Perceptions Of Collaboration Research Articles

Psychosocial interprofessional perinatal education: Design and evaluation of an interprofessional learning experience to improve students’ collaboration skills in perinatal mental health

BackgroundPerinatal mental health disorders are one of the leading causes of maternal illness and suffering and care and services need to be well coordinated by an interprofessional team who are skilled in working collaboratively. AimThe aim of this paper is to describe the design and evaluation of an innovative interprofessional education initiative to increase midwives and other health professional students’ knowledge and skills in caring collaboratively for women with psychosocial issues in the perinatal period, including women experiencing domestic and family violence. MethodsThe Psychosocial Interprofessional Perinatal Education workshop was designed for midwifery, psychology, social work and medical students. It provided a simulated learning experience with case studies based on real life situations. Students undertook pre and post surveys to measure changes in students’ perceptions of interprofessional collaboration and their experiences of participating in the interprofessional simulation-based learning activity. Quantitative survey data were analysed using paired t-tests and a qualitative content analysis was undertaken on the open-ended questions in the survey. FindingsComparison of pre and post surveys found students from all disciplines reported feeling more confident working interprofessionally following the workshop. The following categories were generated from analysis of the open ended survey data: Greater understanding of each others’ roles; Recognising benefits of interprofessional collaboration; Building on sense of professional identity; Respecting each other and creating a level playing field; and Filling a pedagogical gap. ConclusionThrough this innovative, simulated interprofessional education workshop students developed skills essential for future collaborative practice to support women and families experiencing psychosocial distress.

System Cognition and Analytic Technology of Cultivated Land Quality from a Data Perspective

As cultivated land quality has been paid more and more scientific attention, its connotation generalization and cognitive bias are widespread, bringing many challenges to the investigation and evaluation of regional cultivated land quality and its data analysis and mining. Establishing a systematic and interdisciplinary cognitive approach to cultivated land quality is urgent and necessary. Therefore, we explored and developed a conceptual framework of the model for the cultivated land quality analysis from the data perspective, including cultivated land quality ontology, mapping, correlation, and decision models. We identified the primary content of cultivated land quality perceptions and four cognitive mechanisms. We built vital technologies, such as the collaborative perception of the quality of cultivated land, intelligent treatment, diagnostic evaluation, and simulation prediction. Applying this analysis framework, we sorted out the frequency of indicators that characterize the function of cultivated land according to the literature in recent years and have built the cognitive system of cultivated land quality in the black soil region of Northeast China. The system’s central component was production capacity and it had three components: a foundation, a guarantee, and an effect. The black soil region cultivated land quality evaluation system has seven purposes involving 20–31 key indicators: production supply, threat control, farmland infrastructure regulation, cultivated land ecological maintenance, economics, social culture, and environmental protection. In various application contexts, the system had many critical supporting technologies. The results demonstrate that the framework has strong adaptability, efficiency, and scalability, which might offer a theoretical direction for further studies on the evaluation of the quality of cultivated land in the area. The analysis framework established in this study is helpful to deepen the understanding of cultivated land quality systems from the perspective of big data. Taking the big data of cultivated land quality as the driving force, combined with the technical methods of cultivated land quality analysis, the evaluation results of cultivated land quality under different scenarios and different objectives are optimized. In addition, the framework can serve the practice of farmland management and engineering improvement, adapt to the management needs of different objects and different scales, and achieve the combination of theory and practice.

Perspectives on seamless collaboration between primary and secondary care for oral anticancer treatments

ABSTRACT Patients who take oral anticancer drugs (OACD) alternate between the hospital and the community setting. Little is known about how general practitioners (GPs) and community pharmacists (CPs) from primary care (PC) can be involved in providing seamless care. In an exploratory qualitative study, semi-structured interviews with healthcare professionals from primary and secondary care (SC) and (N = 26) were performed to investigate perceptions of seamless collaboration for patients on OACD. Seamless collaboration initiated by SC was restricted to informing GPs about treatment-initiation and delegating limited tasks to them in treatment monitoring. CPs are currently not informed by SC about the treatment. PC expressed willingness for seamless collaboration. However, collaboration is currently impeded due to an expressed lack of trust and desire for control by SC. Moreover, SC expressed unfamiliarity with the organization of PC. Findings suggest that healthcare professionals from SC and PC need to get to know each other and to discuss expectations in the seamless care for patients on OACD. A possible strategy is to elaborate a shared care model based on a partnership between PC and SC, in which the specific expertise of each partner contributes to patient-centered care and the qualitative and safe use of OACD.

Nursing opinions on collaborating with residents in new and legacy OB/GYN programs.

Collaboration among physicians and nurses is vital and has shown to lead to better patient care and improve outcomes. Our study surveyed two groups of Labor and Delivery nurses in two regionally similar community hospitals in midwestern United States: one group from a new Obstetrics and Gynecology (OB/GYN) residency program (n = 49) and another from an established (legacy) OB/GYN residency program (n = 49). The survey asked nurses from the hospital with new and legacy residency program about preparedness for working with residents, perceptions of nurse-resident-patient relationships, collaboration and opinions about how resident physicians impact patient safety. Most nurses from the legacy residency program showed positive perceptions of collaboration with the residency and institutional support. In the new OB/GYN residency program, nurses were generally neutral and showed skepticism about collaboration with OB/GYN resident physicians and institutional support. Nurses from both hospitals felt similarly in their comfort escalating issues to administration and in their satisfaction with interprofessional collaboration within Labor and Delivery units. Providing nurses with opportunities to learn about the role of new medical residents in their patient care setting as well as intentional collaboration between nursing and residency program administration might result in more effective collaboration between physician residents and nursing staff.

A collaborative perception method of human-urban environment based on machine learning and its application to the case area

Human perception refers to people’s psychological feelings about a place. Understanding residents’ perception and their activities is important for promoting people-oriented urban construction. Recently, with the development of machine learning, researchers used this technology to study human perception from the open-source street view images. However, the perception measurement is limited, caused by the inadequate feature extraction. Besides, human perceptions and their activities are separately studied, which hinders the process of revealing the relationship between human and environment. Hence, a human perception model was firstly proposed, where a Transformer network was introduced to extract more discriminative semantic features and visual elements were integrated to enhance the feature representations. Experiments showed that the average deviation of perceptual scores was controlled within 1.6 points, and its performance was improved by around 1%–18% in mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE) compared with the existing best results. Secondly, the collaborative study of environmental perception and residents’ activities was carried out in the case area. Specifically, the perceptual measures of environment were implemented based on the street view video data. Meanwhile, the activities of residents were recognized by SlowFast network and quantified by a new informatics-based diversity indicator (Active Index). This study finally obtained their spatial distribution map, and showed that the perceptual dimensions lively, boring, safe, and depressing are correlated with information quantity of activities. The paper provides a novel method to understand better the urban environment and the distribution of residents’ activities to facilitate urban planning.

YOLOv5s-FP: A Novel Method for In-Field Pear Detection Using a Transformer Encoder and Multi-Scale Collaboration Perception.

Precise pear detection and recognition is an essential step toward modernizing orchard management. However, due to the ubiquitous occlusion in orchards and various locations of image acquisition, the pears in the acquired images may be quite small and occluded, causing high false detection and object loss rate. In this paper, a multi-scale collaborative perception network YOLOv5s-FP (Fusion and Perception) was proposed for pear detection, which coupled local and global features. Specifically, a pear dataset with a high proportion of small and occluded pears was proposed, comprising 3680 images acquired with cameras mounted on a ground tripod and a UAV platform. The cross-stage partial (CSP) module was optimized to extract global features through a transformer encoder, which was then fused with local features by an attentional feature fusion mechanism. Subsequently, a modified path aggregation network oriented to collaboration perception of multi-scale features was proposed by incorporating a transformer encoder, the optimized CSP, and new skip connections. The quantitative results of utilizing the YOLOv5s-FP for pear detection were compared with other typical object detection networks of the YOLO series, recording the highest average precision of 96.12% with less detection time and computational cost. In qualitative experiments, the proposed network achieved superior visual performance with stronger robustness to the changes in occlusion and illumination conditions, particularly providing the ability to detect pears with different sizes in highly dense, overlapping environments and non-normal illumination areas. Therefore, the proposed YOLOv5s-FP network was practicable for detecting in-field pears in a real-time and accurate way, which could be an advantageous component of the technology for monitoring pear growth status and implementing automated harvesting in unmanned orchards.

Role distribution and collaboration between specialists and rural general practitioners in long-term chronic care: a qualitative study in Switzerland

This study explores general practitioners' (GPs') and medical specialists' perceptions of role distribution and collaboration in the care of patients with chronic conditions, exemplified by spinal cord injury. Semi-structured interviews with GPs and medical specialists caring for individuals with spinal cord injury in Switzerland. The physicians we interviewed were recruited as part of an intervention study. We used a hybrid framework of inductive and deductive coding to analyse the qualitative data. Six GPs and six medical specialists agreed to be interviewed. GPs and specialists perceived the role of specialists similarly, namely as an expert and support role for GPs in the case of specialised questions. Specialists' expectations of GP services and what GPs provide differed. Specialists saw the GPs' role as complementary to their own responsibilities, namely as the first contact for patients and gatekeepers to specialised services. GPs saw themselves as care managers and guides with a holistic view of patients, connecting several healthcare professionals. GPs were looking for relations and recognition by getting to know specialists better. Specialists viewed collaboration as somewhat distant and focused on processes and patient pathways. Challenges in collaboration were related to unclear roles and responsibilities in patient care. The expectations for role distribution and responsibilities differ among physicians. Different goals of GPs and specialists for collaboration may jeopardise shared care models. The role distribution should be aligned according to patients' holistic needs to improve collaboration and provide appropriate patient care.

Mitigating knowledge imbalance in AI-advised decision-making through collaborative user involvement

Integrating artificial intelligence (AI) systems into decision-making tasks attempts to assist people by augmenting or complementing their abilities and ultimately improve task performance. However, when considering recommendations from modern “black box” intelligent systems, users are confronted with the decision of accepting or overriding AI’s recommendations. These decisions are even more challenging to make when there exists a significant knowledge imbalance between the users and the AI system—namely, when people lack necessary task knowledge and are therefore unable to accurately complete the task on their own. In this work, we aim to understand people’s behavior in AI-assisted decision-making tasks when faced with the challenge of knowledge imbalance and explore whether involving users in an AI’s prediction generation process makes them more willing to follow the AI’s recommendations and enhances their perception of collaboration. Our empirical study reveals that the involvement of users in generating AI recommendations during a task with notable knowledge imbalance causes them to be more willing to agree with the AI’s suggestions and to perceive the AI agent and their collaboration as a team more positively.

Perceived benefits and challenges of academic involvement in three strategic environmental assessments in Central Europe

The main objective of this paper is to reflect on the contribution academics make to SEA processes in practice, in particular the benefits that arise from that collaboration for both, practitioners and academics, as well as challenges. In this context, the authors focus on the perceptions of those involved in SEA. Three non-routine SEA case studies from Central Europe are explored, including a Polish-German development programme SEA, a 6-country (Austria, Slovenia, Italy, France, Switzerland and Germany) Alpine program SEA and a German marine spatial plan SEA. Information was obtained through interviews and questionnaires conducted with academics as well as private and public SEA actors. Participant observations were used to support the interpretation of results. In the three cases, academics fullfilled different roles, including being providers of expert knowledge and being members of advisory committees. Results suggest an overall positive perception of collaboration between academia and practice, with important contributions being the introduction of novel ideas and innovative assessment methods in SEA, the contribution of knowledge from the academic literature, and the generation of scientific backing for new approaches. Potential challenges for collaboration were found to be associated with negative previous experiences of actors with science-practice interactions along with some contextual factors. Academics benefit from implementing research knowledge in practice. Furthermore, teaching becomes informed by practice and can thus better embrace real life situations.

Mobile Agents-Based Collaborative Perception for Pollution Source Localization in Complex Environments

In this letter, we present a multiagent collaborative perception scheme for pollution source localization in complex environments. To ensure reliable connectivity, a crowd-sensing model is designed to adaptively adjust the sensing range of the swarm of mobile agents. While by introducing the residual energy of agents, a modified mayfly algorithm (MA) is adopted to guide mobile agents to move toward the pollutant source, which can give attention to both energy efficiency and localization accuracy. Besides, artificial potential field is utilized to construct the repulsive force field of each mobile agent to avoid collisions in the process of moving toward the pollution source. Experimental simulations validate that the proposed method has better performance in localization accuracy, collision avoidance, and energy efficiency.

Staff Nurses` Perception of Inter-Professional Collaboration versus Patient Safety Climate

Staff Nurses` Perception of Inter-Professional Collaboration versus Patient Safety Climate

Medical student perceptions and attitudes related to interprofessional collaboration at a student-run free clinic

Many medical universities have student-run free clinics that enable trainees to obtain hands-on clinical experience with underserved populations. This study takes place at one such clinic based at a multidisciplinary health sciences institution in the midwestern U.S. As part of a federally funded program, the research team conducted a survey of the clinic's student volunteers over a 6-month period. Students were queried about their experiences working in the clinic, including perceptions of collaboration with other student volunteers, satisfaction with shared decision-making, confidence with delivering care in various formats (including telehealth), and experiences working on interprofessional teams. Results indicated that overall, students reported a high degree of collaboration within the clinic and expressed confidence working in teams. Moreover, more experienced students reported greater satisfaction with the collaboration among team members, as well as more confidence with working as a member of a team, as compared to first-year students. Students who volunteered at the clinic more frequently also reported greater confidence working as part of a telemedicine team, as compared to students who spent fewer days staffing the clinic. This research can inform institutional efforts to improve the quality of interprofessional education and experiential learning for future physicians and other healthcare professionals.

Need satisfaction and collective efficacy in undergraduate blog-driven classes: A structural equation modelling approach

This paper investigates how psychological needs spurring self-determined motivation relate to collective efficacy for flourishing in online learning communities. Self-determination theory posits individuals experience intrinsic motivation to flourish at educational tasks because of targeted satisfaction of the three psychological needs: autonomy, relatedness, and competence. However, studies conducted to investigate collective, technology-assisted learning processes suggest competence and relatedness may play a pivotal role in online community engagement and knowledge-sharing. Moreover, informal gaming experiences may mirror the collaborative skills needed in online educational/professional communities. These insights suggest confidence in one’s abilities to contribute to a community, the perception of a strong, supportive social culture in the online classroom, and informal online experiences may lead to self-determined motivation enabling agents in distributed, technology-assisted classrooms to collectively flourish. Little work has been done to examine effects of need satisfaction on collective efficacy in using online technologies. To fill this research gap, we used structural equation modelling to investigate perceptions of 636 undergraduate students enrolled in classes within an education department at a midwestern university employing weekly asynchronous blogging. Our results suggest students’ experience with multiplayer gaming, and need satisfaction towards competence and relatedness correlate with higher collective efficacy in technology-assisted classrooms employing discussion forums. Implications for practice or policy: For instructors, student usership and design can spur motivation in online classrooms. For researchers, understanding student perceptions of collaboration using technology can help understand how to design better technology-assisted classrooms. The design of collaborative online educational communities should focus on creating positive social cultures and fostering competence for students.

Stakeholder perceptions of university-industry collaboration on tourism and business students’ employability in two continents

ABSTRACT This study explored whether the teaching environment of six universities across Finland, United Kingdom, and South Africa are currently producing the competencies required by the industry. It also assessed the effects of university-industry collaboration activities on students’ work readiness and employability. The research adopted mixed method approach to data collection. Structured questionnaire survey was used to collect quantitative data from students, and semi-structured interviews were used to collect qualitative data from lecturers and industry representatives. Findings from the University of Zululand (UNIZULU) were compared with findings from the other universities in South Africa. UNIZULU students had the highest ratings compared to the students from the other universities across the dimensions of career preparation, desirable graduate competencies and work readiness. In contrast, UNIZULU students had the lowest ratings in terms of industry engagement and student engagement, for which this study provided management implications.

Exploring Special Education and Center for Independent Living Professional Beliefs on Collaboration and the Value-Based Principles That Drive Secondary Transition Service Delivery

The importance of interagency collaboration to support the postschool outcomes of youth with disabilities is underscored in many ways. Perhaps one of the most important among them is the place of interagency collaboration as an evidence-based predictor of postschool success. Although Centers for Independent Living (CILs) receive U.S. federal funding to serve people with disabilities across the lifespan, little research exists to map the nature of their collaboration with local education agencies (LEAs) to this end. The current survey-based study examined perceptions of professionals in both settings (i.e., LEAs and CILs) on their current level of collaboration with one another and the value-based principles they believe influence their work as they support transition-age youth with disabilities ( n = 581). Findings indicate a widespread belief in the importance of CILs in youth transition service delivery, a stark contrast between CIL and school-based transition professional perceptions of current collaboration, and a dynamic landscape of shared and divergent ratings of importance across value-based principles of transition practice. Practical implications are outlined to inform CIL and LEA collaboration to support youth with disabilities alongside directions for future research.

V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Driving

Vehicle-to-everything (V2X) communication techniques enable the collaboration between vehicles and many other entities in the neighboring environment, which could fundamentally improve the perception system for autonomous driving. However, the lack of a public dataset significantly restricts the research progress of collaborative perception. To fill this gap, we present V2X-Sim, a comprehensive simulated multi-agent perception dataset for V2X-aided autonomous driving. V2X-Sim provides: (1) multi-agent sensor recordings from the road-side unit (RSU) and multiple vehicles that enable collaborative perception, (2) multi-modality sensor streams that facilitate multi-modality perception, and (3) diverse ground truths that support various perception tasks. Meanwhile, we build an open-source testbed and provide a benchmark for the state-of-the-art collaborative perception algorithms on three tasks, including detection, tracking and segmentation. V2X-Sim seeks to stimulate collaborative perception research for autonomous driving before realistic datasets become widely available.

Improving Communication and Response to Clinical Deterioration to Increase Patient Safety in the Intensive Care Unit.

In the critical care setting, early recognition of clinical decompensation is imperative to trigger prompt intervention and optimize patient outcomes. In a 20-bed surgical intensive care unit of an urban academic medical center, cases of clinical deterioration that highlighted opportunities to improve the communication process prompted a reassessment of health care provider roles and responsibilities. A quality improvement initiative was implemented to enhance communication among intensive care unit clinical staff members, improve the timeliness of reporting clinical deterioration, and ensure implementation of timely, appropriate interventions to eliminate adverse outcomes. Nurses were surveyed to determine their perceptions of communication and collaboration among providers. Education was provided that focused on familiarizing nurses with clinical conditions necessitating direct notification of the attending surgical intensivist and included review of a case in which escalation of care did not occur. Multidisciplinary rounds were expanded to engage night-shift nurses in clinical discussions and decision-making. A template was created to document episodes of escalation in the electronic health record. Since implementation of the quality improvement interventions, no incidents of patient harm or death related to failure to escalate have occurred to date. A total of 16 episodes of escalation for clinical deterioration were documented in the electronic health record. Most nurses reported an increased level of confidence in understanding when to escalate concerns about clinical deterioration. Implementing a multimodal program to empower nurses to escalate clinical concerns directly to the attending physician eliminated adverse events related to failure to escalate.

Secondary Special Educators’ Perceptions of Transition Collaboration With Vocational Rehabilitation

Although interagency collaboration is one of the most recognized and recommended practices for improving the transition outcomes of students with disabilities (SWD), it remains challenging to understand in both research and practice. This study utilizes the theory of planned behavior to understand better secondary special educators’ beliefs, perceptions, and behaviors related to their collaboration with vocational rehabilitation (VR). Eighty-seven secondary special educators from across the U.S. participated in a survey using both quantitative and qualitative questions. Quantitative results indicate that more familiarity with VR lends itself to more behaviors that promote VR to SWD. Qualitative data describe how participants have created effective collaborative systems, as well as the barriers to working with VR in the transition process. Recommendations are provided at both the practitioner level and the systemic policy level to potentially address barriers to collaborations between these two groups of professionals in supporting post-school goals for SWD.

Multi-Agent Multi-View Collaborative Perception Based on Semi-Supervised Online Evolutive Learning.

In the edge intelligence environment, multiple sensing devices perceive and recognize the current scene in real time to provide specific user services. However, the generalizability of the fixed recognition model will gradually weaken due to the time-varying perception scene. To ensure the stability of the perception and recognition service, each edge model/agent needs to continuously learn from the new perception data unassisted to adapt to the perception environment changes and jointly build the online evolutive learning (OEL) system. The generalization degradation problem can be addressed by deploying the semi-supervised learning (SSL) method on multi-view agents and continuously tuning each discriminative model by collaborative perception. This paper proposes a multi-view agent’s collaborative perception (MACP) semi-supervised online evolutive learning method. First, each view model will be initialized based on self-supervised learning methods, and each initialized model can learn differentiated feature-extraction patterns with certain discriminative independence. Then, through the discriminative information fusion of multi-view model predictions on the unlabeled perceptual data, reliable pseudo-labels are obtained for the consistency regularization process of SSL. Moreover, we introduce additional critical parameter constraints to continuously improve the discriminative independence of each view model during training. We compare our method with multiple representative multi-model and single-model SSL methods on various benchmarks. Experimental results show the superiority of the MACP in terms of convergence efficiency and performance. Meanwhile, we construct an ideal multi-view experiment to demonstrate the application potential of MACP in practical perception scenarios.

Vision beyond the Field-of-View: A Collaborative Perception System to Improve Safety of Intelligent Cyber-Physical Systems.

Cyber-physical systems (CPSs) that interact with each other to achieve common goals are known as collaborative CPSs. Collaborative CPSs can achieve complex goals that individual CPSs cannot achieve on their own. One of the examples of collaborative CPSs is the vehicular cyber-physical systems (VCPSs), which integrate computing and physical resources to interact with each other to improve traffic safety, situational awareness, and efficiency. The perception system of individual VCPS has limitations on its coverage and detection accuracy. For example, the autonomous vehicle’s sensor cannot detect occluded objects and obstacles beyond its field of view. The VCPS can combine its own data with other collaborative VCPSs to enhance perception, situational awareness, accuracy, and traffic safety. This paper proposes a collaborative perception system to detect occluded objects through the camera sensor’s image fusion and stitching technique. The proposed collaborative perception system combines the perception of surrounding autonomous driving systems (ADSs) that extends the detection range beyond the field of view. We also applied logistic chaos map-based encryption in our collaborative perception system in order to avoid the phantom information shared by malicious vehicles and improve safety in collaboration. It can provide the real-time perception of occluded objects, enabling safer control of ADSs. The proposed collaborative perception can detect occluded objects and obstacles beyond the field of view that individual VCPS perception systems cannot detect, improving the safety of ADSs. We investigated the effectiveness of collaborative perception and its contribution toward extended situational awareness on the road in the simulation environment. Our simulation results showed that the average detection rate of proposed perception systems was 45.4% more than the perception system of an individual ADS. The safety analysis showed that the response time was increased up to 1 s, and the average safety distance was increased to 1.2 m when the ADSs were using collaborative perception compared to those scenarios in which the ADSs were not using collaborative perception.