Public databases for glaucoma studies contain color images of the retina, emphasizing the optic papilla. These databases are intended for research and standardized automated methodologies such as those using deep learning techniques. These techniques are used to solve complex problems in medical imaging, particularly in the automated screening of glaucomatous disease. The development of deep learning techniques has demonstrated potential for implementing protocols for large-scale glaucoma screening in the population, eliminating possible diagnostic doubts among specialists, and benefiting early treatment to delay the onset of blindness. However, the images are obtained by different cameras, in distinct locations, and from various population groups and are centered on multiple parts of the retina. We can also cite the small number of data, the lack of segmentation of the optic papillae, and the excavation. This work is intended to offer contributions to the structure and presentation of public databases used in the automated screening of glaucomatous papillae, adding relevant information from a medical point of view. The gold standard public databases present images with segmentations of the disc and cupping made by experts and division between training and test groups, serving as a reference for use in deep learning architectures. However, the data offered are not interchangeable. The quality and presentation of images are heterogeneous. Moreover, the databases use different criteria for binary classification with and without glaucoma, do not offer simultaneous pictures of the two eyes, and do not contain elements for early diagnosis. Glaucoma is an optic neuropathy of asymptomatic progression and characteristic visual field loss that can lead to total and irreversible blindness. It is estimated that in 2013, 64.3 million people aged 40 to 80 years were diagnosed with glaucoma, and this number is expected to increase to 76 million by 2020 and 111.8 million by 2040 [In recent years, deep learning techniques have demonstrated the potential to solve complex problems involving images and medical domains, such as automated glaucoma screening. For example, in visual field examination, deep learning has been shown to differentiate between normal visual fields and those with pre-perimetric glaucoma . Still, In medicine, the use of artificial intelligence (AI), through deep learning techniques, has shown potential for population screening and reducing glaucoma progression in patients waiting for help from professionals, facilitating populations’ access to early diagnoses, especially in more distant locations, which standardizes diagnostic results and even decreases diagnostic divergence between specialists. However, AI offers only one reference for a clinical diagnosis. Thus, medical specialists will always be responsible for diagnosis and treatment . In otheColor fundus photography (CFP) is a cost-effective and non-invasive way to analyze the retina ,6. CFPs Public databases have diverse characteristics that make it difficult to correlate data. For example, some databases present the optic disc (OD) segmentation and cupping made by experts and grouped into sets of “normal” and “glaucomatous” papillae based on appearance. Others give classifications based on patient chart data and show evolving stages of glaucoma, i.e., an early, moderate, and severe glaucoma group.Other retinal pathologies concomitant with glaucoma should be evaluated in clinical practice. The specialist can diagnose them through clinical data or examination findings. Color retinography is an element of immense importance for diagnostic aid and will undoubtedly demand an excellent function of the algorithms to embrace a more comprehensive diagnostic range. In the development of deep learning databases and architectures, a significant research effort is being made to introduce tools for the segmentation of the OD and the optic cup in CFPs and to identify glaucoma cases based on clinical features ,10,11. HThe optic papilla region includes several anatomical variations considered normal in the population. In addition to spatial and non-overlapping differences between the images of right and left papillae, these variations include the insertion of the nerve in the eye, the size, and excavation of the papilla, vascular emergence, pigmentation, and the peripapillary region. Many variables may be presented as different fingerprints in a population capable of influencing the training and the results of neural networks. Therefore, there is a requirement to constantly update the datasets and establish protocols for the images integrated with clinical data and ancillary tests. In addition, there is a need to define the training and validation set of the public databases, develop automated tools for segmentation and classification of the CFP to reduce data deficiency, and ensure more reliable results for effective glaucoma detection. Public databases adapt to these requirements through the challenges for segmentation and classification as in REFUGE and, more recently, another challenge, “Artificial Intelligence for RObust Glaucoma Screening” (AIROGS). This study aims to analyze the gold standard public databases for glaucoma analysis and offer recommendations to improve their contributions to the learning of neural networks showing significant advances for automated screening of glaucomatous papillae. It is divided into five main topics: a few fundamentals of glaucoma, deep learning in the context of artificial intelligence, fundamentals of the existing public databases for the study of the retina, and fundamentals considered the gold standard for the study of glaucoma. Finally, various recommendations will be analyzed to improve existing databases and those used in the future.Some fundamentals of glaucoma will be analyzed with an emphasis on clinical diagnosis. Specifically, classification using fundus photographs, the most used ancillary tests, and the principles used in the treatment will be discussed.Glaucoma is a chronic optic neuropathy characterized by irreversible damage to the retinal nerve fiber layer (RNFL) and characteristic visual field changes. Changes in the nerve fiber layer can be visually translated by irregularities in the inner border of the neuroretinal layer  and incrScreening for glaucoma should be performed routinely and includes detailed medical history, slit lamp examination, CFPs, and tonometry. CFPs are essential in screening and studying disease progression and are used to study the optic nerve structure in glaucoma. However, identifying glaucomatous features in the optic papilla is challenging even for specialists and requires expertise and years of practice. Some of the main glaucoma-related changes are visualized in the neural layer of the optic papilla, including increased cupping and neuroretinal thinning, as well as other changes earlier in the peripapillary region, such as retinal fiber layer defects and peripapillary atrophy . In addiThe most common types of glaucoma have a primary cause, i.e., they originate from ocular factors . They can be grouped according to the angle of outflow of the aqueous humor into open-angle glaucoma and closed-angle glaucoma . There iIn current clinical practice, CFP features are used in conjunction with other clinical data, such as IOP, automated perimetry, and the use of OCT to diagnose glaucoma. However, these approaches are not cost-effective for large-scale population screening for glaucoma . Subsidiary tests may be indicated in suspicious cases and the study of glaucoma progression, especially in OCT and the visual field.The early detection of glaucoma includes structural and functional tests. Structural tests aim to detect structural changes in the retinal fiber layer. Structural tests include confocal laser ophthalmoscopy, OCT, and laser polarimetry. Functional tests such as frequency doubling perimetry and short-wavelength automated perimetry, also known as blue-on-yellow perimetry, are intended to detect visual field damage before changes in visual field examination. These tests have limitations, including the inability to assess eyes with high myopia, large ODs, and areas of peripapillary atrophy . In thesVisual field examination, campimetry, and automated achromatic perimetry (white-on-white) have significant importance in diagnosing and evolving glaucoma. Graphic alteration locates the non-vision region corresponding to the neural layer damage by glaucomatous neuropathy. This scan evaluates 30 degrees where most glaucomatous defects occur and can show changes only in the stages where considerable retinal fiber loss has already occurred ,17, limiOptical coherence tomography is a diagnostic aid exam in several retinal pathologies. It shows sections of the retinal layers. In glaucoma, it is used in suspected cases with structural changes confirmed by fundus photography (retinography) when the cup-to-disc ratio ≥ 0.5 and <0.9, in the presence of asymmetry between the two eyes ≥ 0.2 and localized thinning of the neural ring, or for diagnostic clarification in ocular hypertensive patients (ocular pressure above 21 mmHg). It makes it possible to diagnose and monitor glaucoma through the evolution of macular thickness. Although central vision is often preserved in late glaucoma, the thinning of the macular area is a parameter found in the early stages of the disease and precedes visual field defects . Figure Once the diagnosis is established, treatment should be started as early as possible. The treatment of glaucoma aims to stop the progression of the disease. It is achieved using traditional surgical strategies and laser application to increase intraocular fluid filtration and topical or systemic pharmacological approaches to reduce the target eye pressure and stop disease progression. In addition to these strategies, systemic factors such as diabetes, hypertension, tumors, rheumatic processes, and ocular factors, such as cataracts, vasculopathy, malformations, post-traumatic injuries, infections, and hemorrhages should be stabilized.Some fundamentals of deep learning within artificial intelligence will be analyzed, with an emphasis on application, the challenges of large-scale application, and ways of applying DL architectures in automated glaucoma classification.As a subarea of artificial intelligence, machine learning (ML) algorithms deal with large datasets such as thousands of images, facilitating the resolution of problems that would be impractical through classical statistical analysis. In turn, deep learning is a sub-area of machine learning that operates data analysis through the representation of successive layers  inspired by the human brain. Each layer could filter specific properties and select more relevant characteristics that have significant applications in medical diagnosis problems, allowing complex representations to be learned and divided into intermediate spaces (layers). Deep learning has demonstrated a vast applicability potential in the medical area by improving image accuracy, processing, and identification of diagnostic relevant features in radiographic images, tomography, ultrasonography, histological analysis of organs and tissues, and photographic analysis images. Deep learning can identify features within a complex structure in large datasets using multiple intermediate layers positioned between the input and output layers (as seen in The deep learning workflow can be defined in three steps: (1) pre-processing of image data; (2) model training, model validation, and testing; and (3) evaluation. Pre-processing includes noise reduction, feature selection and extraction from the image, and data normalization. A model to be trained is initially divided into three sets: training data, validation, and testing. The training set allows the model to learn to fit the data parameters of the classifier. The validation set prevents overfitting. The test set is used to evaluate the performance of the trained model. The data provided by the public databases will be used in the training step of the deep learning algorithms. For best results, the data need to be dependable and offered in a sufficient quantity to train and evaluate the system.Many of the main challenges for problem-solving through DL architectures are generated by protocol deficiencies in defining public databases. If the databases do not appropriately train the networks, it may be misleading to networks’ responses. Gold standard public databases such as DRIHTI-GS, RIM-ONE DL, and REFUGE offer a reduced dataset and few data for training/testing. For example, data are classified into glaucoma and non-glaucoma groups based on imaging alone in the case of the RIM-ONE DL database, and there is no information on which clinical bases the clinical classification used in the DRISHT-GS1 and REFUGE databases were based. Furthermore, no public database presents images of the papillae of both eyes. The lack of standardized strategies makes it difficult to compare existing methods .According to , automatAutomated recognition of glaucomatous papillae in CFPs by DL techniques can be performed in two ways: by directly recognizing glaucomatous features in the optic papilla by DL architectures and by segmenting the disc and excavation of the optic papilla. Existing DL approaches are based on adaptations of supervised DL techniques , i.e., tAutomated glaucoma classification directly by DL architectures classifies an input image as glaucoma or non-glaucoma based on the visual characteristics of the optic papilla and the segmentation of the optical disc and cupping. It can be divided into methods based on image similarity, manual techniques, transfer learning methods, and OD limitation. DL methods produce glaucoma diagnosis through image similarity. They need a large dataset for learning networks. Historical and clinical data extracted from the medical consultation can complement DL model features and give reasons for neglected diagnosis results .Manually handcrafted methods used for excavation/disc segmentation are used for feature extraction techniques and ML classifiers using supervised or unsupervised techniques ,10,11. HTransfer learning methods are based on pre-trained architectures with non-medical data. They use weights learned from ImageNet. Russakovsky et al.  and GómeMethods with OD and OC restriction restrict the analysis area to the OD affected by glaucoma. Limiting the image of the optic papilla allows a better exploration of its features and results in better learning performance of the automated models than at full size but determines a substantial restriction in the field of view of the networks and hinders their ability to learn alternative features of other regions . HoweverExcavation segmentation from a retinal image is challenging due to the lack of depth view in 2D images but is relevant because it helps assess glaucomatous damage to the optic nerve head (ONH) . FurtherIn this section, generalities of the public databases used in the retinal study are analyzed, as well some reflections on the choice of data with predefined segmentation and partitions, the use of images  for neural network learning, the importance of the quantity and diversity of images, and the evaluation metrics used in the databases. Public image bases on the internet contain image clusters used for ophthalmic studies, standardization, and DL architecture research. The databases integrate information obtained through manual processing of the images by experts, can be analyzed by computer algorithms, and allow the comparison of the performance of different algorithms analyzing the same background image. They include, for example, the detection of diabetic retinopathy and diabetic macular edema in fundus photographs , lung seThe images are obtained under multiple conditions, with different cameras, in several groups of patients, with objectives defined by various experts. Therefore, there is difficulty using data and methodologies between the various bases. Just as railways should have homogeneous gauge sizes to avoid frequent changes in compositions, public databases should follow some rules to improve the interchangeability of data and methodologies required, allowing updates of color photographs, classification parameters of glaucoma/non-glaucoma groups confirmed through clinical data, and subsidiary examinations allowing more excellent reproducibility of results, representation of each patient through color photographs of both eyes (because they are non-overlapping images), and centralization of retinal images in pre-established structures. In the very recent work about the “Retinal Fundus Glaucoma Challenge” (REFUGE) , a critiNew challenges are currently under development, such as the Artificial Intelligence Challenge for RObust Glaucoma Screening (AIROGS), which is to be held to develop solutions for glaucoma screening from CFPs. Still, the study does not detail the protocols that will be followed .The images from the databases intended for the study of glaucoma are generally focused on different anatomical points of the retina. As exemplified in As can be seen in Significant discrepancies in the evaluation protocols were observed between the databases. These differences  curves are the most commonly used metrics, including the area under the curve (AUC) ,26,34,48The gold standard databases RIM-ONE DL, DRISHTI-GS1, and REFUGE will be analyzed (considered of great interest to applicability in DL architectures) in this section from the point of view of the presentation and characteristics of datasets and results obtained in each base.The methodology used will compare the databases with the gold standard: RIM-ONE DL , DRIHST-https://github.com/miag-ull/rim-one-dl (accessed on 15 June 2022) and was created in 2020 to optimize the three previous versions for use in deep learning. Based on the three previously published versions, a version called RIM-ONE DL (RIM-ONE for Deep Learning) was created and optimized for a deep learning context. All images were again manually segmented (disc and excavation). One image of each eye per patient was kept, and all images were cropped around the optic nerve head using the same proportionality. According to clinical criteria, the images were reclassified into glaucoma and non-glaucoma [The unified retinal image database for assessing glaucoma using deep learning-RIM-ONE DL  is availglaucoma .The RIM-ONE DL base is divided into two large groups partioned_by_hospital and partitioned_randomly, into test_set and training_set groups. Each group presents subgroups of glaucoma and normal datasets. The images demonstrate the magnification of the region of interest of various features of the glaucomatous papilla. The fundus photographs in the test and training groups present irregularity in sizes, colors, and clarity. It allows only limited analysis of the peripapillary region and hinders the investigation of areas of sectorial atrophy of peripapillary fibers, which is essential for early diagnosis. Moreover, the RIM-ONE DL database presents images randomly obtained between the right and left eye. The classification of normal and glaucoma groups in both test and training sets is based only on segmentations performed manually by experts, no clinical data or ancillary tests are mentioned, and symmetrical images of the eyes are not presented.The Retinal Image Dataset for the Assessment of Glaucoma from the Optic Nerve Head Analysis-DRISHT-GS1 presents a set of retinal images for papillae evolution in normal and glaucomatous eyes with manual segmentation by experts that allows measurements of the ratio of the diameter and cupping and the area of the OD, known as the cup-to-disc ratio (CDR). It presents notch analysis in the superior, inferior, nasal, and temporal (notch) sectors. The author warns about the difficulty of comparing the performance of individual methods due to the lack of a more comprehensive set of bases ,53. The features presented in The measures used for the quantitative analysis of the segmentation method were the segmentation region, boundary location, and the estimated CDR measure. The Hough circle was proposed as the algorithm for the initial segmentation of the optical disc. The DRISHT-GS1 base includes segmentation performed by two more specialists. It is based on three strategies: the detection of the color gradient and the transition of small vessels, the presupposition of the excavation depth by visualizing multiple images, and the presupposition of the excavation depth by color variation (available in the test group) and in-depth maps visualized by OCT (available in the training groups). The author warns of the difficulty in comparing the performance of individual methods due to the lack of a more comprehensive set of bases for classification based on clinical data and divided between the test and training groups ,53. The https://refuge.grand-challenge.org/ (accessed on 15 June 2022). It is a competition held as part of the Ophthalmic Medical Image Analysis workshop presented at MICCAI 2018. It was the first initiative to evaluate automated methods for OD/OC segmentation and glaucoma classification from CFPs. For this purpose, the challenge provided the community with 1200 fundus photographs. The Retinal Fundus Glaucoma Challenge (REFUGE) base is available on the website Each image in the REFUGE dataset includes binary glaucoma/non-glaucoma classification performed based on a comprehensive evaluation of patient records, including follow-up fundus images, IOP measurements, OCT images, and visual field. Glaucomatous cases correspond to individuals with glaucomatous damage in the ONH area and reproducible glaucomatous defects. However, early cases or those with pre-perimetric changes and bilateral representation of the right and left papillae are not explained. The images are centered in the posterior pole, between the macula and the visible OD, to evaluate the ONH and potential retinal nerve fiber layer defects.The REFUGE base presentation is divided into three fixed subsets: training, offline, and online test sets containing equal glaucomatous (10%) and non-glaucomatous (90%) cases. Since training DL from scratch on a training set with only 400 images may lead to overfitting, most groups started the convolutional networks with pre-trained ImageNet weights and then adjusted using the CFPs .The REFUGE base is divided into test , traininAutomated methods are currently being developed to predict depth maps of CFPs by correlating ground truth segmentation image features with classifications obtained through other modalities such as stereoscopic photographs. Research is underway in developing automated methods to predict depth maps of CFPs by attempting to correlate image features with ground truth labels obtained from other imaging modalities such as stereo fundus photography  or OCT . These tAccording to , the RIMWe note that the best approaches for glaucoma classification integrate deep learning techniques with well-known glaucoma-specific biomarkers such as vertical cup changes, cup-to-disc ratio, and retinal fiber layer defects. In the REFUGE challenge, the two top-ranked teams achieved better results than two glaucoma specialists, a promising sign for using automated methods to identify glaucoma suspects with fundus images . U-shapeThe network models VGG19 and VGG 16 had satisfactory results . HoweverThe results were based on the segmentation of the optical disc/scan, the location of the boundary performed by the computed region compared to the ground truth, and the estimation of the CDR and the notch of the inner edge of the neural layer (gap). The initial boundary estimation for optical disc segmentation was based on a transformation algorithm by the Hough circular. Notch segmentation was conducted based on three methods according to the path of the vessels (thin) using a monochrome image, a motion structure to demarcate depth/discontinuity, with false-positive results occurring in the regions of most excellent whiteness, and the segmentation method based on color variation and the corresponding depth of the OCT. The proposed method for notch detection was based on the computational evaluation of neural layer thickness changes against an expert opinion. The edge thickness distribution in normal papillae follows the ISNT rule, which states that the edge thickness decreases along with the sectors of the neural layer in the order Inferior > Superior > Nasal > Temporal, as represented in The ROC curve for the training and testing data is presented below, and the curve values are shown in REFUGE contains OD/OC masks, fovea positions, and gold-standard clinical diagnostic classification. This feature aids glaucoma classification methods as it was recently observed that training with categories made by CFPs harms performance in detecting truly diseased cases .Analysis of the results and recommendations will be made to improve the databases and make cross-sectional annotations in the dataset feasible. The public databases’ main limitations and the results’ clinical implications are discussed below.The bases RIM-ONE-DL , DRISHTIA synopsis of the main advantages and disadvantages of the gold standard public databases used in glaucoma is shown in As analyzed in Trucco et al. , the lacThe recommendations for improving the databases suggest a set of protocols to avoid errors in training and make the training of DL nets closer to reality. Data should be continually updated to encompass the normal and pathological anatomical diversities of the fundus of the eye.There should be a more representative dataset including a diversity of ethnicities, comorbidities, genders, and ages; comparative photographs of both eyes; and color fundus photographs with varying qualities.A percentage of glaucoma cases should be maintained that is similar to that expected in a population-screening scenario estimated to be between 1% and 2% in the general population, reaching 6% to 7% after 70 years .Manual disc and cupping segmentations and binary ground truth classifications performed from CFPs should consider cupping depth information from OCT scans, which provide cross-sectional retinal images (and thus depth information) and reference Bruch’s membrane, which is considered to be the best anatomical delimitation of the OD, and serves as a reference for one of the most recent measurements of the number of retinal nerve fibers (BMO-MRW) . The comProtocols should be made available for the analysis of medical records used as the basis for glaucoma/non-glaucoma binary classification to allow other comorbidities that may accompany glaucoma to be addressed.The databases can contribute to more reliable and accurate results for the training/testing groups, increasing the accuracy of the screening results of the DL networks regarding the segmentation and binary classification of the normal/glaucomatous papilla through images.Cross-sectional annotation of datasets using homogeneous protocols could increase the available data and improve the network results. Therefore, to validate a cross-sectional annotation, the images should be repositioned and submitted to homogeneous criteria of disc segmentation and cupping, and a re-analysis of the binary classification between normal/glaucomatous papillae based on clinical data and ancillary tests such as visual field and OCT should be performed, since the analysis by image similarity increases the number of false positives, as reported. The grouping of images with irregularities not yet visible at the inner border of the neural layer but with corresponding initial perimetric alterations would bring advantages in the early diagnosis. Sets of betterand worse-quality images obtained by different cameras in distinct locations and populations could be used in the training of neural networks as parameters closer to reality. Another point of divergence for the network is the presentation of the right papilla image and how the networks would interpret the sample of the left papilla since the papillae of the two eyes do not overlap spatially. Another factor is that the databases cannot be matched as they use different strategies. Protocols with an approach closer to the real world would provide greater sampling security. No single parameter would bring a diagnostic confirmation of glaucoma. Some parameters such as ocular hypertension and glaucomatous papilla features, including enlarged cupping, are factors for suspecting the disease. The diagnostic certainty of glaucoma consists in the correspondence between the glaucomatous part of the papilla with an alteration in the visual field in that region. The same reasoning can be applied to the presence of a notch. This is a feature that can be considered suspicious. Still, it is not pathognomonic of glaucoma by itself, as it may be only an image noise that does not represent a region of neural damage. The detection of a  notch correlated with the visual field may be a goal to be pursued by AI as far as it facilitates early diagnosis.Retinal image pigmentation can undergo a few changes in different ethnicities and influence the performance of others.The percentage of glaucoma cases in the REFUGE, DRIHST-GS1, and RIM-ONE datasets is higher than expected in a screening setting.Including only high-quality photographs makes applying the proposed methods in real screening scenarios challenging.Manual OD/OC segmentations performed from CFPs may be ill-defined.Better binary ground truth classifications follow two-dimensional patterns for delineating OD/OC.Color photographs do not match data from analyzed medical records and do not allow a broader approach to other comorbidities that may accompany glaucoma.Reliable results obtained within a dataset presented in one database may not necessarily reflect the same results in other databases subjected to the same learning values considering heterogeneous protocols (as cited). The automated systems can detect suspected glaucoma cases from fundus photographs as long as they follow some previously analyzed protocols. At the moment, this is still an open question. Although challenges such as REFUGE are moving in a more realistic direction, we do not yet know the significance of the answers that AI could provide in a population setting. With technological development continuously transforming, fundus cameras are improving portability and ease of use, as well as the use of defined protocols. It is hoped to expand the use of AI to diagnose and follow the progression of glaucomatous disease, remembering that the modality of early imaging in databases is still pending due to the subtle manifestation of the initial stages of disease images. We saw that some of the proposed models were able to identify glaucoma with a focus on a few biometric features of the optic papilla, such as the disc-to-cavity ratio in REFUGE and the notch in DRISHT-GS1. We have seen that the REFUGE challenge results also seem to indicate that the use of vCDR may be a feature of greater importance than others, such as ONH hemorrhages, sectorial atrophies, or RNFL defects. Based on vCDR, as a probability of glaucoma, sensitivity and specificity values were statistically equivalent to those obtained using ground truth. Perhaps these parameters alone do not diagnose the disease but may have importance as single screening factors. However, we may incur errors by basing the binary classification on only a few features. Therefore, it is essential to have a conveniently classified sample of data.In the REFUGE challenge, the top-performing teams complemented ONH measurements by DL models. We can significantly outperform expert diagnosis of glaucoma, with increases in sensitivity of up to 10% . AlthougOther metrics derived from relative OD/OC shapes have recently outperformed vCDR in the diagnostic process, such as the rim-to-disc ratio . HoweverRetinal evaluation by CFPs allows for the cost-effective assessment of glaucoma. Although OCT better highlights the excavation and fiber layer damage and provides a three-dimensional view of the retina, its large-scale use is economically unfeasible. Other markers used alone to make transverse scans and quantify the thickness of the RNFL or the size of the excavation have proven to be financially unviable and alone do not confirm the diagnosis. Thus, the development of DL methods for glaucoma screening must integrate CFPs analysis and glaucoma biomarkers.Therefore, we recommend a database with more robust data following some protocols that allow the integration between datasets that may encompass CFPs obtained from multi-population centers, with the segmentation of the OD and cupping and images of both eyes, with diversified image quality, divided into well-defined training/test/validation groups, presenting structured binary classifications using clinical criteria that allow division into groups of papillae with early to severe glaucoma, besides the possibility of analyzing other retinal comorbidities evaluation through methods.Public databases form the training and learning base for automated screening performed by deep learning architectures. Of the various databases used in ophthalmology, many are most helpful in diagnosing diabetic retinopathy, senile macular degeneration, and glaucoma. Among the bases used for glaucoma, the gold standards RIM-ONE DL, DRISHTI-GS1, and REFUGE are the most useful because they present segmentations of the disc and the excavation drawn by specialists and present classifications of normal papillae and those with glaucoma based on images, clinical data, and ancillary tests. Its disadvantages are the heterogeneous photographic quality, varied sizes and positioning of the image, and lack of images of both eyes. It would be advantageous to develop a protocol capable of performing population screening for glaucoma and diagnosing early forms of the disease and other retinal comorbidities in the medical context. Therefore, we suggest that the database data be continually updated and reclassified based on image segmentation and using clinical data and ancillary tests to provide more robust data to public databases and make the results more dependable. Deep learning architectures could be made more dependable by using other clinical biomarkers, symptoms, eye pressure, family, and personal history to make DL models closer to the real thing and to make the results more accurate. We suggest the inclusion of clinical parameters such as notch , CDR measurements as performed in the DRISHT-GS1 database, images with pre-perimetric defects, images with non-glaucomatous peri-papillary changes , and continual updating of images to encompass rare diagnoses and avoid false positives. The possibility of including the simultaneous screening of other retinal pathologies concomitant to glaucoma in DL networks in clinical practice should be screened by specialists through clinical data or be diagnosed as an examination finding. In this case, color retinography is significant in diagnostic aid and will certainly demand an excellent function of the public databases and algorithms to embrace a more comprehensive diagnostic range.


Although methods are used to treat wounds clinically, there are still many challenges in the treatment of chronic wounds due to excessive inflammatory response, difficulties in epithelialization, vascularization, and other factors. With the increasing research on adipose-derived stem cells (ADSCs) in recent years, accumulating evidence has shown that ADSCs scan promotes the healing of chronic wounds by regulating macrophage function and cellular immunity and promoting angiogenesis and epithelialization. The present study reviewed the difficulties in the treatment of chronic wounds, as well as the advantages and the mechanism of ADSCs in promoting the healing of chronic wounds, to provide a reference for the stem cell therapy of chronic wounds. With an increasingly aging population and soaring chronic metabolic diseases such as diabetes increase, chronic injuries have become an increasingly serious public health concern. Chronic wounds refer to wounds that cannot pass through a normal, orderly and timely repair process or the repair process fails to restore normal anatomical structure and function after 2 months . ConventClinically, there are several risk factors for chronic injury. The main risk factors are discussed below.Older patients are more susceptible to chronic wounds. Because aging is associated with a decrease in cellular activity, elderly patients are less responsive to platelet derived growth factor (PDGF), which promotes the growth of wound blood vessels . In addiWounds in patients with underlying diseases are more difficult to heal. For example, in diabetic patients, high blood sugar reduces the solubility of the ECM, which contains multiple cytokines that promote wound healing, which indirectly leading to poor wound healing . In addiNutritional status is one of the key factors affecting wound healing. Due to surgery and trauma, patients with wounds continue to be in a state of high metabolism, which leads to excessive consumption of fat and protein stored in the body, resulting in malnutrition . The lacCurrently, there are numerous challenges in the treatment of chronic wounds, mainly due to the uncontrollable inflammatory response at the wound site, the blocked vascularization process, the difficulty in normal epithelialization and dermal remodeling, and the adverse effects of wound microbes and aging organisms. The underlying diseases that are most likely to cause chronic wounds, such as diabetic foot ulcers, venous leg ulcers, and pressure ulcers, can lead to the above pathological changes and cause chronic wounds .The uncontrollable inflammatory reaction is one of the main challenges in the treatment of chronic injuries. Studies have shown that various of inflammatory cells, such as neutrophils and macrophages, persist on the wound site. An increase in the infiltration of these inflammatory cells may suppress the anti-inflammatory functions of normal immune cells, such as M2 macrophages .Vascularization is the only normal route of wound repair, and inadequate vascularization also complicates the treatment of chronic wounds. Chronic wounds are difficult to vascularize due to the imbalance between the promotion and inhibition of angiogenesis. Furthermore, it is difficult for macrophages to change from M1-type macrophages that stimulate inflammation to M2-type macrophages that promote repair, resulting in insufficient secretion of human vascular endothelial growth factor (hVEGF) and other pro-angiogenic factors by M2-type macrophages. The proIn vitro studies have shown that β-catenin blocks the action of epidermal growth factor, thereby inhibiting wound healing  . Howeverin vitro expansion of T cells by phenotypic characterization and functional analysis of cytotoxic and helper T cell (activation and differentiation marker T cells) proliferation and interferon release  can be derived from various of tissues such as bone marrow, fat, placenta, umbilical cord, umbilical cord blood, amniotic membrane, and dental pulp . TherefoFor the acquisition site, BM-MSCs can only be obtained from the bone marrow, and the success of the acquisition and the number of acquisitions depend on the patient’s condition and the amount of bone marrow aspiration . UC-MSCsThere are some reports on the application of ADSCs in the treatment of chronic wounds. Deng et al. conducted a randomized controlled trial to compare ADSC injection wounds, comparing ADSCs injection combined with standard dressing therapy and standard dressing therapy alone . The resHowever, the application of ADSCs in wound healing has several limitations. Currently, the application of allogeneic ADSCs involves cryopreservation of ADSCs. However, guidelines for optimal and standardized parameters for cryopreservation of ADSCs are largely lacking, and therefore contamination-free and a sufficient number of usable ADSCs cannot be guaranteed . In addiThe healing process of chronic wounds is very complex, and ADSC therapy shows great advantages and potential in the promotion of healing. ADSCs can directly differentiate into fibroblasts, keratinocytes, and other cell types to promote the recovery of the shape and function of the wound by accelerating the wound repair process and regulating the wound and its surrounding microenvironment. In addition, recent studies have found that ADSCs have multiple signal recognition molecules on the cell membrane, which can be used as potential carriers for drug delivery and can be further modified by ADSC applications such as co-incubation, freeze-thaw, and electroporation to carry therapeutic molecules. Therefore, ADSC therapy is an effective and promising method to promote wound healing. Although the experimental application of ADSCs in patients with chronic wounds patients has yielded preliminary results, there are still several problems to be solved before large-scale clinical application on a large-scale. From an overall perspective, there are only small-scale experimental applications of ADSCs in the treatment of chronic wounds currently, making it difficult to obtain higher-level evidence supporting for the safety and efficacy of ADSCs. From the perspective of ADSCs collection and processing, whether the age, gender, body mass index, or fat collection site of enrolled subjects has an impact on the number and viability of ADSCs also warrants further exploration. In addition, the potential tumorigenicity of ADSCs also requires conattention. Therefore, larger-scale randomized controlled clinical trials with unified reporting standards and more in-depth basic research are required to assess safety and efficacy of ADSCs in promoting chronic wound healing.


Distal radial fractures (DRF) are often encountered in upper limb fractures globally, and their associated complications affect the functional independence of the individual following the injury. The potential of gamification in applied rehabilitation is expanding its horizons in the rehabilitation of conditions ranging from neuromotor deficits to cognitive impairments. However, the synthesis of the literature is aimed at analyzing and summarizing the evolution of gamification in DRF rehabilitation. A comprehensive search and extraction of relevant literature were conducted and reviewed for the applicability of population analysis, interventional methodology, comparative factors, outcome measures, and the type of study. Thirteen studies were included and evaluated, including randomized controlled trials (RCTs), literature reviews, systematic reviews, meta-analyses, and bibliometric analyses. The conclusions demonstrated an improvement with gamification and addressed it as an effective rehabilitation method. Based on the analysis of the data that was extracted, the conclusion supports the use of gamification in the rehabilitation of DRF and looks into how it can help improve the person's functional capacity. A distal radial fracture (DRF) is the most common upper limb fracture that limits the functional activities of daily living (ADLs) and requires precise attention during rehabilitation for an effective return to functional independence . PatientVirtual reality (VR), augmented reality (AR), and mixed reality (MR) provide mature access to rehabilitation technology and are versatile fields for evidence-based clinical practice . The OcuResearch methodologyA combination of words was used for searching the literature in all databases, which included "distal radius fracture" AND "physiotherapy" AND "rehabilitation" AND "virtual reality" AND "gamification." The articles published since 2013 were included in the rapid synthesis of the literature. Articles were searched from PubMed, Emerald, ScienceDirect, SAGE Publications, Wiley, and Google Scholar. The inclusion criteria included the peer-reviewed literature having immersive VR or gamification as an intervention in rehabilitation, a rehabilitative approach to DRF, randomized controlled trials (RCTs), systematic reviews and meta-analyses, and articles published since 2013. The exclusion criteria included non-peer-reviewed literature, non-immersive VR as an intervention, gamification used as a diagnostic method, and articles published prior to 2013. The studies exploring the effectiveness of gamification as an intervention in the rehabilitation of different conditions were given preference.The literature was extracted from relevant studies and reviewed for the applicability of population analysis, interventional methodology, comparative factors, outcome measures, and the type of study as shown in Table A study on the epidemiology of DRF predicted risk factors and prognosis and found the responsive factors of chronic disability and pain, which lead to an imperative perspective for therapists to implement more extensive assessment, interventional strategies, and customized educational programs. This leads to the conclusion that DRF is the most common fracture worldwide with a need for rehabilitation to return to functional ADLs . The phyA bibliometric analysis analyzed two-decade data on VR-aided therapy for health. A blended examination strategy was embraced for this exploration, utilizing a bibliometric investigation where a quantitative technique led to an overview outline of VR-assisted treatment, along with a literature review putting an impact on the qualitative insights of the application. The data cost is added to design further healthcare administrations and associations between healthcare counterparts utilizing elements of the game and presenting new exploration programs . Again, A review of RCTs concentrating on physical activity (PA) improvement in adolescents found that exergaming can be a successful tool to further develop PA in adolescents that could be more adequate and maintainable than numerous established procedures following its potential and interests. The resilience of this review lies in its incorporation of RCTs making it a higher level of evidence. In any case, involving exergaming to advance and impact adherence to PA or elements that obstruct or urge adolescents to play active video games has not yet been determined . GamificSystematic review and meta-analysis of randomized clinical trials of VR-based treatments for persistent low backache indicated that VR-based rehabilitation could significantly reduce pain intensity and kinesiophobia in chronic low backache patients. However, the application of VR-based rehabilitation is highly heterogeneous and can affect the outcomes. VR-based rehabilitation can be incorporated into clinical platforms with reference to its impact on the intensity of pain and kinesiophobia following short- and mid-term follow-ups in chronic low backache patients . A systeThe implication of the principle of motor learning in VR-based rehabilitation of patients with cerebral palsy was analyzed in a systematic review of 26 studies, and it was concluded that tailored VR-based rehabilitation programs customized for individual needs and requirements lead to a better functionally independent life. VR-based rehabilitation involves motor learning, including serious gaming as a rehabilitative platform to improve the functional capacity of the upper limbs . It boosA single-blinded prospective RCT was conducted on 51 Parkinson's patients to compare the efficacy of VR-based rehabilitation programs concluding with an improvement in upper limb function, gait adaptation, complex ambulation skills, and quality of life . The utiAn analysis of ambiguity applied as concepts for serious games and gamification in healthcare reviewed the literature systematically and also developed a guideline for gaming, i.e., Game-Based Intervention Reporting Guidelines. It involved an explicit analysis of 206 studies leading to a result of the application of gaming concepts as serious gaming in healthcare elevation. The outcomes highlighted that explicit definition is lacking more than half of the concept application of serious gaming. It is heterogenous in nature, followed by the ambiguity of different perspectives and concepts .The analysis of the literature builds an evolutionary process in the development of gamification in rehabilitation. The impact of the integration of gamification has an imperative effect on the physical activity of adolescents, as well as in patients with chronic low back pain, lower limb amputation, cerebral palsy, and traumatic brain injuries along with clinical practice. The expanded horizon of the application of gamification in rehabilitation is expanding on the basis of its efficacy in improving fine and gross motor skills. The immersive environment providing real-time feedback proves promising in improving the compliance and adaptability of long-term patient care. An effective response time, movement velocity, and precision of movement develop using gamification creating a powerful determination in a diseased condition. Integrating the heterogenous, cost-effective, and creative ways of the pertinence, the ambiguity of the application of gamification can be expanded and explored in a wide range, explaining its evolution in different variants in rehabilitation.


Chitosan is a biodegradable and biocompatible polysaccharide obtained by partial deacetylation of chitin. This polymer has been gaining increasing popularity due to its natural origin, favorable physicochemical properties, and multidirectional bioactivity. In agriculture, the greatest hopes are raised by the possibility of using chitosan as a biostimulant, a plant protection product, an elicitor, or an agent to increase the storage stability of plant raw materials. The most important properties of chitosan include induction of plant defense mechanisms and regulation of metabolic processes. Additionally, it has antifungal, antibacterial, antiviral, and antioxidant activity. The effectiveness of chitosan interactions is determined by its origin, deacetylation degree and acetylation pattern, molecular weight, type of chemical modifications, pH, concentration, and solubility. There is a need to conduct research on alternative sources of chitosan, extraction methods, optimization of physicochemical properties, and commercial implementation of scientific progress outcomes in this field. Moreover, studies are necessary to assess the bioactivity and toxicity of chitosan nanoparticles and chitosan conjugates with other substances and to evaluate the consequences of the large-scale use thereof. This review presents the unique properties of chitosan and its derivatives that have the greatest importance for plant production and yield quality as well as the benefits and limitations of their application. Chitosan is a biopolymer obtained from chitin, which is the second most common natural polysaccharide after cellulose ,2. The d2) to the total number of acetylamino groups (–NHCOCH3) present in chitin [3CO) from chitin and substitution of reactive –NH2 groups, thus resulting in the formation of chitosan, whose deacetylation degree depends primarily on the duration of the reaction, the temperature (90–120 °C), and the concentration of the aqueous NaOH solution (40–50%) used in the process. Although it occurs naturally in the cell walls of some fungi, bacteria, and algae as well as insect cuticles, chitosan for industrial and laboratory use is obtained from chitin derived mainly from the shells of marine invertebrates , which are wastes of marine food processing industry [Currently, the term chitosan denotes a group of biopolymer substances obtained in the process of chemical or enzymatic deacetylation of chitin with different (but not lower than 50%) deacetylation degrees. Both chitosan and chitin are linear copolymers consisting of D-glucosamine and N-acetyl-D-glucosamine linked together by β-1,4-glycosidic bonds. The main difference between these polymers is their deacetylation degree (DD) expressed as a percentage and defined as the ratio of the number of amino groups . It is also involved in interactions of hydroxyl and amine groups with metal ions resulting in metal chelation, adsorption, and ion exchange [2O2 in plant cells as a signal molecule in defense reactions to stress and increase the activity of superoxide dismutase (SOD), peroxidases (POX), and catalase (CAT), i.e., enzymes involved in the direct neutralization of ROS [Ocimum basilicum and ascorbate peroxidase (APX) in Melissa officinalis. Similarly, foliar application of chitosan nanoparticles increased the activity of CAT, APX, and glutathione reductase (GR) in Catharanthus roseus exposed to salt stress [Triticum durum. It was observed that the use of this polymer neutralized the harmful effects of stress through a reduction in the content of superoxide radicals, H2O2, and malondialdehyde and via enhancement of CAT activity. In turn, the addition of chitosan as an elicitor in Psammosilene tunicoides hair root cultures was found to induce the production of nitric oxide and increase the activity of ROS-scavenging enzymes [Curcuma longa [2O2 in Capsicum annuum plants demonstrated that, in comparison with other substances, the foliar application of chitosan induced the lowest H2O2 accumulation in the leaves of this species [Chitosan has been shown to have antioxidant activity consisting in the neutralization of such reactive oxygen species (ROS) as superoxide anion radicals, free hydroxyl radicals, and hydrogen peroxide  or controlled release (CRF) fertilizers. The interest in this polymer has mainly been aroused by its beneficial effect on soil and plants and some physicochemical features. Given its film-forming properties as well as high biocompatibility and biodegradability, chitosan can be used as a coating material regulating the rate of release of minerals into the soil solution; additionally, it can be used to solve the problem with the disposal of residues of coatings produced from non-biodegradable polymers. In the agrochemical industry, chitosan nanoparticles are used both to optimize the activity and efficiency of various types of formulations and to reduce their toxicity to the environment ,61,62. A−1) exerted a positive effect on their health [Phytophthora capsici in a concentration-dependent manner . The highest concentration ensured complete resistance of young cucumber plants to blight caused by the pathogen [Phomopsis viticola spores [The presence of harmful organisms poses a serious threat to agriculture and many industries worldwide. According to data published in 2019 by the Food and Agriculture Organisation of the United Nations (FAO), agrophages cause approximately 20–40% of losses of the world’s crops annually . The user health . In turnpathogen . Treatmepathogen . Moreovea spores . Given ia spores  demonstra spores .Cylindrocladium floridanum, Cylindrocarpon destructans, Fusarium acuminatum, and Fusarium oxysporum fungi responsible for root rot in forest nurseries [Chitosan is also one of the few active substances contained in formulations and fungicides approved for use in forestry for the protection of forest nurseries against pathogenic diseases . As showurseries . MoreoveThe main goal of storage is to reduce food losses by ensuring the longest possible shelf life, good quality of stored products, and the best possible protection of product stability before further distribution. An important role in this process is mainly played by the selection of optimal conditions and storage methods as well as the monitoring of such product quality parameters as the color, weight, firmness, content of bioactive compounds, and rate of ethylene and carbon dioxide production. However, in the case of low-processed raw materials, it is often necessary to employ various types of preservation methods. One of the options to preserve the quality of stored raw materials consists in a reduction in respiration and transpiration through the use of natural edible coatings. The potential of using chitosan in storage is associated with its physicochemical properties and biological activity. Given its natural origin, ability to form semipermeable coatings, and high antioxidant and antimicrobial activity, this polymer facilitates the maintenance and optimization of the postharvest stability of raw materials and food products and influences their chemical composition. Additionally, chitosan delays fruit ripening through the limitation of ethylene and carbon dioxide release. Therefore, it can be widely used in the production of biodegradable films, food packaging, fibers, gels, and films with high strength and flexibility. It can also be used as nanoparticles. Moreover, this polymer can be applied directly to fruits and vegetables as a single ingredient or in combination with other substances in order to create edible protective coatings with bacteriostatic and fungistatic properties ,44,71. MActinidia melanandra fruits, whose storage stability increased after the application of gel coatings containing this polymer [Numerous reports have demonstrated the suitability of chitosan for storage purposes, as its properties help to enhance the stability and quality of stored products. One of the examples is the research on the effect of chitosan coatings on the shelf life and quality of plum fruit. The results of the experiment showed that the use of coatings containing 2% chitosan had a significant effect on the maintenance of the color, firmness, and weight of fruit stored at low temperature . Similar polymer . In an e polymer , the appPenicillium fungi. Moreover, the application of a chitosan-based formulation during the potato vegetation period was found to exert a limiting effect on the presence of Fusarium spp. and P. carotovorum subsp. carotovorum causing dry and wet tuber rot during storage [Acidovorax citrulli, which causes fruit blotch, was achieved in the case of watermelon seedlings [Botrytis cinerea. This was associated with both the direct antifungal activity of chitosan and the induction of a biochemical defense response in the fruit, which resulted in increased accumulation of phenolic compounds and enhanced activity of PPO [A study conducted by Tayel et al.  demonstr storage . A simileedlings . In turneedlings , the usey of PPO .2O2; synthesis of secondary metabolites , enzymes , and growth inhibitors ; and accumulation of lignin and callose. The effect of chitosan on plants is reflected in changes in the chromatin structure, the inhibition of H+-ATPase activity in the cell membrane, the activation of MAP kinases, and an increase in the cytosolic Ca2+ concentration [The potential for application of chitosan and its derivatives in the elicitation process is related to the biological activity of this compound, which primarily involves the ability to stimulate natural plant defense mechanisms and increase plant resistance to stress. This is associated with various types of physiological and biochemical changes, such as oxidative stress; accumulation of Hntration ,44,84. Entration . The effntration ,34.Curcuma longa [Stevia rebaudiana. The application of chitosan increased the biomass and concentration of phenolic compounds and rebaudioside A [Origanum vulgare ssp. hirtum demonstrated that the use of different concentrations of chitosan oligosaccharides  exerted a beneficial effect on plant growth and the content of polyphenolic compounds [Numerous research publications report the effectiveness of chitosan and its derivatives in the elicitation process. Studies on ma longa  indicateioside A . A fieldompounds .S. rebaudiana tolerance to salinity and reducing its phytotoxic effects on these plants. Similar results were obtained in an experiment conducted by Safikhan et al. [Silybum marianum. Furthermore, a study conducted in water deficit conditions showed that chitosan treatment of Salvia officinalis reduced the negative impact of drought stress. It also had a positive effect on the quantity and quality of essential oil, the total content of phenolic compounds and flavonoids, and the antioxidant properties of sage extracts [Ononis arvensis in in vitro conditions was demonstrated as well [Mentha piperita suspension cultures produced a significant increase in the accumulation of menthol [M. piperita with chitosan in greenhouse conditions increased the total content of phenolic compounds and flavonoids and enhanced the antioxidant activity of the extracts [Psammosilene tunicoides hair root cultures [Ocimum basilicum, O. sanctum, and O. gratissimum [O. basilicum indicated the effectiveness of chitosan elicitation in the stimulation of biomass growth, intensified accumulation of total phenolic and terpene compounds, elevation of rosmarinic acid and eugenol concentrations, and enhancement of antioxidant activity [O. basilicum and M. officinalis raw materials [The study conducted by Gerami et al.  suggesten et al. , in whicextracts . A stimu as well . A chito menthol . In turnextracts . Chitosacultures . Moreovetissimum . Other sactivity . The folaterials .The effects of the application of chitosan and its derivatives on the accumulation of secondary metabolites in selected plant species are shown in Due to the wide availability and a number of its beneficial properties, an increase in the number of potential applications of chitosan and its derivatives has been observed in recent years. Nevertheless, despite its numerous advantages, the practical commercial-scale use of this polymer is still limited by some of its physicochemical features and is dependent on progress in the development of optimal methods for chemical modification and adaptation of the polymer for specific applications. To date, the greatest success in this regard has been achieved in nanotechnology, which is regarded as one of the five most groundbreaking fields of science and technology of the last century ,104,105.One of the most important prospects for the use of chitosan in nanotechnology is the concept of sustainability of the agrochemical industry through the production of the so-called agronanochemicals. It mainly involves the preparation of chitosan nanoparticles and chitosan nanocomposites or encapsulation of active substances in chitosan-based nanocarriers. The preparations primarily exhibit high efficiency and bioavailability; hence, they can constitute a more economical environmentally friendly alternative limiting the amounts of currently available chemicals ,106,107.Coffea canephora [Eleusine coracana.Chitosan may exert a positive effect on plant photosynthetic efficiency, ability to biosynthesize and accumulate chlorophyll, and nutrient uptake ,108,109.anephora . Similaranephora , who fouCatharanthus roseus [−1) to bananas enhanced their tolerance to low temperature and improved biometric parameters via a reduction in the oxidative stress intensity [Various research results also indicate the possibility of using chitosan to increase plant tolerance to abiotic and biotic stress factors and mitigate their phytotoxic effects ,107,109.s roseus ,109. Thentensity . In turnntensity  reportedCapsicum annuum tissue cultures showed that a composite of zinc oxide and chitosan nanoparticles contributed to a significant increase in its elicitation efficiency [This polymer can also be used in combination with other compounds not only to extend the spectrum of its activity but also to produce materials with more favorable mechanical, chemical, thermal, and barrier properties ,107,114.ficiency .Chitosan nanoparticles can reduce the amount and frequency of application of plant protection products, ameliorate their negative effects, and help to monitor and remove their excess from soils and waters ,117. DueThe main applications of chitosan and its derivatives in plant production are summarized in Chitosan is an easily available environmentally friendly biopolymer with numerous favorable biological properties; hence, it has many applications in various fields. Additionally, it can be a potential solution to various ecological problems, especially in the production of plants by increasing their internal potential. Biodegradable and biocompatible chitosan and chitosan-based nanomaterials are becoming essential in agriculture due to their unique properties, such as biostimulating, eliciting, and antimicrobial activity and stimulation of plant growth and tolerance to environmental stresses. However, the use of other effective sources of chitosan, the methods for extraction and optimization of its physicochemical properties, and the practical implementation of laboratory results should be investigated comprehensively. Moreover, detailed studies on the potential toxicity of chitosan-based nanomaterials and the ecological consequences of their large-scale use are required. At present, these substances are not being widely used in agriculture, as the mechanisms of their biological activity in plants and action against pathogenic microorganisms have not been fully elucidated to date.


Sustained physical activity is recommended for secondary stroke prevention. Persons with stroke leave rehabilitation having learned exercises to reduce disability. However, once discharged, people may be on their own to navigate psychological, emotional, social, and physical challenges of maintaining those activities and starting new ones. The Health Action Process Approach (HAPA) provides a framework for understanding how self-efficacy differs depending on where a person is in the process of engaging in physical activity. The purpose of this study was to assess the qualitative fit of the HAPA model to the experience of exercise after discharge from formal stroke rehabilitation using a deductive (directed) content analysis approach. Interviews with 12 stroke survivors were analyzed deductively using the HAPA model concepts task self-efficacy, coping self-efficacy, and recovery self-efficacy to create the analysis matrix. In this sample, a period of psychological adjustment interfered with maintaining exercise and included anxiety, depression, embarrassment, and fear of falling that affected motivation and intention to exercise. Experiences with physical activity and exercise as a child and routines prior to the stroke were factors influencing task, coping, and recovery self-efficacy and ease of dealing with interruptions in exercise, including the discharge from formal rehabilitation. The findings support the qualitative fit of the HAPA model with the experience of exercise after having a stroke. A HAPA model framed intervention is being developed to support the transition from formal rehabilitation support to living in the community.


We developed and evaluated an interpersonal model of depression in employees, where passion and perseverance affect occupational stress and perceived control, which in turn affect risk of depression. The participants were employees of 18 private companies and local government organizations in Korea aged 19 to 65 years. A total of 11,422 participants completed questionnaires including the Korean version of the Grit scale, the occupational stress scale, the perceived control subscale in the perceived stress scale, and the Center for Epidemiologic Studies Depression Scale. Mediation analysis was performed to determine relationships among trait-level passion and perseverance, work-related stress, perceived control, and depression. Passion and perseverance preceded depression in employees. Higher occupational stress and lower perceived control mediated the association between passion and depression, and between perseverance and depression. Passion and perseverance exert preventive effects on depression by decreasing workplace stress and elevating perceived control. Future studies should investigate the effects of psychological characteristics on the development of depression in employees. The prevalence of major depression in South Korea is gradually increasing. Major depression is characterized by repeated depressive episodes and the inability to function normally during each episode. According to the Global Burden of Disease statistics  releasedGrit is defined as passion and perseverance to meet long-term goals , and alsSince grit has been considered as an important factor in coping with mental health pressure, several previous studies have examined the relationship between grit and various psychiatric symptoms such as depression, anxiety, insomnia, and suicidal thoughts. In a cross-sectional study on university students in Thailand , gritty In previous studies, grit was regarded as a personality trait and considered an individual’s characteristic that is not easily changed in normal conditions in adults . HoweverBoth types of grit, passion, and perseverance are inversely related to occupational stress and depression, and positively related to perceived control in employees.Higher levels of occupational stress are associated with more severe depression and greater perceived control has a protective effect against depression in employees.Occupational stress and perceived control mediate the relationship between grit and depression in the workplace.Hence, in this study we investigate the relationship between grit already formed as an adult and depression in the workplace, and whether occupational stress and perceived stress underlie the relationship between grit and depression. Our hypotheses were as follows:The study participants were male and female workers who underwent workplace mental health screening at the Workplace Mental Health Institute of Kangbuk Samsung Hospital, Seoul, Republic of Korea, between April 2020 and March 2022. This study included participants over 19 at the beginning of the study in order to involve legal adults, and participants under 65 to prevent the effects of cognitive decline. The subjects were office or manufacturing-facility workers at one of the country’s 18 public institutions or large companies who voluntarily participated in mental health examinations upon invitation from their companies. Among the initial 12,344 respondents, only 11,422 (7750 men and 3672 women) participants who completed questionnaires and sociodemographic information were included in the final analysis.The participants included employees of 2 companies (126 participants) in the field of manufacturing; 2 companies (1668 participants) in the field of transportation and storage; 5 companies (3575 participants) in the field of financial and insurance activities; 1 public institution (903 participants) in the field of education; 1 company (960 participants) and 346 other participants in the field of human health and social work activities; 1 company (57 participants) in the field of arts, entertainment, and recreation; 1 company (2933 participants) in the field of other service activities; and 5 companies (1775 participants) in the field of public administration and defense, and compulsory social security .All study procedures were approved by the Institutional Review Board of Kangbuk Samsung Hospital and adhered to the latest version of the Declaration of Helsinki and principles of Good Clinical Practice . The requirement for informed consent was waived because only de-identified data routinely collected during health screening visits were used.We collected socio-demographic data including age, gender, level of education , and marital status . Job-related demographic factors were also collected, including duration of work at the current workplace (years), hours of work per week, and monthly earned income.Grit was assessed with the eight-item Short Grit Scale , an eighOccupational stress was assessed using the Short Form of the Korean Occupational Stress Scale-Short Form (KOSS-SF) , a 24-itDaily perceived control was measured using the positively worded items of the Korean version of the 10-item Perceived Stress Scale (PSS) , which mDepressive symptoms were assessed using the Korean version of the 20-item Center for Epidemiological Studies Depression (CES-D) scale . It is aWe conducted descriptive analyses of the demographic characteristics and correlation analyses of the four variables. To test the first and second hypotheses, Pearson correlations were performed for the scales to assess the direct associations between grit and depression and to support the associations between occupational stress and perceived control with the other variables: grit and depression. The mediation model was analyzed using Model 4 in the PROCESS Macro in SPSS, developed by Hayes . Bootstrp  <  0.001) and perceived control , and inversely associated with occupational stress  and depression . Perseverance was positively correlated with perceived control  and negatively associated with occupational stress  and depression . Occupational stress was negatively correlated with perceived control  and positively associated with depression . Perceived control was negatively correlated with depression . There were significant positive inter-correlations between scores of subscales of KOSS. Passion, perseverance, and depression were inversely associated with all subscale scores of KOSS  are presented in  of KOSS .As age, sex, degree of education, marital status, years of service, hours of work per week, and monthly earned income were significantly associated with depression in the workplace, these variables were controlled in mediation effect evaluations. The PROCESS macro developed by Hayes  was usedThe significance of the mediating effects was tested using a bootstrap method. p < 0.001) and perseverance  on depression remain significant. These results suggest that the subtest score items of KOSS partially mediate the relationship between grit and depression.We further explored the mediating effects of the eight subtest scores of KOSS on the relationship between grit and depression. As seen in To our knowledge, this is the first study to investigate the protective effects of passion and perseverance against depression and the mediating roles of occupational stress and perceived control in the relationship between passion and perseverance with depression among employees. Our findings demonstrate that high levels of passion and perseverance lead to lower occupational stress and a higher level of perceived control, thereby protecting against the onset of depression. We also demonstrated that among the various occupational stresses measured by KOSS, lack of reward had the greatest mediating effect between passion and perseverance with depression, whereas difficult physical environment had no significant mediating effect on either path. We found that occupational stress mediates the relationship between grit and depression. These results are consistent with previous findings ,31 that Our exploratory investigation showed that high job demands, interpersonal conflict, job insecurity, organizational system injustice, lack of reward, and discomfort in occupational climate were individually partial mediators in the grit-depression relationship. In particular, among occupational stress, lack of reward showed the greatest mediating effect and difficult physical environment showed no significant effect on the grit-depression relationship. Insufficient job control had no significant mediating effect on the negative correlation between persistence and depression. This result is similar to that of a previous study  that exaIn mediating the relationship between passion and depression, insufficient job control of occupational stress had little effect compared to other types of stress, and there was no significant mediating effect of insufficient job control on the relationship between persistence and depression. However, perceived control was found to significantly mediate between both types of grit and depression. This suggests that the cognitive appraisal of controllably recognizing a stressful situation rather than the stress itself is important for predicting the occurrence of depression. This result is in line with those of previous studies ,39 whichThis study had several limitations. First, since only participants in the workplace mental health examination at Kangbuk Samsung Hospital were included in the study, there may be limitations in generalizing this to all workers. However, our sample includes a variety of occupational groups, unlike many previous studies that focused on specific occupational groups. Second, because of its cross-sectional nature, longitudinal trajectories of changes in depressive symptoms could not be determined in this study. Specifically, the mediators could be covariates rather than mediators . Thus, lDespite the limitations of the present study, this was the first investigation of potential mediators of the association between grit and depression in employees. These findings serve as a solid foundation for future studies designed to understand the specific mechanisms underlying grit and depression. Based on our data, forming high levels of grit in adolescence and early adulthood may be important for reducing stressful experiences in the work environment and for maintaining mental health. Along with perceived control, which showed a greater mediating effect on the relationship between grit and depression than the stress caused by insufficient job control, clinical intervention strategies for employees will be more effective when focusing on cognitive therapies aimed at modifying cognitive appraisals.