Cancer survivor re-return work professional support system and method based on opportunity theory

Abstract

The invention relates to the technical field of medical rehabilitation and occupational health crossing, in particular to a professional support system and method for cancer survivors to return work based on the opportunity theory. The problem that the dynamic attention of cancer survivors is insufficient in the work returning process is solved. According to the technical scheme, the system comprises a user interaction layer, a demand evaluation module, a personalized plan generation module, a resource recommendation module and a progress tracking module; the output end of the user interaction layer is connected with the first input end of the demand evaluation module, the first output end of the demand evaluation module is connected with the input end of the personalized plan generation module, the output end of the personalized plan generation module is connected with the input end of the resource recommendation module, and the output end of the resource recommendation module is connected with the input end of the progress tracking module. The output end of the progress tracking module is connected with the second input end of the demand evaluation module. The second output end of the demand evaluation module is connected with the input end of the user interaction layer. The method has the beneficial effects that three-stage dynamic division is carried out, and more accurate and personalized professional support is provided.

Description

Technical Field

[0001] This invention relates to the field of medical rehabilitation and occupational health, and in particular to a professional support system and method for cancer survivors to return to work based on the timing theory. Background Technology

[0002] Cancer is a major public health issue. Statistics show that approximately 40%-50% of patients are diagnosed with cancer while still of working age. Meanwhile, with the development of early cancer screening and treatment technologies, cancer survival rates are gradually improving, and the number of cancer survivors in the recovery phase continues to grow (see the paper: TAMMINGA SJ, VAN HEZEL S, DE BOERA GEM, FRINGS-DRESEN MH W. Enhancing the Return to Work of Cancer Survivors: Development and Feasibility of the Nurse-Led eHealth Intervention Cancer@Work[J]. JMIR Research Protocols, 2016, 5(2).). This trend is particularly important for cancer survivors of working age, who are expected to be able to maintain their daily lives and return to work after treatment.

[0003] Return to work refers to an individual's return to their original or similar job after leaving their previous one for some reason. See the paper: Guo YW, Fu B, Mei YX, et al. Research progress on return-to-work assessment tools [J]. Chinese Journal of Rehabilitation Theory and Practice, 2018, 24(12):1417-21. Existing research shows that returning to work is a marker of complete recovery for cancer survivors. See the paper: GUO YJ, TANG J, LI JM, et al. Exploration of interventions to enhance return-to-work for cancer patients: A scoping review [J]. Clinical Rehabilitation, 2021, 35(12):1674-93. Facilitating the return to work for cancer survivors is of great significance to the individuals, families, and society of cancer survivors. See the paper: KAYA C, CHAN F, TANSEY T, et al. Evaluating the World Health Organization's International Classification of Functioning, Disability and Health Framework as a Participation Model for Cancer Survivors in Turkey[J]. Rehabilitation Counseling Bulletin, 2018, 62(4):222-33.

[0004] However, the situation regarding cancer survivors returning to work in my country is not optimistic (see paper: DE BOER AGTT). (753-62) A, ET AL. Cancer survivors and unemployment: a meta-analysis and meta-regression[J]. JAMA, 2009: . Studies show that the return-to-work rate of cancer patients in my country is 21.35%-83.40%, which is lower than the return-to-work rate of cancer survivors in developed countries (43%-93%). See the paper: Tang Cong, Qiao Chengping, Jiang Chen, et al. A systematic review of the current status and influencing factors of cancer patients returning to work in my country[J]. Military Nursing, 2022, 39(08):73-7. However, returning to work is not something that can be achieved overnight. It is a complex and dynamic process of transitioning from a disease state to a working state, which is affected by many factors. Physical and psychological factors are important factors affecting the return to work. The symptom burden brought by the disease and the negative psychological experience generated during the treatment process are prominent manifestations. Domestic and international studies have confirmed that the symptom burden experienced by cancer survivors, such as fatigue, upper limb lymphedema, and cognitive impairment, reduces their work capacity and hinders their re-employment. See the papers JSK, SUNYOUNG P, SUE KA scoping review of return to work decision-making and experiences of breast cancer survivors in Korea[J]. Supportive care in cancer: official journal of the Multinational Association of Supportive Care in Cancer, 2021. and Zhang Xin, Cui Hanfei, Dong Fengqi, Zheng Ruishuang. Meta-integration of real experiences of cancer survivors in the process of returning to work[J]. Chinese Nursing Management, 2020, 20(12):1838-44. Dai Xinyi's qualitative research further clarifies this point. See the paper: Dai Xinyi, Xu Jiashuo, Wang Han, et al. Qualitative study on the real experience of cancer patients giving up returning to work during the recovery period [J]. Journal of Nursing, 2022, 37(04):75-8. Survivors of cancer diagnosis experience a strong sense of stigma, which affects their decision to return to work.

[0005] Therefore, as professional guides for cancer survivors, medical staff need to play an important role in the process of survivors returning to work. See the paper: PORRO B, CAMPONE M, MOREAU P, ROQUELAURE Y. Supporting the Return to Work of Breast Cancer Survivors: From a Theoretical to a Clinical Perspective [J]. International Journal of Environmental Research and Public Health, 2022, 19(9). See also the paper: Xu Jiashuo, Ji Hongjuan, Li Jiamei, et al. Research on the adaptation experience and coping resources of cancer patients returning to work [J]. Journal of PLA Nursing, 2021, 38(02): 1-5. Xu Jiashuo et al. believe that cancer survivors returning to work is a process of rebuilding themselves by utilizing advantageous resources. Promoting the return to work of cancer survivors requires the effective integration of internal and external resources, strengthening multi-party collaboration, and working together to build a strong support system for this group. Medical staff are regarded as the best candidates to provide professional advice to the workplaces and other stakeholders of cancer survivors. This fully demonstrates the importance that cancer survivors attach to the advice of medical staff in the process of returning to work. This emphasis stems not only from cancer survivors' desire to return to work, but also from their recognition of the crucial role of professional support from healthcare professionals in coping with work stress, maintaining physical and mental health, and developing personalized return-to-work plans. This support comprehensively helps them smoothly reintegrate into the workplace.

[0006] A review of domestic and international literature reveals that foreign countries focused earlier on professional support for cancer survivors returning to work, with professionals developing multidisciplinary return-to-work intervention models, multimodal career support programs, and vocational rehabilitation plans. These measures have not only significantly improved the readiness of cancer survivors to return to work but also effectively improved their working conditions. However, despite these achievements abroad, limitations remain in practical application. For example, some intervention models lack precise consideration of individual differences, making it difficult to meet the diverse needs of different cancer survivors; eHealth systems face challenges in data security and privacy protection, potentially affecting cancer survivors' trust in the system; and multimodal career support programs and vocational rehabilitation plans suffer from inconsistent effectiveness due to uneven resource allocation and insufficient professional training. Furthermore, differences in cultural background, healthcare systems, and social environments across countries and regions mean that some foreign professional support methods and systems cannot be directly applied in China and require localization and innovation tailored to my country's specific circumstances. Additionally, a review of previous patents indicates that there is currently no dedicated professional support system specifically designed to meet the return-to-work needs of cancer survivors in my country.

[0007] In summary, existing technologies have the following limitations:

[0008] (1) There is insufficient attention to the dynamic nature of cancer survivors' return to work. Traditional methods often focus on assessment and intervention at a fixed point in time, while ignoring the differentiated needs faced by cancer survivors at different stages, such as the diagnosis and treatment period, the preparation period for return to work, and the adaptation period for return to work. This single-point intervention model is difficult to comprehensively and accurately capture the changes in the physical, psychological, and social functions of cancer survivors during the process of returning to work, and thus cannot provide timely and effective professional support.

[0009] (2) There are also limitations in quantitatively assessing the readiness of cancer survivors to return to work. The lack of scientific and objective assessment tools leads to a lack of targeted intervention measures, making it difficult to meet the actual needs of cancer survivors. In addition, most existing technologies focus on the medical support aspect, while neglecting the key link of job matching. They fail to fully consider the recovery of cancer survivors' vocational abilities and social functions, thus limiting the success rate of cancer survivors returning to work and the improvement of their quality of life. Summary of the Invention

[0010] The purpose of this invention is to provide a professional support system and method for cancer survivors returning to work based on timing theory. Therefore, this invention investigates the current needs and influencing factors of professional support for cancer survivors returning to work, and then constructs a comprehensive professional support system for cancer survivors returning to work. This system aims to meet the professional support needs faced by survivors during their return to work and to improve the service quality of medical personnel in this area, ensuring that cancer survivors can smoothly return to their jobs and society. Based on this, this invention constructs a three-stage return-to-work support system based on timing theory. Through dynamic division and quantitative timing identification models of the diagnosis and treatment period, the return preparation period, and the return adaptation period, it achieves precise intervention throughout the entire process from medical support to job adaptation, filling a gap in existing technologies.

[0011] A specialized support system is tailored for cancer survivors in the diagnosis and treatment phase, the return-to-work preparation phase, and the adaptation phase. This system utilizes carefully designed software modules to achieve its functionality, encompassing the following key modules: a user interaction layer, a needs assessment module, a personalized plan generation module, a resource recommendation module, and a progress tracking module. Specifically, the user interaction layer, serving as the system's front-end interface, has its output closely connected to the first input of the needs assessment module, ensuring accurate transmission of user needs. Upon receiving user information, the needs assessment module transmits its assessment results to the input of the personalized plan generation module via its first output, generating a personalized plan tailored to the user's specific circumstances. The personalized plan generation module sends the generated plan to the input of the resource recommendation module via its output. The resource recommendation module recommends appropriate resources based on the plan and transmits the recommendation results to the input of the progress tracking module via its output. The progress tracking module monitors the user's progress in real time and connects its output to the second input of the needs assessment module to adjust the assessment results based on the latest developments. The second output of the needs assessment module then feeds back the adjusted information to the input of the user interaction layer, forming a closed-loop information flow system. In addition, the system integrates a multi-dimensional evaluation model, primarily embedded in the system's data acquisition and analysis module, for comprehensively and accurately assessing user needs and progress. The built-in rule engine, as one of the system's core components, undertakes the crucial task of parsing and executing various business rules within the system, ensuring its efficient and accurate operation.

[0012] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0013] A professional support system for cancer survivors returning to work based on timing theory includes a user interaction layer, a needs assessment module, a personalized plan generation module, a resource recommendation module, and a progress tracking module. The output of the user interaction layer is connected to the first input of the needs assessment module, the first output of the needs assessment module is connected to the input of the personalized plan generation module, the output of the personalized plan generation module is connected to the input of the resource recommendation module, the output of the resource recommendation module is connected to the input of the progress tracking module, the output of the progress tracking module is connected to the second input of the needs assessment module, and the second output of the needs assessment module is connected to the input of the user interaction layer.

[0014] The user interaction layer specifically provides mobile app and web platforms. It enables cancer survivors to complete online questionnaires and track their personalized treatment plans.

[0015] The needs assessment module uses a standardized questionnaire with a reliability coefficient of Cronbach's α = 0.943, covering four dimensions: disease information support, work support, emotional support, and social resource mobilization. A cross-sectional survey was conducted by selecting a certain number (30 cases) of cancer survivors in medical institutions through convenience sampling.

[0016] The personalized treatment plan generation module dynamically combines intervention measures based on cancer type (e.g., breast cancer) and treatment stage characteristics. Breast cancer patients require upper limb function training.

[0017] The resource recommendation module connects to a resource library containing over 200 professional courses and over 30 psychological solutions. It supports filtering suitable resources based on cancer type, treatment stage, and other relevant conditions.

[0018] The progress tracking module integrates a wearable device interface to collect HRV (Heart rate variability) physiological indicators in real time, and automatically adjusts the intensity of psychological intervention when abnormal fluctuations are detected.

[0019] The needs assessment module collects patient data through an online questionnaire system and uses algorithms to analyze and prioritize needs.

[0020] The progress tracking module records the intervention process and monitors physiological indicators in real time.

[0021] A multi-dimensional assessment model and a three-stage timing recognition engine were constructed. The engine sets stage transition thresholds by quantifying treatment progress (≥95%) and recovery weeks (≥8 weeks) indicators, and integrates wearable device data interfaces to collect physiological indicators in real time to dynamically determine the patient's stage.

[0022] A timing-based approach to professional support for cancer survivors returning to work, implemented on a system based on user actions, includes the following:

[0023] S1: Users complete the survey questionnaire through the user layer;

[0024] S2: Conduct a needs assessment based on the feedback from the survey questionnaire;

[0025] S3: Generate personalized intervention measures based on the assessment content;

[0026] S4: Users combine intervention measures with the resource recommendation module to carry out interventions;

[0027] S5: The progress tracking module collects user information, records it, and provides feedback.

[0028] S6: Users make adjustments based on feedback.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] (1) This invention is based on the timing theory to make a three-stage dynamic division, which breaks through the limitations of traditional single-time-point intervention and can provide more precise and personalized professional support according to the specific needs of cancer survivors in different treatment and rehabilitation stages.

[0031] (2) This invention achieves a scientific assessment of the readiness of cancer survivors to return to work through a quantitative timing identification model, providing a strong basis for developing targeted intervention measures.

[0032] (3) This invention realizes the whole process intervention from medical support to job matching. It not only focuses on the physical health of cancer survivors, but also on the recovery of their professional abilities and social functions, thereby effectively improving the success rate and quality of life of cancer survivors returning to work.

[0033] (4) The present invention can accurately grasp the needs of cancer survivors at different stages through dynamic evaluation model, providing strong support for personalized intervention and avoiding the inaccuracy and limitations of the one-size-fits-all evaluation method in traditional technology.

[0034] (5) The multi-party collaborative support network integrates resources from multiple parties to form a comprehensive support system. Compared with the existing technology where resources are scattered and support is singular, it can more effectively promote cancer survivors to return to work and improve their quality of life. Attached Figure Description

[0035] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0036] Figure 1 This is a schematic diagram of the system model of the present invention. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. Of course, the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0038] Example 1

[0039] like Figure 1 The aforementioned professional support system for cancer survivors returning to work based on timing theory includes a user interaction layer, a needs assessment module, a personalized plan generation module, a resource recommendation module, and a progress tracking module. The output of the user interaction layer is connected to the first input of the needs assessment module, the first output of the needs assessment module is connected to the input of the personalized plan generation module, the output of the personalized plan generation module is connected to the input of the resource recommendation module, the output of the resource recommendation module is connected to the input of the progress tracking module, the output of the progress tracking module is connected to the second input of the needs assessment module, and the second output of the needs assessment module is connected to the input of the user interaction layer.

[0040] The user interaction layer specifically provides mobile app and web platforms. It enables cancer survivors to complete online questionnaires and track their personalized treatment plans.

[0041] The needs assessment module uses a standardized questionnaire with a reliability coefficient of Cronbach's α = 0.943, covering four dimensions: disease information support, work support, emotional support, and social resource mobilization. A cross-sectional survey was conducted by selecting a certain number (30 cases) of cancer survivors in medical institutions through convenience sampling.

[0042] The personalized treatment plan generation module dynamically combines intervention measures based on cancer type (e.g., breast cancer) and treatment stage characteristics. Breast cancer patients require upper limb function training.

[0043] The resource recommendation module connects to a resource library containing over 200 professional courses and over 30 psychological solutions. It supports filtering suitable resources based on cancer type, treatment stage, and other relevant conditions.

[0044] The progress tracking module integrates a wearable device interface to collect HRV (Heart rate variability) physiological indicators in real time, and automatically adjusts the intensity of psychological intervention when abnormal fluctuations are detected.

[0045] The needs assessment module collects patient data through an online questionnaire system and uses algorithms to analyze and prioritize needs.

[0046] The progress tracking module records the intervention process and monitors physiological indicators in real time.

[0047] A multi-dimensional assessment model and a three-stage timing recognition engine were constructed. The engine sets stage transition thresholds by quantifying treatment progress (≥95%) and recovery weeks (≥8 weeks) indicators, and integrates wearable device data interfaces to collect physiological indicators in real time to dynamically determine the patient's stage.

[0048] A timing-based approach to professional support for cancer survivors returning to work, implemented on a system based on user actions, includes the following:

[0049] S1: Users complete the survey questionnaire through the user layer;

[0050] S2: Conduct a needs assessment based on the feedback from the survey questionnaire;

[0051] S3: Generate personalized intervention measures based on the assessment content;

[0052] S4: Users combine intervention measures with the resource recommendation module to carry out interventions;

[0053] S5: The progress tracking module collects user information, records it, and provides feedback.

[0054] S6: Users make adjustments based on feedback.

[0055] Example 2

[0056] Based on Example 1,

[0057] The study selected cancer survivors from the Affiliated Hospital of Nantong University as the research subjects. This group included patients of different ages, with different types of cancer, and at different stages. Before the system was applied, a comprehensive assessment of the patients' physical function, psychological state, and basic work ability was conducted. These assessment data served as the initial baseline for the system intervention.

[0058] Based on the assessment results, the system develops a personalized return-to-work plan for each patient. For example, for patients with good physical recovery, a positive mental state, and who previously worked in offices, the system will gradually increase their working hours, starting with two days a week, four hours a day, while also providing regular psychological counseling and physical examinations. During implementation, the system collects weekly data on the patient's physical indicators (such as blood tests, physical fitness test results, etc.), psychological status feedback (assessed through professional psychological scales), and work performance data (evaluated by supervisors and colleagues).

[0059] Based on the collected data, the system adjusts the treatment plan twice a week. If patients show signs of fatigue, the system reduces working hours and increases rest time; if patients experience fluctuations in their mental state, the system adjusts the frequency and content of psychological counseling accordingly. After a period of implementation, the system's effects on patients' physical recovery, mental state, and return-to-work success rate were compared before and after its application. The results showed that after using this system, patients recovered faster, their mental state was more stable, and the return-to-work success rate was higher than with traditional methods, fully demonstrating the effectiveness and superiority of this system in providing professional support for cancer survivors returning to work.

[0060] Example 3

[0061] Building upon Example 1, the scope of the study was further expanded to include cancer survivors from two other large general hospitals and one specialized hospital in Nantong City. This also included patients of different ages, with various cancer types, and at different stages of treatment.

[0062] Before implementing the system, a comprehensive assessment of physical function, psychological state, and basic work ability is conducted on these patients. The obtained assessment data serves as the initial benchmark for system intervention. Based on the assessment results, the system tailors a personalized return-to-work plan for each patient. For patients whose physical function has recovered to some extent, whose psychological state is acceptable, and who previously worked in technical fields, the system will arrange for them to participate in some simple collaborative projects, working three days a week, three hours a day, while also arranging skills review courses and regular psychological support activities.

[0063] During implementation, detailed data on patients' physical indicators (such as tumor marker test results, physical flexibility test data, etc.), psychological status feedback (assessed through more detailed professional psychological scales), and work performance data (evaluated by the project leader and team members) are collected weekly.

[0064] Based on the collected data, the system adjusts the treatment plan three times a week. If abnormalities are detected in a patient's physical indicators, the system suspends work arrangements and schedules further medical examinations. If a patient experiences negative emotions such as anxiety, the system promptly arranges one-on-one counseling with a professional psychologist and adjusts the content and format of psychological support activities. After a period of implementation, the system's effects on patients' physical recovery, psychological state, and return-to-work success rate were compared before and after its implementation. The results showed that after using the system, patients recovered well, maintained a positive psychological state, and achieved a higher return-to-work success rate compared to traditional methods, further demonstrating the effectiveness and significant superiority of this system in providing professional support for cancer survivors returning to work.

[0065] Example 4

[0066] Building upon Example 3, this study further selected cancer survivors from multiple tertiary hospitals and oncology hospitals in different regions of Jiangsu Province. This study population not only included patients of different ages, with various cancer types and at different stages of treatment, but also included patients with significant differences in economic circumstances to enhance the diversity and representativeness of the study.

[0067] Before the system is implemented, these patients undergo a comprehensive and in-depth assessment of their physical function, psychological state, and basic work capacity. This assessment data serves as the initial baseline for the system's intervention. Based on the assessment results, the system develops a highly personalized return-to-work plan for each patient. For patients with moderate physical recovery, complex psychological states, and who previously engaged in manual labor, the system will arrange for them to first attempt some light physical work, such as simple logistical work or handicrafts, working two and a half days a week, two hours a day, while also providing nutritional guidance courses and regular group psychological counseling.

[0068] During implementation, comprehensive data on patients' physical indicators (such as electrocardiogram, pulmonary function test results, etc.), psychological status feedback (assessed through multi-dimensional professional psychological scales), and work performance (evaluated jointly by workplace supervisors and colleagues) are collected weekly.

[0069] Based on the collected data, the system adjusts the treatment plan four times a week. If a patient experiences significant physical discomfort, the system immediately halts the work schedule and arranges a comprehensive medical check-up. If a patient experiences severe negative emotions such as depression, the system promptly arranges a consultation with a psychologist and adjusts the form and content of group psychological counseling, increasing individualized psychological intervention. After a period of implementation, the system's effects on patients' physical recovery, psychological state, and return-to-work success rate were compared before and after its application. The results showed that after applying this system, patients experienced significant physical recovery, marked improvement in their psychological state, and a higher return-to-work success rate compared to traditional methods, further validating the system's broad effectiveness and outstanding superiority in providing professional support for cancer survivors returning to work.

[0070] This study further expands the application scenarios of a professional support system for cancer survivors returning to work based on timing theory. The system has developed a subtyping assessment module for survivors at different stages (diagnosis and treatment, return-to-work preparation, and return-to-work adaptation) and with different cancer types (e.g., breast cancer, lung cancer, colorectal cancer). By incorporating clinical variables such as tumor stage, treatment method, and complications, a more accurate demand prediction model is constructed. During the intervention phase, the system introduces virtual reality technology to provide survivors with adaptive training in a simulated workplace environment. It also collaborates with companies to conduct "Workplace Experience Day" activities to help survivors adapt to the work rhythm in advance. The tracking and optimization phase uses machine learning algorithms to deeply mine historical intervention data, automatically identify key factors affecting return to work (e.g., fatigue level, cognitive function, social support), and dynamically adjust intervention strategies. For example, for survivors with cognitive impairment after chemotherapy, the system prioritizes brain training games; for survivors with limb dysfunction, it collaborates with the rehabilitation department to develop personalized exercise programs. In the final evaluation phase, in addition to retaining the work ability scale, employer satisfaction surveys and peer evaluation modules have been added, forming a three-dimensional evaluation system to ensure that the intervention effect is verified from multiple perspectives.

[0071] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A professional support system for cancer survivors returning to work based on timing theory, characterized in that: It includes a user interaction layer, a requirements assessment module, a personalized plan generation module, a resource recommendation module, and a progress tracking module. The output of the user interaction layer is connected to the first input of the requirements assessment module, the first output of the requirements assessment module is connected to the input of the personalized plan generation module, the output of the personalized plan generation module is connected to the input of the resource recommendation module, the output of the resource recommendation module is connected to the input of the progress tracking module, the output of the progress tracking module is connected to the second input of the requirements assessment module, and the second output of the requirements assessment module is connected to the input of the user interaction layer.

2. The professional support system for cancer survivors returning to work based on timing theory according to claim 1, characterized in that, The user interaction layer specifically provides mobile apps and web platforms.

3. The professional support system for cancer survivors returning to work based on timing theory according to claim 1, characterized in that, The needs assessment module uses a standardized questionnaire covering four dimensions: disease information support, work support, emotional support, and social resource mobilization. A cross-sectional survey is conducted by selecting a certain number of cancer survivors in medical institutions using convenience sampling.

4. The professional support system for cancer survivors returning to work based on timing theory according to claim 1, characterized in that, The personalized treatment plan generation module dynamically combines intervention measures based on cancer type and treatment stage characteristics.

5. The professional support system for cancer survivors returning to work based on timing theory according to claim 1, characterized in that, The resource recommendation module connects to the resource library.

6. The professional support system for cancer survivors returning to work based on timing theory according to claim 1, characterized in that, The progress tracking module integrates a wearable device interface to collect HRV physiological indicators in real time, and automatically adjusts the intensity of psychological intervention when abnormal fluctuations are detected.

7. The professional support system for cancer survivors returning to work based on timing theory according to claim 3, characterized in that, The needs assessment module collects patient data through an online questionnaire system and uses algorithms to analyze and prioritize needs.

8. The professional support system for cancer survivors returning to work based on timing theory according to claim 6, characterized in that, The progress tracking module records the intervention process and monitors physiological indicators in real time.

9. The timing-based professional support system for cancer survivors returning to work according to any one of claims 4 and 6, characterized in that, A multi-dimensional assessment model and a three-stage timing recognition engine were constructed. The engine sets stage transition thresholds by quantifying treatment progress and rehabilitation week indicators, and integrates wearable device data interfaces to collect physiological indicators in real time, dynamically determining the patient's stage.

10. The method for providing professional support for cancer survivors returning to work based on timing theory according to any one of claims 1-8, characterized in that, The method, based on user actions on the system, specifically includes the following: S1: Users complete the survey questionnaire through the user layer; S2: Conduct a needs assessment based on the feedback from the survey questionnaire; S3: Generate personalized intervention measures based on the assessment content; S4: Users combine intervention measures with the resource recommendation module to carry out interventions; S5: The progress tracking module collects user information, records it, and provides feedback. S6: Users make adjustments based on feedback.

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