CN111599442A - Mental health state dynamic assessment early warning system - Google Patents
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Abstract
The invention provides a mental health state dynamic assessment early warning system, which comprises: the data acquisition module is used for providing a data acquisition template for collecting the user mental state information, extracting key information items from the data acquisition template, assembling the key information items into user mental health state description characteristics and then sending the user mental health state description characteristics to the data analysis and early warning generation module; and the data analysis and early warning generation module is used for inquiring corresponding static scores, static early warning grades, dynamic scores and dynamic early warning grades from a pre-constructed user mental health static and dynamic state evaluation score table according to the mental health state static and dynamic description characteristics, finally obtaining final early warning grades according to the mapping relation between the pre-constructed user mental health state evaluation scores and the early warning grades, and sending the early warning grades to the report generation module to generate a mental state report. The invention can provide accurate mental health state evaluation and analysis results and provide important data basis for psychological problem discovery and treatment.
Description
Technical Field
The invention relates to the field of psychological crisis prevention and intervention, in particular to a psychological health state dynamic assessment early warning system.
Background
If a serious psychological problem is considered to be a "sick" condition, the following factors contribute to the development and maintenance of the disease: 1. the presence of external pathogenic factors; 2. the patient has poor congenital constitution; 3. the living conditions and hygiene habits of the patient; and 4. the above factors cannot be improved in a short period of time.
In order to find and treat psychological problems, a psychological analyst usually collects psychological state information of a patient by using an existing questionnaire or questionnaire for evaluating psychological health, then scores the psychological state information according to a grading mechanism carried by the questionnaire or questionnaire to obtain an evaluation on the current psychological health state of the patient, and finally makes a treatment scheme according to an evaluation result.
However, the existing mental state information collection and analysis of patients are based on a single scale or combined with subjective judgment of psychological workers, and the mental state of a potential risk object is influenced by the existing emergencies besides the past and intrinsic factors; the existing analysis method does not perform subsequent dynamic tracking screening after the potential risk object is screened for the first time, and does not take the emergency into account. The existing method is a static method, so that the screening accuracy is low, selection is missed or selected more, the working efficiency is not high, and resources cannot be fully applied to the crowds with the most urgent requirements.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a system for dynamically evaluating the mental health state of an individual by integrating various internal and external factors, physiological factors, social factors, past factors and current factors, and can directly provide a data analysis result of mental health state scoring and early warning which is closer to the actual situation of the individual, and the analysis result can provide reference for a mental analyst and improve the working efficiency and the effect.
The technical scheme is as follows: in order to achieve the technical effects, the technical scheme provided by the invention is as follows:
a mental health state dynamic assessment early warning system comprises: the system comprises a data acquisition module, a data analysis and early warning generation module and a report generation module;
the data acquisition module provides a data acquisition template for collecting user mental state information, extracts preset key information items from the data acquisition template, assembles the key information items into user mental health state description characteristics according to a preset format, and sends the user mental health state description characteristics to the data analysis and early warning generation module; the data acquisition template comprises a static data acquisition template and a dynamic data acquisition template, the data acquired by the static data acquisition template is used for generating the mental health state static description characteristics, and the data acquired by the dynamic data acquisition template is used for generating the mental health state dynamic description characteristics; the static data collection template includes: college student personality questionnaire UPI scale, love scale, social support scale and coping style scale; the dynamic data acquisition template includes: interview records, consultation records, records of emergency events in the user's life, records of relationship conflicts, records of basic risks, and records of negative features;
the data analysis and early warning generation module inquires corresponding static scores and static early warning grades from a pre-constructed user mental health static state evaluation score table according to mental health state static description characteristics, inquires corresponding dynamic scores and dynamic early warning grades from a pre-constructed user mental health dynamic state evaluation score table according to mental health state dynamic description characteristics, adds the static scores and the dynamic scores to obtain final user mental health state evaluation scores, finally obtains final early warning grades according to the mapping relation between the pre-constructed user mental health state evaluation scores and the early warning grades, and sends the early warning grades to the report generation module;
the report generation module is used for pre-establishing a mapping relation between the early warning grade and different types of mental state reports, and when the report generation module receives the early warning grade, the report generation module generates the corresponding mental state report according to the mapping relation.
Further, the user mental health static state evaluation score table is shown in table 1:
TABLE 1
Further, the mapping relationship between the user mental health status evaluation score and the early warning level is shown in table 2:
TABLE 2
| Early warning level | Minimum value (inclusive) | Maximum value (not inclusive) |
| Red three | 100 | All-round |
| Red two | 95 | 100 |
| Red one | 90 | 95 |
| Orange three | 85 | 90 |
| Orange II | 80 | 85 |
| Orange 1 | 75 | 80 |
| Huangsan (Chinese character of Huangsan) | 70 | 75 |
| Yellow wine | 60 | 70 |
| Yellow 1 | 50 | 60 |
| Blue three | 40 | 50 |
| Blue two | 30 | 40 |
| Blue 1 | 20 | 30 |
| Lvssan (a Chinese character of 'Lvssan') | 10 | 20 |
| Green two | 5 | 10 |
| Green to | 0 | 5 |
Further, in the negotiation record or the consultation record, if there is a dynamic early warning level given by the active rating of the consultant, the data analysis early warning generation module executes the following steps:
calculating the sum of the current static score and the dynamic score to serve as the user mental health state score, finding out the early warning level corresponding to the user mental health state score, and judging whether the current calculated early warning level and the dynamic early warning level are high or low;
if the dynamic early warning grade is high, updating the current early warning grade to be the dynamic early warning grade, and assigning the final user mental health state score to be the lowest score of the dynamic early warning grade corresponding to the score section in the user mental health dynamic state evaluation score table;
if the dynamic early warning level is low, keeping the current early warning level and the user mental health state score unchanged;
and if the dynamic early warning grade is the same as the currently calculated early warning grade, keeping the current early warning grade and the user mental health state score unchanged.
Has the advantages that: compared with the prior art, the invention has the following advantages:
the system for dynamically evaluating the individual mental health state by integrating various internal and external factors, physiological factors, social factors, past factors and current factors can directly give the data analysis result of mental health state scoring and early warning which is closer to the actual situation of the individual, and the analysis result can provide reference for a mental analyst and improve the working efficiency and effect.
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Fig. 1 is a schematic diagram illustrating a functional module architecture of a mental health state dynamic assessment early warning system according to an embodiment;
FIG. 2 is a diagram illustrating the selection of key information items in various gauges according to an exemplary embodiment;
FIG. 3 is a flow diagram of a data analysis and alert generation module according to an embodiment;
fig. 4 is a hardware platform of a mental health state dynamic assessment early warning system.
Detailed Description
The invention will be further described with reference to the accompanying drawings and specific embodiments. It is to be understood that the present invention may be embodied in various forms, and that there is shown in the drawings and will hereinafter be described some exemplary and non-limiting embodiments, with the understanding that the present invention is not intended to be limited to the specific embodiments illustrated.
It is to be understood that the features listed above for the different embodiments may be combined with each other to form further embodiments within the scope of the invention, where technically feasible. Furthermore, the particular examples and embodiments of the invention described are non-limiting, and various modifications may be made in the structure, steps, and sequence set forth above without departing from the scope of the invention.
The invention provides a mental health state dynamic assessment early warning system, and fig. 1 shows a functional architecture of the mental health state dynamic assessment system provided in this embodiment, which includes: the system comprises a data acquisition module, a data analysis and early warning generation module and a report generation module;
the data acquisition module provides a data acquisition template for collecting user mental state information, extracts preset key information items from the data acquisition template, assembles the key information items into user mental health state description characteristics according to a preset format, and sends the user mental health state description characteristics to the data analysis and early warning generation module; the data acquisition template comprises a static data acquisition template and a dynamic data acquisition template, the data acquired by the static data acquisition template is used for generating the mental health state static description characteristics, and the data acquired by the dynamic data acquisition template is used for generating the mental health state dynamic description characteristics; the static data collection template includes: college student personality questionnaire UPI scale, love scale, social support scale and coping style scale; the dynamic data acquisition template includes: interview records, consultation records, records of emergency events in the user's life, records of relationship conflicts, records of basic risks, and records of negative features;
the work flow of the data analysis early warning generation module is shown in fig. 3: the data analysis and early warning generation module inquires corresponding static scores and static early warning grades from a pre-constructed user mental health static state evaluation score table according to the mental health state static description characteristics, inquires corresponding dynamic scores and dynamic early warning grades from a pre-constructed user mental health dynamic state evaluation score table according to the mental health state dynamic description characteristics, adds the static scores and the dynamic scores to obtain final user mental health state evaluation scores, finally obtains final early warning grades according to the mapping relation between the pre-constructed user mental health state evaluation scores and the early warning grades, and sends the early warning grades to the report generation module;
the report generation module is used for pre-establishing a mapping relation between the early warning grade and different types of mental state reports, and when the report generation module receives the early warning grade, the report generation module generates the corresponding mental state report according to the mapping relation. The psychological state report records the evaluation content and coping strategies of the psychological health state corresponding to different early warning levels, and the following table shows:
in the above example, university student personality questionnaire (UPI) is one of the most commonly used neonatal psychological condition screening tools in schools, and its credibility and degree of local engagement are supported by a large body of literature. The table was compiled in 1966 by a psychological counsel specialist at university of japan in collective with a psychiatrist. In 1991, the society of Japan students talks about Long Sonada before and how long translation is introduced with Long translation. In 1993, the fan with long, Wang Jianzhong ' nationwide UPI applied course study ', UPI's relevant item screening standards, implementation process and the like were systematically revised.
The format of the loving scale can be specifically referred to as the following documents:
[1]Bartholomew K,Horowitz,M.L.Attachment styles among young adults:Atest of a four-category model.Journal of Personality and Social Psychology,1991,61(2)，226-244.
[2]Griffin D,Bartholomew K.Models of the self and other:Fundamentaldimensions underlying measures of adult attachment.Journal of Personality andSocial Psychology, 1994,67(3)，430-445.
[3] u. a beautiful jade of youth, guo yongyu [ J ]. internal work model of love, south kyo university newspaper (social science edition), 2008(1), 98-104.
In the early warning model, the measurement result of the UPI is an important basis for screening and is also a reference key point for early warning classification. Besides the total score, the judgment of the individual case early warning result by the following items of the UPI also has a great reference value: item 8 'i past and family are unfortunate' has a high degree of prediction of serious cases that may occur later; item 25, which is' thought to be light, has stronger prediction value when being matched with high total score or other key items; item 67 'experience with psychological counseling' is an important indicator of whether the post-case will actively enter counseling; the score of the test is an important index for judging the effectiveness of the user in answering the questionnaire.
In the attachment scale, attachment types are divided into four according to Bowlby (1969,1973,1988) theory: safety type (active others and active self), denial type (passive others and active self), fear type (passive others and passive self), preemption type (active others and passive self), wherein the latter three types are collectively referred to as non-safety type. The loving model has important influence on the establishment and maintenance of the relationship in the adult stage, has internal association with various psychological disorders and has important significance on the understanding of self-injury/suicide.
The social support scale mainly comprises two dimensions of family support and interpersonal support, wherein the group with low score needs to be considered by integrating the results of the attaching type and life significance scale, and the support scale is also an important basis for dividing the early warning grade by referring to the UPI result. The method can be divided into high support, medium support and low support.
A coping style table, which indicates an automated process (automated process) that an individual case employs in the face of a stressful event. Whether relying on internal coping or seeking external help, whether using positive or negative means, or more of changing cognition or reducing action. The result of the coping style scale shows at least two aspects, namely the energy bet (using real experience or disguised defense) of the individual case in daily life, which has important reference value for helping to screen the UPI false question high-score people. Secondly, behavior prediction, different classified cases will have different actions when they are also exposed to external stress, and those with the three characteristics of negative/action/internal handling should pay more attention in case management. Can be divided into active treatment and passive treatment.
The relationship conflict record is used for describing conflict characteristics such as language lines and the like existing between the object and relevant key persons or crowds, and comprises parent-child conflict, companion conflict and lover conflict, wherein the parent-child conflict refers to the characteristics of conflict between the object and parents (including live parents, nurturing parents and succeeding parents), such as whether the conflict is violent and whether the conflict is accompanied by walking behavior and the like; the peer conflict refers to the characteristics of conflict between the object and the peer (including classmates, colleagues, friends, and the like, mainly age-matched people), such as the cause of conflict, whether there is a conflict between limbs, and the like; the lover conflict refers to conflict characteristics between the object and the lover, such as whether two persons have been separated, whether the language or behavior of the other party is threatened, and the like.
Basic risk records describe the subject's existing physical and mental disorders or diseases and their characteristics, such as whether they suffer from depression, whether they relapse, whether they affect daily functioning, etc.
And the negative characteristic record is used for describing negative events and characteristics of the object in daily life, study and the like, such as poor examination, influence on acquisition of academic degree and the like.
As shown in fig. 2, in this embodiment, question 8, question 25, question 67, total score of UPI, and pseudo score in university student personality questionnaire UPI are selected as key information items, an attaching type is selected from an attaching scale as a key information item, a social support type is selected from a social support scale as a key information item, a corresponding mode is selected from a corresponding mode scale as a key information item, and the key information items are arranged and combined to form 73 combinations, each combination is a static description feature for generating mental health status. Each combination corresponds to a primary early warning grade and is assigned with an initial score (the score is shown in table 1), 15 grades are provided in total and are divided into five major classes, namely red early warning (red three, red two, red one), orange early warning (orange three, orange two, orange one), yellow early warning (yellow three, yellow two, yellow one), blue early warning (blue three, blue two, blue one), green (green three, green two, green one), the psychological crisis is gradually reduced from red to green, the red three psychological crisis is the most serious, and the green one psychological crisis the least serious. An early warning grade is formed for each individual through the model and is treated respectively.
TABLE 1
In table 1, the first column is a combination number, the second column is a result of whether the 25 th item in the UPI scale is selected, the third column is a total UPI score, the fourth column is a small combination of results of whether the 8 th item and the 67 th item in the key UPI option are selected, the fifth column is a result of an attaching scale (safe type and non-safe type), the sixth column is a result of a social support and response mode scale, the seventh column is a warning grade result of each combination, and the eighth column is an initial score of each warning grade. The column-to-column relationship is "and", that is, the several results must be simultaneously obtained to obtain the corresponding warning level. In the sixth column, the results in the column are in an or relationship, that is, if one of the results is combined with the results in the first five columns, an early warning level can be obtained.
The psychoanalyst may do the following according to the primary alert level and mental health status score:
in subsequent treatment and daily treatment, the psychological states of the individual subjects are continuously pre-warned or the daily treatment is directly carried out without test, including the treatment of interviewing and consultation; daily tracking treatment: information such as emergencies, relationship conflicts, basic risks, negative characteristics, negotiation records, consultation records, emergencies records, relationship conflict records, basic risk records, negative characteristics and the like is recorded into the system through a data acquisition template provided by the data acquisition module so as to facilitate subsequent analysis. The combination of the six dynamic factors is the dynamic description characteristics of the mental health state, and the corresponding dynamic scores and the dynamic early warning grades are inquired from a pre-constructed evaluation score table of the mental health dynamic state of the user according to the dynamic description characteristics of the mental health state. And finally, obtaining a final early warning grade according to a mapping relation between the pre-constructed user mental health state evaluation score and the early warning grade. The mapping relationship between the user mental health state evaluation score and the early warning level is shown in table 2:
TABLE 2
| Early warning level | Minimum value (inclusive) | Maximum value (not inclusive) |
| Red three | 100 | All-round |
| Red two | 95 | 100 |
| Red one | 90 | 95 |
| Orange three | 85 | 90 |
| Orange II | 80 | 85 |
| Orange 1 | 75 | 80 |
| Huangsan (Chinese character of Huangsan) | 70 | 75 |
| Yellow wine | 60 | 70 |
| Yellow 1 | 50 | 60 |
| Blue three | 40 | 50 |
| Blue two | 30 | 40 |
| Blue 1 | 20 | 30 |
| Lvssan (a Chinese character of 'Lvssan') | 10 | 20 |
| Green two | 5 | 10 |
| Green to | 0 | 5 |
In the negotiation and consultation, an option that a consultant initiatively evaluates the early warning grade exists, the consultant can directly give an early warning grade to a user according to knowledge and experience, meanwhile, other items can be filled in the negotiation and consultation records, the scores of the other items are added with the initial score to obtain a new score and a new early warning grade, the early warning grade is compared with the initiatively evaluated early warning grade and is determined according to the old plateau, and the method is as follows:
calculating the sum of the current static score and the dynamic score to serve as the user mental health state score, finding out the early warning level corresponding to the user mental health state score, and judging whether the current calculated early warning level and the dynamic early warning level are high or low;
if the dynamic early warning grade is high, updating the current early warning grade to be the dynamic early warning grade, and assigning the final user mental health state score to be the lowest score of the dynamic early warning grade corresponding to the score section in the user mental health dynamic state evaluation score table;
if the dynamic early warning level is low, keeping the current early warning level and the user mental health state score unchanged;
and if the dynamic early warning grade is the same as the currently calculated early warning grade, keeping the current early warning grade and the user mental health state score unchanged.
Preferably, the mental health state dynamic assessment and early warning system according to the above embodiment may be deployed on a hardware platform shown in fig. 4, where the whole hardware platform includes an early warning system server, a memory/database, an input/output device, and a terminal. The data acquisition module, the data analysis and early warning generation module and the report generation module are all deployed on the early warning system server to realize the functions of the modules. The memory/database is used for storing various data acquisition templates, a user mental health static state evaluation score table, a user mental health dynamic state evaluation score table, a mapping relation table between the user mental health state evaluation score and early warning grades, a mapping relation table between the early warning grades and different types of mental state reports and pre-constructed mental state reports. The input and output equipment is used for realizing the external data acquisition and output of the early warning system server. The terminal can interact with the early warning system server, receive and display the generated mental state report, and the terminal includes but is not limited to: intelligent equipment such as cell-phone, pad, computer.
The technical scheme provided by the invention at least has the following technical effects:
the system and the method can acquire the current mental health state information of the individual in real time, and perform data analysis to obtain the current mental health state score and early warning grade of the individual. After the primary early warning data is generated, the later individual daily data information can be tracked, the tracking information is recorded into the system to serve as dynamic data, and the system generates the latest early warning level according to the static data and the current dynamic data in the past period; performing corresponding treatment according to the latest current early warning level; the process is repeated continuously, the mental health state score and the early warning grade of the user can be analyzed accurately at any time, professional personnel such as a psychoanalyst or a psychologist are given accurate data analysis results as references, and the efficiency of the mental analysis work is improved.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (4)
1. A mental health state dynamic assessment early warning system, characterized by comprising: the system comprises a data acquisition module, a data analysis and early warning generation module and a report generation module;
the data acquisition module provides a data acquisition template for collecting user mental state information, extracts preset key information items from the data acquisition template, assembles the key information items into user mental health state description characteristics according to a preset format, and sends the user mental health state description characteristics to the data analysis and early warning generation module; the data acquisition template comprises a static data acquisition template and a dynamic data acquisition template, the data acquired by the static data acquisition template is used for generating mental health state static description characteristics, and the data acquired by the dynamic data acquisition template is used for generating mental health state dynamic description characteristics; the static data collection template includes: college student personality questionnaire UPI scale, love scale, social support scale and coping style scale; the dynamic data acquisition template includes: interview records, consultation records, records of emergency events in the user's life, records of relationship conflicts, records of basic risks, and records of negative features;
the data analysis and early warning generation module inquires corresponding static scores and static early warning grades from a pre-constructed user mental health static state evaluation score table according to mental health state static description characteristics, inquires corresponding dynamic scores and dynamic early warning grades from a pre-constructed user mental health dynamic state evaluation score table according to mental health state dynamic description characteristics, adds the static scores and the dynamic scores to obtain final user mental health state evaluation scores, finally obtains final early warning grades according to the mapping relation between the pre-constructed user mental health state evaluation scores and the early warning grades, and sends the early warning grades to the report generation module;
the report generation module is used for pre-establishing a mapping relation between the early warning grade and different types of mental state reports, and when the report generation module receives the early warning grade, the report generation module generates the corresponding mental state report according to the mapping relation.
2. The mental health state dynamic assessment and pre-warning system as claimed in claim 1, wherein the evaluation score table of the user mental health static state is shown in table 1:
TABLE 1
3. The mental health state dynamic assessment pre-warning system according to claim 2, wherein the mapping relationship between the user mental health state evaluation score and the pre-warning level is shown in table 2:
TABLE 2
4. The system of claim 1, wherein if there is a dynamic warning level given by the active rating of the consultant in the negotiation record or consultation record, the data analysis warning generation module performs the following steps:
calculating the sum of the current static score and the dynamic score to serve as the user mental health state score, finding out the early warning level corresponding to the user mental health state score, and judging whether the current calculated early warning level and the dynamic early warning level are high or low;
if the dynamic early warning grade is high, updating the current early warning grade to be the dynamic early warning grade, and assigning the final user mental health state score to be the lowest score of the dynamic early warning grade corresponding to the score section in the user mental health dynamic state evaluation score table;
if the dynamic early warning level is low, keeping the current early warning level and the user mental health state score unchanged;
and if the dynamic early warning grade is the same as the currently calculated early warning grade, keeping the current early warning grade and the user mental health state score unchanged.
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| CN112927782A (en) * | 2021-03-29 | 2021-06-08 | 山东思正信息科技有限公司 | Mental and physical health state early warning system based on text emotion analysis |
| CN112927782B (en) * | 2021-03-29 | 2023-08-08 | 山东齐鲁心理健康研究院有限公司 | Heart health state early warning system based on text emotion analysis |
| CN113270167A (en) * | 2021-05-18 | 2021-08-17 | 石河子大学 | Child psychological state assessment system based on fuzzy evaluation |
| CN116453656A (en) * | 2023-04-11 | 2023-07-18 | 中国人民解放军总医院第六医学中心 | Psychological health assessment early warning system and psychological health assessment early warning method |
| CN116453656B (en) * | 2023-04-11 | 2023-10-03 | 中国人民解放军总医院第六医学中心 | Psychological health assessment early warning system and psychological health assessment early warning method |
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