Contemporary poisons, to a greater extent than in the past, are based on the use of synthetic substances from the group of organophosphorus compounds and radioactive substances. The possibility of taking appropriate and effective treatment in such cases is the result of many factors, including the possibility of quick and competent rescue intervention, quick and reliable detection of the toxic substance and the possibility of using an antidote.Criminal poisonings are among the least frequently detected crimes in the world. Lack of suspicion of this type of event by police officers and prosecutors, clinical symptoms imitating many somatic diseases and technical difficulties in diagnostics, as well as high research costs make the actual frequency of these events difficult to estimate. The substance used for criminal poisoning is often characterized by: lack of taste, color and smell, delayed action, easy availability and difficulty to detect. The aim of the study was to analyze selected cases of political poisoning that took place in the years 1978–2020, to describe the mechanisms of action of the substances used and to evaluate the diagnosis and treatment. The analyzed cases of criminal poisoning concerned: Georgi Markov (ricin), Khalid Maszal (fentanyl), Wiktor Yushchenko (TCDD dioxin), Jasir Arafat (polonium  Toxicology still refers back to the words of Paracelsus, who stated that toxic effect of each substance depends mostly on its dose. Besides the dose, the toxicity is affected by factors reliant directly on the poisonous substance, such as the route and rate of administration, hydro- and lipophilicity, physical state and formulation  and the clinical state of the victim, particularly including: age, sex, body mass, comorbidities and genetic predisposition. The poison used in a criminal poisoning should be characterized by such features as: colorlessness, lack of taste and smell, delayed toxic effects, difficulties in detection and easy availability  1]..1].Today, with the development of diagnostic techniques, the chance of revealing various types of criminal poisoning has increased. However, it is worth realizing that at the same time there has also been significant progress in planning criminal activities.We would like to outline the historical background of politically motivated crime poisonings, with an emphasis primarily on the detection of toxic substances and medical treatment. There are many poisonings in which circumstances are of a political nature but no toxic substances or their metabolites have been detected. One such example is the case of the suspected poisoning of Pyotr Verzilov, Pussy Riot activist . Verzilo210Po isotope). The following describes the toxicological properties of selected toxic substances used for criminal purposes, as well as the diagnostic methods and the proposed treatment methods.The common feature of the poisoning cases described above was the alleged or proven involvement of secret services in the physical elimination of the political opponents. The symptoms were experienced by the victims almost immediately after poisoning  or a few hours after exposure  pathway. The RTA chain is an enzyme (RNA N-glycosidase) and is responsible for ribosome inactivation (RIP—ribosome inactivating protein). Its action is based on the removal of adenine rRNA from 28S, which prevents the attachment of the translational factor EF2 (elongation factor-2) to the ribosome. In this way, protein synthesis is inhibited, which ultimately leads to cell death .Ricin poisoning is characterized by a delayed onset of symptoms and a slow action with fatal outcome. The lethal dose of ricin depends on the route of its administration . The in After ingestion of the toxin through the alimentary tract, nausea, vomiting, diarrhea and abdominal pain occur. Within about 4–36 h, symptoms may progress, accompanied by: arterial hypertension, renal failure and liver damage.In the case of inhalation, symptoms usually develop within about 8 h and include: cough, shortness of breath, joint pain and fever. Occasionally, these types of patients suffer from respiratory distress and death.In the case of injection, local swelling and redness appear at the site of injection of the toxin. The first symptoms of poisoning develop within approx. 6 h. Among them, the dominant ones are: weakness and muscle pain. After the next 24–36 h, symptoms progress, including: nausea, fever and hypotension, as well as multiorgan failure or death.Treatment of ricin poisoning is symptomatic. It includes the intravenous administration of fluids and vasopressors. In case of oral poisoning, it is possible to administer activated charcoal. Gastric lavage is considered only in cases where the intoxicity has occurred no more than one hour earlier.Currently, the greatest hopes in the postexposure treatment of ricin poisoning are placed in the use of neutralizing antibodies. So far, two preparations for vaccination have been tested: ricin chain deactivated with formaldehyde (ricin toxoid) and deglycosylated ricin. Research using genetic recombination methods has led to the production of the RiVax vaccine.Animal studies were carried out, including pigs exposed to lethal pulmonary exposure and systemic ricin with the use of anti-ricin F(ab’)2 antibodies of equine origin. The results of this study showed that it is possible to create postexposure remedies for ricin poisoning in humans .Diagnosis of ricin poisoning is based on history, identification of ricin in biological fluids or environmental samples. In clinical samples, ricin is difficult to detect due to its strong binding to glycosylated protein. Free ricin (with a molecular weight of 164 Da) is a marker of castor bean consumption . There aFentanyl is a synthetic compound that belongs to the opioid family. First opioid substance was isolated in 1806 by Serturner which, as a tribute to the god of sleep Morpheus, was named morphine. Because of Serturner’s strong addiction to this substance that he developed soon after, he managed to describe the consequences of its chronic abuse in great detail. Since the time of their discovery, opioids have come to be an essential drug in everyday practice of medicine, mainly as analgesics. However, due to their strong addictive potential, they have also been used widely as recreational drugs.Fentanyl is one of the most potent opioids, being a 100 times more potent than morphine. As a strongly lipophilic substance it enters the tissue compartments with ease  and clinically produces an opioid toxidrome with a very characteristic presentation: bradycardia, bradypnea, hypotonia . FentanyOn a molecular level fentanyl acts as a μ, δ and κ receptor agonist, each of which is coupled with a Gi protein (it causes a decrease in intracellular cAMP levels). Fentanyl’s interaction with an opioid receptor causes a decrease in calcium influx in the presynaptic neuron, which then suppresses the release of neurotransmitters into the synaptic cleft, as well as hyperpolarization of postsynaptic neuron due to potassium ion the efflux. All these effects impede physiological neuronal transmission .The most important organ in fentanyl metabolism is the liver . The firIn spite of a fairly characteristic clinical presentation of an opioid toxidrome, fentanyl intoxication may be sometimes difficult to diagnose, even for an experienced clinician . The mosOwing to the fact that fentanyl is a compound, in which metabolites are excreted primarily with urine, urine tests are going to be the base of an accurate detection of this substance. This can be a simple immunochemical test (strip test), as well as more advanced and sensitive diagnostic techniques such as gas chromatography with mass spectrometry (GC/MS) or liquid chromatography with tandem mass spectrometry (LC–MS/MS). It is also possible to detect fentanyl in an environmental sample for instance via ion mobility spectrometry (IMS), which can detect even a nanograms of this substance in a sample tested .p-dioxin) is the most representative, best-known and most toxic substance from the group of dioxin-like compounds (DLCs). Dioxins were discovered in 1957 during a veterinary investigation to explain the mass extinction of farmed chickens. The most scientific reports on the impact of DLCs on living organisms appeared in the 1970s during the Vietnam War . If. If62]. 3 was noted on this occasion, as in its absence the reaction was slower and with the formation of desethyl-VX. The hydrogel adheres well to various surfaces—in 5 min it adjusts the shape to the applied structure, stiffening after 10 min.It is estimated that the above mixture decomposes approx. 50% of VX in 30 min (100% in 3.5 h). Neutralization takes place by peroxide hydrolysis in an environment with a pH of ~9, with HOO- ions (derived from NaBO3) and oxidation with peracetic acid (from TAED). The end product of the reaction is only safe EMPA (ethylmethylphosphonic acid). The key role of NaBOTreatment of poisoning with paralytic and convulsive factors in adults, according to Polish and American standards, is slightly different, but it is absolutely necessary to include atropine and one of the oximes as soon as possible—this combination effectively reduces mortality and long-term effects poisoning  65,66,6,68.The first step in the diagnosis of poisoning with organophosphorus compounds is the determination of cholinesterases  and albumin with phosphorylated tyrosine-411 in the patient’s blood . The timVX can be specifically detected and determined from blood or urine by commonly used methods such as colorimetry and mass spectrometry (MS) . When MSThe reaction takes place in an acidic environment, where the citric acid acts as a surfactant on the metal surface (while electrostatic interactions are preserved). DAET displaces it, forming a thiol-Au bond. Replacing the citric acid molecule with DAET abolishes the electrostatic interactions and brings the gold particles close enough to each other that van der Waals forces begin to act, which stabilize larger metal clusters. One of the physical properties of AuNPs is the change in color depending on the degree of aggregation, which makes it possible to read the result of a chemical reaction with the naked eye. Metal particles in a slightly acidic environment can be prepared from commonly available reagents, and the obtained solution has a shelf life of 2 weeks. The result is available after a few minutes—if positive, the solution changes its color from red (absorption spectrum 520 nm) to blue 680 nm). The sensitivity of the method for the determination of DAET is 16 ng/mL (100 nM). Due to a special protocol for manual extraction, impurities were eliminated, and the method was highly effective under simulated environmental conditions ,68.0 nm. TheOrganophosphorus compounds in the Novichok group were first synthesized in the 1970s and 1980s in Russia as part of the secret “FOLIANT” program. Novichoks are considered binary compounds  suitable for use as chemical weapons. Novichoks are referred to as fourth-generation CW agents . Due to According to the available information, the structure of Novichok is based on an organophosphorus core  containiNovichoks are most commonly found in liquid form. They can also be found in fine powder form. They are extremely stable, which means that they can be stored in containers for long periods of time without changing properties. These compounds do not evaporate and do not dissolve in water . Given tThere is no official or publicly available information on the toxicity of Novichoks. Experts believe that some of them may be up to 5-8 times more toxic than VX  75]..75].Their action most likely involves blocking two sites in the active center of acetylcholinesterase  and causSymptoms resulting from overstimulation of muscarinic receptors include skin flushing, pupil constriction, visual disturbances, drooling and dangerous bronchial hypersecretion, bronchospasm, coughing, dyspnea, lacrimation, sweating, intestinal colic, diarrhea, bradycardia and involuntary urination and defecation. Excessive stimulation of nicotinic receptors is responsible for: tremor, muscle weakness up to complete paralysis, tachycardia, hypertension . It has In the management of patients who may have been exposed to Novichok, it is important to recognize cholinergic toxidrome promptly, to discontinue exposure and to treat it intensively, even before the results of the directional diagnosis are available . SpecifiTherapy should begin with immediate intravenous administration of atropine 2–6 mg and repeated doses every 5–10 min until bradycardia, bronchospasm and excessive sweating resolve. Oxime administration, although effective, should not delay the use of atropine. Because of respiratory muscle paralysis, intubation and mechanical ventilation are necessary. If convulsions occur, diazepam 10–20 mg i.v. is used. Continued symptomatic treatment is necessary. In case of bacterial infection, antibiotic therapy should be introduced. The literature also describes the use of diphenhydramine  and intravenous administration of lipid emulsions in critically ill patients ,78.The diagnostics of poisoning with Novichok group compounds is based primarily on the earliest possible diagnosis of cholinergic toxidrome. Recognition of a characteristic symptom complex allows immediate implementation of potentially life-saving treatment; further diagnostics is of secondary importance and is performed to confirm the substance used and possibly more precisely direct the treatment.Testing the activity of cholinesterase and butyrylcholinesterase  in blood shows complete blockade of both enzymes, which seems quite obvious considering the nature of action of Novichok—it belongs to the group of cholinesterase inhibitors . Mass spIn the course of the study, a full toxicological examination should also be performed for known and available poisons that may cause a similar set of symptoms. Neurophysiologic studies performed when in doubt will show typical conduction abnormalities, i.e., neuromuscular plate blockade and variable prolongation of the action potential between the muscle fibers tested, the so-called jitter .Due to the large diversity of pharmacokinetic and pharmacodynamic properties of toxic substances used for criminal purposes, it is impossible to apply a single and universal scheme for diagnostics and treatment after poisoning. Nevertheless, the flowchart should take into account at least the stages listed in Ricin is a vegetable protein with a very high toxicity, and, as the case of Georgi Markov shows, it causes great diagnostic and treatment difficulties. There is no detailed information on the human toxicity of this compound nor on effective treatments for ricin poisoning. However, this compound is not toxic enough to be used on a large scale in bioterrorism. Historically, its criminal use has been associated with small attacks or in individual cases. For example, apart from Georgi Markov—it is suspected that ricin was also used in the attack on Vladimir Kostov in the Paris metro 10 days before the attack on Markov. There were also attempts at attacks with the use of ricin by the percutaneous route, among others Castor letters sent to White House. It is also possible to use ricin in a chemical attack in a form absorbed through the respiratory tract. However, in the everyday life of a doctor, the most common way of poisoning with this substance is the gastrointestinal tract and accidental ingestion of castor bean seeds, especially by children. Rapid diagnosis of ricin poisoning and effective treatments are not available.Opioids have a wide medical application, characteristic symptoms of poisoning and quite effective methods of treatment. Due to their common use and relatively easy availability, poisoning with them, mainly due to an overdose of opioid used for therapeutic purposes, is quite common in practice, and if not recognized quickly enough, they lead to severe hypoxia, multiorgan failure and death of the patient.The use of TCDD as a poison, despite its high potency, did not directly lead to the death of any of the poisoned persons whose cases are described in the literature. The relatively long  period of acute nonspecific symptoms may, however, prevent the poisoned person from functioning normally—in the case of Viktor Yushchenko it was an election campaign. In population, the probability of isolated poisoning with dioxin-like compounds is very low. Most often, in acute poisoning, other xenobiotics are responsible for clinical manifestation and mortality.Poisoning with this element is difficult to diagnose due to nonspecific symptoms. Initially, it manifests itself with problems with the digestive system, such as nausea, vomiting, diarrhea and abdominal pain. These symptoms are usually associated with food poisoning. Other symptoms such as hair loss and bone marrow depression have been associated with cytotoxic treatment, which also makes differentiation difficult. Polonium-210 poisoning can be similar to thallium poisoning, which also causes hair loss, anemia and leukocytosis. However, thallium causes painful peripheral sensory neuropathy, which helps rule out its possible use . There aKim’s case identifies the VX as one of the most effective chemical weapons. Knowledge about its synthesis is widely available, and the necessary laboratory facilities can be organized privately. This is evidenced by the activity of the Aum-Shinrikyo sect, which was the first to use VX for criminal poisoning in the 1990s ,82. A paThere is still little reliable and publicly available information about compounds from the Novichok group. Most of the reports about them come from a single source, which does not provide adequate reliability (and sometimes even contradicts the studies performed), and the fact that all data about these substances are diligently guarded makes it still a very difficult challenge to determine their properties, toxicity and metabolism. Consequently, the diagnostic and therapeutic algorithms also cannot be precisely adjusted, resulting in a high risk of death for the exposed patient. The issue of poisoning prevention also remains unsolved. To date, a way to prevent Novichok poisoning has not been developed. The only options today are not to leave one’s belongings unattended and not to take liquids and food from an unknown source, although, as the cases of known poisonings described in this publication show, this, too, may not be sufficient.Contemporary poisons used in political crime poisonings are based, to a greater extent than in the past, on the use of synthetic substances from the group of organophosphorus compounds and radioactive substances. The possibility of proper and effective treatment is the result of many factors, including the possibility of quick and competent rescue intervention, reliable detection of the substance and its metabolites in evidence and biological material  and the possibility of using an antidote. Contrary to other criminal poisonings, potential victims-politicians and their environment most often are fully aware of the threat to life and health, which may affect quick and targeted diagnostics and effective treatment. Prevention should include three elements: (1) the availability of simple, quick tests in critical infrastructure, (2) regular education of medical personnel, simplified to the patterns of conduct within the first hours after the poisoning  and (3) securing drug reserves in forms with a long due-date, together with kits necessary for quick decontamination in the event of a mass incident.


Digital applications in health care are a concurrent research and management question, where implementation experiences are a core field of information systems research. It also contributes to fighting pandemic crises like COVID-19 because contactless information flow and speed of diagnostics are improved. This paper presents three digital application case studies from emergency medicine, administration management, and cancer diagnosis with AI support from the University Medical Centers of Münster and Göttingen in Germany. All cases highlight the potential of digitalization to increase speed and efficiency within the front end of medicine as the crucial phase before patient treatment starts. General challenges for health care project implementations and human-computer interaction (HCI) concepts in health care are derived and discussed, including the importance of specific processes together with user analysis and adaption. A derived concept for HCI includes the criteria speed, accuracy, modularity, and individuality to achieve sustainable improvements within the front end of medicine. Digitalization and digital applications are current topics in health care management research and practice  ,5,6,7,8.A comparison of the cases offers valuable insights regarding the shared challenges and features for digital applications in health care that address the human–computer interaction (HCI) domain. Health care systems are typically characterized by their need for a human-centered approach owing to the inclusion of high-priority questions, such as the timely provision of medical items, personnel, and resources to injured or ill people. The health technology sector has experienced rapid growth in recent years due to the high demand for digital services and products. Such services not only improve health care quality but also reduce cost and increase efficiency in hospital work processes . The advantages of artificial intelligence (AI) implementation especially support these processes and provide the opportunity for automated data-driven analyses that increase efficiency and quality in medical treatment . In thisConsiderable research has been conducted to define HCI principles and develop evaluation models in information systems (IS). The beginnings of this research date back to the late 1970s, when computers from the back office came to the organizational front lines in the form of time-sharing systems and later in the form of office productivity tools on personal computers. The initial thematic focus was on the material characteristics of computers such as keyboard design or the ergonomic factors that influence user efficiency. Much of the later research, which ultimately distinguished HCI as a field in its own right, focused on how forms of computer interaction enabled or hindered user behavior based on the availability of designed computer functions. Hence the goal of HCI is to investigate the phenomenon of user interaction with technology and understand the implications of design on this interaction. The review of HCI-related publications shows a growing body of literature that uses models, principles, and rules to evaluate HCI elements such as usability, user experience, and aesthetics in different IS ,16,17,18Altogether, some thoughts and resources have been invested in this important sector of HCI in general and within the health care and hospital management sub-field. However, these efforts are insufficient due to three reasons and the need for HCI concepts to evolve. First, resource constraints are increasing faster, which not only affects material and budgets but also the availability of experienced care and medical personnel. This situation implies that digital systems must take over labor and processes sooner than later and support the training of inexperienced staff, thereby increasing the complexity of HCI. Second, technology itself allows for substantial changes in HCI as systems become increasingly autonomous in their analysis and decisions, even in communicating and interacting with one another. Consequently, tasks for and interactions with humans also change as their roles shift increasingly toward supervision and exception handling. Third, an increasing conflict between the required sustainability of digital systems and the increasing speed of hardware and software development, especially in the health care sector, likewise demands new solutions for HCI, including ad hoc revisions and updates addressing possible crises. This paper contributes to the literature in two ways: first, (a) three use cases for digital applications with their individual technical and organizational requirements are described for broader comparison and learning; and second, (b) the generalization of insights from the three cases supplies the opportunity to recognize shared challenges to all digital applications in health care, centered in the HCI field for the specific requirements of medical personnel. The structure of this paper is as follows. HCI research is defined as “a discipline concerned with the design, evaluation, and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them” . It typiSeveral features like the multitude of actor groups inside and outside the hospital and the interaction of a large number of IS make the HCI requirements in the front end of medicine (before patient treatment) special . As variThe interface between emergency medical services (EMS) and inpatient care in emergency departments (EDs) is of major importance to the front end of medicine before patients are treated ,34. It iSuccessful EMS depends on fast, high-quality care and the effective communication between all participants. As opposed to other countries, EMS in Germany includes the care of emergency doctors at the site of the emergency. Typically, paramedics are the first EMS to arrive at the emergency site, followed by an emergency doctor. Emergency doctors must have completed special training and have experiences in a relevant medical specialty, such as internal medicine, surgery, or anesthesiology. Once the emergency doctor has assessed and stabilized the patient, it is crucial that the patient is quickly transported to the nearest appropriate hospital. Clarke et al. show that after 90 min the mortality of patients with abdominal trauma increases by 1% every 3 min . The selhttps://eena.org/advanced-mobile-location-aml-report-card (accessed on 17 September 2022).; http://www.traumaregister-dgu.de. (accessed on 17 September 2022)). This frequency defines a certain injury pattern, which represents the relative distribution of injury frequencies in certain body regions. To achieve high coverage during the conception phase, the following relevant cases could be identified using TraumaRegister DGU: head, thorax, extremities/spine, and fractures. Based on this, a process analysis method is used that conveys a comprehensive and complete process overview and creates a vitalization for all participants and the requirements analysis. In addition to the visualization of the whole rescue process, associated information flows are included. The recording of these steps follows the time axis with a chronological and functional time reference. Subsequently, the recorded process is represented and used as basis for annotations for improvement  determination of relevant processes/cases, (ii) process recordings in the form of expert workshops, and (iii) annotation of identified user requirements. To determine the relevant processes or cases, different statistics on severely injured persons are analyzed. Within the statistics, the number of serious injuries is examined according to certain injury patterns. A suitable case categorization proposal is the injury pattern of the TraumaRegister DGU. The annual report of TraumaRegister DGU determines the frequency of various injuries in nine body regions with a severity of at least 2 points . On a technical level, the system must integrate a functionality to transfer information to a display within the resuscitation room. In case of multiple resuscitation rooms within a clinic, the possibility of selecting a resuscitation room from a list should be integrated.To come up with a solution for the requirements specified during the workshops, three distinct applications were created: (1) a smart phone application for the emergency doctor, (2) a smart phone application for the hospital staff , and (3) a web application to be deployed in the resuscitation room itself. One example would be the question about the patient’s current heart rate, which could be answered with one of three options: <60, 60–100, or >100. We decided to follow this idea instead of giving the emergency doctors the option to enter free text for two reasons. First, it helps focus on valuable information instead of unnecessary details . Second, it helps speed up the information-gathering process. After the emergency doctor decides which hospital he wants to approach, the collected information will be transmitted to the hospital (Step 2). This decision is supported by the application by showing the certification level of the hospital issued by “TraumaNetzwerk DGU” and the capacity of the hospital. Starting from the beginning of the information transmission to a certain hospital until the emergency is manually finished—normally when the emergency doctor hands over the patient to the hospital staff—the application tries to send yet-unsent information continuously (Step 3) and submits the current location of the emergency doctor to the target hospital (Step 4). The resuscitation room leader will be notified of the incoming emergency through push notifications in the mobile phone and can view the submitted information. The emergency case can also be assigned to a monitor mounted in the resuscitation room where the information is displayed for the whole team (Steps 5 and 6). The information is presented until the team leader marks the emergency case as finished (Step 7). HCI concept developments were included in the digital application, especially in the speedy inclusion of EMS data at accident sites for emergency personnel before patient transportation to hospitals. Speedy and exact data acquisition from personnel into a digital app for delivery to the addressed hospital were of central importance in providing the least hindrances to EMS personnel and, at the same time, maximum information and preparedness options for the receiving hospital staff. While a centralized platform  for patient data is envisioned to enable data exchange between different health care institutions and platforms , analog Last but not least, diagnosis and treatment data must be coded for billing in the DRG system. These repetitive entries are time-consuming and error-prone. This case study aims for automated data extraction of routine findings from non-structured PDF documents. As a proof of principle, the extraction of the TNM tumor formula from a pathology finding was to be carried out. The TNM classification describes the size of a tumor (T), as well as the involvement of lymph nodes (N) and the presence of metastases (M). Furthermore, characteristics of the local growth behavior are coded , invasion into vein (V), completeness of operation (R)) . ColorecTo identify the relevant functional requirements of a potential digital solution to the described problem, focus group discussions and interviews were conducted with experts  from the UMG. Furthermore, literature was identified that underlines the aspects of the experts and provides approaches for technical realizations. Overall, three requirements were identified. First, process automation through digital software eases the workload of medical personnel who would otherwise have to complete these processes manually. The manual transfer of data into IS, even though these data already exist, is an example of such a process. Media disruption causes medical staff to transfer the information they need into multiple digital systems until now. Experts indicated that manual data entry takes up to 5 min per patient, time which could be used to interact with the patient and improve the quality of care . TherefoFor information occurring in fixed patterns, such as TNM codes, pattern recognition and regular expressions (regex) have proven to be very efficient . In GermA concept was developed consisting of an expert interaction module (EIM) and a feature extraction module (FEM) . The EIMThe EIM implements the complete pipeline from analog paper-based reports to visualization of the automated extracted features that can be validated by the medical expert. In the first step, the paper-based medical report was digitized through a scan. This step is a common standard because the documents are usually saved as pdf attachments. Second, the digital document was converted into a text document through optical character recognition. In this text format, the data were forwarded to the FEM for information extraction. For the visualization, the EIM expects the individual features with their extracted values from the FEM. Each feature has, next to its value, a list of information relevant to the prediction . A user interface  was desip ≥ 95%, yellow for p ≥ 90%, and red for p < 90%)  . The feaTo obtain a comparable result for the automated feature extraction, the same pathological findings were manually coded by a medical postgraduate student. The student coded the data twice  to ensure validity. This coding was expected to represent the comparable truths. However, the comparison of both data sets, indicated that even the manual coding included a few errors . The corOverall, the results show that the automated transmission results in an accuracy of 93.5% for complete data, however the individual features are extracted with an accuracy of 97.5% or higher. For further evaluation, the absolute errors on an aggregated patient level were compared. The EIM expected a validation of the extracted feature in 9 cases, where the algorithm examined ambiguous results. Therefore, medical personnel were only required to manually assess the finding of 9 patients. In comparison to the current procedure, where medical personnel manually copy the information for all cases, the automated transmission is a tame-saving and accurate alternative. The results provide a proof of concept for the automation of feature extraction based on text mining methods  as an alternative to error-prone, repetitive manual evaluations. However, the evaluation of the algorithm was conducted through a small sample of pathological findings and should be validated through a larger sample. An extension of the data pool could improve the results here on the one hand and enable a broad application on the other hand. An evaluation of additional documents, for example for other tumor entities, could lead to a further improvement of the algorithm as well. This use case shows that an automated data extraction with sufficient reliability is possible with reasonable effort and could be useful for clinical routine and research. Further development of corresponding algorithms with transferability to findings from different practice management systems and hospital IS could contribute to reducing the documentation effort and improving the data usability for clinic and research.The described information from medical reports is of high importance for medical staff and must be equally and accurately available in each of the used systems. Hence, it was crucial not to develop a black-box solution for automation but to integrate an interface for simple verification and validation. The user interface is intuitive to use and dynamically displays the relevant points in the existing findings. The supervised learning approach based on user feedback ensures that the physicians improve the algorithm and thus learn to trust it, with the result that, at a certain point, manual validation and interaction are only necessary in a limited number of cases.The complex and challenging case of head and neck tumor treatment often affects bone, soft tissue, and the tumor microenvironment at the invasive edge of tumor transition . Head anfind the most important attributes for treatment decisions,predict an optimal treatment for a patient based on all available attributes, andestimate the prediction accuracy.Such multilateral and complex approaches lead to interlocking medical treatments that are effective particularly for head and neck cancers ,64. HoweTo address these requirements and include the increasing tumor complexity, a Division-of-Labor (DoL) structure can support DSSs and offer a framework for developing durable ML systems . Such DoWe develop a DSS that (1) finds the most important attributes for treatment decisions, (2) predicts an optimal treatment for a patient based on all available attributes (not restricted to the most important ones), and (3) estimates the prediction accuracy. In the following, we describe the components of the developed DSS. Expert: We divide an Expert’s tasks into learning tasks, performed when the Expert receives new labeled data, and analysis tasks, performed when the Expert is queried for information. The learning tasks of an Expert are defined as (1) learning attribute importance ratings for each of the 6 treatment decisions and (2) modeling the relationship between the 160 features and the treatment decisions. Each time an Expert is provided with a data element, it updates its learning models for both tasks in an online manner and returns the suggested treatment decisions.Central Executive: Again, we divide the CE’s tasks into learning tasks and analysis tasks. The CE has a single learning task of performing patient segmentation and creating/updating an Expert for each segment. The analysis tasks involve (1) querying the most suitable Expert for a prediction and (2) identifying the most important attributes for decision making.Base Models: For our DoL system, we use of three kinds of ML models. First, we employ a feature selection method, namely, the least absolute shrinkage and selection operator , to ideAs to requirement (1), the following The attributes identified by the DSS are evaluated with respect to their validity by multiple physicians from the UMG. On the one hand, many identified attributes confirm existing theory on head and neck cancer treatments and are already used by physicians to make decisions, such as tumor-(T)-classification, lymph node-(N)-classification, and metastasis-(M)-classification. The TNM classification of malignant tumors, comprising a patient’s T-, N-, and M-status, was developed by the Union for International Cancer Control and is globally recognized as a standard for classifying the extent of spread of cancer. Derived from the TNM classification, head and neck tumors are grouped into clinical stages, an attribute that our DSS also identifies as a significant contributor to the treatment plan. On the other hand, the DSS identifies attributes that researchers and practitioners do not typically consider for making treatment plans, such as a patient’s reasons for the initial visit to the doctor, an attribute that has limited causal implications but is of statistical importance for treatment decisions, as well as attributes that have not yet been introduced into medical guidelines but have been the focus of ongoing research, such as the inflammatory response of tissues surrounding a tumor. The invasive potential of cancer is dependent on the tumor environment and its interactions at the invasive edge of cancer . As to rteration .Generally speaking, the DoL system based on logistic regression achieves the highest performance. Note that this particular model was implemented in an online manner, as initial analyses revealed its superior performance in contrast to other models implemented as batch models. Noteworthy classification tasks are the recommendation of an “operation” and the recommendation of an “other therapy.” The former is the only task for which the prior classifier is not (significantly) outperformed by the other models. For the latter task, multiple classifiers are tied in terms of highest accuracy. This outcome can be explained by the fact that these attributes have highly imbalanced values; about 92% of the recorded patients have received an “operation” while about 98% have not received “other therapy.” Classifiers, therefore, tend to recommend an operation and no other therapy for every data element. The DNN generally performed poorly. This poor performance can be explained by the small sample size, which is generally not suitable for highly complex models such as DNNs. We developed an intelligent DSS that is evidence based and makes situationally relevant recommendations . It achiThe surgeons within this case clarified that they do not want to have to use another IT system as they were very cautious about potential distractions from their work and further administrative efforts. Nevertheless, they were very interested in the outcomes the system provided. These outcomes were primarily numerical and categorical (see tables above). The surgeons perceived the insights generated by the system as starting points for further discussions or even new research projects. Therefore, no graphical use interface has been developed. Instead, the results of the system were delivered to surgeons upon request in the form of tables and graphs with no further interaction possibility. Accordingly, what emerged was a more indirect and cognitive interaction, not a direct and technical interaction between the system and the human experts. The surgeons found that the system’s value does not lie in the automation of the decision processes around treatment recommendations. They had the feeling that, in the best case, the system could provide what they already do. Instead, the human experts were fascinated by unconventional findings of the system that were surprising. These outcomes of the system were then discussed in the group of surgeons and could trigger further investigations. Thus, the input by the system may deliver new inputs for exploration and learning. The implementation of digital applications as outlined by the three case studies highlights the relevance of detailed process and requirements analyses, especially in health care contexts. Specific requirements toward HCI concepts arise from the complex environment of health care  and a dedicated process complexity due to highly specialized work tasks and a high division of labor for a series of actors and organizations in this sector. Accuracy: For the Münster use case, accuracy plays a central role given that information regarding severely injured persons is transported digitally to the medical center. Therefore, data input and specific information sequences are of high relevance. This is addressed in the digital application, where specific fields for medical data are included. For the second case from Göttingen, the central information required is compressed into codes. Accuracy is the essential criterion when transmitting this information since individual letters and numbers determine the diagnosis and treatment of the patient. Therefore, the automatic extraction is additionally validated by the medical expert if the algorithm is below the set threshold of accuracy. For the third case from Göttingen, medical insights such as the relevance of certain factors for treatment recommendations were at the center of the user’s interest in the developed tool. Accordingly, the accuracy of the information is of major importance. Although this information does not automatically trigger actions, it is meant to enrich and support expert discussions. In sum, all cases share the need for high levels of accuracy. This insight underscores the importance of medical information in all phases of the medical front end. While the cases reveal differences in how this information is processed  or the purpose of their use , the accuracy of specific patient-related information is essential. Speed: Within use case 1 in Münster, the time needed for patient transport to the medical center location is crucial for treatment and survival probability. Therefore, information and decision speed for emergency personnel is one of the elements of HCI concepts for the emergency medicine sector. For use case 2, the automation of information extraction is intended to save time and manual working steps for the medical personnel. The information is transferred immediately to all necessary systems and is in this way available to the medical staff in the respective environments. In this case, speed represents a central HCI element. In use case 3, speed is an important issue. While the tool is not used for each and every decision in everyday practice, it needs to deliver results almost immediately after the surgeons request it. The tight schedule of the surgeons demands that calculation times are minimized and the tool is always ready. The DoL architecture allows for increased speed. In sum, the cases reveal that speed in HCI is of particular relevance to accelerate the front end of medical processes. On the one hand, medical conditions can create temporal pressures . On the other hand, the temporal resources of associated experts  are scarce. The time needed for HCI, either in entering, retrieving, or transferring medical information, must be minimized. Modularity: Within the first application case in Münster, a multitude of systems are included in emergency medicine processes and therefore modular setups are required. For example, this is implemented with picture and voice recording options in the developed application for EMS teams, thereby enabling individual development and innovation for digital EMS features. The second case deals with bridging the modularity of the systems used so that information is automatically transferred to systems. The developed tool also consists of a modular structure, which essentially comprises two components: feature extraction and expert interaction. While the tool developed in the reported third case from Göttingen does not encompass multiple systems, its DoL architecture and the differentiation of Experts and CEs are inherently modular. In sum, the cases illustrate the importance of modularity in the technical architectures underlying HCI at the medical front end. Although variations exist in the embedding of the respective digital applications in further systems, this insight underscores the complexity of medical processes and medical decisions. Individuality: As different user groups are involved in the first case for data processing during emergency medicine activities , individual handling and adjustment options are included in the implemented HCI concept. For example, emergency doctors can include hospital ratings and notes for future decision situations where the digital application can report on past experiences and rating data. Although the second use case from Göttingen focuses on standardized automation, the EIM requires individual feedback from physicians. Thus, transparency for the physicians is given to promote the improvement of automatic extraction. The interface is designed to show the information in a clear, traceable manner to avoid the impression of a black-box algorithm. While the system in the third case is developed for a particular hospital department, the surgeons involved varied in their experience, fields of expertise, and digital nativeness. Therefore, it was of utmost importance to display the information neutrally and clearly so that the experts could absorb them in an unbiased manner for their particular purpose. Furthermore, it was crucial to not create technological barriers hindering the accessibility of the information. In sum, the three application cases show that individuality is a particularly relevant aspect for HCI at the medical front end. The cases illustrate that a multitude of different stakeholder groups involved in the respective processes interact with the digital applications. In addition, individuals within a particular stakeholder group vary substantially in their traits and capabilities. The described case studies and the derived concept drafts as exploratory research approaches are limited in their validity due to the small empirical sample base . This liOn a strategic level, results and insights from this HCI requirements draft can be connected to two major discourse areas. First, the extension of requirement items leads to differing objectives with competing interests in HCI design. For example, increasing accuracy in data collection will work against speed and simplicity. Therefore, a core requirement for digital systems in front-end medicine sectors is to balance these conflicting objectives. To illustrate, the emergency medicine case study from Münster was confronted with the requirement of collecting patient age as an important input factor for later treatment decisions in severe trauma cases. However, implementing a text field or pulldown list for specific age data input  would have had a negative impact on speed and simplicity for users. Therefore, it was decided that only three age groups  can be ticked, making the interaction very fast and simple. This approach combines medically relevant information with the requirements of speed and simple data processing interaction for emergency medical personnel. Second, typically for front-end medicine systems, different knowledge bases are addressed and required. Besides medical knowledge, areas such as administration, organization, logistics, or other relevant topics and persons are required and integrated. These two specific framework characteristics have to be considered for successful HCI design within the front end of medicine.This paper provided detailed insights into the specific requirements and restrictions of digital applications in the front-end areas of medical processes, that is, before patient treatment starts ,82,83,84An overview was presented regarding common elements, identifying especially the necessary extraction of specific medical requirements in all three exemplary cases with elaborate instruments like process analyses, interviews, or other instruments. Moreover, the extraordinary relevance of HCI concepts and their adaption to specific health care management requirements were highlighted. An adapted HCI concept was also drafted for further evaluation and discussion. Further empirical research is highly warranted as these success factors for digital application projects in health care are the basis for effective digital transformations with a high level of improvement expectations attached.


Childhood is considered to be the most vital period for mental, physical, and social development. Even short-term deprivation of nutrition, health care, education, and affection in childhood can have long-term and irreversible negative consequences. Various social assistance programs are being launched around the world to eliminate or alleviate social problems, including those experienced by children in their immediate environment. Different solutions have been proposed around the world, but welfare systems in all countries share the following common features: social assistance is necessary and underfinanced, and social workers struggle to cope with caseloads. As a result, welfare work is stressful and not highly effective. In this study, modern Geographic Information System (GIS) tools for supporting the employees of social assistance centers (SACs) have been proposed. The data relating to welfare beneficiaries were analyzed by nonparametric kernel density estimation and divided into five datasets. The kernel density tool in ArcGIS Pro software  was used to visualize areas with a relatively high prevalence of social problems, as well as areas where the neighborhood can deliver synergistic effects. A multicriteria analysis (MCA) procedure for mapping social problems was proposed, and an algorithm was developed in the GIS environment. The generated maps deliver helpful information for supporting SAC employees, as well as monitoring, planning, and initiating preventive measures. Above all, the presented method was designed to improve living conditions by facilitating the management of welfare workers’ duties. Therefore, the proposed approach had to be effective and easy to use without an advanced knowledge of GIS tools. Temporary or permanent social problems that are too complex to be individually resolved affect many people in all countries around the world. Poverty is a multidimensional problem that thwarts the social and economic development of many nations and obstructs sustainable development. Individual crises can result from poor life choices but also from circumstances that are beyond individual control ,2. NaturVarious approaches to social assistance and different social support programs exist around the world. Regardless of the guiding principles and the implemented solutions adopted by different countries, social assistance has the following common points: it is essential—welfare programs preserve human dignity and prevent social problems from escalating; it is underfinanced—welfare programs drain the budget without generating quick and satisfactory results. In addition to cash benefits, welfare programs require personal involvement of social workers employed in social assistance centers (SACs). Social assistance programs are long-term schemes which aim to improve the beneficiaries’ skills and qualifications, eliminate harmful behaviors and overcome devastating addictions. These measures require sufficient numbers of qualified social workers and effective organization of their duties. Social assistance institutions cannot reach large numbers of geographically dispersed recipients when they are understaffed. Therefore, social welfare schemes focus on those who most need social protection and on special interventions, whereas preventive measures, although equally important, are often not taken. As a result, SAC employees are under considerable stress and suffer from case overload. Social assistance is a difficult and costly process, which is why modern technological solutions should be introduced to improve the quality of welfare services and lighten the burden of social workers.The following research hypothesis was formulated to address the above concerns: SACs require technical support, and the quality of social services can be improved by providing SACs with Geographic Information System (GIS) tools for mapping and visualizing the geographic distribution of potential welfare recipients. The main aim of this study was to propose an original GIS-based method for supporting SAC operations. A GIS-based multicriteria decision analysis was performed to map the geographic distribution and concentration of crisis events that should be addressed by social workers. The analysis relied on five sets of criteria to identify specific social problems. Five groups of negative social phenomena were identified based on a review of the literature and empirical research: (1) poverty, (2) risk of poverty, (3) personal assistance from social workers, (4) aging, and (5) domestic violence. The applicability of the proposed method was tested on the example of an SAC in a municipality, which is the smallest unit of administrative division in Poland. Data for the study were obtained from publicly available statistical datasets, the respective departments of municipal offices, SACs, and police stations. The names of the investigated towns and villages were coded to prevent stigmatization. The proposed method is universal and can be applied in all types of territorial units. The presented GIS tools are flexible and can be easily adapted to the needs of other countries by incorporating country-specific welfare data in the analysis. Data can be shared and analyzed using the Infrastructure for Spatial Information in the European Community INSPIRE . In addiA multicriteria analysis (MCA), also referred to as multiple-criteria decision-making (MCDM), multiple-criteria decision analysis (MCDA), multi-objective decision analysis (MODA), multiple-attribute decision-making (MADM), or multi-dimensional decision-making (MDDM), includes various classes of methods, techniques, and tools of varying complexity that explicitly take into account many goals and criteria (or attributes) in decision-making problems . Data viSocial welfare was an important rationale for undertaking the present study because in addition to explaining and describing specific phenomena, the proposed approach should also serve the community. Therefore, the developed method was designed to be practicable. However, the proposed methodology has to meet several conditions in order to be applicable in practice. The discussed approach for visualizing the severity of social problems is designed for social welfare employees who usually have little or no experience in working with advanced data processing tools. Therefore, the developed tool should be effective, useful, as well as relatively simple and easy to use. The employees of social welfare centers, as well as the supervising institutions (the Supreme Audit Office in Poland), rely on selected indicators to calculate the percentage share of various types of welfare payments and to determine changes in the number of welfare recipients in the analyzed period. These institutions also calculate other indices, including the poverty index and indices describing local levels of social deprivation, structure of welfare recipients, social work, social contracts, needs fulfilment, changes in foster care, and active aging.Different cultures and communities have developed various ways of empathizing with and providing social assistance for people in difficult circumstances. In some countries, welfare services are addressed only to individuals who are unable to work due to physical disability. For example, in the Republic of South Africa, social assistance consists mostly of retirement pensions, disability benefits, and child support benefits. Similar to Latin American countries, the South African welfare system relies on the fundamental assumption that social services should be addressed only to physically disabled people, whereas healthy individuals should be able to secure their livelihoods through work  and shouSocial assistance is provided by SAC employees. Social work is a profession that requires high qualifications, and it is physically and psychologically demanding. Social workers must be sensitive, empathetic, able to effectively plan their operations and work under stress because SACs tend to be understaffed. The British Local Government Association has developed eight standards for supporting the employment of social workers across different agencies, including transparent systems for workload planning and agenda management. Social assistance is also chronically underfinanced. An audit conducted by the Polish Supreme Audit Office in 2018 revealed numerous problems that undermine social workers’ effectiveness. Above all, SACs were understaffed, and the number of cases handled by social workers exceeded their contractual workload three-fold. Welfare needs were not regularly monitored and addressed in real time to prevent future problems. Predictions regarding the number of individuals in need of support were developed based on statistical data within a strict financial framework rather than based on assessments of real-world needs. Information about local needs was not presented in reports or planning documents, which prevented SACs from planning realistic budgets and addressing current needs. Social workers in other countries, including the United Kingdom, face similar difficulties . The impIn Poland, municipal authorities are responsible for fulfilling local communities’ basic social needs, and this goal is accomplished by dedicated organizations, namely social assistance centers (SACs). Each welfare district is divided into smaller areas where social assistance is provided by dedicated SAC employees. Social workers perform office duties and help welfare recipients directly in their place of residence (within their respective districts). They regularly monitor the beneficiaries’ life situation by visiting homes, performing comprehensive family assessments, working with various institutions, undertaking preventive measures to minimize the risk of social problems, and responding to domestic violence during interventions.Social assistance consists of various types of services. Individuals and households with incomes below the poverty threshold are eligible to social assistance, including cash benefits, noncash benefits, counseling, and support. Pursuant to the provisions of the Social Assistance Act of 2004, social assistance services are provided to individuals and families affected by poverty, orphanhood, homelessness, unemployment, disability, and violence, to protect human trafficking victims, support large families and destitute mothers, promote social inclusion of young offenders leaving detention facilities, prevent alcoholism and drug abuse, support individuals and families affected by a personal crisis, or a natural or environmental disaster. Individuals and families who are experiencing a crisis for at least one of the above reasons and whose incomes are below the poverty threshold are entitled to cash benefits and social assistance.(1)regular benefits for individuals who are permanently unable to work due to old age or disability;temporary benefits for individuals affected by prolonged illness, disability or unemployment;targeted benefits that meet specific life needs, such as total or partial reimbursement of the costs associated with medication or food purchases;cash benefits , including(2)noncash benefits , including shelter, meals, clothing, personal care, accommodation in welfare homes, and housing benefits (help towards rent).Social assistance includes the following:Social assistance is also provided to individuals and families who are affected by specific problems and are at risk of social exclusion, regardless of income. Beneficiaries are expected to cooperate with social workers to resolve their life difficulties. Benefits and social assistance may be revoked or limited, and cash benefits can be replaced with noncash benefits, when beneficiaries abuse the welfare program. Social workers monitor the recipients’ progress to ensure that the awarded benefits are spent properly. Modern GIS tools can be applied to support SAC employees who regularly visit the beneficiaries’ homes in the process of planning their trips.Children are a special category of welfare recipients. As childhood is the most vital period during mental, physical, and social development, short-term deprivation of nutrition, health care, education, and affection in childhood could have long-term irreversible consequences . It is uIn Poland, family assistants work with dysfunctional families to prevent negative patterns from being repeated by household members, including children. Assistants provide dysfunctional families with support, give advice, and promote positive social behaviors. The main role of a family assistant is to manage and counteract social problems in dysfunctional families. Assistants assume the role of mediators, representatives, and counselors who give support to families and encourage them to actively participate in the process of overcoming their problems. They undertake various measures to change the family dynamics, motivate family members to initiate positive changes, and build a sense of self-worth in family members. Assistants also prepare families to assume age-appropriate social roles; they motivate family members to improve their qualifications and find work. Assistants must be highly motivated to encourage all members of dysfunctional families to take active steps towards improving their fate and rebuilding family ties .Social assistance centers protect disadvantaged children and prevent social problems from propagating. These tasks pose an immense challenge for SAC employees who are not only expected to manage crisis situations, but also to prevent them. To effectively counteract social problems, social workers have to regularly monitor the environment in which children are raised, including their homes (support in the resolution of family problems) as well as the neighborhood (support for entire districts or communities). Maps generated with the use of the proposed method can be very helpful in this process.The following research hypothesis was formulated: maps presenting the location and intensity of social problems or the risk of social problems in a given area constitute effective tools that support the operations of SACs. Social problems are a complex and multi-faceted issue, which is why numerous, unrelated sources of data had to be obtained for research purposes. As a result, the study was conducted in four stages: I, Data acquisition; II, Development of an integrated database; III, Development of thematically linked datasets; IV, Generation of thematically linked maps in GIS. The research process was designed with the use of the MCA algorithm which is presented in In stage I, data relating to poverty and other crisis situations were aggregated. In most countries, including Poland, eligibility for social assistance is determined mainly based on income. The Social Assistance Act stipulates that the main goal of social assistance is to support individuals and families affected by poverty, orphanhood, homelessness, unemployment, disability, prolonged or serious illness, domestic violence; to protect human trafficking victims, support large families and destitute mothers, individuals who require assistance with childcare and household matters, in particular in broken, single-parent or large families; to promote the integration of foreigners who have been granted refugee status, subsidiary protection, or a temporary residence permit; to promote social inclusion of offenders leaving detention facilities; to prevent alcoholism and drug abuse, support individuals and families affected by a personal crisis, or a natural or environmental disaster. The existing types and forms of social assistance are prescribed by legal regulations. The provisions of Polish legal acts were analyzed to determine the number of welfare recipients in various categories. The relevant databases are kept by SACs in Polish municipalities. Population data, the number of large families (with at least three children), and the age structure of the population were determined based on the data obtained from the civil registry department of the municipal office. The rate of population aging and the aging index were calculated. Information about the availability of social housing, the number of evictions from social housing, and the number of people who are in arrears with rent payments was obtained from the real estate department of the municipal office. Information about the number of domestic violence interventions and the number of families covered by the Blue Card procedure (families that are registered and monitored due to a history of domestic violence) was acquired from the local police station.In stage II, the data acquired from the above sources were used to develop an integrated database. The gathered data were divided into thematic groups and linked with welfare districts according to the territorial division system applied by SACs. Five groups of negative social phenomena were identified based on a review of the literature and empirical research.In stage III, each of the identified crisis phenomena was linked with information about the types of provided social assistance or the description of a social problem. The resulting datasets and their characteristics are presented in Dataset 1 contains information about actual poverty. Poverty was visualized by the number of households receiving income support and housing benefits. Dataset 2 describes the risk of poverty. Each of the described social problems contributes to the risk of a crisis situation. The accumulation of social problems also jeopardizes the well-being of children residing in high-risk areas. For instance, children who grow up in areas affected by alcoholism or drug abuse are more likely to adopt dysfunctional behaviors and carry them into adulthood. Dataset 3 was identified to describe cases where individuals required assistance in coping with childcare or household tasks. Social workers regularly visit such households to provide beneficiaries with help in daily matters. Dataset 4 has prognostic value. Persons living in areas with a high age dependency ratio are likely to require social assistance in the near future. Dataset 5 contains information about domestic violence. Domestic violence is a serious and complex problem which requires preventive measures and, if such measures are ineffective, interventions conducted by social workers with the assistance of the police and healthcare professionals .In stage IV of the research procedure, the results of the analyses conducted in the previous stages were visualized on thematic maps. An algorithm for mapping social data was developed by the authors. Kernel density, raster reclassify, and raster calculator tools were used for this purpose. The authors relied on GIS tools that are widely applied in various scientific disciplines to process and analyze spatial data . Based ok0–quadratic kernel functionλ–smoothing parameterGIS tools are highly useful for visualizing research results on maps , and thet ≤ 1 in the remaining casesi = 1,…, n are the input points. Only points located within the search radius from location  are included in the sum;ipop is the population field value of point i, which is an optional parameter;idist is the distance between point i and the location .This function is implemented in the Kernel Density tool in Esri ArcGIS software . The category of point features is selected, and the Kernel Density tool calculates surfaces that are fitted to each point. The Kernel Density tool calculates the density of features in the neighborhood around those features. It can be calculated for both point and line features . Kernel Kernel Interpolation is a variant of first-order Local Polynomial Interpolation, where a method similar to ridge regression in the estimation of regression coefficients is applied to prevent the instability of the calculations. When the estimate has only a small bias and is much more precise than an unbiased estimator, it may well be the preferred estimator . The EpaIn the procedure, the aggregated statistical data were used to build a database. The purpose of using specific databases (minimum databases and problem-specific databases) is to ensure systematic and consistent data collection . The relKernel Density maps were developed for each studied feature. Each map was reclassified on the same scale, and in the next step, the maps illustrating the distribution of features assigned to a given social problem  were appThe proposed method was used to generate maps presenting five sets of data (1 to 5) in the analyzed area. The spatial distribution of poverty areas is visualized in Map 1 .The second dataset was visualized in Map 2 to present areas that may be affected by poverty in the future due to the spatial concentration of risk factors for social problems. It should be noted that Maps 1 and 2 contain the same areas marked in dark blue , but differences between the two maps can also be observed . In both maps, areas marked with the darkest shade of blue represent welfare districts affected by permanent poverty. Despite income support payments , social problems that increase the risk of poverty are still prevalent in these areas. Therefore, these areas should be closely monitored to identify possible solutions to the existing problems. In turn, a certain discrepancy can be observed in area No. 3, where the number of social assistance services exceeds the number of reported problems. There are two possible explanations for the above: the situation has improved, and the number of welfare benefits is likely to decrease in the following year, or the existing social problems were overestimated, which led to the payment of higher benefits. These observations indicate that area No. 3 should be monitored closely in the future. The status of districts No. 6 and 13 and the surrounding areas should also be controlled. Despite the presence of social factors contributing to the risk of poverty, the number of welfare beneficiaries was very low or low in these areas. These districts should be analyzed in detail and included in prevention programs. Special measures should be also initiated to protect children in areas that are at risk of poverty. Districts marked in darker shades of blue are affected by social problems such as unemployment, lack of parenting skills, and alcoholism. The spatial distribution of different risk factors can be visualized on maps in successive analyses. Areas where the risk of social problems is particularly high due to neighborhood effects were also identified. For example, in areas No. 1 and 2, the accumulation of negative social phenomena is moderate, but the fact that these districts are neighbors can contribute to synergistic effects . In other cases, an area with a lower prevalence of social problems can be potentially threatened by the accumulation of negative phenomena in the immediate neighborhood. This situation can be observed in district No. 11 which remains under the direct influence of districts No. 4, 16, and 17. It should also be noted that neighborhood exerts a particularly strong effect on children—exposure to negative behaviors and social patterns during childhood affects life choices in adulthood ,47,48. FThe spatial distribution of the third dataset was visualized in Map 3 . This daThe risk of domestic violence (dataset 4) is presented in Map 4 .. The seThe fifth dataset has prognostic value, and it is visualized in Map 5 . This daChildhood is a time that should be particularly protected. Children should grow and develop in a safe and healthy environment. Therefore, social workers should attempt to eliminate social problems in specific areas. This study investigated the applicability of modern GIS tools for supporting the management of social welfare programs. Their applicability was expanded to include another group of users—SAC employees. The proposed solution was tested in a case study of a Polish municipality, and GIS tools were used to visualize the spatial distribution of social problems and persons in crisis.It is worth noting that social welfare centers rarely use modern methods of data analysis. In most cases, the results are expressed in percentages which are used to calculate the relevant indicators, such as the ratio of long-term welfare recipients to the total number of welfare recipients. Social welfare organizations are understaffed in all countries around the world, and welfare employees rarely have experience in using data processing systems because most of them have degrees in pedagogy, special education, political science, social policy, psychology, sociology, or family science. Therefore, the methods for facilitating social work must be both effective and easy to use.The fact that many countries, including Poland, have not developed cohesive databases of social problems poses a significant limitation in research dedicated to social phenomena. Data from different, unrelated sources were acquired for the needs of this study. The relevant information is not exchanged between institutions that generate such data. The authors did not have access to variables describing the magnitude of the analyzed problems, such as alcoholism. The relevant databases contain only information about the number of registered individuals with an addiction problem. These limitations further accentuate the need for an integrated database of the social problems identified in this study.The key result of the present study was the observation that the nonparametric density estimator function in Esri ArcGIS software can be applied to process information about welfare beneficiaries and generate maps containing useful information. Social assistance involves temporary relief for persons in need, but also preventive measures and programs that enable individuals, families and entire communities to fully tap into their potential. Welfare support is essential for the achievement of sustainable development goals.The study confirmed that GIS tools are useful for developing an MCA procedure for social sciences. An algorithm for visualizing five social phenomena was developed. This approach does not involve a prescribed method for compiling suitability or constraint maps because the Reclassify tool supports data transformation on the same scale, but the analyst must apply the same classification method. The analyst is also tasked with identifying the most effective method of qualifying the examined features/criteria. Above all, the same method should be applied to all raster reclassified data. Raw data (features) should also be selected at the analyst’s discretion. This is a useful option when the analyst does not have access to a full set of data or chooses different criteria than those presented in this article. It enables the analyst to select or eliminate key data describing a given social phenomenon. Despite the fact that the proposed tool is easy to use, the selection of features is a more difficult task; therefore, the analyst should have a working knowledge of the studied phenomena and the GIS environment. The tools available in the Arc GIS Pro program were used in this study. However, according to Abastante et al. , QGIS shThe empirical results of the study revealed welfare districts with a high prevalence of social problems as well as areas whose welfare status could deteriorate due to the synergistic effects of problematic districts in the immediate neighborhood. The generated maps can be compared to make interesting observations. For example, a map presenting the number of registered income support beneficiaries in a given area was compared with a map illustrating areas that are at risk of poverty due to the presence of social factors that contribute to poverty.The results of this study can be useful for SAC employees who are responsible for planning and managing social assistance services. Social workers can rely on the generated maps to plan visits to the supported families and households, monitor their progress and plan preventive measures. The present findings also have important implications for children from dysfunctional families. By identifying areas with the highest concentration of social problems, SACs can implement preventive programs to ensure that negative social patterns learned by children in dysfunctional families are not carried into adulthood. These observations are of great practical importance not only for Polish SACs, but also for welfare organizations in other countries. The proposed method is universal, and it can be applied in all types of territorial units. The presented GIS tool is flexible, and it can be easily adapted to the needs of other countries by incorporating country-specific welfare data in the analysis. The study has considerable practical relevance because it offers an effective method for adapting the existing GIS tools to new uses.


This paper uses a large-scale nationally representative dataset to examine the nonlinear effect of income on mental health. To investigate their causal relationship, the exogenous impact of automation on income is utilized as the instrument variable (IV). In addition, to explore their nonlinear relationship, both income and its quadratic term are included in regressions. It is found that the impact of income on mental health is U-shaped rather than linear. The turning point (7.698) of this nonlinear relation is near the midpoint of the income interval . This suggests that depression declines as income increases at the lower-income level. However, beyond middle income, further increases in income take pronounced mental health costs, leading to a positive relationship between the two factors. We further exclude the possibility of more complex nonlinear relationships by testing higher order terms of income. In addition, robustness checks, using other instrument variables and mental health indicators, different IV models and placebo analysis, all support above conclusions. Heterogeneity analysis demonstrates that males, older workers, ethnic minorities and those with lower health and socioeconomic status experience higher levels of depression. Highly educated and urban residents suffer from greater mental disorders after the turning point. Religious believers and Communist Party of China members are mentally healthier at lower income levels, meaning that religious and political beliefs moderate the relationship between income and mental health. In the area of mental health, an almost universally accepted conclusion is that depression is inversely related to income . In earlWorld Happiness Report, data show that the COVID-19 outbreak significantly reduced both income and life satisfaction , conducted in 2017 and 2018. CGSS is one of the most important national, comprehensive and continuous academic survey projects in China. CGSS is in the world General Social Survey family, jointly carried out jointly by Renmin University of China and Hong Kong University of Science and Technology. The sampling of CGSS is based on the multi-stage stratified design. It aims to gather data on Chinese society to monitor and explain trends in income, attributes, behaviors, health and attitudes to examine the structure and functioning of society in general. Details of the study protocol and data files are introduced in the Unraveling the effect of income on mental health is difficult because randomized controlled trials of income are almost not available. The main endogeneity issue here is reverse causality, whereby mental health also affects income . TherefoIn the model, Dictionary of Occupational Titles by the United States Department of Labor in 1977. Because the individual traits of current workers could not affect the characteristics of occupations in 1977, this instrument variable well satisfies the exogeneity condition from the perspective of avoiding reverse causality. Therefore, this paper can use above 2SLS model to scientifically investigate how income affects mental health based on dealing with endogeneity.In this 2SLS model, the instrument variable is This measure ranges from-6.190 to 4.235. According to this index, the The explained variable used in this paper is the depression level of the individual. This variable is based on the classic Likert scale from 1 to 5 to characterize people’s depression level. In CGSS, this indicator comes from respondents’ intensity of feeling depressed, from not depressed, mildly depressed, moderately depressed, very depressed to severely depressed. This indicator is also one of the most commonly used depression indicators in the existing literature . The expEstimation results using above 2SLS model are demonstrated in Specifically, according to the results in column (6) of Based on the above analysis, we naturally further propose the question: Whether the relationship between income and depression is a U-shaped relationship or a more complex one with more turning points, such as a W-shaped or M-shaped relation. We test this hypothesis by further incorporating the cubic term of income, p values of their estimates should be larger than 0.1. We conduct robustness checks on the U-shaped effects of income on mental health in the following four aspects. First, the sample sizes are different from Columns (1) to (6). The reason is that the numbers of different control variables’ observations are slightly different. Consequently, as more control variables are added in the regressions, sample size decreases to some extent. Naturally, we are concerned whether this affects the analytical results of this paper. We further conduct a robustness test and the results are shown in This paper further investigates the heterogeneity of the U-shaped relationship between income and depression in multiple aspects and the results are illustrated in With regard to regional heterogeneity, results show that below the turning point, urban residents have lower levels of depression. But at the high-income stage, they take on more burden of mental disorders. This may be caused by the fact that the urban labor market is more competitive and the mental health costs of improving incomes are higher. As to health heterogeneity, self-rated healthy respondents have lower levels of depression and a much bigger turning point of the U-shaped relationship. This means that the overall health status is closely associated with mental health and those with higher overall health status tend to be mentally healthier. Regarding socioeconomic status, the higher socioeconomic status group is less depressed. Its turning point of the nonlinear relationship is much larger and the U-shaped curve is relatively flatter. This means lower mental health costs to improve income for the higher socioeconomic group.Concerning social identity, we examine the heterogeneities in the aspects of ethnicity, religious belief and political identity. Analytical results show that ethnic minorities have higher levels of depression. Especially in the high-income stage, their mental health cost to further increase income is obviously higher. In general, religious believers’ mental health condition is better. Moreover, there is no significant difference in depression between Chinese Communist Party (CPC) members and non-CPC members. However, in the lower income interval, CCP members have higher levels of mental health. This may be due to the fact that CCP members are educated and required to sacrifice selflessly, making them easier to accept lower income.Using a large-scale nationally representative survey, the Chinese General Social Survey (CGSS), this paper systematically explores the relationship between income and mental health. In terms of research methods, we use the exogenous impact of automation on income as the instrument variable and investigate income’s impact on depression based on scientifically dealing with endogeneity. In addition, to examine the nonlinear relationship between income and depression, we analyze both income and its quadratic term in regressions. Results demonstrate that the estimated coefficients of income and its square are statistically negative and positive, respectively. This means that the relationship between income and mental health is U-shaped rather than a simple linear correlation. The turning point (7.698) of the U-shaped effect is close to the midpoint of the income interval . This suggests that, in lower levels of income, depression declines as income rises. However, beyond the turning point around middle income, further increases in income bring about notable mental health costs, leading to a positive relationship between the two factors. Findings of the nonlinear causal relationship contribute to the existing literature where a simple linear correlation between income and mental health is assumed. In addition, we also exclude the possibility of more complex nonlinear relationships between income and mental health. Moreover, robustness tests are carried out, such as using other types of instrument variables, mental health indicators and IV models, as well as placebo analysis. Their results further confirm that the U-shaped effects of income on mental health are robust.Most of existing studies conclude that there is a linear relationship between income and mental health, which is proved to be positive in both earlier studies e.g.,  and more: The Causes of Happiness and Misery. The research in this report analyzes the possible nonlinear relationship between income and mental health from a theoretical perspective, that is, income positively affects mental health with diminishing marginal returns  returns . However returns . Specifi returns . It is fBesides, this paper conducts a detailed analysis on the heterogeneity of the U-shaped relationship between income and depression in multiple aspects. It is shown that men, older workers, minority groups and those with lower health and socioeconomic status experience higher levels of depression at nearly all income levels compared with their counterparts. These findings are consistent with existing literature. For example, it is concluded that groups with lower socioeconomic status have higher rates of mental illness . In addiWe further compare the results of this paper with existing studies based on Chinese samples as well as those in other countries from the perspective of international comparisons. The literature reveals that studies focusing on China in this area are very limited. It also means that this study contributes to the literature by providing novel evidence on the relationship between income and mental disorders among Chinese people. Existing studies using Chinese samples e.g.,  mainly uper capita income, the turning point for Chinese people may be lower. Therefore, for other countries, whether there exists a nonlinear relationship between income and depression, and whether the turning point varies with different levels of economic development, is a valuable direction for further research. Second, China is a country profoundly influenced by Confucianism, a culture that emphasizes that people should bear working pressure, contribute to their family and be responsible for both supporting their parents and raising children. Therefore, Chinese people may have a higher tolerance for working pressure and working hours, which may also lead to a larger turning point in the Chinese sample. In view of this, an international comparative study of the nonlinear relationship between income and depression based on the comparable microdata of China and other countries would be a very meaningful research direction.In addition, the particularity of the relationship between income and depression in China should be emphasized, which may be reflected in two aspects. First of all, China is a middle-income developing country. Therefore, compared with those in developed economies, Chinese people may have a more urgent need to further improve their income, a greater tolerance for stress caused by work, and thus a higher turning point in the relationship between income and depression. But compared to countries with lower Clinical implications of the study include: First, our results reveal that the relationship between income and mental health is U-shaped rather than a simple linear correlation. This confirms that when people’s income exceeds the median income, further increase in income takes considerable mental health costs. From clinical experience, it is also found that the depression problem in the high-income group is very prominent because of increased work pressure. Therefore, for people with higher income, it is of great importance to be aware of the mental health costs of further raising income. It is crucial to rationally weigh the costs and benefits between income and mental health in the high-income stage. Second, according to the heterogeneity results of this paper, more attention should be paid to the vulnerable subgroups in terms of mental health in clinical practice. For example, men and older workers are generally more depressed than women, meaning that they take on more work pressures and their mental health problems should receive more attention. In addition, depression problems before the turning point are mainly reflected in individuals with lower educational levels, but the mental health risks of people with higher education in the high-income stage should be emphasized. Furthermore, mental health problems in those with lower overall health levels and socioeconomic status and ethnic minorities are more prominent. Therefore, their depressive disorders need to be focused on in clinical practice.This paper has the following shortcomings. First, this study uses a cross-sectional data, rather than panel data. Although the instrument variable method is used to solve the endogeneity problem, the panel data can further control individual fixed effects and so the omitted variable bias can be better solved. The reason why this study does not use longitudinal data is that the existing panel datasets does not include the necessary explained or instrument variables used in this paper. Therefore, we look forward to a further study of the relationship between income and mental health based on better panel data in the future. Second, this paper proves the nonlinear relationship between income and mental health but fails to further examine the underlying mechanisms of the U-shaped relationship. We have proposed several possible mechanisms, which could hardly be tested due to the lack of relevant variables in the data. Third, scales like PHQ-9 are better indicators to measure the degree of depression and contain more comprehensive information than self-rated depression levels. However, this is not available in the CGSS dataset, which is also a shortcoming of this study. It would be meaningful to collect specific data for this topic to further explore the underlying mechanisms of the nonlinear relationship between income and mental health.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Institutional Review Board, Renmin University of China. The patients/participants provided their written informed consent to participate in this study.CL contributed to the conception and design of the study, performed the statistical analysis, and wrote the first draft of the manuscript. GN, LW, and FC generated the tables and figures based on CL’s analysis. GN, LW, and FC worked on revisions of the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the Humanities and Social Science Research Project of the Ministry of Education of China (grant number 19YJC790055), the Project of Natural Science Foundation of China (grant number 71973081), the Project of Natural Science Foundation of Shandong Province, China (grant number ZR2020QG038), the Project of Social Science Foundation of Shandong Province, China (grant number 19DJJJ08), and the Project of Teaching Reform of Shandong University (grant number Y2022007).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. 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