A lumbar degenerative disease patient treatment expectation evaluation system

Abstract

The application discloses a lumbar degenerative disease patient treatment expectation evaluation system and relates to the technical field of medical health information processing; the system comprises a data acquisition unit, a expectation evaluation unit, an influence factor analysis unit and a report generation unit; the data acquisition unit is used for collecting multidimensional information of a lumbar degenerative disease patient; the expectation evaluation unit is connected with the data acquisition unit and is used for quantitatively evaluating the treatment expectation of the patient based on the collected information; the influence factor analysis unit is connected with the expectation evaluation unit and is used for analyzing key factors influencing the treatment expectation of the patient; the report generation unit is connected with the expectation evaluation unit and the influence factor analysis unit and is used for integrating evaluation and analysis results and generating a visual evaluation report. The application integrates various evaluation tools that have been tested for reliability and validity, converts subjective inquiries that are originally scattered and depend on the personal experience of medical staff into a unified, standardized and multidimensional quantitative evaluation process, and ensures the scientificity and comparability of evaluation results.

Description

Technical Field

[0001] This invention relates to the field of medical and health information processing technology, and in particular to a treatment expectation assessment system for patients with lumbar degenerative diseases. Background Technology

[0002] Degenerative lumbar spine diseases are the most common type of spinal degenerative diseases, mainly including lumbar spondylolisthesis, lumbar disc herniation, and lumbar spinal stenosis, with a global incidence rate as high as 60%. They are a major cause of lower back pain, functional impairment, and decreased quality of life for patients. With the development of medical technology, the clinical focus has shifted from simply the success rate of surgery to a comprehensive evaluation of postoperative functional recovery and long-term quality of life. Studies have shown that patients' treatment expectations are a key psychological factor influencing treatment outcomes and satisfaction. Positive and reasonable treatment expectations help improve treatment effectiveness and patient satisfaction, while unrealistic high expectations can lead to a gap between expectations and reality, resulting in patient dissatisfaction and even medical disputes.

[0003] Currently, research on treatment expectations, both domestically and internationally, covers a variety of diseases. However, systematic assessment tools for treatment expectations in patients with lumbar degenerative diseases are still incomplete. In clinical practice, healthcare professionals often rely on experience or simple questioning to understand patient expectations, lacking standardized, multi-dimensional quantitative assessment methods. This makes it difficult to comprehensively and accurately capture patients' expectation levels and the complex influencing factors related to pain, fatigue, emotional distress, and limitations in daily activities. This results in the inability to develop individualized expectation management and clinical intervention plans for patients, affecting the optimization of overall treatment outcomes. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a treatment expectation assessment system for patients with lumbar degenerative diseases.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A treatment expectation assessment system for patients with lumbar degenerative diseases, comprising: The data acquisition unit is used to collect multi-dimensional information on patients with lumbar degenerative diseases. An expectation assessment unit, connected to the data acquisition unit, is used to quantitatively assess the patient's treatment expectations based on the collected information. The influencing factor analysis unit, connected to the expectation assessment unit, is used to analyze key factors that affect patients' treatment expectations. The report generation unit, connected to the expected assessment unit and the influencing factor analysis unit, is used to integrate the assessment and analysis results and generate a visual assessment report.

[0006] Preferably, the data acquisition unit includes: The data collection module is used to collect patients' sociodemographic data and disease-related data. The sociodemographic data includes age, gender, marital status, place of residence, education level, occupation, average monthly income per capita in the family, and medical expense payment method. The disease-related data includes disease diagnosis type, pain location, pain nature, position-related pain, presence of functional impairment, number of hospitalizations due to the disease, and presence of other chronic diseases. The symptom assessment module is used to collect patients' symptom severity scores in four dimensions: pain, fatigue, emotional distress, and limitation of daily activities. The psychosocial assessment module is used to collect scores on patients' anxiety levels, depression levels, and social support levels.

[0007] Preferably, the expectation assessment unit uses a patient-centered outcome questionnaire to quantitatively assess the patient's treatment expectations. The assessment includes five aspects: normal level, ideal expectation, success criteria, predicted expectation, and importance of symptom improvement. Each aspect is scored for four symptom dimensions: pain, fatigue, emotional distress, and limitation of daily activities.

[0008] Preferably: the normal level represents the severity of each symptom in the week prior to admission, with a higher score indicating more severe symptoms; The ideal expectation refers to the patient's expectation that each symptom can reach the best state after treatment; The success criteria indicate the extent to which patients believe their symptoms need to improve after treatment in order to be considered a successful treatment. The predicted expectation refers to the level that the patient predicts each symptom may reach after treatment; The higher the scores for ideal expectation, success criteria, and predicted expectation, the lower the patient's treatment expectations for that symptom dimension. The importance of symptom improvement indicates the degree to which the improvement of each symptom is important to the patient; the higher the score, the more important it is.

[0009] Preferably, the symptom assessment module uses a digital rating scale to measure and score the patient's pain level; the psychosocial assessment module uses a comprehensive hospital anxiety and depression scale to measure and score the patient's anxiety and depression levels, and uses a social support rating scale to measure and score the patient's social support level.

[0010] Preferably, the influencing factor analysis unit includes: The univariate analysis module is used to analyze statistical differences among patients’ general information, symptom scores, psychosocial scores, and scores of each dimension of treatment expectations. The correlation analysis module is used to analyze the correlation between the scores of each dimension of treatment expectation and the scores of the numerical rating scale, anxiety score, depression score, and social support score. The multivariate analysis module is used to perform multiple linear regression analysis with statistically significant variables from univariate and correlation analyses as independent variables and scores of each dimension of treatment expectation as dependent variables to identify the factors influencing treatment expectation.

[0011] Preferably, the influencing factors of the normal level of pain determined by the multifactor analysis module include: pain location, pain nature, presence of functional impairment, and numerical rating scale score; The factors influencing typical level fatigue include: Digital Rating Scale score and anxiety score; The factors influencing the typical level of emotional distress include: numerical rating scale score, anxiety score, and depression score. The factors influencing the typically limited daily activities include: the presence of functional impairment and the Digital Rating Scale score. The factors influencing the ideal expected pain identified by the multifactor analysis module include: marital status, pain nature, and numerical rating scale score. The factors influencing the ideal expected fatigue include: positional pain; The factors influencing emotional distress related to ideal expectations include: occupation, location of pain, and position-related pain. Factors affecting the limitation of ideal daily activities include: the nature of pain and position-related pain.

[0012] Preferably, the factors influencing the success criteria pain determined by the multifactor analysis module include: pain nature and anxiety score; The factors influencing the success criteria for fatigue include: the nature of the pain; The factors influencing emotional distress as defined by the success criteria include: depression score; The factors influencing the limited daily activities mentioned in the success criteria include: the presence or absence of other chronic diseases and depression scores; The influencing factors for predicting expected fatigue identified by the multivariate analysis module include: postural pain and depression score; The factors influencing the predicted expected emotional distress include: the number of hospitalizations due to this illness; The factors that influence the predicted limitation of daily activities include: the location of pain and the number of hospitalizations due to the disease.

[0013] Preferably, the influencing factors of the symptom improvement importance of pain determined by the multivariate analysis module include: postural pain, numerical rating scale score, depression score, and social support score; The factors influencing the importance of improving fatigue symptoms include: occupation, numerical rating scale score, and anxiety score; The factors influencing the improvement of symptoms and emotional distress include: position-related pain, digit rating scale score, anxiety score, and depression score. The factors influencing the improvement of symptoms and limitations in daily activities include: postural pain and social support score.

[0014] Preferably, the assessment report generated by the report generation unit includes: a display of scores for each dimension of the patient's treatment expectations, a comparative analysis with norms or historical data, risk warnings based on the analysis results of influencing factors, and targeted clinical intervention recommendations, including expectation management, pain care, psychological support, fatigue intervention, and social support enhancement strategies.

[0015] The beneficial effects of this invention are as follows: 1. This invention integrates multiple assessment tools that have been tested for reliability and validity, transforming the originally scattered and subjective inquiries that rely on the personal experience of medical staff into a unified, standardized, and multi-dimensional quantitative assessment process, ensuring the scientific nature and comparability of the assessment results.

[0016] 2. The system of this invention not only assesses the severity of symptoms, but also innovatively creates a comprehensive profile of the patient's treatment expectations from refined dimensions such as normal level, ideal expectation, success criteria, predicted expectation, and importance of improvement. It accurately captures the patient's complex psychological expectations for improvement in pain, fatigue, mood, and daily function, filling the gap in assessment tools in this field.

[0017] 3. This invention integrates assessment, analysis, and report generation through an automated process. This system can significantly shorten the time required for a comprehensive patient assessment, enabling medical staff to quickly grasp the patient's core needs and psychosocial risks, thereby developing and implementing more targeted and forward-looking individualized treatment, communication, and care plans.

[0018] 4. The objective evaluation results provided by the system of this invention can serve as an effective tool for doctor-patient communication, helping both parties to establish reasonable and consistent expectations before treatment, reducing misunderstandings and dissatisfaction caused by information asymmetry or gaps in expectations, thereby improving treatment compliance and satisfaction and preventing potential doctor-patient conflicts. Attached Figure Description

[0019] Figure 1 This is a flowchart of a treatment expectation assessment system for patients with lumbar degenerative diseases proposed in this invention. Detailed Implementation

[0020] The technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0021] Example 1:

[0022] A treatment expectation assessment system for patients with lumbar degenerative diseases, which mainly includes a data acquisition unit, an expectation assessment unit, an influencing factor analysis unit, and a report generation unit.

[0023] Study subjects: A cross-sectional study design was adopted. From August 2024 to February 2025, convenience sampling was used to select inpatients with preoperative lumbar degenerative diseases who met the inclusion and exclusion criteria from a tertiary hospital in Chongqing as the study subjects. The data acquisition unit is responsible for comprehensively collecting patient information. This is achieved through the following modules: Data Collection Module: This module collects patients' sociodemographic and disease-related data. During implementation, this data can be automatically obtained through the electronic medical record interface or input by healthcare professionals / patients via a terminal interface. For example, it collects information such as age, gender, marital status, place of residence, education level, medical expense payment method, occupation, average monthly household income per capita, disease location, nature of pain, position-related pain, presence of functional impairment, number of hospitalizations due to this disease, and presence of other chronic diseases. The following shows the statistical results of general information for 281 patients:

[0024]

[0025] Symptom assessment module: The Numerical Rating Scale (NRS) was used to collect patients' current pain intensity. This scale uses a 0-10 scale, where 0 represents "no pain" and 10 represents "most severe pain." Patients marked their pain levels according to their own experience. In this study sample, the average NRS score was (5.33±1.58), falling within the moderate pain range.

[0026] Psychosocial assessment module: The Comprehensive Hospital Anxiety and Depression Scale was used to assess anxiety and depression levels. This scale includes two subscales, anxiety and depression, each with 7 items, and a total score of 0-21. A score of 0-7 indicates no symptoms, 8-10 indicates suspected symptoms, and 11-21 indicates definite symptoms. In this study, the average anxiety score of the sample patients was (4.84±3.14), and the average depression score was (5.66±2.91). Simultaneously, the social support rating scale was used to assess social support levels. This scale includes three dimensions: objective support, subjective support, and support utilization, with a total of 10 items and a total score of 12-66. Higher scores indicate higher support levels. The average social support score of the sample patients was (39.98±5.46), which is considered a moderate level of support. Details are as follows:

[0027]

[0028] The expectation assessment unit is the core of the system, using a patient-centered outcomes questionnaire to quantify treatment expectations. The assessment is conducted in five aspects: Normal level: Assess the severity of pain, fatigue, mood disturbance, and limitation of daily activities over the past week (0-10 points, higher scores indicate greater severity). In this study, the sample patients had a normal level of pain of (6.04±1.63) points, a normal level of limitation of daily activities of (6.29±1.98) points, and relatively mild fatigue and mood disturbance. Details are as follows:

[0029]

[0030] Ideal expectation: The patient's expectation that each symptom will reach the best state after treatment (0-10 points, the higher the score, the lower the expectation).

[0031] Success criteria: The extent to which patients perceive improvement in their symptoms after treatment as a success (0-10 points, with higher scores indicating lower expectations). The average success criteria score for the sample patients ranged from 0.80 to 1.20.

[0032] Predictive expectation: Patients predict the level of each symptom they may reach after treatment (0-10 points, with higher scores indicating lower expectations). The average predictive expectation score for the sample patients ranged from 0.72 to 1.20.

[0033] Importance of improvement: The degree of importance of improvement of each symptom to the patient (0-10 points, the higher the score, the more important). The median importance of improvement for pain and limitation of daily activities was 10 points for the sample patients, followed by fatigue and mood disturbance.

[0034] The influencing factors analysis unit conducts in-depth analysis of the collected data, including: Univariate analysis module: Analyzes differences in demographic, disease data, and treatment expectation scores. Univariate analysis revealed that pain location, nature, functional impairment, and number of hospitalizations significantly affected normal level pain; education level, occupation, and pain nature significantly affected ideal expectations.

[0035] The correlation analysis module calculates the correlation coefficients between treatment expectation scores and NRS, anxiety, depression, and social support scores. The correlations between expectations and psychosocial variables for each dimension are detailed below. For example, normal level pain is significantly positively correlated with NRS scores, anxiety, and depression; improvement in importance pain is positively correlated with NRS scores, anxiety, and depression, but negatively correlated with social support.

[0036]

[0037]

[0038] Multivariate analysis module: Based on univariate and correlation analyses, multiple linear regression analysis is performed to identify the main influencing factors. In practice, variables with p < 0.05 in the univariate and correlation analyses are used as independent variables, and the scores of each dimension of treatment expectation are used as dependent variables. Stepwise regression is employed for analysis. The following are the results of the multiple linear regression analysis. For example, the regression analysis confirms that the NRS score and the presence of functional impairment are the main influencing factors for limitation of daily activities at the normal level; postural pain and depression are the main influencing factors for predicting expected fatigue.

[0039]

[0040]

[0041]

[0042] Note: Pain: R 2 =0.058, adjust R 2 =0.048, F=5.681, p<0.001; Fatigue: R 2 =0.108, adjust R 2 =0.092, F=6.675, p<0.001; Emotional distress: R 2 =0.097, adjust R 2 =0.077, F=4.892, p<0.001; Daily activities are limited: R 2 =0.056, adjust R 2 =0.049, F=8.173, p<0.001.

[0043]

[0044] Note: Pain: R 2 =0.048, adjust R 2 =0.034, F=3.461, p=0.009; Fatigue: R 2 =0.111, adjust R 2 =0.081, F=3.752, p<0.001; Emotional distress: R 2 =0.046, adjust R 2 =0.036, F=4.445, p=0.005; Daily activities are restricted: R 2 =0.081, adjust R 2 =0.061, F=4.024, p<0.001.

[0045]

[0046] Note: Pain: R 2=0.137, adjust R 2 =0.108, F=4.775, p<0.001; Fatigue: R 2 =0.204, adjust R 2 =0.183, F=9.989, p<0.001; Emotional distress: R 2 =0.274, adjust R 2 =0.242, F=8.445, p<0.001; Daily activities are restricted: R 2 =0.111, adjust R 2 =0.088, F=4.875, p<0.001.

[0047] The report generation unit integrates all assessment and analysis results to generate a structured, visualized assessment report. The report content may include:

[0048] Overview of basic patient information.

[0049] Treatment expectation profile: Displays the patient's scores in five aspects and four symptom dimensions in the form of a radar chart or bar chart, clearly presenting their expectation characteristics (e.g., high ideal expectation, moderate predictive expectation).

[0050] Analysis of influencing factors: Highlights key factors that influenced the patient’s treatment expectations as determined by multivariate analysis (e.g., “Your pain level (NRS score) is an important factor influencing your expectations of pain improvement”).

[0051] Risk warnings and intervention recommendations: Suggestions are automatically generated based on the analysis results. For example, for patients with high pain scores and low social support, the suggestion is "Pain management and enhanced social support are the current priorities"; for patients with significant anxiety and depression and high expectations for fatigue improvement, the suggestion is "Psychological and emotional intervention and fatigue management should be addressed simultaneously".

[0052] Dynamic comparison: If multiple assessments are conducted, a trend comparison chart of the results from each assessment can be provided.

[0053] The system's workflow is as follows: First, the data acquisition unit collects patient information; then, the expectation assessment unit conducts a PCOQ questionnaire assessment to obtain a quantitative score of treatment expectation; next, the influencing factor analysis unit calls univariate analysis, correlation analysis, and multiple linear regression analysis models to explore the deep relationship between the expectation score and various variables; finally, the report generation unit integrates all the results, generates and outputs an assessment report.

[0054] This invention integrates scattered assessment tools and complex statistical analysis processes into an intelligent platform, which can quickly and accurately provide patients with lumbar degenerative diseases with a comprehensive "profile" of their treatment expectations. This enables clinical medical staff to go beyond experience-based judgment and gain insights into patients' core needs and psychosocial risks based on data, thereby implementing more precise preoperative communication, expectation management, and perioperative intervention, ultimately improving treatment outcomes and patient satisfaction.

[0055] Analysis of basic characteristics of patients with lumbar degenerative diseases: This study included 281 patients with LDD (Lower Deficiency Disease). The gender distribution was relatively balanced, with males accounting for 48%, lower than females (52%). The patients were predominantly middle-aged and elderly, with an average age of (57.12±15.16) years, and 81.9% over 40 years old. The highest percentage of patients had only primary school education (36.3%), followed by junior high school education (27%), reflecting a generally low level of education among the respondents. This may be related to the advanced age and lower educational attainment of the respondents. Most patients were married (90%), with average monthly household income concentrated around 3000-3999 yuan (40.6%), followed by 4000-4999 yuan (26.3%), indicating that the respondents generally had a middle or upper-middle economic level. This may be related to the fact that most respondents lived in urban areas (72.2%) and had relatively stable income sources. Furthermore, 93.3% of patients used medical insurance for payment, demonstrating the broad coverage and relatively comprehensive policies of my country's medical security system. This study found that the pain in patients with LDD was mainly located in the lower back and lower limbs. In this study, 31% of patients had lower limb dysfunction, indicating that LDD leads to a loss of standing and walking ability, significantly impacting patients' lives and work. Secondly, the pain primarily occurred during activity (86.8%), and 58.7% of patients were hospitalized more than twice due to this disease. This may be because LDD is a chronic overuse injury, prone to recurrence or progressive worsening, leading to repeated hospitalizations.

[0056] Analysis of the current treatment expectations of patients with lumbar degenerative diseases: The results of this study showed that the average scores of pain, fatigue, mood disturbance, and limited daily activities in patients with LDD were (6.04±1.63), (2.32±1.63), (3.58±1.85), and (6.29±1.98), respectively. This suggests that patients with LDD were already in a state of low quality of life characterized by moderate to severe pain and limited daily activities before admission, accompanied by a certain degree of fatigue and mood disturbance.

[0057] The results of this study show that the median scores of LDD patients on ideal expectations of pain, fatigue, emotional distress, and limitation of daily activities were as low as zero, indicating that LDD patients have high ideal expectations for symptom relief.

[0058] In this study, the mean scores for the success criteria were (1.02±0.67) for pain, (0.83±0.68) for fatigue, (0.91±0.67) for emotional distress, and (0.80±0.60) for limitation of daily activities. The study showed that treatment success was indicated by a reduction of 3.4 points in pain, 3.35 points in fatigue, 3.64 points in emotional distress, and 4.3 points in limitation of daily activities. The reason for this may be that the patients included in this study had relatively mild symptoms overall and were more inclined to pursue the ideal state of being asymptomatic, thus having higher expectations for the success criteria, resulting in a lower mean score for the success criteria.

[0059] The average scores of patients' predicted expected pain were (0.72±0.61), fatigue (1.10±0.67), emotional distress (1.20±0.67), and limitation of daily activities (1.17±0.68), indicating that LDD patients have a consistent expectation of symptom improvement and generally have a realistic and positive treatment expectation, believing that the symptoms can be relieved to a certain extent after treatment.

[0060] In this study, the median (interquartile range) scores for pain and limitation of daily activities were 10.00 (1.00) and 10.00 (0), respectively, indicating that pain relief and restoration of daily function were the core expectations of patients with lumbar degenerative diseases (LDD), followed by fatigue and emotional distress. This suggests that in subsequent clinical treatment and patient education for lumbar degenerative diseases, healthcare professionals should prioritize and clearly address patients' expectations for pain control and improvement of daily function to enhance treatment adherence and patient satisfaction.

[0061] Analysis of factors influencing treatment expectations in patients with lumbar degenerative diseases:

[0062] Factors influencing the typical level of pain in patients with lumbar degenerative diseases: Pain location, pain nature, presence of functional impairment, and NRS score are factors influencing the typical level of pain. Compared with patients with lumbar or lower extremity pain, patients with lumbar and lower extremity pain, as well as hip and lumbar pain, have higher typical level pain. This may be because functional activities in these areas are closely related to daily weight-bearing, posture maintenance, and body movement; once pain occurs, it is more likely to interfere with patients' basic daily living functions. Therefore, clinicians should pay more attention to these patients and develop targeted interventions based on the location and severity of their pain to alleviate their pain levels. This study shows that patients with persistent pain have more severe typical level pain. This may be because persistent pain not only leads to sensitization of the patient's peripheral and central nervous systems but is also often accompanied by sleep disorders, decreased daily activity abilities, and impaired social function, making the patient's pain experience more severe and difficult to relieve. Patients with functional impairment and higher NRS scores have higher typical level pain. This may be because intense pain can directly limit patients' physical activity abilities, exacerbate functional impairment, lead to reduced participation in daily activities, muscle atrophy, and joint stiffness, and thus create a vicious cycle of pain and functional impairment. Therefore, clinicians should pay close attention to the interaction between pain and functional impairment. When assessing patients, they should not only focus on a single pain score, but should also consider the patient's physical function, daily living abilities, and psychosocial factors.

[0063] NRS score and anxiety are influencing factors on patients' usual level of fatigue. This study showed that patients with higher NRS scores and more severe anxiety generally experienced higher levels of fatigue. This may be because high-intensity pain can lead to negative emotions such as anxiety, increasing the body's stress response, interfering with sleep quality, and exacerbating fatigue. Therefore, in clinical practice, healthcare professionals should pay attention to the interaction between pain and emotional state, combining pain assessment with emotional screening, and implementing comprehensive interventions to more effectively alleviate patients' fatigue symptoms.

[0064] NRS score, anxiety, and depression are factors influencing patients' general level of symptom and emotional distress. Although depression and anxiety have not been identified as specific causes of lumbar degenerative diseases, numerous studies have shown that patients with chronic lower back pain have a higher incidence of depression and anxiety.

[0065] Factors influencing patients' ideal pain expectations in lumbar degenerative diseases: Regression analysis showed that marital status, pain nature, and NRS score were influencing patients' ideal pain expectations. This study revealed that widowed and divorced patients had higher ideal pain expectation scores than married patients. This may be because married patients have more stable partner support and may have higher confidence and positive expectations regarding treatment, while patients experiencing widowhood or divorce face more emotional challenges, leading to more realistic expectations for pain relief. Patients with radiating pain had higher ideal pain expectation scores, indicating lower ideal pain expectations. This may be because patients gradually adjust their expectations during long-term treatment, focusing more on symptom control and functional maintenance rather than pursuing complete pain relief. Furthermore, correlation analysis showed that higher NRS scores correlated with higher ideal pain expectations, indicating lower ideal pain expectations. Severe pain is often accompanied by a decline in quality of life and social adaptability, which may lead to more realistic expectations for pain relief. These findings suggest that in chronic pain management, healthcare professionals should pay attention to the relationship between patients' self-reported pain intensity and their psychological expectations. By understanding and guiding patients to establish reasonable pain expectations, we can encourage them to participate more actively in the rehabilitation process, thereby improving long-term pain management adherence and life satisfaction.

[0066] Factors influencing the success criteria for symptom management in patients with lumbar degenerative diseases: Anxiety and the nature of pain are influencing patients' expectations of pain improvement in their success criteria. This study found that the more severe the anxiety, the higher the pain score of the success criteria, i.e., the lower the expectation of success in pain improvement. Anxiety exacerbates an individual's catastrophic perception of pain, thereby reducing their positive expectations for rehabilitation outcomes; at the same time, anxiety may also affect patients' confidence in the treatment effect, further weakening their expectations of pain recovery. Patients with radiating pain had lower pain scores in their success criteria, i.e., higher expectations of success in pain improvement, possibly because radiating pain is usually associated with a clear pathological basis, and patients have higher expectations for targeted treatment. Therefore, in clinical practice, medical staff need to pay attention to the interaction between patients' psychological state and the nature of pain, strengthen cognitive behavioral interventions for those with high anxiety, and provide reasonable guidance on the treatment expectations of patients with radiating pain to achieve more individualized and precise pain management goals.

[0067] The nature of pain is a factor influencing patients' expectations of success criteria for fatigue. Patients with persistent pain have lower fatigue scores on success criteria, indicating higher expectations for fatigue improvement, meaning pain is a major risk factor for fatigue. This is because pain and fatigue are often mutually causal; prolonged, persistent pain easily triggers or worsens fatigue, while significant fatigue further reduces pain tolerance, thus prompting patients to have a more urgent and positive expectation for recovery. Therefore, in clinical practice, healthcare professionals should pay closer attention to patients' fatigue levels and improve the overall management of pain and fatigue through multidisciplinary collaboration combined with psychological support, sleep management, and physical activity guidance.

[0068] Factors influencing patients' symptom prediction expectations in lumbar degenerative diseases: Postural pain and depression are influencing factors in patients' predicted fatigue expectations. Compared with active periods, patients experiencing pain while standing and bending had lower predicted fatigue scores, indicating higher predicted expectations of fatigue improvement. This may be because these postures directly induce or aggravate pain, and fatigue and pain interact, leading to higher predicted fatigue expectations. Correlation analysis showed a positive correlation between depression and predicted fatigue expectations; higher levels of depression resulted in higher predicted fatigue scores, indicating lower predicted expectations of fatigue improvement. Depression not only directly affects fatigue levels but may also indirectly influence fatigue self-management and the recovery process by reducing patients' positive expectations of fatigue improvement. Therefore, in clinical interventions, healthcare professionals need to simultaneously consider the interaction between depressive mood and fatigue expectations, combining psychological intervention with fatigue management to improve the overall treatment effect.

[0069] The number of hospitalizations for this disease is a factor influencing patients' predicted expected emotional distress. Patients who have been hospitalized for this disease more than twice have higher predicted expected emotional distress scores, meaning they have lower predicted expectations of emotional distress. This may be because the experience of multiple hospitalizations makes patients more familiar with the disease and treatment process, accumulates coping experience, and thus enhances their ability to regulate emotional distress and their psychological resilience, resulting in lower predicted expectations of emotional distress.

[0070] Factors influencing the importance of symptom improvement in patients with lumbar degenerative diseases (LDD): Posturally related pain (PRD), NRS score, depression, and social support are key influencing factors. Patients experiencing pain while sitting or standing scored lower on the importance of pain improvement compared to those experiencing pain during activity. This is likely because patients often perceive this type of pain as being relieved by postural adjustments or short rests, and therefore may not subjectively consider it a priority, resulting in lower scores for symptom improvement. Correlation analysis showed that higher NRS scores and depression levels correlated with higher pain improvement scores. This may be because depression can exacerbate pain perception, making patients more acutely aware of the interference pain causes to their physical and mental function, thus increasing their focus on pain improvement. Insufficient social support may exacerbate feelings of isolation and helplessness, amplifying the negative impact of pain on quality of life, making pain improvement a more pressing need. This suggests that healthcare professionals should focus on LDD patients with low social support, encouraging them to actively seek and fully utilize external support systems, reducing psychological stress, and continuously improving their social support systems to improve their pain experience and recovery process.

[0071] Occupation, NRS score, and anxiety were influencing factors on the importance of fatigue improvement in patients. Linear regression results showed that self-employed patients had lower fatigue improvement importance scores compared to corporate employees. This may be because self-employed individuals may be more focused on specific symptoms that directly affect their work performance, such as pain and mobility, thus subjectively downplaying the importance of fatigue improvement in overall recovery. Correlation analysis showed that higher NRS scores and anxiety levels correlated with higher fatigue improvement importance scores, consistent with multiple studies. This may be because high pain levels directly exacerbate physiological fatigue, while anxiety increases an individual's sensitivity and focus on physical symptoms, thus prompting patients to expect fatigue improvement. Therefore, healthcare professionals need to prioritize the management of comorbid pain and anxiety, especially for patients with high levels of pain and anxiety, and simultaneously monitor their fatigue symptoms. Interventions such as cognitive behavioral therapy, pain education, and relaxation training can help patients alleviate anxiety, improve pain, and reduce fatigue.

[0072] in conclusion:

[0073] The quantitative results of this study showed that patients with lumbar degenerative diseases generally experienced moderate pain and limited daily activities within one week prior to admission, with milder levels of fatigue and emotional distress. Patients had the highest level of ideal expectations, followed by success criteria and predicted expectations. Improvement in pain and limited daily activities was of the highest importance, followed by fatigue and emotional distress. The expectation levels of patients with lumbar degenerative diseases were influenced by sociodemographic factors, disease factors, psychological factors, and social factors. This suggests that medical staff, based on a comprehensive assessment of influencing factors, should prioritize developing individualized management plans targeting patients' most pressing concerns of pain and limited daily activities. Simultaneously, they should focus on guiding patients to establish reasonable treatment expectations and integrate psychological support and fatigue management interventions into the overall treatment, thereby improving treatment adherence and rehabilitation outcomes, and ultimately enhancing patients' quality of life.

[0074] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A treatment expectation assessment system for patients with lumbar degenerative diseases, characterized in that, include: The data acquisition unit is used to collect multi-dimensional information on patients with lumbar degenerative diseases. An expectation assessment unit, connected to the data acquisition unit, is used to quantitatively assess the patient's treatment expectations based on the collected information. The influencing factor analysis unit, connected to the expectation assessment unit, is used to analyze key factors that affect patients' treatment expectations. The report generation unit, connected to the expected assessment unit and the influencing factor analysis unit, is used to integrate the assessment and analysis results and generate a visual assessment report.

2. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 1, characterized in that, The data acquisition unit includes: The data collection module is used to collect patients' sociodemographic data and disease-related data. The sociodemographic data includes age, gender, marital status, place of residence, education level, occupation, average monthly income per capita in the family, and medical expense payment method. The disease-related data includes disease diagnosis type, pain location, pain nature, position-related pain, presence of functional impairment, number of hospitalizations due to the disease, and presence of other chronic diseases. The symptom assessment module is used to collect patients' symptom severity scores in four dimensions: pain, fatigue, emotional distress, and limitation of daily activities. The psychosocial assessment module is used to collect scores on patients' anxiety levels, depression levels, and social support levels.

3. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 2, characterized in that, The expectation assessment unit uses a patient-centered outcome questionnaire to quantitatively assess patients’ treatment expectations. The assessment includes five aspects: normal level, ideal expectation, success criteria, predicted expectation, and importance of symptom improvement. Each aspect is scored for four symptom dimensions: pain, fatigue, emotional distress, and limitation of daily activities.

4. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 3, characterized in that, The normal level indicates the severity of each symptom in the week prior to admission; a higher score indicates more severe symptoms. The ideal expectation refers to the patient's expectation that each symptom can reach the best state after treatment; The success criteria indicate the extent to which patients believe their symptoms need to improve after treatment in order to be considered a successful treatment. The predicted expectation refers to the level that the patient predicts each symptom may reach after treatment; The higher the scores for ideal expectation, success criteria, and predicted expectation, the lower the patient's treatment expectations for that symptom dimension. The importance of symptom improvement indicates the degree to which the improvement of each symptom is important to the patient; the higher the score, the more important it is.

5. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 2, characterized in that, The symptom assessment module uses a digital rating scale to measure and score the patient's pain level; the psychosocial assessment module uses a comprehensive hospital anxiety and depression scale to measure and score the patient's anxiety and depression levels, and a social support rating scale to measure and score the patient's social support level.

6. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 1, characterized in that, The influencing factor analysis unit includes: The univariate analysis module is used to analyze statistical differences among patients’ general information, symptom scores, psychosocial scores, and scores of each dimension of treatment expectations. The correlation analysis module is used to analyze the correlation between the scores of each dimension of treatment expectation and the scores of the numerical rating scale, anxiety score, depression score, and social support score. The multivariate analysis module is used to perform multiple linear regression analysis with statistically significant variables from univariate and correlation analyses as independent variables and scores of each dimension of treatment expectation as dependent variables to identify the factors influencing treatment expectation.

7. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 6, characterized in that, The factors influencing the normal level of pain identified by the multifactor analysis module include: pain location, pain nature, presence of functional impairment, and numerical rating scale score. The factors influencing typical level fatigue include: Digital Rating Scale score and anxiety score; The factors influencing the typical level of emotional distress include: numerical rating scale score, anxiety score, and depression score. The factors influencing the typically limited daily activities include: the presence of functional impairment and the Digital Rating Scale score. The factors influencing the ideal expected pain identified by the multifactor analysis module include: marital status, pain nature, and numerical rating scale score. The factors influencing the ideal expected fatigue include: positional pain; The factors influencing emotional distress related to ideal expectations include: occupation, location of pain, and position-related pain. Factors affecting the limitation of ideal daily activities include: the nature of pain and position-related pain.

8. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 6, characterized in that, The success criteria for pain identified by the multifactor analysis module include: pain nature and anxiety score; The factors influencing the success criteria for fatigue include: the nature of the pain; The factors influencing emotional distress as defined by the success criteria include: depression score; The factors influencing the limited daily activities mentioned in the success criteria include: the presence or absence of other chronic diseases and depression scores; The influencing factors for predicting expected fatigue identified by the multivariate analysis module include: postural pain and depression score; The factors influencing the predicted expected emotional distress include: the number of hospitalizations due to this illness; The factors that influence the predicted limitation of daily activities include: the location of pain and the number of hospitalizations due to the disease.

9. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 6, characterized in that, The multivariate analysis module identified the following factors influencing the importance of pain in symptom improvement: postural pain, numerical rating scale score, depression score, and social support score. The factors influencing the importance of improving fatigue symptoms include: occupation, numerical rating scale score, and anxiety score; The factors influencing the improvement of symptoms and emotional distress include: position-related pain, digit rating scale score, anxiety score, and depression score. The factors influencing the improvement of symptoms and limitations in daily activities include: postural pain and social support score.

10. The treatment expectation assessment system for patients with lumbar degenerative diseases according to claim 9, characterized in that, The assessment report generated by the report generation unit includes: a display of scores for each dimension of the patient's treatment expectations, a comparative analysis with norms or historical data, risk warnings based on the results of influencing factor analysis, and targeted clinical intervention recommendations, including expectation management, pain care, psychological support, fatigue intervention, and social support enhancement strategies.

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