Mental health assessment method and system for urinary patient

Abstract

The invention discloses a urinary patient psychological health assessment method and system, and relates to the technical field of urinary patient psychological health assessment, and the method comprises the steps: obtaining multi-dimensional health data, and carrying out the preprocessing; constructing a game model, simulating interactive behaviors of a patient, a doctor and a nurse, and solving an optimal strategy of the game model; and evaluating the mental health state of the patient and generating an intervention suggestion in combination with a game model solving result. According to the method, a high-quality basis is provided for subsequent model construction and decision making, the accuracy and objectivity of subsequent analysis and evaluation are ensured, benefit conflicts in the medical treatment process are effectively relieved, it is ensured that patients obtain personalized evidence-based intervention measures, the clinical medical treatment efficiency is improved, and the clinical medical treatment cost is reduced. The risk of worsening psychological problems of the patient is also reduced, and the overall health level of the patient is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of psychological health assessment for urology patients, and in particular to a method and system for psychological health assessment for urology patients. Background Art

[0002] In recent years, research on mental health assessment in the field of medical and health care has gradually received attention, especially the assessment of the mental health status of patients with chronic diseases. Due to the dual burden of physical and psychological problems, patients with urinary system diseases have increasingly prominent mental health problems. The medical community generally adopts multidimensional data collection methods, such as self-assessment questionnaires and physiological data monitoring, to comprehensively assess patients' mental health status. With the development of big data and artificial intelligence technology, related research has gradually shifted to multi-field integration and dynamic monitoring. The acquisition of multidimensional health data is not limited to self-reports, but also includes physiological indicators such as heart rate variability (HRV) and sleep quality scores. Through these data, a more objective mental health assessment system can be formed. At the same time, the introduction of game theory provides a new perspective for the interactive behavior between patients, doctors and caregivers, which improves the personalization and effectiveness of therapeutic interventions.

[0003] Although the current mental health assessment methods have made some progress in multidimensional data collection, there are still many shortcomings. Traditional assessment methods are often limited to a single data source and it is difficult to fully reflect the patient's mental health status. Psychological questionnaires that rely solely on self-reports are often affected by the patient's subjective factors and easily lead to biased assessment results. Most of the existing assessment tools are static and lack real-time monitoring and feedback on the dynamic changes of the patient's mental state. They cannot adjust the intervention strategy in time. In practical applications, they often cannot accurately simulate complex medical scenarios. The existing game model lacks an effective dynamic adjustment mechanism and cannot adjust the strategy according to the patient's real-time feedback data, resulting in low treatment effects. Such models usually ignore the individual differences of patients and cannot provide personalized health assessments, thus affecting the actual effect of intervention recommendations. For the mental health assessment of urinary patients, the current technology is insufficient in the comprehensive assessment of physiological indicators. Related studies often separate physiological and mental health and fail to establish an effective multidimensional health assessment system. This division leads to a one-sided understanding of the patient's health status and cannot achieve precise intervention. Therefore, a new method is urgently needed to comprehensively integrate multidimensional health data and build a dynamic game model to more accurately assess the patient's mental health status and generate personalized intervention recommendations to achieve the coordinated improvement of the patient's psychological and physiological health. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: the existing mental health assessment technology has a single data source, ignores the dynamic integration of physiological and mental health, lacks personalized intervention suggestions, and how to use a game model to comprehensively evaluate the patient's mental state to achieve personalized intervention.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a method for evaluating the psychological health of urological patients, comprising obtaining multidimensional health data and performing preprocessing; constructing a game model to simulate the interactive behavior of patients, doctors and caregivers, and solving the optimal strategy of the game model; evaluating the patient's mental health status and generating intervention suggestions in combination with the solution results of the game model; the construction of the game model includes describing the interest relationship between patients, doctors and caregivers through the utility function of the game model, quantifying the psychological pressure through the standard deviation of the patient's mood fluctuation score, constructing a psychological pressure function, normalizing the original score of the psychological questionnaire, constructing a mental health score function, combining the patient's heart rate variability and sleep quality score, comprehensively evaluating the physiological health status, and constructing a physiological health score function.

[0007] As a preferred embodiment of the method for assessing the psychological health of urological patients described in the present invention, the multidimensional health data includes the patient's psychological health data, the patient's physiological health data, the doctor's intervention data and the nursing staff's support data; the patient's psychological health data includes the psychological questionnaire score and the mood fluctuation record data; the patient's physiological health data includes the heart rate variability and the sleep quality score; the doctor's intervention data includes the intervention frequency and the intervention intensity; the nursing staff's support data includes the support duration and the support intensity.

[0008] As a preferred embodiment of the method for evaluating the psychological health of urinary patients described in the present invention, the utility function of the game model is expressed as: ; in, is the utility function, Represent patients, doctors and nurses, respectively. index variable for patients, is the total number of patients, For the The mental health scores of the patients For the The patient's physical health score, For the The psychological stress score of each patient , are the weight parameters of mental health score and physical health score in the utility function, is the weight parameter of the pressure factor, , are the resource consumption weight parameters of the doctor intervention frequency and the nursing staff support strength in the utility function, is the frequency of physician intervention, Support for nursing staff.

[0009] As a preferred embodiment of the method for evaluating the psychological health of urinary patients of the present invention, the psychological stress function is expressed as: ; in, For the The psychological stress score of each patient For the The standard deviation of the mood swing scores of each patient was is the minimum value of the mood swing score, The maximum value for the mood swing score; The mental health score function is expressed as: ; in, For the The mental health scores of the patients For the The original mental health scores of the patients were is the minimum value of the original mental health scores of all patients. It is the maximum value among all patients’ raw scores of mental health; The physiological health score function is expressed as: ; in, For the The physical health score of each patient, For the Heart rate variability of each patient, For the Sleep quality scores of each patient.

[0010] As a preferred embodiment of the method for evaluating the psychological health of urinary patients described in the present invention, the optimal strategy for solving the game model includes: based on the utility function of the game model , the Nash equilibrium method is used to solve the optimal strategy combination of patients, doctors and nurses; by optimizing the patient's willingness to accept intervention and the intervention strategies of doctors and nurses, the strategy combination that maximizes utility is obtained, which is expressed as: ; in, represents the set of all strategies for the patient, represents the set of all doctors’ strategies, represents the set of all nursing staff strategies, , , Respectively represent the specific selection values ​​of patients, doctors and nurses in the strategy set, represents the utility value under the three-party strategy, represents the utility value under the optimal strategy combination, , , are the optimal strategies for patients, doctors and caregivers, respectively. ={0,1}, indicating whether the patient accepted the intervention, =[0,1], indicating the frequency of doctor’s intervention, =[0,1], indicating the support intensity of nursing staff; through the Nash equilibrium solution, doctors and nursing staff dynamically adjust the intervention frequency and support intensity according to the patient's mental health status and physiological feedback, traverse all strategy combinations, and find the optimal strategy combination when the value of the utility function is maximized.

[0011] As a preferred embodiment of the method for evaluating the mental health of urology patients of the present invention, the evaluation of the mental health status of the patient includes calculating the probability score of the mental health status of the patient based on the solution of the game model and the health data of the patient, which is expressed as: ; in, Indicates The mental health probability score of each patient is For the The mental health scores of the patients For the The patient's physical health score, is the bias parameter of the game model, Score your mental health The regression coefficient of Score your physical health The regression coefficient of For the Patient psychological stress score The weight parameter of .

[0012] As a preferred embodiment of the method for evaluating the mental health of urinary patients described in the present invention, the generating of intervention suggestions includes: When the probability score is less than the first threshold, it indicates that the patient's mental health is poor and requires emergency intervention. The doctor is responsible for developing a personalized psychological intervention plan, and the nurse is responsible for implementing the psychological intervention plan. Through interactive care, the nurse promptly transmits the patient's emotional and psychological change information to the doctor and optimizes the patient's hospitalization environment. The two jointly monitor the patient's psychological and physiological data in real time and coordinate the adjustment of the intervention plan. When the mental health status probability score is When the score is greater than or equal to the first threshold and less than or equal to the second threshold, it indicates that the patient's mental health is moderate and requires focused observation and appropriate intervention. Doctors conduct regular psychological assessments and guide patients to use emotion management tools. Nurses assist doctors in collecting patient feedback and recording data by observing patients' behavior and emotional changes on a daily basis. Nurses are responsible for organizing patients to participate in support group activities, creating an atmosphere conducive to psychological recovery and enhancing patients' social support networks. Doctors optimize treatment plans based on nursing reports. Through data monitoring meetings held every three days, doctors and nursing staff jointly evaluate the intervention effect and confirm the stable improvement of patients' mental states. When the mental health status probability score is When it is greater than the second threshold, it means that the patient's mental health is in good condition and only requires routine follow-up and positive guidance. The doctor is responsible for popularizing mental health knowledge for the patient and giving the patient positive feedback on the recovery progress. The nursing staff is responsible for daily care, further consolidating the mental health status through communication with the patient, assisting the patient in developing appropriate exercise or hobby plans, and observing the patient's implementation. The doctor and nursing staff collaborate regularly to review the patient's psychological and physiological data in follow-up meetings to determine the long-term maintenance of the health status, and dynamically adjust the follow-up frequency based on the nursing staff's observations to avoid a rebound in the mental health status.

[0013] Another object of the present invention is to provide a urological patient psychological health assessment system, which can describe the interest relationship between patients, doctors and caregivers through the utility function of the game model, solve the optimal strategy of the game model, and solve the problem of lack of dynamic interaction and accurate assessment in the current traditional medical model technology.

[0014] As a preferred solution of the urinary patient psychological health assessment system described in the present invention, it includes: a preprocessing module, an optimal strategy solving module, and an intervention suggestion generating module.

[0015] The preprocessing module is used to obtain multidimensional health data and perform preprocessing; the optimal strategy solution is used to describe the interest relationship between patients, doctors and caregivers through the utility function of the game model, and solve the optimal strategy of the game model; the intervention suggestion generation module is used to evaluate the patient's mental health status and generate intervention suggestions in combination with the game model solution results.

[0016] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a method for evaluating the psychological health of urology patients.

[0017] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for evaluating the psychological health of urology patients.

[0018] Beneficial effects of the present invention: The method for assessing the mental health of urinary patients provided by the present invention obtains multidimensional health data and performs preprocessing, which provides a high-quality foundation for subsequent model construction and decision-making, ensures the accuracy and objectivity of subsequent analysis and evaluation, describes the interest relationship between patients, doctors and caregivers through the utility function of the game model, solves the optimal strategy of the game model, effectively alleviates the conflict of interest in the medical process, ensures that patients obtain personalized, evidence-based intervention measures, and evaluates the patient's mental health status and generates intervention suggestions in combination with the game model solution results, which not only improves the efficiency of clinical medical care, but also reduces the risk of worsening of patients' psychological problems and promotes the improvement of patients' overall health level. The present invention has achieved better results in health data integration and processing, multi-party interest optimization and personalized intervention plan generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0020] Figure 1 This is an overall flow chart of a method for assessing the psychological health of urinary patients provided in Example 1 of the present invention.

[0021] Figure 2 This is an overall module diagram of a urology patient psychological health assessment system provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0023] Example 1, reference Figure 1, as an embodiment of the present invention, provides a method for evaluating the psychological health of urology patients, comprising: S1: Obtain multidimensional health data and perform preprocessing.

[0024] Furthermore, the multidimensional health data includes the patient's mental health data, the patient's physiological health data, the doctor's intervention data and the nursing staff's support data; the patient's mental health data includes psychological questionnaire scores and mood fluctuation record data; the patient's physiological health data includes heart rate variability and sleep quality scores; the doctor's intervention data includes intervention frequency and intervention intensity; the nursing staff's support data includes support duration and support intensity.

[0025] It should be noted that preprocessing includes normalizing all data, mapping them to the interval [0,1], and normalizing the numbers, expressed as: ; in, represents the normalized value, is the original data value, and are the minimum and maximum values ​​of the data respectively.

[0026] It should also be noted that by obtaining multidimensional health data and preprocessing it, it is possible to comprehensively collect patients' mental health data (such as psychological questionnaire scores and mood swing records), physiological health data (such as heart rate variability and sleep quality scores), doctor intervention data (such as intervention frequency and intensity), and nursing staff support data (such as support duration and intensity). By normalizing the various collected data and mapping all data to the range of [0,1], calculation bias due to different data dimensions is avoided, and the integration and comparability of the data are guaranteed, thereby providing a solid and reliable foundation for subsequent analysis, ensuring that the obtained data has a high degree of consistency and availability, and facilitating the accurate assessment of the patient's health status in subsequent steps. Holistic data collection and standardization avoid the phenomenon of information islands, and improve the effect of model analysis by enriching data samples. It not only makes up for the narrow perspective of the traditional medical system due to being limited to a single data source, but also ensures the scientificity and accuracy of subsequent analysis. The normalization of data provides a unified standard for the algorithm model, making subsequent algorithm calculations more efficient, thereby saving time and resources, effectively promoting the integration of multi-party medical information, and improving the accuracy and real-time nature of medical decision-making.

[0027] S2: Construct a game model to simulate the interactive behaviors of patients, doctors, and caregivers, and solve the optimal strategy of the game model.

[0028] Furthermore, constructing a game model involves describing the interest relationship among patients, doctors, and caregivers through a utility function and determining the best combination of interaction strategies; the utility function of the game model is expressed as: ; in, is the utility function used to measure the patient P ,doctor D and nursing staff N The comprehensive utility value of the intervention is combined with the patient's health status and intervention resource investment. Respectively represent patients, doctors and nurses, which are the three subjects participating in the game model. Patient index variable, used to indicate the patient number. is the total number of patients, indicating the number of patients in the game model, For the The mental health scores of the patients For the The patient's physical health score, For the The psychological stress score of each patient , are the weight parameters of mental health score and physical health score in the utility function, is the weight parameter of the stress factor, which is used to adjust the negative impact of psychological stress on utility value. , are the resource consumption weight parameters of the doctor intervention frequency and the nursing staff support strength in the utility function, is the doctor's intervention frequency, indicating the number of times the doctor intervenes in the patient. It is the support level of the nursing staff, indicating the time investment of the nursing staff for the patients.

[0029] It should also be noted that the construction of the game model also includes quantifying psychological stress through the standard deviation of the patient's mood swing score and constructing a psychological stress function, which is expressed as: ; in, For the The psychological stress score of each patient is used to quantify the degree of psychological stress, ranging from [0,1]. For the The standard deviation of the mood swing scores of each patient is a measure of the dispersion of the mood swing scores. is the minimum value of the mood swing score, is the maximum value of the emotional fluctuation score; the original score of the psychological questionnaire is normalized to construct the mental health score function, which is expressed as: ; in, For the The mental health scores of the patients For the The original mental health score of each patient is derived from the score of the mental health questionnaire or related assessment tool. is the minimum value of the original mental health scores of all patients. is the maximum value of the original mental health scores of all patients; combined with the heart rate variability and sleep quality scores of patients, the physiological health status is comprehensively evaluated, and the physiological health score function is constructed, which is expressed as: ; in, For the The physiological health score of each patient comprehensively reflects the patient's physiological state, ranging from [0,1]. For the Heart rate variability of each patient, For the Sleep quality scores of each patient.

[0030] It should be noted that the optimal strategy for solving the game model includes: the utility function based on the game model , the Nash equilibrium method is used to solve the optimal strategy combination of patients, doctors and nurses; by optimizing the patient's willingness to accept intervention and the intervention strategies of doctors and nurses, the strategy combination that maximizes utility is obtained, which is expressed as: ; in, represents the set of all strategies for the patient, represents the set of all doctors’ strategies, represents the set of all nursing staff strategies, , , Respectively represent the specific selection values ​​of patients, doctors and nurses in the strategy set, represents the utility value under the three-party strategy, represents the utility value under the optimal strategy combination, , , are the optimal strategies for patients, doctors and caregivers, respectively. ={0,1}, indicating whether the patient accepted the intervention, =[0,1], indicating the frequency of doctor’s intervention, =[0,1], indicating the support intensity of nursing staff; through the Nash equilibrium solution, doctors and nursing staff dynamically adjust the intervention frequency and support intensity according to the patient's mental health status and physiological feedback, traverse all strategy combinations, and find the optimal strategy combination when the value of the utility function reaches the maximum. Patients hope to maximize their mental health. and physical health , while minimizing psychological stress , doctors and caregivers want to improve patients’ health while minimizing the frequency of interventions and support hours .

[0031] It should also be noted that a game model was constructed to describe the interest relationship between patients, doctors and nurses through utility functions, simulate their respective interactive behaviors and solve the optimal strategy of the game model. The dynamic interaction and decision-making of participants in the medical process, with the help of the Nash equilibrium method, can effectively find the best strategy combination to achieve a balance of interests among all parties in a specific situation. Based on the game model, the health interests of patients, the intervention costs of doctors and nurses, etc. can be reasonably optimized, so that the interests of the three parties can be coordinated with each other to maximize the efficiency of resource utilization, clarify the role positioning of patients, doctors and nurses, help participants understand the impact of their respective decisions and how to achieve a new medical service model through cooperation. The construction of this dynamic game model solves the problems of multi-party interest conflicts and information asymmetry in the traditional medical process, so that medical intervention can be more scientific, reasonable and flexible to adapt to the actual needs of patients. Through the use of the model, the allocation of resources in the medical process is more reasonable, the cost of medical intervention is reduced, the treatment compliance of patients is improved, and the quality of patient health management is promoted. The innovative interactive model effectively promotes the local application of game theory in the industry and provides ideas and guidance for future medical decision-making.

[0032] S3: Combine the game model solution results to evaluate the patient's mental health status and generate intervention recommendations.

[0033] Furthermore, evaluating the patient's mental health status includes calculating the probability score of the patient's mental health status based on the solution of the game model and the patient's health data, which is expressed as: ; in, Indicates The mental health probability score of each patient is For the The mental health score of each patient ranges from [0,1], For the The physiological health score of each patient is a combination of heart rate variability and sleep quality score, ranging from [0,1]. is the bias parameter of the game model, Score your mental health The regression coefficient of , which represents the initial score when all remaining eigenvalues ​​are zero, Score your physical health The regression coefficient of For the Patient psychological stress score The weight parameter of .

[0034] It should be noted that generating intervention recommendations includes the probability score of mental health status When it is less than the first threshold, it indicates that the patient's mental health is poor and requires emergency intervention. The doctor is responsible for formulating a personalized psychological intervention plan, and the nursing staff is responsible for implementing the psychological intervention plan. Through interactive care, the doctor can promptly convey the patient's emotional and psychological change information to the doctor and optimize the patient's hospitalization environment. The two jointly monitor the patient's psychological and physiological data in real time and coordinate and adjust the intervention plan. A preferred solution for the first threshold includes setting the first threshold to 0.4.

[0035] When the probability score of mental health status When it is greater than or equal to the first threshold and less than or equal to the second threshold, it indicates that the patient's mental health state is moderate and requires key observation and moderate intervention. Doctors conduct regular psychological assessments and guide patients to use emotion management tools. Nurses assist doctors in collecting patient feedback and recording data by observing patients' behavior and emotional changes on a daily basis. Nurses are responsible for organizing patients to participate in support group activities, creating an atmosphere conducive to psychological recovery and enhancing patients' social support networks. Doctors optimize treatment plans based on nursing reports. Through data monitoring meetings held every three days, doctors and nursing staff jointly evaluate the intervention effects and confirm the stable improvement of patients' mental states. A preferred solution for the first and second thresholds includes setting the first threshold to 0.4 and the second threshold to 0.6.

[0036] When the probability score of mental health status When it is greater than the second threshold, it means that the patient's mental health is in good condition and only requires routine follow-up and positive guidance. The doctor is responsible for popularizing mental health knowledge for the patient and giving the patient positive feedback on the recovery progress. The nursing staff assumes the daily care responsibilities, further consolidates the mental health status through communication with the patient, assists the patient in developing appropriate exercise or hobby plans, and observes the patient's execution. The doctor and nursing staff collaborate regularly to review the patient's psychological and physiological data in follow-up meetings to determine the long-term maintenance of the health status, and dynamically adjust the follow-up frequency based on the nursing staff's observations to avoid a rebound in the mental health status. A preferred solution for the second threshold includes setting the second threshold to 0.6.

[0037] It should also be noted that the results of the game model are combined to evaluate the patient's mental health status, and personalized intervention suggestions are generated based on the evaluation results. By calculating the probability score of the patient's mental health, it is possible to flexibly identify the patient's needs under different mental health conditions and intelligently formulate corresponding intervention plans, ensuring data-driven personalized medicine. It can accurately and promptly respond to the patient's health needs. For patients with poor mental health, an emergency intervention mechanism will be triggered; for patients with good mental health, follow-up will be maintained and positive guidance will be given, so as to formulate intervention measures at different levels, realize the quantification of the patient's mental health assessment, make the intervention suggestions more practical and targeted, and solve the shortcomings of the medical system in the past when facing patients' mental health problems, which are often generalized, lacking in targeting and timeliness, thereby promoting the improvement of treatment efficiency. This new intervention mechanism can not only improve the patient's recovery speed and satisfaction, but also strengthen the real-time monitoring of the patient's dynamic state by doctors and nurses, further improve the patient's overall health management, not only optimize the intervention process, but also provide patients with a coherent and systematic mental health support method, paving the way for the innovative development of mental health management.

[0038] Example 2 is an embodiment of the present invention, which provides a method for evaluating the psychological health of urinary patients. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0039] First, a total of 50 patients were included in the experiment, and the data types included mental health data, physiological health data, doctor intervention data, and nursing staff support data. For the patient mental health data, including psychological questionnaire scores and mood fluctuation record data, the original data were mapped to the [0,1] interval through the normalization method; the mood fluctuation record was used to calculate the psychological stress score through its standard deviation to reflect the amplitude of mood fluctuations. The physiological health data included heart rate variability and sleep quality scores, and their means were taken to construct the physiological health score. The doctor's intervention frequency (number of interventions per day) and the nursing staff's support intensity (support duration, in hours) were converted to [ 0,1] interval. For example, the frequency range of doctor intervention for a patient is 0.5 times, and the range of support intensity is 0.8 hours. The normalized result is calculated according to the formula. After all the data are input, a game model is constructed. The patient's psychological and physiological health scores are used as the main target variables to optimize the combination of intervention strategies of doctors and nurses. Finally, the Nash equilibrium strategy is solved. According to the results of the game model, the patient's mental health status is further evaluated, and intervention suggestions are generated. If the patient's mental health status probability score is lower than 0.4, it is considered to require emergency intervention. By optimizing the resource investment of doctors and nurses, the improvement of the patient's mental state is ensured. Refer to Table 1, which is a record of experimental data.

[0040] Table 1 Experimental data record table Parameter name Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Mental health score 0.85 0.72 0.63 0.78 0.9 0.68 Physical health score 0.8 0.65 0.7 0.75 0.88 0.6 Psychological stress (normalized) 0.2 0.35 0.4 0.25 0.15 0.3 Physician intervention frequency (normalized) 0.6 0.5 0.45 0.55 0.7 0.4 Nursing support intensity (normalized) 0.5 0.4 0.6 0.45 0.65 0.35 Mental health status probability score 0.68 0.6 0.55 0.62 0.72 0.58 The present invention constructs a game model to optimize the resource allocation strategy among patients, doctors and nursing staff, and effectively improves the mental health of patients. Taking patient 1 as an example, his mental health score is 0.85, his physical health score is 0.80, and his psychological stress score is only 0.20. Under the condition of low resource input (doctor intervention frequency 0.60, nursing support intensity 0.50), his mental health probability score is 0.68, indicating that his mental state is significantly better than that of most patients. In contrast, patient 3 has lower mental health scores and physical health scores (0.63 and 0.70, respectively), and a higher psychological stress score (0.40). In addition, resource allocation is limited (doctor intervention frequency 0.45, nursing support intensity 0.60), and the probability score of mental health status is only 0.55, indicating that the patient needs to increase intervention resources to improve his mental health status. The game model is used to optimize the interactive behavior of patients, doctors and nurses, which effectively improves the probability score of the patient's mental health status. Under limited intervention resources, the doctor's intervention frequency and nursing support intensity are reasonably adjusted through normalization and game model calculation to maximize resource utility. The existing technology usually finds it difficult to dynamically adjust intervention resources, while the present invention dynamically optimizes the three-party strategy through normalized data and game model calculation to improve patients' mental health.

[0041] Example 3, reference Figure 2 , as an embodiment of the present invention, provides a urology patient psychological health assessment system, including a preprocessing module, an optimal strategy solving module, and an intervention suggestion generating module.

[0042] The preprocessing module is used to obtain and preprocess multidimensional health data; the optimal strategy solution is used to describe the interest relationship between patients, doctors and caregivers through the utility function of the game model and solve the optimal strategy of the game model; the intervention recommendation generation module is used to evaluate the patient's mental health status and generate intervention recommendations based on the game model solution results.

[0043] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0044] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0045] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk case (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0046] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logical function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0047] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for assessing the psychological health of urology patients, characterized in that: include: Acquire multidimensional health data and preprocess them; Construct a game model to simulate the interactive behaviors of patients, doctors, and nurses, and solve the optimal strategy of the game model; Combined with the game model solution results, the patient's mental health status is evaluated and intervention recommendations are generated; The construction of the game model includes describing the interest relationship between patients, doctors and nursing staff through the utility function of the game model, quantifying psychological stress through the standard deviation of the patient's mood fluctuation score, constructing a psychological stress function, normalizing the original scores of the psychological questionnaire, constructing a mental health score function, combining the patient's heart rate variability and sleep quality scores, comprehensively evaluating the physiological health status, and constructing a physiological health score function.

2. The method for evaluating the psychological health of urology patients according to claim 1, characterized in that: The multidimensional health data includes the patient's mental health data, the patient's physiological health data, the doctor's intervention data and the nursing staff's support data; The patients’ mental health data included psychological questionnaire scores and mood swing record data; Patients’ physiological health data included heart rate variability and sleep quality scores; Physician intervention data included intervention frequency and intervention intensity; Caregiver support data included duration of support and intensity of support.

3. The method for evaluating the psychological health of urology patients according to claim 2, characterized in that: The utility function of the game model is expressed as: ； in, is the utility function, Represent patients, doctors and nurses, respectively. index variable for patients, is the total number of patients, For the The mental health scores of the patients For the The patient's physical health score, For the The psychological stress score of each patient , are the weight parameters of mental health score and physical health score in the utility function, is the weight parameter of the pressure factor, , are the resource consumption weight parameters of the doctor intervention frequency and the nursing staff support strength in the utility function, is the frequency of physician intervention, Support for nursing staff.

4. The method for evaluating the psychological health of urology patients according to claim 3, characterized in that: The psychological stress function is expressed as: ； in, For the The psychological stress score of each patient For the The standard deviation of the mood swing scores of each patient was is the minimum value of the mood swing score, The maximum value for the mood swing score; The mental health score function is expressed as: ； in, For the The mental health scores of the patients For the The original mental health scores of the patients were is the minimum value of the original mental health scores of all patients. It is the maximum value among all patients’ raw scores of mental health; The physiological health score function is expressed as: ； in, For the The patient's physical health score, For the Heart rate variability of each patient, For the Sleep quality scores of each patient.

5. The method for evaluating the psychological health of urology patients according to claim 4, characterized in that: The optimal strategy for solving the game model includes: based on the utility function of the game model , using the Nash equilibrium method to solve the optimal strategy combination of patients, doctors and nursing staff; By optimizing the patient's willingness to accept intervention and the intervention strategies of doctors and nurses, a strategy combination that maximizes utility is obtained, which is expressed as: ； in, represents the set of all strategies for the patient, represents the set of all doctors’ strategies, represents the set of all nursing staff strategies, , , Respectively represent the specific selection values ​​of patients, doctors and nurses in the strategy set, represents the utility value under the three-party strategy, represents the utility value under the optimal strategy combination, , , are the optimal strategies for patients, doctors and caregivers, respectively. ={0,1}, indicating whether the patient accepted the intervention, =[0,1], indicating the frequency of doctor’s intervention, =[0,1], indicating the support level of nursing staff; Through the Nash equilibrium solution, doctors and caregivers dynamically adjust the frequency of intervention and the intensity of support according to the patient's mental health status and physiological feedback, traverse all strategy combinations, and find the optimal strategy combination when the value of the utility function is maximized.

6. The method for evaluating the psychological health of urology patients according to claim 5, characterized in that: The evaluating of the patient's mental health state includes calculating a probability score of the patient's mental health state based on a solution of the game model and the patient's health data, which is expressed as: ； in, Indicates The mental health probability score of each patient is For the The mental health scores of the patients For the The patient's physical health score, is the bias parameter of the game model, Score your mental health The regression coefficient of Score your physical health The regression coefficient of For the Patient psychological stress score The weight parameter of .

7. The method for evaluating the psychological health of urology patients according to claim 6, characterized in that: The generated intervention recommendation includes the mental health status probability score When it is less than the first threshold, it means that the patient's mental health is poor and requires emergency intervention. The doctor is responsible for formulating a personalized psychological intervention plan, and the nursing staff is responsible for implementing the psychological intervention plan. Through interactive care, the nurse promptly transmits the patient's emotional and psychological change information to the doctor and optimizes the patient's hospitalization environment. The two jointly monitor the patient's psychological and physiological data in real time and coordinate to adjust the intervention plan. When the probability score of mental health status When the value is greater than or equal to the first threshold and less than or equal to the second threshold, it indicates that the patient's mental health is moderate and requires focused observation and appropriate intervention. Doctors conduct regular psychological assessments and guide patients to use emotion management tools. Nurses assist doctors in collecting patient feedback and recording data by observing patients' behavior and emotional changes on a daily basis. Nurses are responsible for organizing patients to participate in support group activities, creating an atmosphere conducive to psychological recovery and strengthening patients' social support networks. Doctors optimize treatment plans based on nursing reports. Through data monitoring meetings held every three days, doctors and nursing staff jointly evaluate the intervention effect and confirm the stable improvement of patients' mental states. When the probability score of mental health status When it is greater than the second threshold, it means that the patient's mental health is in good condition and only requires routine follow-up and positive guidance. The doctor is responsible for popularizing mental health knowledge for the patient and giving the patient positive feedback on the recovery progress. The nursing staff is responsible for daily care, further consolidating the mental health status through communication with the patient, assisting the patient in developing appropriate exercise or hobby plans, and observing the patient's implementation. The doctor and nursing staff collaborate regularly to review the patient's psychological and physiological data in follow-up meetings to determine the long-term maintenance of the health status, and dynamically adjust the follow-up frequency based on the nursing staff's observations to avoid a rebound in the mental health status.

8. A system using the method for evaluating the psychological health of urology patients as claimed in any one of claims 1 to 7, characterized in that: It includes pre-processing module, optimal strategy solving module, and intervention suggestion generation module; The preprocessing module is used to obtain multi-dimensional health data and perform preprocessing; The optimal strategy solution is used to describe the interest relationship between patients, doctors and nursing staff through the utility function of the game model, and solve the optimal strategy of the game model; The intervention suggestion generation module is used to evaluate the patient's mental health status and generate intervention suggestions in combination with the game model solution results.

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