Pneumoconiosis risk assessment index construction and judgment method

Abstract

The invention relates to a pneumoconiosis risk assessment index construction and judgment method, and belongs to the technical field of health risk assessment, and the method comprises the following steps: S1, analyzing a co-occurrence relationship between pneumoconiosis risk index keywords by using a literature retrieval database; s2, preliminarily determining a pneumoconiosis risk index according to the co-occurrence relationship, and determining a consulting expert; s3, collecting scores and opinions of experts on each index; s4, calculating composite weights of the indexes based on expert scoring and literature metering; s5, according to the screened indexes, constructing a pneumoconiosis disease risk assessment index system with three levels of indexes; and S6, predicting the pneumoconiosis risk of the user by using the pneumoconiosis risk assessment index system.

Description

Technical Field

[0001] The invention belongs to the technical field of health risk assessment and relates to a method for constructing and judging a pneumoconiosis risk assessment index. Background Art

[0002] Pneumoconiosis can be prevented but not cured. Accurate early warning and effective protective measures before the disease occurs are effective ways to reduce the risk of pneumoconiosis. However, there are many factors that affect the risk of pneumoconiosis, and the hazards and risk levels of different factors vary. By establishing an indicator system, early signs of pneumoconiosis can be discovered in a timely manner, providing opportunities for early intervention and reducing the incidence and severity of the disease.

[0003] At present, researchers have established some risk assessment models to predict and evaluate the risk of pneumoconiosis. These models are often based on epidemiological survey data, combined with factors such as dust exposure level, working years, and use of personal protective measures; some countries and regions have also established occupational health monitoring systems to collect and analyze the incidence and trends of occupational diseases such as pneumoconiosis. However, there is currently a lack of unified standards for pneumoconiosis risk assessment, and different studies and regions use different indicators. For example, using relatively single indicators such as cumulative dust exposure and exhaled gas composition is difficult to accurately and comprehensively reflect the risk of disease, making the results difficult to compare and apply; some researchers have established a coal mine dust hazard evaluation index system through questionnaire surveys, but the questionnaire method is mostly qualitative and semi-quantitative, and the expert selection and expert scoring are highly subjective, affecting the accuracy and reliability of risk assessment.

[0004] Therefore, the current risk indicators for pneumoconiosis are still relatively simple, or are simply established based on subjective will. There are problems such as unrepresentative expert selection, non-objective expert opinions, difficulty in reaching consensus, and limited knowledge updating, resulting in the lack of targetedness and accuracy in pneumoconiosis warning and prevention. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method for constructing and judging a risk assessment index for pneumoconiosis.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A method for constructing and judging a risk assessment index for pneumoconiosis comprises the following steps:

[0008] S1: The co-occurrence relationship between the keywords of pneumoconiosis risk indicators was analyzed using the literature search database;

[0009] S2: Preliminarily determine the risk index of pneumoconiosis based on the co-occurrence relationship and determine the consulting expert;

[0010] S3: Collect experts’ scores and opinions on each indicator;

[0011] S4: composite weights based on expert scoring and bibliometric calculation indicators;

[0012] S5: Based on the selected indicators, a risk assessment indicator system for pneumoconiosis with three-level indicators was constructed;

[0013] S6: Predicting the user's pneumoconiosis risk using the pneumoconiosis risk assessment index system.

[0014] Further, the method of analyzing the co-occurrence relationship between the pneumoconiosis risk indicator keywords using the literature retrieval database specifically includes the following steps:

[0015] S11: Determine the literature search database, including the China National Knowledge Infrastructure Academic Journal Network Publishing Database, Web of Science Database, Engineering Village, and Wanfang Data Knowledge Service Platform;

[0016] S12: constructing subject words related to pneumoconiosis risk indicators, searching in the literature search database, and saving the search results;

[0017] S13: Extract keywords related to pneumoconiosis risk from the retrieved literature, analyze the co-occurrence relationship between keywords, and determine the distribution of key researchers and research institutions through citation analysis.

[0018] Furthermore, the preliminarily determining the pneumoconiosis risk index according to the co-occurrence relationship specifically includes:

[0019] S21: Filter keywords related to occupational health and safety management evaluation, individual differences, working environment and health monitoring from the keywords in step S13, and sort them from high to low according to the frequency of occurrence to form an indicator set t;

[0020] S22: Sort the key researchers in step S13 according to the literature distribution, and select the top N1 experts in the distribution ranking as preliminary consultation objects.

[0021] Furthermore, the scores and opinions of the experts on each indicator are collected, including:

[0022] S31: Design expert questionnaire consultation form, including the first-level index T{A,B,C,D} scoring table, the second-level index T'{A1,A2,…,A j ; B1, B2, …, B k ; C1, C2, …, C p ; D1, D2, ..., D q}Score table, three-level indicator T"{A 1.1,A 1.2 , …, A j.j' ; B1, B2, …, B k.k' ; C1, C2, …, C pp' ; D1, D2, ..., D q.q'}Score sheet;

[0023] S32: Based on step S22, select the top N2 experts in the distribution ranking as questionnaire experts, N2>2N1; divide the top N2 questionnaire experts into four fields according to the research institution field: management consulting, medical health, education and training, and industrial and mining enterprises, to form an expert database Ex{MS i , HC i , E.T. i , IM i}, i is the number of experts in each field in the expert database, i≥10; when the number of experts in a certain field i<10, the database is re-screened and supplemented through literature retrieval;

[0024] S33: Send the expert questionnaire consultation form to the first N2 questionnaire experts, and the questionnaire experts score the importance of each indicator, and collect the opinions of the experts on each indicator.

[0025] Furthermore, the composite weights based on expert scoring and bibliometric calculation indicators specifically include:

[0026] S41: Method for constructing an indicator system based on expert scoring: Statistically analyze the expert scoring results in S31, calculate the average score of each indicator, calculate the total score based on the average score, divide the average score of each indicator by the total score to obtain the normalized preliminary weight, and convert the weight into a percentage to obtain a preliminary indicator system for the risk of pneumoconiosis based on expert scoring;

[0027] Feedback the first round of scoring results and preliminary weights to experts for a second round of expert scoring. Calculate the average score and standard deviation of each indicator based on the second round of scoring; Calculate the standard deviation of each indicator. If the standard deviation of an indicator is ≥5, eliminate the indicator; Then divide the average score of each eliminated indicator by the total score to obtain the normalized weight, and convert the weight into percentage form to form a pneumoconiosis risk indicator system based on expert scoring;

[0028] S42: Method for constructing an index system based on bibliometrics: using the indicators of the pneumoconiosis risk index system based on expert scoring formed in step S41 as keywords, the bibliometric weights of the pneumoconiosis risk index within the scope of the literature in step S1 are calculated, and the steps are as follows:

[0029] ①Build a document-keyword matrix to record the number of occurrences of each keyword in each document;

[0030] ②According to the formula Calculate the IDF value of each keyword, where |D| is the total number of documents in step S1, |d∈D:t∈d| is the number of documents containing keyword t;

[0031] ③Multiply TF and IDF to get the TF-IDF(t,d,D) value of each keyword;

[0032] ④Use formula Normalize the TF-IDF(t,d,D) value to get the TF-IDF value of each indicator;

[0033] ⑤ Convert the TF-IDF value into percentage to form a risk index system for pneumoconiosis based on bibliometrics;

[0034] S43: Calculation of composite index weights

[0035] The bibliometric weight and expert scoring weight are weighted and summed according to the weight coefficient to obtain the comprehensive weight W of each indicator:

[0036] W=a×W i +β×W s

[0037] Among them, W i and W s are the bibliometric weight and expert scoring weight, α and β are the weight coefficients of the bibliometric weight and expert scoring weight, respectively.

[0038] Furthermore, the pneumoconiosis risk assessment index system includes 4 first-level indicators, 12 second-level indicators, and 56 third-level indicators, as follows:

[0039] First-level indicators: A-occupational health and safety management evaluation, B-individual differences, C-working environment, D-health monitoring;

[0040] Secondary indicators: A1-organization and management, A2-preventive measures, A3-supervision and detection, A4-occupational hazard handling and response, B1-physical quality, B2-occupational behavior quality, C1-workplace characteristics, C2-exposure characteristics, C3-protection characteristics, D1-occupational health monitoring, D2-symptom self-assessment, D3-indicator screening;

[0041] Level 3 indicator: A 1.1 - Occupational health management organization and personnel configuration, A 1.2 - Construction of occupational disease hazard prevention and control management system, A 1.3 -Promotion and training, A 1.4 - Funding for occupational health and safety, A 2.1 -Warning sign setting, A 2.2- Check equipment integrity, A 2.3 -Employees' knowledge of laws and prevention, A 2.4 - Notification of occupational hazards, A 2.5 - Work injury insurance coverage, A 3.1 -Dust detection cycle and coverage, A 3.2 - Guardianship expenses as a percentage of total costs, A 3.3 -Test result qualified, A 3.4 - Archiving and reporting of test results, A 4.1 - Alarm device settings, A 4.2 - Emergency Preparedness, A 4.3 -Test result feedback and rectification, B 1.1 - Lung disease, B 1.2 -Vital capacity, B 1.3 - Nutritional status, B 2.1 - Gender, B 2.2 - Type of work, B 2.3 -Age, B 2.4 - Years of working experience, B 2.5 -Education level, B 2.6 - Professional skills, B 2.7 -Smoking status, B 2.8 - Occupational Hazards Knowledge and Practice, C 1.1 -Unit nature scale, C 1.2 -Workmanship level, C 1.3 -Degree of automation, C 1.4 -Wet working conditions, C 1.5 - Ventilation and dust removal measures, C 1.6 - Dust source sealed, C 1.7 - Regular cleaning and maintenance, C 2.1 -Dust type, C 2.2 -Dust generation intensity, C 2.3 -Dust concentration, C 2.4 -Silicon dioxide content, C 2.5 -Dispersion, C 2.6 - Wind speed and direction, C 2.7 -Ambient temperature and humidity, C 2.8 -Labor intensity, C 2.9 -Contact time, C 2.10 -Contact frequency, C 3.1 -Protective equipment status, C 3.2 -Dust-proof effect of protective equipment, C 3.3 - Utilization rate of protective equipment, D 1.2 - Medical examination pass rate, D 1.3 - Occupational disease detection rate, D 1.4 - Post-job medical follow-up, D 2.1 - Expectoration, D2.2 - Chest tightness, D 2.3 -Dyspnea, D 3.1 -Biochemical indicators, D 3.2 - Imaging examination.

[0042] Furthermore, the weights of each indicator satisfy the following relationship:

[0043]

[0044] In the formula Indicators A to D 3.2 The weight of .

[0045] Further, step S6 specifically includes the following steps:

[0046] S61: Divide all three-level indicators into four risk levels, and set judgment conditions for each risk level of each three-level indicator; the value of the risk level is The value range is 1 to 4, where 1 indicates low risk, 2 indicates average risk, 3 indicates high risk, and 4 indicates high risk;

[0047] S62: Calculate the risk level score S of the person to be predicted:

[0048]

[0049] Among them, W i is the weight of the third-level indicator of pneumoconiosis risk, is the risk level value corresponding to the third-level indicator;

[0050] S63: Setting a risk warning value, comparing the pneumoconiosis risk level score S of the person to be predicted with the risk warning value. When S is less than the risk warning value, the risk of the disease is small; when S is greater than or equal to the risk warning value, the risk of the disease is high.

[0051] Furthermore, the risk warning value is set in the following manner: n persons with a history of pneumoconiosis are selected, their risk level scores S are calculated, a normality test is performed on the distribution of the risk level scores S, and the 95% unilateral lower limit of the reference range is taken as the risk warning value.

[0052] The beneficial effects of the present invention are:

[0053] 1. Obtain keywords, researchers, research institutions and other information related to the construction of the indicator system through literature search, so that the indicator screening process has a basis and a traceable path;

[0054] 2. Through the literature keyword co-occurrence method, an initial set of indicators can be formed, preliminary experts for the questionnaire can be determined, and the uncertainty and subjectivity generated by experience can be reduced.

[0055] 3. Combining literature review with expert scoring to construct a pneumoconiosis risk index system, so that the index system construction process has both the accuracy of quantitative analysis and the flexibility and exploratory nature of qualitative analysis.

[0056] 4. A three-level indicator system for the risk of pneumoconiosis was constructed, which includes 4 first-level indicators, 12 second-level indicators, and 56 third-level indicators, covering the various causes and processes of pneumoconiosis.

[0057] 5. The pneumoconiosis risk assessment index system constructed by the present invention is used to predict the pneumoconiosis risk, thereby improving the accuracy and efficiency of the pneumoconiosis risk assessment.

[0058] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0060] Figure 1 Construct a flow chart for the risk assessment indicator system for pneumoconiosis;

[0061] Figure 2 is the keyword co-occurrence relationship;

[0062] Figure 3 It is a distribution map of key researchers;

[0063] Figure 4 This is a distribution map of research institutions. DETAILED DESCRIPTION

[0064] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0065] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0066] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0067] like Figure 1 As shown, the present invention provides a method for constructing and judging a risk assessment index for pneumoconiosis, comprising the following steps:

[0068] Step 1: Literature review and measurement

[0069] 1.1. Determine the literature search database, including but not limited to the China National Knowledge Infrastructure (CNKI) Academic Journal Online Publishing Database, Web of Science Database (WOS), Engineering Village (EICompendex), Wanfang Data Knowledge Service Platform, etc.

[0070] 1.2. Search the literature search database in 1.1 using the keywords "pneumoconiosis", "risk", "indicator", etc. and save the search results.

[0071] 1.3. Use CiteSpace or CNKI literature analysis function to extract keywords related to pneumoconiosis risk from the literature and analyze the co-occurrence relationship between keywords, such as Figure 2 As shown; through citation analysis, the distribution of key researchers and research institutions is determined, such as Figure 3 and Figure 4 shown.

[0072] Step 2: Initial indicator determination

[0073] 2.1. Filter the keywords related to the four categories of occupational health and safety management evaluation A, individual differences B, working environment C and health monitoring D from the keywords in step 1.3, and sort them from high to low according to the frequency of occurrence to form the indicator set t.

[0074] 2.2. Sort the key researchers in step 1.3 according to the literature distribution, and select the top N1 experts as the preliminary consultation objects, with the preferred value of N1 being 5; send the indicator set t to the preliminary consultation experts, and form the pneumoconiosis risk indicator set t through expert supplementary screening.

[0075] Step 3: Expert Questionnaire Scoring

[0076] Step 3.1 Design the expert questionnaire.

[0077] The expert questionnaire consultation form consists of three parts: preface, expert basic information questionnaire, and pneumoconiosis risk indicator system consultation questionnaire.

[0078] The introduction includes the background introduction of the questionnaire, the purpose of the questionnaire and the conclusion;

[0079] The questionnaire on basic information of experts includes the expert's name, work unit, position and title, age, education level, years of work experience, current main work and field, and familiarity with the construction of the indicator system.

[0080] The consultation questionnaire on the pneumoconiosis risk index system includes the questionnaire filling instructions, the first-level index T{A,B,C,D} scoring table, the second-level index T,{A1,A2,…,A j ; B1, B2, …, B k ; C1, C2, …, C p ; D1, D2, ..., D q}Score table, three-level index T,,{A 1.1 ,A 1.2 , …, A j.j, ; B1, B2, …, B k.k, ; C1, C2, …, C pp, ; D1, D2, ..., D q.q,}Score sheet.

[0081] Step 3.2 Expert selection.

[0082] Based on step 2.2, the top N2 experts in the distribution ranking are selected as questionnaire experts, N2>2N1. The top N2 questionnaire experts are divided into four fields according to the research institution field: management consulting, medical health, education and training, and industrial and mining enterprises, forming an expert database Ex{MS i , HC i , E.T. i , IM i}, i is the number of experts in each field in the expert database, i≥10. When the number of experts in a certain field i is less than 10, the literature search database is searched with the subject word "pneumoconiosis" and the classification number "R1" or "X33" or "TD7" or "X964", and the literature is sorted from high to low according to the relevance, and the authors of the literature are screened and extracted to add to Ex{MS i , HC i , E.T. i , IM i}, until i ≥ 10.

[0083] Step 3.3 Expert scoring.

[0084] Send the expert questionnaire in step 3.1 to the experts in the expert database in step 3.2, and ask the experts to rate the importance of each indicator. At the same time, collect the experts' scores and opinions on each indicator.

[0085] Step 4: Calculate indicator weights

[0086] 4.1. Method of constructing an indicator system based on expert scoring

[0087] Perform statistical analysis on the expert scoring results in step 3.1, calculate the average score of each indicator, calculate the total score based on the average score, then divide the average score of each indicator by the total score to obtain the normalized preliminary weight, and convert the weight into percentage form to obtain a preliminary indicator system for the risk of pneumoconiosis based on expert scoring.

[0088] Feedback the first round of scoring results and preliminary weights to the experts for the second round of expert scoring. Calculate the average score and standard deviation of each indicator based on the second round of scoring; calculate the standard deviation of each indicator in 4.2. If the standard deviation of an indicator is ≥5, then eliminate the indicator, indicating that experts have great disagreement on the importance of the indicator. Then divide the average score of each eliminated indicator by the total score to obtain the normalized weight, and convert the weight into percentage form to form a pneumoconiosis risk indicator system based on expert scoring.

[0089] 4.2 Methods for constructing an indicator system based on bibliometrics

[0090] Using the indicators of the pneumoconiosis risk index system based on expert scoring formed in step 4.1 as keywords, calculate the bibliometric weight of the pneumoconiosis risk index within the scope of the literature in step 1. The steps are as follows:

[0091] ①Build a document-keyword matrix to record the number of occurrences of each keyword in each document;

[0092] ②According to the formula Calculate the IDF value of each keyword, where |D| is the total number of documents in step 1, |d∈D:t∈d| is the number of documents containing keyword t;

[0093] ③Multiply TF and IDF to get the TF-IDF(t,d,D) value of each keyword;

[0094] ④Use formula Normalize the TF-IDF(t,d,D) value to get the TF-IDF value of each indicator.

[0095] ⑤ Convert the TF-IDF value into percentage to form a risk index system for pneumoconiosis based on bibliometrics.

[0096] 4.3. Calculation of composite index weights

[0097] The bibliometric weight and expert scoring weight are weighted and summed according to the weight coefficient to obtain the comprehensive weight W of each indicator.

[0098] W=α×W i +β×W s

[0099] Among them, W i and W s are the bibliometric weight and expert scoring weight, α and β are the weight coefficients of the bibliometric weight and expert scoring weight, respectively.

[0100] Step 5: Construction of indicator system

[0101] According to the selected indicators, a pneumoconiosis risk assessment indicator system with three-level indicators was constructed. There are 4 first-level indicators, 12 second-level indicators, and 56 third-level indicators. The details are shown in Table 1. In the table, the weight of each indicator satisfies the following relationship:

[0102]

[0103] Table 1

[0104]

[0105]

[0106]

[0107] Step 6: Pneumoconiosis risk prediction

[0108] The pneumoconiosis risk assessment index system listed in Table 1 is used to evaluate the various indicators of the user, and the pneumoconiosis risk is predicted based on the comprehensive evaluation results.

[0109] The construction and judgment methods of pneumoconiosis risk assessment indicators are as follows:

[0110] ① The risk warning index system for pneumoconiosis in workers is divided into 4 levels according to the risk level, with values ​​of 1, 2, 3, and 4 from low to high, where 1 represents low risk, 2 represents general risk, 3 represents greater risk, and 4 represents high risk. As shown in Table 2.

[0111] Table 2

[0112]

[0113]

[0114]

[0115]

[0116] ② Calculate the risk level score S according to Table 2

[0117]

[0118] Among them, W i is the weight of the third-level indicator of pneumoconiosis risk, It is the risk level value corresponding to the third-level indicator.

[0119] ③ Select n (n≥200) pneumoconiosis patients in the past 30 years, calculate their risk level score S, and perform a normality test on the distribution of the risk level score S. From the perspective of protecting 95% of the population, take the 95% unilateral lower limit of the reference range as the risk warning value, and compare the pneumoconiosis risk level score S of the predicted person with the lower limit to determine the risk of pneumoconiosis. When S is less than the lower limit, the risk of pneumoconiosis is small; when S is greater than or equal to the lower limit, the risk of pneumoconiosis is large.

[0120] In the above embodiments, the description's reference to "this embodiment" indicates that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple occurrences of "this embodiment" do not necessarily all refer to the same embodiment.

[0121] In the above-described embodiments, although the invention has been described in conjunction with specific embodiments of the invention, many substitutions, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other storage structures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed. Embodiments of the invention are intended to encompass all such substitutions, modifications, and variations that fall within the broad scope of the appended claims.

[0122] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, any one of the methods in this embodiment is implemented.

[0123] This embodiment also provides an electronic terminal, including: a processor and a memory;

[0124] The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes any one of the methods in this embodiment.

[0125] The computer-readable storage medium in this embodiment can be understood by ordinary technicians in this field: all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0126] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication with each other. The memory is used to store computer programs, the communication interface is used to communicate, and the processor and the transceiver are used to run computer programs so that the electronic terminal executes each step of the above method.

[0127] In this embodiment, the memory may include a random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0128] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0129] The present invention can be used in many general or special computing system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like.

[0130] The present invention may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution 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 solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for constructing and judging a risk assessment index for pneumoconiosis, characterized in that: The following steps are involved: S1: The co-occurrence relationship between the keywords of pneumoconiosis risk indicators was analyzed using the literature search database; S2: Preliminarily determine the risk index of pneumoconiosis based on the co-occurrence relationship and determine the consulting expert; S3: Collect experts’ scores and opinions on each indicator; S4: composite weights based on expert scoring and bibliometric calculation indicators; S5: Based on the selected indicators, a risk assessment indicator system for pneumoconiosis with three-level indicators was constructed; S6: Assess and judge the user's pneumoconiosis risk using the pneumoconiosis risk assessment index system.

2. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 1, characterized in that: The method of analyzing the co-occurrence relationship between the keywords of the pneumoconiosis risk indicators by using the literature retrieval database specifically includes the following steps: S11: Determine the literature search database, including the China National Knowledge Infrastructure Academic Journal Network Publishing Database, Web of Science Database, Engineering Village, and Wanfang Data Knowledge Service Platform; S12: constructing subject words related to pneumoconiosis risk indicators, searching in the literature search database, and saving the search results; S13: Extract keywords related to pneumoconiosis risk from the retrieved literature, analyze the co-occurrence relationship between keywords, and determine the distribution of key researchers and research institutions through citation analysis.

3. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 2, characterized in that: The preliminary determination of the pneumoconiosis risk index based on the co-occurrence relationship specifically includes: S21: Filter keywords related to occupational health and safety management evaluation, individual differences, working environment and health monitoring from the keywords in step S13, and sort them from high to low according to the frequency of occurrence to form an indicator set t; S22: Sort the key researchers in step S13 according to the literature distribution, and select the top N1 experts in the distribution ranking as preliminary consultation objects.

4. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 3, characterized in that: The scores and opinions of experts on various indicators are collected, including: S31: Design expert questionnaire consultation form, including the first-level index T{A,B,C,D} scoring table, the second-level index T,{A1,A2,…,A j ; B1, B2, …, B k ; C1, C2, …, C p ; D1, D2, ..., D q }Score table, three-level index T,,{A 1.1 ,A 1.2 , …, A j.j, ; B1, B2, …, B k.k, ; C1, C2, …, C pp, ; D1, D2, ..., D q.q, }Score sheet; S32: Based on step S22, select the top N2 experts in the distribution ranking as questionnaire experts, N2>2N1; divide the top N2 questionnaire experts into four fields according to the research institution field: management consulting, medical health, education and training, and industrial and mining enterprises, to form an expert database Ex{MS i , HC i , E.T. i , IM i }, i is the number of experts in each field in the expert database, i≥10; when the number of experts in a certain field i<10, the database is re-screened and supplemented through literature retrieval; S33: Send the expert questionnaire consultation form to the first N2 questionnaire experts, and the questionnaire experts score the importance of each indicator, and collect the opinions of the experts on each indicator.

5. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 4, characterized in that: The composite weights based on expert scoring and bibliometric calculation indicators specifically include: S41: Method for constructing an indicator system based on expert scoring: Statistically analyze the expert scoring results in S31, calculate the average score of each indicator, calculate the total score based on the average score, divide the average score of each indicator by the total score to obtain the normalized preliminary weight, and convert the weight into a percentage to obtain a preliminary indicator system for the risk of pneumoconiosis based on expert scoring; Feedback the first round of scoring results and preliminary weights to experts for a second round of expert scoring. Calculate the average score and standard deviation of each indicator based on the second round of scoring; Calculate the standard deviation of each indicator. If the standard deviation of an indicator is ≥5, eliminate the indicator; Then divide the average score of each eliminated indicator by the total score to obtain the normalized weight, and convert the weight into percentage form to form a pneumoconiosis risk indicator system based on expert scoring; S42: Method for constructing an index system based on bibliometrics: using the indicators of the pneumoconiosis risk index system based on expert scoring formed in step S41 as keywords, the bibliometric weights of the pneumoconiosis risk index within the scope of the literature in step S1 are calculated, and the steps are as follows: ①Build a document-keyword matrix to record the number of occurrences of each keyword in each document; ②According to the formula Calculate the IDF value of each keyword, where |D| is the total number of documents in step S1, |d∈D:t∈d| is the number of documents containing keyword t; ③Multiply TF and IDF to get the TF-IDF(t,d,D) value of each keyword; ④Use formula Normalize the TF-IDF(t,d,D) value to get the TF-IDF value of each indicator; ⑤ Convert the TF-IDF value into percentage to form a risk index system for pneumoconiosis based on bibliometrics; S43: Calculation of composite index weights The bibliometric weight and expert scoring weight are weighted and summed according to the weight coefficient to obtain the comprehensive weight W of each indicator: W=α×W i +β×W s Among them, W i and W s are the bibliometric weight and expert scoring weight, α and β are the weight coefficients of the bibliometric weight and expert scoring weight, respectively.

6. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 1, characterized in that: The pneumoconiosis risk assessment index system includes 4 first-level indicators, 12 second-level indicators, and 56 third-level indicators, as follows: First-level indicators: A-occupational health and safety management evaluation, B-individual differences, C-working environment, D-health monitoring; Secondary indicators: A1-organization and management, A2-preventive measures, A3-supervision and detection, A4-occupational hazard handling and response, B1-physical quality, B2-occupational behavior quality, C1-workplace characteristics, C2-exposure characteristics, C3-protection characteristics, D1-occupational health monitoring, D2-symptom self-assessment, D3-indicator screening; Level 3 indicator: A 1.1 - Occupational health management organization and personnel configuration, A 1.2 - Construction of occupational disease hazard prevention and control management system, A 1.3 -Promotion and training, A 1.4 - Funding for occupational health and safety, A 2.1 -Warning sign setting, A 2.2 - Check equipment integrity, A 2.3 -Employees' knowledge of laws and prevention, A 2.4 - Notification of occupational hazards, A 2.5 - Work injury insurance coverage, A 3.1 -Dust detection cycle and coverage, A 3.2 - Guardianship expenses as a percentage of total costs, A 3.3 -Test result qualified, A 3.4 - Archiving and reporting of test results, A 4.1 - Alarm device settings, A 4.2 - Emergency Preparedness, A 4.3 -Test result feedback and rectification, B 1.1 - Lung disease, B 1.2 -Vital capacity, B 1.3 - Nutritional status, B 2.1 - Gender, B 2.2 - Type of work, B 2.3 -Age, B 2.4 - Years of working experience, B 2.5 -Education level, B 2.6 - Professional skills, B 2.7 -Smoking status, B 2.8 - Occupational Hazards Knowledge and Practice, C 1.1 -Unit nature scale, C 1.2 -Workmanship level, C 1.3 -Degree of automation, C 1.4 -Wet working conditions, C 1.5 - Ventilation and dust removal measures, C 1.6 - Dust source sealed, C 1.7 - Regular cleaning and maintenance, C 2.1 -Dust type, C 2.2 -Dust generation intensity, C 2.3 -Dust concentration, C 2.4 -Silicon dioxide content, C 2.5 -Dispersion, C 2.6 - Wind speed and direction, C 2.7 -Ambient temperature and humidity, C 2.8 -Labor intensity, C 2.9 -Contact time, C 2.10 -Contact frequency, C 3.1 -Protective equipment status, C 3.2 -Dust-proof effect of protective equipment, C 3.3 - Utilization rate of protective equipment, D 1.2 - Medical examination pass rate, D 1.3 - Occupational disease detection rate, D 1.4 - Post-job medical follow-up, D 2.1 - Expectoration, D 2.2 - Chest tightness, D 2.3 -Dyspnea, D 3.1 -Biochemical indicators, D 3.2 - Imaging examination.

7. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 6, characterized in that: The weights of each indicator satisfy the following relationship: In the formula Indicators A to D 3.2 The weight of .

8. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 6, characterized in that: Step S6 specifically includes the following steps: S61: Divide all three-level indicators into four risk levels, and set judgment conditions for each risk level of each three-level indicator; the value of the risk level is The value range is 1 to 4, where 1 indicates low risk, 2 indicates average risk, 3 indicates high risk, and 4 indicates high risk; S62: Calculate the risk level score S of the person to be predicted: Among them, W i is the weight of the third-level indicator of pneumoconiosis risk, is the risk level value corresponding to the third-level indicator; S63: Setting a risk warning value, comparing the pneumoconiosis risk level score S of the person to be predicted with the risk warning value. When S is less than the risk warning value, the risk of the disease is small; when S is greater than or equal to the risk warning value, the risk of the disease is high.

9. The method for constructing and judging the risk assessment index for pneumoconiosis according to claim 8, characterized in that: The risk warning value is set in the following manner: n persons with a history of pneumoconiosis are selected, their risk level scores S are calculated, a normality test is performed on the distribution of the risk level scores S, and the 95% unilateral lower limit of the reference range is taken as the risk warning value.

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