Industry 4.0 technologies need to plan reactive and Preventive Maintenance (PM) strategies for their production lines. This applied research study aims to employ the Predictive Maintenance (PdM) technology with advanced automation technologies to counter all expected maintenance problems. Moreover, the deep learning based AI is employed to interpret the alarming patterns into real faults by which the system minimizes the human based fault recognition errors. The Sensors Information Modeling (SIM) and the Internet of Things (IoT) have the potential to improve the efficiency of industrial production machines maintenance management. This research work provides a better maintenance strategy by utilizing a data-driven predictive maintenance planning framework based on our proposed SIM and IoT technologies. To verify the feasibility of our approach, the proposed framework is applied practically on a corrugated cardboard production factory in real industrial environment. The Fuzzy Logic System (FLS) is utilized to achieve the AI based PM while the Deep Learning (DL) is applied for the alarming and fault diagnosis in case the fault already occured. Through high precision smart sensors, we collect a huge amount of data that indicate the state of machines and their healthy or faulty operation2. By analyzing these data, we predict quickly and accurately the possible failures of the machine. PdM strategies reduce machine maintenance costs and extend the service lifespan of machine parts. The probability of line production machine faults are calculated on the basis of historic data from previously tested the expert systems3. Machine parameters (such as machine type), operator experience, machine age, operation time, component types and operation location), are taken into consideration for fault diagnosis and prediction. This research work discusses the role of the AI based IoT and its development, by integrating heterogeneous distributed sensor data of all machines to analyze their operation conditions4. To achieve this target, we developed an algorithm that helps analyze the data and to make a precise decision5. The presented research work aims to prevent halting the production line without reasonable causes.Industry 4.0 technology is a revolution of the way factories achieve mass production, improve, and distribute their products. Producers are merging new techniques, including IoT, cloud computing and computational analytics with AI and machine learning into their production lines during the manufacturing process. Through the continuous development of AI based automation technologies, the IoT and their applications have the opportunity to benefit from the industrial development, especially in applying PdM systems6 based on analyzing and processing the collected data. When a faulty operation takes place by an operator, the system analyzes the performance, and the operator can be quickly notified of the faulty act. By applying the proposed system, it is expected to avoid breakdowns, reduce loss of time, minimize the effort, limit the operation cost7, and predict failure before its occurrence. The most important results are to increase the operating lifetime of machines, reduce the cost of spare parts, reduce production downtime, improve product quality, and save energy.Relying on predictive maintenance, it is possible to improve the performance of production machines, predict their conditions and recognize faults, predict their maintenance dates, and also predict their lifetime8. Due to this faulty operation the percentage of wastage in production will also increase, and the failure could be due to the natural malfunctions of the machine that depend on the lifetime of the spare parts. This research work will lead to precisely recognition of PM and predicts faults clearly before the malfunction occurs9.The overall production line depends on the machinery and a slight failure may cause the entire production line to halt. Whether it is a failure in a sub or auxiliary parts, the cause of the failure may be on behalf of the operators. In the long run, if the basic parts of the machines in the wrong operation continues, failure will follow after the other, which will increase the cost and consume a longer time. This faulty operation will negatively affects the production process12. This research aims to determine the sensors on the machine which recognize failures before they occur.The needs arose in this study are to determine severity and risk evaluation of sudden failure of corrugated cardboard production machine parts which may lead to prolong the wasted time. Generally, PM has to be carried out every week for inspection, revision and lubrication of mechanical parts, every month to remove the mechanical and electrical parts that have been monitored for abnormal performance which require close inspection before unexpected failures occurThe rest of the paper is organized as follows; “13 extended the anomaly detection problems. To extract the patterns, they developed a method to considering contextual parameters associated with data. Then compliance of the new data and, according to the knowledge extracted, can detect anomaly. Zhang et al.11, developed a method to reveal the temporal-dependency embedded in sensor data streams as the basis for engine degradation prediction. Huang et al.Industry 4.0 technologies development and progress result in rapid increase in the size of machines, quantity of production modules, mass production, mega stores, big data, and high precision. These changes require for sure the IoT, AI and High Performance Computing (HPC) to apply the predictive maintenance. This motivated many researchers recently to direct their research studies to the field of data analysis for predictive maintenance which became an essential tool in industry 4.0 Technology. Rabatelab et al.14 showed that machine maintenance is ramified issue that relates to many other factors for the requirements of modern industrial development. When symmetric components do not perform the same function, the system is out of balance. A preventive maintenance action is performed once the state difference. The research did not take into account the difference in method of operation despite the similarity of the elements. Wanga and Miaob15 presents Predictive maintenance for aircraft systems relying on proportional hazard models. The authors link open overlay panel proposed by Wim et al.16 showing that aircraft operating in hot, sandy airports or regions have very different circumstances of operation than aircraft operation in normal cold, wet airports, will lead to several failure modes and lifetimes for spare parts. Aircraft fault prediction at maintenance service on the basis of regression data and aircraft parameters are studied by Pogačnik et al.17 for predictive Maintenance and Reliability. Brauers and Balezentis18 developed a Multi-Objective Decision Making technique for Linguistic Reasoning with an Application to staff Selection. The FMEA Traditional Modifications (FMEA Improvement) in IT Risk management is proposed by Nina Fadilah et al.19. Liu et al.20 studied the Failure mode and its effect analysis.Reference21, this paper investigates the major historical milestones in the evolution of manufacturing systems simulation technologies and examines recent industrial and research approaches in key fields of manufacturing and PM. In 2021, Filz et al.22, proposed a data-driven Failure Mode and Effect Analysis (FMEA) methodology by using deep learning models on historical and operational data from the use stage of industrial investment goods. The developed methodology is supposed to support the maintenance planning for industrial investment goods by enhancing transparency and providing decision support. In 2021, Mourtzis et al.23, presented a Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) can be considered as the cornerstones of the lifecycle of a manufacturing asset. Since the above-mentioned processes often involve multiple engineers, from different departments even from different companies, it is crucial to ensure the flawless communication between the different individuals as well as to make the design process more intuitive. In 2018, Mourtzis et al.24, proposed a framework for the modeling of milling and lathe CNC machine-tools, through a general machine model. The framework is based on the Open Platform Communications—Unified Architecture (OPC-UA) communications standard to provide a macroscopic and microscopic view of machine shops, towards the Machine Shop 4.0 concept.In 2020, Mourtzis25, in this paper a methodology to build monitoring solutions for machining devices is defined, based on the main equipment and operations used by molds industry companies. For a standardized approach, OPC-UA is used for high-level communication between the various systems. In 2019, Liu et al.26, this paper proposes a CPMT Platform based on OPC-UA and MT Connect that enables standardized, interoperable and efficient data communication among machine tools and various types of software applications. In 2021, Schmid et al.27, proposed Acquisition of machine tool data via the open source implementation open62541 for OPC-UA. current Industry 4.0 Communication methods are defined as OPC-UA, MQTT, or REST. These communication standards can integrate machine tool and process data in IoT-Clouds or external devices. In 2022, Eswaran and Bahubalendruni28, this paper demonstrates the research progress and developments in the AR/VR technologies for product design and evaluation, Repair & Maintenance, Assembly, Warehouse management, Quality control, Plant layout and CNC Simulation. The critical challenges in AR/VR technology implementation at hardware and software level and opportunities for the further developments are discussed.In 2021, Martins et al.29, presented the concept of intelligent additive manufacturing and design (IAMD) while providing a triple-layer model for reference. Details about these three layers, i.e., digital thread layer, cyber-physical layer, and intelligent service layer, are presented. Moreover, both scientific and engineering challenges rose during the studies and implementations of IAMD are discussed together with potential solutions. In 2023, Liu et al.30, in this study, we develop a novel and highly practical maintenance model to fill the gap. The proposed model simultaneously considers the predictive maintenance and inventory policies of spare parts. In light of the high degree of complexity in modern manufacturing systems and the profound stochastic city in component degradation, a met modeling-based simulation optimization method is proposed to find the optimal component inventory policy and degradation level thresholds of each component. In 2022, van Dinter et al.31, this research aims to gather and synthesize the studies that focus on predictive maintenance using Digital Twins to pave the way for further research. A systematic literature review (SLR) using an active learning tool is conducted on published primary studies on predictive maintenance using Digital Twins, in which 42 primary studies have been analyzed. In 2023, Gupta et al.32, this paper presents a scalable and economical maintenance 4.0 solution for such a system using data from sensors installed . Differentiating between anomaly detection and outlier detection the paper presents an algorithm that can be used to remove idle and noisy data from the datasets. In 2022, Liu et al.33, this article proposed Predictive Maintenance (PdM), as a pivotal part of Prognostics and Health Management (PHM), plays a vital role in enhancing the reliability of machine tools in the Internet of Things (IoT)-enabled manufacturing. In order to realize a highly reliable maintenance plan integrated with the fault prediction, the maintenance decision-making, and the Augmented Reality (AR)-enabled auxiliary maintenance, an intelligent predictive maintenance approach for machine tools is proposed in this paper via multiple services cooperating within a single framework.In 2022, Xiong et al.10. The first important step is to activate the role of IoT applications4.In this research work we study the possibilities of applying the human faulty operation effect on PdM. Data are collected and analyzed to identify operational measurable factors and its influence on the maintenance. We adopt a PdM strategy based on the availability of performance over time, service life prediction models, and Methods for developing a decision support system for corrective maintenance, PdM. Basis of maintenance, and monitoring system. Design of a machine is depending on the technologies of the current industrial revolution, and production lines system’s needsThe data acquisition system is used to collect the output signals of sensors located on all parts of the production lines and converts them into addressable electronic signals and digital data that can be analyzed and compared to increase data integrity and to provide an analysis of these data for the benefit of the production process. Figure 11.All of sensors are connected to an electronic interface card (velamen interface card type: k8055) that is connected to the internal network of the factory and then to the cloud through the Internet gateway using Message Queuing Telemetry Transport (MQTT) protocol to connect to the IoT such as shown in Fig. To assess the effectiveness of the proposed system, we implemented it on a corrugated board factory in Egypt as a case of study. The following subsections present the implementation of the proposed system to apply our proposed approach in a real case of study.2. Data of this form are recorded for each running order as shown in Fig. Monitoring of faulty operation in the hydraulic systems of the machine maintenance in corrugating and gluing paper layers machine is depending on the operation orders. The monitoring of a human operation is depending on the recommended operation order requirementsAppropriate exploration method, an active scan method, is applied to identify which parts and components of the machine need to have more sensors to provide the system with sufficient data. To achieve this target, we rely on applying the information Failure Modes and Effect Analysis (FMEA), Fig. In IoT world, the challenges of system networking are more clear than ever. The introduction of digital technologies is becoming increasingly relevant. IoT applications range from Big-Data approach to full digital Industrial IoT solutions. These applications need not only a new technology in terms of IoT networks, but also innovative methods to integrate existing machines and AI based IoT workflows. In the arena of industrial communication protocols, two standards dominate this context: The first is the OPC-UA andthe second is the MQTT, which are compared in this article.The MQTT message protocol relies on the concept of the publish-subscribe pattern. Important for the publish-subscribe model of MQTT is a broker, which is the key point of communication. Clients can be interfaced to the message broker and handle data with each other through topics, which are sent with messages. If a message is published on a certain topic, then this is transferred to all participants with subscription of this topic.The server/client design is the classical communication protocol in OPC-UA. It relies on the idea that there is a passive server component that delivers data for all client applications in the system. These applications may access data from the server through several standard services.IoT applications are the primary utility case for MQTT. When data are needed from remote stations and sent over an unreliable internet, MQTT should be the first choice. MQTT can guarantee secure and complete data exchange through built-in properties. Another typical use case of the messaging protocol is the IoT gateways that integrate sensor data, pre-process it, and send it to the cloud for data analysis via MQTT.The main case of the OPC-UA communication protocol is the closed-loop system control in the local area network (LAN). When machines on a factory floor require to communicate in real time, the standard presents its strengths. The standard is especially suitable for the integrated services and extensions of SCADA systems.In the methodology we assess the failure impact and apply Fuzzy MULTIMOORA method.19. Conventional FMEA makes use of a Risk Priority Number (RPN) to calculate failure elements O, SandD, where O is the probability occurrence of the failure, S is the severity of the failure, and D is the ability of detection for each failure. Each of risk elements have mathematical scale from 1 to 10. The risk priority is directly proportional to the RPN of the failure mode. Figure We use FMEA which is a methodology that aimes to prevent failures relying on the perfect assessment of impacts, and then determines the priority of possible actions for reducing the occurrence of failures. Applying of FMEA is achieved to the maintenance system where the analysis of FMEA distinguishes the possible failure modes, evaluates the cause and effects of dissimilar failure modes, and predict of high-risk failures35. These are considered the best way to analyze the potential failure modes, their causes, and arrange them depending on the priority and the effects of failure on the machine. This mainly aims to assess the risk associated with the identified failure modes and prioritize them. The main target of this is to increase the ability of the system to predict the failure in any machine part to support expansion of the scope of its industrial applications. MOORA is the main idea of MULTIMOORA method. MCDM technique makes use of a new model where fuzzy set concept and MULTIMOORA method are implemented for the evaluation of failure modes and rating in FMEA37. The risk factors and their relative weights are treated as fuzzy variables and evaluated by using fuzzy linguistic terms using different teams and fuzzy ratings38. MULTIMOORA method is used mainly to compare and to determine the real risk ranking of the failure modes that have been identified and calculate the effect of its weights. We study the trapezoidal fuzzy numbers which will be utilized in the FMEA model proposed in this article. Figure 39.FMEA is a methodology uses the potential failure modes to prevent machine failures depending on the evaluation of impacts, probability of occurrence, and how difficult is it to detect. After that, FMEA determines the priority of possible actions to eliminate the occurrence of this failures. FMEA helps to study the influence of machine parts failures on system performance, safety, and machine functions success. The multi-objective optimization by ratio analysis (MULTIMOORA) method is a recently introduced based on the multi-criteria decision-making (MCDM) methods40. Ensuring the non-stop production requires a solid maintenance plan. Our machine consists of three major systems hydraulic, steam, and gluing where it is intended to conduct an FMEA project to minimize the potential for failure occurrence. Through the data collection and the sensors readings, 11 potential failure modes were explored and listed, presented in Fig. S, O, andD), to calculate RPN for each failure mode which are presented in Table A case of study of corrugated cardboard machine is provided to illustrate the practicality and usefulness of the proposed Fuzzy FMEA approach. The main purpose of that is to arrange all failures and determine the extent of the risk exposure by which we carry out the appropriate maintenance procedureHelwan University and EAEA Research had approved the publishing of this article.m.FMEA team member Step 1 The objectives of the failure risk assessment are defined and the scope of the FMEA is accurately described. Defining the main machine function and its sub-parts and defining the systems and components that we want to analyze for failure. This step controls the results failure modes Step 2 To execute the MULTIMOORA method, team 1 and team 2 members  have weights (0.55 and 0.45) respectively for the same failure modes FM1 to FM11 RPN calculation. The two teams’ members can rate the failure modes and risk factors in linguistic terms as well. The linguistic ratings given by the two team members are .Step 3 Define risk factors and select suitable linguistic variables set of risk elements and their calculation metrics which are established to evaluate the hazard of failure modes. FMEA teams members use the linguistic terms to evaluate the importance of risk factors and the rate failure modes. Then, transformed into fuzzy numbers with the correspondence of their fuzzy equivalents.Step 4 Assemble the teams’ members linguistic assessment of the fuzzy collected ratings which belong to failure modes of each risk factor. Then, risk factors can be calculated to set the fuzzy group matrix. The data aggregation for risk factors and weighs then can be deducted.Aggregated fuzzy weight for each risk factor Step 5 The Normalized fuzzy assessment matrix uses the fuzzy ratio system to clear the normalization of the fuzzy numbers according to appropriate values of fuzzy numbers. The aggregated fuzzy values are calculated by Eqs. ( by Eqs.  and 5)  Step 5 TThe ratio wing Eq. :5\documeStep 6 The fuzzy maximal objective reference point (MORP) vector:The distance of each failure mode from the fuzzy MORP can be calculated the appropriate ranking. The ranking orders of all failure modes are defined according to the eccentricity from the reference point, Eq. .6\documeStep 7 The fuzzy full multiplicative of the overall utility, the ith failure mode, can be expressed as dimensionless fuzzy number by Eq.  of a 1, a is a regression parameter represents amount of increment on the variable y when x which increases by single unit, value of b yields P when X is zero. Odds ratio for occurs failure constituents categories. We are going to study a dependent variable that is binary a categorical variable that has two values such as “occurs” and “not occurs” rather than continuous. At binominal logistic regression by knowing the reference of machine parameters and we can predict whether that fault will be cause of failure or not. We can talk about the probability and about the odds of being failure or not. For example, let’s probability of failure occurs is 0.80. Then the odds of being failure would be given from the Eq. . The logistic regression curve relates the independent variable,  the Eq. :10\documln where the natural log of 8/2 is 2.217 logof2/8 is X < 1, the natural log is less than zero, and decreases rapidly as X approaches zero. When ln(odds) is negative. ln logistic regression, the dependent variable is the natural log of the odds, see Eq. . SCP is considered one of the most important parts of the production line . This critical point has 12 alarming input signals  and the possibility of output faults are 9 faults . The definition of the faults and their corresponding alarms are shown in Fig. 44.This proposed technique can be used in the global fault diagnosis system in all critical points in the production lines. According to every Training pattern the hidden layer nodes have their own outputs which are used as inputs of the output layer nodes. As the learning process is continuing the Root Mean Square (RMS) error decreases tell the allowed error is achieved, then the training stops, see algorithm 2. After network training every pattern of data have their own error value which is called pattern error. For More Information , please, readThe proposed maintenance analysis model is a superior analysis method since it can correlate maintenance reports of machine failures with data sent from sensors. Moreover, it can analyze the severity and evaluate the risk when data are very often imprecise and fuzzy. The traditional model of failures evaluation indicates failures FM10, FM8 and FM7 which have the highest priority and needing early corrective actions more than the rest of the failures. The proposed fuzzy FMEA model using MULTIMOORA method easily quantifies these types of data. This method includes an effective method to weight the risk factors and to rank the failure modes as a result, failures FM4, FM10, and FM6 become the highest risk priority. The results of comparison analysis show that a more accurate ranking can be determined for the machine failures by application of fuzzy set theory and MULTIMOORA method to FMEA. That prevents the machine parts to fail by which we can identify the main and sub-causes for the failure and we can determine the risk priority of failures. On the other hand the DLFD could translate the the different alarming patterns into clear faults by which it guides the control room engineers to find the faults.


The neck is a critical region containing many essential structures. Before surgical intervention, it is crucial to assess the adequacy of the airway and circulation, as well as the presence of any skeletal or neurological damage. Here, we present a case of a 33-year-old male with a background of amphetamine abuse who presented to our emergency department with a penetrating neck injury just below the mandible at the hypopharynx level, resulting in an upper zone II neck injury with complete separation of the airway. The patient was taken immediately to the operating room for exploration. Airways were managed by direct intubation, hemostasis was maintained, and the open laryngeal injury was repaired. After the surgery, this patient was transferred to the intensive care unit for two days and discharged after a satisfactory full recovery. Penetrating neck injuries are rare but often fatal. Advanced trauma life support guidelines emphasize the importance of managing the airway as the first action. Providing multidisciplinary care before, during, and after trauma can help prevent and treat such incidents. Penetrating neck injury (PNI), characterized by a disruption of the platysma muscle, is associated with a mortality rate of up to 10% in the United States ,3. OptimA 33-year-old man with amphetamine-induced psychosis presented to the emergency department (ED) with a neck injury caused by a large knife just below the mandible at the level of the hypopharynx. The patient was hemodynamically stable upon arrival and conscious, with a Glasgow coma scale score of 13 out of 15. While on room air, he was breathing spontaneously and had equal air entry bilaterally, with no esophageal injury or neurological abnormalities. On examination, the airways were partially exposed due to a transverse cut wound at upper zone two extending between the right and left sternocleidomastoid muscles. We later discovered that this injury was associated with a complete separation of the airway superior to the thyroid cartilage and bleeding, which we controlled on applying direct pressure. The patient was then taken to the operating room (OR), where the trauma team initially managed the airway with an endotracheal tube size of 7 millimeters inserted into the trachea via the wound Figures , 1B.The patient was shifted to the OR table for a formal tracheostomy through a separate incision site away from the primary injury site Figures , 2B. AvoAn intraoperative laryngoscope and endoscope examination were carried out prior to the patient's neck exploration in the operating room. The neck of this patient was completely transected. The transection involved the thyroid cartilage, hyoid bone, aryepiglottic fold, and epiglottis. This was associated with a full-thickness cut in the right upper part of the thyroid lamina, which was displaced and attached only posteriorly, and the left anterior upper part of the thyroid lamina, which was stable. The wound was further explored. The wound was more superficial on the right side and deeper on the left. Upon further exploration of the wound, it was found to be associated with a laceration that separated the epiglottis and vocal cords at the level of the hypopharynx, as well as a fracture of the right thyroid and thyroid alar cartilage Figure .Upon assessment of the wound vasculature, active bleeding was discovered from the left facial vein and the anterior jugular veins. The bleeding was thoroughly controlled, and the facial vein transection was managed by ligation. Additionally, a complete transection of the bilateral anterior jugular veins was identified and subsequently managed by meticulous proximal and distal ligation to ensure hemostasis. The internal jugular and the vagus nerve were identified, and the left carotid sheet was dissected, revealing no evidence of injury. After the neck wound closure, this patient's examination was concluded with an esophagogastroduodenoscopy to evaluate the cervical esophagus; the scope was successfully passed through the oropharynx and area of repair down to the esophagus. No hematomas were found distal to the injury on the endoscopic examination. A nasogastric tube (NGT) was inserted under direct vision afterward. The airway was secured with a tracheostomy.The ear, nose, and throat team repaired the hypopharynx; the right and left thyroid lamina fracture lines were sutured bilaterally by polypropylene 2.0 sutures . The patient's upper part of the chest and chin were fixed using micro-suture 3.0  to keep the neck at complete flexion at all times. The epiglottis base was sutured back to the laryngeal surface of the thyroid lamina in the midline by three interrupted stitches using polypropylene 2.0 (Figure Nearly 5%-10% of all trauma cases presented to the ED are directed to the head and neck . PNIs caZone I reaches the level of the cricoid cartilage between the clavicles and sternal notch. Zone II is the area between the cricoid and the inferior mandibular border ,3. The aThis invasive intervention was in favor of early detection of vascular bleeding that could be missed by physical examination . This reNowadays, most surgeons support treating penetrating wounds selectively based on the neck zone, the patient’s physiological condition, and the clinical findings after evaluating the entire neck as a single entity . This imUpon the primary survey, we ensured that the airway was protected; the literature does not agree on a single airway intervention for patients with airway compromise . TreatmePrior to commencing the repair procedure, the patient's cervical region was subjected to a thorough re-examination to detect any comminuted fractures. Given its technical ease relative to wire fixation, we first utilized it to stabilize the minimally displaced fractures when the perichondrium was still in place. Various techniques for fixing the laryngeal framework have been reported. Including laryngeal framework fixing techniques using nonabsorbable monofilament sutures, stainless steel wire, and titanium mini plates ,16. PolyThe drains are removed, when output becomes negligible, and there are no signs of subcutaneous collections. In most patients undergoing transcervical repair of laryngeal fractures, swallowing function will be reduced in the early postoperative term. Until a modified barium swallow demonstrates a functional, secure swallow, nasogastric feeding should be continued. Due to the patient's background of psychological instability and the tendency to frequently removing the NGT tube, stent removal was not performed before the nasogastric feeding , as thatThis report at hand discusses a rare yet oftentimes fatal presentation of penetrating neck trauma, which poses a significant risk of immediate life-threatening events due to the potential damage to the airway resulting from the presence of a multitude of vital structures in the neck region. The risk of immediate life-threatening events makes the initial assessment and management of the affected individual of utmost importance. The Advanced Trauma Life Support guideline emphasizes the need to manage the airway as a crucial part of the primary survey, followed by a meticulous evaluation of the patient's vital signs and hard signs upon presentation. The use of an endotracheal tube may be necessary until the definitive airway is established, maintaining the airway and preserving the blood supply during the repair process. Additionally, the selection of the appropriate type of suture is essential for each repair, considering the location and severity of the injury.


BackgroundWhile a considerable amount of information on neck pain is available online, the quality and comprehensiveness of this information can vary greatly. Particularly, the representation of the biopsychosocial model - which recognizes neck pain as an interplay of biological, psychological, and social factors - in online information remains unclear. Given the prevalence and accessibility of online health information, it is important to understand its quality and how it may shape individuals' understanding and management of neck pain. Therefore, the objective of this study was to analyze the quality of online Japanese information on the causes of neck pain from a biopsychosocial perspective.MethodologyA descriptive cross-sectional study was conducted. The search term "neck pain" was utilized on Google's search engine in June 2023, and the websites from the first two pages of the search results were included in the study. Ten advertisement websites were excluded, resulting in 19 websites being analyzed. Each website was evaluated based on the presence of the Health-on-the-Net (HON) code. Biomedical and psychosocial factors present in each website were identified using the biopsychosocial analysis tool. Websites were then categorized as biomedical, limited biopsychosocial, or biopsychosocial based on the number of psychosocial factors they mentioned.ResultsAmong the 19 evaluated websites, only one possessed the HON certification, indicating a potential lack of credibility for the remaining sites. Of these websites, a large majority (63.2%) were classified as biomedical, while the remaining (36.8%) were classified as limited biopsychosocial. All the websites included some form of biomedical information on the causes of neck pain, while only seven websites mentioned psychological factors and one website mentioned social factors. The most common biomedical causes of neck pain discussed were cervical muscle strain and radicular pain due to cervical disc prolapse. On the other hand, the limited biopsychosocial websites highlighted perceived stress, depressed mood, and job-related mental stress as psychosocial factors contributing to neck pain.ConclusionsThis analysis revealed that freely accessible Japanese online information on the causes of neck pain, as found through Google, predominantly focuses on the biomedical causes, often neglecting or insufficiently addressing the psychosocial aspects. This finding underscores a gap between the available online resources and the comprehensive understanding promoted by the biopsychosocial model of health. Healthcare professionals need to be proactive in guiding their patients toward reliable, well-rounded resources that acknowledge the crucial role of psychosocial factors in neck pain. Furthermore, developers of online health information must aim to improve the depth and breadth of psychosocial factors discussed, promoting a more holistic understanding of neck pain for the Japanese public. Neck pain is a common musculoskeletal pain disorder that is recognized as a major health problem in Japan . Neck paIt has been reported that many patients search the Internet to gather health-related information. Yamamoto et al.  in a stuHowever, these studies have focused on online English information. This study aims to fill the gap by analyzing the quality of Japanese online information on the causes of neck pain from the perspective of biopsychosocial models.Ethics approval and consent to participateThis research did not involve any human research subjects and only included written texts publicly available on the Internet; therefore, ethics approval or consent to participate was not required. Online information was anonymized and used.Search engine and strategyA descriptive cross-sectional study was conducted to analyze online information regarding the causes of neck pain. An online search was conducted using Google’s search engine on June 28, 2023, using the keyword "neck pain." Google was used because it accounts for more than 77% of searches in Japan as of May 2023 and is the most popular search engine compared to other search engines . To miniWebsite identification and categorizationIn this study, we referred to the website inclusion criteria developed by Neelapala et al. , a comprQuality assessmentTo identify the number of websites certified by established benchmarks for quality health information, the presence of the HON code was identified . The HONBiopsychosocial analysisA qualitative assessment of online information on the causes of neck pain was performed for biomedical and psychosocial factors based on the biopsychosocial analysis tool developed by Neelapala et al.  This cheData analysisThe results of the quality of online information were calculated using descriptive statistics. This study used a similar methodology as the report by Neelapala et al. : websiteWebsite identification and categorizationGoogle generated 37,100,000 links using the search term "neck pain." Of the websites up to the first two pages, after eliminating the 10 advertisement websites, 19 independent websites remained and were included in the review  and seven as limited biopsychosocial (36.8%) , and therefore, the true breadth of the biopsychosocial focus of many websites could be gained through further studies analyzing the many images and video clips displayed. Finally, this study was conducted in June 2023. It is unclear to what extent the same results will be reproduced since the study, owing to the rapid and continuous evolution of technology and information on the Internet. Despite these limitations, the results of this study reveal the need to improve the description of Japanese online information about the causes of neck pain and provide important information for the development of websites based on biopsychosocial models.In this study, the quality of online Japanese information on the causes of neck pain was analyzed from the perspective of a biopsychosocial model. The results showed that online information on the causes of neck pain in Japanese, which is freely accessible through the Google search engine, contains limited or no information on the psychosocial factors of neck pain. Consequently, the findings of this study underline the necessity to enhance the portrayal of Japanese online information related to the etiology of neck pain. These insights contribute significantly to the future development of web resources grounded in biopsychosocial models.


At present, text-guided image manipulation is a notable subject of study in the vision and language field. Given an image and text as inputs, these methods aim to manipulate the image according to the text, while preserving text-irrelevant regions. Although there has been extensive research to improve the versatility and performance of text-guided image manipulation, research on its performance evaluation is inadequate. This study proposes Manipulation Direction (MD), a logical and robust metric, which evaluates the performance of text-guided image manipulation by focusing on changes between image and text modalities. Specifically, we define MD as the consistency of changes between images and texts occurring before and after manipulation. By using MD to evaluate the performance of text-guided image manipulation, we can comprehensively evaluate how an image has changed before and after the image manipulation and whether this change agrees with the text. Extensive experiments on Multi-Modal-CelebA-HQ and Caltech-UCSD Birds confirmed that there was an impressive correlation between our calculated MD scores and subjective scores for the manipulated images compared to the existing metrics. Research fields of computer vision and natural language processing have gradually developed by interacting with each other. Particularly, with the emergence of recent deep learning techniques, such as a convolutional neural network, long short-term memory , transfoWith the emergence of generative models such as the variational autoencoder , generatText-guided image manipulation methods reflect great potential, and the establishment of evaluation metrics is necessary for their further development. Since the results of text-guided image manipulation are based on a text given by the user, subjective evaluations are the most reliable, but the collection of subjective evaluations requires tremendous time and effort. Considering this, several metrics for automatically evaluating image manipulation performance have been proposed and practically implemented ,33,34,35The similarity between a text prompt and the manipulated image completely ignores how an input image has been changed.The similarity between the input and manipulated images completely ignores regions manipulated according to the text prompt and evaluates the image reconstruction.There are limitations in deriving the performance of image manipulation models from both scores listed above because they commonly have a trade-off relationship.Although a research field on image quality assessment has been established, there is insufficient research on evaluation metrics for image manipulation performance. The existing evaluation metrics have limitations in directly evaluating image manipulation according to text prompts. Specifically, as shown in Specifically, point (a) shows the problem of evaluating only image synthesis from the text prompt, and there are no constraints on the changes made to the input image. Point (b) shows the problem of similarity between the input and manipulated images not evaluating the performance of preserving the text-irrelevant regions only, and instead, evaluating the performance of simple image reconstruction. In point (c), we show that image manipulation causes a trade-off relationship between the similarities shown in points (a) and (b), and it is difficult to derive the accuracy of text-guided image manipulation from them. This indirect evaluation is limited in its ability to collaboratively evaluate how an image has changed before and after its manipulation and whether the change is consistent with the text prompts. If they could be collectively evaluated on a single scale, no trade-off relationship would arise, although this is yet to be resolved. Consequently, previous studies have performed time-consuming and laborious subject experiments and shown numerous samples to supplement this incompleteness.To address the above problem of indirectly evaluating image manipulation, as shown above, we establish a logical yet simple metric, called Manipulation Direction (MD), for evaluating the accuracy of text-guided image manipulation in this study. We name the evaluation metric “MD” because it is designed to focus on the direction of changes in images and texts that occur before and after image manipulation in the common embedding space. Using MD as an evaluation metric, we can calculate evaluation scores that focus on the similarity between changes in a text provided by a user and changes from the input to the manipulated image. In text-guided image manipulation, a user specifies the desired image manipulation by performing word replacement in the text prompt accompanying an input image. This replacement in the text space can be interpreted as the direction of the image manipulation desired by the user in the image space. When image manipulation is not according to a text prompt, or when text-irrelevant regions are manipulated, the similarity with the direction of the text change inevitably decreases. Moreover, the more similar the direction of changes in the text prompt and the image are, i.e., the higher the MD score, the more accurate we can consider the image manipulation to be. MD comprehensively evaluates the image manipulation according to a text prompt and the preservation of text-irrelevant regions based on the direction of the text change; thus, there is no trade-off relationship, unlike existing evaluation metrics. MD precisely captures the changes between each modality and can directly evaluate the performance of image manipulation according to the text prompts. The eventual purpose of MD is to provide quantitative evaluations of text-guided image manipulation and to calculate evaluation scores that correlate with subjective evaluations of manipulated images. Our primary contributions are summarized as follows.We newly propose MD, which is an evaluation metric for text-guided image manipulation.MD is defined as the consistency of changes between images and texts occurring before and after manipulation in the common embedding space.MD comprehensively evaluates the image manipulation according to a text prompt and the preservation of text-irrelevant regions on a single scale.The remainder of this article is organized as follows. In Recently, vision-language tasks and text-guided image manipulation, in particular, have gained considerable attention. The major advantage of text-guided image manipulation is that it provides highly flexible image manipulation by receiving text prompts from a user. Text-guided image manipulation methods generally aim to manipulate text-relevant regions according to a text prompt and preserve text-irrelevant regions. Dong et al.  first prResearch on image quality assessment has a long history and can be broadly classified into three categories—full-reference (FR), reduced reference, and no-reference—according to whether or not reference images are needed. In general, previous studies on text-guided image manipulation have evaluated the image generation performance of models by reconstructing the manipulated images from the input images. Since the input image can be used as a reference to evaluate the quality of the manipulated image, evaluation metrics based on FR are beneficial. In this section, we describe the evaluation metrics based on FR before and after the introduction of machine learning.Before the introduction of machine learning into the field of image quality assessment, the mean squared error (MSE), peak signal-to-noise ratio (PSNR), and SSIM were typical FR-based evaluation metrics. MSE is computed by averaging the squared intensity differences between the pixels of the manipulated and the input images, and it is widely used because of its simplicity. PSNR is an evaluative metric that adjusts the value of MSE by using the maximum possible power of a signal and it can be considered as a type of MSE. MSE and PSNR fail to consider the content of an image and the characteristics of the human visual system (HVS), and their evaluation values usually show a weak correlation with human perception. As an evaluation approach that considers the HVS, Wang et al. proposed SSIM . SSIM adMachine learning has proven to be successful in evaluating image quality. In particular, IS  and FID In text-guided image manipulation, manipulated images are evaluated from two perspectives: image quality and accuracy of image manipulation. These evaluation approaches are independent of each other and should be conducted separately. In this paper, we propose a new metric that evaluates the accuracy of image manipulation rather than image quality.The main purposes of text-guided image manipulation are to manipulate attributes in an image according to a text prompt and reconstruct the content in the text-irrelevant regions of the input image. In previous studies, the results were separately evaluated for these two objectives. In particular, one objective concerned the consistency between a manipulated image and a given text prompt, and the other concerned the similarity between a manipulated image and an input image. The details of these two evaluation approaches are described as follows.k and R-precision from the calculated cosine similarity. Recent improvements in the common embedding space represented by CLIP hold promise for text-guided image manipulation evaluation; however, there is insufficient research on the approach to calculating evaluation scores based on such a space.The consistency between a manipulated image and a given text prompt is generally evaluated by focusing on the similarity between the two modalities. Particularly, previous studies, such as for the deep attentional multimodal similarity model  and the The similarity between the input and manipulated images is generally evaluated by focusing on the distance between them. Particularly, L1 and L2 distances have been used in previous research. With this calculation approach, distances increase even when the changes in a manipulated region are appropriate. The calculation of these distances is also sensitive to shifting positions and is difficult to generalize. The L1 or L2 distance is calculated by comparing an input image with a manipulated image at the pixel level, increasing these distances when there is a slight misalignment. However, in terms of human perception, a slight misalignment has only a minor effect on the accuracy of image manipulation.These similarities and distances are usually calculated and evaluated separately. Moreover, Li et al. proposed MP , which uIn this study, we develop a new metric for evaluating the performance of text-guided image manipulation, categorized as the metric described in this section. Existing evaluation metrics separately evaluate image manipulation according to a text prompt and the preservation of text-irrelevant regions. Further, two evaluation scores calculated at different scales are forcibly merged. Moreover, the proposed metric, MD, focuses on text and image changes that occur before and after image manipulation and can comprehensively evaluate the performance of text-guided image manipulation.change in image features from the input to manipulated images and the change in text features by the word replacement for performing the manipulation in the common embedding space. Thus, we name the evaluation metric “MD” because it is designed to focus on the direction of changes in images and texts that occur before and after image manipulation in the common embedding space. To perform the evaluation, as shown in To evaluate the performance of text-guided image manipulation, we examine the case shown in i) i, and the text encoder t) t. Notably, D denotes the dimensionality of the common embedding space. During the training of the image and text encoders, CLIP maximizes the cosine similarity of N pairs of correct image and text embeddings in a batch and minimizes the cosine similarity of N pairs of incorrect embeddings. Finally, the image and text encoders are trained simultaneously to obtain a multimodal embedding space. Particularly, CLIP is trained on a very large image–text pair dataset and thus provides high expressive power for embedding.To perceive how changes occurred between image and text modalities based on image manipulation, we embed the input, manipulated images, and text prompts before and after the word replacement. To embed these modalities, we apply the recently proposed CLIP . CLIP inI, manipulated image T, and replaced text prompt I), T), and I to the manipulated image T to the replaced text prompt We evaluate the performance of text-guided image manipulation using the elements that are processed and generated during the manipulation  and L1 distance (L1) as the comparative metrics, as well as manipulative precision (MP)  to evaluCS calculates the cosine similarity between the manipulated image  on CLIP . This meI and the manipulated image C, H, and W denote the number of color channels, height, and width of the images, respectively. This metric takes a value between 0 and 1.L1 calculates the L1 distance between the input image MP evaluates the performance of text-guided image manipulation by multiplying the normalized CS and L1 values. This metric takes a value between 0 and 1.Notably, higher scores calculated by the above metrics indicate better image manipulation.We calculated a mean opinion score (the MOS) according to  for eachIn To verify the correlation between the MOS and the evaluation scores calculated by the proposed and comparative metrics, scatter plots are shown in To quantitatively verify the relationship between the MOS and the evaluation score by each metric, following ,46, we uIn the above validation, because the image manipulation performance depends on existing text-guided image manipulation methods, there is a limitation in evaluating the extensive performance of image manipulation. This section verifies how the evaluation score calculated by the metrics changes in response to continuous changes in a manipulated image. We applied an evaluation metric to the loss function of the image manipulation network to qualitatively confirm the change in the evaluation score during training and the corresponding manipulated image.Finally, we verify the influence of the common embedding space used to calculate the MD score. Although we used the common embedding space provided by CLIP, it was confirmed in the previous verification that MD does not completely rely on its expressive capabilities. Particularly, CLIP is also applied to the calculation of CS and MP used as the comparative methods, and MD has a significantly higher correlation with the MOS than CS and MP. However, a strong embedding model such as CLIP is necessary to a highly accurate evaluation, and its expressive capabilities can influence MD. In the following, we verify the correlation between MD and the MOS using various common embedding spaces.D for each common embedding space is shown in To embed images and text prompts into a common embedding space, we used CLIP , whose iWe show the correlation coefficients between the MOS and the MD score calculated in different common embedding spaces in the change in the image modality and the change in the text modality occurring before and after image manipulation. The evaluation using MD simultaneously considers both image manipulation according to text prompts and the preservation of text-irrelevant regions on the same scale. The experimental results demonstrated that MD could calculate evaluation scores more strongly correlated with the MOS than the existing metrics. Further, we constructed an image manipulation network applying evaluation metrics to a loss function and we confirmed that the manipulated images improved as the MD score increased. The approach of calculating MD to focus on the relationship between image and text changes is useful for evaluating the accuracy of text-guided image manipulation, but the performance of the embedding model is necessary for a highly accurate evaluation. Expectedly, the accuracy of MD will improve in the future as the common embedding space becomes more robust. In future works, to evaluate a variety of image manipulation, we plan to construct an evaluation metric that focuses not only on the global features of the whole image, but also on local features. We proposed a logical and robust metric, MD, to evaluate the accuracy of text-guided image manipulation. MD calculates the similarity between


Social skills training (SST) is used to help individuals with autism spectrum conditions (ASC) better understand the perspectives of others and social interactions, develop empathy skills, and learn how to engage with others socially. However, many individuals with ASC cannot easily sustain high motivation and concentration during such an intervention when it is administered by humans. We developed a social skills training program using multiple humanoid robots (STUH), including an android robot, that aimed to enable individuals with ASC to become familiar with the perspectives of others and improve their sociability and empathy skills. The objective of the present study was to investigate the effectiveness of STUH for these individuals.In STUH, we prepared 50 social exercises that consisted of conversations and behavioral interactions between an android robot and a simple humanoid robot. We prepared another humanoid robot that featured a cartoon-like and mechanical design, which played the role of host. In the first half-session of STUH, participants worked on the exercise from the perspective of an outsider. In the second half-session of STUH, they simulated experience by using robots as their avatars. The intervention associated with STUH was conducted for five days in total. We conducted an analysis of variance (ANOVA) featuring the intervention time point as the independent variable to examine changes in each score on the sociability index items.In total, 14 individuals with ASC participated in the study. The results of multiple comparison tests using the Bonferroni method indicated that all sociability index items improved between preintervention and follow-up. Our program enabled the participants to become familiar with the perspectives of others and improve their sociability.Given the promising results of this study, future studies featuring long-term follow-up should be conducted to draw definitive conclusions about the efficacy of our training system. Autism spectrum conditions (ASC) is characterized by deficits in social communication and limited and repetitive behavioral patterns . IndividThe use of SST for individuals with ASC has been received a great deal of attention , 7. HoweIncreasing anecdotal evidence attests to the fact that individuals with ASC may have special opportunities to use robots for such help –19. RoboA previous study revealed that using multiple robots provides individuals with ASC flexible and realistic role-play scenarios, promoting concentration during the evaluation and encouraging high levels of motivation from start to finish . In anotOne concern in this context is that the acquisition of skills through the help of robotic intervention does not allow those skills to be generalized to daily life. The appearance and behaviors of an android robot resemble those of an actual human , 26. AndIn light of these factors, we developed a social skills training program using multiple humanoid robots (STUH), including an android robot, that aimed to help individuals with ASC become familiar with the perspectives of others and improve their sociability and empathy skills. In STUH, we prepared 50 social exercises that consisted of conversations and behavioral interactions between android robots and simple humanoid robots. Previous studies suggested that individuals with ASC have different preferences for the appearance of robots , with eaThe present study was conducted with the approval of the Ethics Committee of Kanazawa University. Participants were recruited through leaflets explaining the details of the experiment. All procedures performed in studies involving human participants were conducted in accordance with the ethical standards of the institutional and/or national research committee and the 1964 Declaration of Helsinki and its subsequent amendments or equivalent. After receiving a full explanation of the study, all participants and their guardians agreed to participate in the study. Written informed consent for the release of any potentially personally identifiable images or data contained in this article has been obtained from the individual and/or the legal guardian of the minor. No conflicts of beha exist in this study. The inclusion criteria included (1) having a diagnosis of autism spectrum disorders (ASD) according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition  from the experienced psychiatrist, (2) having an IQ ≥ 70, and (3) not on any medication. The exclusion criteria were medical conditions associated with ASD . To exclude other psychiatric diagnoses, the Mini-International Neuropsychiatric Interview  was perfParticipants did the Autism Spectrum Quotient-Japanese version (AQ-J) , which hFull-scale IQ scores were measured by either using the Wechsler Adult Intelligence Scale–Third Edition (WAIS-III) or the Japanese Adult Reading Test (JART) . We usedThe severity of participant’s social anxiety traits was measured by using the Liebowitz Social Anxiety Scale (LSAS) . This clThe Adolescent/Adult Sensory Profile  is a seThe Interpersonal Reactivity Index (IRI) is a multidimensional scale of empathic traits that includes 28 self-report items across four subscales . In thiIn total, 14 individuals with ASC participated. The details are shown in We used A-Lab android ST  41, 42), 4241, 4A desktop-type, simple humanoid robot   11, 43,,43, 44 wSota  45–47) –47 45–47The intervention associated with STUH each day  lasted approximately 1 h and was conducted over 5 days  in total. The average interval of each intervention was 2 weeks. Each day, participants received an intervention that was divided into the first half-session and the second half-session, each of which included of five exercises. The flow chart of this study is shown in After the first half-session, the participants were seated facing each other, and the computers used to operate the robots were placed in front of them. In this study, before the second half-session, the research assistant explained the operation of the robots  and provided an example. After confirming that there were no questions regarding the operation of the robot, the second half-session of the intervention began. Preintervention (1 week before the experiment), after each intervention and at follow-up (2 weeks after the last session), two raters independently rated the sociability index item pertaining to the participants’ understanding of and beliefs regarding the feelings, behaviors, and perceptions of others in daily life situations as noted below.(1)Understand the other person’s way of thinking and situation.(2)Understand the other person’s feelings.(3)Understand the reason why the other person acted the way they did.(4)Try to understand why they think the way they do when conversing with others who think differently.(5)Even in cases of conflict, make an effort to put yourself in the other person’s shoes.(6)When listening to others, consider what they want to say.(7)Always try to put yourself in other people’s shoes to understand them.(8)Do not criticize the other person without considering their perspective.The score ranged from 1 (very poor) to 7 (very excellent). Prior to the experiment, both raters received training (lasting approximately 5 h) on scoring the interviews while watching videos of interview scenes. The score used in this study was the average of the scores of the two raters. The intraclass correlation coefficient was calculated to confirm interrater reliability. The coefficient was low but acceptable (ICC = 0.684). After the intervention, the following questions were asked of the participant’s supporters: “Did the participants learn to understand the perspective of the interviewer after the intervention?”We conducted statistical analysis using SPSS version 24.0 software . We conducted an analysis of variance (ANOVA) featuring the intervention time point as the independent variable to examine the changes in each score on the sociability index items.t-test was conducted on the IRI scores between preintervention and postintervention. Subsequently, the correlation coefficient between the change in IRI scores and the AQ-J was calculated. An alpha level of 0.05 was used for these analyses.The following analyses were conducted to examine the relationships between the intervention and the corresponding changes in empathy and autistic tendencies. First, a Since this study had a small sample size, the Shapiro–wilk test for normality was conducted, and we confirmed that the data were parametric. Although normality was not confirmed for the sociability index items, all parametric tests were conducted in this study due to the fact that analysis of variance is robust against deviations from normality. A one-way ANOVA was conducted to examine the changes in each sociability index item score from preintervention to follow-up. The assumption of sphericity was not confirmed by all analyses, and so Huynh-Feldt’s correction was employed. Since the ANOVA was repeated for eight items, the Bonferroni correction was used to evaluate significance.p < 0.05). The results of multiple comparison tests using the Bonferroni method showed that all sociability index items improved from the preintervention assessment to follow-up evaluation. Descriptive statistics and the results of the ANOVA are presented in The results indicated a significant main effect of measurement time in all sociability index items . The results of the correlation analysis are shown in To examine the efficacy of STUH with regard to improving empathy skills, a t test was conducted on the IRI subscore from preintervention to postintervention. The results showed no significant differences. The details are shown in After the intervention, all participants’ supporters responded to the following statement: “Participants learned to understand the point of view of the interviewer after the intervention.”In the current study, we assessed the efficacy of STUH, i.e., a social skills training program using multiple humanoid robots, including an android robot. The completion rate suggests that participants in STUH were able to continue to participate in the program without losing motivation. The establishment of a highly structured learning environment may have sustained their motivation and concentration during the program and enabled them to become familiar with the perspectives of others. Most notably, participants could enhance their sociability in a way that was generalizable to real-world settings. Interestingly, no human trainers were present in the training room. On the other hand, we did not find an improvement in empathy skills, although we did observe a relationship between the autistic traits of participants and the improvement of their empathy skills.Social skills training program using multiple humanoid robots is a social skills training program using multiple humanoid robots that is targeted at individuals with ASC. Individuals with ASC often achieve a higher degree of task engagement through interactions with robots than through interactions with human trainees , 17, 18.In this study, two participants worked in pairs, which may have allowed participants to understand that their thoughts are different from those of others. A previous study  demonstrIn this study, participants were able to improve their sociability in a way that was generalizable to real-world settings. It is generally difficult for individuals with ASC to improve their skills that can be generalized to real-world settings . SimulatIn light of the fact that the fantasy scale in the IRI is correlated with the cognitive aspect of empathy , this stThe intervention associated with STUH was conducted in a space featuring no human trainers, which is beneficial with respect to maintaining social distancing in the pandemic era. In our teleoperating system, the operator can control the robot from everywhere in the world, which is beneficial in terms of recruiting human resources, especially in rural areas with few human trainers. Most notably, in light of the greater affinity of individuals with ASC with robots than with humans –19, the The study possesses some notable strengths. First, the intervention was conducted only using the robot, and all learnings to acquire the perspective of others were conducted using the robot. Second, we also simulated social situations by using the robot as an avatar. Third, we conducted these learning activities in a peer-to-peer setting. These strengths have been linked to the improvement of sociability in participants.It should be recognized that this study has several limitations. First, the number of participants was relatively small. In addition, most participants were male. Future studies with larger samples including female participants are needed to offer more meaningful data on the potential use of this training. Second, this study was not a controlled study. We did not include a human trainer comparison group for comparison. At the time this experiment was conducted, the Japanese government had declared a state of emergency due to the spread of COVID-19, so we could not ask the participants to participate in comparison settings. Given that establishing effective SST is a pressing problem that can prevent individuals with ASC from obtaining and maintaining a competitive position, it was necessary for us to conduct pilot studies without a comparison. Since the expenses of providing care for individuals with ASC is very high , supportUnlike previous studies , 26, 42,The raw data are available from the corresponding authors on reasonable request.The studies involving human participants were reviewed and approved by the ethics committee of Kanazawa University. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin. Written informed consent was obtained from the individuals and/or minors’ legal guardian for the publication of any potentially identifiable images or data included in this article.KT and HK designed the study, conducted the experiment, conducted the statistical analyses, analyzed and interpreted the data, and drafted the manuscript. TM, YY, YM, HI, and MM conceptualized the study, participated in its design, assisted with the data collection and scoring of the behavioral measures, analyzed and interpreted the data, were involved in drafting the manuscript, and revised the manuscript critically for important intellectual content. HK was involved in the final approval of the version to be published. All authors read and approved the final manuscript.


Background: Pediatricians can cultivate a more trusting relationship with their non-English speaking patients by emphasizing the importance of upholding patient confidentiality in the presence of an interpreter. We designed a case for pediatric residents to increase comfort when conducting an adolescent interview using a medical interpreter, emphasizing the importance of upholding patient confidentiality, specifically when discussing sensitive health topics.Methods: We developed a standardized patient encounter (SPE) for pediatric residents at a large academic institution that focused on exploring sensitive health topics with an adolescent, non-English speaking female patient using an interpreter. A validated survey was administered upon completion of the case, prompting participants to reflect on their comfort and skills with specific activities before and after the case, and was analyzed using paired t-tests.p<0.01), indicating perceived personal growth in all educational objective categories. The majority of the participants  agreed that they built skills in understanding cultural humility and caring for future patients .Results: Eighty-nine residents participated; 66 were interns and 23 were in their second year of residency. The mean scores of all paired survey items significantly increased after the case (Conclusions: Upon completion of the case, residents reported increased comfort and skills using a medical interpreter for non-English speaking patients within the context of patient-centered care, discussing various sensitive health topics, emphasizing the importance of upholding patient confidentiality, and demonstrating skills in adolescent interviewing. Both medical confidentiality and cultural humility education can be integrated into simulation-based medical education to improve the quality of care for diverse patient populations. Communication is a core foundation of a patient-provider relationship, and the delicate complexities of this relationship can be compromised when an interpreter is introduced to the situation . EspeciaThese challenges can be further exacerbated when discussing sensitive topics, especially in populations with emerging autonomy, such as adolescents. Within the standard adolescent interview, the HEEADSSS exam is often used to document the social history and screen critical preventative health topics for adolescents . The resPracticing cultural humility is a strategy that medical providers can use to overcome these challenges, especially for providers who differ culturally from their patient population. Cultural humility has been defined as “a lifelong commitment to self-evaluation and critique, to redressing power imbalances . . . and to developing mutually beneficial and non-paternalistic partnerships with communities on behalf of individuals and defined populations” . The skiEducational contextThe concept for this teaching SPE was developed from a partnership between a refugee organization and members of our pediatric faculty. During a prior study on refugee perspectives on experiences with local healthcare providers, members of the community voiced concerns about the potential for private medical information to be shared with others by their interpreter . ConcernThis SPE was conducted on three separate days and took place in the simulation lab at The Simulation Center at Fairbanks Hall at the Indiana University School of Medicine over the course of five hours of protected educational time, during the annual required residency simulation curriculum. The SPE was one of eight simulations completed by the residents, with each simulation lasting approximately 20 minutes. Pediatric residents and residents in pediatric combined training programs, henceforth known as residents, participated in this simulation, held approximately nine months, 11 months, and 13 months after the start of their intern years. This specific scenario was performed in a simulation room that was designed to imitate a clinic room setting. For completion of the SPE, we had a chair for the SP, an earpiece microphone for the SP, an exam table, a chair for the resident, a chair for the interpreter, and a one-way glass mirror.Ethics approval and consent to participateThe need for informed consent and approval was waived by the ethics committee/Institutional Review Board of Indiana University as it was considered a quality improvement study. All methods were performed in accordance with the relevant guidelines and regulations of the Declaration of Helsinki.LogisticsResidents rotated through the eight simulation scenarios in groups of three to five residents per group. Residents were randomly pre-assigned into groups by a simulation educator who had no prior knowledge of the communication skills or relevant background or experiences of the residents. The groups rotated the lead on each new scenario they worked through during their day at the simulation lab. With each participating group in this specific scenario, the lead resident went into the simulation room while the rest of the residents in the group were led by the facilitator to observe the SPE from behind a one-way mirror. The actors portraying the adolescent and the medical interpreter in the SPE were recruited by our team and were trained on how to act and react in the presence of the resident. Both actors were bilingual. For the first iteration, the simulation actors were bilingual in Spanish and English. For the second and third iterations, the simulation actors were bilingual in Hakha-Chin and English. An experienced pediatrician faculty member facilitated the SPE. The facilitator was able to instruct via an earpiece microphone to the SP about how to respond as needed.For this simulation, the patient-facing scenario lasted approximately 10 minutes and was followed by a 10-minute debriefing with the group of residents. Before the resident entered the simulation room, they were informed that the patient was a 15-year-old non-English speaking female adolescent coming alone for a well-child check and that she needed an interpreter, who were both already seated in the room . The DebriefingOnce the SPE was completed, there was a 10-minute debriefing period, in which there was feedback discussion among the residents, facilitator, interpreter, and SP. This debriefing discussion included a review of key learning objectives, such as conducting an adolescent interview using non-judgmental language, appropriately using an interpreter, being perceptive of the patient’s demeanor changes, and addressing concerns in an open-ended way that demonstrates cultural humility. There were also opportunities for the SP and interpreter as well as the residents to share their perspectives and thoughts on the session. The SP and interpreter were also able to offer feedback on how the resident navigated the case to further meet the objectives of the SPE and to develop skills with patients in the future.Learner assessmentDuring the SPE, the observing residents were given a score sheet to evaluate the interaction between the actors and the lead resident, guided by the main objectives of the SPE . These AnalysisThe characteristics of the residents and the results of the survey were analyzed using descriptive statistics. Paired t-tests were performed to compare the results of the pre- and post-simulation questions. P-value (α) was set at 0.05. Unanswered survey questions were excluded from the analysis.Of the 139 residents in their respective residency classes, 90 were present for the simulation day. Forty-nine of the residents did not attend any part of the simulation day, due to having clinical responsibilities outside of the pediatrics department or vacation time. One resident declined to participate in the research. The remaining 89 residents represented seven different residency programs . The characteristics of the participants are displayed in Table During the SPE, all lead residents were able to transition into aspects of the HEEADSSS interview and recognized the adolescent’s discomfort regarding their discussion of sensitive information. Within the survey, the mean comfort level between pre-simulation and post-simulation significantly increased  Table .The mean difference between the Likert scores pre- and post-simulation ranged from +0.24 to +0.57 for enthusiasm to see adolescent patients, communicating and gaining rapport with the adolescent, appropriate use of an interpreter, discussing confidentiality, exploring depression symptoms, and exploring alcohol and drug issues. The greatest gains in Likert scores were seen in comfort taking a sexual health history, discussing confidentiality, and engaging in difficult conversations with diverse patient populations, with increases of +0.57, +0.45, and +0.45, respectively.The majority of residents  noted some level of agreement that this simulation helped them build skills in understanding cultural humility  as well as valuable skills to improve the care of future patients .At the end of the survey, there was an opportunity to write comments about the simulation in a free-text section. Many residents left comments, often describing how they valued the simulation, though two comments did note that it would be helpful if all residents were able to be the lead residents Table . The purpose of this SPE was to provide an opportunity for pediatric residents to navigate the challenges of communicating with non-English speaking adolescent patients in a way that fosters a trusting patient-provider relationship. The simulation’s focus was to conduct an adolescent interview using a medical interpreter and to discuss the importance of medical confidentiality. By addressing this issue in the SPE, residents were able to practice emphasizing the importance of upholding medical confidentiality with both the patient and the medical interpreter. Many of the residents agreed that the SPE helped them learn and build skills in cultural humility as well as improve care in future patient interactions.While the combination of an adolescent interview and the use of an interpreter can be challenging, it is important as a recent study showed that adolescent refugees commonly have health concerns that require intervention . ResidenThe contribution of perspectives by the local Burmese refugee population of Indianapolis was a huge asset in creating a relevant and realistic scenario to improve the care of refugee and minority populations. In small and close-knit communities, medical interpreters may be known by the patients they work with, which could make having sensitive discussions more uncomfortable for the patient ,14. If tThere are a few limitations to the study. There were a small number of residents who were the lead residents of the SPE compared to the observing residents, and we were unable to compare the survey results of the lead resident to the results of the observing residents, though there is evidence that vicarious learning can be as effective as learning by doing . AdditioOverall, 97% of residents agreed that this simulation helped them build skills in understanding cultural humility and improve the care of future patients. In addition, all residents experienced an increase in comfort in caring for non-English speaking adolescent patients, working with medical interpreters, and conducting both an adolescent interview and a discussion on medical confidentiality. Communication is a critical component of a patient-provider relationship and being intentional in developing trusting relationships with patients helps to improve the overall quality of healthcare they receive.