Cognitive deficits are one of the important clinical features of patients with brain tumours, which can affect up to 30–90% of patients before treatment. The consequence is a significant and rapid degradation of the patient’s intellectual functioning, seizures, paralysis and other symptoms that prevent independent functioning. This results in a reduced quality of life and a psychological crisis not only for the patient but also for their relatives. Maintaining the patient’s function at the highest level for as long as possible is particularly important, given that long-term remission or a cure is unlikely or accompanied by significant disability.This paper aims to provide a narrative review to the neuropsychological procedure for monitoring cognitive function in patients with brain tumours, which may be helpful in developing adequate clinical practice and appropriate management procedures.A narrative review was applied to search broadly across disciplines, retrieving literature from several databases .(1) discussing the methodological aspects of neuropsychological tools for monitoring cognitive function in brain tumour patients, (2) identifying the most commonly used tools and (3) their practical applicability according to the cognitive function components of the International Classification of Functioning, Disability and Health (ICF).This article points to the need to systematise research tools or develop new ones, adapted to diagnostic needs with high psychometric characteristics, with particular attention to memory processes and learning effect. Rehabilitation of patients is also an important issue, which requires the use of adequate tools to assess functional disability. The International Classification of Functioning, Disability and Health (ICF) seems to be useful in this respect. The ICF has the advantage of targeting actions to improve the condition of the individual and to keep them as long as possible in a state of well-being that allows them to function effectively in society or to return to work. This is particularly important in view of the ageing population and the increasing number of diagnoses related to brain tumours. The degDepending on the area in which the tumor is located, the patient presents certain, specific deficits in cognitive and other areas . A tumorGenerally, the consequence of the brain tumours is a significant and rapid degradation of the patient’s intellectual functioning, seizures, paralysis and other symptoms that prevent independent functioning. This results in a reduced quality of life and a psychological crisis not only for the patient, but also for their relatives. In this context, maintaining the patient’s function at the highest level for as long as possible is particularly important, given that long-term remission or a cure is unlikely or accompanied by significant disability .National Cancer Institute (NCI) Brain Tumor Progress Review Group recommends that the routine assessment of cognitive ability and quality of life (QOL) should become the standard of care for patients with brain tumours. Unfortunately, monitoring presents many difficulties in clinical practice, and one of the key issues is the lack of a consistent methodological framework for conducting the study. Neuropsychological assessment is challenging as it requires knowledge of several disciplines, including knowledge of clinical interviewing, neuroanatomy and neuropsychological symptoms. Knowledge of test administration and interpretation and psychometrics is also required. The selected measures of cognitive functioning should be psychometrically sound, with established reliability as well as validity and appropriate normative tests  discussing the methodological aspects of neuropsychological tools for monitoring cognitive function in brain tumour patients, (2) identifying the most commonly used tools and (3) their practical applicability according to the cognitive function components of the ICF.2.2.1.Assessment of cognitive function is an important and necessary part of the contemporary, comprehensive oncology care for cancer patients especially with brain tumours. Cancer-related cognitive impairment may result from the direct effects of the cancer itself, non-specific factors or comorbidities that are independent of the disease or result from adverse effects of treatment or treatment combinations used in conjunction with the disease. The prevalence and extent of cognitive impairment associated with cancer are known but not well understood, in part due to significant differences in the research methods and definitions used to assess cognitive functioning in these patients .A properly applied research method should be based on the possibility that there is a reliable relationship between observable behavioural changes and the presence of a focal region of brain damage with a specific anatomical position. Procedural errors, such as the use of inappropriate neuropathological samples or inappropriate composition of study groups, can severely limit the usefulness of the method .Despite a large increase in the number of clinical trials, cognitive decline is difficult to study in patients—not only for methodological reasons but also because of the relatively small sample sizes, differences in the patients’ age, the nature and location of the tumour(s), additional anticancer treatment  and the intensity of adjuvant treatment . There iIn most clinical trials involving adult patients with brain tumours, assessment of cognitive function is based on performance status, mental status examination, patient complaints and clinical observation . These mTherefore, it is important to use neuropsychological tests that are sensitive to mild changes in cognitive function, have multiple versions or are robust to learning effects. Mood and QOL scales and assessment of estimated pre-disease intelligence quotient (IQ) should also be used here. In turn, given the need to minimise the effects of fatigue, sessions should be short and not exceed 1  hour. In addition, to guarantee data quality and consistency between medical centres, training and certification of professionals involved in test administration and supervision by a neuropsychologist are essential .Neuropsychological supervision should concern not only the knowledge of reliability, validation and appropriate use of tests but, above all, the ability to interpret their results. Interpretation of the test results is a complex process, as many factors—both on the patient’s side and contextually—can influence the result obtained. For example, in a memory function test situation, it is not only the patient’s attention, language or executive functioning that influences the result, but also the level of stress or fatigue experienced.Understanding the above issues regarding the test and patient factors that may undermine the reliability of test results plays a key role in the reliability and safety of the testing procedures performed .2.2.The traditional outcome measures used in brain tumour research include the overall and recurrence-free survival of patients and, in some cases, respond to treatment with chemotherapy and radiotherapy. Such an analysis of the treatment outcomes usually neglects the aspects related to patients’ quality of life and the biological response to treatment. From a practical point of view, these issues are important in two situations: (1) for brain tumours, where there are currently no effective treatment therapies; (2) for tumours detected in children, where tumour control is linked to the possibility of the disease being considered chronic. Improved measurement tools would allow for the rapid rejection of potentially neurotoxic therapies and continuation of effective therapies .In the context of research questions about the prospective neurocognitive testing of patients, it is, therefore, important to consider: (1) pre-treatment cognitive problems to establish a baseline; (2) data showing which treatment regimens improve neurocognitive function, slow down the expected deterioration or have neurotoxic effects in the shorter and longer term. Neurocognitive diagnostics are also important for diagnostic differentiation  in order to optimise treatment and therapeutic intervention . RegardiStudies show that, for the diagnosis of primary brain tumours, extensive surgical resection has a survival benefit , and aftThe treatment of brain tumours with chemotherapy is of limited use, which is related to low primary chemosensitivity, early secondary chemo-resistance, the presence of the blood–brain barrier and the neurotoxicity of some cytostatic drugs and their adverse interactions with other drugs . It is estimated that, among patients receiving chemotherapy, between 13 and 70% exhibit measurable cognitive impairment), some of which may be present even before treatment , 2011a. The pathophysiological mechanisms of chemotherapy-induced CNS damage are not well understood but are thought to include microvascular damage, demyelination and a secondary inflammatory response. Acute neurotoxicity may occur during or shortly after treatment with chemotherapy  and fatiMost of the possible complications after chemotherapy pass quickly and do not damage the body. Only a small proportion may be life-threatening  or permanent . Such situations require the application of appropriate treatment as well as adequate preventive measures .An alternative or complementary treatment for patients with brain tumours is radiotherapy. It is often used postoperatively as adjuvant therapy to reduce the risk of local failure, delay tumour progression, prolong survival  and sometimes as preoperative treatment to avoid serious neurological consequences of surgery . IonisinPatients undergoing RT to the brain often experience radiation-induced fatigue and headache as well as possible cognitive impairment. It has been shown that whole brain radiotherapy (WBRT) can exacerbate fatigue .Irradiation can lead to significant but mostly transient cognitive impairment (50–90% of patients), occurring in the acute (during irradiation), subacute: early-delayed (in the first months after irradiation) and late (many years after irradiation) phases. Acute and early adverse effects are thought to be transient, whereas late damage may be a risk factor as the associated cognitive impairment may be irreversible and progressive .Some anatomical and functional structures, such as the white matter, hippocampus, cerebellum or temporal and frontal lobes, appear to be sensitive to radiation in human and animal models. The deterioration of their integrity during RT is partly correlated with induced cognitive impairment .The subacute toxicity effect is associated with the impairment of information processing, attention, verbal memory, executive functioning and motor skills. Alterations in the white matter are responsible for this, and its recovery after RT may lead to improvements in these functions over time.The risk factors for the development of cognitive impairment due to irradiation include: an age less than 5 years or greater than 60 years, dose greater than 2 Gy per fraction, higher total dose, hyperfractionated regimens, shorter total treatment time, presence of concurrent vascular risk factors, concurrent or subsequent treatment with chemotherapy and larger total volume of the irradiated brain . Long-teReducing the risk of cognitive difficulties is possible by using less invasive irradiation techniques  and sparing the hippocampus during irradiation . In addiIndependent of the ongoing research into the development of more effective standard causal treatments, supportive treatment plays an important role in the management of brain tumour patients, aimed at controlling symptoms and side effects directly or indirectly caused by the tumour. Adjuvant treatments used in this group of patients include the following adverse reactions: brain oedema around the tumour site, venous thromboembolism (VTE), seizures, depression and opportunistic infections.Pneumocystis jiroveci pneumonia), osteoporosis, psychiatric disorders and adrenal insufficiency. In turn, the use of antiepileptic drugs may cause a decrease in cognitive function, which suggests caution in the selection of these preparations in the treatment process  strongly recommends that longitudinal studies with repeated assessments should be conducted whenever possible to monitor changes in cognitive functioning. Cross-sectional studies, only after treatment, with appropriate comparison groups may be useful for exploratory analysis, hypothesis generation and proof-of-concept trials, with the confirmation of results in longitudinal studies . In the Preoperative assessment that it may be necessary to assess the impact of cancer and its treatment on cognitive function  but may In addition, the wide range of potential factors that may influence lower than expected cognitive performance before treatment has not yet been precisely identified. According to the researchers, cognitive impairment before treatment does not appear to be explained by factors such as depression, anxiety or fatigue . On the As many patients receive a variety of anticancer therapies , the outcome of cognitive function testing is in practice the effect of the combination treatment. In theory, the efficacy of a specific treatment could be assessed, but this would require the timing of drug administration in specific groups while assessing a comparison group. Findings from clinical treatment indicate that ideal comparison groups may not exist for the type of cancer or treatment of interest .2.4.2.The selection of the patient population to be studied depends on the research question posed at the outset. The exclusion criteria determine the subsequent interpretation of the causes of cognitive changes. On the one hand, they may be caused by anticancer treatment—after excluding all other conditions or drugs that could affect cognitive functioning. On the other hand, the study involves patients and controls with comorbidities, e.g., hypertension, diabetes melitus and systematically taking the prescribed medication. A significant challenge and dilemma are the group of patients currently taking selective serotonin reuptake inhibitors (SSRIs). Antidepressants and SSRIs have been shown to affect cognitive performance . GPs andFor most clinical trials, it is recommended to create several control groups—disease-specific and healthy controls —that undergo the same cognitive assessments at the same time as the study group. This approach may help to determine whether cognitive impairment is present and whether the apparent changes in cognitive function are due to a practice effect  or are secondary to the cancer itself, treatment or both. In a non-randomised study, the disease-specific group is likely to consist of patients with the same cancer who are receiving a different anti-cancer treatment .It is not easy to collect a sufficient number of patients for the study to provide a basis for reliable statistical analysis and a comparison of the treatment regimens. One of the proposed solutions is to conduct the study within several institutions, where employed neuropsychologists would control the quality of procedures and data analysis.Studies can also be conducted in the context of cooperative group studies. In this approach, a large number of patients who meet similar inclusion and exclusion criteria are randomised to a standardised treatment. A weakness of this approach is the risk of maintaining a low level of quality control and consistency in the conduct of neuropsychological assessments. Nevertheless, several studies of this type have been conducted as part of Radiation Therapy Oncology Group studies, and the results obtained may serve as a model for further work .Analysing the issue of research into the cognitive functions of patients with brain tumours, it is assumed that further analysis of the pathophysiological mechanisms of cognitive deficits is necessary in order to adequately target interventions. The same is true for intervention studies which, based on preliminary indications of efficacy, using appropriate methodology and multivariate statistics, minimise the risk of errors of the first kind. Treatment and rehabilitation programmes aimed at alleviating other common symptoms of cancer, such as fatigue, may also be beneficial in treating cognitive symptoms and deficits. On the other hand, effective treatment of cognitive deficits may benefit other areas of functioning and patients’ quality of life.3.The selection of test kits to assess the neurocognitive status in clinical trials is difficult due to competing demands for brevity and sensitivity. Some patients undergoing treatment with chemotherapy and radiotherapy show increased levels of fatigue and decreased motivation to perform tasks—especially long and complex tasks. Adequate brevity of the test reduces patients’ endurance requirements and provides time to measure other outcomes.Short test batteries are also more economical and they keep the testing costs at a reasonable level, while longer batteries offer greater sensitivity in detecting cognitive impairments and changes. When preparing for clinical trials, researchers typically try to select test batteries from multiple cognitive domains , but also those that are sensitive to generalised dysfunction. This is an attempt to detect potential focal changes due to the effect of the cancer as well as to detect more generalised dysfunction that may be due to drugs or other factors. The selection of appropriate tests for clinical trials is further complicated by the heterogeneous patient population with varying tumour extent and locations and, therefore, associated cognitive symptoms .delirium or significant dementia. The MMSE has also been found to have very low sensitivity in detecting neurocognitive problems in patients with brain tumours. Self-reporting of cognitive problems  is also controversial. Because of cognitive impairment, patients often rate their cognitive problems as worse. Furthermore, as studies indicate, in other cancer patient populations, self-reported cognitive impairment correlates much more strongly with fatigue and depression than with tested cognitive parameters  are often available. However, these are considered problematic in the investigation of brain tumour patients as they only detect rameters .According to There are a few studies that examine cognitive assessment tools that have been described in systematic reviews. Most of these focus on describing which tools are most commonly used to assess people with a brain tumour diagnosis over the age of 18 years. The cognitive functions most commonly included in studies of patients with brain tumours include memory and learning, working memory for visual and auditory modalities, verbal fluency, processing speed and executive functions .Another study  analysedComparing multiple studies shows that many different tests are currently used to measure the same functions, which, in the context of conducting reliable clinical trials or rehabilitation, introduces a number of complications and inaccuracies.312 articles on cognitive function testing in patients diagnosed with glioma were analysed by In an effort to understand how cancer and its treatment interact with adult patients’ cognitive-behavioural functions, the International Cognition and Cancer Task Force (ICCTF) was established in 2006 to study cancer patients’ congenital disorders . This teThe ICCTF has also identified recommended cognitive assessment tools depending on the cognitive area of interest to the researcher. In the area of Learning and memory, the recommended tool is the Hopkins Verbal Learning Test-Revised (HVLT-R) and similar tools include the California Verbal Learning Test—II (CVLT-II), Rey Auditory Verbal Learning Test (RAVT), Brief Visuospatial Memory-Revised . The tasks performed by the patient consist of learning from a list of concepts, immediate and deferred recall, and recognition. For executive function, the recommended tools are Trail Making Test and Controlled Oral Word Association (COWA), as an alternative the Delis-Kaplan Executive Function Scale (D-KEFS) Trail Making or Delis-Kaplan Executive Function Scale (D-KEFS) Verbal Fluency is suggested. Tasks in this area examine a range of cognitive skills involved in performing tasks relating to attention, working memory, speed of information processing and mental flexibility as well as spontaneous word generation. Processing speed according to the ICCTF should be tested using the Trail Making Test or alternatively the Delis-Kaplan Executive Function Scale (D-KEFS) Trail Making, Wechsler Adult Intelligence Scale-IV (WAIS-IV) Coding, Symbol Digit Modalities Test (SDMT), while the cognitive skills tested here include Multiple cognitive skills involved in performing a task, including attention, working memory, information processing speed, and mental flexibility. Working memory is recommended to be measured by the Auditory Consonant Trigrams , Paced Auditory Serial Attention Test , Brief Test of Attention , and Wechsler Adult Intelligence Scale -IV (WAIS-IV) Letter Number Sequencing .There is a need to systematise cognitive testing tools. Currently, there is a wide variety of tests measuring the same or similar cognitive parameters. Tests should cover many areas, but this depends on the type of research being conducted, e.g., treatment process, cognitive rehabilitation, clinical trials with experimental and control groups.4.In addition to the need for the reliable assessment of cognitive function in patients with brain tumours, their rehabilitation and the consequent need for functional disability assessment is an important issue . There aThe International Classification of Functioning, Disability and Health (ICF) was introduced by the WHO in 2001 as a comprehensive coding system for functioning and disability. It creates a new conceptual framework for disability and provides a “common language” for all professions. Since then, the classification has continued to be improved and disseminated, and more countries have signed a convention to implement it. The ICD-10 and the ICF are complementary and users are encouraged to use them together: the ICD-10 provides a ‘diagnosis’ of diseases, disorders or other health conditions and the ICF complements this information in terms of the functioning of the individual. The ICF can also serve as an epidemiological tool and allow the collection and comparison of disability data from different countries with different legislation, definitions of disability, standards of living and welfare policies.The ICF consists of two parts—the first is “Functioning and Disability” and the second describes “Contextual Factors” . “FunctiIn terms of the tools used to objectively measure cognitive function, they included: MMSE, ACE-III, TMT A and B, CTT, CVLT, WSCT; Benton test, Stroop test, while among the tools for subjective self-assessment regarding quality of life, EORTC QLQ-C30 and EORTC QLQ- BN20 were selected. Among the neuropsychological assessment tools, the MMSE and TMT are among the most commonly used in the diagnosis of people with brain tumours, with the psychometric properties of the MMSE being better documented . In the EORTC QLQ-C30 questionnaire contains five scales assessing functional status, relating to: physical functioning, social role performance, emotional functioning, memory and concentration, social functioning as well as three scales assessing disease symptoms: fatigue, nausea, vomiting and pain as well as an overall health/quality of life rating scale. In addition, it includes six single questions assessing illness symptoms such as loss of appetite, shortness of breath, insomnia, constipation, diarrhoea and financial difficulties as a consequence of illness  and monitoring of the course of the disease. However, it is indicated that it should not be used as a stand-alone diagnostic tool to identify dementia (dementia .Addenbrooke’s Cognitive Examination-III (ACE-III) is a test that assesses five core areas of cognitive functioning: attention, memory, verbal fluency, language function, and visuospatial function. Tasks assess orientation functions, perception, thinking, computational functions and sequencing of movements. The test is a new version of Addenbrooke’s Cognitive Examination-Revised (ACE-R). The overall test score ranges from 0 to 100, with higher scores indicating better cognitive functioning. The ACE-III takes an average of 15 min to complete, which is important in the context of testing patients who exhibit elevated levels of fatigue ( fatigue . The ACE fatigue  and diff fatigue . The sca fatigue .Trail Making Test/Test of Connecting Points A and B (TMT A and B) assesses visuospatial aspects of working memory, general attentional efficiency, search-field functions, thinking functions and in particular interhemispheric functioning. The TMT consists of two parts: in part A, the patient combines consecutive numbers; in part B, the patient alternates between consecutive numbers and letters of the alphabet. The result of the tests is the time needed to draw the path correctly. If the time to complete TMT B is twice as long as the time to complete TMT A, this is considered to indicate frontal cortex dysfunction  is a test used to examine a variety of intellectual processes related to attention and executive functions, and in particular to assess the purposeful searching of material, sustained and metastatic attention, sequential processing of information, thinking and monitoring of one’s own behaviour. Visual-motor skills are also involved in performance. CTT is a test similar to TMT—it also consists of two parts—in the first part of the test the respondent has to connect coloured circles with numbers from 1 to 25 in the shortest possible time. In the second part of the test, the respondent is instructed to connect alternating numbers with colours (most often pink and yellow are used). The result is the execution time, the number of hints, the number of mistakes in the order of colours and numbers. The maximum time for each part of the test is 4 min. The test demonstrates high reliability in terms of absolute stability of the indices, high constancy of clinical interpretations, and confirmed diagnostic accuracy by means of intergroup comparisons, which involved people with different locations and different aetiologies of brain damage  is used to measure attention, the ability to learn and remember verbal material, and the mental functions of language. It consists of three lists of words: List A, List B and a list of words to be recognised. Lists A and B each contain 16 categorically related words. The recognition word list contains 44 stimuli including the whole List A, some words from List B, and other distractor words fulfilling certain conditions. A limitation of the test is its long execution time (approximately 60 min), which may be difficult for patients with increased levels of fatigue. Moreover, the CVLT has only one version and the study of the dynamics of changes in memory functioning is in its case burdened with the risk of the re-presentation of the same material. The reliability and validity of the test has been confirmed, showing proven correlations with measures of cognitive function and confirmed diagnostic accuracy using intergroup comparisons  is considered to be a diagnostically specific tool for assessing working memory and, in addition, for evaluating executive function disorders and problem solving skills. The performance of this type of test requires a complex pattern of functioning that takes into account instructions and goals, taking into account current experience and feedback as well as planning a specific strategy  seems to be useful in this respect. The ICF has the advantage of targeting actions to improve the condition of the individual and to keep them as long as possible in a state of well-being that allows them to function effectively in society or to return to work. This is particularly important in view of the ageing population and the increasing number of diagnoses related to brain tumours.6.The article can be useful for summarizing the literature. However, the nature of any narrative review is subjective in the determination of which studies to include, the way the studies are analyzed, and the conclusions drawn. There is possibility of misleading in drawing conclusions that are normally due to selection bias, subjective weighing of the studies chosen for the review, unspecified inclusion criteria, and failure to consider the relationships between study characteristics and study results.AgP has given substantial contributions to the conception or the design of the manuscript. KH and AnP to acquisition and interpretation of the data. AgP, AnP, and KH have participated to drafting the manuscript. KH revised the manuscript critically. All authors have read and approved the final version of the manuscript.This research was funded by Grant NCN-OPUS 19: UMO-2020/37/B/NZ7/01122.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.


Studies evaluating the local quality of death certification in Brazil focused on completeness of death reporting or inappropriate coding of causes of death, with few investigating missing data. We aimed to use missing and unexpected values in core topics to assess the quality of death certification in Brazilian municipalities, to evaluate its correlation with the percentage of garbage codes, and to employ a data-driven approach with non-linear models to investigate the association of the socioeconomic and health infrastructure context with quality of death statistics among municipalities. This retrospective study used data from the Mortality Information System (2010–2017), and municipal data regarding healthcare infrastructure, socioeconomic characteristics, and death rates. Quality of death certification was assessed by missing or unexpected values in the following core topics: dates of occurrence, registration, and birth, place of occurrence, certifier, sex, and marital status. Models were fit to classify municipalities according to the quality of death certification . Municipalities with poor quality of death certification (43.9%) presented larger populations, lower death rates, lower socioeconomic index, healthcare infrastructure with fewer beds and physicians, and higher proportion of public healthcare facilities. The correlation coefficients between quality of death certification assessed by missing or unexpected values and the proportion of garbage codes were weak (0.11–0.49), but stronger for municipalities with lower socioeconomic scores. The model that best fitted the data was the random forest classifier . This innovative way of assessing the quality of death certification could help quality improvement initiatives to include the correctness of essential fields, in addition to garbage coding or completeness of records, especially in municipalities with lower socioeconomic status where garbage coding and the correctness of core topics appear to be related issues. Functioning civil registration and vital statistics (CRVS) systems provide comprehensive, timely, reliable, continuous, permanent, and up-to-date population and mortality statistics enabling governments to deliver health and social development programs more effectively. Despite their recognized importance for population health, progress in the quality of CRVS systems around the world has been slow, with many low-income and middle-income countries still lacking adequate mortality systems covering their whole population and registering reliable cause of death information. However, some low-income and middle-income countries have conducted CRVS improvement initiatives resulting in substantial progress , 2.In Brazil, the Ministry of Health’s Mortality Information System (MIS) has been collecting and providing death statistics since 1975 . In receMoreover, subnational disparities in the quality of death statistics are still of concern, with poorer performance in many states from the North and Northeast regions and municipalities in all regions , 15, 16.Although completeness and causes of death are key components to assess the quality of death reporting, additional information from death certificates is also relevant to produce accurate statistics. The United Nations recommends core topics to be investigated for death statistics purposes related to characteristics of the event and the decedent . To the Towards the goal of assessing the association of municipality socioeconomic and health infrastructure context with the observed outcome, we employed a data-driven approach. Traditional linear models present strong assumptions about the underlying data, such as linear relationship between dependent and independent variables as well as the absence of multicollinearity. As socioeconomic variables in Brazilian municipalities are highly correlated , we chosftp://ftp.datasus.gov.br/dissemin/publicos/SIM/This retrospective study was conducted mainly with data collected from the Brazilian Mortality Information System and included death certificates registered between 2010 and 2017. This is a disidentified and publicly available database administered by the federal government, therefore this study was not submitted for ethical approval. All analyses were performed in Python 3.7 and the Mortality Information System database can be accessed through this link: We assessed the quality of death certification based on the occurrence of missing or unexpected values on MIS variables that represent the core topics recommended by the United Nations to be investigated for death statistics purposes . We inclhttps://opendatasus.saude.gov.br/dataset/geoses. Inference with confidence intervals and hypothesis tests was not performed, given that the study included the whole “population” of death certificates and municipalities [Death certificates with missing or unexpected values in one or more core topics were considered of poor quality, and the total percentage of poor-quality certificates was calculated for each municipality. Also, we assessed the percentage of garbage coding in each municipality. Garbage codes refer to all deaths assigned to codes that should be redistributed to enhance the validity of public health analysis. We used the list of codes proposed by Naghavi et al, which was based on the Global Burden of Disease Study from 2010 . This lipalities .http://www.atlasbrasil.org.br.Municipal death rates (per 1000 population) included in the predictive models, were obtained by dividing the number of deaths reported in the MIS in 2010 by the number of inhabitants, which was extracted from the 2010 Demographic Census performed by the Brazilian Institute of Geography and Statistics. This database is publicly available and can be accessed through this link: Socioeconomic municipal characteristics included in the predictive models  were derived from the GeoSES. For the present analyses, the values of the dimensions “education” and “deprivation” were multiplied by –1 to facilitate their interpretation, since to compose the index, “education” was explained by people without instruction, and “deprivation” was explained by car ownership .ftp://ftp.datasus.gov.br/dissemin/publicos/CNES/. The following municipal indicators were included in the predictive models: number of physicians/1000 population, number of hospital beds/1000 population, percentage of healthcare facilities that provided care through the Brazilian Universal Health System, and percentage of healthcare facilities that had emergency departments. The total population of each municipality was extracted from the 2010 Demographic Census.Hypothesizing that health infrastructure could also be related to the quality of death certification, we collected information on municipal healthcare services infrastructure from the 2010 National Healthcare Facilities Registry (CNES). The CNES is a publicly available national database containing information on the installed capacity and health human resources of all Brazilian healthcare facilities, which can be accessed through this link: Classification models were built to predict the quality of death certification as the dichotomous target variable , having municipalities as the units of observation. Predictive models were chosen to better fit the multivariate, non-linear data. To create the dichotomous target variable, municipalities were classified as having poor quality of death certification if the percentage of death certificates with missing or unexpected values (correct entries) for any core topic was ≥80%. This threshold was empirically defined based on the median percentage of all municipalities. The following steps, described in further detail below, were employed to build models, select and evaluate the model with the best performance: data splitting, grid search, assessment of metrics from multiple models, and assessment of features importance and residuals from the best performing model.Data splitting: The data was initially split into three different sets: 70% for training, 15% for validation, and 15% for testing. To avoid overfitting, the training set was further split within the grid search, which consisted of a 5-fold cross-validation iterator with non-overlapping groups. Data splitting respected the Brazilian division of health regions, therefore municipalities belonging to the same region were not separated . This waGrid search: A grid search technique was used to automatically split the data and assess a set of various linear and non-linear models. Linear models (logistic regression and stochastic gradient descent) and support vector machines were coupled with a standardization preprocessing step, while tree-based models  received the raw data directly. Hyperparameters used in each model can be seen in the Metrics: The main metric used to select the best model was the area under the ROC curve. In the context of predictive modeling, it provides an overview of the true positive and false positive rates with respect to the threshold probability chosen for the model. A value of 0.50 is used as a reference for a random estimator, while a perfect model would present a value of 1.0. The precision-recall curve, which assesses the true positive rate and the positive predictive value, was also obtained for the different model probabilities. Its reference value for a random model depends on the proportion of classes in the model, which resulted in a value of 0.47 for the final selected model. To further evaluate the model performance, histograms were used to explore the distribution of test samples per class and the predicted probability by the model. For a given probability threshold  fixed for the model, the ratios of positive and negative outcomes were assessed toward the expected classification.Features importance: The Shapley Additive exPlanations (SHAP) was used to understand the contribution of each feature to the final predictive model, as it provides additional insight on the direction of the feature values and the respective impact on the model output .Residuals: The residuals of the model’s predictions were computed as the difference between the observed value  and the model predicted probability (between 0 and 1) for the poor quality of death certification. These estimates were used to identify municipalities with socioeconomic and health infrastructure characteristics that, according to the model, were incompatible with the quality of death certificates.https://github.com/GuilhermeZimeo/quality-death-cert).The scripts used to run the models and reproduce the results using the publicly available databases can be found in . The distribution of death certification quality per municipality can be visualized in Municipalities with poor quality of death certification presented larger populations, lower death rates, lower scores for socioeconomic characteristics, and healthcare services infrastructure with fewer beds and physicians, with a higher proportion of healthcare facilities that provided care through the Brazilian Universal Health System, when compared to municipalities with good quality of death certification , howeverThe distribution of death certificates with missing or unexpected values for each core topic among municipalities can be found in Overall, correlation coefficients between percentages of poor quality of death certification and percentages of garbage codes were weak, with a non-stratified coefficient of 0.33. In the stratified analyses , correlaThe predictive model returned from the grid search as the best estimator was the random forest classifier consisting of 1,000 decision trees, each of them with a maximum depth of 10. The details of all fitted models can be found in The performance of the random forest model for a fixed probability threshold of 0.50 can be visualized in The SHAP results  showed tThe distribution of the calculated residuals for the random forest model can be seen in CRVS systems should aim for the highest quality in terms of completeness, correctness, availability, and timeliness, which depends on the implementation of processes for quality assurance and assessment, including the measurement of entry correctness. More specifically, in order to target efforts to improve the utility of death certification data for policy, it is important to first recognize key errors, which has been mainly focused on the correctness of codification of causes of death. However, other entry fields are also considered as core topics and their evaluation, including the frequency of missing or unexpected values, could bring additional insights regarding the quality of death certification.Since the 1980s, Brazil has registered a steady improvement in the quality of death certification, which was achieved by interventions aimed at increasing the completeness of death registration and improving cause-of-death certification . In 1996As of 2016, the Ministry of Health started to work with the concept of garbage codes to improve information quality on the underlying cause of death. This term refers to a concept introduced in the first Global Burden of Disease study. By definition, Garbage Codes are causes of death that would not be the underlying ones or would be unspecific, being, therefore, of little use for public health . It is wStill, in 2016, the Ministry of Health joined the Data for Health Initiative, at the invitation of Bloomberg Philanthropies, which aimed to improve the lives of populations by improving the quality of information on mortality and using this information to formulate health policies. There were four priority interventions: to reduce the proportion of garbage codes in mortality statistics, through the investigation of deaths; to validate and introduce a reduced form for the application of verbal autopsy for deaths without medical assistance or with ill-defined causes of death; to develop a free mobile application in order to assist medical professionals in the correct death certification; to introduce the Iris software for coding the causes of death declared in the death certificate and automatic selection of the underlying cause in the MIS online module [Despite these advances in the last decades, the quality of mortality data has been shown to vary among Brazilian regions and municipalities , 15, 16,Sex and age were among the core topics that presented good quality for most municipalities and are the same variables that compose one of the dimensions of the vital statistics performance index . An evalThe correlation between percentages of poor quality of death certification and percentages of garbage codes was weak overall, but stronger for municipalities in the lowest GeoSES quartile, showing the possibility of effect modification on this association by socioeconomic status. This result could indicate that for municipalities with lower socioeconomic status, garbage coding and the correctness of core topics could be approached as a common issue, but for municipalities of higher socioeconomic status, they probably follow different pathways. Therefore, quality improvement initiatives focused on garbage coding could also impact the correctness of essential fields in municipalities with lower socioeconomic status. However, in municipalities with higher socioeconomic status, separated approaches would be warranted. On the other hand, the low correlation found could indicate that the basis associated with quality of death statistics measured by each approach differs. The relationship between different approaches to measure subnational quality of death statistics could be investigated in future studies, which should also include the assessment of completeness of death records. Targeted interventions to further improve death statistics could then be designed based on common factors.The non-linear model showed acceptable discrimination and the socioeconomic variables derived from the GeoSES were the most important predictors of poor quality of death certification. Previous recommendations for quality improvement efforts of CRVS systems have been based on which components of the vital statistics performance index should be prioritized based on the country’s index . The modIt is important to mention the limitations of the present analysis. Although Brazil has been investing to increase the completeness of death records in the past decades , currentThis study investigated an innovative way to assess the quality of death certification through missing and unexpected values on core topics, which could be used as a complement to the more frequently employed, such as assessment of completeness, garbage coding evaluation or the composite vital statistics performance index on regions that have already reached good quality levels. Besides, a data-driven non-linear model with acceptable discrimination for this outcome was developed, which could be used to guide and evaluate quality interventions, while also pointing to new insights that could lead to new improvement policies.S1 TableTable displaying grid search results for the machine learning models assessed.(PDF)Click here for additional data file.


This study aimed to develop an English version of a doping drug-recognition system using deep learning-based optical character recognition (OCR) technology. A database of 336 banned substances was built based on the World Anti-Doping Agency’s International Standard Prohibited List and the Korean Pharmaceutical Information Center’s Drug Substance Information. For accuracy and validity analysis, 886 drug substance images, including 152 images of prescriptions and drug substance labels collected using data augmentation, were used. The developed hybrid system, based on the Tesseract OCR model, can be accessed by both a smartphone and website. A total of 5379 words were extracted, and the system showed character recognition errors regarding 91 words, showing high accuracy (98.3%). The system correctly classified all 624 images for acceptable substances, 218 images for banned substances, and incorrectly recognized 44 of the banned substances as acceptable. The validity analysis showed a high level of accuracy (0.95), sensitivity (1.00), and specificity (0.93), suggesting system validity. The system has the potential of allowing athletes who lack knowledge about doping to quickly and accurately check whether they are taking banned substances. It may also serve as an efficient option to support the development of a fair and healthy sports culture. During the Beijing 2022 Winter Olympics, female figure skater Kamila Valieva under the Russian Olympic Committee (ROC) tested positive for a banned substance. The Court of Arbitration for Sport (CAS) ruled, under the World Anti-Doping Code by the World Anti-Doping Agency (WADA), that the figure skater lacked the capacity to control her drug use at her young age—she was 16 years old at the time. Following the ruling, Valieva was permitted to compete in the Beijing 2022 Winter Olympics, sparking one of the biggest controversies that occurred during the Olympics ) and acceptable drugs are correctly recognized (true non-master [TN]) in all prescription and drug substance images. Sensitivity refers to the percentage of banned substances’ images that are correctly classified as banned (TM). Specificity refers to the percentage of acceptable substances’ images that are correctly classified as acceptable (TN). This study developed a doping drug-recognition system using the Tesseract OCR model provided by Google. This hybrid system makes the analyzed results accessible to the user through both a smartphone and website through the UI. System accessibility is important for athletes not totally familiar with the applicable doping regulations to easily identify the banned substances. Accordingly, the procedure of the use of the doping drug-recognition system was divided into four steps , and user convenience was prioritized so that anyone can easily use the system. Consequently, it was observed that the time required for scanning and processing the image to provide a response to the user ranged from 10 to 15 s. This study confirmed the character recognition accuracy of the developed doping drug-recognition system using 886 images, including prescriptions and drug substance labels. The analysis of the 886 acceptable and banned drug substance images revealed that the system correctly classified all 624 images with acceptable substances as acceptable drugs. In addition, it correctly classified 218 out of the 262 images with banned substances as banned drugs, but incorrectly recognized 44 of them as acceptable drugs. To validate the system developed, a binary classification table was used to calculate the accuracy, sensitivity, and specificity of the classifications .The validation showed an accuracy of 0.95, sensitivity of 1.00, and specificity of 0.93. Given that an accuracy of 0.80 or higher describes a desirable level of validity, these results suggest that the developed doping system effectively classifies both banned and acceptable substances. These findings indicate the validity of the system for classifying banned and acceptable substances.This study is a follow-up to the research conducted by Park et al.  and presFirst, deep learning has been applied across various fields, including computer vision, pattern recognition, robotics, autonomous driving, art, and prediction . To effeSecond, the author confirmed the character recognition accuracy of the developed doping drug-recognition system using 886 images, including images of prescriptions and drug substance labels. The system showed recognition errors for 91 words . Thus, the system showed a high level of accuracy in recognizing words for drug substances. As the system in this study was developed for determining whether a drug contained a banned substance, it was considered unnecessary for the system to recognize characters other than those for drug substances. Therefore, the system’s character recognition accuracy was analyzed based on characters extracted as words in the drug substance section of images. Hassan et al.  reportedThird, the system correctly classified all 624 images for acceptable substances and 218 (out of 262) images for banned substances. However, it incorrectly recognized 44 of the banned substances as acceptable drugs. Regarding the validity of the system, results showed a high level of accuracy (0.95), sensitivity (1.00), and specificity (0.93). These findings suggest the validity of the system for classifying banned and acceptable drugs. In total, 152 prescription and drug substance images were selected as the primary data for this study; however, they were collected from a search engine and mostly consisted of drugs that anyone can buy easily on the market. Considering that prescriptions and drugs containing doping substances are not commonly available in the market, this can be considered a limitation of the data collection process.To improve the performance of the system, increase the accuracy of the model, and compensate for the insufficient sample size, this study applied data augmentation to the images of acceptable and banned drugs . Notwithstanding, to ensure that the list of all 336 banned substances in the database is correctly classified, additional efforts should be made in the future to compensate for the shortcomings of the system. For example, researchers can collect images of more banned substances in a future study. In addition, if the system developed in this study is continuously updated with the annually revised list of banned drugs and successfully commercialized, it is expected to serve as an effective option to prevent doping among athletes.In developing the English version of the doping drug-recognition system using deep learning-based OCR technology, it is hoped that this study helps athletes who lack knowledge about doping to easily and accurately identify whether they are taking banned substances. It is also expected that the system provided by this study supports the development of a fair and healthy sports culture. In the following, the conclusions of this study are described.First, this study used the Tesseract OCR model provided by Google to develop the system. This yielded a hybrid system that allows for the analyzed results to be accessible to the user by both a smartphone and website through the UI. Furthermore, the procedure of use for the system was divided into four steps , and user convenience was prioritized to enable for anyone to easily use the system.Second, the author confirmed the character recognition accuracy of the system using 886 images, including images of prescriptions and drug substance labels, showing a high character recognition accuracy of 98.3% (recognition errors for 91 out of 5379 words).Third, the system correctly classified all images for acceptable substances and most images for banned substances (44 banned substances were incorrectly recognized as acceptable). The results also suggested the validity of the system for classifying banned and acceptable drugs.In summary, the study developed a doping drug-recognition system to provide an effective and convenient option to support the efforts against the use of banned drugs, which could undermine a fair and healthy competition culture in the sports community and potentially harm the health of athletes. Further research is needed to address some of the issues with the system and improve it to ensure its practical applicability. Specifically, the validity of the system developed in this study maintains a high level, as mentioned in the research findings. However, regarding minor errors that result in providing incorrect information to athletes, they can have a detrimental impact on their careers. Such issues can be addressed through system modifications and enhancements in future research. The 44 errors that occurred in the study’s results were analyzed and categorized into two types based on issues that happened during the segmentation process—15 errors were caused by tilted photos and 29 errors were related to photo resolution. These errors can be attributed to excessive rotation, scaling, zooming, and color adjustments during the segmentation process. Therefore, it is deemed that implementing a system to detect and request the re-uploading of excessively tilted or low-resolution photos when athletes utilize the system could resolve such issues.The significance of this study lies in the development of a doping drug-recognition system that can relatively easily classify banned substances, which some athletes may face difficulties in identifying and classifying, through deep learning-based technology. Further research is expected to improve system performance and allow it to more clearly detect banned substances. One suggestion is for researchers to continuously update the system with the annual list of banned substances and the built system database. Finally, the doping drug-recognition system, if successfully commercialized, can serve as an effective option for the prevention of the use of banned substances among athletes.


Chronic diseases, such as childhood diabetes mellitus (DM), are a complex and continuous struggle as well as a great challenge both for the children who face the disease and for their parents. DM is characterized by the complex management of therapeutic treatments, thus causing physical and psychological complications infamily members. There are many families who, upon hearing the diagnosis of their child with DM, stand still in front of these new facts as their lives change. All these unprecedented conditions cause parents intense stress and discomfort, leading them to a mental burden, as the only thing that concerns them upon diagnosis is how the family will survive in the face of the current conditions they are experiencing as well as the future of the sick child. The purpose of this brief literature review is to present the research findings related to the psychological burden of families withchildren with DM, focusing on the quality of life and stress. Diabetes mellitus (DM) is a metabolic disease and a global crisis. It is the most frequent endocrine disease in children 2/1000) and adolescents (5/1000), with children—almost always of the insulinopenic type (type 1)—constituting 5% of the total population with diabetes. Type 1 diabetes is one of the most common chronic diseases in childhood, and its prevalence is increasing worldwide [000 and aType 1 DM is caused by insulin deficiency and must be treated with daily insulin injections. In the general population, it accounts for 10% of all cases but is more common than type 2 DM in children [The proposed treatment recommended for the management and treatment of DM, either for type 1 or type 2, is complex and demanding since it requires daily control of blood glucose levels (at least four times a day), control and regulation of carbohydrate intake, frequent administration of insulin (three to four injections a day or infusion from a pump), changing insulin doses to match eating and activity patterns, and testing urine for ketones when necessary ,4.DM affects the lives of the family, children, minors, and adults mentally and physically. Next to the sick child stands the family as well, as the child’s social environmentis affected by the disease, and parents or caregivers must provide daily care to their child. Both the child and their family during the announcement of the disease go through the stages of mourning , and thThe purpose of this brief literature review is to present the research findings related to the quality of life among parents of children and adolescents with diabetes by focusing on the psychosocial well-being entire system.This literature review examined the following research question: How does chronic disease impact the quality of life of families with children or adolescents who have been diagnosed with diabetes? The review was limited to families with diabeticchildren or adolescents. The following keywords and phrases were searched in the Web of Science (WOS), PubMed, CINAHL, Psych Info, and Google Scholar databases: diabetes *, diabetes mellitus *, quality of life* OR health-related quality of life *, child * OR adolescent * OR paediatric*, physical disability *, and chronic disease OR illness *. Articles were included if they have been published between 1995 and 2022 and included a sample of children and adolescents with diabetes. Titles and abstracts were screened, and articles that met theinitial screening criteria were organized in Mendeley. The appropriateness of the included articles was confirmed by an external colleague. After the final selection, references from the included articles were reviewed and additional appropriate studies that were missed through the initial search were added.After searching the literature, 682 articles were found. At the end of the first screening, we selected 76 articles eligible for reading the whole text following the selection criteria described above. Finally, after checking the reference lists, 31 eligible articles were selected for the final analysis. A PRISMA flowchart of the selection and screening method is provided .The diagnosis of a chronic illness or disability such as diabetes in a child leads to family upheaval and disorganization. The effects of this stress on parents can not only negatively affect the mental health of the parents but also affect the health of the child with diabetes. There have been several quantitative and qualitative studies in Greece and abroad thatstudied the burden and mental health of parents of children with diabetes.Several studies have been carried out to measure the quality of life of children with diabetes and the impact of the disease on their families. One study took place in Saudi Arabia, in which 315 adolescent patients, aged 12–18 years, and their caregivers participated. The results of the study showed that early adolescents  had a better quality of life compared to the group of adolescents aged 16–18 years old. This outcome has been attributed to the fact that adolescents feel more autonomous and handle the insulin regimen by themselves with less parental influence, resulting in poor self-care management. Conversely, the younger age groups showed a better quality of life. Throughout this study, the concern of parents of children with diabetes mellitus was highlighted in terms of the impact of the disease on the family, as well as regarding the complications and treatments related to diabetes. Additionally, the results indicated a negative impact on parents’ psychological well-being .Another study carried out in the pediatric hospitals of Patras, Athens, and Ioannina in 2016 aimed to investigate the socio-demographic factors that influence psychopathology, external shame, and the potential experience of shame of 285 parents with diabeticchildren. The findings of this study showed that the duration of the illness is associated with a reduced intensity of the psychological impact on parents over time, as growing children often become responsible for managing the treatment and, thus, partially relieve their parents. Additionally, over time, parents themselves accept the disease as part of their lives, thus reducing the consequences of the psychosomatic shock they suffered after the initial diagnosis, as well as the consequences of internal and external shame. Additionally, the gender of the child play an important role, as girls show lower rates of self-esteem and areless emotionally stable compared to boys. The same applies to parents, as their well-being is influenced by their place of residence and their educational level [Parentsof children attending secondary schoolshada better understanding of the illness severity. Respondents residing in small towns and who were parents of girls presentedhigher scores ofpsychopathologycompared to the parents of boys. An equally important finding of this study wasthat the origin of the child’s name from the respondent parent’s grandparent wasan influencing factor of the scale of shame (ESS), which had a greater influence onthe residents of small towns. In conclusion, through this research, it was pointed out that supportive interventions for parents of children with diabetes should be considered as factors influencing the place of residence, the educational level, the gender of the child, and the origin of the child’s name .Another study was conducted in a pediatric endocrinology unit in Turkey and involved a total of 64 children aged 8–12 years and 85 adolescents aged 13–18 years with type 1 diabetes. The PedsQL was used to measure the quality of life of the children, adolescents, and their parents. The parent form had questions about marital status, education, and family income. There were also questions about whether the children had hypoglycemic attacks and how many, as well as how many times they needed to be taken to the hospital because of diabetes, including the days of hospitalization required. The results forparents and childrenwere relatively the same. The school life scale and the emotional scale were low, whereasthe social scale was high, indicating the social needs of these children and their parents and that such needs must be met. Additionally, this finding may be related to the fact that families have to engage in the school system whilst seeking proper care. Therefore, school safety is a crucial issue. A correlation was also observed between the Child and Adolescent Quality of Life Scalescores. A negative correlation was found between the number of children and the quality of life of children and parents .A study carried out in Sweden with the participation of 130 families from four diabetes centers also examinedthe quality of life of parents and children (5–18 years) with diabetes. The results of the research showed that parents were more likely to identifywith diabetes than their children and participated to a large extent in the management of diabetes. In fact, parents shared responsibility for the management of the disease, and this is something that burdened them to a great extent. Parents were the ones who perceived that the disease limits their children from many activities. Additionally, during the research, it was observed that there was a difference in the perception of the psychological influence ofthe child’s gender. In particular, girls often “freeze” when faced with psychological difficulties to a greater extent than boys .Other researchers have studied the effects of parents’ overprotection towards their children and the problems that arise. The Parent Protection Scale was used to measure parental overprotection. A total of 43 children (15 boys and 28 girls) aged 8–12 years and their mothers (28–48 years) participated in the study. The results showed that parental stress was associated with high levels of depressive symptoms among children .Another study sought to assess the quality of life and health of young children with type 1 diabetes compared to their healthy peers, considering family functioning and mothers’ duties. A total of 113 mothers provided data for the study, 28 of whom had preschool children with type 1 diabetes. There were no differences in the quality of life and family functioning between children with diabetes and healthy children. Mothers of children with diabetes mellitus reported lower levels of resilience and depressive symptoms to a greater extent than mothers of healthy children. Regression analysis revealed that the mothers of children with diabetes mellitus were affected by their child’s disease, resulting in depressive symptoms, and the overall functioning of the family was largely dependent on the child’s illness. Mothers experience great discomfort with diabetes management; however, the family can function properly and young children can live similarly to their healthy peers. In conclusion, based on this study, the quality of life of preschool children is affected by the depression of their mothers. However, as mentioned above, there was no difference in functioning between families that have a child with diabetes or not, as this percentage is related to the child’s quality of life, family functioning, mother’s resilience, life satisfaction, and well-being .Diagnosing diabetes in a child often causes reactions of intense anxiety, shock, sadness, grief, frustration, guilt, and depression in parents. Several studies have been conducted to study the burden onparents of children with diabetes as well as to understand why thesefeelingsare more intense in these families. A study carried out in Norway aimed to identify the similarities and differences between mothers and fathers regarding the degree of emotional distress that arises from caring for a child with diabetes. A total of 103 mothers and 97 fathers participated, as well as 115 children aged 1–15 years. The results showed that both mothers and fathers reported that emotional burden was related to long-term anxiety about their child’s health. Mothers reported a high burden related to the medical care required for their children, feeling more emotional stress than fathers did. Nighttime scores are significantly related to parental burden and emotional stress experienced by both genders .Another study conducted by Hatton et al.  identifiFaulkner  studied Dashiff  in her sAnother study, conducted in 2007involving 17 parents of children with diabetes amongwhom 10–17 years had passed since the diagnosis of the disease, found that parents adapted to the needs of diabetes management, but most did notemotionally accept the fact that their child was diagnosed with diabetes. They experienced many times a resurgence of their grief during the development of their child, and many of the mothers were upset during the interviews, even though 10–17 years had passed since the initial diagnosis. Mothers processed their emotions more than fathers did, and both parents experienced feelings of sadness, pain, and anger .Another study approved by the Yale School of Nursing Human Research Review Committee and involving 28 mothers of children with diabetes addressed the burden and emotions experienced by families of children with diabetes. The results of this study showed that mothers of children with diabetes are constantlyvigilant, have constant concerns about hypoglycemia, and care intensively for their children. There were many mothers who felt insufficient support for this, and the necessity of supportive healthcare policies wasemphasized inthe study . In the Another qualitative study interviewed 30 parents about their experiences of raising a child with diabetes. This analysis revealed sixthemes that focused on parental concerns as follows: (1) long-term complications of diabetes, (2) challenges from disease management, (3) financial concerns, (4) child mental health, (5) health coverage, and (6) experiences with people outside the family and at school . ParentsFinally, another study by Jean and colleagues aimed to show the way parents communicate with their children suffering from diabetes, as well asexplore the communication patterns that may lead to a better understanding within the family and more efficient problem-solving strategies. The results of the study showed that there wasa large degree of frustration when parents communicated with their children. Both parents and children expressed insecurity and fear in expressing their feelings, which led parents to psychological pressure and permanent stress, which worethem down psychologically .The effects of parental stress often lead parents to develop mental disorders, which also affect the health of the child with diabetes. So, not only does the family affect diabetes but diabetes also affects the family. A longitudinal study conducted with the participation of 132 teenagers with diabetes and their parents showed that the stress of the parents, which is related to diabetes, leads to poor mental health amongthem and their children.In particular, this study examined parental stress and its influence on parents’ mental healthas well as the relationship between parental stress and health-related quality of lifeinchildren with diabetes . AnotherA study investigating the pediatric stress experienced by fathers of a child with diabetes showed that children experience low levels of pediatric stress, but the correlates of paternalstress may have effects on general family functioning as well as children’s behavior. Forty-three fathers of children (aged 2–6 years) with diabetes completed aself-report questionnaire . AnotherA study by Lowes and colleagues, which aimed to gain a new theoretical understanding of parental reactions and adjustment processes to the disease, showed that the diagnosis of childhood diabetes leads parents to a psychosocial transition. This transition is the grieving process and the stages of adjustment that parents experience. In all these stages, parents experience strong emotions such as stress, depression, guilt, and fear, as they are overwhelmed by uncertainty regarding the outcome of the disease and the life of their children .A descriptive study conducted in 2016 involving 113 parents of children and adolescents with diabetes in Shiraz, using the Depression Anxiety Scales (DASS-21) and the Connor-Davidson Resilience Scale, aimed to identify psychological predictors of resilience in parents of children and adolescents who are insulin-dependent. The results showed that parents had high levels of stress, with 71.4% reporting mild to extremely severe symptoms of depression and anxiety. Additionally, 49% of the changes in resilience weredue to factors such as stress, depression, and life satisfaction. Since nearly half of the parents experienced anxiety, depression, and stress, and there was a correlation between resilience and these psychological variables, parents’ psychological problems, especially depression, may be reduced by improving their resilience .The aim of anotherstudy by Antonio Zayas and his colleagues was to study the levels of depression in parents and to analyze the resilience of these parents. Thirty-oneparents of children with diabetes were evaluated by the JEREZ diabetic association. The results of the study showed that these parents showed moderate levels of depression. It was also found that those who were more resilient had lower levels of depression . AnotherAnother study referred to by Koegelenberg investigates the properties of resilience and concludes that family communication, the routine of everyday life, and the time a family spends together are important characteristics of resilience and influence the adjustment of families with children diagnosed with diabetes . Ozlem KDiabetes mellitus is a challenge for patients andtheir families who are suddenly challenged to adapt to a condition that causes changes in the functioning of the whole family, especially when it comes to children or teenagers. Primary health care must provide support to these families so that they can overcome in the smoothest possible way all the transitional stages from the information of the disease to the acceptance of their children’s disease. Parents, as we have seen through the above studies in which they participated, felt strong negative feelings of stress, anger, and pain, which, through appropriate support from experts, can bealleviated in order tolead them to a more functional behavior so that they can accept the disease. Parents who show increased levels of depression, overprotection, and stress increase the likelihood of their children experiencingsuch negative symptoms.The recognition of the influence of socio-demographic factors on the psychopathology of parents highlights the need for targeted interventions to helpthem become more effective in supporting their children in dealing with diabetes mellitus.The above observations raise new questions about the psychological processes associated with the occurrence of diabetes mellitus, a disease that inevitably affects the unconscious perceptions and associations of the parent in relation to the child and creates new questions that, to the extent that they cannot answer, create guilt and increase stress and indicators of psychopathology. The sudden adverse changescanproduce feelings of inferiority, which in turn are related to shame, anxiety, and depression .In the context of therapeutic interventions, the role of caregivers is very important because of the care they offer. It is critical to understand their needs and assess the burden on their lives. Thus, appropriate interventions should be implemented to at least limit the burden on caregivers by focusing on the individual factors that contribute to this phenomenon. In this context, it is proposed that research efforts should be made in this direction.Finally, it must be noted that during the past 30 years, there has been a dramatic change in diabetes managementregarding insulin administration, glucose measurement, and types of insulin. These changes have improved the lives of children with diabetes as well as their families . Moreove


This study aims to identify the characteristics and future directions of online medical education in the context of the novel coronavirus outbreak new through visual analytics using CiteSpace and VOSviewer bibliometric methods.From Web of Science, we searched for articles published between 2020 and 2022 using the terms online education, medical education and COVID-19, ended up with 2555 eligible papers, and the articles published between 2010 and 2019 using the terms online education, medical education and COVID-19, and we ended up with 4313 eligible papers.Before the COVID-19 outbreak, Medical students and care were the most frequent keywords and the most cited author was BRENT THOMA with 18 times. The United States is the country with the greatest involvement and research impact in the field of online medical education. The most cited journal is ACAD MED with 1326 citations. After the COVID-19 outbreak, a surge in the number of research results in related fields, and ANXIETY and four secondary keywords were identified. In addition, the concentration of authors of these publications in the USA and China is a strong indication that local epidemics and communication technologies have influenced the development of online medical education research. Regarding the centrality of research institutions, the most influential co-author network is Harvard Medical School in the United States; and regarding the centrality of references, the most representative journal to which it belongs is VACCINE.This study found that hey information such as keywords, major institutions and authors, and countries differ in the papers before and after the COVID-19 outbreak. The novel coronavirus outbreak had a significant impact on the online education aspect. For non-medical and medical students, the pandemic has led to home isolation, making it difficult to offer face-to-face classes such as laboratory operations. Students have lost urgency and control over the specifics of face-to-face instruction, which has reduced the quality of teaching. Therefore, we should improve our education model according to the actual situation to ensure the quality of teaching while taking into account the physical and psychological health of students.The online version contains supplementary material available at 10.1186/s12909-023-04193-5. Two thousand nineteen Coronavirus disease is a disease caused by a novel coronavirus called severe acute respiratory syndrome coronavirus .On DecemOnline education, the Internet-based model of education in which teachers' curricula and materials are shared remotely with students through the Internet, enables the separation of teaching and learning, facilitates the flow of high-quality teaching resources, and further improves educational equity in society as a whole . Since 2To elucidate the impact COVID-19 has had on medical online education and to provide a systematic and objective overview of the development of medical online education, this study used Citespace, VOSviewer to separately identify, through scientometric methods, the bibliographic data published in the 10 years prior to the COVID-19 outbreak (2010–2019) and between the COVID-19 outbreak and the present day in Web of Science (WoS) journals published in the field and visualized their relationships. The analysis was based on CiteSpace. Specifically, the study was guided by four key objectives: (1) to understand the characteristics of the keywords of research topics before and after the outbreak; (2) to identify the most prominent researchers in the field before and after the outbreak and the associations between them; (3) to describe the main research institutions and the evolution of the links between geographic regions in the field before and after the outbreak; and (4) the journals with the highest number of citations and publications in the field before and after the outbreak. Each part of this paper is organized as follows. The "Materials and Methods" section describes the data collection and CiteSpace and VOSviewer, and the "In this study, the literature visualization and analysis tools used were CiteSpace 5.8.R3 and VOS viewer 1.6.18.CiteSpace is a Java language-based visual literature analysis software developed by Professor Chaomei Chen of Drexel University . It is aVOS viewer is a JAVA-based software tool for building and visualizing bibliometric networks, developed in 2009 by van Eck and Waltman of The Centre for Science and Technology Studies at CWTS . Its basIn CiteSpace, time chosen to build the dataset is selected as the time window, and the time slice is 1 year, and the text processing options of Title, Abstract, Author Keywords, and Keywords Plus are selected, and Author, Institution, and Keyword are selected as the nodes respectively The text processing options of Title, Abstract, Author Keywords, and Keywords Plus are selected, and Author, Institution, and Keyword are selected as nodes, respectively.In the VOS viewer, you can create clusters and density diagrams by creating a bibliographic dataset based map to read the data in bibliographic database file, then filtering in the data from the scientific network and selecting co-existing, co-authorship, and other small cells in the entries to create clusters and density map that are more intuitive and clear.The literature included in this paper was obtained from the Web of Science, written in English, and the Web of Science Core Collection was used as the database. In this paper, in order to better reflect the research results at different time points, the datasets were created based on the pre-COVID-19 and post-COVID-19 outbreaks, respectively. For Early Access papers published in Web of Science, we manually categorized them according to their topics, and the rest of the papers were categorized according to their publication dates.For the literature before the COVID-19 outbreak, we chose the publication period from January 1, 2010 to December 31, 2019, 2022; the search formula was TS = online education AND medical. 4313 documents were obtained in total.For the literature after the COVID-19 outbreak, we chose the publication dates of January 1, 2020 to July 16, 2022; the search formula was TS = online education AND medical AND COVID-19. 2555 papers were obtained in total.The obtained documents were exported to Plain text file Full record with cited references format for analysis.The number of papers and the trend of changes can measure the level and dynamics of scientific research results in the field, which is very important for predicting future development trends. As shown in the Fig. An analysis of keywords in the literature for the decade prior to the epidemic (January 2010 to December 2019) and the post-epidemic period (January 2020 to June 2022) led to the following conclusions.Scholars around the world before and after the epidemic maintained a certain level of attention to online teaching of clinical research, but after the epidemic, with the rapid development of Internet technology and the trend of the current social situation, online teaching that can communicate remotely has received extensive attention from schools , 14.A total of 10,942 keywords from the decade before the epidemic constructed a keyword network for clinical research teaching research in the decade before the epidemic. Based on the keywords in the 21 main thematic clusters, keywords with a frequency of ≥ 3 were filtered and keywords with "covid-19", "education" and their related synonyms, i.e. the terms used in the literature search for this study, were removed. We obtained 1822 keywords that were the most prominent, dominant and relevant. The visualization of the keywords drawn using VOSviewer is shown in Fig. Based on the "total link strength" indicator, it is easy to see that the following ten keywords are among the keywords with a strong link strength, which are not listed in this paper due to space, but are shown in Table The second largest cluster is shown in blue in the graph and contains 157 items. The most frequent phrase in this cluster is "care", with 321 occurrences and 2257 links, making it the most frequent phrase in this cluster.The third largest cluster contains 132 items and is shown in pink in the graph. The most frequent phrase in this cluster is "impact", with 248 occurrences and 1835 links.The fourth largest cluster contains 117 items, highlighted in brown in the graph. Knowledge" is the most frequent phrase in this cluster, with 213 occurrences and 1578 links.The fifth largest cluster, containing 109 items, is highlighted in light green in the graph. The most frequent phrase in this cluster is "attitudes", with 209 occurrences and 1522 links.A total of 6283 keywords were used to construct a keyword network for clinical research and teaching research during the novel coronavirus outbreak. Based on the keywords in the 14 main thematic clusters, keywords with a frequency of ≥ 3 were filtered and keywords with "covid-19", "education" and their related synonyms, i.e. the terms used in the literature search for this study, were removed. We obtained 1004 of the most prominent, dominant and relevant keywords. The visualization of the keywords drawn using VOSviewer is shown in Fig. Based on the "total link strength" indicator, it is easy to see that the following ten keywords are among the keywords with strong linkage, which are not listed in this paper due to space, but are shown in Table . The terIn terms of subject clusters, the subject clusters were ranked according to the strength of relevance and frequency of the keywords included. Anxiety" is the most frequent phrase in this cluster, with 252 occurrences and 2138 links.The second largest cluster is shown in red in the graph and contains 282 items. The most frequent phrase in this cluster is "Impact", which has 224 occurrences and 1685 links.The third largest cluster contains 57 items and is shown in brown in the graph. Pandemic" is the most frequent phrase in this cluster, with 216 occurrences and 1441 links.The fourth largest cluster contains 141 items, highlighted in green in the graph. Health" is the most frequent phrase in this cluster, with 175 occurrences and 1210 links.The fifth largest cluster, containing 93 items, is shown in blue. Knowledge" is the most frequent phrase in this cluster, with 140 occurrences and 861 links.By analyzing the top ten keywords before and after the epidemic, it is easy to find that "Students", "Impact" and "Health" are the main keywords before and after the epidemic. However, the ranking of "Knowledge" has dropped and the position of "Impact" has increased. After the epidemic, keywords such as "Anxiety" and "Stress" gradually emerged to describe psychological stress states, and the focus on students' health was gradually refined to include mental health.In the author coupling analysis before and after the epidemic using VOSviewer, the threshold was set to ≥ 7. 17 authors were obtained from 16,989 authors screened before the epidemic, and 18 authors were obtained from 15,676 authors screened after the epidemic. The deeper the curve in the figure indicates the stronger the association. From Figs. Then using Citespace to summarize the top 10 authors of the cited articles published, as shown in the figure, before the epidemic, Brent Thoma's article was the most cited with 18 times; after the epidemic, Chungying Lin's article was the most cited with 11 times, so for a quick understanding of the field, the articles of these two are more readable Tables  and 4.TaIn terms of author centrality, pre-epidemic A Bullock, E Barnes, A Kavadella and A Liepa ranked first with a centrality of 17, while post-epidemic Aimen Khacharem and Achim Jerg ranked first with a centrality of 54, indicating the strong influence of these authors in the field Tables .Table 5TIn this country density map showing each country's involvement in online teaching and learning during the novel coronavirus outbreak. Each point in the item density visualisation has a colour that indicates the density of the item at that point. The colours range from blue to green to yellow . The grePrior to the COVID-19 outbreak, most countries had not conducted extensive research in this area Fig. . Among tThe visualization of the institutional collaboration network (nodes are the names of institutions that connect institutions that have collaborative relationships) provides a clear visual representation of the collaborative relationships and key institutions. Figs.  and 9. TBased on the centrality index, it is easy to conclude that "University of Toronto" is in the first place with a centrality of 2450. "Harvard University" is the second most centralised institution in the online inter-institutional collaboration network. The No. 3 institution for centrality is “University of California, San Francisco”.According to the "Ducuments" metric, the highest-ranking institution in the visual agency collaboration network is "University of Toronto" with 115. "University of California, San Francisco" ranked second with 84, followed by "McMaster University" with 38. It is not difficult to find that the average number of "ducuments" of the top ten comprehensive literatures is about 67."Total link strength" refers to the Total co-occurrence times of keywords and other keywords (including repeated co-occurrence times). In the organization cooperation network of the visual co-author, it can indicate the close cooperation degree between the organization and different institutions. By analyzing the data, it's easy to know that "University of Toronto" ranks first with 20,123, "McMaster University" came in second with 17,301, and "Johns Hopkins University" came in third with 11,631. Not surprisingly, the top three are all over 10,000.Based on the centrality index, it is easy to conclude that "National University of Singapore" is in the first place with a centrality of 3324. "Harvard Medical School" is the second most centralised institution in the online inter-institutional collaboration network. The No. 3 institution for centrality is “Huazhong University of Science and Technology”.According to the "Ducuments" metric, the highest-ranking institution in the visual agency collaboration network is "Harvard Medical School" with 47. "University of Toronto "ranked second with 39, followed by "The University of Hong Kong" with 38. It is not difficult to find that the average number of "ducuments" of the top ten comprehensive literatures is about 34."Total link strength" refers to the Total co-occurrence times of keywords and other keywords (including repeated co-occurrence times). In the organization cooperation network of the visual co-author, it can indicate the close cooperation degree between the organization and different institutions. By analyzing the data, it's easy to know that "Harvard Medical School" ranks first with 10,080. "Johns Hopkins University" came in second with 8431, and "University of Toronto" came in third with 8062.However, considering the three indicators of "Ducuments", "Citations" and "Total link strength", it is easy to find that the development of "Harvard Medical School" in terms of publications, centrality, and total link strength with other institutions is more balanced and better. In addition, it is easy to find that the institution "Harvard Medical School" has direct links with many other institutions, which further reflects that this is a very influential institution and it maintains close cooperation with many other institutions. We realize that the outbreak of COVID-19 has produced a dramatic change in the research community in terms of online medical education. Taking this change into account in a timely manner when selecting a partner institution can go a long way in helping researchers find the right partner institution.The clustering network drawn by the journals to which the visual references in this study belong , and the clustering analysis is performed according to the main research keywords of the journals. By looking at the graphs and analyzing the data, you can explore the interconnections between journals. Specifically, the following conclusions are obtained:The journals included in the study before the epidemic were divided into 21 clusters through cluster analysis. Fig.  The jourThe journals included in the study after the epidemic were divided into 19 clusters through cluster analysis. Fig.  By rankiA comprehensive comparison between before and after the epidemic showed that 60% of the journals remained in the top 10 citation numbers after the epidemic. The analysis included "JAMA-J AM MED ASSOC" "BMC MED EDUC" "NEW ENGL J MED" "BMJ-BRIT MED J" "J MED INTERNET RES" "LANCET".The essence of online education is to use Internet technology to transfer knowledge to learners through a network platform in order to achieve the purpose of cross-distance education and teaching. In addition to not being restricted by time and space, online education mode also saves time and money costs for learning to a certain extent. What's more, as a new way of education that has emerged in recent years, online education can effectively exercise students' independent learning ability and flexibility, so that learners can arrange their learning contents according to their own learning progress and interests. Medical students, because of the special nature of their profession, need to learn knowledge and accumulate experience over a long period of time, and medical education is very focused on clinical practice and hands-on. In order to meet this demand, online education combines modern intelligent visual technology to build online virtual simulation experiment simulation courses that can meet the needs of medical education. Obviously, the teaching mode of teachers and students is also facilitated by online education. In recent years, medical education and online education have shown a good trend of complementing and promoting each other. However, at the same time, online education also faces some challenges.With the development of Internet and computer technologies, the technical difficulties of online teaching methods have been largely overcome, but more issues regarding students' mental health have been revealed . The outFrom the visual keyword clustering, it is easy to find that students/knowledge is also a hot direction of research. When students receive online education, it is difficult to generate direct communication with teachers, and it is even more difficult to realize the learning of experiments and clinical operations . MeganneA bibliometric analysis cannot present a complete picture of the current and future state of the research field, and this study is no exception; therefore, the results of this paper are limited to its scope—that is, this paper focuses on the development of online education programs for medical students before and after the COVID-19 outbreak from 2010 to 2022 , 34. HowWith the development of the epidemic, the education industry, especially face-to-face medical education, which requires practice, has taken a huge hit. Online teaching is still lacking as the first method to deal with the educational problems of students affected by the epidemic. After the COVID-19 outbreak, there has been a surge in the number of relevant studies, with changes in research hotspots and in the leading researchers, institutions, countries, and the most cited journals. Analyzing a large number of academic papers can help to filter more valuable content so that the right method can be used to mitigate the negative effects of the epidemic on people.Additional file 1.