Mental health intervention effect evaluation method and system

Abstract

The invention relates to the technical field of mental health management, in particular to a mental health intervention effect assessment method and system. Collecting demographic basic information, psychological health problem types, psychological state improvement evaluation values before and after intervention and intervention feature information of each intervention object; for any intervention object, screening a historical intervention object matched with the intervention object from a historical intervention database as a reference object according to the demographic basic information, the psychological health problem type and the intervention feature information of the intervention object; calculating a deviation difference value between the psychological state improvement evaluation value of the intervention object and the psychological state improvement evaluation value of the reference object, comparing and judging the deviation difference value based on a preset deviation threshold value, and judging whether the intervention object is a suspected effect abnormal object or not; and for any suspected effect abnormal object, obtaining intervention behavior data during the intervention period.

Description

Technical Field

[0001] The present invention relates to the technical field of mental health management, and particularly to a method for evaluating the effect of mental health intervention. Background Art

[0002] With the acceleration of the pace of life and the increase in competitive pressure, the incidence rate of various mental health problems shows an upward trend, which has a significant impact on the quality of life of individuals, work and learning efficiency, and social functions. To cope with mental health problems, various mental health intervention measures have emerged, including psychological counseling, psychotherapy, psychological counseling courses, and related rehabilitation training. However, different individuals have significant differences in their responses to the same intervention measure, and due to the diversity of intervention methods and the complexity of intervention objects, how to accurately evaluate the effect of mental health intervention has become a key and challenging problem.

[0003] The existing methods for evaluating the effect of mental health intervention usually take the improvement of mental state as a single index, ignoring the influence of individual differences and intervention characteristics on the effect. For example, the same intervention measure may have completely different effects on different occupational groups, resulting in a deviation between the evaluation result and the actual effect, and it is difficult to guide the formulation of personalized intervention strategies. At the same time, the existing methods only focus on the intervention results and do not systematically collect the behavioral data during the intervention, resulting in the attribution of abnormal effects remaining at the hypothesis level. For example, the score of a depression patient does not improve after intervention, which may be due to poor medication compliance or insufficient family support, but the existing technology cannot verify it through data, making the improvement measures lack pertinence and difficult to form a closed-loop optimization. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a method for evaluating the effect of mental health intervention, which can customize intervention strategies for different intervention objects, enhance the effectiveness of intervention, and help individuals better cope with mental health problems.

[0005] In a first aspect, the present invention provides a method for evaluating the effect of mental health intervention, which determines a number of intervention objects to be evaluated for mental health, and collects the demographic basic information, types of mental health problems, evaluation values of mental state improvement before and after intervention, and intervention characteristic information of each of the intervention objects; For any one of the intervention objects, according to the demographic basic information, the types of mental health problems, and the intervention characteristic information thereof, historical intervention objects matching the same are screened in a historical intervention database as reference objects; Calculate the deviation difference between the evaluation value of the mental state improvement of the intervention object and the evaluation value of the mental state improvement of the reference object, and compare and determine the deviation difference based on a preset deviation threshold to judge whether the intervention object is a suspected object with abnormal effect; For any of the suspected objects with abnormal effects, obtain the intervention behavior data during the intervention period, and comprehensively evaluate the differences between it and the intervention behavior data corresponding to the reference object to obtain a comprehensive intervention effect score. Then, based on a preset comprehensive threshold, determine whether there is a situation of poor intervention effect for the suspected object with abnormal effects.

[0006] Further, the intervention behavior data includes the type of intervention means, intervention execution frequency, intervention execution cycle, intervention object participation data, interaction quality data, physiological index time series data, psychological state time series data, and external environmental factor data.

[0007] Further, the demographic basic information includes at least age, gender, occupation, and education level.

[0008] Further, the intervention characteristic information includes at least the intervention implementation location and duration.

[0009] Further, the types of mental health problems are collected through self-assessment questionnaires in which the intervention object fills out the Symptom Checklist, Self-Rating Depression Scale, and Self-Rating Anxiety Scale.

[0010] Further, the method for constructing the historical intervention database includes: Collect historical intervention cases; Standardize the collected historical intervention cases; Clean the standardized data to remove duplicate, incomplete, and incorrect data; Classify and store the data in the historical intervention database according to different types and characteristics of the data; Establish a data indexing and retrieval mechanism in the historical intervention database; Take encryption, backup, and access control measures for the database to prevent data leakage and illegal access.

[0011] Further, the influencing factors for setting the preset deviation threshold include the error range of the evaluation tool, individual differences of the intervention object, influence of intervention characteristics, analysis results of historical data, and requirements and goals of practical applications.

[0012] On the other hand, the present application also provides a mental health intervention effect evaluation system, which includes: A data collection module, which determines a number of intervention objects to be evaluated for mental health and collects the demographic basic information, types of mental health problems, evaluation values of the improvement of the mental state before and after the intervention, and intervention characteristic information of each intervention object. A reference object screening module, for any one of the intervention objects, screens the historical intervention objects that match it in the historical intervention database as reference objects according to the demographic basic information, the type of mental health problem, and the intervention characteristic information of the intervention object; A preliminary abnormal determination module calculates the deviation difference between the mental state improvement evaluation value of the intervention object and the mental state improvement evaluation value of the reference object, and makes a comparison determination on the deviation difference based on a preset deviation threshold to determine whether the intervention object is a suspected abnormal effect object; A depth evaluation module, for any one of the suspected abnormal effect objects, obtains the intervention behavior data during the intervention period, and conducts a comprehensive difference evaluation on it and the intervention behavior data corresponding to the reference object to obtain a comprehensive intervention effect score, and determines whether there is a poor intervention effect for the suspected abnormal effect object according to a preset comprehensive threshold.

[0013] In a third aspect, the present application provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor. The transceiver, the memory, and the processor are connected through the bus. When the computer program is executed by the processor, the steps in any one of the above methods are implemented.

[0014] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in any one of the above methods are implemented.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: collecting the demographic basic information, the type of mental health problem, the mental state improvement evaluation value before and after the intervention, and the intervention characteristic information of the intervention object; these information cover multiple aspects that may affect the intervention effect, breaking the limitation of traditional single-index evaluation; compared with the traditional evaluation method, the multi-source data collection method fully considers the individual differences such as different occupations and ages and the influence of intervention characteristics on the effect, effectively reducing the deviation between the evaluation result and the actual effect; by collecting multi-dimensional information such as occupation, the intervention effect of different groups is evaluated more realistically; according to the characteristics of each intervention object, screening the matching historical intervention objects in the historical intervention database as reference objects; it can find historical cases with similar backgrounds for each intervention object's unique situation, making the evaluation process more targeted, thereby significantly improving the accuracy of the evaluation; For suspected objects with abnormal effects, collect behavioral data during the intervention period and compare it with reference objects; this breaks through the drawback of traditional methods that only focus on the intervention results and provides a data basis for analyzing the reasons for abnormal effects; when the score of a depression patient does not improve after the intervention, by analyzing the behavioral data during the intervention period, it can be verified whether it is due to poor drug compliance or insufficient family support, etc., making the subsequent improvement measures more targeted; based on comprehensive evaluation results, the mental health management team can develop personalized intervention strategies for different intervention objects and continuously optimize the intervention plan; by continuously collecting and analyzing data, a closed-loop management from evaluation to intervention and then to feedback optimization is achieved, continuously improving the intervention effect; During the evaluation process of this evaluation method, individual differences and various factors during the intervention process are fully considered, providing rich and accurate information for mental health intervention; based on this information, mental health professionals can customize intervention strategies for different intervention objects, enhance the effectiveness of the intervention, help individuals better cope with mental health problems, improve the quality of life, and assist them in better functioning in work, study, and social life. Brief Description of the Drawings

[0016] Figure 1 is the flowchart of the present invention; Figure 2 is the flowchart of the construction method of the historical intervention database; Figure 3 is the structural diagram of a mental health intervention effect evaluation system. Detailed Implementation Modes

[0017] In the description of the present application, those skilled in the art should know that the present application can be implemented as a method, a device, an electronic device, and a computer-readable storage medium. Therefore, the present application can be specifically implemented in the following forms: completely hardware, completely software (including firmware, resident software, microcode, etc.), and a combination of hardware and software. In addition, in some embodiments, the present application can also be implemented in the form of a computer program product in one or more computer-readable storage media, which contains computer program code.

[0018] The above computer-readable storage medium may adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, compact disc read-only memories, optical storage devices, magnetic storage devices, or any combination of the above. In the present application, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in conjunction with an instruction execution system, device, or component.

[0019] In the technical solution of the present application, the acquisition, storage, use, processing, etc. of data all comply with the relevant provisions of national laws.

[0020] The present application describes the provided method, device, and electronic device through flowcharts and / or block diagrams.

[0021] It should be understood that each block of the flowchart and / or block diagram, as well as the combination of blocks in the flowchart and / or block diagram, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, thereby producing a machine. These computer-readable program instructions are executed by a computer or other programmable data processing devices, resulting in a device that implements the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0022] These computer-readable program instructions can also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product that includes the instructions for implementing the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0023] The computer-readable program instructions can also be loaded onto a computer, other programmable data processing device, or other device, such that a series of operation steps are executed on the computer, other programmable data processing device, or other device, resulting in a computer-implemented process. Thus, the instructions executed on the computer or other programmable data processing device can provide a process for implementing the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0024] The present application will be described below in conjunction with the accompanying drawings in the present application.

[0025] Embodiment 1: As Figures 1 to 2 shown, a method for evaluating the effect of mental health intervention of the present invention specifically includes the following steps: S1. Determine a number of intervention subjects to be evaluated for mental health, and collect the demographic basic information, types of mental health problems, evaluation values of the improvement of mental state before and after the intervention, and intervention characteristic information of each of the intervention subjects; the demographic basic information includes at least age, gender, occupation, and education level; the intervention characteristic information includes at least the intervention implementation location and duration; Before conducting the evaluation of the mental health intervention effect, with the help of medical institutions, community mental health service centers, and enterprise employee assistance programs, determine the intervention subjects to be evaluated for mental health; the community mental health service center can identify residents with mental health problems or who have received mental health interventions through community censuses; the enterprise employee assistance program can lock in the employee groups participating in mental health counseling; Collect demographic basic information: Age and gender information: Obtain the age and gender information of the intervention subjects through methods such as identity registration and questionnaires; nowadays, many mental health management systems support the online questionnaire function, and the intervention subjects can fill in the relevant information independently, and the system automatically records it; Occupation information: With the help of big data technology, associate systems such as social security and employment registration to obtain accurate occupation information; taking the mental health assessment carried out by a large enterprise as an example, the job information of employees can be directly obtained through the enterprise human resources management system to accurately determine their occupation categories; Education level: After obtaining the authorization of the individual, access authoritative educational background data by connecting to educational databases such as the China Higher Education Student Information Network; Collect types of mental health problems: Rely on psychiatrists or psychological counselors to conduct professional diagnoses on the intervention subjects; at the same time, let the intervention subjects fill in self-assessment questionnaires such as the Symptom Checklist-90, Self-Rating Depression Scale, and Self-Rating Anxiety Scale. By combining the two, accurately judge the types of mental health problems; enter the professional diagnosis results and self-assessment scale data into the mental health management system, analyze the text descriptions and scale scores, and classify the types of mental health problems; Collect evaluation values of the improvement of mental state before and after the intervention: Before and after the intervention, let the intervention subjects fill in relevant psychological assessment scales, including the Symptom Checklist-90, to quantitatively evaluate the changes in mental state; the system automatically calculates the scale scores and generates an evaluation report of the mental state before and after the intervention; evaluate the mental state before the start and after the end of the intervention respectively to obtain the evaluation values of the improvement of the mental state before and after the intervention; Collect intervention characteristic information: Intervention implementation location: In the intervention record, require the intervention implementer to clearly record whether the intervention is carried out in a medical institution, a community service center, or an online platform. There are differences in the intervention environment, resource support, etc. at different locations; Duration: Record the duration of the intervention, including the duration of each intervention and the total intervention cycle; for offline interventions, the implementer is required to manually enter the intervention duration.

[0026] In this step, through multi-channel cooperation such as medical institutions, community mental health service centers, and enterprise employee assistance programs, it is possible to widely and accurately identify the intervention targets to be evaluated for mental health; not only ensuring the coverage of the evaluation, but also improving the pertinence and effectiveness of the evaluation; the collection of demographic basic information such as age, gender, occupation, and education level provides important background information for the subsequent evaluation of the intervention effect; helps to analyze the response differences of different groups to the intervention measures and provides a basis for the formulation of personalized intervention strategies; through various methods such as online questionnaires, big data technology to link the social security and employment registration systems, and docking educational databases such as the China Higher Education Student Information and Career Counseling Center, the accuracy and integrity of the information are ensured, and the efficiency and accuracy of data processing are improved; relying on the professional diagnosis of psychiatrists or psychologists and combining with the self-assessment questionnaires filled in by the intervention targets, it is possible to accurately judge the types of mental health problems; improving the accuracy of problem identification and laying a solid foundation for the subsequent intervention and evaluation; by asking the intervention targets to fill in relevant psychological assessment scales before and after the intervention, the system calculates the scale scores and generates an evaluation report, which can quantitatively evaluate the changes in the mental state and helps to more accurately judge the intervention effect; clearly recording the intervention characteristic information such as the implementation location and duration of the intervention helps to analyze the impact of different intervention environments and resource supports on the effect; optimizing the intervention strategy and improving the pertinence and effectiveness of the intervention; this step provides a comprehensive and accurate data basis for the evaluation of the mental health intervention effect by comprehensively identifying the intervention targets, systematically collecting demographic basic information, accurately judging the types of mental health problems, quantitatively evaluating the changes in the mental state, and detailedly recording the intervention characteristic information; helps to improve the accuracy and reliability of the evaluation and provides strong support for the formulation and optimization of personalized intervention strategies.

[0027] S2. For any one of the said intervention targets, based on its said demographic basic information, said types of mental health problems, and said intervention characteristic information, screen the historical intervention targets that match them in the historical intervention database as reference targets; Comprehensively organize and analyze the demographic basic information, types of mental health problems, and intervention characteristic information of the currently collected intervention targets; clarify the specific values or categories of each information dimension; Based on the analysis results, formulate the screening criteria for the historical intervention database; for the basic demographic information, set the screening conditions of age within a certain range, the same gender, the same or similar occupational categories, and comparable educational levels; for the types of mental health problems, require a complete match with the records in the historical database; for the intervention characteristic information, the intervention implementation location can be set as the same location or the same region according to the actual situation, and the duration is set within a fluctuating range; Query and screen in the historical intervention database according to the set screening criteria; a large amount of information on past intervention objects is stored in the database, and by retrieving the records that meet the various conditions, the matching historical intervention objects can be found; From the screened historical intervention objects, further determine the final reference objects according to the specific research purposes and requirements; if the number of screened objects is large, a certain number of reference objects can be selected by random sampling or other appropriate methods; if the number is small, all of them can be used as reference objects; The construction method of the historical intervention database includes: Collect historical intervention cases; collect historical intervention cases through various channels, including mental health institutions, hospitals, research institutions, etc.; ensure the diversity and representativeness of the cases to cover different types of intervention objects, intervention methods, and intervention effects; Standardize the collected historical intervention cases to ensure the consistency and comparability of the data; convert the evaluation values of the improvement of mental state obtained by different assessment tools into unified standard scores, and uniformly code the intervention characteristic information in different formats; Clean the standardized data to remove duplicate, incomplete, and incorrect data; at the same time, verify the accuracy and reliability of the data through expert review, cross-validation, etc.; Classify and store the data in the historical intervention database according to different types and characteristics of the data; Establish a data indexing and retrieval mechanism; in order to facilitate the subsequent rapid screening of reference objects, an effective data indexing and retrieval mechanism needs to be established; indexes can be established according to keyword fields such as basic demographic information, types of mental health problems, and intervention characteristic information to support multi-condition combined retrieval; Take encryption, backup, and access control measures for the database to prevent data leakage and illegal access and ensure the security of the database; at the same time, regularly maintain and update the database to keep the data timely and accurate.

[0028] In this step, by comprehensively sorting out and analyzing the demographic basic information, types of mental health problems, and intervention characteristic information of the current intervention object, and formulating specific screening criteria based on this information, it is possible to accurately screen out matching historical intervention objects in the historical intervention database as reference objects; this helps to improve the accuracy and reliability of subsequent intervention effect evaluation; the screened reference objects are highly similar to the current intervention object in key characteristics, making the evaluation results better reflect the actual situation of the current intervention object, thus providing strong support for formulating personalized intervention strategies; it helps to meet the unique needs of different intervention objects; by standardizing historical intervention cases, the consistency and comparability of data are ensured; the differences brought by different evaluation tools and data formats are eliminated, enabling the data in the historical intervention database to more accurately reflect the intervention effect and providing a solid foundation for subsequent screening and evaluation; an effective data indexing and retrieval mechanism is established to support multi-condition combined retrieval, making the process of screening reference objects in the historical intervention database more efficient and convenient; the screening time is greatly shortened, and the efficiency of the evaluation work is improved; encryption, backup, and access control measures are taken for the database to ensure data security and prevent data leakage and illegal access; at the same time, the database is regularly maintained and updated to keep the data timely and accurate; the long-term availability and reliability of the historical intervention database are ensured, providing continuous support for subsequent intervention effect evaluation; this step has beneficial effects in many aspects such as accurately matching reference objects, improving the personalization and pertinence of evaluation, enhancing the comparability and consistency of data, improving screening efficiency and convenience, and ensuring data security and timeliness.

[0029] S3. Calculate the deviation difference between the mental state improvement evaluation value of the intervention object and the mental state improvement evaluation value of the reference object, and compare and determine the deviation difference based on a preset deviation threshold to judge whether the intervention object is a suspected abnormal effect object; For each intervention object, calculate its mental state improvement evaluation value; From the reference objects selected from the historical intervention database, obtain the corresponding mental state improvement evaluation value; Calculate the difference between the mental state improvement evaluation values of the intervention object and the reference object, that is, the deviation difference; the deviation difference reflects the performance difference of the intervention object compared to the reference object in terms of mental state improvement. Compare the calculated deviation difference with the preset deviation threshold; If the deviation difference exceeds the threshold, mark this intervention object as a suspected abnormal effect object; this means that there is a significant difference in mental state improvement of this object compared to the reference object, and further investigation and analysis may be required. If the deviation difference is less than or equal to the preset deviation threshold, it is determined that the intervention effect of the intervention object is within the normal range, and no further abnormal investigation is required; the system normally records and stores the evaluation results of the intervention object as the basic data for subsequent analysis and summary; For the intervention objects marked as suspected of abnormal effects, their relevant information is recorded in detail, including basic demographic information, types of mental health problems, intervention characteristic information, and the calculated deviation difference; The influencing factors for setting the preset deviation threshold include: The error range of the evaluation tool: Different mental state evaluation tools have different reliabilities and validities, and their measurement errors are the basic factors to be considered when setting the preset deviation threshold; for example, some self-rating scales may have certain measurement errors. If the error range is large, the preset deviation threshold may need to be relaxed accordingly to avoid misjudging normal measurement fluctuations as abnormal effects; for evaluation tools that have undergone strict standardization verification, their error ranges are relatively small, and the preset deviation threshold can be set more precisely; Individual differences of the intervention object: Differences in an individual's demographic characteristics, severity and type of mental health problems, etc. will affect the variability of the intervention effect; people of different ages, genders, occupations, and educational levels may respond differently to the same mental health intervention measures; individuals with more severe mental health problems have a greater room for improvement after intervention, but they also face more recovery obstacles. Therefore, these factors need to be considered when setting the preset deviation threshold, and different thresholds can be set for different characteristic populations; The influence of intervention characteristics: Intervention characteristics such as the intervention implementation location and duration will also affect the intervention effect; different intervention implementation locations may mean different environmental atmospheres, resource allocations, etc., and there is usually a certain correlation between the intervention duration and the effect; short-term interventions are difficult to achieve significant improvement in mental state, while long-term interventions can bring obvious effect changes; therefore, when setting the preset deviation threshold, it is necessary to adjust according to the specific characteristics of the intervention to accurately judge whether the intervention effect is abnormal; The analysis results of historical data: By analyzing historical intervention data, the distribution and variability of the mental state improvement evaluation values of intervention objects in different situations can be understood; if the historical data shows that under similar intervention conditions, the mental state improvement evaluation values of most intervention objects are concentrated within a certain range and have small fluctuations, then the preset deviation threshold can be relatively small; conversely, if the variability of the historical data is large, the threshold needs to be increased accordingly; historical data can also help determine reasonable thresholds under different factor combinations and provide a reference basis for the current evaluation; Requirements and goals of practical applications: The setting of the preset deviation threshold also needs to consider the requirements and goals of practical applications; if the purpose of the evaluation is to early detect intervention cases that may have problems in order to adjust the intervention plan in a timely manner, then a relatively low threshold is set to improve the sensitivity of detection; if more attention is paid to avoiding misjudgment and reducing unnecessary subsequent evaluations and intervention adjustments, then the threshold can be appropriately increased to ensure the specificity of the evaluation.

[0030] In this step, by considering the error range of the evaluation tool, the individual differences of the intervention objects, the influence of intervention characteristics, and the analysis results of historical data, this step can set the preset deviation threshold more accurately, thus avoiding misjudging normal measurement fluctuations or individual differences as abnormal intervention effects; by detailedly recording the relevant information of the intervention objects marked as suspected abnormal effects, it provides basic data for subsequent in-depth analysis and verification, further improving the accuracy of the evaluation; this step considers the individual differences of the intervention objects and the influence of intervention characteristics, making the evaluation results more targeted and personalized; for different characteristic populations and different intervention characteristics, different preset deviation thresholds can be set, so as to more accurately judge whether the intervention effect is abnormal; through automated calculation of the deviation difference and comparison with the preset deviation threshold, this step can quickly and efficiently screen out the intervention objects suspected of abnormal effects, improving the efficiency of the evaluation; the evaluation results can be used as the basic data for subsequent analysis and summary, providing strong support for formulating personalized intervention strategies, optimizing intervention plans, and improving evaluation methods, enhancing the practicality of the evaluation; this step considers the requirements and goals of practical applications, and can flexibly adjust the setting of the preset deviation threshold according to different evaluation purposes and focuses to meet different application requirements such as early problem detection and avoiding misjudgment; this step scientifically and objectively judges whether the intervention object is a suspected abnormal effect object, improving the accuracy, pertinence, and personalization of the evaluation, improving the efficiency and practicality of the evaluation, and meeting the requirements of practical applications.

[0031] S4. For any one of the suspected abnormal effect objects, obtain the intervention behavior data during the intervention period, and conduct a comprehensive difference evaluation of it with the intervention behavior data corresponding to the reference object to obtain a comprehensive intervention effect score, and judge whether there is a situation of poor intervention effect for this suspected abnormal effect object according to the preset comprehensive threshold; For each intervention object suspected of abnormal effects, comprehensively collect various behavior data during the intervention period; the intervention behavior data includes: Type of intervention means: Record which specific intervention method is adopted; Intervention execution frequency: The implementation frequency of the intervention measure; Intervention execution cycle: The total duration of the intervention measure; Intervention object participation data: Record the participation degree of the intervention object during the intervention process; Interactive quality data: evaluate the quality of interaction between the intervention recipient and the intervention provider; Physiological index time-series data: the changes in physiological indexes such as heart rate and blood pressure during the intervention; Psychological state time-series data: the change trajectory of the psychological state obtained through scale evaluation, questionnaire survey, etc. during the intervention; External environmental factor data: external factors such as family support and work environment changes that may affect the intervention effect; Compare the above-mentioned intervention behavior data of the suspected abnormal effect objects with the corresponding behavior data of the reference objects one by one, and analyze the differences in each data dimension; including individual comparisons of each data dimension and comprehensive evaluations on the whole; Based on the results of the comprehensive evaluation of the differences, calculate a comprehensive intervention effect score for each suspected abnormal effect object; the calculation of the comprehensive score takes into account the weights of different data dimensions to reflect their importance to the intervention effect; Judge the comprehensive intervention effect score according to the preset comprehensive threshold; if the score is lower than the preset comprehensive threshold, it is considered that the intervention effect of this intervention object is abnormal; for the intervention objects judged to have abnormal intervention effects, further analyze their behavior data to find out the specific reasons for the abnormal effects.

[0032] In this step, by comprehensively collecting the intervention behavior data of the suspected abnormal effect objects and comparing them with the behavior data of the reference objects, it is possible to more accurately identify which intervention objects have poor intervention effects; not only considering a single data dimension, but also conducting a comprehensive evaluation on the whole, thus improving the accuracy of identification; this step covers multiple data dimensions, including the type of intervention means, execution frequency, execution cycle, intervention object participation, interaction quality, physiological indexes, psychological state, and external environmental factors, etc.; it can more comprehensively reflect the actual situation of the intervention objects during the intervention process, helping to more deeply understand the influencing factors of the intervention effect; based on the results of the comprehensive evaluation of the differences, calculate a comprehensive intervention effect score for each suspected abnormal effect object and consider the weights of different data dimensions; it can more accurately reflect the actual situation of each intervention object and provide a basis for subsequent targeted feedback and improvement suggestions; for the intervention objects judged to have abnormal intervention effects, by further analyzing their behavior data, the specific reasons for the abnormal effects can be found; it helps to optimize the intervention strategy, improve the intervention effect, and thus better meet the needs of the intervention objects; through the implementation of this step, problems in the intervention process can be discovered and solved in a timely manner, avoiding waste of resources and delay of time; at the same time, by continuously optimizing the intervention strategy, the overall efficiency and quality of the intervention can be improved.

[0033] Example 2: As Figure 3As shown in the figure, a mental health intervention effect evaluation system of the present invention specifically includes the following modules; <> A data collection module determines a number of intervention objects whose mental health is to be evaluated, and collects the demographic basic information, mental health problem types, mental state improvement evaluation values before and after the intervention, and intervention characteristic information of each of the intervention objects; <> A reference object screening module, for any one of the intervention objects, screens a historical intervention object that matches it in the historical intervention database as a reference object according to the demographic basic information, the mental health problem type, and the intervention characteristic information thereof; <> A preliminary anomaly determination module calculates the deviation difference between the mental state improvement evaluation value of the intervention object and the mental state improvement evaluation value of the reference object, and compares and determines the deviation difference based on a preset deviation threshold to determine whether the intervention object is a suspected effect anomaly object; <> A depth evaluation module, for any one of the suspected effect anomaly objects, obtains the intervention behavior data during the intervention period, and performs a comprehensive difference evaluation on it and the intervention behavior data corresponding to the reference object to obtain a comprehensive intervention effect score, and determines whether there is a situation of poor intervention effect for the suspected effect anomaly object according to a preset comprehensive threshold. <> <>

[0034] The system collects detailed information of the intervention objects through the data collection module, including demographic basic information, mental health problem types, and intervention characteristic information, providing a comprehensive individual portrait for each intervention object; the reference object screening module screens matching historical intervention objects in the historical intervention database as references according to this information, considering the influence of individual differences and intervention characteristics on the effect, making the evaluation more personalized; <> The preliminary anomaly determination module not only focuses on the intervention results, but also identifies suspected effect anomaly objects by calculating the deviation difference, introducing the concept of relative evaluation; the depth evaluation module further obtains the intervention behavior data during the intervention period, performs a comprehensive difference evaluation with the reference object, and obtains a more comprehensive comprehensive intervention effect score, realizing a full-range evaluation from the result to the process; <> Through the combination of the preliminary anomaly determination module and the depth evaluation module, the system can accurately identify the objects whose intervention effects may be abnormal; the depth evaluation module provides specific data support for the abnormal effect by comparing the intervention behavior data, making the attribution no longer stay at the hypothesis level, but having an empirical basis; <> The system provides a detailed intervention effect evaluation report, including the comprehensive intervention effect score and possible abnormal reasons, providing targeted suggestions for the formulation of improvement measures; it helps to form a closed-loop optimization mechanism and continuously improve the effect and efficiency of mental health intervention; <> In summary, the mental health intervention effect evaluation system accurately identifies objects with abnormal intervention effects through personalized and multi-dimensional evaluation methods, provides an empirical basis and targeted suggestions for improvement measures, helps to form a closed-loop optimization mechanism, and improves the overall effect and efficiency of mental health intervention.

[0035] The various change methods and specific embodiments of the mental health intervention effect evaluation method in the foregoing Embodiment 1 are equally applicable to the mental health intervention effect evaluation system of this embodiment. Through the foregoing detailed description of the mental health intervention effect evaluation method, those skilled in the art can clearly know the implementation method of the mental health intervention effect evaluation system in this embodiment. Therefore, for the sake of brevity of the specification, it will not be elaborated here.

[0036] In addition, the present application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor. The transceiver, the memory, and the processor are respectively connected through the bus. When the computer program is executed by the processor, it realizes each process of the method embodiment for controlling the output data, and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0037] The foregoing is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for evaluating the effect of mental health intervention, characterized in that, The method includes: Determine a number of intervention objects to be evaluated for mental health, and collect the demographic basic information, mental health problem types, evaluation values of mental state improvement before and after intervention, and intervention characteristic information of each of the intervention objects; For any one of the intervention objects, based on its demographic basic information, mental health problem types, and intervention characteristic information, screen for matching historical intervention objects in the historical intervention database as reference objects; Calculate the deviation difference between the mental state improvement evaluation value of the intervention object and the mental state improvement evaluation value of the reference object, and make a comparison determination based on a preset deviation threshold for the deviation difference to determine whether the intervention object is a suspected abnormal effect object; For any one of the suspected abnormal effect objects, obtain the intervention behavior data during the intervention period, and conduct a comprehensive evaluation of the differences with the intervention behavior data corresponding to the reference object to obtain a comprehensive intervention effect score, and determine whether there is a poor intervention effect for the suspected abnormal effect object according to a preset comprehensive threshold.

2. The mental health intervention effect evaluation method according to claim 1, characterized in that, The intervention behavior data includes the type of intervention means, intervention execution frequency, intervention execution cycle, intervention object participation data, interaction quality data, physiological index time series data, mental state time series data, and external environmental factor data.

3. The mental health intervention effect evaluation method according to claim 1, wherein The demographic basic information at least includes age, gender, occupation, and education level.

4. The mental health intervention effect evaluation method according to claim 1, characterized in that, The intervention characteristic information at least includes the intervention implementation location and duration.

5. The mental health intervention effect evaluation method according to claim 1, wherein The mental health problem types are collected through self-assessment questionnaires of symptom self-assessment scale, self-rating depression scale, and self-rating anxiety scale filled out by the intervention objects.

6. The mental health intervention effect evaluation method according to claim 1, wherein The construction method of the historical intervention database includes: Collect historical intervention cases; Conduct standardized processing on the collected historical intervention cases; Clean the standardized data to remove duplicate, incomplete, and incorrect data; Classify and store the data in the historical intervention database according to different types and characteristics of the data; Establish a data indexing and retrieval mechanism in the historical intervention database; Take encryption, backup, and access control measures for the database to prevent data leakage and illegal access.

7. The mental health intervention effect evaluation method according to claim 1, wherein The influencing factors for setting the preset deviation threshold include the error range of the evaluation tool, individual differences of the intervention objects, influence of intervention characteristics, analysis results of historical data, and requirements and goals of actual applications.

8. A mental health intervention effect evaluation system, characterized in that, The system includes: A data collection module that determines a number of intervention objects to be evaluated for mental health, and collects the demographic basic information, mental health problem types, evaluation values of mental state improvement before and after intervention, and intervention characteristic information of each of the intervention objects; A reference object screening module that, for any one of the intervention objects, screens for matching historical intervention objects in the historical intervention database as reference objects based on its demographic basic information, mental health problem types, and intervention characteristic information; A preliminary abnormal determination module that calculates the deviation difference between the mental state improvement evaluation value of the intervention object and the mental state improvement evaluation value of the reference object, and makes a comparison determination based on a preset deviation threshold for the deviation difference to determine whether the intervention object is a suspected abnormal effect object; The in-depth evaluation module, for any one of the suspected objects with abnormal effects, obtains the intervention behavior data during the intervention period, and comprehensively evaluates the differences between it and the intervention behavior data corresponding to the reference object to obtain a comprehensive intervention effect score, and determines whether there is a situation of poor intervention effect for the suspected object with abnormal effects according to a preset comprehensive threshold.

9. An electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected through the bus, and characterized in that, When the computer program is executed by the processor, it implements the steps in the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the method according to any one of claims 1-7.

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