Supervision Model Research Articles

The digital operational resilience act: challenges and some reflections on the adequacy of Europe’s architecture for financial supervision

The paper critically analyses the Digital Operational Resilience Act (DORA) within the European Union (EU) with respect to challenges such as supervision and the oversight framework coordination. It delves into the adequacy of the European System of Financial Supervision (ESFS) in ensuring compliance with this regulation, highlighting issues of fragmented supervision at national level and inconsistent approaches. The main argument suggests that while the DORA Regulation is a positive step for harmonising digital operational resilience regulation, it brings about challenges in supervisory convergence and cooperation due to the existing fragmented supervisory architecture. The authors propose potential solutions like a more centralised supervision model to address these challenges. The paper follows a structured format with an overview of the DORA Regulation, discussion on identified challenges, and a concluding section.

상담 수퍼비전 통합적 모델의 국내·외 연구 동향과 과제 및 기독(목회) 상담에의 적용점 고찰

To investigate domestic and international trends of integrated supervision models, this study analyzed domestic and international journals from 2000 to June 2022. The results of the study showed that the domestic trend is mainly applying the concept of 'developmental model' rather than an 'integrated model' of supervision, and it tends to be used as a guiding framework to illuminate the developmental process of supervisory processes and activities, supervisors and supervisees rather than a model. Internationally, studies have proposed creative and diverse integrative supervision models that incorporate various counseling techniques into supervision theory.And as psychological counseling itself has become more fragmented and specialized, supervision models have also become more fragmented and specialized. Through a comparative analysis of the trends in domestic and international research on integrated supervision models, this paper examines the direction of research on integrated supervision models in Korea and discusses an integrated supervision model for Christian (pastoral) counseling.

Efektifitas Sosialisasi Supervisi 4S dalam Rangka Peningkatan Budaya Keselamatan Pasien

Healthcare facilities must adhere to patient safety principles to reduce the risk of harm. Prof. Dr. M.A. Hanafiah SM Batusangkar Hospital is among the healthcare providers in West Sumatra, necessitating endeavors to enhance and sustain service quality, especially regarding patient safety. The effectiveness of the patient safety culture depends on the 4 S supervision elements, including Structure, Skill, Support, and Sustainability. The 4S supervision model guides and aids nurses in advancing their skills related to patient safety. Survey findings at the hospital revealed that the promotion of 4S supervision was suboptimal, manifesting as nurses' limited grasp of the concept. On July 28-29, 2023, a structured socialization, education, and mentorship program was conducted for nursing executives and managers. The objective was to empower nurses to incorporate multilayered supervision into patient care and oversee the implementation of patient safety in inpatient, outpatient, and emergency room settings, aiming to enhance the patient safety culture.

A Model of Election Supervision Based on Village Judicial Institutions; A Review of Legal Anthropology in Madura

The General Election Law has placed villages at the forefront of the election monitoring system by establishing Village Panwaslu. However, it still needs to be fully able to unravel the complexity of the election monitoring system. This study aims to strengthen the election supervision system so that all electoral issues can be resolved at the village level. This research uses normative legal research methods that focus on the reconstruction and institutionalization of the election supervision system at the village level through the synergy of village judicial institutions. The result of the research is that the design of election supervision at the village level, which only places one member, has yet to resolve the many burdens of election supervision fully. Although Article 448 paragraph (3) of the Election Law authorizes the community to monitor actively, it has proven not optimal because there is no clear legal protection for the participatory monitoring system. The weakness of the monitoring system can be strengthened through 1) The establishment of Village Panwaslu members that involve village judicial institutions consisting of Babinkantibmas, Babinsa, and community leaders; 2) Expanding the authority of the Village Panwaslu to resolve disputes over the election process at the village level.

Development of Learning Supervision Model Website Based on Improving Teacher Performance at Elementary School

This research aims to produce products and test the feasibility of products, such as producing a website-based supervision model development system in improving teacher performance in elementary schools, to facilitate the management of conventional/manual supervision of website-based management information systems and determine the feasibility of website-based learning supervision system models in improving teacher performance in elementary schools. The method used in this research is Research and Development (R&D). The research steps include 1) data information, 2) model design, 3) model testing, 4) model revision, 5) development, 6) trial/testing, 7) model revision, 8) finalization and socialization. This research was conducted in a participatory manner. The research output targets at this stage are preparing a website-based learning supervision model design. This website-based principal learning supervision model design has been tested and revised to obtain an effective learning supervision model and develop a website-based learning supervision model. The results of this research are: (1) Learning supervision activities are carried out through the website http://supervisipbelajaran.educmps.com, (2) Principals feel greatly helped by the Website-Based Supervision Model because it is practical, effective, and efficient, (3) Making it easier for teachers to improve performance at school.

Automatic de-identification of French electronic health records: a cost-effective approach exploiting distant supervision and deep learning models

BackgroundElectronic health records (EHRs) contain valuable information for clinical research; however, the sensitive nature of healthcare data presents security and confidentiality challenges. De-identification is therefore essential to protect personal data in EHRs and comply with government regulations. Named entity recognition (NER) methods have been proposed to remove personal identifiers, with deep learning-based models achieving better performance. However, manual annotation of training data is time-consuming and expensive. The aim of this study was to develop an automatic de-identification pipeline for all kinds of clinical documents based on a distant supervised method to significantly reduce the cost of manual annotations and to facilitate the transfer of the de-identification pipeline to other clinical centers.MethodsWe proposed an automated annotation process for French clinical de-identification, exploiting data from the eHOP clinical data warehouse (CDW) of the CHU de Rennes and national knowledge bases, as well as other features. In addition, this paper proposes an assisted data annotation solution using the Prodigy annotation tool. This approach aims to reduce the cost required to create a reference corpus for the evaluation of state-of-the-art NER models. Finally, we evaluated and compared the effectiveness of different NER methods.ResultsA French de-identification dataset was developed in this work, based on EHRs provided by the eHOP CDW at Rennes University Hospital, France. The dataset was rich in terms of personal information, and the distribution of entities was quite similar in the training and test datasets. We evaluated a Bi-LSTM + CRF sequence labeling architecture, combined with Flair + FastText word embeddings, on a test set of manually annotated clinical reports. The model outperformed the other tested models with a significant F1 score of 96,96%, demonstrating the effectiveness of our automatic approach for deidentifying sensitive information.ConclusionsThis study provides an automatic de-identification pipeline for clinical notes, which can facilitate the reuse of EHRs for secondary purposes such as clinical research. Our study highlights the importance of using advanced NLP techniques for effective de-identification, as well as the need for innovative solutions such as distant supervision to overcome the challenge of limited annotated data in the medical domain.

Defining the passage of wisdom: A taxonomy of supervision for RANZCP trainees and Fellows.

Trainees and Fellows of the Royal Australian and New Zealand College of Psychiatrists (RANZCP) work in complex interpersonal and organisational environments. Engagement in supervision can be a helpful way for trainees and Fellows to achieve interpersonal, professional, and organisational success. Supervision comes in many forms depending on the stage and state of one's career. An awareness of different supervision models is relevant to trainees' understanding of what is expected of them and their supervisors in their work and educational contexts. This paper explores the taxonomy of supervision models available to RANZCP trainees and Fellows in Australia and New Zealand. Supervision is a heterogeneous concept with multiple aims, outcomes, and processes that change with ones' stage of career.

Fostering Pre-Professionals and Learning Experiences in End-of-Life Care Contexts: Music Therapy Internship Supervision.

Certified music therapists use music within therapeutic relationships to address human needs, health, and well-being with a variety of populations. Palliative care and music therapy are holistic and diverse fields, adapting to unique issues within end-of-life contexts. Palliative care music therapy has been formally practiced since the late 1970s and affords a variety of benefits, including pain and anxiety reduction, enhancement of quality of life, emotional expression, and relationship completion. The training of music therapists varies around the globe, but clinical supervisors play a key role in skill acquisition. Clinical supervisors support pre-professionals as they realize the application of their training, foundational competencies, and authentic therapeutic approaches in end-of-life care, while navigating the challenges and rewards of this work. This article is a narrative review which offers background information on palliative care music therapy, and reports the authors' viewpoints and reflections on supervision strategies and models employed with music therapy interns in palliative care settings based on their experiences. Approaches are shared on supporting pre-professionals as they begin working in palliative care contexts, as well as implications for supervision practices.

Exploring the professional nurse advocate role and restorative clinical supervision.

The professional nurse advocate (PNA) role is the key enabler of delivery of the NHS England Advocating and Educating for Quality Improvement (A-EQUIP) model of professional nursing leadership and clinical supervision. The aim of the PNA role is to provide clinical, educational and well-being support to nurses through restorative clinical supervision. This article describes the PNA role and the A-EQUIP model and discusses some of the challenges experienced by nurses in relation to delivering care to older people and current workforce pressures. The author suggests that restorative clinical supervision may support nurses to manage these challenges and enhance their practice in the care of older people, and describes part of a workforce improvement project to illustrate this in practice. Finally, the author considers some of the barriers to implementation of restorative clinical supervision.

Why I am trapped in the spiral of abuse? A nexus of low core self-evaluations and job dependency

PurposeThe present research aims to empirically test the “Barriers to abusive supervision model” to find how employee-related (core self-evaluations) and situational factors (perceived job dependency) make an employee trapped in the spiral of supervisory abuse. In addition, the work–family spillover lens is used to explain how employees' retaliation is targeted at their families in response to abuse from their bosses.Design/methodology/approachThe current study has employed a three-wave longitudinal moderated mediation design and analysed data from 265 employees working in the hospitality industry of Pakistan.FindingsThe results of this study have shown that low core-self evaluations put employees in a spiral of supervisory abuse and they instil aggression towards their families. This association is further strengthened when employees are dependent on their job.Originality/valueThis study is one of the first to use the “Barriers to Abusive supervision” model to answer who and in which conditions tend to trap in the spiral of abuse and integrate the work-to-family interface model for elaborating the outcomes to the family domain.

Advancing sustainable implementation of an evidence-based mental health intervention in Sierra Leone’s schools: protocol for a hybrid type 3 implementation-effectiveness trial

BackgroundMental health disorders among youth contribute substantially to the global burden of disease, which is exacerbated in low- and middle-income countries (LMICs) due to large mental health treatment gaps. In Sierra Leone, a West African country with a long history of complex adversity, the mental health treatment gap is estimated at 98%. Implementing innovative mental health interventions that can be sustained at scale is a priority. The Youth Readiness Intervention (YRI) is an evidence-based mental health intervention for youth that can be delivered feasibly by lay health workers/nonspecialists. Using mobile-based technologies to assist implementation could improve the reach and sustainability of the YRI in Sierra Leone. This study aims to train teachers to deliver the YRI in Sierra Leone’s secondary schools and test the feasibility, acceptability, cost, and fidelity to the YRI of a mobile-based supervision model compared with standard, in-person supervision.MethodsWe will conduct a hybrid type 3 implementation-effectiveness cluster randomized trial to assess the feasibility, acceptability, costs and fidelity to the YRI implemented by teachers receiving mobile-based supervision vs. standard supervision. Enrolled schools (N = 50) will be randomized to YRI + mobile supervision (N = 20), YRI + standard supervision (N = 20) or waitlist control (N = 10). We will recruit and enroll four teachers per intervention-condition school (N = 160) and 1200 youth. We will collect data on implementation outcomes among teachers, principals and youth via a mixed methods approach at baseline and post-intervention. We will also collect quantitative data on youth mental health and functioning as secondary outcomes at baseline and post-intervention, as well as cost-effectiveness data at 12-month follow-up.DiscussionStudy findings have the potential to expand the reach of mental health services among youth in low-resource settings via a teacher workforce. The use of mobile tools, if successful, could support further scale out and sustainment of the YRI to other regions of Sierra Leone and West Africa more broadly, which could help address the mental health treatment gap.Trial registrationClinical Trial Network: NCT05737667.

Supervision Models and Supervisory Feedback in English Language Teacher Education: A Meta-Synthesis Study Adopting a Discourse Analytic Perspective

This meta-synthesis reviewed and synthesized the findings of 53 studies on supervisory post-conferences and feedback with a total of 807 participants published between 2004-2023. The aim of this meta-synthesis was to illustrate the trends in the reviewed studies and synthesize the results of the studies on supervisory discourse and models of supervision in the field of English language teaching. The criteria for eligibility for selection were being empirical, peer-reviewed, and published in English. Articles were scanned through the Web of Science, ERIC, SCOPUS, and Google Scholar till July, 2023. The studies lacking a report of detailed and clear-cut data collection and analysis phases were removed in the appraisal phase to avoid a risk of bias. The results indicated that supervisors implemented directive supervisory styles as well as collaborative approaches exploiting power dynamics such as expert power. The findings also showed that the use of conversational techniques such as mediation, mitigators, and elicitation in supervisory talk play a central role in supervising English language teachers. The results suggested that supervised teachers demonstrated confronting, autonomous, and fluid identities when faced with a directive style of supervision. The limitations of evidence for this study related the search strategy, participants and variations in educational settings.

Analysis of the Current Status and Enhancement Strategies for University Party Committee Supervision and Administration Work in the New Era

This research delves into the current circumstances and challenges faced by supervision and administration work in Chinese universities. It begins by identifying key issues such as the insufficient independence in the organization of supervision bodies, unclear division of personnel roles, and inadequate use of digital tools. Further analysis uncovers the fundamental causes behind the ineffectiveness of supervision work, notably the mismatch between supervision models and university characteristics, the so-called "Supervision Paradox" (the negative correlation between supervision frequency and governance effectiveness), and a shortfall in digital tools application. To tackle these challenges, the paper proposes effective strategies, including balancing the academic and administrative elements of the supervision system, utilizing various approaches to alleviate workload and boost efficiency, and advancing the digital transformation of supervision activities, all aimed at enhancing the modernization of university governance systems and capabilities.

Academic Supervision of Madrasah Heads in Improving the Teacher’s Performance of Madrasah Tsanawiyah Negeri 2 Tangerang City

This research aims to understand and analyse the academic supervision of Madrasah principals in improving teacher performance at Madrasah Tsanawaiyah Negeri 2 Tangeran City. The research method used was descriptive method with a qualitative approach. Data collection techniques include observation, interviews and documentation. The data analysis technique includes four components, namely, data collection, data reduction, data presentation and drawing conclusions. The research results show that the academic supervision of the madrasa head in improving teacher performance at Madrasah Tsanawaiyah Negeri 2 Tangerang City includes checking the syllabus, annual program, semester program and lesson plans made by the teacher periodically. The supervision model used is a clinical supervision model with a collaborative approach and the techniques used include individual and group techniques. Scheduled supervision is carried out at the beginning and end of each semester, while informally it is carried out every day in guidance or coaching. The obstacles faced in the implementation of academic supervision of madrasa heads at Madrasah Tsanawaiyah Negeri 2 Tangerang City, the main obstacle is time. Factors that influence supervision include internal factors such as intellectual ability and personality, teaching motivation, concern of the madrasah principal, discipline and the presence of teachers.

Contribution of peer group supervision to nursing practice: An interpretive phenomenological study

AimTo provide insight into peer group supervision practices through understanding the lived experience of community health nurses. BackgroundThe recent Covid-19 health crisis highlights the importance of supportive mechanisms to sustain and retain nurses in the workforce. While the support of quality clinical supervision for registered nurses is recognised, the benefits and challenges of peer group supervision are less clearly articulated. DesignNurses’ experiences of peer group supervision in an Australian tertiary health service were explored using a Gadamerian philosophical hermeneutic approach. MethodSemi-structured in-depth interviews were conducted in 2021 and provided nurses with the opportunity to share their experiences of using the New Zealand Coaching and Mentoring Model of peer group supervision. The study included a total of 31 nurse participants across multiple community health contexts. Interview data were analysed using a hermeneutic approach from which themes arose. FindingsThe findings demonstrated that strong peer group supervision foundations that include personal and professional preparation and active participation are essential. Dual pillars of “the unique individual” and “the unique group” with responsibilities identified in each pillar that enable interactions and worthiness in peer group supervision practice. The foundations and pillars support peer group supervision in nursing practice to provide a mechanism for reflection, support and professional guidance. ConclusionsPeer group supervision is a worthy, contributory process in community health nursing when implementation processes are supported and teams are educated and prepared. Perceptions of peer group supervision are unique and varied across individuals. The individual experience has an impact on the group experience and vice versa. Knowledge of the process and group by participants is required to enable professional reflection through nursing peer group supervision.

Model Supervisi Transformasional untuk Mendorong Inovasi Pendidikan di Sekolah Dasar Islam Terpadu (SDIT) Al Ikhlas Kabupaten Cirebon

This research describes an effective transformational supervision model for making changes to encourage educational innovation in the Integrated Islamic Elementary School (SDIT) Al Ikhlas Cirebon Regency, aiming to achieve real success. Method: The research employs a qualitative approach using a case study research method. The subjects in this research include supervisors, teachers, and principals involved in the transformational supervision programs in schools. Data collection is conducted through interviews, documentation, and observation. Data analysis adopts an inductive and thematic approach to identify emerging patterns and findings. The research results confirm that the Transformational Supervision Model is a powerful approach for driving educational innovation in primary schools. By engaging educational leaders who play a critical role in supporting and inspiring teachers, this model creates a supportive and motivating environment for innovative learning practices. As a result, it improves the quality of education, develops relevant student skills, and prepares them for the future to meet the demands of the global society.
 Keywords : Innovation, Integrated Islamic Elementary School Education (SDIT), Transformational Supervision

MangroveSeg: Deep-Supervision-Guided Feature Aggregation Network for Mangrove Detection and Segmentation in Satellite Images

Mangrove forests are significant participants in coastal ecological environment systems. For the development of protection strategies, it is crucial to automatically and accurately detect the distribution and area of mangroves using satellite images. Although many deep-learning-based mangrove detection and segmentation algorithms have made notable progress, the complex regional structures and the great similarity between mangroves and the surrounding environment, as well as the diversity of mangroves, render the task still challenging. To cover these issues, we propose a novel deep-supervision-guided feature aggregation network for mangrove detection and segmentation called MangroveSeg, which is based on a U-shaped structure with ResNet, combining an attention mechanism and a multi-scale feature extraction framework. We also consider the detection and segmentation of mangroves as camouflage detection problems for the improvement and enhancement of accuracy. To determine more information from extracted feature maps in a hidden layer, a deep supervision model is introduced in up-sampling to enhance feature representation. The spatial attention mechanism with attention gates is utilized to highlight significant regions and suppress task-independent feature responses. The feature fusion module can obtain multi-scale information by binding each layer to the underlying information and update feature mappings. We validated our framework for mangrove detection and segmentation using a satellite image dataset, which includes 4000 images comprising 256 × 256 pixels; we used 3002 for training and 998 for testing. The satellite images dataset was obtained from the Dongzhaigang National Nature Reserve located in Haikou City, Hainan Province, China. The proposed method achieved a 89.58% overall accuracy, 89.02% precision, and 80.7% mIoU. We also used the trained MangroveSeg model to detect mangroves on satellite images from other regions. We evaluated the statistical square measure of some mangrove areas and found that the evaluation accuracy can reach 96% using MangroveSeg. The proposed MangroveSeg model can automatically and accurately detect the distribution and area of mangroves from satellite images, which provides a method for monitoring the ecological environment.

Development Of A Supervision Model To Enhance Competency In Educational Quality Assurance Among Academic Institution Administrators

Quality assurance plays a pivotal role in ensuring the effectiveness and reliability of academic institutions, which requires understanding and attention from their administrators. This research aims to contribute to the enhancement of educational quality assurance competency among academic institution administrators through the development and evaluation of a supervision model. The study comprises three phases: phase 1 involves an investigation into the existing quality assurance competency framework and its relevance to the current context. Phase 2 focuses on the formulation and implementation of the supervision model derived from the established framework. Finally, phase 3 assesses the effectiveness of the implemented model at the curtain focus group. The supervision model integrates four strategic dimensions, termed the '4As': Awareness, Action, Assessment, and Accreditation, alongside seven approaches aimed at fostering knowledge, skills, and attributes on educational quality assurance. These approaches cover supervision documentation, online supervision seminars, remote supervision workshops, online learning platforms, focus group discussions, networking, and hybrid supervision sessions. The implementation of the model was conducted among 32 executives from secondary academic institutes in Nakhon Ratchasima, Chaiyaphum, Buriram, and Surin provinces, Thailand. The evaluation results reveal a significant improvement in the educational quality assurance competency among administrators who underwent the supervision model compared to both the control group and their initial competency levels. Furthermore, participants expressed high satisfaction levels with the model's efficacy.

Mentoring Philosophy as a Guide to Navigate Challenges From the Lens of Certified Mental Performance Consultant Mentors

The purpose of this paper is to show how philosophies and guiding theoretical models have helped develop the mentoring practices of a master’s degree program with students seeking to become Certified Mental Performance Consultants. We present a series of challenges that we have encountered as mentors in this program. These challenges center around the consulting student, coach interactions, situations that have warranted a need for referrals, and mentor burnout. In each challenge, we discuss how our philosophy and models of supervision helped guide our decisions and the lessons learned from these various situations. Ultimately, these challenges and experiences helped us improve the program through changes in our mentorship structure and general logistics. We hope that our lessons, ideas for program improvement, and the rationale of how our mentoring philosophy supported our decision making at the time may be useful to mentors who oversee graduate-level programs.

SCorP: Statistics-Informed Dense Correspondence Prediction Directly from Unsegmented Medical Images.

Statistical shape modeling (SSM) is a powerful computational framework for quantifying and analyzing the geometric variability of anatomical structures, facilitating advancements in medical research, diagnostics, and treatment planning. Traditional methods for shape modeling from imaging data demand significant manual and computational resources. Additionally, these methods necessitate repeating the entire modeling pipeline to derive shape descriptors (e.g., surface-based point correspondences) for new data. While deep learning approaches have shown promise in streamlining the construction of SSMs on new data, they still rely on traditional techniques to supervise the training of the deep networks. Moreover, the predominant linearity assumption of traditional approaches restricts their efficacy, a limitation also inherited by deep learning models trained using optimized/established correspondences. Consequently, representing complex anatomies becomes challenging. To address these limitations, we introduce SCorP, a novel framework capable of predicting surface-based correspondences directly from unsegmented images. By leveraging the shape prior learned directly from surface meshes in an unsupervised manner, the proposed model eliminates the need for an optimized shape model for training supervision. The strong shape prior acts as a teacher and regularizes the feature learning of the student network to guide it in learning image-based features that are predictive of surface correspondences. The proposed model streamlines the training and inference phases by removing the supervision for the correspondence prediction task while alleviating the linearity assumption. Experiments on the LGE MRI left atrium dataset and Abdomen CT-1K liver datasets demonstrate that the proposed technique enhances the accuracy and robustness of image-driven SSM, providing a compelling alternative to current fully supervised methods.