Method and system for evaluating adaptability influence factors of cancer patient return work

Abstract

The invention discloses a method and a system for evaluating adaptability influence factors of cancer patient return work. The method comprises the following steps: preliminarily testing questionnaires, including literature review and evaluation tool review; pretesting, including expert consultation and trial survey; performing project analysis; analyzing exploratory factors; analyzing reliability and content validity; carrying out verification factor analysis; and extracting average variance and combining validity. The method is high in reliability and validity, good in language universality and item understandability, capable of providing an evaluation practical tool for clinical and occupational rehabilitation and capable of laying a foundation for making a personalized occupational rehabilitation plan in the future.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of psychosocial rehabilitation of tumors, and more particularly relates to an evaluation method and system for factors affecting the adaptability of cancer patients returning to work. BACKGROUND

[0002] Although scholars have paid attention to how cancer patients adapt to returning to work, most studies focus on the adaptation experience and influencing factors of cancer patients at a certain specific time point or transition stage before, during and after returning to work, and no study has comprehensively evaluated and explained the entire process from diagnosis to stable work state of cancer patients. Existing domestic research shows that the adaptability of cancer patients returning to work is at a medium or low level and needs to be improved. Therefore, identifying the predictors of cancer patients' return-to-work adaptability is of great significance for providing personalized interventions for cancer patients and achieving high-level return-to-work adaptability of cancer patients. However, there is currently no relevant research.

[0003] Existing surveys show that the adaptability of cancer patients returning to work is affected by many factors, such as religious beliefs, cancer types, self-efficacy, etc., but the results of the current investigation differ due to differences in evaluation tools, statistical methods, etc., and further investigation is needed. It is understood that the guidance of clinical medical staff for cancer patients returning to work is mainly based on personal experience, and there is a lack of effective evaluation tools and practical guidelines.

[0004] According to the reports of related research, the factors affecting the adaptability of cancer patients returning to work include: sociodemographic factors (such as marital status, religious beliefs, age, etc.), disease-related factors (such as surgical plan, complications, etc.), occupation-related factors (such as job nature, work experience, etc.), mental and psychological factors (such as psychological resilience, self-efficacy, etc.), social resource factors (such as family adaptation and intimacy, social support, etc.). However, the importance of each factor on the adaptability of returning to work is not clear, and the research results differ, which needs to be verified; existing research has not focused on the impact of employment-related factors (such as work and health cognition, work and emotional coping factors), unit support, peer support, and policies on the adaptability of cancer patients returning to work. The specific influencing factors are shown in Table 1.

[0005] Table 1 Summary of factors affecting the adaptability of cancer patients returning to work

[0006]

[0007] The concept of return-to-work adaptability is relatively new, and most of the research is domestic. Although current status surveys on return-to-work adaptability of cancer patients mostly use multiple regression analysis to identify some influencing factors, this method may ignore the complex nonlinear relationships and potential characteristics of the data, and the research results do not involve the influence of unit support on return-to-work adaptability. Therefore, comprehensively identifying the factors affecting the return-to-work adaptability of cancer patients is conducive to assisting medical staff to efficiently evaluate and predict the return-to-work adaptability level of cancer patients and its dominant influencing factors, and to provide a scientific basis for developing personalized intervention and support strategies. SUMMARY

[0008] In order to solve at least one of the above technical problems, according to an aspect of the present application, an evaluation method for influencing factors of return-to-work adaptability of cancer patients is provided, comprising the following steps:

[0009] Preliminary test of questionnaire, including literature review and review of evaluation tools;

[0010] Pre-test, including expert consultation and pilot survey;

[0011] Project analysis;

[0012] Exploratory factor analysis;

[0013] Analysis of reliability and content validity;

[0014] Confirmatory factor analysis;

[0015] Average variance extraction and composite validity.

[0016] Further, the project analysis sorts the questionnaire data according to the total score from high to low, sets the data of the top 27% and the bottom 27% as the high score group and the low score group respectively, calculates the average score of each item of the two groups, and uses independent sample t test for comparison;

[0017] Item deletion criteria: t < 3.00; no statistically significant difference between the two groups; according to the dimension framework of the questionnaire, the correlation coefficient (r) between the item score and the corresponding dimension is calculated to evaluate the representativeness and independence of the item; when r < 0.40, or the difference is not statistically significant, the item is considered to be deleted;

[0018] Through the Cronbach's alpha coefficient, if the Cronbach's alpha coefficient becomes larger after deleting an item, the item is considered to be deleted; the item total correlation corrected, namely CITC, is the Pearson correlation coefficient between the item score and the total score of the questionnaire after deleting the item; if CITC < 0.30, the corresponding item is recommended to be deleted.

[0019] Further, the exploratory factor analysis determines whether the data is suitable for factor analysis through KMO and Bartlett test; when KMO>0.70 and Barlett spherical test shows P<0.05, EFA can be performed; public factors are extracted based on theoretical basis and professional knowledge, 10 public factors are set according to the previous theoretical basis; when the loading amount of the item belonging to the public factor is small, that is, the factor loading is less than 0.40, or the factor loading is induced to two or more than two factors and the loading size is similar, that is, the difference is less than 0.20, it is suggested to delete the item.

[0020] Further, the reliability analysis includes internal consistency test, split-half reliability and retest reliability.

[0021] The content validity analysis selects a plurality of experts to carry out content validity analysis, that is, CVI analysis, to evaluate the degree of conformity between the questionnaire items and the expected measurement content.

[0022] Further, the confirmatory factor analysis measures the relationship between the known potential variables and the corresponding items, and verifies the structure fitting degree of the questionnaire.

[0023] Further, the average variance extraction and combined validity calculates the average variance extraction of each factor of the questionnaire, that is, AVE and combined reliability, that is, CR, based on the confirmatory factor analysis, to test the convergent validity of the questionnaire; when AVE>0.500 and CR>0.700, it indicates that the structure convergent validity of the questionnaire is better.

[0024] According to an aspect of the present application, an evaluation system for the adaptability of cancer patients returning to work is provided, which comprises a questionnaire pretest module, a pretest module, an item analysis module, an exploratory factor analysis module, a reliability and content validity analysis module, a confirmatory factor analysis module and an average variance extraction and combined validity module.

[0025] The questionnaire pretest module is used to initiate a random questionnaire, carry out literature review and evaluation tool review.

[0026] The pretest module is used to carry out expert consultation and pilot investigation.

[0027] The item analysis module is used to sort the questionnaire data according to the total score, set the data of the top 27% and the bottom 27% as the high score group and the low score group respectively, calculate the average score of each item of the two groups, compare them by using independent sample t test, and determine whether the item should be deleted.

[0028] The exploratory factor analysis module is used to determine whether the data is suitable for factor analysis through KMO and Bartlett test.

[0029] The reliability and content validity analysis module is used for analyzing the reliability and evaluating the compliance of the questionnaire items with the expected measurement content.

[0030] The confirmatory factor analysis module is used for evaluating the relationship between the known latent variables and the corresponding items and verifying the questionnaire structure fitting degree.

[0031] The average variance extraction and combination validity module is used for calculating the average variance extraction amount of each factor of the questionnaire to test the questionnaire convergent validity.

[0032] According to another aspect of the present application, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for evaluating the factors affecting the adaptability of cancer patients to return to work according to the present application.

[0033] According to still another aspect of the present application, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for evaluating the factors affecting the adaptability of cancer patients to return to work according to the present application when executing the program.

[0034] Compared with the prior art, the present application has at least the following beneficial effects:

[0035] (1) The present application adopts various professional theories and statistical methods to strictly screen the items of the questionnaire, and the items are progressively screened and refined to achieve the best solution.

[0036] (2) The present application combines expert consultation and field investigation, and the reliability, validity, scientificity and authority of the questionnaire are guaranteed.

[0037] (3) The dimension structure design of the present application adopts the ecosystem theory, contains the micro, meso and macro levels, and conforms to the national discourse system, and embodies the value of constructing unity. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings of the embodiments will be briefly introduced below. Obviously, the drawings in the following description only relate to some embodiments of the present application and are not a limitation on the present application.

[0039] Figure 1 The present application shows the method construction process schematic diagram;

[0040] Figure 2 The present application shows the three-stage schematic diagram of the questionnaire compilation of embodiment 1. DETAILED DESCRIPTION

[0041] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application.

[0042] Unless otherwise defined, technical terms or scientific terms used herein should be understood as having the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0043] Embodiment 1

[0044] As Figures 1-2 The evaluation method for the adaptability influencing factors of cancer patients returning to work, as shown in Tables 2-5, comprises the following steps:

[0045] Pilot test of the questionnaire;

[0046] Pre-test;

[0047] Item analysis;

[0048] Exploratory factor analysis;

[0049] Reliability and content validity analysis;

[0050] Confirmatory factor analysis;

[0051] Average variance extraction and composite validity.

[0052] According to the item response theory (Item Response Theory) and the classical measurement theory (Classical Test Theory) and the guidance of the questionnaire item screening. The screening basis is:

[0053] ①Critical ratio method: by sorting the questionnaire data according to the total score, setting the data of the top 27% and the bottom 27% as the high score group and the low score group respectively, calculating the average score of each item of the two groups, and using independent sample t test for comparison. Item deletion standard: t < 3.00; there is no statistical significance between the two groups (P > 0.05).

[0054] ②Correlation coefficient method: According to the dimension framework of the questionnaire, the correlation coefficient (r) between the item score and the dimension to which it belongs is calculated to evaluate the representativeness and independence of the item. When r < 0.40 or the statistical test difference does not reach a significant level (P > 0.05), the item is considered for deletion. ③Cronbach's alpha coefficient method: Cronbach's alpha coefficient (referred to as alpha coefficient) reflects the correlation between items. If the coefficient increases after deleting an item, the item is considered for deletion. Corrected item-total correlation (CITC), which is the Pearson correlation coefficient between the item score and the total score of the questionnaire after deleting the item. If CITC < 0.30, the corresponding item is recommended for deletion.

[0055] Exploratory factor analysis (EFA): KMO and Bartlett test are used to determine whether the data is suitable for factor analysis. When KMO > 0.70 and Bartlett's sphericity test shows P < 0.05, EFA can be performed. Based on theoretical basis and professional knowledge, public factors are extracted, and 10 public factors are set based on previous theoretical basis. When the loading amount of the item belonging to the public factor is small (factor loading < 0.40), or its factor loading is induced into 2 or more factors and the loading size is similar (difference < 0.20), the item is recommended for deletion.

[0056] Reliability analysis: including internal consistency test, split-half reliability and test-retest reliability. Among them, internal consistency test: Cronbach's alpha coefficient is used to calculate the homogeneity between the total questionnaire and each index. When the alpha coefficient > 0.500, it indicates that the internal consistency of the questionnaire is good; when the alpha coefficient > 0.700, it indicates that the reliability of the questionnaire is high. Split-half reliability, also known as half reliability, is to divide the items into odd and even parts according to the order of the questions, and to test the reliability of the items by calculating the correlation coefficient of the total scores of the odd and even parts. When the odd and even numbers are different, the Spearman-Brown unequal length coefficient is used, otherwise the Spearman-Brown equal length coefficient is selected. The higher the value, the higher the reliability of the questionnaire. Test-retest reliability: used to evaluate the stability of the questionnaire, using Pearson correlation analysis test. Randomly select 30 subjects, calculate the correlation degree of the questionnaire evaluation results before and after 4-7 days interval. The time interval takes into account the possible result bias caused by short-term review of cancer patients, hospitalization time and memory of the first evaluation. When it is ≥ 0.700, it indicates that the stability of the questionnaire is high.

[0057] Content validity analysis: Eight experts were selected to conduct content validity (Content Validity Index, CVI) analysis to evaluate the degree of conformity between questionnaire items and expected measurement content, including scale-level CVI (S-CVI) and item-level CVI (I-CVI). When I-CVI ≥ 0.700 and S-CVI ≥ 0.800, the content of the questionnaire can be accepted. I-CVI = (the number of experts scoring 4 or 5) / the total number of experts; S-CVI = (the number of items scored 4 or 5) / the total number of items.

[0058] Confirmatory factor analysis: Confirmatory factor analysis (CFA) was used to evaluate the relationship between known latent variables and corresponding items to verify the structure fitting degree of the questionnaire. KMO test and Bartlett's sphericity test were used to determine whether factor analysis could be performed. CFA test was conducted, and the fitting indicators were > 0.400, R 2 > 0.300

[15] , and also met the following conditions: (1) Chi-square degrees of freedom ratio (χ 2 / df): the value range was 0-5, and if it was less than 3.000, it indicated that the overall fitting degree of the model was good. (2) Comparative fit index (CFI): if CFI > 0.850, the model fitting degree was considered acceptable. (3) Tucker-Lewis index (TLI): if TLI > 0.850, the model fitting was considered to be within the acceptable range. (4) Root mean square error of approximation (RMSEA): if RMSEA < 0.080, it indicated that the fitting of the structure model was ideal. (5) Standardized Root Mean Square Residual (SRMR): if SRMR < 0.050, it indicated that the model fitting was ideal. Based on CFA, the average variance extraction (AVE) and composite reliability (CR) of each factor of the questionnaire were calculated to test the convergent validity of the questionnaire. When AVE > 0.500 and CR > 0.700, it indicated that the convergent validity of the questionnaire structure was good.

[0059] The application discloses an evaluation system for factors affecting the adaptability of cancer patients returning to work, and comprises a questionnaire pretest module, a pretest module, an item analysis module, an exploratory factor analysis module, a reliability and content validity analysis module, a confirmatory factor analysis module and an average variance extraction and combined validity module.

[0060] The questionnaire pretest module is used for initiating a random questionnaire, carrying out literature review and evaluating tools.

[0061] The pretest module is used for expert consultation and pilot investigation.

[0062] The item analysis module is used for sorting questionnaire data according to total scores, setting data of the top 27% and the bottom 27% of the total scores as high-score groups and low-score groups respectively, calculating average scores of items of the two groups, comparing the average scores by using independent sample t-test and judging whether the items should be deleted.

[0063] The exploratory factor analysis module is used for determining whether data is suitable for factor analysis by KMO and Bartlett tests.

[0064] The reliability and content validity analysis module is used for analyzing reliability and evaluating the degree of conformity between questionnaire items and expected measurement content.

[0065] The confirmatory factor analysis module is used for evaluating the relationship between known latent variables and corresponding items and verifying the structure goodness of the questionnaire.

[0066] The average variance extraction and combined validity module is used for calculating average variance extraction of each factor of the questionnaire to test the convergent validity of the questionnaire.

[0067] There are totally 9 dimensions and 34 items.

[0068] The micro level includes four dimensions of health cognition, emotional coping, work cognition and work coping, and totally 15 items. Cancer patients will face more problems in physical, psychological and work ability reconstruction, and therefore, identifying the health cognition, emotional coping, work cognition and work coping of cancer patients is important for building personalized adaptive intervention schemes in the future.

[0069] The meso level includes three dimensions of unit support, family support and economic burden, and totally 12 items. Social support can improve the psychological and social adaptation and self-efficacy of cancer patients, and the social support provided by units, families and peers is crucial for the return-to-work adaptation of the cancer patients.

[0070] The macro level includes two dimensions of social atmosphere and policy support, and totally 7 items. Employment, economy, medical insurance and other welfare guarantees can provide professional safety for cancer patients and encourage them to participate in work.

[0071] The questionnaire distribution, follow-up and recovery are responsible for the members of the team who have been trained. Before the survey, the electronic medical records of the patients should be reviewed to screen the eligible subjects and communicate with the responsible doctors and nurses to preliminarily assess their physical and mental health status. Before the questionnaire distribution, the investigators should explain the purpose and method of the survey to the subjects and obtain their informed consent. The questionnaire should be filled out independently by the subjects. If necessary, the investigators can objectively restate the items and record the first choice of the subjects to ensure the accuracy and integrity of the data. The support of the relevant departments should be obtained before the survey. In order to minimize errors, all investigators should receive at least two training sessions on the survey procedures before they can participate in the actual survey work. The investigators should conduct one-on-one face-to-face communication with the subjects to guide them in filling out the questionnaire. The investigators should check the recovered questionnaires and give the subjects the corresponding rewards. The questionnaires should be sorted out in a timely manner to eliminate invalid or unqualified questionnaires and ensure the quality of the data. Double cross-verification is used for data entry. During the data analysis stage, missing values should be handled carefully, the statistical methods and analysis should be selected correctly according to the research purpose, and strong support should be provided for the results and conclusions.

[0072] Table 2

[0073]

[0074] Note: ** P<0.01.

[0075] Table 3

[0076]

[0077] Note: Factor 1 is work cognition; factor 2 is work coping; factor 3 is emotional coping; factor 4 is unit support; factor 5 is policy support; factor 6 is health cognition; factor 7 is social atmosphere; factor 8 is economic burden; factor 9 is support from relatives and friends.

[0078]

[0079]

[0080] Table 4 Literature review: basic information of included quantitative studies (17 studies)

[0081]

[0082]

[0083]

[0084]

[0085] Table 5 Literature review: basic information of included qualitative studies (10 studies)

[0086] ​​

[0087]

[0088] The results of the 43-item questionnaire showed that KMO=0.86, Bartlett's sphericity test χ 2 / df=8863.857 / 903 and P<0.001, suggesting that factor analysis can be performed. CFA test was carried out, as shown in Table 2, first, 5 items (GY20, GY22, DZ46, DZ19, DZ18) with factor load less than 0.400 and R 2 <0.300 were removed, and then 4 items (GY21, GY35, GY49, DZ48) with R 2 <0.300 were removed.

[0089] The model fitting index χ 2 / df<3.000; RMSEA=0.067, SRMR=0.052; CFI=0.914, TLI=0.902, all within the acceptable range. The item factor load in the 9 common factors was 0.738-0.963. The AVE of each factor of the model was 0.615-0.792 and was greater than the correlation coefficient with other factors, indicating that, on average, the degree of explanation of each latent factor to its related observation value variance was greater than that of other factors, and the correlation coefficient between factors was greater than that between other factors, providing empirical evidence with good discriminant validity. This result shows that the questionnaire itself has good discriminant validity. CR was 0.834-0.938, and the value was greater than 0.70, indicating that the questionnaire had good convergent validity. This high CR indicates that the observation indicators within each factor have high consistency in measuring the latent construct. For details, see Table 3. The total Cronbach's alpha coefficient of the questionnaire was 0.923, and the Cronbach's alpha coefficient of each dimension ranged from 0.833 to 0.936.

[0090] The final questionnaire has high reliability and validity, good language universality and item understandability, and can provide a practical tool for clinical and vocational rehabilitation and lay the foundation for future development of personalized vocational rehabilitation plans.

[0091] Embodiment 2:

[0092] The computer readable storage medium of this embodiment has a computer program stored thereon, which, when executed by a processor, implements the steps in the evaluation method for factors affecting the return-to-work adaptability of cancer patients of embodiment 1.

[0093] The computer readable storage medium of the embodiment can be an internal storage unit of the terminal, for example, a hard disk or a memory of the terminal; the computer readable storage medium of the embodiment can also be an external storage device of the terminal, for example, a plug-in hard disk, a smart memory card, a secure digital card, a flash memory card and the like equipped on the terminal; further, the computer readable storage medium can include both the internal storage unit and the external storage device of the terminal.

[0094] The computer readable storage medium of the embodiment is used to store a computer program and other programs and data required by the terminal, and can also be used to temporarily store data that has been output or will be output.

[0095] Embodiment 3:

[0096] The computer device of the embodiment includes a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps in the evaluation method for the influence factors of the cancer patient's return-to-work adaptability of embodiment 1 when executing the program.

[0097] In the embodiment, the processor can be a central processing unit, and can also be other general-purpose processors, digital signal processors, application-specific integrated circuits, ready programmable gate arrays or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components and the like, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor and the like; the memory can include read-only memories and random access memories, and provide instructions and data for the processor, and a part of the memory can also include non-volatile random access memories, for example, the memory can also store device type information.

[0098] Those skilled in the art should understand that the embodiments disclosed herein can be provided as a method, a system or a computer program product. Therefore, the present solution can be in the form of a hardware embodiment, a software embodiment or an embodiment combining software and hardware aspects. Moreover, the present solution can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage and optical storage and the like) containing computer usable program code.

[0099] The present solution is described with reference to flowcharts and / or block diagrams of the method and computer program product according to the embodiments of the present solution, and it should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions; these computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a machine for realizing the functions described in the flowcharts and / or block diagrams.Figure 1 one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0100] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flowchart Figure 1 one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowchart Figure 1 one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0102] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by computer programs instructing relevant hardware, and the programs can be stored in a computer-readable storage medium. When the programs are executed, they can include the processes of the above-mentioned embodiment methods. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM), a random access memory (RAM), or the like.

[0103] The examples described in the present application are merely used to describe the preferred embodiments of the present application, and are not used to limit the concept and scope of the present application. Without departing from the design idea of the present application, various modifications and improvements of the technical solutions of the present application made by those of ordinary skill in the art should fall within the protection scope of the present application.

Claims

1. A method for assessing factors influencing the adaptability of cancer patients returning to work, characterized in that, Includes the following steps: Initial questionnaire testing, including literature review and assessment tool review; Pre-testing, including expert consultation and pilot surveys; Project analysis; Exploratory factor analysis; Reliability and content validity analysis; Confirmatory factor analysis; Mean variance extraction and combined validity.

2. The method according to claim 1, characterized in that, The project analysis involved sorting the questionnaire data by total score, setting the top 27% and bottom 27% of the total score as the high group and low group, calculating the average score of each item in the two groups, and comparing them using an independent samples t-test. Item deletion criteria: t < 3.00; no statistically significant difference between the two groups; calculate the correlation coefficient (r) between the item score and its corresponding dimension according to the questionnaire dimensional framework to evaluate the representativeness and independence of the item; if r < 0.40, or the statistical test does not reach the significance level, the item is considered to be deleted. Using the Cronbach's α coefficient, if deleting an item increases the Cronbach's α coefficient, then consider deleting that item; the joint-corrected item total correlation, i.e., CITC, is the Pearson correlation coefficient between the item score and the total questionnaire score after deleting the item; if CITC < 0.30, it is recommended to delete the corresponding item.

3. The method according to claim 1, characterized in that, The exploratory factor analysis (EFA) was performed by using the KMO and Bartlett tests to determine whether the data were suitable for factor analysis. EFA could only be performed if KMO > 0.70 and Bartlett's test of sphericity showed P < 0.

05. Based on theoretical foundations and professional knowledge, common factors are extracted. Ten common factors are set according to the previous theoretical foundation. If the factor loading of an entry is small, i.e., factor loading < 0.40, or if its factor loading is summarized from two or more factors and the loadings are similar, i.e., the difference is < 0.20, it is recommended to delete the entry.

4. The method according to claim 1, characterized in that, The reliability analysis includes internal consistency tests, split-half reliability, and test-retest reliability. The content validity analysis, namely CVI analysis, was conducted by multiple experts to assess the degree of conformity between the questionnaire items and the expected measurement content.

5. The method according to claim 1, characterized in that, The confirmatory factor analysis assesses the relationship between known latent variables and corresponding items, and verifies the goodness of fit of the questionnaire structure.

6. The method according to claim 5, characterized in that, The mean variance extraction and combined validity are calculated based on confirmatory factor analysis, namely the mean variance extraction amount (AVE) and combined reliability (CR) of each factor in the questionnaire, in order to test the convergent validity of the questionnaire. When AVE > 0.500 and CR > 0.700, it indicates that the questionnaire structure has good convergent validity.

7. An assessment system for factors influencing the adaptability of cancer patients returning to work, characterized in that, It includes a questionnaire initial test module, a pre-test module, an item analysis module, an exploratory factor analysis module, a reliability and content validity analysis module, a confirmatory factor analysis module, and a mean variance extraction and combinatorial validity module; The questionnaire initial test module is used to initiate follow-up questionnaires, conduct literature reviews, and review assessment tools. The pre-testing module is used for expert consultation and pilot surveys; The project analysis module is used to sort the questionnaire data according to the total score, set the top 27% and bottom 27% of the total score as the high group and low group, calculate the average score of each item in the two groups, compare them using an independent samples t-test, and determine whether an item should be deleted. The exploratory factor analysis module is used to determine whether the data is suitable for factor analysis using the KMO and Bartlett tests. The reliability and content validity analysis module is used to analyze reliability and assess the degree of conformity between questionnaire items and the expected measurement content. The confirmatory factor analysis module is used to evaluate the relationship between known latent variables and corresponding items, and to verify the goodness of fit of the questionnaire structure. The mean variance extraction and combined validity module is used to calculate the mean variance extraction of each factor in the questionnaire to test the convergent validity of the questionnaire.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by the processor, it implements the steps in the method for assessing the factors influencing the adaptability of cancer patients returning to work as described in any one of claims 1 to 6.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the method for assessing factors influencing the adaptability of cancer patients returning to work as described in any one of claims 1 to 6.

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