barriers and increased awareness of their discomfort in talking about patient emotions. Participants also described barriers and struggles related to supporting students in gaining counseling skills. Screening for internal challenges helped clinicians remember to talk with patients about their difficult thoughts and emotions. Clinician hesitancy to engage in conversations with patients about their emotions can interfere with opportunities for patients to share their struggles and with training student in these skills.

Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

Picking Apart a Program Evaluation Committee: A Multiple Case Study Characterizing Primary Care Residency Program Evaluation Committee Structure, Program Improvement, and Outcomes.

As of 2014, the Accreditation Council for Graduate Medical Education (ACGME) mandates initiating a Program Evaluation Committee (PEC) to guide ongoing program improvement.However, little guidance nor published reports exist about how individual PECs have undertaken this mandate. To explore how four primary care residency PECs configure their committees, review program goals and undertake program evaluation and improvement. We conducted a multiple case study between December 2022 and April 2023 of four purposively selected primary care residencies (e.g., family medicine, pediatrics, internal medicine). Data sources included semi-structured interviews with four PEC members per program and diverse program artifacts. Using a constructivist approach, we utilized qualitative coding to analyze participant interviews and content analysis for program artifacts. We then used coded transcripts and artifacts to construct logic models for each program guided by a systems theory lens. Results: Programs adapt their PEC structure, execution, and outcomes to meet short- and long-term needs based on organizational and program-unique factors such as size and local practices. They relied on multiple data sources and sought diverse stakeholder participationto complete program evaluation and improvement. Identified deficiencies were often categorized as internal versus external to delineate PEC responsibility, boundaries, and feasibility of interventions. The broad guidance provided by the ACGME for PEC configuration allows programs to adapt the committee based on individual needs. However, further instruction on program evaluation and organizational change principles would augment existing PEC efforts.

Opening the Black Box of Implementation: Developing the Creating Active Schools Logic Model

ABSTRACT Global guidance is driving systems thinking to the forefront of research, policy, and practice. To achieve this, we need to consider how things work to ensure successful implementation. The use of the implementation research logic model as a contemporary tool to aid the planning, reporting, synthesizing, executing, and evaluating of the novel Creating Active Schools (CAS) program is illustrated. A five-step iterative process, underpinned by the implementation research logic model, was undertaken to hypothesize and identify conceptual pathways between the CAS: 1) program determinants, 2) program components and actions, 3) implementation strategies, 4) mechanisms of action, and 5) outcomes. Throughout development, school-based and CAS stakeholders engaged in reviewing appropriate implementation theories, models and frameworks, terminology, and content. An in-depth CAS logic model was created to detail the CAS program and underpinning mechanisms. This article provides novel insights into how contemporary implementation tools can be applied and adapted to enhance the planning, reporting, synthesizing, executing, and evaluating of complex interventions and strategies. The CAS logic model provides a blueprint for future school-based interventions to develop evidence-based logic models and to increase the likelihood of acceptance, feasibility, and sustainability.

Relationship between staff and quality of care in care homes: StaRQ mixed methods study.

Quality of life and care varies between and within the care homes in which almost half a million older people live and over half a million direct care staff (registered nurses and care assistants) work. The reasons are complex, understudied and sometimes oversimplified, but staff and their work are a significant influence. To explore variations in the care home nursing and support workforce; how resident and relatives' needs in care homes are linked to care home staffing; how different staffing models impact on care quality, outcomes and costs; how workforce numbers, skill mix and stability meet residents' needs; the contributions of the care home workforce to enhancing quality of care; staff relationships as a platform for implementation by providers. Mixed-method (QUAL-QUANT) parallel design with five work packages. WP1 - two evidence syntheses (one realist); WP2 - cross-sectional survey of routine staffing and rated quality from care home regulator; WP3 - analysis of longitudinal data from a corporate provider of staffing characteristics and quality indicators, including safety; WP4 - secondary analysis of care home regulator reports; WP5 - social network analysis of networks likely to influence quality innovation. We expressed our synthesised findings as a logic model. English care homes, with and without nursing, with various ownership structures, size and location, with varying quality ratings. Managers, residents, families and care home staff. Staffing's contribution to quality and personalised care requires: managerial and staff stability and consistency; sufficient staff to develop 'familial' relationships between staff and residents, and staff-staff reciprocity, 'knowing' residents, and skills and competence training beyond induction; supported, well-led staff seeing modelled behaviours from supervisors; autonomy to act. Outcome measures that capture the relationship between staffing and quality include: the extent to which resident needs and preferences are met and culturally appropriate; resident and family satisfaction; extent of residents living with purpose; safe care (including clinical outcomes); staff well-being and job satisfaction were important, but underacknowledged. Many of our findings stem from self-reported and routine data with known biases - such as under reporting of adverse incidents; our analysis may reflect these biases. COVID-19 required adapting our original protocol to make it feasible. Consequently, the effects of the pandemic are reflected in our research methods and findings. Our findings are based on data from a single care home operator and so may not be generalised to the wider population of care homes. Innovative and multiple methods and theory can successfully highlight the nuanced relationship between staffing and quality in care homes. Modifiable characteristics such as visible philosophies of care and high-quality training, reinforced by behavioural and relational role modelling by leaders can make the difference when sufficient amounts of consistent staff are employed. Greater staffing capacity alone is unlikely to enhance quality in a cost-effective manner. Social network analysis can help identify the right people to aid adoption and spread of quality and innovation. Future research should focus on richer, iterative, evaluative testing and development of our logic model using theoretically and empirically defensible - rather than available - inputs and outcomes. This study is registered as PROSPERO CRD42021241066 and Research Registry registration: 1062. This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/144/29) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 8. See the NIHR Funding and Awards website for further award information.

130 Developing a Conceptual Data Model for Nursing Workload

OBJECTIVES/GOALS: Nurses are leaving the profession at an alarming rate due to increased workload and burnout.#_msocom_1 Computational models that are reliable and reproducible are needed to quantitatively examine nursing workload and estimate potential effect of interventions. This project developed a logical data model to represent nursing EHR interactions. METHODS/STUDY POPULATION: With nursing EHR interactions as a starting point, we expand upon literature that examined the EHR workload of physicians. We conducted an exploratory analysis of nursing EHR audit log data at a large academic medical center, and explored components of nursing workload that can be extracted from other health system data. Using concepts derived from the studying temporal biomedical data patterns, we formulated a data structure that describes nurse EHR interactions, nurse intrinsic and situational characteristics, and nurse outcomes of interest in a scalable and extensible manner. RESULTS/ANTICIPATED RESULTS: Temporal machine learning models are grounded in the concept of vectors. We developed a logical data model that describes tasks performed by nurses (NTask), nurse types (NType), and nursing outcomes (NOutcome). For each nurse (k), we define a function <NTask (k, i)>, i=1 to N as a vector of dimension N, where N is the number of time periods in the study. The i component corresponds to the activity that the nurse is doing. The model will allow the quantitative classification of activity patterns for any finite number of nurses for an arbitrary set of tasks and for time at any specified resolution. The expected outcome is a set of vectors that can then be utilized to quantitatively model nurse activity trajectories and other patterns of nurse EHR interactions. DISCUSSION/SIGNIFICANCE: By instantiating the logical data model, we will demonstrate how nurse EHR interactions can be studied using temporal unsupervised learning and state-of-the-art artificial intelligence methods. We plan to simulate the potential impact of workload interventions and predict risk for nurse burnout.

Measuring Color Index of Transformer Oil–Enabling Single-Wavelength Spectroscopy With Artificial Neural Network-Fuzzy Logic Model

Conventionally, the color index of transformer oil is determined by a color comparator based on the American Society for Testing and Materials (ASTM) D 1500 standard. The equipment requires humans to operate, which leads to human error and limited number of samples tested per day. This work proposes the utilization of single-wavelength spectroscopy with 405 nm laser diode using artificial neural network (ANN) to determine the color index of transformer oil. Two ANN models were developed using data collected from 50 oil samples with different optical pathlengths of 1 to 10 mm, and laser output powers of 1 to 15 mW. The first model classified the input into different color indices and another model correlated the input parameters through regression analysis to determine the color index. A hybrid ANN-fuzzy logic model was also developed to improve the color index prediction. The root-mean-squared error (RMSE) obtained from the prediction by ANN regressor and ANN classifier are 0.5602 and 0.6416, respectively. The hybrid ANN-fuzzy logic model improves the RMSE especially for optical pathlengths <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&lt;$</tex-math> </inline-formula> 5 mm, which is required for measuring samples with high color index. This proposed method reduces the dependency on complex optoelectronic hardware to obtain highly accurate results. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Unlike the conventional testing method for color index of transformer oil that requires human observation, the findings of this study enables the possibility of compact and smart portable device through the utilization of single wavelength spectroscopy with machine learning models. With no human involvement, more computational power with lesser hardware dependency, the maintenance cost and error can be reduced. This proposed method can potentially be applied to measure the color of other amber-colored liquid products such as olive oil, honey and others.

180 Building an evaluation platform to capture the impact of Frontiers CTSI activities

OBJECTIVES/GOALS: In 2021, Frontiers CTSI revamped its evaluation infrastructure to be comprehensive, efficient, and transparent in demonstrating outputs and outcomes. We sought to build a platform to standardize measures across program areas, integrate continuous improvement processes into operations, and reduce the data entry burden for investigators. METHODS/STUDY POPULATION: To identify useful metrics, we facilitated each Core’s creation of a logic model, in which they identified all planned activities, expected outputs, and anticipated outcomes for the 5-year cycle and beyond. We identified appropriate metrics based on the logic models and aligned metrics across programs against extant administrative data. We then built a data collection and evaluation platform within REDCap to capture user requests, staff completion of requests, and, ultimately, request outcomes. We built a similar system to track events, attendance, and outcomes. Aligning with other hubs, we also transitioned to a membership model. Membership serves as the backbone of the evaluation platform and allows us to tailor communication, capture demographic information, and reduce the data entry burden for members. RESULTS/ANTICIPATED RESULTS: The Frontiers Evaluation Platform consists of 9 redcap projects with distinct functions and uses throughout the Institute. Point-of-service collection forms include the Consultation Request Event Tracking. Annual Forms include a Study Outcome, Impact, and Member Assessment Survey. Set timepoint collections include K &amp; T application, Mock Study Section, and Pilot grant application submission, review, and outcomes. Flight Tracker is used to collect scientific outcomes and integrated with the platform. Using SQL, the membership module has been integrated into all forms to check and collect membership before service access and provide relevant member data to navigators. All relevant data is then synched into a dashboard for program leadership and management to track outputs and outcomes in real-time. DISCUSSION/SIGNIFICANCE: Since the launch of the evaluation platform in Fall 2022, Frontiers has increased its workflow efficiency and streamlined continuous improvement communication. The platform can serve as a template for other hubs to build efficient processes to create comprehensive and transparent evaluation plans.

Advancing the decadal plan for the science of nutrition: Progressing a framework for implementation.

In 2019, the Australian Academy of Science in collaboration with the nutrition community published the decadal plan for the science of nutrition. This article aims to review progress towards each of its pillar goals (societal determinants, nutrition mechanisms, precision and personalised nutrition, and education and training) and two enabling platforms (a national data capability and a trusted voice for nutrition science), prioritise actions, and conceptualise program logic implementation models. This process also brought together public health nutrition researchers to reflect on societal determinants of health, and advise how the next 5 years of the decadal plan could reflect contemporary issues. Two engagement events, in 2023, brought together experienced and mid- and early-career nutrition professionals for co-creation of implementation logic models. One hundred and nine early and mid-career professionals were involved. A revised model for the decadal plan pillars emerged from synthesis of all logic models. This new model integrated the precision and personalised nutrition pillar with nutrition mechanisms pillar. These combined pillars build towards the national data capability enabling platform and created new cross-cutting themes for education and training. The need arose for greater focus on respectful engagement with Aboriginal and Torres Strait Islander communities and sustained effort to build cross-disciplinary collaboration to realise the plan's societal determinants goals. A new alliance for nutrition science is proposed to become a unified advocacy voice and build trust in nutrition professionals. A programmatic approach provides a road map for implementing the decadal plan for the final 5 years.

Deprivatization: current judicial practice

The article considers the legal framework and trends of judicial practice in claims for the recovery of previously privatized assets. The purpose is to identify risk factors for the deprivatization of enterprise property, as well as circumstances affecting the prospects of possible litigation. The authors used such research methods as logical, theoretical-prognostic, formal-legal, system-structural and legal modeling methods. The methodological apparatus consists of the following dialectical techniques and methods of scientific cognition: analysis, abstraction, induction, deduction, hypothesis, analogy, synthesis, typology, classification, systematization and generalization. The authors analyzed relevant legal cases within the context of legal regulation and doctrinal approaches to the interpretation of civil legislation. It is concluded that violation of the privatization procedure means the absence of the will of the public owner to property alienation. As a result, the public owner has the opportunity to claim property even from a bona fide purchaser. Shares in the authorized capital of companies, and individual objects (buildings, structures, movable property) are subject to deprivatization. The basis for the claim of property in favor of the state is most often the privatization of property classified as federal property, with the approval of only regional authorities as well as the privatization of property in respect of which prohibitions and restrictions are established. It is stated that the courts reject references to the expiration of the limitation period, at the same time, judicial practice regarding the application of objective limitation periods has only begun to form. Considering the specifics of the participation of public legal entities in civil turnover, the authors conclude that it is necessary to clarify the established practice of applying law by the Constitutional Court of the Russian Federation.

Social prescribing for people living with dementia (PLWD) and their carers: what works, for whom, under what circumstances and why – protocol for a complex intervention systematic review

IntroductionDementia is a complex medical condition that poses significant challenges to healthcare systems and support services. People living with dementia (PLWD) and their carers experience complex needs often exacerbated by...

Qualified Listening to Relatives of Users at a Psychosocial Care Center

Introduction. The Psychiatric Reform introduced a new people-centered care model to replace psychiatric hospitals: the Psychosocial Care Center. Qualified listening can be used to achieve the integrality and humanization of the health care provided. It allows for the appreciation of content, the respect of its uniqueness, empathy, and the promotion of a space in which freedom of expression is provided. Objective. To identify the understanding of qualified listening from the perspective of the relative of a person with a mental disorder at a Psychosocial Care Center. Method. Qualitative, descriptive, exploratory study. Ten relatives over the age of 18 participated, contributing to the production of information. Data was obtained through the triangulation method, through semi-structured individual and collective interviews, observation, and field diary records. Results. For relatives, qualified listening translates into clarifying the illness, understanding the family’s painful situation and providing help and support during the psychosocial rehabilitation process. Discussion and conclusion. Listening constitutes a means of consolidating care networks, through the strengthening of bonds and co-responsibility, in a centered and expanded family-user logic model.

Alpha 2 agonists for sedation to produce better outcomes from critical illness (A2B trial): protocol for a mixed-methods process evaluation of a randomised controlled trial

IntroductionAn association between deep sedation and adverse short-term outcomes has been demonstrated although this evidence has been inconsistent. The A2B (alpha-2 agonists for sedation in critical care) sedation trial is...