Service providers may experience difficulties in providing appropriate care to optimize the functioning of individuals with intellectual disability and challenging behaviour. External consultation to identify and address the unmet support needs underlying the behaviour may be beneficial. Applying the multidimensional American Association Intellectual and Developmental Disabilities (AAIDD) model may facilitate this approach. We aimed to describe the content and outcomes of consultation for individuals with intellectual disability and challenging behaviour referred to the Dutch Centre for Consultation and Expertise in relation to the AAIDD model. Interventions were based on the clients’ diagnostic, treatment, and support needs and were categorized according to the five dimensions of the AAIDD model. Outcomes of the consultations were assessed based on reports in the file and rated as ‘clear improvement’, ‘improvement’ or ‘no improvement or deterioration’. In two-thirds of the 104 studied files, consultees were satisfied with the improvement in functioning. Interventions targeted the difficulties of the service providers in supporting their clients and were most often applied within the Health and Context dimensions of the AAIDD model. We may conclude that consultation of an expert team may be valuable to support the care providers, and the use of the AAIDD model may be helpful to address the unmet needs to improve the functioning of individuals with challenging behaviour. Challenging behaviour is defined as ‘behaviour of such an intensity, frequency or duration that the physical safety of the person or others is likely to be placed in serious jeopardy, or behaviour which is likely to seriously limit use of, or result in the person being denied access to, ordinary community facilities’ . Many inBoth externalising behaviours  behaviours, hyperactivity and/or irritability or other disruptive behaviours) and internalising behaviours  may constitute challenging behaviours ,12. IndiThe presence and persistence of challenging behaviours in people with intellectual disability is associated with many factors, such as male sex, a higher degree of intellectual disability and higher care need ,17, commGiven the variety of factors that may lead to challenging behaviours, interventions to reduce these behaviours should be applied from a multidisciplinary perspective, aiming to optimize the individual’s quality of life, including physical and mental functioning, emotional well-being and social participation . An inteThe American Association of Intellectual and Developmental Disabilities (AAIDD)  developeTo use the model among people with challenging behaviours, we operationalised this model by distinguishing three factors of the biopsychosocial model  ,26,27 wiRegarding Context, Olivier-Pijpers et al.  found asEspecially for individuals with serious and/or persistent challenging behaviours and complex problems, it is important to thoroughly assess their functioning on all dimensions in the AAIDD model and to align these with the systems of support and outcomes as described above . HoweverIn The Netherlands, the Centre for Consultation and Expertise (CCE) has been designated by the Ministry of Health, Welfare and Sports to support service providers in providing care for individuals with serious challenging behaviours and complex needs. The CCE may be consulted by healthcare professionals, parents and families who experience difficulties in the assessment, treatment, management or guidance of the challenging behaviours of the individual for whom they care. The care responsibility always remains with the original care provider. The clients of the CCE are individuals with serious challenging behaviours in long-term care, including specialised youth, the elderly, and those under disability and mental healthcare. The CCE performs 1700 consultations per year, of which approximately 650 are for clients with an intellectual disability. After an application for consultation is approved, one of the 60 CCE coordinators is designated to the case. As the core member, the coordinator compiles a ‘consultation team’ from a pool of more than 600 experts/consultants. Usually, a behaviour scientist  is included; many times, a specialist nurse, an intellectual disability physician or a psychiatrist, and sometimes other experts such as a psychotherapist or a physio/sensorimotor therapist are also included. In essence, a consultation team is specifically tailored to the needs of the case. This may be a benefit, but it also has the risk of randomness since consultants may differ in expertise and adherence to professional standards. Nevertheless, in all their consultations, the CCE’s consultants take an integrative and multidisciplinary approach. The starting point is the inability of the clients’ care team to rise to the client’s behaviours that challenge and to find ways to support the team and care providers to find solutions to manage these behaviours and to optimize the clients’ functioning and quality of life. The consultation team considers all factors that may cause or maintain the challenging behaviours, ranging from client factors to contextual factors (a broad view). The client factors include the person’s own, unique story (an idiographic view). The consultation team not only considers facts but also includes the different perspectives  of all persons and bodies/authorities in the client’s social environment (a layered view). Based on the relevant factors from the status, history and context of the client, the team drafts a working hypothesis (an idiographic theory) as the basis for finding leads for the interventions. A consultation often includes a multidimensional method of history taking and observation as well as interviewing of the client in his/her own environment . The available files are studied to investigate whether additional diagnostics are necessary, e.g., a physical examination to complete all personal and contextual information for a broad and layered assessment of the client’s challenging behaviour.Based on the analysis, the CCE makes recommendations on the diagnostic interventions as well as on the treatment/support interventions needed to reduce the challenging behaviour and improve the functioning. The CCE team members may coach the client’s own care team in performing and monitoring the treatment interventions, but they do not perform them directly. Consultants may perform diagnostic interventions themselves when the client’s own care professionals do not have the expertise. This approach may be beneficial in the sense of care teams learning to practise new knowledge. However, there may be difficulties in the implementation of the CCE’s recommendations at the team and/or organisation level as described by Wood et al. , leadingThe CCE has its own specific approach in assessments of challenging behaviour. This approach and their working methods may fit with the AAIDD model because the CCE adds their expertise to the care as delivered by the service providers by addressing the support needs of the individuals with challenging behaviour. Unfortunately, the CCE has no data on the effectiveness of their consultations, and the outcomes are yet unclear. It is also unclear in which specific dimensions the service providers experience difficulties when addressing the support needs of these clients . In the We aimed to study the files of all 274 individuals with a moderate, severe or profound intellectual disability who had been accepted for consultation to the CCE in 2016. Individuals with a moderate, severe or profound intellectual disability and challenging behaviour had a developmental age below 6 years, commonly combined with complex needs. We chose to include consultations that started in 2016, since these were most likely to be finished by the time data collection for this study was performed (in 2021). All eligible files were identified by an administrative CCE employee, and legal representatives of those 274 individuals were sent information letters about the study and asked to consent to the use of the files.Because this was a file study, there was no need for IRB approval according to the Dutch legislations and regulations. Of course, we had to adhere to the Dutch and European laws concerning data protection rules. Therefore, informed consent of legal representatives regarding use of the clients’ file for this study was necessary.We sent letters by mail to the legal representatives of the 274 eligible individuals, providing information about the study. The representatives were informed that data collection would take place by researchers who would adhere to the Dutch and European laws concerning general data protection rules, and that data would be encrypted and analysed anonymously. When the legal representative consented that the CCE file of the person they represented could be used in the study, they were requested to sign and send back the informed consent form.We collected CCE file data on the following characteristics: demographics (age and sex), degree of intellectual disability (AAIDD dimensions I and II), daytime activities (dimension III), somatic and mental comorbidities, including chronic conditions and the types of challenging behaviours (dimension IV) and the living situation . These data were directly provided to the CCE consultants by clients’ healthcare professionals . Commonly, the degree of intellectual disability was based on psychological examination by registered psychologists commissioned by the Centre Indication Care (in Dutch CIZ). Characteristics of the CCE consultations were retrieved from the files, i.e., administrative data and notifications from free text fields and standardized progression and advisory reports of the CCE coordinator and consultants. These included the reason for referral as categorized by the CCE, whether the client had consulted the CCE before , the number of the involved consultants and their professions, the diagnostic interventions the consultants recommended or performed and the treatment interventions they recommended, the duration of the trajectory and the outcome of the consultation. All interventions were monitored by the CCE coordinator and guided or coached by the CCE consultants.The outcomes of the consultation were assessed by the second author in consultation with the first author and were based on the content of progression and advisory reports within the CCE file, which were discussed with the clients’ representatives and professional caregivers and on the CCE coordinators’ notifications in the file. We rated the outcomes as (1) clear improvement ; (2) improvement ; and (3) no improvement or deterioration in behaviour and/or functioning and/or recommended interventions were not or insufficiently implemented and/or consultees’ questions were unsatisfactorily addressed.The diagnostic and treatment/support interventions were categorized by the second author in consultation with the first author according to the operationalized dimensions of the AAIDD model , e.g., tWe computed the frequencies of categorical variables and means of continuous variables for the client  and consultation characteristics . We investigated possible differences in client and consultation characteristics between adults and children/youth with Pearson Chi-square tests and t-tests, respectively. To investigate correlations between client and consultation characteristics, Pearson correlation tests were used for continuous variables.p < 0.1 level were included in a multivariate linear regression analysis to investigate the multifactorial model. All analyses were performed in IBM SPPS Statistics 26. p-values < 0.05 were regarded as statistically significant.Univariate linear regression analyses were used to investigate associations between consultation characteristics and outcomes of the consultation trajectories. Variables associated at the We received informed consent from legal representatives to study 104 of the potential 274 eligible CCE records. Of those, 72 (69%) were adults, and 32 (31%) were children/youth.p = 0.02).The mean number of consultants in the 104 consultations was 2.6 , including the CCE coordinator/behavioural scientist. In 53% of cases, a psychologist was involved; in 14%, a psychiatrist; and in 11%, an intellectual disability physician. Other involved disciplines were case manager (14%), physio/sensorimotor therapist (14%), nurse (10%), social worker (7%), physiotherapist (6%), psychomotor therapist (7%) and systemic/family therapist (7%). More than one-third of the consultations were re-referrals, in children as well as in adults. In the consultations, interviews and history taking were conducted in 75% of the cases, observation and/or video of the clients in their context in 73% and the request for and study of additional files in 66%.Outcomes in two-thirds of the cases were assessed from the files as favourable, i.e., the clients’ functioning had clearly improved and/or the consultees’ questions were satisfactorily addressed by the CCE. In approximately one-quarter, the results were likely favourable, i.e., there was an improvement, but some remaining interventions were needed in which service providers indicated they could implement these recommendations by themselves without the CCE’s support and/or not all questions were satisfactorily addressed, and in approximately 10%, outcomes were less favourable, i.e., there was no improvement and/or the consultees’ questions were unsatisfactorily addressed.Most of the recommended interventions were applied within the dimensions Health and Context. Regarding Health, the treatment of physical disorders included paramedic therapy. Change in prescriptions of medication included change in psychotropics (28%), anti-epileptics (11%) and other medication (10%). Regarding the dimension Context, changes in the microsystem were most often the explanation of the needs of the clients and the training of the caregivers to adapt their guidance and communication style to the needs of their client. Recommended diagnostic health interventions were often re-assessing, expanding or updating the diagnostics of chronic conditions such as pain, epilepsy, sleep and mood disorders; diagnostic context interventions were often the analysis of support needs and systems, communication, staff/client and staff/client’s systems interactions, team collaboration and team support. Recommended treatment health interventions were often medication changes, applying sensorimotor or other body-oriented therapies or adjustments of daily activities. Recommended treatment context interventions were often education of teams regarding the specific symptoms and treatments of psychopathology and/or challenging behaviour of the clients and the training of communication and treatment skills in responding to symptoms and behaviours. Often, multiple diagnostic or treatment/support interventions were applied for one case, sometimes covering various dimensions. Furthermore, diagnostic interventions within one dimension could result in treatment/support interventions within another dimension. For example, diagnosing deafness  resulted in the application of communication aids and training of the client in using these aids, e.g., use of icons (dimension Adaptive behaviour).p = 0.02); education of system in 68% compared with 47% .Some of the interventions were more often applied in adults than in children/youth, i.e., psychotropic drug prescription in 35% compared with 12.5% in children/youth , a social worker more often in the presence of sensory–integration problems , a psychiatrist in the case of affective disorders  and a system therapist and a psychomotor therapist in the case of destructive behaviour .Because we aimed to provide recommendations to the service providers in identifying and addressing the support and treatment needs of the clients with intellectual disability and challenging behaviours, we also investigated the potential relationships between client and consultation characteristics. When comparing groups based on the reason for consultation  and the deployment of education and training to adapt the caregivers’ guidance and communication style to their client’s needs  were associated with better outcomes. Additionally, the advice to stop or to start medication other than psychotropics and/or anti-epileptics and/or to lower or raise the dosage of this medication was associated with worse outcomes . That is, the consultees’ questions were not (or not completely) addressed, and/or there was less or no improvement or deterioration in behavioural and/or overall functioning.These variables were included in a multivariate analysis to investigate a multifactorial model. This analysis showed that the involvement of a psychiatrist as a CCE consultant  for improving the functioning of individuals with persistent challenging behaviours. The reasons for consultation were mainly diagnostic and treatment questions to address the clients’ needs for support and to seek advice for appropriate guidance and living environment. We investigated the consultation questions, content and outcomes in relation to the client characteristics. We used the internationally well-known AAIDD functioning model to categorize the dimensions on which the CCE’s expertise in diagnostics and treatment was targeted as an indication of which clients’ needs were (not) met in their own facility. In addition, the CCE’s interventions of supporting the client’s own caregivers in addressing these unmet needs to improve the clients’  functioning were categorized according to this model.The first important finding of our study shows that the involvement of an expert consultants team for individuals with intellectual disability, challenging behaviours and complex needs seems valuable. We found that consultees, i.e., representatives and professional caregivers of clients, were satisfied with the outcomes of the consultation in approximately two-thirds of the cases, as assessed from the CCE reports and notifications in the file, meaning that the client’s challenging behaviours had decreased and/or their functioning had improved and/or that all consultees’ questions were addressed and clarified. Apparently, external consultation is helpful in improving the identification of all unmet needs related to the client’s challenging behaviour. In almost one-quarter of the consultations, there was improvement, but more interventions were needed to address the clients’ unmet needs, which could be implemented without the support of the CCE, and/or there were some questions that were not satisfactorily addressed.Additionally, our study showed that the CCE approach was in line with the AAIDD model in that consultants had taken a multidimensional and integrative view in their assessments, and the interventions were directed to reducing the challenging behaviour and improving the functioning. The finding that actual diagnostic and treatment interventions or recommendations of the consultants did not cover all dimensions in all cases can be explained by the fact that the consultation team aims to provide case-tailored support, using all diagnostic information that is already available and coordinating the CCE interventions with the care that the clients already receive from their own care professionals. This may explain why the Intellectual functioning and Adaptive behaviour dimensions were not often recommended in diagnostic interventions , likely because this information was already available in the provided files.In addition, the model revealed the specific dimensions where the service providers needed the CCE’s expertise in identifying the client’s unmet needs and to intervene to address the client’s needs for support and/or treatment for optimal functioning. For example, in the present study, more diagnostics were needed in the clients’ healthcare, education of staff in the clients’ context and changes in day-care activities for better social participation. The most frequent diagnostic interventions that were performed or recommended fell within the Health/Physical and Health/Psychological dimensions. This is not surprising based on the high percentages of somatic and mental comorbidities in the sample (80–90%). These comorbidities may interfere with or underly the challenging behaviours. The presence of physical and mental health problems is known to be related to aggressive behaviour ,11,18, wFinally, we found associations between consultation characteristics and the outcomes of the consultations. First, when the intervention was directed at the microsystem to address the individual’s needs and adapt their support and communication style, the outcome was better. Second, outcomes also were better when a consultant psychiatrist was involved. As described by Axmon et al. , a psychAs far as we know, our study is the first to explore the use of the AAIDD model in the care for individuals with intellectual disability. Alford et al.  concludeIn this retrospective file study, we met some limitations which should be considered when interpreting the results of this study. First, the standardised and validated outcome measures of the effect of interventions are missing, and outcomes had to be broadly assessed from information in the files. Second, we had no data on the criteria which were used by the CCE coordinator in the formation of the multidisciplinary consultant team and the decision to close the consultation. In addition, data were lacking regarding the professional standards that were used by the consultants in their diagnostic and treatment/support interventions and how the effects of these were monitored. Additionally, although the CCE consultations may last for several years, there may be risks of shortcomings in sustainably anchoring the implementation of the contextual interventions, such as changes in the working methods, staff education and coaching in the management of challenging behaviours due to the contextual problems of the service providers ,32. FurtA strength of our study was the value for clinical practice and healthcare policies in the care for individuals with intellectual disability and challenging behaviour. The results represent the clinical practice of caregivers and healthcare professionals having concerns regarding the quality of life and  functioning of the person for whom they care and their struggle regarding how to improve these. Our study clearly shows that resources should be sought for an improvement in appropriate healthcare and contextual support.This study shows that involvement of an expert consultant team with individuals with intellectual disability, challenging behaviours and complex needs may be valuable. In two-thirds of the 104 cases, consultants noted that the consultees’ questions were addressed, the individual’s functioning had improved and/or the client’s context had become more adjusted to their needs.The use of the AAIDD model in exploring the content of consultations in our study showed that in assessments, consultants had taken a multidimensional and integrative view. In addition, the model revealed the specific dimensions where service providers had to intervene to address the client’s needs for support and/or treatment for optimal functioning. In particular, contextual and health interventions were often applied. Results suggest that the education and support of staff regarding the communication and guidance of the client are associated with reducing the challenging behaviours and improving the clients’ functioning, even though these are almost never the direct reasons for consultation.We strongly recommend that service providers invest in care teams for clients with challenging behaviours, not just regarding education and training in diagnosis and treatments of (psycho)pathology, behavioural therapies and guidance of these clients but also in team coaching and support. Furthermore, when service providers know which specific professional expertise should be deployed for identifying and meeting these clients’ support needs, they can adapt their personnel policies to provide effective care. However, more studies are needed to investigate which client and contextual characteristics are related to the care pathways these clients should be offered. Building upon our current findings, the next step would be to perform prospective studies with robust methodologies on the effectiveness of the consultants’ interventions and seen in the light of client’s functioning by using the AAIDD model.


Fishing landings in Chile are inspected to control fisheries that are subject to catch quotas. The control process is not easy since the volumes extracted are large and the numbers of landings and artisan shipowners are high. Moreover, the number of inspectors is limited, and a non-automated method is utilized that normally requires months of training. In this work, we propose, design, and implement an automated fish landing control system. The system consists of a custom gate with a camera array and controlled illumination that performs automatic video acquisition once the fish landing starts. The imagery is sent to the cloud in real time and processed by a custom-designed detection algorithm based on deep convolutional networks. The detection algorithm identifies and classifies different pelagic species in real time, and it has been tuned to identify the specific species found in landings of two fishing industries in the Biobío region in Chile. A web-based industrial software was also developed to display a list of fish detections, record relevant statistical summaries, and create landing reports in a user interface. All the records are stored in the cloud for future analyses and possible Chilean government audits. The system can automatically, remotely, and continuously identify and classify the following species: anchovy, jack mackerel, jumbo squid, mackerel, sardine, and snoek, considerably outperforming the current manual procedure. In 2020, the Food and Agriculture Organization (FAO) estimated the global production of aquatic animals to be 178 million tons, recognizing the essential contribution of the fisheries and aquaculture sectors to global food security and nutrition [To prevent a critical condition, the monitoring and control of fish landings and catch quotas in Chile is overseen by the Fisheries and Aquaculture National Service (Sernapesca). Sernapesca’s role is to execute the national fisheries policy and oversee its compliance, and, especially, to ensure the proper application of legal and regulatory norms regarding fishing, maritime hunting, and other forms of exploitation of hydrobiological resources . ContrarFocusing on the main challenges and research gaps that need to be addressed in the field of smart aquaculture, such as recognition, measurement, tracking, and classification, a couple of studies have presented overviews of proposed techniques and approaches by bridging the gap between solutions developed in academia and the practical requirements of the fishing industry ,6. For iAdditionally, there are some further investigations that align closely with the objectives of this paper. Patent number CN214282791U presented a system that identifies and counts fish species passing through a water tube using a camera . Patent In this paper, we present a fish recognition system based on deep convolutional neural networks. The proposed system can automatically, remotely, and continuously identify and classify different Chilean pelagic species in real time, as well as estimate their size. It considerably outperforms the current manual procedure carried out by the Sernapesca inspectors.The rest of this paper is organized as follows. In The proposed system for the detection, classification, and size estimation of pelagic species is composed of seven main modules, including both hardware and software components. The architecture of the system is illustrated in To implement the fish recognition system installed on a conveyor belt in fishing plants, an optomechanical device was designed. The main component of the device is a gate that consists of a stainless steel structure, two RGB cameras, flicker-free LED panels to avoid visual flickering problems in the cameras, and a ventilation system.Two versions of the gate were designed and implemented. The first version has four LED panels distributed around two Hikvision 2MP IP cameras (model DS-2CD2721G0-IZS), which operate in the visible spectrum. The connection to the cameras can be established through HTTP and RTSP protocols, and management and monitoring can be performed using Hikvision’s control software. This software allows the extraction of video feeds with a variable resolution, capture rate, bitrate, and other user-modifiable characteristics. The model selected for the cameras in the design of the second gate was the Hikvision DS-2CD1653G0-IZ. This 5MP model can operate in low-light conditions, and the field of view can be conveniently zoomed in or out according to the size of the species to be classified. This version of the gate has a single LED panel located in between the two cameras. The first design version of the gate was installed in an industrial fishing plant in south-central Chile, which we named Plant 1, whereas the second design version of the gate was installed in a different plant with conditions similar to those of Plant 1, which we named Plant 2, also in south-central Chile. Data capture was performed remotely by establishing a direct connection from an external computer to the cameras installed on each gate. For Plant 1, the captures consisted of images with a resolution of Engraulis ringens), jack mackerel (Trachurus murphyi), mackerel (Scomber japonicus), and sardine (Strangomera bentincki) belonging to Plant 1, and jack mackerel, mackerel, jumbo squid (Dosidicus gigas), and snoek (Thyrsites atun) belonging to Plant 2. The final number of labeled samples for each species and for each plant is summarized in The captures were manually reviewed for the presence of accompanying fauna, which were caught together with the target species and can either be exploited or discarded. The free access platform, Roboflow, was used to tag the images . Expert To address the challenge of identifying and labeling fish species that were overlapping or present in large numbers within the same image, two image processing techniques were used. The first technique involved applying blurring to the image background while preserving the labeled species, effectively removing unidentified spots. The second technique randomly selected an image from a collection of several pictures showing sections of an empty belt, replacing areas of the original image that were not labeled. In this way, the unlabeled fish were removed, and by replacing parts of the image with a segment of the empty belt, it allowed the model to learn the differences between a fish and an empty belt. These techniques were randomly applied with an equal probability for each image in the database. Examples of modified images using these techniques are shown in Finally, data augmentation techniques were applied to improve the model’s ability to detect fish, and, especially, to recognize the accompanying fauna, which has a low probability of occurrence in a common fish landing. The data augmentation techniques used included horizontal and vertical flips, maximum 30-degree rotations, brightness and contrast changes, noise addition, and blurring.The inference preprocessing module consists of three main functions that are applied prior to the detection and classification models. Firstly, the color composition format of the images is transformed from BGR to RGB. This conversion is necessary because OpenCV, the image processing library, uses BGR format. Secondly, the images are resized using a letterboxing algorithm, ensuring that the original aspect ratio is preserved while adjusting the resolution from For the development of the fish detection and classification system, several convolutional neural network models were utilized, including YOLOv4, YOLOv7, and Mask R-CNN. The choice of these models was based on the distinctive features of their architectures and their specific capabilities to detect objects in images.YOLOv4, which stands for ’You Only Look Once’, is an object detection model that uses bounding boxes to tightly enclose and associate a class label for objects of interest within an image, all within a single-step neural network architecture . This model was initially chosen for its high inference speed, which is particularly well suited for real-time object detection and processing. However, due to its reliance on bounding boxes, YOLOv4 faced challenges in accurately classifying fish species with overlapping features.Mask R-CNN focuses on a different approach known as instance segmentation. This model goes beyond bounding boxes and provides detailed object segmentation, creating masks or polygons, which are pixel-level structures that delineate the exact shape of each detected object. This segmentation approach offers rich and detailed information about the objects, which can be especially valuable when dealing with fish species with overlapping appearances. However, its inference speed is considerably slower than any YOLO network, reaching rates of 1 to 2 FPS using an Nvidia A100 GPU in Google Colab .With the release of YOLOv7, a new model emerged that combined the benefits of obtaining mask-like information similar to Mask R-CNN but with a significantly faster inference speed that outperformed YOLOv4. Consequently, YOLOv7 emerged as the most suitable choice among the evaluated models .The hyperparameters employed for the YOLOv7 model were as follows: an initial learning rate of The performance of the model was measured using the following metrics: precision, confusion matrix, macro-average precision, and mean average precision. The latter two are explained in this subsection.The macro-average precision is the average precision calculated across all classes or categories in a multi-class classification problem. It gives equal weight to each class without considering class imbalance. The macro-average precision is calculated by taking the mean of the precision values for each class.The mean average precision is a commonly used performance metric in object detection tasks. It measures the average precision across multiple classes and different levels of prediction confidence thresholds. The mAP summarizes the precision–recall curve by calculating the area under the curve (AUC) and provides an overall performance score. It is calculated as the mean of the average precision (AP) values for each class.The weight of each species was estimated through a relationship with its length given byW, in grams, and the fish standard length, L, in centimeters, incorporating two parameters denoted as a and b. It is important to note that these parameters can vary depending on factors such as the geographical location, season, and other variables specific to each fish species. Consequently, the estimations may differ from year to year and across fishing grounds. Equation  presentsTo implement the processing algorithms related to the proposed system, a web user interface was developed based on the Laravel Framework, which incorporated a number of benefits in terms of security that are relevant to industrial environments. Additionally, Python 3.7.x was utilized for programming the preprocessing, postprocessing, and sorting algorithms.In this interface, an algorithm running on a server continuously monitors the cameras installed on the gates. It utilizes a CPU version of the YOLOv7 model specifically trained for the corresponding plant to automatically detect the presence of fish. The inference information, which includes a timestamp, the length, weight, model used, gate name, plant name, and other pertinent details, is then uploaded to a separate server’s database. The postprocessing algorithm incorporates three modules. The first module is responsible for discarding detections based on their size, allowing for more precise filtering of the results. The second module implements a multiclass non-maximum suppression algorithm (NMS), which helps eliminate redundant or overlapping detections. Lastly, the third module is responsible for drawing the resulting bounding boxes of each detection on the original image. It also includes the predicted label and confidence level, providing visual representations and informative annotations. Explained in more detail, the module for discarding detections specifically focuses on two scenarios: when a sardine or an anchovy exceeds the threshold of the average size  and when a jack mackerel or mackerel falls below the threshold of the average size . By identifying these instances, the module effectively filters out detections that meet these size conditions for both cases, ensuring that only fish within the expected size ranges are considered valid. By discarding abnormal detections, the system improves the accuracy and reliability of the subsequent processing and analysis steps.The module for the multiclass NMS plays a crucial role in optimizing the detection results. It iterates over all the bounding boxes detected and checks for close proximity between boxes of different classes. If two bounding boxes are found to be very close to each other, the module eliminates the box with the lower confidence level. This step ensures that only the most confident and distinct detections are retained, preventing redundancy and improving the overall accuracy of the system.Once the valid bounding boxes have been determined by the previous modules, they are visualized in the original image using predefined unique colors assigned to each fish class. Additionally, the classification model’s confidence level for each detection is displayed alongside the bounding box and label, providing a clear and intuitive understanding of each detected fish species.Finally, the system includes a data storage module that facilitates the organization and management of the processed data. This module includes the delivery of the estimated size and weight of each detected fish, along with a comprehensive summary of all processed data. The system generates files in Excel and PDF formats, allowing for convenient access and analysis of the collected information. In the web user interface, users have the option to select specific fish landings and view detailed reports containing statistics and graphs related to the processed data.The trained models, as described in For Plant 1, the model was evaluated on 752 fish samples. The results obtained are summarized in the confusion matrix in The models for this plant were trained using the Google Colab platform, with a total time of 1.358 h to complete 150 epochs in training, using an Nvidia A100 GPU. The inference time obtained while processing a whole image was 18.5 ms, which corresponds to a frame rate of 54 FPS.For Plant 2, the model was evaluated for the detection of jack mackerel, mackerel, jumbo squid, and snoek using a total of 1771 validation samples. The validation results are summarized in the confusion matrix in The precision–recall curve of the model in this plant is shown in The models for this plant were also trained using the Google Colab platform, with a total time of 1.6 h in completing 150 epochs in training, using an Nvidia A100 GPU. The inference time obtained while processing a whole image was 18.5 ms, which corresponds to a frame rate of 54 FPS.In terms of model performance, the results from Plant 1 indicate that the accuracy for larger species was generally higher. This can be attributed to the fact that the cameras are capable of capturing greater detail and distinguishing the characteristics of larger fish species more effectively compared to smaller ones. In In The results obtained from Plant 2 highlight the challenges in snoek detection, as visually distinguishing snoek from mackerel and jack mackerel was not straightforward from our imagery. Nevertheless, jumbo squid was easily recognizable by the system due to its large size and distinctive color, making it stand out compared to other species.In In terms of practical considerations, when using YOLOv7 for real-time classification of fish species with varying sizes, there is a delicate balance between the frame rate and image resolution. In our case, we adjusted the frame rate to synchronize with the conveyor belt’s speed, ensuring that the same fish did not appear in two consecutive images. This simple optimization allows for the efficient utilization of computing resources to process multiple images simultaneously.Furthermore, image resolution plays a crucial role in distinguishing smaller or similarly-sized species such as sardine or anchovy. We decided to maintain YOLOv7’s default input image resolution of As shown in the results, the system allows for the identification of species with high accuracy. Nevertheless, there are certain inherent limitations in the methodology. The system can only detect species on the top layer, is sensitive to overlapping objects, and fails to classify fish in a deteriorated state. Additionally, some environmental sources of error such as intense sunlight can cause pixel saturation, as well as humidity conditions, which may result in fogging, requiring the system to be cleaned by plant operators.In this work, we have presented a computer vision system for fish detection, classification, and weight estimation, fine-tuned for two different landing plants of Chilean pelagic fish. The obtained results demonstrate the system’s ability to detect and distinguish different species, as well as the challenges associated with certain species that exhibit visual similarities and the limitations in capturing them completely in a single image.The implementation of the system represents a significant improvement compared to the current inspection procedures, providing an automated method for the identification and estimation of the size and weight of fish. The system is able to provide more accurate and reliable fish landing traceability to fisheries management agencies, which could contribute to the sustainability of marine resources and the long-term viability of the fishing industry. Further work includes extending the current database to incorporate new marine species, as well as improving the performance of the weight and length estimation module.


Since the withdrawal of government forces from Northwest Syria due to the conflict, several national initiatives have aimed to create alternative governance approaches to replace the central governmental system. One of the recent initiatives was the formulation of so-called ‘Central Bodies’ as institutional governance structures responsible for thematic planning and service provision; for example, the referral unit is responsible for planning and delivering medical referral services. However, the governance and administrative rules of procedures of these bodies could be immature or unsystematic. Assessing the governance of this approach cannot be condoned, especially with the urgent need for a methodical approach to strategic planning, achieving strategic humanitarian objectives, and efficiently utilizing available resources. Multiple governance assessment frameworks have been developed. However, none were created to be applied in protracted humanitarian settings. This research aims to assess the extent to which the existing health governance structure  was capable of performing the governance functions in the absence of a legitimate government in Northwest Syria.A governance assessment framework was adopted after an extensive literature review and group discussions. Four principles for the governance assessment framework were identified; legitimacy, accountability and transparency, effectiveness and efficiency, and strategic vision. Focus Group Discussions were held to assess the levels of the selected principles on the governance thermometer scale. Qualitative and quantitative data were analyzed using NVivo 12 and SPSS 22 software programs, respectively.The level of the four principles on the governance thermometer scale was between the lowest and middle quintiles; ‘very poor or inactive’ and ‘fair and requires improvement’, respectively. The results indicate that the governance approach of Central Bodies in NWS is underdeveloped and summons comprehensive systematic development. The poor internal mechanisms, poor planning and coordination, and the absence of strategic vision were among the most frequent challenges to developing the approach.Humanitarian actors and donors should pay more attention to health governance approaches and tools in protracted crises. The central bodies must improve coordination with the stakeholders and, most importantly, strategic planning. Establishing or utilizing an independent planning committee, with financial and administrative independence, is crucial to maintain and improving contextual governance mechanisms in Northwest Syria. The Government of Syria GoS has relinquished many areas in Syria as a result of the war against the various military factions since 2011 . Many huThe health system governance in Syria is collapsed and fragmented due to the multiple power of control in the region and the absence of a central national system , 7. SincEstablishing a quasi-state health governance structure in NWS encouraged donors to support the HDs . Many inFinancial support has come from multiple donors. For example, World Health Organization (WHO) supported an integrated approach to service delivery in NWS by funding the referral network of Harim, Idleb  . DHIS waThe bottom-up development of the current governance system of central units in NWS resulted from the necessity to respond to the health needs of affected communities . RelevanAccording to Brinkerhoff and Bossert, governance in health systems is the process of developing and implementing effective institutional rules for policies, programs, and activities related to fulfilling public health functions in order to achieve health sector objectives . AbimbolA systematic assessment of governance, as one of the health system's building blocks, is essential to influencing the system's performance . AlthougIslam (2007) argued that health governance is based on the World Governance Indicators (WGI) and health determinants . (WGI) wThe development of health systems in contexts of protracted conflict is usually unsystematic, lopsided, and of an arbitrary nature, determined by certain factors that vary according to the context . In addiThis study aims to assess the health system governance in NWS, which has been impacted by a violent war, outbreaks, collapsed infrastructure, and a lack of resources for over a decade . In lineOne of the workshop's objectives was to extract governance assessment principles based on the participant's understanding of the research concept; health system governance assessment. Therefore, contextualized scientific knowledge of the research concepts was developed on the first day through interactive sessions on the previous and current health governance initiatives and available governance assessment mechanisms in NWS. In consonance with the participants' feedback and inputs, four thematic principles were deduced to assess the health system governance; legitimacy, transparency and accountability, effectiveness and efficiency, and strategic vision. Later, the research team identified and adapted relevant and context-specific definitions and indicators for these principles in accordance with the reviewed literature. A scale of 1 to 10 was suggested to measure the functionality of the four principles, which was converted to a percentage and reflected in a governance thermometer scale of 0% (very poor) to 100% (excellent) . For thiOn the second day, the definitions of the four selected principles were presented to the attendees for in-depth discussion from a scientific perspective. Four Focus Group Discussions FGDs, one for each of the selected central bodies, were conducted to assess the health system governance of the central bodies approach in NWS based on the four principles and relevant definitions and indicators. The invitees who accepted to join the FGDs had to sign a consent form. All the consent forms were stored in the King’s College archive and accessible only by the principal researcher. The participants were divided into the FGDs based on their relevant experience, area of work, and educational background. The participants were asked to provide a quantitative measurement of the level of functionality of the health system governance against each of the four principles for the selected central bodies based on the governance thermometer scale. Semi-structured questions were administered later to allow the participants to present qualitative justification for the given level of functionality.Data were anonymized and transcribed in Arabic, which was translated into English later by an official translator. Qualitative and quantitative data were analyzed using NVivo 12 software and SPSS statistics software v22, respectively.https://doi.org/10.7910/DVN/K0A252.Research framework, transcripts, definitions, questionnaires, written consent form, ethical clearance, and data analysis extractions are available at A total of 24 individuals from multiple entities participated in the discussion. The participants were from NGOs, donors, SIG MoH and HDs, and central bodies. Each FGD was divided into four main sessions relevant to the adapted health governance assessment principles. While all the participants have Syrian nationality, most live either in Turkey or Europe. More than 80% of the participants were physicians in senior positions (manager or coordinator). It is worth mentioning that all the participants were males, although the invitation to the workshop was circulated to a broad spectrum of NGOs, local authorities, and UN agencies, which might reflect gender imbalance in the health sector in NWS.Health system governance legitimacy was defined as the belief that a rule, institution, or leader has the right to govern. It is an individual judgment about the rightfulness of a hierarchy between the ruler and the subordinate’s obligations toward the rule or ruler . In the The majority of the answers about the legitimacy of the central bodies approach were on the 3rd and 4th quintiles on the thermometer scale Table . While 3“There are three sources of legitimacy: NGOs, WHO, and the health cluster, besides the willingness and possibility to support HIS unit, and donors who have the power to impose cooperation with the HIS on their implementing partners.”When the participants were asked about the challenges to improving legitimacy (multiple answers per participant), the most frequent challenge (23%) was ‘competition and the lack of unification across the health sector’. Competition refers to the negative contest between NGOs for financial support. Other frequent challenges were ‘the weak cooperation by NGOs with the central bodies’ and ‘weakness in the internal system or operational model and project design’.Table When the participants were asked about the institutional factors that drive more legitimacy to the central bodies' governance approach, it was found that cooperation with SIG MoH and its HDs, WHO and the health cluster, and NGOs was the most important driver to legitimize the current health governance approach in NWS. Quality of services and products was one of the most frequent factors contributing to legitimizing the central bodies, according to the participants. Figure Transparency and accountability can reduce the risk of corruption and unethical behavior while increasing public trust in government institutions , 60]. T. T60]. Tμ ≈ 30%) (Table Almost 66% of the answers were on the 1st and 2nd quintiles of the governance thermometer scale, referring to an inactive or poor accountability mechanism within the central bodies mean μ ≈ 0% (Table“There is a lack of clarity in the administrative structure and the decision-making mechanism, which created challenges in the governance of the central system, which is supposed to support the health sector governance.”The answers of the participants were based on their practical experience in coordination and work with central bodies. Most of the participants debated how the weak accountability and transparency mechanism has caused challenges associated with administrative and field coordination between the NGOs and central bodies.“The low turnover rate of the position for a long time is one of the central bodies weaknesses.”“The head of the central body is accountable to the provincial health directors. However, none of them can terminate his contract or hold him accountable.”Along with the inactive or poor accountable governance system in the health sector, the participants mentioned various challenges preventing the health sector in NWS from building a rigorous accountability and transparency mechanism. Among these challenges Table , ‘weakne“By comparing the inputs to the outputs and observing whether the best methods were used to reach the goal, I can say that perhaps the best efforts were made but not the best performance. Knowing what resources were made available to the central bodies and understanding the primary goal is necessary.”Effective and efficient governance is critical to the well-being of any country . EffectiIn fact, 75% of the participants pointed out that the current mechanism is either inactive or requires significant improvement.The challenges to enhancing the system's effectiveness and efficiency Table  were mai“Health governance is absent in SBOMS. There is no future vision of the goals, strategic planning, and accountability system.”“The central bodies must develop a strategic vision of the health system in Syria.”According to , strategμ ≈ 12%.When participants were asked if there was a clear strategic plan and engagement with organizations and stakeholders Table , 96% of Based on the participants' views, ‘strategic planning and increasing sustainability and efficiency’ is the most crucial way to support the central bodies' approach in NWS for sustainable services, especially during the health system recovery phase Fig. .Fig. 3NW“The central units should be more efficient in investing resources, especially in light of the lack of resources. Thus, improving efficiency is key to marketing this approach and convincing donors to support the central projects. Additionally, service quality and performance should be enhanced.”Other ways to support the current governance approach in NWS were ‘develop meaningful partnerships with NGOs and stakeholders’, ‘enhance the quality of services and products’, and ‘attract more resources’.The research aims to explore and assess the existing health system governance in NWS by applying an adapted framework assessment after an extensive literature review of the relevant literature. In fact, all of the reviewed framework assessments were limited to stable states and systems. Therefore, an assessment framework was deduced based on the research team's contextual understanding of the current NWS governance system within the scope of the reviewed literature through a two-day workshop in Turkey. During this workshop, participants from various institutions presented detailed explanations of the historical brief of the current health sector governance system. The workshop also reviewed the current experiences of the so-called central bodies and their governance mechanisms. Group sessions with participants followed these activities to assess the governance of central bodies based on the deducted assessment framework. The governance assessment framework principles were legitimacy, transparency and accountability, effectiveness and efficiency, and strategic vision.The research assessed the level of each of the four principles on the health governance thermometer scale Fig. . The legAccording to the central bodies' management, the accountability and transparency mechanism is immature and not appropriately documented. This is confirmed by the fact that the turnover rates in the central projects' managerial positions are almost non-existent. Nonetheless, activating accountability mechanisms is not an independent procedure. It entails changing dynamics, assigning roles and responsibilities, engaging communities meaningfully, and developing an inclusive strategic vision –68. MoreCentral projects represent an innovative approach to health governance in chronic conflict settings where health governance is generally neglected. Delaying governance support during emergencies could be of disastrous impact on service delivery and quality control. Humanitarian actors and donors should pay more attention to health governance approaches and tools in protracted crises to enhance resource utilization effectiveness and efficiency. Besides improving the coordination with all stakeholders, accountability mechanisms, and efficiency, central bodies must concentrate on strategic vision and planning. Due to the lack of resources, shifting to strategic planning might be at the expense of service delivery. Therefore, formulating a committee for this purpose with financial and administrative independence is crucial at this stage for strategic planning and comprehensive improvement in the health system governance in NWS. This research was silent on the health economics aspects of the governmental structure in NWS. Therefore, pursuing further research to investigate and study the cost efficiency of this approach is recommended to complement and support advocacy for health governance in conflict settings.


The emergence of the new WHO classification standard in 2021 incorporated molecular characteristics into the diagnosis system for meningiomas, making the diagnosis and treatment of meningiomas enter the molecular era.At present, there are still some problems in the clinical molecular detection of meningioma, such as low attention, excessive detection, and a long cycle. In order to solve these clinical problems, we realized the intraoperative molecular diagnosis of meningioma by combining real-time fluorescence PCR and AIGS, which is also the first known product applied to the intraoperative molecular diagnosis of meningioma.We applied AIGS to detect and track a patient with TERTp mutant meningioma, summarized the process of intraoperative molecular diagnosis, and expounded the significance of intraoperative molecular diagnosis under the new classification standard, hoping to optimize the clinical decision-making of meningioma through the diagnosis and treatment plan of this case. Meningiomas have the highest incidence rate (39%) among all primary intracranial and central nervous system tumors. According to a report released in 2021 by the Central Brain Tumor Registry of the United States, the annual age-adjusted incidence rate of meningiomas in the United States (US) was 9.49 per 100,000 population in 2014–2018. The incidence increases with age, with a strong increase after the age of 65 years . The WHOOn 23 March 2022, a 54-year-old male patient was treated for half a year due to paroxysmal headache. MRI and MRV examinations were performed on the same day, which showed that there were solid space-occupying lesions near the right frontal midline that were closely related to the superior sagittal sinus, mild compression of brain tissue, and local skull invasion –E. AccorSince it is clearly pointed out in the 2021 WHO classification standard for meningiomas, regardless of its histological diagnosis of grade 1, grade 2, or grade 3, as long as there is a TERTp mutation and/or CDKN2A/BB homozygous deletion, it is defined as WHO grade 3 . TherefoP < 0.0001; Meningiomas are mostly benign tumors and grow slowly. However, some meningiomas relapse, often accompanied by an improvement in grade; most of these meningiomas have specific gene mutations . Many stAs a result, understanding how to accurately grade meningiomas using molecular detection is critical, as it not only affects patients’ follow-up adjuvant treatment plans but also predicts their survival and prognosis. At present, the mainstream detection method in the market is NGS, but in the actual clinical work, it is found that the average time of this detection is 10 days, and the results cannot play a role in the intraoperative surgical decision-making. In the guidelines for the diagnosis and treatment of meningiomas issued by the European Association of Neuro-Oncology EANO; , it is sEANO clearly stated in the guidelines for the diagnosis and management of meningiomas that molecular diagnosis of meningiomas is strongly recommended, which is not only related to accurate classification but also plays an important role in the treatment decision of meningiomas . At presThe detection time is a critical factor in the surgical process. Even though we can complete the detection in 1 h, strict surgical procedures may have an effect on the process. As a result, we have upgraded the next generation of AIGS products to further reduce detection time (within 35 min), and the sample size for synchronous detection has been expanded (16 detection channels) to meet different surgical needs while minimizing the impact on the surgical process. As a case report, this study cannot provide a clear conclusion on the level of evidence-based medicine, which would necessitate increasing the sample size and conducting long-term follow-up to assess prognosis. In addition, our team is conducting research in this area.In this case study, AIGS real-time fluorescence PCR was used for intraoperative molecular diagnosis of TERTp mutant meningioma. As the first product applied to intraoperative molecular diagnosis of meningioma, it has important pioneering significance. Through this technology, TERTp mutation can be accurately judged during operation, allowing us to adjust the operation plan in real time, optimize the treatment strategy, and provide important evidence support for intraoperative targeted treatment in the future. Finally, we strive to improve the survival and prognosis of patients.Now is the 10th month after the operation. The patient came to the clinic for re-examination. From the imaging performance, the patient recovered well without any sign of recurrence. The patient was very satisfied with the surgical results and expressed his affirmation on the application of intraoperative molecular diagnosis and judgment technology to the determination of meningioma nature. Finally, the patient was also very happy to help more people with his diagnosis and treatment through case sharing.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.Ethical approval was not provided for this study on human participants because this study does not interfere with the normal diagnosis and treatment of patients. As a case report, it is important to record the whole diagnosis and treatment process of patients. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.HX and GL designed and concepted of the study. ZH drafted the manuscript. HX revised the manuscript. HL, XL, DJ, KZ, and SN analyzed and interpreted of the data. ZH, HC, QW, and ZF played the role in the acquisition of data. All authors contributed to the article and approved the submitted version.This work was supported by the research on the future application prospect of classical gene marker Kit (contract no. 6010122006), Key Clinical Research Project of Clinical Research Center of Shandong University (2020SDUCRCA011), and Taishan Pandeng Scholar Program of Shandong Province (no. tspd20210322).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Alzheimer's disease (AD) is the most prevalent form of dementia, accounting for 60–80% of cases. Although initially described more than 100 years ago, the pathogenic mechanisms underlying AD are very complex and remain poorly understood. The accumulation of amyloid plaques and neurofibrillary tangles is the key histopathological hallmark of the disease. The amyloid cascade, in which the accumulation of Aß peptides results from their overproduction or decreased clearance, has been shown to be an early event in AD and has thus been the focus of intense research. However, years of clinical failures prompted the emergence of alternative hypotheses that are not mutually exclusive.Remarkably, genetic studies have highlighted the important role of glial cells, which are now recognized for their multifaceted contribution to maintaining neuronal health and function, in the pathogenesis of AD. As a result, an important area of investigation revolves around the intricate interplay between microglia, glia, and Alzheimer's disease, along with other related dementias. Unraveling the precise impact exerted by glial cells on the progression of AD is challenging. Among the glial cells, microglia have received significant attention due to their potential involvement in the pathogenesis of Alzheimer's disease. In fact, it has been postulated that microglia may have a dual role in the pathogenesis of the disease: they are protective in the early stages, while they drive synaptic loss and neuroinflammatory/neurodegenerative processes later on Hansen et al. . The othTherefore, there is a pressing necessity for a comprehensive exploration to elucidate the relationship between glial cells and Alzheimer's disease. Our aim with this Research Topic was to provide a critical evaluation of the state of research in the field of glial cells and Alzheimer's disease.Elsworthy et al. have nicely summarized the current literature on the potential involvement of astrocytic ADAM10  in AD pathology and underscored the need for additional evidence to further comprehend the multifunctional role of these glial cells during disease progression. Continuing with the involvement of astrocytes in AD, the opinion paper by Milinkeviciute and Green not only dives into the role of clusterin (CLU) (mainly expressed by astrocytes) in Alzheimer's disease but also highlights the necessity for novel and improved models focusing on the different CLU isoforms in order to elucidate the function of this genetic risk factor for AD. Interestingly, Bonaterra-Pastra et al. performed a multicentric cohort study and showed that various CLU SNPs were associated with several Cerebral Amyloid Angiopathy (CAA) markers. They also observed an association between CLU SNPs and APOE protective genotypes with higher levels of ApoJ and ApoE in circulating lipoproteins, supporting the important role of ApoE/J in cerebral β-amyloidosis. Both CLU and APOE are important factors in the transport and metabolism of lipids (including cholesterol). In the brain, they may also modulate Aß aggregation and deposition. In this vein, Sharp et al. explored the interesting hypothesis that white matter injury, which is recognized as an important component of AD neuropathology, may contribute to cholesterol dysmetabolism, thereby increasing Aß deposition, which in turn may lead to white matter lesions, setting off a vicious injury cycle. The Blood-Brain Barrier (BBB), which is meant to protect the brain from systemic blood circulation, is another brain component that is affected in the early stages of AD. After reviewing known BBB dysfunction in AD, Sousa et al. highlighted how it may represent both a therapeutic target and a therapeutic vehicle in the treatment of the disease.In addition to the key role of microglial cells during the onset and progression of Alzheimer's disease, there has been recent interest in unraveling the role of astrocytes in neurodegenerative diseases. Although it is now well-established that astrocytes are essential for maintaining brain homeostasis and that astrocytic dysfunction contributes to the pathogenesis of AD, the specific mechanism remains elusive. In this context, Because AD affects one of humanity's most important abilities—the ability to reason—and because the management of the disease will weigh even more heavily on our economies in the years to come, the need for effective treatments that can halt or even slow the disease is becoming ever more pressing. Exploring alternative hypotheses and integrating them with current knowledge is both a challenge and an opportunity.AG-A: Writing—original draft, Writing—review and editing. HH: Writing—original draft, Writing—review and editing.


Adopting change is something that is often resisted, as is often the case in the adoption of electronic health records (EHRs) in healthcare organizations. Embracing this will require computer knowledge to handle the system for the management of patients and their care. This study aims to determine the computer skills required for the uptake of electronic health records (EHR) by healthcare workers in an annex of the state teaching hospital, Okela Health Centre (OHC) Ado-Ekiti. The study uses a cross-sectional research design with a structured questionnaire distributed to 30 healthcare workers across seven disciplines working in the hospital. Descriptive statistics of frequency tables and percentages were used to ascertain the relationship between computer skill usage and the adoption of EHR. The majority of respondents were only efficient in Microsoft Word (MW), email, and WhatsApp, with efficiency rates of 63.4%, 76.6%, and 73.3%, respectively. The majority were not efficient in Microsoft Excel (ME) and Microsoft Access (MA), at 56.7% and 70%, respectively. Computer appreciation is an important basis for the adoption of EHR in hospitals. The healthcare data stored as electronic health records need to be updated from time to time. Patient information, such as previous history, must be readily available anytime and anywhere to support treatment. Such stored information requires highly skilled manpower with information communication and technology (ICT) which must be continuously maintained. The healthcare organization is required to manage the right of access to the data alongside its retrieval and any communication .Several data are generated from the activities of healthcare workers in the process of patient management. These must be stored and processed in an efficient way to allow for quick access and dependable storage of the information . The worDespite the great benefits, many hospitals are yet to embrace EHRs in the management of their patients. In research of the primary factors that affect healthcare professionals’ willingness to adopt an EHR system, computer literacy was discovered to be one of them . HealthcThe factors that affect the adoption of EHRs include attitudes toward EHRs, perceived usefulness, perceived ease of use, social influence, computer self-efficacy, potential threat to physician autonomy, and confidentiality concerns.Attitude Toward EHRsThis refers to a patient’s positive or negative feelings about engaging in the desired behavior. One’s mindset toward using technology is a critical indicator in the technology acceptance/adoption model. In implementing an EHR system, effort must be concentrated on developing peoples’ attitude towards its use .Perceived UsefulnessThis is the extent to which people believe that adopting an EHR system will increase their job performance .Perceived Ease of UseThis considers whether individuals believe that using the system will require less effort. According to TAM, user satisfaction is a significant component in both attitudes toward technology use and its perceived benefits .Social InfluenceThe influence of peers and colleagues regarding the use of a system significantly affects the number of people who may then go on to use it. If a person believes that individuals who are significant to him or her are using the system, his or her involvement is likely to be swayed toward its adoption. Coworkers and peers, as well as top management, are examples of people who can have a social influence on healthcare teams’ acceptance of EHR systems .Computer Self-EfficacyThe ability to use a computer quite well determines his/her efficacy. Healthcare providers who have high computer self-efficacy are more likely to use EHRs than their counterparts who do not. As technology advances, it becomes necessary for healthcare providers to be computer compliant, as this has become a requirement for employment in several organizations. Following that, a constant on-the-job training program can be planned to refresh people’s computer knowledge prior to EHR implementation to boost its acknowledgement .Potential Threat to Physician AutonomyPhysicians are distinguished by their high level of professional independence. This is when an individual assumes that by employing a specific system, he or she would lose control over the circumstances, methods, procedures, or content of his or her work, which is untrue. Though opposition is likely due to the significant changes occurring in EHR implementation, which may influence leadership roles or power dynamics in medical practice, this should not influence their choice to utilize EHRs .Confidentiality ConcernsIt is a source of wider issue, especially in developing countries, that EHRs could be accessed by unauthorized persons. Some individuals are concerned about the confidentiality of patient information, which is one of the reasons they are hesitant to adopt EHRs . Having During research on the implementation and feasibility of an electronic health record-integrated patient-reported outcomes symptom and needs monitoring pilot in ambulatory oncology, an EHR system was discovered to be a helpful technique for patient maintenance and appointment reminders. Patients received a reminder via their patient portal to complete an assessment on Epic MyChart. Epic MyChart is a tool used to complete assessment through a previously stated preferred mode . Evaluations were accessible in English and Spanish and took approximately 8–10 min to complete through the patient’s MyChart account (web or smartphone app). Patients were instructed to finalize these evaluations 72 h prior to their next appointment. Without adequate knowledge of healthcare staff on computer use, this may result in missing appointments which could have been corrected through messages, emails, and calls to the patients at least 72 h before the appointment. There is also a possibility of work overload as staff will be forced to do this on behalf of patients at their walk-in time .Another effect of poor implementation of EHRs on patient care management is waste of resources. Some institutions committed to implementing an EHR system financially no matter how small its use may be, hence the need for effective use to prevent a waste of resources. Sustainability of the system is imperative and may be ensured through the training of healthcare professionals, a change of attitude, and the right mindset on the part of end-users .Automated clinical data generated for policy making, disease incidence definition, and care outcomes will be disorganized, thereby forfeiting the impact of EHRs on patient care management .The issue of training cannot be overemphasized. Khan S.Z et al. (2012) opines that EHRs will not be effective if there is no necessary training. The technical complexity involved in the use of EHRs demands a high level of technical competency on the part of the healthcare provider in order to prevent information use from becoming a burden when the EHR system is put in place. This also applies when considering poor preparation and use of data .Having considered the various factors affecting the adoption of EHRs, there is a need to highlight the aim of the study, which is to determine the need for computer skills as a determinant in the adoption of EHRs in Okela Health Centre (OHC), an annex of Ekiti State University Teaching Hospital Ado-Ekiti, in southwest Nigeria.Adopting EHRs, as with other technologies, may be determined and explained by the use of the technology acceptance model (TAM) which is depicted in Using the TAM diagram, when a technology is introduced, the first stage involves assessment of the organizational system already in use. The technological aspects are then considered, which are the probable tools and equipment used. The next step includes assessing the environmental buildings and the personal aspects, including an evaluation of their knowledge on the use of EHRs, which in this case is computer skills. This is followed by the knowledge stage. The unfreeze-move-freeze system gradually moves away from their paper-based method previously being used, encouraging people towards adopting the new system (move) and final implementation of the adopted system before it is frozen back .The methodology employed in the study as shown in A structured questionnaire was self-designed and self-distributed to the entire population of healthcare professionals working at OHC Ado Ekiti, which comprises of 4 nurses, 13 community health extension workers, 5 attendants, 1 health assistant, 1 pharmacy technician, 1 laboratory technician, 3 doctors, and 2 health information management technicians, totaling to 30 respondents. The questionnaires were designed to include questions regarding their demographic information and respondents were also asked to rate their level of efficiency from ‘not at all efficient’ to ‘extremely efficient’ in the usage of some computer functions, such as MS Excel, MS Word, MS Access, email, and WhatsApp. These categories of healthcare workers were given the questionnaires to fill, which was self-administered by the researcher to the respondents at their duty post and was retrieved after completion. The study, which was conducted in early 2023, lasted approximately 2 weeks in order to be able to capture staff off-duty during the first week that the study began. The paper-based questionnaires were taken to the study area to be self-administered by the researcher. The questionnaires were retrieved and returned after being filled. The retrieved questionnaire was subjected to analysis using frequency tables and percentages.The results from the analyzed questionnaire are shown below, where ME means Microsoft Excel, MW means Microsoft Word, and MA means Microsoft Access.The demographic information of the respondents showed that the highest percentage of the respondents were females at 73.3% as shown in Respondents’ level of skills in ME is depicted in This result is consistent with the findings on the study conducted on artificial intelligence healthcare service resource adoption by medical institutions based on the technology organization environment (TOE) framework, where computer processing power, computer experience, computer knowledge, perceived usefulness of intelligent systems, and their ease of use are seen as factors influencing the adoption of intelligent healthcare services by medical institutions with integrated medical care .All healthcare professionals, including nurses, health information management practitioners, doctors, laboratory scientists, pharmacists, and all other members in healthcare teams, are expected to have extensive knowledge and be competent in the use of computer systems for the management of their patients’ healthcare using EHRs. Adopting EHRs will largely depend on the computer skill usage of the end users before it can optimally be put into use. In the light of the huge data requirements and improved patient care, there is a pressing need for all healthcare professionals to acquaint themselves with adequate computer appreciation in order to meet the with the needs of improved healthcare services through electronic health appliances, which are fast growing around the world ,32,33. SThere is a need for continuous training and retraining of existing staff, and computer literacy must be emphasized as part of the requisite for future employment. This will ensure the smooth running of EHRs in hospitals. Computer appreciation and its knowledge are great determinants for the adoption of EHRs, and if it is going to be introduced into practice there is need for all staff, no matter their job title, to become acquainted with it.Limitation of the study: This study is limited to an annex of the main hospital EKSUTH, because they are yet to utilize the EHR system unlike the main hospital itself. Future studies may be undertaken on the applicability of computer appreciation on practical use and the challenges encountered with this. Research may also focus on the other annex of the hospital.