Placement Model Research Articles

Virtual Network Function Placement Model Considering Both Availability and Probabilistic Protection for Service Delay

This paper proposes a virtual network function (VNF) placement model considering both availability and probabilistic protection for the service delay to minimize the service deployment cost. Both availability and service delay are key requirements of services; a service provider handles the VNF placement problem with the goal of minimizing the service deployment cost while meeting these and other requirements. The previousworks do not consider the delay of each route which the service can take when considering both availability and delay in the VNF placement problem; only the maximum delay was considered. We introduce probabilistic protection for service delay to minimize the service deployment cost with availability. The proposed model considers that the probability that the service delay, which consists of networking delay between hosts and processing delay in each VNF, exceeds its threshold is constrained within a given value; it also considers that the availability is constrained within a given value. We develop a two-stage heuristic algorithm to solve the VNF placement problem; it decides primary VNF placement by solving mixed-integer second-order cone programming in the first stage and backup VNF placement in the second stage. We observe that the proposed model reduces the service deployment cost compared to a baseline that considers the maximum delay by up to 12%, and that it obtains a feasible solution while the baseline does not in some examined situations.

A novel cost-based replica server placement for optimal service quality in cloud-based content delivery network

<span lang="EN-US">Replica server placement is one of the crucial concerns for a given geographic diversity associated with placement problems in content delivery network (CDN). After reviewing the existing literatures, it is noted that studies are more for solving placement problem in conventional CDN and not much over cloud-based CDN architectures, which some few studies are reported towards replica selection are much in its nascent stages of development. Moreover, such models are not benchmarked or practically assessed to prove its effectiveness. Hence, the proposed study introduces a novel design of computational framework associated with cloud-based CDN which can facilitate cost-effective replica server management for enhanced service delivery. Implemented using analytical research methodology, the simulated study outcome shows that proposed scheme offers reduced cost, reduced resource dependencies, reduced latency, and faster processing time in contrast to existing models of replica server placement.</span>

Implementing a Near Peer Instructor Placement Model in Physiotherapy Education

Purpose: The aim of this case report is to describe the design, implementation, and outcomes of a near peer instructor (NPI) placement for a physiotherapy student. Client Description: Participants included a Year-2 placement student (the NPI), Year-1 students from the McMaster Master of Science (Physiotherapy) Program, the anatomy instructor (AI), and the director of clinical education (DCE). Intervention: The AI and DCE designed a two day/week placement whereby the NPI developed and facilitated clinical application stations during scheduled anatomy and physiology (A&P) sessions with Year-1 physiotherapy students. Measures and Outcomes: Students, the AI and NPI provided feedback through surveys for the purpose of placement evaluation. Implications: Three areas of impact of this placement model were identified: (1) greater perceived ability of learners to integrate A&P knowledge with clinical skills, (2) NPI growth in transferrable skills and the seven essential competencies required of physiotherapists in Canada, and (3) additional clinically relevant A&P curricular resources.

Development of the agro-industrial complex of the Republic of Moldova, ways to improve the sphere and management system

Relevance of the research. The agro-industrial complex is the most important component of the economy of the Republic of Moldova. The protracted crisis of the agrarian sphere was, first of all, the result of the weakening of the role of state regulation and the management system of the agro-industrial complex. The effective economic development of the agricultural sector of the Republic of Moldova at the macro and micro levels requires the improvement of the system of management of the agricultural sector at all levels. Formulation of the problem. Related to the improvement of management at all levels of the country's agro-industrial complex, namely the competitiveness of enterprises under the influence of various risk factors, the correct formation of strategic management at the level of the state and enterprises, the use in the production of certain models of rational placement of production infrastructure for the effective development of enterprises, which ultimately ensure the sustainable economic growth of the country's agricultural sector. Setting the task, the purpose of the study. The purpose and objectives of the article are to study the structure of the agro-industrial complex management system, the dynamics of the main indicators characterizing the state of agriculture of the Republic of Moldova; identify problems, and develop recommendations for improving the management system of the agro-industrial complex of Moldova. Material and methodology. During the writing of the article, general scientific and special methods were used, namely the abstract-logical, statistical-economic, and graphic methods. The information and empirical base of the study are based on data from the National Bureau of Statistics of the Republic of Moldova. Presentation of the main material (results of work). The article conducted a study of the composition of the agro-industrial complex of the Moldavian SSR; the current state management system of the agro-industrial complex was analyzed; the degree of impact of reforms on the management structure of the agro-industrial complex was determined; in-depth analysis of the main indicators characterizing the state of this industry was carried out; proposed are directions of market infrastructure development through suitable channels of agricultural products distribution. Field of application of results. The materials, results, and conclusions of the study can be used by government bodies, higher education institutions, and student organizations. Conclusions according to the article. The results of the reforms carried out in the agricultural sector of the country's economy were summarized, problems that arose as a result of the ongoing reorganizations in the agro-industrial complex system were identified, and a deep analysis of the development of the agricultural economy was made. The authors also presented recommendations for improving the processes of management of the agricultural sector of the Republic of Moldova, and presented the author's conceptual approaches to the formation of the composition of the agro-industrial complex.

An equitable patient reallocation optimization and temporary facility placement model for maximizing critical care system resilience in disasters

Medical infrastructure disruptions during disasters pose a major threat to critically ill patients with advanced chronic kidney disease or end-stage renal disease. There is a need to assess the potential threat to critical care facilities from hazardous events to improve patient access to dialysis treatment. We propose optimization models for patient reallocation and temporary medical facility placement to equitably improve critical care system resilience. We leverage human mobility data in Texas to assess patient access to critical care facilities and dialysis centers under the simulated hazard impacts. The optimization model was formulated as an integer programming and solved by COIN-OR Branch-and-Cut (CBC) solver. The results show (1) the capability of the optimization model in efficient patient reallocation to alleviate disrupted access to dialysis facilities; (2) the importance of large facilities in maintaining the system functionality. The critical care system, particularly the network of dialysis centers, is heavily reliant on a few larger facilities, characteristic of scale-free networks, making it susceptible to targeted disruption, such as capacity failures. (3) Considering equity in the optimization model formulation reduces access loss for vulnerable populations in the simulated scenarios. (4) The proposed temporary facilities placement could improve access for the vulnerable population, thereby improving the equity of access to critical care facilities in disaster. The proposed patient reallocation optimization model and temporary facilities placement offer a data-driven and analytics-based decision support tool tailored to the needs of healthcare organizations across private and public sectors to proactively mitigate the potential loss of access to critical care facilities during disasters.

Near-perfect turning of robot-based 3D printing continuous carbon fiber reinforced nylon composites based on fiber-scale internal stress characterization

Mechanical metamaterials based on continuous fiber reinforced composites exhibit excellent mechanical properties. Continuous fiber 3D printing is counted as an ideal manufacturing approach for mechanical metamaterials. Currently, most metamaterial lattice structures are printed at centimeter-scale. The significant change in the width of the printed filament caused by fiber twist and shift during steering is an obvious defect when turning with minor radius. Near-perfect turning is proposed herein as a turning under the smallest possible printing radius, and the printed filaments present superior width retention rate. The key to printing high-precision composite lattice structures below centimeter-scale is to assess the near-perfect turning radius. Therefore, a fiber near-perfect turning placement model was established and the near-perfect turning radius ra was assessed by measuring the fiber-scale internal stress required in the model. The precision evaluations show that the near-perfect turning radius calculated by the model is in good agreement with the experimental value, proving the model’s validity. In the case of the Robot-based printing platform and Nylon-carbon fiber composites, the near-perfect turning radius is 2.0 mm. This study establishes a solid process foundation for metamaterial manufacturing below the centimeter scale.

An integrated vertiport placement model considering vehicle sizing and queuing: A case study in London

The increasing level of congestion and infrastructure costs in cities have created a need for more intelligent and flexible transport systems. Urban Air Mobility (UAM) introduces the third dimension to intra-urban transport at a minimal infrastructure cost, bypassing congestion and providing reliable travel times to users through the provision of air passenger transportation. The performance of UAM systems is highly dependent on vertiport locations, vehicle sizing and infrastructure specifications, which themselves are intrinsically linked. This study takes a holistic approach to UAM network optimisation by considering the inter-relatedness of these decisions in a three-stage algorithm. In the first stage, a linear vertiport placement model with vehicle sizing constraints is developed to determine the optimal vertiport configuration while considering eVTOL performance. The vertiport configuration serves to determine the operational requirements of the aircraft and are incorporated in the vehicle sizing models. The resulting network configuration and vehicle sizing constraints are used as inputs in the infrastructure model, which utilises open network theory to determine the service rate requirements and the allowed loiter and waiting times based on the number of take-off, landing, and charging pads at each vertiport. These stages are executed sequentially through a feedback mechanism, which balances the infrastructure, operational costs as well as passenger waiting times. The algorithm optimises the profitability of the UAM network ensuring all operational constraints are satisfied. A case study based on the hypothetical implementation of UAM in the city of London is presented using Rolling Origin and Destination Survey data to estimate demand patterns. Our results suggest that ignoring vehicle sizing and infrastructure modelling in the network optimisation stage results in infeasible UAM networks. Furthermore, reducing waiting times and loiter times are critical to reduce operational costs of the UAM network, with all optimal configurations yielding waiting times below 5% of the total flight time. The proposed method can be used to plan future UAM developments whilst ensuring operational viability.

An MILP model for reliability-based placement of recloser, sectionalizer, and disconnect switch considering device relocation

An MILP model for reliability-based placement of recloser, sectionalizer, and disconnect switch considering device relocation

Intelligent Base Station Placement in Urban Areas With Machine Learning

This paper presents a time-reliable machine learning model for accurate and rapid base station placement in urban areas. Several real-world city data are used for training the machine learning model to predict parameters such as path loss values. It is developed using supervised training and multiple regressions with the use of artificial intelligence. Parameters such as coverage dimensioning, bandwidth of frequencies, building's density and height, propagation model tuning and path loss values are used to predict the locations of base stations. Once the predicted base station position is obtained, the average percentage error is calculated against the real-world data of base station that shows an accuracy of 84%. This proves that our model is a reliable tool to predict future base station locations. This model will benefit the telecommunication industries to reduce time and cost for rapid base station planning in urban areas that see frequent changes to their landscapes.

A Mixed-Methods Implementation Evaluation of Virtual Reality Job Interview Training in IPS Supported Employment.

Employment rates among individuals with serious mental illness may be improved by engagement in the individual placement and support (IPS) model of supported employment. Results from a recent randomized controlled trial (RCT) indicate that virtual reality job interview training (VR-JIT) improves employment rates among individuals with serious mental illness who have been actively engaged in IPS for at least 90 days. This study reports on an initial implementation evaluation of VR-JIT during the RCT in a community mental health agency. A sequential, complementary mixed-methods design included use of qualitative data to improve understanding of quantitative findings. Thirteen IPS staff trained to lead VR-JIT implementation completed VR-JIT acceptability, appropriateness, and feasibility surveys. Participants randomly assigned to IPS with VR-JIT completed acceptability (N=42) and usability (N=28) surveys after implementation. The authors also conducted five focus groups with IPS staff (N=11) and VR-JIT recipients (N=13) and semistructured interviews with IPS staff (N=9) and VR-JIT recipients (N=4), followed by an integrated analysis process. Quantitative results suggest that IPS staff found VR-JIT to be highly acceptable, appropriate for integration with IPS, and feasible for delivery. VR-JIT was highly acceptable to recipients. Qualitative results add important context to the quantitative findings, including benefits of VR-JIT for IPS staff as well as adaptations for delivering technology-based interventions to individuals with serious mental illness. These qualitative and quantitative findings are consistent with each other and were influenced by VR-JIT's adaptability and perceived benefits. Tailoring VR-JIT instruction and delivery to individuals with serious mental illness may help optimize VR-JIT implementation within IPS.

Preoperative Planning Framework for Robot-Assisted Dental Implant Surgery: Finite-Parameter Surrogate Model and Optimization of Instrument Placement.

For robot-assisted dental implant surgery, it is necessary to feed the instrument into a specified position to perform surgery. To improve safety and efficiency, a preoperative planning framework, including a finite-parameter surrogate model (FPSM) and an automatic instrument-placement method, is proposed in this paper. This framework is implemented via two-stage optimization. In the first stage, a group of closed curves in polar coordinates is used to represent the oral cavity. By optimizing a finite number of parameters for these curves, the oral structure is simplified to form the FPSM. In the second stage, the FPSM serves as a fast safety estimator with which the target position/orientation of the instrument for the feeding motion is automatically determined through particle swarm optimization (PSO). The optimized feeding target can be used to generate a virtual fixture (VF) to avoid undesired operations and to lower the risk of collision. This proposed framework has the advantages of being safe, fast, and accurate, overcoming the computational burden and insufficient real-time performance of complex 3D models. The framework has been developed and tested, preliminarily verifying its feasibility, efficiency, and effectiveness.

One-shot models for local core network placement and traffic optimization in self deployable networks

In recent years, we have witnessed a proliferation of core network (CN) virtualization, coupled with the emergence of self deployable architectures in cellular networks. These advances provide greater flexibility and allow CN functions to be virtualized and co-located with one or more base stations. However, they introduce new challenges, such as the optimal location of CN functions based on the physical architecture. In this paper, we tackle this problem and propose a new generic and efficient solution that locates the best base station to host the CN functions, while optimizing a given performance metric (e.g., maximum flow, max–min fairness, etc.) The core of our solution relies on jointly modeling the problem as a Mixed-Integer Nonlinear Programming (MINLP) and efficiently linearizing the nonlinear constraints. After presenting our model, we evaluate its performances, considering the global maximum flow as an optimization metric. The results showed that our joint modeling significantly reduces the run time compared to existing solutions while achieving the same optimal results. Furthermore, we highlight the genericity of our model, and we show how it can be easily adapted to handle different optimization metrics. We particularly consider some variants to address the fairness problem in conjunction with the local CN placement issue. We perform extensive simulations and discuss the obtained results. The latter allow us to derive insights regarding the tradeoff between maximum flow and fairness of proportional satisfaction, while highlighting the strengths of the proposed joint modeling.

CREB3L2 Regulates Hemidesmosome Formation during Epithelial Sealing.

The long-term success rate of dental implants can be improved by establishing a favorable biological sealing with a high-quality epithelial attachment. The application of mesenchymal stem cells (MSCs) holds promise for facilitating the soft tissue integration around implants, but the molecular mechanism is still unclear and the general application of MSC sheet for soft tissue integration is also relatively unexplored. We found that gingival tissue-derived MSC (GMSC) sheet treatment significantly promoted the expression of hemidesmosome (HD)-related genes and proteins in gingival epithelial cells (GECs). The formation of HDs played a key role in strengthening peri-implant epithelium (PIE) sealing. Further, high-throughput transcriptome sequencing showed that GMSC sheet significantly upregulated the PI3K/AKT pathway, confirming that cell adhesion and HD expression in GECs were regulated by GMSC sheet. We observed that the expression of transcription factor CREB3L2 in GECs was downregulated. After treatment with PI3K pathway inhibitor LY294002, CREB3L2 messenger RNA and protein expression levels were upregulated. Further experiments showed that overexpression or knockdown of CREB3L2 could significantly inhibit or promote HD-related genes and proteins, respectively. We confirmed that CREB3L2 was a transcription factor downstream of the PI3K/AKT pathway and participated in the formation of HDs regulated by GMSC sheet. Finally, through the establishment of early implant placement model in rats, we clarified the molecular function of CREB3L2 in PIE sealing as a mechanical transmission molecule in GECs. The application of GMSC sheet-implant complex could enhance the formation of HDs at the implant-PIE interface and decrease the penetration distance of horseradish peroxidase between the implant and PIE. Meanwhile, GMSC sheet reduced the length of CREB3L2 protein expression on PIE. These findings elucidate the potential function and molecular mechanism of MSC sheet regulating the epithelial sealing around implants, providing new insights and ideas for the application of stem cell therapy in regenerative medicine.

The Method of Restoring Parameters of Mobile Agents in a Unified Dynamic Environment Considering Similarity Coefficients

We described the placing of the mobile agents in a dynamic environment. It formed a dynamic environment for a complex of dynamically changing mobile agents. We described a two-level system of connections at the global and local levels of interaction. Such a scheme allows you to support the survivability of a dynamic environment. We presented the model of placement of mobile agents in a dynamic environment, which forms the basis of the trajectory of interaction between mobile agents, enabling us to combine the dynamic environment into a unified dynamic environment. The proposed method for mobile agents parameters restoring in a unified dynamic environment, taking into account the similarity coefficients, allows restore 80% parameters of an inaccessible mobile agent. This indicates the high efficiency of the objects description in the form of a unified dynamic environment in order to maintain its integrity.

Testing Effects of Job Satisfaction and OCBs on the Relationship between Talent Management and Talented Employee Turnover for Sustainable Human Resource Development in Healthcare

Purpose; The purpose of this study is to better understand the impact of talent management on reducing turnover of talented staff in the Nigerian public health sector. This requires considering the mediating role of both job satisfaction and OCB variables in achieving success at both individual and organisational levels.
 Design/methodology/approach; This study achieves its objective through a conceptual analysis using the lenses of talent management, social exchange theory (SET) and existing literature.
 Findings; This study shows that good talent management is not enough to retain and sustain talented employees in the Nigerian health sector. The partial placement model hypotheses were supported by the SET model, implying that talent management requires both job satisfaction of talented employees and OCB to reduce turnover of talented employees.
 Practical implications; This study enhances the use of the mediating role of job satisfaction and OCBs to better understand the mechanism of talent management in reducing employee turnover within the framework of the social exchange theory model.
 Originality/value; The originality of this study states that effective implementation of talent management in the Nigerian health sector must be complemented with appropriate mechanisms to achieve effective retention of talented employees.

Patterns, no patterns, that is the question: Quantifying users’ electric vehicle charging

Policymakers have structured legislation and set targets to increase the adoption of electric vehicles and the deployment of charging stations. As questions arise on how to expand the electric vehicle infrastructure, advanced computational models are attempting to quantify the future placement of charging stations. These models, however, do not necessarily incorporate the variability of user behavior as a subgroup of consumer behavior, as this information is not well-understood. This paper explores a state-wide network of 68 public charging stations' data representing 58,273 charging events to determine users' charging patterns. The methodological approach applied k-means clustering with Minkowski embedded distances to distinguish unique charging subgroups from 608 frequent users. The results indicate four user types: convenient (n = 319, 53%), gradual (n = 147, 24%), anxious (n = 104, 17%), and urgent (n = 38, 6%). Quantifying these users’ unique patterns supports the human variability knowledge required for more comprehensive and holistic models of electric vehicle charging station placement. More broadly, these results support the user-centric design of public charging infrastructure, which assists in reducing the electric vehicle adoption threshold in the long run and facilitating the transition to a low-carbon, sustainable transportation system.

Supporting the needs of pre- and primary school children in rural Victoria: Multidisciplinary views and experiences.

Predicted effects on children from the COVID-19 pandemic include poorer mental health and increased behavioural and developmental concerns. Rural children are at higher risk due to socio-economic factors, isolation and reduced access to services. Investigation by health services into the physical, social and emotional needs of children in rural areas is critical to inform local health promotion planning, service delivery priorities and workforce capacity building. Located in a Modified Monash Model category 5, our northern Victorian health service undertook a child-focused needs assessment in order to be strategically responsive to community issues. The project utilised a quantitative community profiling approach and qualitative interviews with a purposive sample (n = 17) of multidisciplinary professionals. Three main themes emerged: (1) Perpetual navigation of rural access limitations highlighted professionals' exhaustion in working in environments with ongoing unmet needs. (2) Cycles of disadvantage and early intervention gaps identified flow-on negative effects, with concerning trends in poorer child outcomes. (3) Solutions through collaboration grouped ideas to improve support for children. Community-level enablement strategies could increase contact with allied health professionals for rural children and reduce reliance on individualised treatment approaches. One collaborative action is to pilot and evaluate allied health student placement models to deliver group programs for rural children.

Increasing capacity by moving away from one-to-one clinical supervision: using peer-assisted learning and a group model of student placements in community paediatric speech and language therapy to enable student-led service delivery.

Health Education England (HEE) and the Royal College of Speech and Language Therapists (RCSLT) have identified the need to increase placement capacity. Speech and language therapy is a shortage profession in the UK, so services need to consider innovative placement models to increase their placement offers without increasing the time burden on speech and language therapists (SLTs). To increase capacity for pre-registration practice-based learning by using peer-assisted learning (PAL) in a group model of student placement to enable student-led service delivery which provides high standards of clinical care and student experience and is an efficient use of SLT time. A paediatric speech and language therapy service hosted eight student speech and language therapists (SSLTs) for their final pre-registration placement. SSLTs completed pre- and post-placement confidence ratings for a range of clinical skills; SSLTs and SLTs rated how useful different types of support were, and education settings provided feedback about working with the SSLTs. The number of clinical sessions completed by the SSLTs and the percentage of outcomes achieved for children with speech, language and communication needs were calculated. SLTs completed time-trackers for placement-related activities. The impact of the placements was assessed using a tri-vector methodology consisting of: self-reporting by the student (using an evaluation form), feedback from the placement sites (schools) and analysis of targets set for individual children. SSLTs reported increased confidence in all clinical areas in their post-placement evaluation form. SLTs reported increased confidence in SSLTs working independently and an increase in the perceived benefit to the service for having SSLTs in comparison with the time invested in supporting SSLTs. SSLTs and SLTs found all types of support provided during the placement useful. Schools reported high levels of satisfaction for working with SSLTs. SSLTs completed more clinical sessions than an SLT would have been able to in the time SLTs invested in placement-related activities. Children achieved 60% of the targets set by SSLTs. This placement model increased the capacity for SSLT placements by using PAL in a group model of student placement to enable student-led service delivery. The model provided high standards of clinical care and student experience and was an efficient use of SLT time. Wider use of this placement model would increase placement capacity and could also address vacancies in services. What is already known on the subject SSLTs and SLTs are positive about the benefits of paired placements in comparison with individual placements. Other allied health professions have demonstrated that larger placements can be an effective way to support students and have used students to deliver student-led services. What this study adds to existing knowledge This paper is the first to look at whether PAL in a group model of student placements can be used in speech and language therapy to enable student-led service delivery which provides high standards of clinical care, maintains high standards of student experience and is an efficient use of SLT time. What are the potential or actual clinical implications of this work? This paper demonstrates that PAL can be used effectively in a group model of student placements in a paediatric SLT service to increase student capacity and enable student-led service delivery. The proposed placement model provides a high-quality placement for SSLTs and the children they work with, and is also an efficient use of SLT time.

Description of Standardized Planes and Angles for Percutaneous Supra-acetabular Screw Placement.

Percutaneous screw fixation for pelvic fractures has become a minimally invasive alternative to an open operation. The complex anatomy of the pelvis renders this procedure challenging. The objective of this study was to assess standardized angles and dimensions of safety zones within a 3D computed tomography model for optimal supra-acetabular screw placement. Computed tomography scans of 107 patients that suffered major trauma without showing any bone injury of the pelvis were collected. Using a software-based analysis, raw computed tomography data were transformed into 3D models to set standardized landmarks and determine the possible insertion corridor. Screws not exceeding a length of 97mm in females and 106.4mm in males were, in 95% of the evaluated cases, insertable without cortical bone penetration. The safety zone was 6.6mm for females and 7.9mm for males. Screws not exceeding these diameters were safely insertable in 95% of the cases. For the midsagittal plane, the angle was 36.4±5.1 on the left and 34.7±2.9 on the right (p=0.008). For the anterior pelvic plane, the angle was 31.3±4.5° on the left and 34.0±4.8° on the right (p=0.008). Percutaneous fixation using supra-acetabular screws is a promising method to treat simple supra-acetabular fractures. These results may improve its safe utilization and could facilitate its broader clinical application.

Enhancing educational and vocational recovery in adolescents and young adults with early psychosis through Supported Employment and Education (SEEearly): study protocol for a multicenter randomized controlled trial

BackgroundPsychotic disorders often develop a chronic course with devastating consequences for individuals, families, and societies. Early intervention programs for people in the first 5 years after the initial psychotic episode (early psychosis) can significantly improve the outcome and are therefore strongly recommended in national and international guidelines. However, most early intervention programs still focus on improving symptoms and relapse prevention, rather than targeting educational and vocational recovery. The aim of the present study is to explore the effects of Supported Employment and Education (SEE) following the Individual Placement and Support (IPS) model in people with early psychosis.MethodsThe SEEearly trial compares treatment as usual (TAU) plus SEE to TAU alone in outpatient psychiatric settings. The study is a six-site, two-arm, single-blinded, superiority randomized controlled trial (RCT). Participants are randomly assigned (1:1) to the intervention or control group. Aiming to recruit 184 participants, with an assumed drop-out rate of 22%, we will be able to detect a 24% difference in the main outcome of employment/education with 90% power. We make assessments at baseline and at 6- and 12-month follow-ups. Outcome data on employment/education, medication, and current psychiatric treatment is obtained monthly through phone based short assessments. The primary outcome is steady participation for at least 50% of the 12-month follow-up in competitive employment and/or mainstream education. Secondary employment outcomes capture length of employment/education, time to first employment/education, monthly wages/educational attainment, and social return on investment (SROI). Secondary non-employment outcomes include subjective quality of life, psychopathology, substance use, relapse, hospitalization, and functional impairment. To be eligible, participants must be between 16 and 35 years, fulfill diagnostic criteria for early psychosis, and be interested in competitive employment and/or mainstream education.DiscussionIn SEEearly, we hypothesize that participants with psychosis, who receive TAU plus SEE, present with better primary and secondary outcomes than participants, who receive TAU alone. Positive results of this study will justify SEE as an evidence-based strategy for clinical routine treatment in people with early psychosis.Trial registrationSEEearly was registered nationally and internationally in the German Clinical Trials Register (DRKS; identifier: DRKS00029660) on October 14, 2022.